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.

    2015-12-23

    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. 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

    DOE PAGES

    Albertsson, K.; Andre, J-M; Andronidis, A.; ...

    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 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

  6. 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.

  7. Event Builder and Level 3 trigger at the CDF experiment

    NASA Astrophysics Data System (ADS)

    Anikeev, K.; Bauer, G.; Furić, I.; Holmgren, D.; Korn, A.; Kravchenko, I.; Mulhearn, M.; Ngan, P.; Paus, Ch.; Rakitin, A.; Rechenmacher, R.; Shah, T.; Sphicas, P.; Sumorok, K.; Tether, S.; Tseng, J.; Wüerthwein, F.

    2001-10-01

    The Event Builder and Level 3 trigger systems of the CDF experiment at Fermilab are required to process about 300 events per second, with an average event size of ˜200 KB. In the event building process the event is assembled from 15 sources supplying event fragments with roughly equal sizes of 12-16 KB. In the subsequent commercial processor-based Level 3 trigger, the events are reconstructed and trigger algorithms are applied. The CPU power required for filtering such a high data throughput rate exceeds 45 000 MIPS. To meet these requirements a distributed and scalable architecture has been chosen. It is based on commodity components: VME-based CPU's for the data read out, an ATM switch for the event building and Pentium-based personal computers running the Linux operating system for the event processing. Event flow through ATM is controlled by a reflective memory ring. The roughly homogeneous distribution of the expected load allows the use of 100 Mbps Ethernet for event distribution and collection within the Level 3 system. Preliminary results from a test system obtained during the last year are presented.

  8. 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.

  9. 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.

  10. 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

    ... Reserves Network, Jackson, OH; Masco Builder Cabinet Group, Waverly, OH; Masco Builder Cabinet Group, Seal... Building Cabinet Group, Jackson, Ohio. The workers are engaged in activity related to the production of... workers of Masco Building Cabinet Group in Waverly, Ohio, Seal Township, Ohio, and Seaman, Ohio....

  11. 76 FR 19466 - Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Reliable...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-07

    ... Reserves Network, Reliable Staffing, and Third Dimension Waverly, OH; Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Reliable Staffing, and Third Dimension Seal Township... Seal Township, Ohio (TA-W- 71,287B). The company reports that workers leased from Third Dimension were...

  12. "Big Events" and Networks.

    PubMed

    Friedman, Samuel; Rossi, Diana; Flom, Peter L

    2006-01-01

    Some, but not all, "big events" such as wars, revolutions, socioeconomic transitions, economic collapses, and ecological disasters in recent years seem to lead to large-scale HIV outbreaks (Friedman et al, in press; Hankins et al 2002). This was true of transitions in the USSR, South Africa and Indonesia, for example, but not those in the Philippines or (so far) in Argentina. It has been hypothesized that whether or not HIV outbreaks occur is shaped in part by the nature and extent of changes in the numbers of voluntary or involuntary risk-takers, which itself may be related to the growth of roles such as sex-sellers or drug sellers; the riskiness of the behaviors engaged in by risk-takers; and changes in sexual and injection networks and other "mixing patterns" variables. Each of these potential causal processes, in turn, is shaped by the nature of pre-existing social networks and the patterns and content of normative regulation and communication that happen within these social networks-and on how these social networks and their characteristics are changed by the "big event" in question. We will present ideas about what research is needed to help understand these events and to help guide both indigenous community-based efforts to prevent HIV outbreaks and also to guide those who organize external intervention efforts and aid.

  13. ARACHNE: A neural-neuroglial network builder with remotely controlled parallel computing.

    PubMed

    Aleksin, Sergey G; Zheng, Kaiyu; Rusakov, Dmitri A; Savtchenko, Leonid P

    2017-03-31

    Creating and running realistic models of neural networks has hitherto been a task for computing professionals rather than experimental neuroscientists. This is mainly because such networks usually engage substantial computational resources, the handling of which requires specific programing skills. Here we put forward a newly developed simulation environment ARACHNE: it enables an investigator to build and explore cellular networks of arbitrary biophysical and architectural complexity using the logic of NEURON and a simple interface on a local computer or a mobile device. The interface can control, through the internet, an optimized computational kernel installed on a remote computer cluster. ARACHNE can combine neuronal (wired) and astroglial (extracellular volume-transmission driven) network types and adopt realistic cell models from the NEURON library. The program and documentation (current version) are available at GitHub repository https://github.com/LeonidSavtchenko/Arachne under the MIT License (MIT).

  14. 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.

  15. 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.

  16. 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.

  17. Builders Challenge High Performance Builder Spotlight - Kacin Homes, Pittsburgh, Pennsylvania

    SciTech Connect

    2008-01-01

    Building America/Builders Challenge fact sheet on Kacin Homes, an energy-efficient home builder in cold climate using airtight envelope, efficient lighting, and tankless water heater. Evaluates cost impacts.

  18. Importance of individual events in temporal networks

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  19. eProject Builder

    SciTech Connect

    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

  20. eProject Builder

    SciTech Connect

    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

  1. 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

  2. Emergence of event cascades in inhomogeneous networks

    PubMed Central

    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. Emergence of event cascades in inhomogeneous networks

    NASA Astrophysics Data System (ADS)

    Onaga, Tomokatsu; Shinomoto, Shigeru

    2016-09-01

    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.

  4. Arntz Builders, Inc. Information Sheet

    EPA Pesticide Factsheets

    Arntz Builders, Inc. (the Company) is located in Novato, California. The settlement involves renovation activities conducted at property constructed prior to 1978, located in San Francisco, California.

  5. Rodan Builders, Inc. Information Sheet

    EPA Pesticide Factsheets

    Rodan Builders, Inc. (the Company) is located in Burlingame, California. The settlement involves renovation activities conducted at property constructed prior to 1978, located in San Francisco, California.

  6. 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.

  7. 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.

  8. 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.

  9. Sampling rare switching events in biochemical networks.

    PubMed

    Allen, Rosalind J; Warren, Patrick B; Ten Wolde, Pieter Rein

    2005-01-14

    Bistable biochemical switches are widely found in gene regulatory networks and signal transduction pathways. Their switching dynamics are difficult to study, however, because switching events are rare, and the systems are out of equilibrium. We present a simulation method for predicting the rate and mechanism of the flipping of these switches. We apply it to a genetic switch and find that it is highly efficient. The path ensembles for the forward and reverse processes do not coincide. The method is widely applicable to rare events and nonequilibrium processes.

  10. 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.

  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. 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

  13. We Must Be Bridge Builders.

    ERIC Educational Resources Information Center

    Andringa, Robert C.

    1982-01-01

    Higher education, and trustees in particular, must be "bridge builders" among academe, government, and business communities. Trustees must also be the mediators and a reconciling force when the public and independent campuses lose sight of their common cause. (MLW)

  14. Builder's foundation handbook

    SciTech Connect

    Carmody, J. . Underground Space Center); Christian, J. ); Labs, K. )

    1991-05-01

    This handbook contains a worksheet for selecting insulation levels based on specific building construction, climate, HVAC equipment, insulation cost, and other economic considerations. The worksheet permits optimization of foundation insulation levels for new or retrofit applications. Construction details representing good practices for the design and installation of energy efficient basement, crawl space, and slab-n-grade foundations are the focal point of the handbook. The construction details are keyed to lists of critical design information useful for specifying structural integrity; thermal and vapor control; subsurface drainage; waterproofing; and mold, mildew, odor, decay, termite, and radon control strategies. Another useful feature are checklist chapter summaries covering major design considerations for each foundation type--basement, crawl space, and slab-on-grade. These checklist summaries are useful during design and construction inspection. The information in this handbook is drawn heavily from the first foundation handbook from the DOE/ORNL Building Envelope Systems and Materials Program, the Building Foundation Design Handbook (Labs et al., 1988), which is an extensive technical reference manual. This book presents what to do in foundation design'' in an inviting, concise format. This handbook is intended to serve the needs of active home builders; however, the information is pertinent to anyone involved in foundation design and construction decisions including homeowners, architects, and engineers. 17 refs., 49 figs., 18 tabs.

  15. Event Discrimination using Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Menon, Hareesh; Hughes, Richard; Daling, Alec; Winer, Brian

    2017-01-01

    Convolutional Neural Networks (CNNs) are computational models that have been shown to be effective at classifying different types of images. We present a method to use CNNs to distinguish events involving the production of a top quark pair and a Higgs boson from events involving the production of a top quark pair and several quark and gluon jets. To do this, we generate and simulate data using MADGRAPH and DELPHES for a general purpose LHC detector at 13 TeV. We produce images using a particle flow algorithm by binning the particles geometrically based on their position in the detector and weighting the bins by the energy of each particle within each bin, and by defining channels based on particle types (charged track, neutral hadronic, neutral EM, lepton, heavy flavor). Our classification results are competitive with standard machine learning techniques. We have also looked into the classification of the substructure of the events, in a process known as scene labeling. In this context, we look for the presence of boosted objects (such as top quarks) with substructure encompassed within single jets. Preliminary results on substructure classification will be presented.

  16. 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.

  17. 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.

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

    DTIC Science & Technology

    2016-01-01

    network emulations experiments for NSRL. 15. SUBJECT TERMS Experiment Control, Simulation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...falsification of theoretical models, and characterization of protocols and algorithms for mobile wireless networks. It is used for a range of experiments ...network science experimentation by providing fine control over timing of modeled events external to the experiment . Emulated networks developed by NSRL

  19. Digital Learning Network Event with Robotics Engineer Jonathan Rogers

    NASA Image and Video Library

    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...

  20. Asynchronous networks and event driven dynamics

    NASA Astrophysics Data System (ADS)

    Bick, Christian; Field, Michael

    2017-02-01

    Real-world networks in technology, engineering and biology often exhibit dynamics that cannot be adequately reproduced using network models given by smooth dynamical systems and a fixed network topology. Asynchronous networks give a theoretical and conceptual framework for the study of network dynamics where nodes can evolve independently of one another, be constrained, stop, and later restart, and where the interaction between different components of the network may depend on time, state, and stochastic effects. This framework is sufficiently general to encompass a wide range of applications ranging from engineering to neuroscience. Typically, dynamics is piecewise smooth and there are relationships with Filippov systems. In this paper, we give examples of asynchronous networks, and describe the basic formalism and structure. In the following companion paper, we make the notion of a functional asynchronous network rigorous, discuss the phenomenon of dynamical locks, and present a foundational result on the spatiotemporal factorization of the dynamics for a large class of functional asynchronous networks.

  1. Automatic Distribution Network Reconfiguration: An Event-Driven Approach

    SciTech Connect

    Ding, Fei; Jiang, Huaiguang; Tan, Jin

    2016-11-14

    This paper proposes an event-driven approach for reconfiguring distribution systems automatically. Specifically, an optimal synchrophasor sensor placement (OSSP) is used to reduce the number of synchrophasor sensors while keeping the whole system observable. Then, a wavelet-based event detection and location approach is used to detect and locate the event, which performs as a trigger for network reconfiguration. With the detected information, the system is then reconfigured using the hierarchical decentralized approach to seek for the new optimal topology. In this manner, whenever an event happens the distribution network can be reconfigured automatically based on the real-time information that is observable and detectable.

  2. 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.

  3. 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.

  4. Builders Challenge High Performance Builder Spotlight: Ecofutures Building Inc., Boulder, Colorado

    SciTech Connect

    2009-12-22

    Building America Builders Challenge fact sheet on Ecofutures Building Inc. of Boulder, Colorado. Ecofutures’ first Builders Challenge house has been equipped with extensive energy monitoring equipment and many energy-efficient features.

  5. 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.

  6. 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.

  7. Builders Challenge High Performance Builder Spotlight - Centex Corporation, San Ramon, California

    SciTech Connect

    2008-01-01

    Building America/Builders Challenge fact sheet on Centex, an energy-efficient home builder in hot/mixed dry climate using advanced insulation techniques, engineered headers, and tankless water heaters.

  8. 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.

  9. Secure complex event processing in a heterogeneous and dynamic network

    NASA Astrophysics Data System (ADS)

    Buddhika, Thilina; Ray, Indrakshi; Linderman, Mark; Jayasumana, Anura

    2014-06-01

    Battlefield monitoring involves collecting streaming data from different sources, transmitting the data over a heterogeneous network, and processing queries in real-time in order to respond to events in a timely manner. Nodes in these networks differ with respect to their trustworthiness, processing, storage, and communication capabilities. Links in the network differ with respect to their communication bandwidth. The topology of the network itself is subject to change, as the nodes and links may become unavailable. Continuous queries executed in such environments must also meet some quality of service (QoS) requirements, such as, response time and throughput. Data streams generated from the various nodes in the network belong to different security levels; consequently, these must be processed in a secure manner without causing unauthorized leakage or modification. Towards this end, we demonstrate how an existing complex event processing system can be extended to execute queries and events in a secure manner in such a dynamic and heterogeneous environment.

  10. USS Cal Builders, Inc. Information Sheet

    EPA Pesticide Factsheets

    USS Cal Builders, Inc. (the Company) is located in Stanton, California. The settlement involves renovation activities conducted at property constructed prior to 1978, located in San Francisco, California.

  11. A convolutional neural network neutrino event classifier

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  12. A convolutional neural network neutrino event classifier

    DOE PAGES

    Aurisano, A.; Radovic, A.; Rocco, D.; ...

    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

  13. A convolutional neural network neutrino event classifier

    SciTech Connect

    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 without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  14. A convolutional neural network neutrino event classifier

    SciTech Connect

    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 without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  15. Bayesian-network-based soccer video event detection and retrieval

    NASA Astrophysics Data System (ADS)

    Sun, Xinghua; Jin, Guoying; Huang, Mei; Xu, Guangyou

    2003-09-01

    This paper presents an event based soccer video retrieval method, where the scoring even is detected based on Bayesian network from six kinds of cue information including gate, face, audio, texture, caption and text. The topology within the Bayesian network is predefined by hand according to the domain knowledge and the probability distributions are learned in the case of the known structure and full observability. The resulting event probability from the Bayesian network is used as the feature vector to perform the video retrieval. Experiments show that the true and false detection rations for the scoring event are about 90% and 16.67% respectively, and that the video retrieval result based on event is superior to that based on low-level features in the human visual perception.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26612009

  17. 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.

  18. 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.

  19. A classification of event sequences in the influence network

    NASA Astrophysics Data System (ADS)

    Walsh, James Lyons; Knuth, Kevin H.

    2017-06-01

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

  20. 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

  1. 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.

  2. Epidemiologic Considerations in Network Modeling of Theoretical Disease Events

    DTIC Science & Technology

    2006-12-01

    of this type of intervention include the oral polio vaccine, which like wild-type polio virus is spread by fecal-oral route, and, potentially...RTO-MP-IST-063 11 - 1 Epidemiologic Considerations in Network Modeling of Theoretical Disease Events Marcus Lem, MD, MHSc, FRCP(C...the armament of public health and epidemiology . Epidemiologists and communicable disease control researchers have been turning to network analysis to

  3. 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.

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

    PubMed

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

    2015-12-15

    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.

  5. 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

  6. 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.

  7. A framework for network-wide semantic event correlation

    NASA Astrophysics Data System (ADS)

    Hall, Robert T.; Taylor, Joshua

    2013-05-01

    An increasing need for situational awareness within network-deployed Systems Under Test has increased desire for frameworks that facilitate system-wide data correlation and analysis. Massive event streams are generated from heterogeneous sensors which require tedious manual analysis. We present a framework for sensor data integration and event correlation based on Linked Data principles, Semantic Web reasoning technology, complex event processing, and blackboard architectures. Sensor data are encoded as RDF models, then processed by complex event processing agents (which incorporate domain specific reasoners, as well as general purpose Semantic Web reasoning techniques). Agents can publish inferences on shared blackboards and generate new semantic events that are fed back into the system. We present AIS, Inc.'s Cyber Battlefield Training and Effectiveness Environment to demonstrate use of the framework.

  8. A Framework for Event Prioritization in Cyber Network Defense

    DTIC Science & Technology

    2014-07-15

    myong H. KAng Jim Z. Luo ALex VeLAZqueZ Center for High Assurance Computer Systems Information Technology Division July 15, 2014 Approved for public...OF ABSTRACT A Framework for Event Prioritization in Cyber Network Defense Anya Kim, Myong H. Kang, Jim Z. Luo, and Alex Velazquez Naval Research

  9. 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.

  10. A Network-Coding Based Event Diffusion Protocol for Wireless Mesh Networks

    NASA Astrophysics Data System (ADS)

    Beraldi, Roberto; Alnuweiri, Hussein

    Publish/subscribe is a well know and powerful distributed programming paradigm with many potential applications. In this paper we consider the central problem of any pub/sub implementation, namely the problem of event dissemination, in the case of a Wireless Mesh Network. We propose a protocol based on non-trivial forwarding mechanisms that employ network coding as a central tool for supporting adaptive event dissemination while exploiting the broadcast nature of wireless transmissions. Our results show that network coding provides significant improvements to event diffusion compared to standard blind dissemination solutions, namely flooding and gossiping.

  11. 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.

  12. [Imhotep--builder, physician, god].

    PubMed

    Mikić, Zelimir

    2008-01-01

    The medicine had been practiced in ancient Egypt since the earliest, prehistoric days, many millenia before Christ, and was quite developed in later periods. This is evident from the sceletal findings, surgical instruments found in tombs, wall printings, the reliefs and inscriptions, and most of all, from the sparse written material known as medical papyri. However, there were not many physicians from that time whose names had been recorded. The earliest physician in ancient Egypt known by name was Imhotep. WHO WAS IMHOTEP?: Imhotep lived and worked during the time of the 3rd Dynasty of Old Kingdom and served under the pharaoh Djoser (reigned 2667-2648 BC) as his vizier or chief minister, high priest, chief builder and carpenter. He obviously was an Egyptian polymath, a learned man and scribe and was credited with many inventions. As one of the highest officials of the pharaoh Djoser Imhotep is credited with designing and building of the famous Step Pyramid of Djoser at Saqqarah, near the old Egyptian capital of Memphis. Imhotep is also credited with inventing the method of stone-dressed building and using of columns in architecture and is considered to be the first architect in history known by name. It is believed that, as the high priest, Imhotel also served as the nation's chief physician in his time. As the builder of the Step Pyramid, and as a physician, he also had to take medical care of thousands of workers engaged in that great project. He is also credited with being the founder of Egyptian medicine and with being the author of the so-called Smith papirus containing a collection of 48 specimen clinical records with detailed accurate record of the features and treatment of various injuries. As such he emerges as the first physician of ancient Egypt known by name and, at the same time, as the first physician known by name in written history of the world. GOD: As Imhotep was considered by Egyptian people as the "inventor of healing", soon after the death, he

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

    NASA Astrophysics Data System (ADS)

    Mahmoud, Magdi S.; Sabih, Muhammad

    2014-11-01

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

  14. Computational Model Builder for Multi-Dimensional Models

    DTIC Science & Technology

    2015-08-12

    Rev. 8-98) Prescribed by ANSI Std. Z39.18 Public reporting burden for this collection of information is estimated to average 1 hour per...Model Builder (CMB) and includes applications for processing LiDAR (PointsBuilder), creating appropriate geometric scenes (SceneBuilder), creating...various scanned based data such as LiDAR  SceneBuilder – provides the ability of creating geometric scenes of the domain being modeled  GeologyBuilder

  15. 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.

  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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  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.

  18. 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.

  19. 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

  20. 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

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

    PubMed

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

    2014-01-01

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

  2. Regional Small-Event Identification Using Seismic Networks and Arrays

    DTIC Science & Technology

    2007-11-02

    PL-TR-97-2160 REGIONAL SMALL-EVENT IDENTIFICATION USING SEISMIC NETWORKS AND ARRAYS Michael A.H. Hedlin University of California/San Diego...This technical report has been reviewed and is approved for publication. JAMES C. BATTIS ^ CHARLES P. PIKE, Deputy Director jiontract Manager...by your organization, please notify AFRL/VSOE, 29 Randolph Road, Hanscom AFB, MA 01731-3010. This will assist us in maintaining a current mailing

  3. Supporting Proactive Application Event Notification to Improve Sensor Network Performance

    NASA Astrophysics Data System (ADS)

    Merlin, Christophe J.; Heinzelman, Wendi B.

    As wireless sensor networks gain in popularity, many deployments are posing new challenges due to their diverse topologies and resource constraints. Previous work has shown the advantage of adapting protocols based on current network conditions (e.g., link status, neighbor status), in order to provide the best service in data transport. Protocols can similarly benefit from adaptation based on current application conditions. In particular, if proactively informed of the status of active queries in the network, protocols can adjust their behavior accordingly. In this paper, we propose a novel approach to provide such proactive application event notification to all interested protocols in the stack. Specifically, we use the existing interfaces and event signaling structure provided by the X-Lisa (Cross-layer Information Sharing Architecture) protocol architecture, augmenting this architecture with a Middleware Interpreter for managing application queries and performing event notification. Using this approach, we observe gains in Quality of Service of up to 40% in packet delivery ratios and a 75% decrease in packet delivery delay for the tested scenario.

  4. 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.

  5. 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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  8. 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.

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

    PubMed

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

    2017-09-01

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

  10. A methodology for detecting routing events in discrete flow networks.

    SciTech Connect

    Garcia, H. E.; Yoo, T.; Nuclear Technology

    2004-01-01

    A theoretical framework for formulating and implementing model-based monitoring of discrete flow networks is discussed. Possible flows of items are described as the sequence of discrete-event (DE) traces. Each trace defines the DE sequence(s) that are triggered when an entity follows a given flow-path and visits tracking locations distributed within the monitored system. Given the set of possible discrete flows, a possible-behavior model - an interacting set of automata - is constructed, where each automaton models the discrete flow of items at each tracking location. Event labels or symbols contain all the information required to unambiguously distinguish each discrete flow. Within the possible behavior, there is a special sub-behavior whose occurrence is required to be detected. The special behavior may be specified by the occurrence of routing events, such as faults. These intermittent or non-persistent events may occur repeatedly. An observation mask is then defined, characterizing the actual observation configuration available for collecting item tracking data. The analysis task is then to determine whether this observation configuration is capable of detecting the identified special behavior. The assessment is accomplished by evaluating several observability notions, such as detectability and diagnosability. If the corresponding property is satisfied, associated formal observers are constructed to perform the monitoring task at hand. The synthesis of an optimal observation mask may also be conducted to suggest an appropriate observation configuration guaranteeing the detection of the special events and to construct associated monitoring agents. The proposed framework, modeling methodology, and supporting techniques for discrete flow networks monitoring are presented and illustrated with an example.

  11. Associative nature of event participation dynamics: A network theory approach

    PubMed Central

    Smiljanić, Jelena; Mitrović Dankulov, Marija

    2017-01-01

    The affiliation with various social groups can be a critical factor when it comes to quality of life of each individual, making such groups an essential element of every society. The group dynamics, longevity and effectiveness strongly depend on group’s ability to attract new members and keep them engaged in group activities. It was shown that high heterogeneity of scientist’s engagement in conference activities of the specific scientific community depends on the balance between the numbers of previous attendances and non-attendances and is directly related to scientist’s association with that community. Here we show that the same holds for leisure groups of the Meetup website and further quantify individual members’ association with the group. We examine how structure of personal social networks is evolving with the event attendance. Our results show that member’s increasing engagement in the group activities is primarily associated with the strengthening of already existing ties and increase in the bonding social capital. We also show that Meetup social networks mostly grow trough big events, while small events contribute to the groups cohesiveness. PMID:28166305

  12. New CSC segment builder algorithm with Monte-Carlo TeV muons in CMS experiment

    NASA Astrophysics Data System (ADS)

    Palichik, V.; Voytishin, N.

    2017-09-01

    The performance of the new Cathode Strip Chamber segment builder algorithm with simulated TeV muons is considered. The comparison of some of the main reconstruction characteristics is made. Some case study events are visualized in order to illustrate the improvement that the new algorithm gives to the reconstruction process.

  13. Event Clustering: Accuracy and Precision of Multiple Event Locations with Sparse Networks

    NASA Astrophysics Data System (ADS)

    Baldwin, T. K.; Wallace, T. C.

    2002-12-01

    In the last 15 years passive PASSCAL experiments have been fielded on every continent. Most of these deployments were designed to record teleseismic or large local seismic events to infer crustal and mantle structure. However, the deployments inevitably record small, local seismicity. Unfortunately, the configuration of the experiments are not optimal for location (typically the stations are arranged in linear arrays), and the seismicity is recorded at a very limited number of stations. The standard location procedure (Geiger's method) is severely limited without a detailed crustal model. A number of methods have been developed to improve relative location precision, including Joint Hypocenter Determination (JHD) and Progressive Multiple Event Location (PMEL). In this study we investigate the performance of PMEL for a very sparse network where there appears to be strong event clustering. CHARGE is a passive deployment of broadband seismometers in Chile and Argentina, with a primary focus of investigating the changes in dip along the descending Nazca Plate. The CHARGE stations recorded a large number of small, local events in 2000-2002. For this study events were selected from the northern profile (approximately along 30o S) in Chile. The events look similar, and appear to be clustered southeast of the city of La Serena. We performed three sets of experiments to investigate precision: (1) iterative Master Event Corrections to measure the scale length of clusters, (2) PMEL locations, and (3) PMEL locations using a cross-correlation to determine accurate relative phase timing. The analysis shows that for the PMEL experiment clusters must occupy an area of 600 km2 for the results to be consistent. We will present a method to estimate the precision errors based on bootstrapping. Charge Team: S. Beck, G. Zandt, M. Anderson, H. Folsom, R. Fromm, T. Shearer, L. Wagner, and P. Alvarado (all University of Arizona), J. Campos, E. Kausel, and J. Paredes (all University of

  14. AutoCorrel: a neural network event correlation approach

    NASA Astrophysics Data System (ADS)

    Dondo, Maxwell G.; Japkowicz, Nathalie; Smith, Reuben

    2006-04-01

    Intrusion detection analysts are often swamped by multitudes of alerts originating from installed intrusion detection systems (IDS) as well as logs from routers and firewalls on the networks. Properly managing these alerts and correlating them to previously seen threats is critical in the ability to effectively protect a network from attacks. Manually correlating events can be a slow tedious task prone to human error. We present a two-stage alert correlation approach involving an artificial neural network (ANN) autoassociator and a single parameter decision threshold-setting unit. By clustering closely matched alerts together, this approach would be beneficial to the analyst. In this approach, alert attributes are extracted from each alert content and used to train an autoassociator. Based on the reconstruction error determined by the autoassociator, closely matched alerts are grouped together. Whenever a new alert is received, it is automatically categorised into one of the alert clusters which identify the type of attack and its severity level as previously known by the analyst. If the attack is entirely new and there is no match to the existing clusters, this would be appropriately reflected to the analyst. There are several advantages to using an ANN based approach. First, ANNs acquire knowledge straight from the data without the need for a human expert to build sets of domain rules and facts. Second, once trained, ANNs can be very fast, accurate and have high precision for near real-time applications. Finally, while learning, ANNs perform a type of dimensionality reduction allowing a user to input large amounts of information without fearing an effciency bottleneck. Thus, rather than storing the data in TCP Quad format (which stores only seven event attributes) and performing a multi-stage query on reduced information, the user can input all the relevant information available and instead allow the neural network to organise and reduce this knowledge in an

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Applying Association Rule of the Data Mining Method for the Network Event Analysis

    NASA Astrophysics Data System (ADS)

    Kim, Wankyung; Soh, Wooyoung

    2007-12-01

    Network event analysis gives useful information on the network status that helps protect from attacks. It involves finding sets of frequently used packet information such as IP addresses and requires real-time processing by its nature. This paper applies association rules to network event analysis. Originally association rules used for data mining can be applied to find frequent item sets. So, if frequent items occur on networks, information system can guess that there is a threat. But existed association rules such as Apriori algorithm are not suitable for analyzing network events on real-time due to the high usage of CPU and memory and thus low processing speed. This paper develops a network event audit module by applying association rules to network events using a new algorithm instead of Apriori algorithm. Test results show that the application of the new algorithm gives drastically low usage of both CPU and memory for network event analysis compared with existing Apriori algorithm.

  20. Aspirin Use and Cardiovascular Events in Social Networks

    PubMed Central

    Strully, Kate W.; Fowler, James H.; Murabito, Joanne; Benjamin, Emelia J.; Levy, Daniel; Christakis, Nicholas A.

    2012-01-01

    We tested whether friends’ and family members’ cardiovascular health events and also their own aspirin use are associated with the likelihood that an individual takes aspirin regularly. Analyses were based on longitudinal data on 2,724 members of the Framingham Heart Study (based in Massachusetts, U.S.A) who were linked to friends and family members who were also participants in the same study. Men were more likely to take aspirin if a male friend had recently been taking aspirin (OR 1.48, 95% CI 1.03, 2.13), and women were more likely to take aspirin if a brother (OR 1.35, 95% CI 1.03, 1.77) had recently been taking aspirin. Men were also more likely to take aspirin if a brother recently had a cardiovascular event (OR 1.41, 95% CI 1.04, 1.93), and women were more likely to take aspirin if a female friend recently experienced a cardiovascular event (OR 2.85, 95% CI 1.27, 6.37). Aspirin use is correlated with the health and behavior of friends and family. These findings add to a growing body of evidence, which suggests that behavioral changes that promote cardiovascular health may spread through social networks. PMID:22361089

  1. BioNetBuilder2.0: bringing systems biology to chicken and other model organisms.

    PubMed

    Konieczka, Jay H; Drew, Kevin; Pine, Alex; Belasco, Kevin; Davey, Sean; Yatskievych, Tatiana A; Bonneau, Richard; Antin, Parker B

    2009-07-14

    Systems Biology research tools, such as Cytoscape, have greatly extended the reach of genomic research. By providing platforms to integrate data with molecular interaction networks, researchers can more rapidly begin interpretation of large data sets collected for a system of interest. BioNetBuilder is an open-source client-server Cytoscape plugin that automatically integrates molecular interactions from all major public interaction databases and serves them directly to the user's Cytoscape environment. Until recently however, chicken and other eukaryotic model systems had little interaction data available. Version 2.0 of BioNetBuilder includes a redesigned synonyms resolution engine that enables transfer and integration of interactions across species; this engine translates between alternate gene names as well as between orthologs in multiple species. Additionally, BioNetBuilder is now implemented to be part of the Gaggle, thereby allowing seamless communication of interaction data to any software implementing the widely used Gaggle software. Using BioNetBuilder, we constructed a chicken interactome possessing 72,000 interactions among 8,140 genes directly in the Cytoscape environment. In this paper, we present a tutorial on how to do so and analysis of a specific use case. BioNetBuilder 2.0 provides numerous user-friendly systems biology tools that were otherwise inaccessible to researchers in chicken genomics, as well as other model systems. We provide a detailed tutorial spanning all required steps in the analysis. BioNetBuilder 2.0, the tools for maintaining its data bases, standard operating procedures for creating local copies of its back-end data bases, as well as all of the Gaggle and Cytoscape codes required, are open-source and freely available at http://err.bio.nyu.edu/cytoscape/bionetbuilder/.

  2. Functional fission of parvalbumin interneuron classes during fast network events

    PubMed Central

    Varga, Csaba; Oijala, Mikko; Lish, Jonathan; Szabo, Gergely G; Bezaire, Marianne; Marchionni, Ivan; Golshani, Peyman; Soltesz, Ivan

    2014-01-01

    Fast spiking, parvalbumin (PV) expressing hippocampal interneurons are classified into basket, axo-axonic (chandelier), and bistratified cells. These cell classes play key roles in regulating local circuit operations and rhythmogenesis by releasing GABA in precise temporal patterns onto distinct domains of principal cells. In this study, we show that each of the three major PV cell classes further splits into functionally distinct sub-classes during fast network events in vivo. During the slower (<10 Hz) theta oscillations, each cell class exhibited its own characteristic, relatively uniform firing behavior. However, during faster (>90 Hz) oscillations, within-class differences in PV interneuron discharges emerged, which segregated along specific features of dendritic structure or somatic location. Functional divergence of PV sub-classes during fast but not slow network oscillations effectively doubles the repertoire of spatio-temporal patterns of GABA release available for rapid circuit operations. DOI: http://dx.doi.org/10.7554/eLife.04006.001 PMID:25375253

  3. 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.

  4. 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.

  5. Long Range Plan for Peterson Builders, Inc

    DTIC Science & Technology

    1982-02-22

    minecraft and mid-size combat vessel builder. 2. Consolidate Peterson’s strong tuna seiner position into leadership in medium sized comercial vessels...family to pursue several interesting personal goals, not the least of which is to maintain their role as the sole remaining U.S. Navy minecraft ...the following ship categories: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. U.S. Navy minecraft . Aluminum ships, government and commercial, 50 to market 200 feet or

  6. 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.

  7. MSFC evaluation of the space fabrication demonstration system (beam builder)

    NASA Technical Reports Server (NTRS)

    Adams, E. O.; Irvine, C. N.

    1981-01-01

    The beam builder, designed and manufactured as a ground demonstration model, is a precursor to a machine for use in the space environment, transportable by the space shuttle. The beam builder has the capability to automatically fabricate triangular truss beams in low Earth orbit with a highly reliable machine that requires a minimum of in-space maintenance and repair. A performance assessment of the beam builder, which was fabricated from commercial hardware is given.

  8. 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

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

    PubMed

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

    2017-09-26

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

  10. Edge Event-Triggered Synchronization in Networks of Coupled Harmonic Oscillators.

    PubMed

    Wei, Bo; Xiao, Feng; Dai, Ming-Zhe

    2016-08-30

    The synchronization problems of networks of coupled harmonic oscillators are addressed by the edge event-triggered approach in this paper. The network dynamics with respect to edge states are presented and a new edge event-triggered control protocol is designed. Combined with the periodic event-detecting and edge event-triggered approach, sufficient conditions that guarantee the synchronization of coupled harmonic oscillators are presented. Two event-detecting rules are given to achieve the synchronization of coupled harmonic oscillators with low resource consumption. Finally, simulations are conducted to illustrate the effectiveness of the edge event-triggered control algorithm.

  11. 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.…

  12. 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.

  13. 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

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

    PubMed

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

    2017-10-01

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

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

    USDA-ARS?s Scientific Manuscript database

    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 ...

  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. 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…

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

    PubMed

    Demblon, Julie; D'Argembeau, Arnaud

    2016-07-07

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

  19. GeoBuilder: a geometric algorithm visualization and debugging system for 2D and 3D geometric computing.

    PubMed

    Wei, Jyh-Da; Tsai, Ming-Hung; Lee, Gen-Cher; Huang, Jeng-Hung; Lee, Der-Tsai

    2009-01-01

    Algorithm visualization is a unique research topic that integrates engineering skills such as computer graphics, system programming, database management, computer networks, etc., to facilitate algorithmic researchers in testing their ideas, demonstrating new findings, and teaching algorithm design in the classroom. Within the broad applications of algorithm visualization, there still remain performance issues that deserve further research, e.g., system portability, collaboration capability, and animation effect in 3D environments. Using modern technologies of Java programming, we develop an algorithm visualization and debugging system, dubbed GeoBuilder, for geometric computing. The GeoBuilder system features Java's promising portability, engagement of collaboration in algorithm development, and automatic camera positioning for tracking 3D geometric objects. In this paper, we describe the design of the GeoBuilder system and demonstrate its applications.

  20. 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.

  1. Social network changes and life events across the life span: a meta-analysis.

    PubMed

    Wrzus, Cornelia; Hänel, 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 changes and the effects of life events on social networks using 277 studies with 177,635 participants from adolescence to old age. Cross-sectional as well as longitudinal studies consistently showed that (a) the global social network increased up until young adulthood and then decreased steadily, (b) both the personal network and the friendship network decreased throughout adulthood, (c) the family network was stable in size from adolescence to old age, and (d) other networks with coworkers or neighbors were important only in specific age ranges. Studies focusing on life events that occur at specific ages, such as transition to parenthood, job entry, or widowhood, demonstrated network changes similar to such age-related network changes. Moderator analyses detected that the type of network assessment affected the reported size of global, personal, and family networks. Period effects on network sizes occurred for personal and friendship networks, which have decreased in size over the last 35 years. Together the findings are consistent with the view that a portion of normative, age-related social network changes are due to normative, age-related life events. We discuss how these patterns of normative social network development inform research in social, evolutionary, cultural, and personality psychology.

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

    NASA Astrophysics Data System (ADS)

    Mahecha, Miguel D.; Gans, Fabian; Sippel, Sebastian; Donges, Jonathan F.; Kaminski, Thomas; Metzger, Stefan; Migliavacca, Mirco; Papale, Dario; Rammig, Anja; Zscheischler, Jakob

    2017-09-01

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

  3. Magnetic location of C IV events in the quiet network

    NASA Technical Reports Server (NTRS)

    Porter, Jason G.; Reichmann, Ed J.; Moore, Ronald L.; Harvey, Karen L.

    1986-01-01

    Ultraviolet Spectrograph and Polarimeter (UVSP) observations of C IV intensity in the quiet sun were examined and compared to magnetograms and He I 10830 A spectroheliograms from Kitt Peak National Laboratory. The observations were made between 3 and 9 April, 1985. Spatially rastered UVSP intensity measurements were obtained at 11 wavelength positions in the 1548 A line of C IV. It was concluded that the stochastic process whereby convective shuffling of loop footprints leads to many topically dissipative events in active regions and the larger bipoles treated here continues to operate in regions of fewer, weaker flux loops, but the resulting events above threshold are less frequent.

  4. 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.

  5. 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.

  6. Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

    PubMed

    Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

    2016-12-08

    This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

  7. Supervised machine learning on a network scale: application to seismic event classification and detection

    NASA Astrophysics Data System (ADS)

    Reynen, Andrew; Audet, Pascal

    2017-09-01

    A new method using a machine learning technique is applied to event classification and detection at seismic networks. This method is applicable to a variety of network sizes and settings. The algorithm makes use of a small catalogue of known observations across the entire network. Two attributes, the polarization and frequency content, are used as input to regression. These attributes are extracted at predicted arrival times for P and S waves using only an approximate velocity model, as attributes are calculated over large time spans. This method of waveform characterization is shown to be able to distinguish between blasts and earthquakes with 99 per cent accuracy using a network of 13 stations located in Southern California. The combination of machine learning with generalized waveform features is further applied to event detection in Oklahoma, United States. The event detection algorithm makes use of a pair of unique seismic phases to locate events, with a precision directly related to the sampling rate of the generalized waveform features. Over a week of data from 30 stations in Oklahoma, United States are used to automatically detect 25 times more events than the catalogue of the local geological survey, with a false detection rate of less than 2 per cent. This method provides a highly confident way of detecting and locating events. Furthermore, a large number of seismic events can be automatically detected with low false alarm, allowing for a larger automatic event catalogue with a high degree of trust.

  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. Prevalence and test characteristics of national health safety network ventilator-associated events.

    PubMed

    Lilly, Craig M; Landry, Karen E; Sood, Rahul N; Dunnington, Cheryl H; Ellison, Richard T; Bagley, Peter H; Baker, Stephen P; Cody, Shawn; Irwin, Richard S

    2014-09-01

    The primary aim of the study was to measure the test characteristics of the National Health Safety Network ventilator-associated event/ventilator-associated condition constructs for detecting ventilator-associated pneumonia. Its secondary aims were to report the clinical features of patients with National Health Safety Network ventilator-associated event/ventilator-associated condition, measure costs of surveillance, and its susceptibility to manipulation. Prospective cohort study. Two inpatient campuses of an academic medical center. Eight thousand four hundred eight mechanically ventilated adults discharged from an ICU. None. The National Health Safety Network ventilator-associated event/ventilator-associated condition constructs detected less than a third of ventilator-associated pneumonia cases with a sensitivity of 0.325 and a positive predictive value of 0.07. Most National Health Safety Network ventilator-associated event/ventilator-associated condition cases (93%) did not have ventilator-associated pneumonia or other hospital-acquired complications; 71% met the definition for acute respiratory distress syndrome. Similarly, most patients with National Health Safety Network probable ventilator-associated pneumonia did not have ventilator-associated pneumonia because radiographic criteria were not met. National Health Safety Network ventilator-associated event/ventilator-associated condition rates were reduced 93% by an unsophisticated manipulation of ventilator management protocols. The National Health Safety Network ventilator-associated event/ventilator-associated condition constructs failed to detect many patients who had ventilator-associated pneumonia, detected many cases that did not have a hospital complication, and were susceptible to manipulation. National Health Safety Network ventilator-associated event/ventilator-associated condition surveillance did not perform as well as ventilator-associated pneumonia surveillance and had several undesirable

  10. IBACOS Builder System Performance Packages: January 2003-December 2003

    SciTech Connect

    Broniek, John; Norton, P.

    2004-07-01

    This report presents system design packages for cold and mixed-humid climates that builders and contractors can use to construct homes that achieve a Home Energy Rating System (HERS) score between 86 and 88.

  11. 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

  12. Builder's plate at east end of pier. Pennsylvania & ...

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

    Builder's plate at east end of pier. - Pennsylvania & New Jersey Railroad, Delaware River Bridge, Spanning Delaware River, south of Betsy Ross Bridge (State Route 90), Philadelphia, Philadelphia County, PA

  13. Builder's plate and pin connection detail at junction of inclined ...

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

    Builder's plate and pin connection detail at junction of inclined end post and top chord. Plate reads "Nelson and Buchanan agents Chambersburg, PA." - Yeakle Mill Bridge, State Route 3026 (Mill Road) spanning Little Cove Creek, Sylvan, Franklin County, PA

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

    SciTech Connect

    2004-10-01

    Building America works with the residential building industry to develop and implement innovative building energy systems -- innovations that save builders and homeowners millions of dollars in construction and energy costs.

  15. 15. Detail view of Boston Bridge Works builders plate, north ...

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

    15. Detail view of Boston Bridge Works builders plate, north portal brace, looking southwest - India Point Railroad Bridge, Spanning Seekonk River between Providence & East Providence, Providence, Providence County, RI

  16. Representing Dynamic Social Networks in Discrete Event Social Simulation

    DTIC Science & Technology

    2010-12-01

    applied settings in the areas of marketing and behavior modification programs (exercise adoption, smoking cessation) ( Icek Ajzen 2006). The model has an...society. The action choice component of the conceptual model is based on the theory of planned behavior (TPB) (I. Ajzen 1991). The TPB states that an...information networks into military simulations. In Pro- ceedings of the 40th Conference on Winter Simulation. pp. 133–144. Ajzen , I. 1991. The theory of

  17. Discrete Event Command & Control for Networked Teams with Multiple Missions

    DTIC Science & Technology

    2009-03-16

    of the key ideas responsible for our DEC formulation, which allows formal computations for efficient on- line real-time task sequencing and dynamic...effectively and fairly sequences the tasks of all programmed missions and assigns the required resources on- line in real time as events occur and as...Harris, B., Lewis, F. L., and Cook, D. J., “Machine planning for manufacturing: dynamic resource allocation and on- line supervisory control,” Journal

  18. 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.

  19. Relational event models for longitudinal network data with an application to interhospital patient transfers.

    PubMed

    Vu, Duy; Lomi, Alessandro; Mascia, Daniele; Pallotti, Francesca

    2017-03-30

    The main objective of this paper is to introduce and illustrate relational event models, a new class of statistical models for the analysis of time-stamped data with complex temporal and relational dependencies. We outline the main differences between recently proposed relational event models and more conventional network models based on the graph-theoretic formalism typically adopted in empirical studies of social networks. Our main contribution involves the definition and implementation of a marked point process extension of currently available models. According to this approach, the sequence of events of interest is decomposed into two components: (a) event time and (b) event destination. This decomposition transforms the problem of selection of event destination in relational event models into a conditional multinomial logistic regression problem. The main advantages of this formulation are the possibility of controlling for the effect of event-specific data and a significant reduction in the estimation time of currently available relational event models. We demonstrate the empirical value of the model in an analysis of interhospital patient transfers within a regional community of health care organizations. We conclude with a discussion of how the models we presented help to overcome some the limitations of statistical models for networks that are currently available. Copyright © 2017 John Wiley & Sons, Ltd.

  20. Event-triggered H∞ filter design for delayed neural network with quantization.

    PubMed

    Liu, Jinliang; Tang, Jia; Fei, Shumin

    2016-10-01

    This paper is concerned with H∞ filter design for a class of neural network systems with event-triggered communication scheme and quantization. Firstly, a new event-triggered communication scheme is introduced to determine whether or not the current sampled sensor data should be broadcasted and transmitted to quantizer, which can save the limited communication resource. Secondly, a logarithmic quantizer is used to quantify the sampled data, which can reduce the data transmission rate in the network. Thirdly, considering the influence of the constrained network resource, we investigate the problem of H∞ filter design for a class of event-triggered neural network systems with quantization. By using Lyapunov functional and linear matrix inequality (LMI) techniques, some delay-dependent stability conditions for the existence of the desired filter are obtained. Furthermore, the explicit expression is given for the designed filter parameters in terms of LMIs. Finally, a numerical example is given to show the usefulness of the obtained theoretical results.

  1. 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.

  2. 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.

  3. Micro seismic event detection based on neural networks in the Groningen area, The Netherlands

    NASA Astrophysics Data System (ADS)

    Paap, Bob; van Maanen, Peter-Paul; Carpentier, Stefan; Meekes, Sjef

    2017-04-01

    Over the past decades, the Groningen gas field has been increasingly faced by induced earthquakes resulting from gas production. The seismic monitoring network at Groningen has been densified in order to acquire more accurate information regarding the onset and origin of seismic events, resulting in increasing amounts of seismic data. Although traditional automated event detection techniques generally are successful in detecting events from continuous data, its detection success is challenged in cases of lower signal-to-noise ratios and often limited availability of seismologists. Besides the recent expansion of the Groningen seismic network, additional new seismic networks have been deployed at several geothermal and CO2 storage fields. The data stream coming from these networks has sparked specific interest in neural networks for automated classification and interpretation. Here we explore the feasibility of neural networks in classifying the occurrence of seismic events. For this purpose a three-layered feedforward neural network was trained using public data related to a seismic event in the Groningen gas field obtained from the Royal Netherlands Meteorological Institute (KNMI) data portal. The first arrival times that were determined by KNMI for a subset of the station data were used to determine the arrival times for the other station data. Different derivatives, using different frequency sub-band and STA/LTA settings, were used as input. Based on these data, the network's parameters were then optimized to predict arrival times accurately. Although this study is still ongoing, we anticipate our approach can significantly increase the performance as compared to detection methods usually applied to the Groningen gas field. This will clear the way for future real-time micro seismic event classification.

  4. Supplement consumption in body builder athletes

    PubMed Central

    Karimian, Jahangir; Esfahani, Parivash Shekarchizadeh

    2011-01-01

    BACKGROUND: Widespread use of supplements is observed among world athletes in different fields. The aim of this study was to estimate the prevalence and determinants of using supplements among body builder athletes. METHODS: This cross-sectional study was conducted on 250 men and 250 women from 30 different bodybuilding clubs. Participants were asked to complete a self-administered standardized anonymous check-list. RESULTS: Forty nine percent of the respondents declared supplement use. Men were more likely to take supplements than women (86.8% vs. 11.2%, p = 0.001). Reasons for using supplements were reported to be for health (45%), enhancing the immune system (40%) and improving athletic performance (25%). Most athletes (72%) had access to a nutritionist but underused this resource. Coaches (65%) had the greatest influence on supplementation practices followed by nutritionists (30%) and doctors (25%) after them. CONCLUSIONS: The prevalence of supplement use among bodybuilders was high. Sex, health-related issues and sport experts were determinant factors of supplement use. PMID:22973330

  5. 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.

  6. 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.

  7. 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.

  8. Neural Network-Based Event-Triggered State Feedback Control of Nonlinear Continuous-Time Systems.

    PubMed

    Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

    2016-03-01

    This paper presents a novel approximation-based event-triggered control of multi-input multi-output uncertain nonlinear continuous-time systems in affine form. The controller is approximated using a linearly parameterized neural network (NN) in the context of event-based sampling. After revisiting the NN approximation property in the context of event-based sampling, an event-triggered condition is proposed using the Lyapunov technique to reduce the network resource utilization and to generate the required number of events for the NN approximation. In addition, a novel weight update law for aperiodic tuning of the NN weights at triggered instants is proposed to relax the knowledge of complete system dynamics and to reduce the computation when compared with the traditional NN-based control. Nonetheless, a nonzero positive lower bound for the inter-event times is guaranteed to avoid the accumulation of events or Zeno behavior. For analyzing the stability, the event-triggered system is modeled as a nonlinear impulsive dynamical system and the Lyapunov technique is used to show local ultimate boundedness of all signals. Furthermore, in order to overcome the unnecessary triggered events when the system states are inside the ultimate bound, a dead-zone operator is used to reset the event-trigger errors to zero. Finally, the analytical design is substantiated with numerical results.

  9. 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

  10. Scale-Free Brain Networks Based on the Event-Related Potential during Visual Spatial Attention

    NASA Astrophysics Data System (ADS)

    Li, Ling; Jin, Zhen-Lan

    2011-04-01

    The human brain is thought of as one of the most complex dynamical systems in the universe. The network view of the dynamical system has emerged since the discovery of scale-free networks. Brain functional networks, which represent functional associations among brain regions, are extracted by measuring the temporal correlations from electroencephalogram data. We measure the topological properties of the brain functional network, including degree distribution, average degree, clustering coefficient and the shortest path length, to compare the networks of multi-channel event-related potential activity between visual spatial attention and unattention conditions. It is found that the degree distribution of the brain functional networks under both the conditions is a power law distribution, which reflects a scale-free property. Moreover, the scaling exponent of the attention condition is significantly smaller than that of the unattention condition. However, the degree distribution of equivalent random networks does not follow the power law distribution. In addition, the clustering coefficient of these random networks is smaller than those of brain networks, and the shortest path length of these random networks is large and comparable with those of brain networks. Our results, typical of scale-free networks, indicate that the scaling exponent of brain activity could reflect different cognitive processes.

  11. Doctor AI: Predicting Clinical Events via Recurrent Neural Networks

    PubMed Central

    Choi, Edward; Bahadori, Mohammad Taha; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng

    2017-01-01

    Leveraging large historical data in electronic health record (EHR), we developed Doctor AI, a generic predictive model that covers observed medical conditions and medication uses. Doctor AI is a temporal model using recurrent neural networks (RNN) and was developed and applied to longitudinal time stamped EHR data from 260K patients over 8 years. Encounter records (e.g. diagnosis codes, medication codes or procedure codes) were input to RNN to predict (all) the diagnosis and medication categories for a subsequent visit. Doctor AI assesses the history of patients to make multilabel predictions (one label for each diagnosis or medication category). Based on separate blind test set evaluation, Doctor AI can perform differential diagnosis with up to 79% recall@30, significantly higher than several baselines. Moreover, we demonstrate great generalizability of Doctor AI by adapting the resulting models from one institution to another without losing substantial accuracy. PMID:28286600

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

    PubMed

    Jiang, Peng; Xu, Yiming; Liu, Jun

    2017-01-19

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

  13. 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.

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

    SciTech Connect

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

    2016-05-15

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

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

    PubMed

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

    2016-12-01

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

  16. 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

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

    PubMed Central

    Li, Liangda; Zha, Hongyuan

    2014-01-01

    In many applications in social network analysis, it is important to model the interactions and infer the influence between pairs of actors, leading to the problem of dyadic event modeling which has attracted increasing interests recently. In this paper we focus on the problem of dyadic event attribution, an important missing data problem in dyadic event modeling where one needs to infer the missing actor-pairs of a subset of dyadic events based on their observed timestamps. Existing works either use fixed model parameters and heuristic rules for event attribution, or assume the dyadic events across actor-pairs are independent. To address those shortcomings we propose a probabilistic model based on mixtures of Hawkes processes that simultaneously tackles event attribution and network parameter inference, taking into consideration the dependency among dyadic events that share at least one actor. We also investigate using additive models to incorporate regularization to avoid overfitting. Our experiments on both synthetic and real-world data sets on international armed conflicts suggest that the proposed new method is capable of significantly improve accuracy when compared with the state-of-the-art for dyadic event attribution. PMID:24917494

  18. The Contextual Association Network Activates More for Remembered than for Imagined Events.

    PubMed

    Gilmore, Adrian W; Nelson, Steven M; McDermott, Kathleen B

    2016-02-01

    The human capacities to remember events from the past and imagine events in the future rely on highly overlapping neural substrates. Neuroimaging studies have revealed brain regions that are more active for imagined events than remembered events, but the reverse pattern has not been shown consistently. Given that remembered events tend to be associated with more contextual information ( Johnson et al. 1988), one might expect a set of regions to demonstrate greater activity for remembered events. Specifically, regions sensitive to the strength of contextual associations might be hypothesized to show greater activity for remembered events. The present experiment tests this hypothesis. fMRI was used to identify brain regions within the contextual association network ( Bar and Aminoff 2003); regions within this network were then examined to see whether they showed differential activity during remembering and imagining. Bilateral regions within the parahippocampal cortex and retrosplenial complex responded more strongly to remembered past events, supporting work that suggests these events have more contextual information associated with them. Follow-up voxel-wise analysis demonstrated the specificity of these results, as did re-analysis of previous experimental datasets. These results suggest that a key differentiating feature of remembering and imagining is the strength of contextual associations. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  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.

  20. 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

  1. 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.

  2. OSCAR experiment high-density network data report: Event 3 - April 16-17, 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 network, as well as airborne air chemistry and cloud chemistry measurements, surface air chemistry measurements, and supporting meteorological measurements. Four separate storm events were studied during the experiment. This report summarizes data taken by Pacific Northwest Laboratory (PNL) during the third storm event, April 16-17. The report contains the high-density network precipitation chemistry data, air chemistry and cloud chemistry data from the PNL aircraft, and meteorological data for the event, including standard National Weather Service products and radar and rawindsonde data from the network. 4 references, 76 figures, 6 tables.

  3. OSCAR experiment high-density network data report: Event 1 - April 8-9, 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-densiy component of OSCAR was located in northeast Indiana and included sequential precipitation chemistry measurements on a 100 by 100 km network, as well as airborne air chemistry and cloud chemistry measurements, surface air chemistry measurements, and supporting meteorological measurements. Four separate storm events were studied during the experiment. This report summarizes data taken by Pacific Northwest Laboratory (PNL) during the first storm event, April 8-9. The report contains the high-density network precipitation chemistry data, air chemistry data from the PNL aircraft, and meteorological data for the event, including standard National Weather Service products and radar data from the network. 4 references, 72 figures, 5 tables.

  4. 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.

  5. Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events

    SciTech Connect

    Davis, Michael J.; Janke, Robert

    2015-01-01

    Network model detail can influence the accuracy of results from analyses of water distribution systems. Some previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregated adverse effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. But, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).

  6. Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events

    SciTech Connect

    Davis, Michael J.; Janke, Robert

    2015-01-01

    Network model detail can influence the accuracy of results from analyses of water distribution systems. Previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregated adverse effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. However, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).

  7. Influence of Network Model Detail on Estimated Health Effects of Drinking Water Contamination Events

    DOE PAGES

    Davis, Michael J.; Janke, Robert

    2015-01-01

    Network model detail can influence the accuracy of results from analyses of water distribution systems. Some previous work has shown the limitations of skeletonized network models when considering water quality and hydraulic effects. Loss of model detail is potentially less important for aggregated effects such as the systemwide health effects associated with a contamination event, but has received limited attention. The influence of model detail on such effects is examined here by comparing results obtained for contamination events using three large network models and several skeletonized versions of the models. Loss of model detail decreases the accuracy of estimated aggregatedmore » adverse effects related to contamination events. It has the potential to have a large negative influence on the results of consequence assessments and the design of contamination warning systems. But, the adverse influence on analysis results can be minimized by restricting attention to high percentile effects (i.e., 95th percentile or higher).« less

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

    PubMed Central

    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

  9. 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

  10. Understanding the role of human variation in vaccine adverse events: the Clinical Immunization Safety Assessment Network.

    PubMed

    LaRussa, Philip S; Edwards, Kathryn M; Dekker, Cornelia L; Klein, Nicola P; Halsey, Neal A; Marchant, Colin; Baxter, Roger; Engler, Renata J M; Kissner, Jennifer; Slade, Barbara A

    2011-05-01

    The Clinical Immunization Safety Assessment (CISA) Network is a collaboration between the Centers for Disease Control and Prevention (CDC) and 6 academic medical centers to provide support for immunization safety assessment and research. The CISA Network was established by the CDC in 2001 with 4 primary goals: (1) develop research protocols for clinical evaluation, diagnosis, and management of adverse events following immunization (AEFI); (2) improve the understanding of AEFI at the individual level, including determining possible genetic and other risk factors for predisposed people and subpopulations at high risk; (3) develop evidence-based algorithms for vaccination of people at risk of serious AEFI; and (4) serve as subject-matter experts for clinical vaccine-safety inquiries. CISA Network investigators bring in-depth clinical, pathophysiologic, and epidemiologic expertise to assessing causal relationships between vaccines and adverse events and to understanding the pathogenesis of AEFI. CISA Network researchers conduct expert reviews of clinically significant adverse events and determine the validity of the recorded diagnoses on the basis of clinical and laboratory criteria. They also conduct special studies to investigate the possible pathogenesis of adverse events, assess relationships between vaccines and adverse events, and maintain a centralized repository for clinical specimens. The CISA Network provides specific clinical guidance to both health care providers who administer vaccines and those who evaluate and treat patients with possible AEFI. The CISA Network plays an important role in providing critical immunization-safety data and expertise to inform vaccine policy-makers. The CISA Network serves as a unique resource for vaccine-safety monitoring efforts conducted at the CDC.

  11. Complex network based techniques to identify extreme events and (sudden) transitions in spatio-temporal systems.

    PubMed

    Marwan, Norbert; Kurths, Jürgen

    2015-09-01

    We present here two promising techniques for the application of the complex network approach to continuous spatio-temporal systems that have been developed in the last decade and show large potential for future application and development of complex systems analysis. First, we discuss the transforming of a time series from such systems to a complex network. The natural approach is to calculate the recurrence matrix and interpret such as the adjacency matrix of an associated complex network, called recurrence network. Using complex network measures, such as transitivity coefficient, we demonstrate that this approach is very efficient for identifying qualitative transitions in observational data, e.g., when analyzing paleoclimate regime transitions. Second, we demonstrate the use of directed spatial networks constructed from spatio-temporal measurements of such systems that can be derived from the synchronized-in-time occurrence of extreme events in different spatial regions. Although there are many possibilities to investigate such spatial networks, we present here the new measure of network divergence and how it can be used to develop a prediction scheme of extreme rainfall events.

  12. 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.

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

    PubMed Central

    Jiang, Peng; Xu, Yiming; Liu, Jun

    2017-01-01

    For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA). After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes’ being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II) to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS). The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network’s best service quality and lifetime. PMID:28106837

  14. 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. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

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

    PubMed

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

    2007-08-02

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

  17. Time Series Modeling of Army Mission Command Communication Networks: An Event-Driven Analysis

    DTIC Science & Technology

    2013-06-01

    critical events. In a detailed analysis of the email corpus of the Enron Corporation, Diesner and Carley (2005; see also Murshed et al. 2007) found that...established contacts and formal roles. The Enron crisis is instructive as a network with a critical period of failure. Other researchers have also found...Diesner, J., Frantz, T. L., & Carley, K. M. (2005). Communication networks from the Enron email corpus “It’s always about the people. Enron is no

  18. 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).

  19. 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

  20. Coarse-grained event tree analysis for quantifying Hodgkin-Huxley neuronal network dynamics.

    PubMed

    Sun, Yi; Rangan, Aaditya V; Zhou, Douglas; Cai, David

    2012-02-01

    We present an event tree analysis of studying the dynamics of the Hodgkin-Huxley (HH) neuronal networks. Our study relies on a coarse-grained projection to event trees and to the event chains that comprise these trees by using a statistical collection of spatial-temporal sequences of relevant physiological observables (such as sequences of spiking multiple neurons). This projection can retain information about network dynamics that covers multiple features, swiftly and robustly. We demonstrate that for even small differences in inputs, some dynamical regimes of HH networks contain sufficiently higher order statistics as reflected in event chains within the event tree analysis. Therefore, this analysis is effective in discriminating small differences in inputs. Moreover, we use event trees to analyze the results computed from an efficient library-based numerical method proposed in our previous work, where a pre-computed high resolution data library of typical neuronal trajectories during the interval of an action potential (spike) allows us to avoid resolving the spikes in detail. In this way, we can evolve the HH networks using time steps one order of magnitude larger than the typical time steps used for resolving the trajectories without the library, while achieving comparable statistical accuracy in terms of average firing rate and power spectra of voltage traces. Our numerical simulation results show that the library method is efficient in the sense that the results generated by using this numerical method with much larger time steps contain sufficiently high order statistical structure of firing events that are similar to the ones obtained using a regular HH solver. We use our event tree analysis to demonstrate these statistical similarities.

  1. Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions.

    PubMed

    Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

    2016-12-24

    It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources.

  2. Stochastic Optimal Regulation of Nonlinear Networked Control Systems by Using Event-Driven Adaptive Dynamic Programming.

    PubMed

    Sahoo, Avimanyu; Jagannathan, Sarangapani

    2017-02-01

    In this paper, an event-driven stochastic adaptive dynamic programming (ADP)-based technique is introduced for nonlinear systems with a communication network within its feedback loop. A near optimal control policy is designed using an actor-critic framework and ADP with event sampled state vector. First, the system dynamics are approximated by using a novel neural network (NN) identifier with event sampled state vector. The optimal control policy is generated via an actor NN by using the NN identifier and value function approximated by a critic NN through ADP. The stochastic NN identifier, actor, and critic NN weights are tuned at the event sampled instants leading to aperiodic weight tuning laws. Above all, an adaptive event sampling condition based on estimated NN weights is designed by using the Lyapunov technique to ensure ultimate boundedness of all the closed-loop signals along with the approximation accuracy. The net result is event-driven stochastic ADP technique that can significantly reduce the computation and network transmissions. Finally, the analytical design is substantiated with simulation results.

  3. Compound Event Barrier Coverage in Wireless Sensor Networks under Multi-Constraint Conditions

    PubMed Central

    Zhuang, Yaoming; Wu, Chengdong; Zhang, Yunzhou; Jia, Zixi

    2016-01-01

    It is important to monitor compound event by barrier coverage issues in wireless sensor networks (WSNs). Compound event barrier coverage (CEBC) is a novel coverage problem. Unlike traditional ones, the data of compound event barrier coverage comes from different types of sensors. It will be subject to multiple constraints under complex conditions in real-world applications. The main objective of this paper is to design an efficient algorithm for complex conditions that can combine the compound event confidence. Moreover, a multiplier method based on an active-set strategy (ASMP) is proposed to optimize the multiple constraints in compound event barrier coverage. The algorithm can calculate the coverage ratio efficiently and allocate the sensor resources reasonably in compound event barrier coverage. The proposed algorithm can simplify complex problems to reduce the computational load of the network and improve the network efficiency. The simulation results demonstrate that the proposed algorithm is more effective and efficient than existing methods, especially in the allocation of sensor resources. PMID:28029118

  4. Adverse Event Assessment of Antimuscarinics for Treating Overactive Bladder: A Network Meta-Analytic Approach

    PubMed Central

    Kessler, Thomas M.; Bachmann, Lucas M.; Minder, Christoph; Löhrer, David; Umbehr, Martin; Schünemann, Holger J.; Kessels, Alfons G. H.

    2011-01-01

    Background Overactive bladder (OAB) affects the lives of millions of people worldwide and antimuscarinics are the pharmacological treatment of choice. Meta-analyses of all currently used antimuscarinics for treating OAB found similar efficacy, making the choice dependent on their adverse event profiles. However, conventional meta-analyses often fail to quantify and compare adverse events across different drugs, dosages, formulations, and routes of administration. In addition, the assessment of the broad variety of adverse events is dissatisfying. Our aim was to compare adverse events of antimuscarinics using a network meta-analytic approach that overcomes shortcomings of conventional analyses. Methods Cochrane Incontinence Group Specialized Trials Register, previous systematic reviews, conference abstracts, book chapters, and reference lists of relevant articles were searched. Eligible studies included randomized controlled trials comparing at least one antimuscarinic for treating OAB with placebo or with another antimuscarinic, and adverse events as outcome measures. Two authors independently extracted data. A network meta-analytic approach was applied allowing for joint assessment of all adverse events of all currently used antimuscarinics while fully maintaining randomization. Results 69 trials enrolling 26′229 patients were included. Similar overall adverse event profiles were found for darifenacin, fesoterodine, transdermal oxybutynin, propiverine, solifenacin, tolterodine, and trospium chloride but not for oxybutynin orally administered when currently used starting dosages were compared. Conclusions The proposed generally applicable transparent network meta-analytic approach summarizes adverse events in an easy to grasp way allowing straightforward benchmarking of antimuscarinics for treating OAB in clinical practice. Most currently used antimuscarinics seem to be equivalent first choice drugs to start the treatment of OAB except for oral oxybutynin dosages

  5. A uniform instrumentation, event, and adaptation framework for network-aware middleware and advanced network applications

    SciTech Connect

    Reed, Daniel A.

    2003-03-14

    Developers of advanced network applications such as remote instrument control, distributed data management, tele-immersion and collaboration, and distributed computing face a daunting challenge: sustaining robust application performance despite time-varying resource demands and dynamically changing resource availability. It is widely recognized that network-aware middleware is key to achieving performance robustness.

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

    PubMed

    Yang, Hongjiu; Xu, Yang; Zhang, Jinhui

    2016-05-23

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

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

    PubMed Central

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

    2016-01-01

    In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput. PMID:27827905

  8. Asynchronous Periodic Edge-Event Triggered Control for Double-Integrator Networks With Communication Time Delays.

    PubMed

    Duan, Gaopeng; Xiao, Feng; Wang, Long

    2017-01-23

    This paper focuses on the average consensus of double-integrator networked systems based on the asynchronous periodic edge-event triggered control. The asynchronous property lies in the edge event-detecting procedure. For different edges, their event detections are performed at different times and the corresponding events occur independently of each other. When an event is activated, the two adjacent agents connected by the corresponding link sample their relative state information and update their controllers. The application of incidence matrix facilitates the transformation of control objects from the agent-based to the edge-based. Practically, due to the constraints of network bandwidth and communication distance, agents usually cannot receive the instantaneous information of some others, which has an impact on the system performance. Hence, it is necessary to investigate the presence of communication time delays. For double-integrator multiagent systems with and without communication time delays, the average state consensus can be asynchronously achieved by designing appropriate parameters under the proposed event-detecting rules. The presented results specify the relationship among the maximum allowable time delays, interaction topologies, and event-detecting periods. Furthermore, the proposed protocols have the advantages of reduced communication costs and controller-updating costs. Simulation examples are given to illustrate the proposed theoretical results.

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

    ERIC Educational Resources Information Center

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

    2014-01-01

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

  10. Life-Course Events, Social Networks, and the Emergence of Violence among Female Gang Members

    ERIC Educational Resources Information Center

    Fleisher, Mark S.; Krienert, Jessie L.

    2004-01-01

    Using data gathered from a multi-year field study, this article identifies specific life-course events shared by gang-affiliated women. Gangs emerge as a cultural adaptation or pro-social community response to poverty and racial isolation. Through the use of a social-network approach, data show that violence dramatically increases in the period…

  11. Event-triggered asynchronous intermittent communication strategy for synchronization in complex dynamical networks.

    PubMed

    Li, Huaqing; Liao, Xiaofeng; Chen, Guo; Hill, David J; Dong, Zhaoyang; Huang, Tingwen

    2015-06-01

    This paper presents a new framework for synchronization of complex network by introducing a mechanism of event-triggering distributed sampling information. A kind of event which avoids continuous communication between neighboring nodes is designed to drive the controller update of each node. The advantage of the event-triggering strategy is the significant decrease of the number of controller updates for synchronization task of complex networks involving embedded microprocessors with limited on-board resources. To describe the system's ability reaching synchronization, a concept about generalized algebraic connectivity is introduced for strongly connected networks and then extended to the strongly connected components of the directed network containing a directed spanning tree. Two sufficient conditions are presented to reveal the underlying relationships of corresponding parameters to reach global synchronization based on algebraic graph, matrix theory and Lyapunov control method. A positive lower bound for inter-event times is derived to guarantee the absence of Zeno behavior. Finally, a numerical simulation example is provided to demonstrate the theoretical results.

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

    ERIC Educational Resources Information Center

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

    2014-01-01

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

  13. Life-Course Events, Social Networks, and the Emergence of Violence among Female Gang Members

    ERIC Educational Resources Information Center

    Fleisher, Mark S.; Krienert, Jessie L.

    2004-01-01

    Using data gathered from a multi-year field study, this article identifies specific life-course events shared by gang-affiliated women. Gangs emerge as a cultural adaptation or pro-social community response to poverty and racial isolation. Through the use of a social-network approach, data show that violence dramatically increases in the period…

  14. Simulating adverse event spontaneous reporting systems as preferential attachment networks: application to the Vaccine Adverse Event Reporting System.

    PubMed

    Scott, J; Botsis, T; Ball, R

    2014-01-01

    Spontaneous Reporting Systems [SRS] are critical tools in the post-licensure evaluation of medical product safety. Regulatory authorities use a variety of data mining techniques to detect potential safety signals in SRS databases. Assessing the performance of such signal detection procedures requires simulated SRS databases, but simulation strategies proposed to date each have limitations. We sought to develop a novel SRS simulation strategy based on plausible mechanisms for the growth of databases over time. We developed a simulation strategy based on the network principle of preferential attachment. We demonstrated how this strategy can be used to create simulations based on specific databases of interest, and provided an example of using such simulations to compare signal detection thresholds for a popular data mining algorithm. The preferential attachment simulations were generally structurally similar to our targeted SRS database, although they had fewer nodes of very high degree. The approach was able to generate signal-free SRS simulations, as well as mimicking specific known true signals. Explorations of different reporting thresholds for the FDA Vaccine Adverse Event Reporting System suggested that using proportional reporting ratio [PRR] > 3.0 may yield better signal detection operating characteristics than the more commonly used PRR > 2.0 threshold. The network analytic approach to SRS simulation based on the principle of preferential attachment provides an attractive framework for exploring the performance of safety signal detection algorithms. This approach is potentially more principled and versatile than existing simulation approaches. The utility of network-based SRS simulations needs to be further explored by evaluating other types of simulated signals with a broader range of data mining approaches, and comparing network-based simulations with other simulation strategies where applicable.

  15. Heuristic scenario builder for power system operator training

    SciTech Connect

    Irisarri, G.; Rafian, M. ); Miller, B.N. ); Dobrowolski, E.J. )

    1992-05-01

    The Heuristic Scenario Builder (HSB), a knowledge-based training scenario builder for the EPRI Operator Training Simulator (OTS), is described in this paper. Expert systems and heuristic searches are used in the HSB to find training scenarios that closely fit trainee profiles and that address particular training requirements. Expert knowledge obtained from instructors and other operations personnel is used throughout the HSB to determine the scenarios. The HSB is an integral part of the OTS and is currently in operation at Philadelphia Electric's OTS installation.

  16. Differential gene expression analysis and network construction of recurrent cardiovascular events.

    PubMed

    Liao, Jiangquan; Chen, Zhong; He, Qinghong; Liu, Yongmei; Wang, Jie

    2016-02-01

    Recurrent cardiovascular events are vital to the prevention and treatment strategies in patients who have experienced primary cardiovascular events. However, the susceptibility of recurrent cardiovascular events varies among patients. Personalized treatment and prognosis prediction are urged. Microarray profiling of samples from patients with acute myocardial infarction (AMI), with or without recurrent cardiovascular events, were obtained from the Gene Expression Omnibus database. Bioinformatics analysis, including Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were used to identify genes and pathways specifically associated with recurrent cardiovascular events. A protein-protein interaction (PPI) network was constructed and visualized. A total of 1,329 genes were differentially expressed in the two group samples. Among them, 1,023 differentially expressed genes (DEGs; 76.98%) were upregulated in the recurrent cardiovascular events group and 306 DEGs (23.02%) were downregulated. Significantly enriched GO terms for molecular functions were nucleotide binding and nucleic acid binding, for biological processes were signal transduction and regulation of transcription (DNA-dependent), and for cellular component were cytoplasm and nucleus. The most significant pathway in our KEGG analysis was Pathways in cancer (P=0.000336681), and regulation of actin cytoskeleton was also significantly enriched (P=0.00165229). In the PPI network, the significant hub nodes were GNG4, MAPK8, PIK3R2, EP300, CREB1 and PIK3CB. The present study demonstrated the underlying molecular differences between patients with AMI, with and without recurrent cardiovascular events, including DEGs, their biological function, signaling pathways and key genes in the PPI network. With the use of bioinformatics and genomics these findings can be used to investigate the pathological mechanism, and improve the prevention and treatment of recurrent cardiovascular events.

  17. Event-Triggered Fault Detection Filter Design for a Continuous-Time Networked Control System.

    PubMed

    Wang, Yu-Long; Shi, Peng; Lim, Cheng-Chew; Liu, Yuan

    2016-12-01

    This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays and packet dropouts, which do not impose a constraint on the event-triggering mechanism, and proposing the simultaneous network bandwidth utilization ratio and fault occurrence probability-based event-triggering mechanism, a new closed-loop model for the considered NCS is established. Based on the established model, the event-triggered H ∞ performance analysis, and FDF and controller coordinated design are presented. The combined mutually exclusive distribution and Wirtinger-based integral inequality approach is proposed for the first time to deal with integral inequalities for products of vectors. This approach is proved to be less conservative than the existing Wirtinger-based integral inequality approach. The designed FDF and controller can guarantee the sensitivity of the residual signal to faults and the robustness of the NCS to external disturbances. The simulation results verify the effectiveness of the proposed event-triggering mechanism, and the FDF and controller coordinated design.

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

    NASA Astrophysics Data System (ADS)

    Odenweller, Adrian; Donner, Reik V.

    2017-04-01

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

  19. The 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  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. 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.

  3. 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.…

  4. Effects of target routing model on the occurrence of extreme events in complex networks

    NASA Astrophysics Data System (ADS)

    Ling, Xiang; Hu, Mao-Bin; Ding, Jian-Xun; Shi, Qing; Jiang, Rui

    2013-04-01

    This paper investigates the effect of routing protocol on the occurrence of extreme events (EE) in complex networks, as an extension of [V. Kishore, M.S. Santhanam, R.E. Amritkar, Phys. Rev. Lett. 106, 188701 (2011)]. The target routing model [W.X. Wang, B.H. Wang, C.Y. Yin, Y.B. Xie, T. Zhou, Phys. Rev. E 73, 026111 (2006)] is considered. In the model, a tunable power parameter α controls the packets' preference of forwarding direction. We derive exact expressions for the stationary distribution probability of packets and estimate the occurrence probability of EE on the nodes. The occurrence of EE strongly depends on the routing parameter. For Barabási-Albert scale-free network, Erdös-Rényi random network and Newman-Watts small-world network, it is shown that the minimal occurrence of EE is achieved at α = -1.

  5. 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

  6. 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

  7. 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.

  8. 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...

  9. 8. DETAIL VIEW OF BUILDER'S PLATE ON NORTHWEST SIDE OF ...

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

    8. DETAIL VIEW OF BUILDER'S PLATE ON NORTHWEST SIDE OF BRIDGE AT CENTER OF SPAN OVER CENTER PIER WHICH READS 'DESIGNED AND BUILT BY LUTEN BRIDGE CO., KNOXVILLE, TENN., 1922' - Illinois River Bridge, Spanning Illinois River at Benton County Road 3, Siloam Springs, Benton County, AR

  10. 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

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

    SciTech Connect

    Not Available

    2004-10-01

    The U.S. Department of Energy's (DOE) Building America Program is reengineering new and existing American homes for energy efficiency, energy security, and affordability. Building America works with the residential building industry to develop and implement innovative building energy systems--innovations that save builders and homeowners millions of dollars in construction and energy costs.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  13. 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...

  14. 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.

  15. 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,…

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

    PubMed

    Su, Housheng; Li, Zhenghao; Ye, Yanyan

    2017-06-24

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

  17. 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.

  18. An adaptive fault-tolerant event detection scheme for wireless sensor networks.

    PubMed

    Yim, Sung-Jib; Choi, Yoon-Hwa

    2010-01-01

    In this paper, we present an adaptive fault-tolerant event detection scheme for wireless sensor networks. Each sensor node detects an event locally in a distributed manner by using the sensor readings of its neighboring nodes. Confidence levels of sensor nodes are used to dynamically adjust the threshold for decision making, resulting in consistent performance even with increasing number of faulty nodes. In addition, the scheme employs a moving average filter to tolerate most transient faults in sensor readings, reducing the effective fault probability. Only three bits of data are exchanged to reduce the communication overhead in detecting events. Simulation results show that event detection accuracy and false alarm rate are kept very high and low, respectively, even in the case where 50% of the sensor nodes are faulty.

  19. Event-based H2/H∞ controllers for networked control systems

    NASA Astrophysics Data System (ADS)

    Orihuela, L.; Millán, P.; Vivas, C.; Rubio, F. R.

    2014-12-01

    This paper is concerned with event-based H2/H∞ control design for networked systems with interval time-varying delays. The contributions are twofold. First, conditions for uniform ultimately bounded stability are provided in the H2/H∞ event-based context. The relation between the boundedness of the stability region and the threshold that triggers the events is studied. Second, a practical design procedure for event-based H2/H∞ control is provided. The method makes use of Lyapunov-Krasovskii functionals (LKFs) and it is characterised by its generality, as only mild assumptions are imposed on the structures of the LKF and the cost functional. The robustness and performance of the proposed technique is showed through numerical simulations.

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

    PubMed Central

    Yu, Shanen; Liu, Shuai; Jiang, Peng

    2016-01-01

    Most existing deployment algorithms for event coverage in underwater wireless sensor networks (UWSNs) usually do not consider that network communication has non-uniform characteristics on three-dimensional underwater environments. Such deployment algorithms ignore that the nodes are distributed at different depths and have different probabilities for data acquisition, thereby leading to imbalances in the overall network energy consumption, decreasing the network performance, and resulting in poor and unreliable late network operation. Therefore, in this study, we proposed an uneven cluster deployment algorithm based network layered for event coverage. First, according to the energy consumption requirement of the communication load at different depths of the underwater network, we obtained the expected value of deployment nodes and the distribution density of each layer network after theoretical analysis and deduction. Afterward, the network is divided into multilayers based on uneven clusters, and the heterogeneous communication radius of nodes can improve the network connectivity rate. The recovery strategy is used to balance the energy consumption of nodes in the cluster and can efficiently reconstruct the network topology, which ensures that the network has a high network coverage and connectivity rate in a long period of data acquisition. Simulation results show that the proposed algorithm improves network reliability and prolongs network lifetime by significantly reducing the blind movement of overall network nodes while maintaining a high network coverage and connectivity rate. PMID:27973448

  1. 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.

  2. 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.

  3. Event-Triggered Generalized Dissipativity Filtering for Neural Networks With Time-Varying Delays.

    PubMed

    Wang, Jia; Zhang, Xian-Ming; Han, Qing-Long

    2016-01-01

    This paper is concerned with event-triggered generalized dissipativity filtering for a neural network (NN) with a time-varying delay. The signal transmission from the NN to its filter is completed through a communication channel. It is assumed that the network measurement of the NN is sampled periodically. An event-triggered communication scheme is introduced to design a suitable filter such that precious communication resources can be saved significantly while certain filtering performance can be ensured. On the one hand, the event-triggered communication scheme is devised to select only those sampled signals violating a certain threshold to be transmitted, which directly leads to saving of precious communication resources. On the other hand, the filtering error system is modeled as a time-delay system closely dependent on the parameters of the event-triggered scheme. Based on this model, a suitable filter is designed such that certain filtering performance can be ensured, provided that a set of linear matrix inequalities are satisfied. Furthermore, since a generalized dissipativity performance index is introduced, several kinds of event-triggered filtering issues, such as H∞ filtering, passive filtering, mixed H∞ and passive filtering, (Q,S,R) -dissipative filtering, and L2 - L∞ filtering, are solved in a unified framework. Finally, two examples are given to illustrate the effectiveness of the proposed method.

  4. A novel decentralised event-triggered ? control for network control systems with communication delays

    NASA Astrophysics Data System (ADS)

    Li, Fuqiang; Fu, Jingqi; Du, Dajun

    2016-10-01

    This paper studies a novel decentralised event-triggered ? control for network control systems with communication delays and external disturbances. To overcome the drawbacks that the relative event-triggered mechanism (ETM) generates many events when system is close to the origin and the absolute ETM produces many events when system is far away from the origin, a novel decentralised sampled-data-based ETM is first proposed. By using both local state-dependent and state-independent information, the decentralised ETM can effectively reduce network loads in each channel during the whole operation time. Then, a novel general system model with parameters of the decentralised ETM, communication delays and external disturbances is presented, and sufficient conditions for the ultimately bounded stability and asymptotic stability of the closed-loop system are obtained. Specially, the quantitative relationship between the boundness of the stability region and the parameters of the decentralised ETM is established. Moreover, to overcome the inconvenience of the two-step design method that controllers are required to be given a priori, a co-design scheme is presented to design the decentralised event generators and the output-based controller simultaneously. Finally, numerical examples confirm the effectiveness of the proposed method.

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

    NASA Astrophysics Data System (ADS)

    Pinsky, Vladimir; Shapira, Avi

    2017-01-01

    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.

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

    DOE PAGES

    Acciarri, R.; Adams, C.; An, R.; ...

    2017-03-14

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

  7. CVN A Convolutional Visual Network for Identication and Reconstruction of NOvA Events

    NASA Astrophysics Data System (ADS)

    Psihas, Fernanda; NOvA Collaboration

    2017-09-01

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

  8. Neural-Event-Triggered fMRI of large-scale neural networks.

    PubMed

    Logothetis, Nikos K

    2015-04-01

    Brains are dynamic systems, consisting of huge number of massively interconnected elementary components. The activity of these components results in an initial condition-sensitive evolution of network states through highly non-linear, probabilistic interactions. The dynamics of such systems cannot be described merely by studying the behavior of their components; instead their study benefits from employing multimodal methods. Neural-Event-Triggered (NET) fMRI is a novel method allowing identification of events that can be used to examine multi-structure activity in the brain. First results offered insights into the networks that might be involved in memory consolidation. On-going work examines the physiological underpinnings of the up and down modulation of metabolic activity, mapped with this methodology.

  9. Brain Network Activation Analysis Utilizing Spatiotemporal Features for Event Related Potentials Classification

    PubMed Central

    Stern, Yaki; Reches, Amit; Geva, Amir B.

    2016-01-01

    The purpose of this study was to introduce an improved tool for automated classification of event-related potentials (ERPs) using spatiotemporally parcellated events incorporated into a functional brain network activation (BNA) analysis. The auditory oddball ERP paradigm was selected to demonstrate and evaluate the improved tool. Methods: The ERPs of each subject were decomposed into major dynamic spatiotemporal events. Then, a set of spatiotemporal events representing the group was generated by aligning and clustering the spatiotemporal events of all individual subjects. The temporal relationship between the common group events generated a network, which is the spatiotemporal reference BNA model. Scores were derived by comparing each subject's spatiotemporal events to the reference BNA model and were then entered into a support vector machine classifier to classify subjects into relevant subgroups. The reliability of the BNA scores (test-retest repeatability using intraclass correlation) and their utility as a classification tool were examined in the context of Target-Novel classification. Results: BNA intraclass correlation values of repeatability ranged between 0.51 and 0.82 for the known ERP components N100, P200, and P300. Classification accuracy was high when the trained data were validated on the same subjects for different visits (AUCs 0.93 and 0.95). The classification accuracy remained high for a test group recorded at a different clinical center with a different recording system (AUCs 0.81, 0.85 for 2 visits). Conclusion: The improved spatiotemporal BNA analysis demonstrates high classification accuracy. The BNA analysis method holds promise as a tool for diagnosis, follow-up and drug development associated with different neurological conditions. PMID:28066224

  10. 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

  11. 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)

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

    PubMed Central

    Nguyen, Vinh Hao; Suh, Young Soo

    2009-01-01

    This paper is concerned with a networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta (SOD), sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. Event-based sampling has been shown to be more efficient than the time-triggered one in some situations, especially in network bandwidth improvement. However, it cannot detect packet dropout situations because data transmission and reception do not use a periodical time-stamp mechanism as found in time-triggered sampling systems. Motivated by this issue, we propose a modified event-based sampling scheme called modified SOD in which sensor data are sent when either the change of sensor output exceeds a given threshold or the time elapses more than a given interval. Through simulation results, we show that the proposed modified SOD sampling significantly improves estimation performance when packet dropouts happen. PMID:22574063

  13. Redesigned Predictive Event-Triggered Controller for Networked Control System With Delays.

    PubMed

    Wu, Di; Sun, Xi-Ming; Wen, Changyun; Wang, Wei

    2016-10-01

    Event-triggered control (ETC) is a control strategy which can effectively reduce communication traffic in control networks. In the case where communication resources are scarce, ETC plays an important role in updating and communicating data. When network-induced delays are involved, two unsynchronized phenomena will appear if the existing ETC strategy, designed for networked control systems (NCSs) free of delays, is adopted. This paper deals with the ETC problem for NCS with delays existing in both sensor-to-controller and controller-to-actuator channels. A new predictive ETC strategy is proposed to solve both unsynchronized problems. It is shown that the stability of the resulting closed-loop system can be guaranteed under such an ETC strategy. Finally, both simulation studies and experimental tests are carried out to illustrate the proposed technique and verify its effectiveness.

  14. 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

  15. 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.

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

    PubMed

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

    2014-12-01

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

  17. 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

  18. 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

  19. Implementation and performance results of neural network for power quality event detection

    NASA Astrophysics Data System (ADS)

    Huang, Weijian; Tian, Wenzhi

    2008-10-01

    A novel method to detect power quality event in distributed power system combing wavelet network with the improved back-propagation algorithm is presented. The paper tries to explain to design complex supported orthogonal wavelets by compactly supported orthogonal real wavelets, and then explore the extraction of disturbance signal to obtain the feature information, and finally propose several novel wavelet combined information to analyze the disturbance signal, superior to real wavelet analysis result. The feature obtained from WT coefficients are inputted into wavelet network for power quality disturbance pattern recognition. The power quality disturbance recognition model is established and the improved back-propagation algorithm is used to fulfill the network parameter initialization. By means of choosing enough samples to train the recognition model, the type of disturbance can be obtained when signal representing fault is inputted to the trained network. The results of simulation analysis show that the complex wavelet transform combined with wavelet network are more sensitive to signal singularity, and found to be significant improvement over current methods in real-time detection.

  20. Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data.

    PubMed

    Saramago, Pedro; Chuang, Ling-Hsiang; Soares, Marta O

    2014-09-10

    Network meta-analysis methods extend the standard pair-wise framework to allow simultaneous comparison of multiple interventions in a single statistical model. Despite published work on network meta-analysis mainly focussing on the synthesis of aggregate data, methods have been developed that allow the use of individual patient-level data specifically when outcomes are dichotomous or continuous. This paper focuses on the synthesis of individual patient-level and summary time to event data, motivated by a real data example looking at the effectiveness of high compression treatments on the healing of venous leg ulcers. This paper introduces a novel network meta-analysis modelling approach that allows individual patient-level (time to event with censoring) and summary-level data (event count for a given follow-up time) to be synthesised jointly by assuming an underlying, common, distribution of time to healing. Alternative model assumptions were tested within the motivating example. Model fit and adequacy measures were used to compare and select models. Due to the availability of individual patient-level data in our example we were able to use a Weibull distribution to describe time to healing; otherwise, we would have been limited to specifying a uniparametric distribution. Absolute effectiveness estimates were more sensitive than relative effectiveness estimates to a range of alternative specifications for the model. The synthesis of time to event data considering individual patient-level data provides modelling flexibility, and can be particularly important when absolute effectiveness estimates, and not just relative effect estimates, are of interest.

  1. Network meta-analysis of (individual patient) time to event data alongside (aggregate) count data

    PubMed Central

    2014-01-01

    Background Network meta-analysis methods extend the standard pair-wise framework to allow simultaneous comparison of multiple interventions in a single statistical model. Despite published work on network meta-analysis mainly focussing on the synthesis of aggregate data, methods have been developed that allow the use of individual patient-level data specifically when outcomes are dichotomous or continuous. This paper focuses on the synthesis of individual patient-level and summary time to event data, motivated by a real data example looking at the effectiveness of high compression treatments on the healing of venous leg ulcers. Methods This paper introduces a novel network meta-analysis modelling approach that allows individual patient-level (time to event with censoring) and summary-level data (event count for a given follow-up time) to be synthesised jointly by assuming an underlying, common, distribution of time to healing. Alternative model assumptions were tested within the motivating example. Model fit and adequacy measures were used to compare and select models. Results Due to the availability of individual patient-level data in our example we were able to use a Weibull distribution to describe time to healing; otherwise, we would have been limited to specifying a uniparametric distribution. Absolute effectiveness estimates were more sensitive than relative effectiveness estimates to a range of alternative specifications for the model. Conclusions The synthesis of time to event data considering individual patient-level data provides modelling flexibility, and can be particularly important when absolute effectiveness estimates, and not just relative effect estimates, are of interest. PMID:25209121

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

    PubMed

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

    2015-03-01

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

  3. Development and application of CATIA-GDML geometry builder

    NASA Astrophysics Data System (ADS)

    Belogurov, S.; Berchun, Yu; Chernogorov, A.; Malzacher, P.; Ovcharenko, E.; Schetinin, V.

    2014-06-01

    Due to conceptual difference between geometry descriptions in Computer-Aided Design (CAD) systems and particle transport Monte Carlo (MC) codes direct conversion of detector geometry in either direction is not feasible. The paper presents an update on functionality and application practice of the CATIA-GDML geometry builder first introduced at CHEP2010. This set of CATIAv5 tools has been developed for building a MC optimized GEANT4/ROOT compatible geometry based on the existing CAD model. The model can be exported via Geometry Description Markup Language (GDML). The builder allows also import and visualization of GEANT4/ROOT geometries in CATIA. The structure of a GDML file, including replicated volumes, volume assemblies and variables, is mapped into a part specification tree. A dedicated file template, a wide range of primitives, tools for measurement and implicit calculation of parameters, different types of multiple volume instantiation, mirroring, positioning and quality check have been implemented. Several use cases are discussed.

  4. Network of recurrent events: an application to aftershock sequences and the ETAS model of seismicity

    NASA Astrophysics Data System (ADS)

    Davidsen, J.; Peixoto, T. De Paula

    2010-05-01

    Many striking features of geophysical processes can be portrayed as patterns or clusters of localized events including, but not limited to, solar flares and earthquakes. A generic attribute in all these cases is that one event can trigger or somehow induce another one to occur - or possibly numerous further events. Studying the spatiotemporal clustering of such localized events is often the only way to gain insight into the underlying microscopic dynamics that causes the triggering. A recently introduced approach (Geophys. Res. Lett. 33, L11304 (2006)) allows one to quantify non-trivial spatiotemporal clustering and to infer the causal structure of activity patterns based on the view that any suitable definition of clustering should be purely contextual and depend only on the actual history of events. The approach utilizes the notion of space-time records and maps the activity pattern onto a network. Here, we apply this method to compare the spatiotemporal clustering of aftershock sequences (Parkfield and Hector Mine) to that of synthetic catalogs generated by the epidemic type aftershock sequence (ETAS) model.

  5. Network of recurrent events: an application to aftershock sequences and the ETAS model of seismicity

    NASA Astrophysics Data System (ADS)

    Davidsen, J.; Doblhoff, K.; de Paula Peixoto, T.

    2009-12-01

    Many striking features of geophysical processes can be portrayed as patterns or clusters of localized events including, but not limited to, solar flares and earthquakes. A generic attribute in all these cases is that one event can trigger or somehow induce another one to occur - or possibly numerous further events. Studying the spatiotemporal clustering of such localized events is often the only way to gain insight into the underlying microscopic dynamics that causes the triggering. A recently introduced approach (Geophys. Res. Lett. 33, L11304 (2006)) allows one to quantify non-trivial spatiotemporal clustering and to infer the causal structure of activity patterns based on the view that any suitable definition of clustering should be purely contextual and depend only on the actual history of events. The approach utilizes the notion of space-time records and maps the activity pattern onto a network. Here, we apply this method to compare the spatiotemporal clustering of aftershock sequences (Parkfield and Hector Mine) to that of synthetic catalogs generated by the epidemic type aftershock sequence (ETAS) model and other stochastic models of aftershock activity.

  6. Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network.

    PubMed

    Zhao, Bo; Ding, Ruoxi; Chen, Shoushun; Linares-Barranco, Bernabe; Tang, Huajin

    2015-09-01

    This paper introduces an event-driven feedforward categorization system, which takes data from a temporal contrast address event representation (AER) sensor. The proposed system extracts bio-inspired cortex-like features and discriminates different patterns using an AER based tempotron classifier (a network of leaky integrate-and-fire spiking neurons). One of the system's most appealing characteristics is its event-driven processing, with both input and features taking the form of address events (spikes). The system was evaluated on an AER posture dataset and compared with two recently developed bio-inspired models. Experimental results have shown that it consumes much less simulation time while still maintaining comparable performance. In addition, experiments on the Mixed National Institute of Standards and Technology (MNIST) image dataset have demonstrated that the proposed system can work not only on raw AER data but also on images (with a preprocessing step to convert images into AER events) and that it can maintain competitive accuracy even when noise is added. The system was further evaluated on the MNIST dynamic vision sensor dataset (in which data is recorded using an AER dynamic vision sensor), with testing accuracy of 88.14%.

  7. Optimal and event-based networked control of physically interconnected systems and multi-agent systems

    NASA Astrophysics Data System (ADS)

    Demir, Ozan; Lunze, Jan

    2014-01-01

    Many interconnected systems like vehicle platoons or energy networks consist of similar or identical subsystems. The subsystem interconnections are either caused by the physical relations among the subsystems or have to be introduced by the controller to cope with cooperative control goals. This paper proposes strategies to reduce the complexity of the controller design problem (offline information reduction) and to reduce the amount of the system information, which is necessary for the implementation of the designed controller (online information reduction). It consists of two parts. The first part deals with the linear quadratic regulator (LQR) design problem for interconnected systems. A decomposition based on a state transformation is introduced, which allows to design the optimal controller for the interconnected system by considering modified subsystems separately. The proposed decomposition approach can be uniformly applied to multi-agent systems and physically interconnected systems. The second part of the paper introduces an event-based control strategy for multi-agent systems. The event-based control is a means to reduce the communication effort by invoking an information exchange among the subsystems only when the deviation between the estimated and current subsystem state exceeds an event threshold. An event-based controller is proposed, which mimics the continuous state-feedback controller with a desired precision. The relation between the event threshold and the approximation error is analysed.

  8. 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.

  9. 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

  10. 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. Copyright © 2014 Wiley Periodicals, Inc.

  11. 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

  12. 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.

  13. 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

  14. Disentangling the attention network test: behavioral, event related potentials, and neural source analyses.

    PubMed

    Galvao-Carmona, Alejandro; González-Rosa, Javier J; Hidalgo-Muñoz, Antonio R; Páramo, Dolores; Benítez, María L; Izquierdo, Guillermo; Vázquez-Marrufo, Manuel

    2014-01-01

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

  15. Disentangling the attention network test: behavioral, event related potentials, and neural source analyses

    PubMed Central

    Galvao-Carmona, Alejandro; González-Rosa, Javier J.; Hidalgo-Muñoz, Antonio R.; Páramo, Dolores; Benítez, María L.; Izquierdo, Guillermo; Vázquez-Marrufo, Manuel

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    1992-07-01

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

  17. 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.

  18. [Analysis of policies in activating the Infectious Disease Specialist Network (IDSN) for bioterrorism events].

    PubMed

    Kim, Yang Soo

    2008-07-01

    Bioterrorism events have worldwide impacts, not only in terms of security and public health policy, but also in other related sectors. Many countries, including Korea, have set up new administrative and operational structures and adapted their preparedness and response plans in order to deal with new kinds of threats. Korea has dual surveillance systems for the early detection of bioterrorism. The first is syndromic surveillance that typically monitors non-specific clinical information that may indicate possible bioterrorism-associated diseases before specific diagnoses are made. The other is infectious disease specialist network that diagnoses and responds to specific illnesses caused by intentional release of biologic agents. Infectious disease physicians, clinical microbiologists, and infection control professionals play critical and complementary roles in these networks. Infectious disease specialists should develop practical and realistic response plans for their institutions in partnership with local and state health departments, in preparation for a real or suspected bioterrorism attack.

  19. 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.

  20. 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.

  1. 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.

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

    PubMed

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

    1994-04-01

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

  3. 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.

  4. Performance issues in SCM label switched networks due to tunable laser switching events

    NASA Astrophysics Data System (ADS)

    Smyth, F.; Barry, L. P.

    2006-09-01

    Optical Packet Switched (OPS) networks employing Optical Label Switching (OLS) techniques have the potential to enable an all-optical internet. In these networks, data remains in optical format throughout the entire network and routing is performed using a separate optical label. The label information is used to control fast tunable lasers that will transfer data packets to different wavelengths for routing and contention resolution. In this paper we investigate interference between subcarrier multiplexed (SCM) labels in such a network, due to switching events in the tunable laser transmitter. This interference may place a limitation on the channel spacing and subcarrier frequency used. Two 50GHz spaced optical carriers were modulated with 2.5Gbit/s SCM labels at 20GHz. Bit error rate measurements were taken with two lasers fixed 50 GHz apart, and also with one of the lasers (an SG-DBR) switching between this channel and another one 800GHz away. When the SG-DBR laser is not switching, a power penalty of approximately 0.25 dB is introduced due to interference through the optical filter. However, when the SG-DBR laser is switching between wavelengths an error floor of 1x10-5 is introduced due to the time it takes the tunable laser to settle to its target channel. In a systems application, this would result in packets being incorrectly routed.

  5. 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.

  6. 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.

  7. Exact event-driven implementation for recurrent networks of stochastic perfect integrate-and-fire neurons.

    PubMed

    Taillefumier, Thibaud; Touboul, Jonathan; Magnasco, Marcelo

    2012-12-01

    In vivo cortical recording reveals that indirectly driven neural assemblies can produce reliable and temporally precise spiking patterns in response to stereotyped stimulation. This suggests that despite being fundamentally noisy, the collective activity of neurons conveys information through temporal coding. Stochastic integrate-and-fire models delineate a natural theoretical framework to study the interplay of intrinsic neural noise and spike timing precision. However, there are inherent difficulties in simulating their networks' dynamics in silico with standard numerical discretization schemes. Indeed, the well-posedness of the evolution of such networks requires temporally ordering every neuronal interaction, whereas the order of interactions is highly sensitive to the random variability of spiking times. Here, we answer these issues for perfect stochastic integrate-and-fire neurons by designing an exact event-driven algorithm for the simulation of recurrent networks, with delayed Dirac-like interactions. In addition to being exact from the mathematical standpoint, our proposed method is highly efficient numerically. We envision that our algorithm is especially indicated for studying the emergence of polychronized motifs in networks evolving under spike-timing-dependent plasticity with intrinsic noise.

  8. 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.

  9. The South American rainfall dipole: A complex network analysis of extreme events

    NASA Astrophysics Data System (ADS)

    Boers, Niklas; Rheinwalt, Aljoscha; Bookhagen, Bodo; Barbosa, Henrique M. J.; Marwan, Norbert; Marengo, José; Kurths, Jürgen

    2014-10-01

    Intraseasonal rainfall variability of the South American monsoon system is characterized by a pronounced dipole between southeastern South America and southeastern Brazil. Here we analyze the dynamical properties of extreme rainfall events associated with this dipole by combining a nonlinear synchronization measure with complex networks. We make the following main observations: (i) Our approach reveals the dominant synchronization pathways of extreme events for the two dipole phases, (ii) while extreme rainfall synchronization in the tropics is directly driven by the trade winds and their deflection by the Andes mountains, extreme rainfall propagation in the subtropics is mainly dictated by frontal systems, and (iii) the well-known rainfall dipole is, in fact, only the most prominent mode of an oscillatory pattern that extends over the entire continent. This provides further evidence that the influence of Rossby waves, which cause frontal systems over South America and impact large-scale circulation patterns, extends beyond the equator.

  10. 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.

  11. Automatic event picking in pre-stack migrated gathers using a probabilistic neural network

    SciTech Connect

    Clark, G. A..; Glinsky, M. E.; Devi, K. R.S.; Robinson, J. H.; Cheng, P. K.Z.; Ford, G. E.

    1996-04-01

    We describe algorithms for automating the process of picking seismic events in pre-stack migrated gathers. The approach uses supervised learning and statistical classification algorithms along with advanced signal-image processing algorithms. We train a probabilistic neural network (PNN) for pixel classification using event times and offsets (ground truth information) picked manually by expert interpreters. The key to success is in using effective features that capture the important behavior of the measured signals. We use a variety of features calculated in a local neighborhood about the pixel under analysis. Feature selection algorithms are used to ensure that we use only the features that maximize class separability. The novelty of the work lies in (a) the use of pre-stack migrated gathers rather than stacked data, (b) the use of two-dimensional statistical and wavelet features, and (c) the use of a PNN for classification. 8 refs., 3 figs

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

    PubMed Central

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

    2013-01-01

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

  13. 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.

  14. Distributed convex optimisation with event-triggered communication in networked systems

    NASA Astrophysics Data System (ADS)

    Liu, Jiayun; Chen, Weisheng

    2016-12-01

    This paper studies the distributed convex optimisation problem over directed networks. Motivated by practical considerations, we propose a novel distributed zero-gradient-sum optimisation algorithm with event-triggered communication. Therefore, communication and control updates just occur at discrete instants when some predefined condition satisfies. Thus, compared with the time-driven distributed optimisation algorithms, the proposed algorithm has the advantages of less energy consumption and less communication cost. Based on Lyapunov approaches, we show that the proposed algorithm makes the system states asymptotically converge to the solution of the problem exponentially fast and the Zeno behaviour is excluded. Finally, simulation example is given to illustrate the effectiveness of the proposed algorithm.

  15. Fault Isolation Filter for Networked Control System with Event-Triggered Sampling Scheme

    PubMed Central

    Li, Shanbin; Sauter, Dominique; Xu, Bugong

    2011-01-01

    In this paper, the sensor data is transmitted only when the absolute value of difference between the current sensor value and the previously transmitted one is greater than the given threshold value. Based on this send-on-delta scheme which is one of the event-triggered sampling strategies, a modified fault isolation filter for a discrete-time networked control system with multiple faults is then implemented by a particular form of the Kalman filter. The proposed fault isolation filter improves the resource utilization with graceful fault estimation performance degradation. An illustrative example is given to show the efficiency of the proposed method. PMID:22346590

  16. Fault isolation filter for networked control system with event-triggered sampling scheme.

    PubMed

    Li, Shanbin; Sauter, Dominique; Xu, Bugong

    2011-01-01

    In this paper, the sensor data is transmitted only when the absolute value of difference between the current sensor value and the previously transmitted one is greater than the given threshold value. Based on this send-on-delta scheme which is one of the event-triggered sampling strategies, a modified fault isolation filter for a discrete-time networked control system with multiple faults is then implemented by a particular form of the Kalman filter. The proposed fault isolation filter improves the resource utilization with graceful fault estimation performance degradation. An illustrative example is given to show the efficiency of the proposed method.

  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.

  18. Dynamic Context-Aware Event Recognition Based on Markov Logic Networks

    PubMed Central

    Liu, Fagui; Deng, Dacheng; Li, Ping

    2017-01-01

    Event recognition in smart spaces is an important and challenging task. Most existing approaches for event recognition purely employ either logical methods that do not handle uncertainty, or probabilistic methods that can hardly manage the representation of structured information. To overcome these limitations, especially in the situation where the uncertainty of sensing data is dynamically changing over the time, we propose a multi-level information fusion model for sensing data and contextual information, and also present a corresponding method to handle uncertainty for event recognition based on Markov logic networks (MLNs) which combine the expressivity of first order logic (FOL) and the uncertainty disposal of probabilistic graphical models (PGMs). Then we put forward an algorithm for updating formula weights in MLNs to deal with data dynamics. Experiments on two datasets from different scenarios are conducted to evaluate the proposed approach. The results show that our approach (i) provides an effective way to recognize events by using the fusion of uncertain data and contextual information based on MLNs and (ii) outperforms the original MLNs-based method in dealing with dynamic data. PMID:28257113

  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. 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.

  1. The TrainBuilder ATCA data acquisition board for the European-XFEL

    NASA Astrophysics Data System (ADS)

    Coughlan, J.; Day, C.; Edwards, J.; Freeman, E.; Galagedera, S.; Halsall, R.

    2012-12-01

    The TrainBuilder is an Advanced Telecom ATCA data acquisition board being developed at the STFC Rutherford Appleton Laboratory to provide readout for the large 2D Mega-pixel detectors under construction for the European-XFEL in Hamburg. Each ATCA board can process ~ 8 GBytes/sec of raw detector data. The TrainBuilder system merges up to 5,120 partial detector images per second using FPGAs with DDR2 data buffers and an analogue crosspoint switch architecture. The TrainBuilder links operate with 10 Gigabit Ethernet protocols implemented in FPGA logic. The first TrainBuilder demonstrator boards were manufactured in Q1/2012.

  2. The First Documented Space Weather Event That Perturbed the Communication Networks in Iberia

    NASA Astrophysics Data System (ADS)

    Ribeiro, P.; Vaquero, J. M.; Gallego, M. C.; Trigo, R. M.

    2016-07-01

    In this work, we review the first space weather event that affected significantly a number of communication networks in the Iberian Peninsula (Southwest of Europe). The event took place on 31 October 1903, during the ascending phase of solar cycle 14 (the lowest since the Dalton Minimum). We describe the widespread problems that occurred in the telegraph communication network in two midlatitude countries (Portugal and Spain), that was practically interrupted from 09 h30 to 21 h00 UT. Different impacts on the telegraphic communication are described and shown to be dependent on the large-scale orientation of the wires. In order to put these results into a wider context we provide measurements of the concurrent geomagnetic field that are available from the observatories of Coimbra (Portugal) and San Fernando (Spain). The measurements confirm the simultaneous occurrence of large geomagnetic disturbances. In particular, the magnetograms recorded in Coimbra show a clear and large amplitude storm sudden commencement around 05 h30. The main phase, with a H (horizontal component of geomagnetic field) maximum range of ~500 nT, started approximately 1 h later and lasted for almost 10 h, suggesting that the interplanetary magnetic field was strongly southward for long time.

  3. Energy deprivation transiently enhances rhythmic inhibitory events in the CA3 hippocampal network in vitro.

    PubMed

    Gee, C E; Benquet, P; Demont-Guignard, S; Wendling, F; Gerber, U

    2010-07-14

    Oxygen glucose deprivation (OGD) leads to rapid suppression of synaptic transmission. Here we describe an emergence of rhythmic activity at 8 to 20 Hz in the CA3 subfield of hippocampal slice cultures occurring for a few minutes prior to the OGD-induced cessation of evoked responses. These oscillations, dominated by inhibitory events, represent network activity, as they were abolished by tetrodotoxin. They were also completely blocked by the GABAergic antagonist picrotoxin, and strongly reduced by the glutamatergic antagonist NBQX. Applying CPP to block NMDA receptors had no effect and neither did UBP302, an antagonist of GluK1-containing kainate receptors. The gap junction blocker mefloquine disrupted rhythmicity. Simultaneous whole-cell voltage-clamp recordings from neighboring or distant CA3 pyramidal cells revealed strong cross-correlation of the incoming rhythmic activity. Interneurons in the CA3 area received similar correlated activity. Interestingly, oscillations were much less frequently observed in the CA1 area. These data, together with the observation that the recorded activity consists primarily of inhibitory events, suggest that CA3 interneurons are important for generating these oscillations. This transient increase in inhibitory network activity during OGD may represent a mechanism contributing to the lower vulnerability to ischemic insults of the CA3 area as compared to the CA1 area.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Shouxu; Xie, Duosi; Yan, Weisheng

    2017-08-01

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

  5. Time is of the essence: an application of a relational event model for animal social networks.

    PubMed

    Patison, K P; Quintane, E; Swain, D L; Robins, G; Pattison, P

    Understanding how animal social relationships are created, maintained and severed has ecological and evolutionary significance. Animal social relationships are inferred from observations of interactions between animals; the pattern of interaction over time indicates the existence (or absence) of a social relationship. Autonomous behavioural recording technologies are increasingly being used to collect continuous interaction data on animal associations. However, continuous data sequences are typically aggregated to represent a relationship as part of one (or several) pictures of the network of relations among animals, in a way that parallels human social networks. This transformation entails loss of information about interaction timing and sequence, which are particularly important to understand the formation of relationships or their disruption. Here, we describe a new statistical model, termed the relational event model, that enables the analysis of fine-grained animal association data as a continuous time sequence without requiring aggregation of the data. We apply the model to a unique data set of interaction between familiar and unfamiliar steers during a series of 36 experiments to investigate the process of social disruption and relationship formation. We show how the model provides key insights into animal behaviour in terms of relationship building, the integration process of unfamiliar animals and group building dynamics. The relational event model is well suited to data structures that are common to animal behavioural studies and can therefore be applied to a range of social interaction data to understand animal social dynamics.

  6. Incidence and Characteristics of Ventilator-Associated Events Reported to the National Healthcare Safety Network in 2014*

    PubMed Central

    Li, Qunna; Gross, Cindy; Dudeck, Margaret; Allen-Bridson, Katherine; Edwards, Jonathan R.

    2016-01-01

    Objective: Ventilator-associated event surveillance was introduced in the National Healthcare Safety Network in 2013, replacing surveillance for ventilator-associated pneumonia in adult inpatient locations. We determined incidence rates and characteristics of ventilator-associated events reported to the National Healthcare Safety Network. Design, Setting, and Patients: We analyzed data reported from U.S. healthcare facilities for ventilator-associated events that occurred in 2014, the first year during which ventilator-associated event surveillance definitions were stable. We used negative binomial regression modeling to identify healthcare facility and inpatient location characteristics associated with ventilator-associated events. We calculated ventilator-associated event incidence rates, rate distributions, and ventilator utilization ratios in critical care and noncritical care locations and described event characteristics. Measurements and Main Results: A total of 1,824 healthcare facilities reported 32,772 location months of ventilator-associated event surveillance data to the National Healthcare Safety Network in 2014. Critical care unit pooled mean ventilator-associated event incidence rates ranged from 2.00 to 11.79 per 1,000 ventilator days, whereas noncritical care unit rates ranged from 0 to 14.86 per 1,000 ventilator days. The pooled mean proportion of ventilator-associated events defined as infection-related varied from 15.38% to 47.62% in critical care units. Pooled mean ventilator utilization ratios in critical care units ranged from 0.24 to 0.47. Conclusions: We found substantial variability in ventilator-associated event incidence, proportions of ventilator-associated events characterized as infection-related, and ventilator utilization within and among location types. More work is needed to understand the preventable fraction of ventilator-associated events and identify patient care strategies that reduce ventilator-associated events. PMID

  7. 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

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

    NASA Astrophysics Data System (ADS)

    Sao Sabbas, F. T.

    2012-12-01

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

  9. Differential Network Analyses of Alzheimer's Disease Identify Early Events in Alzheimer's Disease Pathology

    PubMed Central

    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 low 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. PMID:25147748

  10. 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.

  11. Creating an infrastructure for safety event reporting and analysis in a multicenter pediatric emergency department network.

    PubMed

    Chamberlain, James M; Shaw, Kathy N; Lillis, Kathleen A; Mahajan, Prashant V; Ruddy, Richard M; Lichenstein, Richard; Olsen, Cody S; Dean, J Michael

    2013-02-01

    Hospital incident reporting is widely used but has had limited effectiveness for improving patient safety nationally. We describe the process of establishing a multi-institutional safety event reporting system. A descriptive study in The Pediatric Emergency Care Applied Research Network of 22 hospital emergency departments was performed. An extensive legal analysis addressed investigators' concerns about sharing confidential incident reports (IRs): (1) the ability to identify sites and (2) potential loss of peer review statute protection. Of the 22 Pediatric Emergency Care Applied Research Network sites, 19 received institutional approval to submit deidentified IRs to the data center. Incident reports were randomly assigned to independent review; discordance was resolved by consensus. Incident reports were categorized by type, subtype, severity, staff involved, and contributing factors. A total of 3,106 IRs were submitted by 18 sites in the first year. Reporting rates ranged more than 50-fold from 0.12 to 6.13 per 1000 patients. Data were sufficient to determine type of error (90% of IRs), severity (79%), staff involved (82%), and contributing factors (82%). However, contributing factors were clearly identified in only 44% of IRs and required extrapolation by investigators in 38%. The most common incidents were related to laboratory specimens (25.5%), medication administration (19.3%), and process variance, such as delays in care (14.4%). Incident reporting provides qualitative data concerning safety events. Perceived legal barriers to sharing confidential data can be addressed. Large variability in reporting rates and low rates of providing contributing factors suggest a need for standardization and improvement of safety event reporting.

  12. Classification and Prediction of Event-based Suspended Sediment Dynamics using Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Hamshaw, S. D.; Underwood, K.; Wemple, B. C.; Rizzo, D.

    2016-12-01

    Sediment transport can be an immensely complex process, yet plays a vital role in the transport of substances and nutrients that can impact receiving waters. Advancements in the use of sensors for indirect measurement of suspended sediments have allowed access to high frequency sediment data. This has promoted the use of more advanced computational tools to identify patterns in sediment data to improve our understanding of physical processes occurring in the watershed. In this study, a network of weather stations and in-stream turbidity sensors were deployed to capture more than three years of sediment dynamics and meteorological data in the Mad River watershed in central Vermont. Monitoring sites were located along the main stem of the the Mad River and on five tributaries. Separate storm events were identified from the data at each site to study event sediment dynamics associated with erosion and deposition over space and time. Two types of artificial neural networks (ANNs), a self-organizing map (SOM) and a radial basis function (RBF), were used to cluster the storm event data based on hydrometeorological metrics and were subsequently compared to traditional classes of hysteresis patterns in suspended sediment concentration - discharge (SSC-Q) relationships. Hysteresis patterns were also directly used as inputs to both ANNs to identify distinct patterns and test the applicability of performing pattern recognition on hysteresis patterns. The results of this study will be used to gain insight into the dynamic physical processes (both spatial and temporal) occurring in the watershed based on patterns observed in SSQ-Q data.

  13. 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.

  14. 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.

  15. Eliminating Critical Incident Tracking Network Patient Safety Events at a Veterans Affairs Institution Through Crew Resource Management Training.

    PubMed

    Kuy, SreyRam; Romero, Ramon A L

    The objective of this study was to determine whether rates of Critical Incident Tracking Network (CITN) patient safety adverse events change after implementation of crew resource management (CRM) training at a Veterans Affairs (VA) hospital. CRM training was conducted for all surgical staff at a VA hospital. Compliance with briefing and debriefing checklists was assessed for all operating room procedures. Tracking of adverse patient safety events utilizing the VA CITN events was performed. There was 100% adherence to performance of briefings and debriefings after initiation of CRM training. There were 3 CITN events in the year prior to implementation of CRM training; following CRM training, there have been zero CITN events. Following CRM training, CITN events were eliminated, and this has been sustained for 2.5 years. This is the first study to demonstrate the impact of CRM training on CITN events, specifically, in a VA medical center.

  16. Networks of recurrent events, a theory of records, and an application to finding causal signatures in seismicity.

    PubMed

    Davidsen, Jörn; Grassberger, Peter; Paczuski, Maya

    2008-06-01

    We propose a method to search for signs of causal structure in spatiotemporal data making minimal a priori assumptions about the underlying dynamics. To this end, we generalize the elementary concept of recurrence for a point process in time to recurrent events in space and time. An event is defined to be a recurrence of any previous event if it is closer to it in space than all the intervening events. As such, each sequence of recurrences for a given event is a record breaking process. This definition provides a strictly data driven technique to search for structure. Defining events to be nodes, and linking each event to its recurrences, generates a network of recurrent events. Significant deviations in statistical properties of that network compared to networks arising from (acausal) random processes allows one to infer attributes of the causal dynamics that generate observable correlations in the patterns. We derive analytically a number of properties for the network of recurrent events composed by a random process in space and time. We extend the theory of records to treat not only the variable where records happen, but also time as continuous. In this way, we construct a fully symmetric theory of records leading to a number of results. Those analytic results are compared in detail to the properties of a network synthesized from time series of epicenter locations for earthquakes in Southern California. Significant disparities from the ensemble of acausal networks that can be plausibly attributed to the causal structure of seismicity are as follows. (1) Invariance of network statistics with the time span of the events considered. (2) The appearance of a fundamental length scale for recurrences, independent of the time span of the catalog, which is consistent with observations of the "rupture length." (3) Hierarchy in the distances and times of subsequent recurrences. As expected, almost all of the statistical properties of a network constructed from a surrogate

  17. Efficient Data Collection and Event Boundary Detection in Wireless Sensor Networks Using Tiny Models

    NASA Astrophysics Data System (ADS)

    King, Kraig; Nittel, Silvia

    Using wireless geosensor networks (WGSN), sensor nodes often monitor a phenomenon that is both continuous in time and space. However, sensor nodes take discrete samples, and an analytical framework inside or outside the WSN is used to analyze the phenomenon. In both cases, expensive communication is used to stream a large number of data samples to other nodes and to the base station. In this work, we explore a novel alternative that utilizes predictive process knowledge of the observed phenomena to minimize upstream communication. Often, observed phenomena adhere to a process with predictable behavior over time. We present a strategy for developing and running so-called 'tiny models' on individual sensor nodes that capture the predictable behavior of the phenomenon; nodes now only communicate when unexpected events are observed. Using multiple simulations, we demonstrate that a significant percentage of messages can be reduced during data collection.

  18. 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.

  19. 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.

  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. 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...

  2. 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...

  3. Statistical downscaling of extreme rainfall events in Romania using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Birsan, Marius-Victor; Busuioc, Aristita; Dumitrescu, Alexandru

    2013-04-01

    The main purpose of statistical downscaling methods is to model the relationship between large-scale atmospheric circulation and climatic variables on a regional and subregional scale. Downscaling is an important area of research as it bridges the gap between predictions of future circulation generated by General Circulation Models (GCMs) and the effects of climate change on smaller areas. In this study we present the first results of a statistical downscaling model, using a neural network-based approach by means of multi-layer perceptron networks. As predictands, various indices associated to temperature and precipitation extremes in Romania are used over the entire country (for temperature extremes) and on selected homogenous areas (for precipitation extremes). Several large-scale predictors (sea-level pressure, temperature at 850 / 700 hPa, specific humidity at 850 / 700 hPa) are tested, in order to select the optimum statistical model for each predictand. Predictands are considered separately or in various combinations. This work has been realised within the research project "Changes in climate extremes and associated impact in hydrological events in Romania" (CLIMHYDEX), code PN II-ID-2011-2-0073, financed by the Romanian Executive Agency for Higher Education Research, Development and Innovation Funding (UEFISCDI).

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. Classification of arrhythmic events in ambulatory electrocardiogram, using artificial neural networks.

    PubMed

    Silipo, R; Gori, M; Taddei, A; Varanini, M; Marchesi, C

    1995-08-01

    We propose artificial neural networks (ANN) for ambulatory ECG arrhythmic event classification, and we compare them with some traditional classifiers (TC). Among them, the one based on the median method (heuristic algorithm) was chosen and taken as a quality reference in this study, while a back propagation based classifier, designed as an autoassociator for its peculiar capability of rejecting unknown patterns, was examined. Two tests were performed: the first to discriminate normal vs ventricular beats and the second to distinguish among three classes of arrhythmic events. The results show that the ANN approach is more reliable than the traditional classifiers in discriminating among many classes of arrhythmic events: 98% by ANN vs 99% by a TC for correctly classified normal beats, 98% by ANN vs 96% by TC for correctly classified ventricular ectopic beats, 96% by ANN vs 59% by TC for correctly classified supraventricular ectopic beats, and 83% by ANN vs 86% by median method for correctly classified aberrated atrial premature beats. This paper also tackles the problem of the management of classification uncertainty. Two concurrent uncertainty criteria have been introduced, to reduce the classification error of the unknown ventricular and supraventricular arrhythmic beats respectively. The error in ventricular beats case was kept close to 0% in average and for supraventricular beats was kept at 35% in average. So we can state that the ANN approach is powerful in classifying beats represented in the training set and that it manages the uncertainty in such a way as to reduce, in any case, the global error percentage.

  10. 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...

  11. 46 CFR 308.409 - Standard form of War Risk Builder's Risk Insurance Policy, Form MA-283.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 46 Shipping 8 2012-10-01 2012-10-01 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...

  12. 46 CFR 308.409 - Standard form of War Risk Builder's Risk Insurance Policy, Form MA-283.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 46 Shipping 8 2014-10-01 2014-10-01 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...

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

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 46 Shipping 8 2011-10-01 2011-10-01 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. 46 CFR 308.409 - Standard form of War Risk Builder's Risk Insurance Policy, Form MA-283.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 46 Shipping 8 2013-10-01 2013-10-01 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...

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

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

    PubMed

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

    2016-11-01

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

  2. 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.

  3. BUILDER v.2: Improving the chemistry of a de novo design strategy

    NASA Astrophysics Data System (ADS)

    Roe, Diana C.; Kuntz, Irwin D.

    1995-06-01

    Significant improvements have been made to the de novo drug design program BUILDER. The BUILDER strategy is to find molecule templates that bind tightly to `hot spots' in the target receptor, and then generate bridges to join these templates. In this paper, the bridging algorithm has been further developed to improve the chemical sense and diversity of the bridges, as well as the robustness of the technique. The improved algorithm is then applied to rebuild known bridges in methotrexate and HIV protease. Finally, the entire BUILDER approach is tested by rebuilding methotrexate de novo.

  4. 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++.

  5. Stabilization of Neural-Network-Based Control Systems via Event-Triggered Control With Nonperiodic Sampled Data.

    PubMed

    Hu, Songlin; Yue, Dong; Xie, Xiangpeng; Ma, Yong; Yin, Xiuxia

    2016-12-26

    This paper focuses on a problem of event-triggered stabilization for a class of nonuniformly sampled neural-network-based control systems (NNBCSs). First, a new event-triggered data transmission mechanism is designed based on the nonperiodic sampled data. Different from the previous works, the proposed triggering scheme enables the NNBCSs design to enjoy the advantages of both nonuniform and event-triggered sampling schemes. Second, under the nonperiodic event-triggered data transmission scheme, the nonperiodic sampled-data three-layer fully connected feedforward neural-network (TLFCFFNN)-based event-triggered controller is constructed, and the resulting closed-loop TLFCFFNN-based event-triggered control system is modeled as a state delay system based on time-delay system modeling approach. Then, the stability criteria for the closed-loop system is formulated using Lyapunov-Krasovskii functional approach. Third, the sufficient conditions for the codesign of the TLFCFFNN-based controller and triggering parameters are given in terms of solvability of matrix inequalities to guarantee the asymptotical stability of the closed-loop system and an upper bound on the given cost function while reducing the updates of the controller. Finally, three numerical examples are provided to illustrate the effectiveness and benefits of the proposed results.

  6. DOE Zero Energy Ready Home Case Study: Preferred Builders, Old Greenwich, Connecticut

    SciTech Connect

    none,

    2013-04-01

    The first Challenge Home built in New England features cool-roof shingles, HERS 20–42, and walls densely packed with blown fiberglass. This house won a 2013 Housing Innovation Award in the custom builder category.

  7. 77 FR 2310 - Notice of Submission of Proposed Information Collection to OMB; Builder's Certification/Guarantee...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-17

    ... termite hazards. Builders certify and guarantee that all required treatment for termites are performed and... treatment for termites are performed and there is no infestation of treated areas for a year. Also,...

  8. DETAIL OF CORNERSTONE, WHICH STATES "J.J. DANIELS, BUILDER 1861." NOTE ...

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

    DETAIL OF CORNERSTONE, WHICH STATES "J.J. DANIELS, BUILDER 1861." NOTE ALSO IRON STRAP AT EAST CORNER OF ABUTMENT. - Jackson Covered Bridge, Spanning Sugar Creek, CR 775N (Changed from Spanning Sugar Creek), Bloomingdale, Parke County, IN

  9. James Williamson d/b/a Golden Triangle Builders Information Sheet

    EPA Pesticide Factsheets

    James Williamson d/b/a Golden Triangle Builders (the Company) is located in Pittsburgh, Pennsylvania. The settlement involves renovation activities conducted at property constructed prior to 1978, located in Pittsburgh, Pennsylvania.

  10. BRIDGE BUILDER WILLIAM FLINN’S “CAMP & BRIDGE BUILDING OUTFIT”. INTERIOR ...

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

    BRIDGE BUILDER WILLIAM FLINN’S “CAMP & BRIDGE BUILDING OUTFIT”. INTERIOR VIEW SHOWING LABORERS AT MEAL TIME. - Clear Fork of Brazos River Suspension Bridge, Spanning Clear Fork of Brazos River at County Route 179, Albany, Shackelford County, TX

  11. Best Practices Case Study: Devoted Builders, LLC, Mediterrtanean Villas, Pasco,WA

    SciTech Connect

    2010-12-01

    Devoted Builders of Kennewick, WA worked with Building America's BIRA team to achieve the 50% Federal tax credit level energy savings on 81 homes at its Mediterranean Villas community in eastern Washington.

  12. 77 FR 28411 - Adrenalina, Affinity Technology Group, Inc., Braintech, Inc., Builders Transport, Incorporated...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-14

    ... From the Federal Register Online via the Government Publishing Office SECURITIES AND EXCHANGE COMMISSION Adrenalina, Affinity Technology Group, Inc., Braintech, Inc., Builders Transport, Incorporated... concerning the securities of Affinity Technology Group, Inc. because it has not filed any periodic reports...

  13. Building with passive solar: an application guide for the southern homeowner and builder

    SciTech Connect

    1981-03-01

    This instructional material was prepared for training workshops for builders and home designers. It includes: fundamental definitions and equations, climate and site studies, building components, passive systems and techniques, and design tools. (MHR)

  14. Multistate Model Builder (MSMB): a flexible editor for compact biochemical models

    PubMed Central

    2014-01-01

    Background Building models of molecular regulatory networks is challenging not just because of the intrinsic difficulty of describing complex biological processes. Writing a model is a creative effort that calls for more flexibility and interactive support than offered by many of today’s biochemical model editors. Our model editor MSMB — Multistate Model Builder — supports multistate models created using different modeling styles. Results MSMB provides two separate advances on existing network model editors. (1) A simple but powerful syntax is used to describe multistate species. This reduces the number of reactions needed to represent certain molecular systems, thereby reducing the complexity of model creation. (2) Extensive feedback is given during all stages of the model creation process on the existing state of the model. Users may activate error notifications of varying stringency on the fly, and use these messages as a guide toward a consistent, syntactically correct model. MSMB default values and behavior during model manipulation (e.g., when renaming or deleting an element) can be adapted to suit the modeler, thus supporting creativity rather than interfering with it. MSMB’s internal model representation allows saving a model with errors and inconsistencies (e.g., an undefined function argument; a syntactically malformed reaction). A consistent model can be exported to SBML or COPASI formats. We show the effectiveness of MSMB’s multistate syntax through models of the cell cycle and mRNA transcription. Conclusions Using multistate reactions reduces the number of reactions need to encode many biochemical network models. This reduces the cognitive load for a given model, thereby making it easier for modelers to build more complex models. The many interactive editing support features provided by MSMB make it easier for modelers to create syntactically valid models, thus speeding model creation. Complete information and the installation package can be

  15. Solar project description for Arno Kahn/Builders and Laborers Commonwealth single family residence Duluth, Minnesota

    SciTech Connect

    Moore, D

    1982-04-30

    The Arno Kahn/Builders and Laborers Commonwealth Site is a house in a Minnesota suburb. It combines a modified direct-gain sun space system with a thermal envelope. The living space is separated from the sun space by a three-story mass wall. Sunlight enters the three-story solarium and heats the mass wall which in turn heats the air. The warm air is then distributed through the thermal envelope. Manually operated shades provide night insulation for the south-facing windows, and roof overhangs and a turbine vent in the solarium roof prevent overheating. Domestic hot water is preheated in four tanks located behind the window of the basement sunroom. The concrete floor in the basement provides part of the heat storage. Wood burning stoves and electric baseboard heaters provide auxiliary heating. Five modes of operation are described: collector-to-storage, collector-to-space heating, storage-to-space heating, solarium cooling and domestic hot water preheating. The instrumentation for the National Solar Data Network is described. The solar energy portion of the construction costs is estimated to be $7000. (LEW)

  16. An Adaptive Method for Scheduling the Sequence and Route of Builder Trials for a New Ship

    DTIC Science & Technology

    2015-09-01

    FOR SCHEDULING THE SEQUENCE AND ROUTE OF BUILDER TRIALS FOR A NEW SHIP by Ahmed Raza Tahir September 2015 Thesis Advisor: Susan M... TRIALS FOR A NEW SHIP 5. FUNDING NUMBERS 6. AUTHOR(S) Tahir, Ahmed Raza 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School...brought into service, it has to undergo various trials as part of its delivery. The builder shipyard aims at completing the maximum number of trials in

  17. Building America Top Innovations 2012: DOE Challenge Home (Formerly Builders Challenge)

    SciTech Connect

    none,

    2013-01-01

    This Building America Top Innovations profile describes DOE’s Builders Challenge. Hundreds of leading-edge builders across the country signed on to the Challenge and more than 14,000 homes earned the label, saving homeowners over $10 million a year in utility bills. DOE’s new program, the DOE Challenge Home, increases the rigor of the guidelines including requiring homes to be Zero Net-Energy Ready.

  18. Long-Term Responses of the Endemic Reef-Builder Cladocora caespitosa to Mediterranean Warming

    PubMed Central

    Kersting, Diego K.; Bensoussan, Nathaniel; Linares, Cristina

    2013-01-01

    Recurrent climate-induced mass-mortalities have been recorded in the Mediterranean Sea over the past 15 years. Cladocora caespitosa, the sole zooxanthellate scleractinian reef-builder in the Mediterranean, is among the organisms affected by these episodes. Extensive bioconstructions of this endemic coral are very rare at the present time and are threatened by several stressors. In this study, we assessed the long-term response of this temperate coral to warming sea-water in the Columbretes Islands (NW Mediterranean) and described, for the first time, the relationship between recurrent mortality events and local sea surface temperature (SST) regimes in the Mediterranean Sea. A water temperature series spanning more than 20 years showed a summer warming trend of 0.06°C per year and an increased frequency of positive thermal anomalies. Mortality resulted from tissue necrosis without massive zooxanthellae loss and during the 11-year study, necrosis was recorded during nine summers separated into two mortality periods (2003–2006 and 2008–2012). The highest necrosis rates were registered during the first mortality period, after the exceptionally hot summer of 2003. Although necrosis and temperature were significantly associated, the variability in necrosis rates during summers with similar thermal anomalies pointed to other acting factors. In this sense, our results showed that these differences were more closely related to the interannual temperature context and delayed thermal stress after extreme summers, rather than to acclimatisation and adaption processes. PMID:23951016

  19. 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…

  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. ABodyBuilder: Automated antibody structure prediction with data–driven accuracy estimation

    PubMed Central

    Leem, Jinwoo; Dunbar, James; Georges, Guy; Shi, Jiye; Deane, Charlotte M.

    2016-01-01

    ABSTRACT Computational modeling of antibody structures plays a critical role in therapeutic antibody design. Several antibody modeling pipelines exist, but no freely available methods currently model nanobodies, provide estimates of expected model accuracy, or highlight potential issues with the antibody's experimental development. Here, we describe our automated antibody modeling pipeline, ABodyBuilder, designed to overcome these issues. The algorithm itself follows the standard 4 steps of template selection, orientation prediction, complementarity-determining region (CDR) loop modeling, and side chain prediction. ABodyBuilder then annotates the ‘confidence’ of the model as a probability that a component of the antibody (e.g., CDRL3 loop) will be modeled within a root–mean square deviation threshold. It also flags structural motifs on the model that are known to cause issues during in vitro development. ABodyBuilder was tested on 4 separate datasets, including the 11 antibodies from the Antibody Modeling Assessment–II competition. ABodyBuilder builds models that are of similar quality to other methodologies, with sub–Angstrom predictions for the ‘canonical’ CDR loops. Its ability to model nanobodies, and rapidly generate models (∼30 seconds per model) widens its potential usage. ABodyBuilder can also help users in decision–making for the development of novel antibodies because it provides model confidence and potential sequence liabilities. ABodyBuilder is freely available at http://opig.stats.ox.ac.uk/webapps/abodybuilder. PMID:27392298

  2. MCPB.py: A Python Based Metal Center Parameter Builder.

    PubMed

    Li, Pengfei; Merz, Kenneth M

    2016-04-25

    MCPB.py, a python based metal center parameter builder, has been developed to build force fields for the simulation of metal complexes employing the bonded model approach. It has an optimized code structure, with far fewer required steps than the previous developed MCPB program. It supports various AMBER force fields and more than 80 metal ions. A series of parametrization schemes to derive force constants and charge parameters are available within the program. We give two examples (one metalloprotein example and one organometallic compound example), indicating the program's ability to build reliable force fields for different metal ion containing complexes. The original version was released with AmberTools15. It is provided via the GNU General Public License v3.0 (GNU_GPL_v3) agreement and is free to download and distribute. MCPB.py provides a bridge between quantum mechanical calculations and molecular dynamics simulation software packages thereby enabling the modeling of metal ion centers. It offers an entry into simulating metal ions in a number of situations by providing an efficient way for researchers to handle the vagaries and difficulties associated with metal ion modeling.

  3. Librarians as Knowledge Builders: Strategic Partnering for Service and Advocacy

    SciTech Connect

    Kreitz, P

    2003-12-15

    In their article on the challenges facing the postmodern library authors Elteto and Frank warn that the ''relevancy of academic libraries are at stake as a result of dramatic budget reductions and ongoing changes in the use of libraries.'' Recognizing the fiscal crisis facing libraries, many leaders in the profession are calling for libraries to strengthen their core roles in supporting campus research, teaching, and learning and to become more proactive and effective communicators of the critical role the library plays in supporting institutional goals. Responding to this difficult period facing academia and interested in highlighting the creative ways academic libraries around the country are responding, ACRL President, Tyrone Cannon has chosen ''Partnerships and Connections: the Learning Community as Knowledge Builders'' 2 as the theme for his presidential year. His intention is to foster opportunities for libraries to ''play a key role in developing, defining and enhancing learning communities central to campus life.'' Focusing our efforts on supporting the core business of academia will ensure that academic libraries continue to be places of ''opportunity, interaction, serendipity and strong collections and remain central to the knowledge building process.''

  4. 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.

  5. 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.

  6. 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.

  7. Toward Regional Clusters: Networking Events, Collaborative Research, and the Business Finder

    NASA Astrophysics Data System (ADS)

    Reichling, Tim; Moos, Benjamin; Rohde, Markus; Wulf, Volker

    Networks of regionally collocated organizations improve the competitiveness of their member companies. This is not only a result of lower transportation costs when delivering or purchasing physical goods but also other matters such as mutual trust or a higher diffusion of specialized knowledge among companies that have emerged as important aspects of regional networks. Even increased competition among collocated companies can lead to comparative advantages over externals as a result of an increased pressure for innovation. While the reasons why regional networks of companies offer comparative advantages has been widely investigated, the question arises as to how networks can be developed in terms of higher interconnectedness and deeper connections.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Newson, A.; See, L.

    2005-12-01

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

  10. Communication activity in a social network: relation between long-term correlations and inter-event clustering.

    PubMed

    Rybski, Diego; Buldyrev, Sergey V; Havlin, Shlomo; Liljeros, Fredrik; Makse, Hernán A

    2012-01-01

    Human communication in social networks is dominated by emergent statistical laws such as non-trivial correlations and temporal clustering. Recently, we found long-term correlations in the user's activity in social communities. Here, we extend this work to study the collective behavior of the whole community with the goal of understanding the origin of clustering and long-term persistence. At the individual level, we find that the correlations in activity are a byproduct of the clustering expressed in the power-law distribution of inter-event times of single users, i.e. short periods of many events are separated by long periods of no events. On the contrary, the activity of the whole community presents long-term correlations that are a true emergent property of the system, i.e. they are not related to the distribution of inter-event times. This result suggests the existence of collective behavior, possibly arising from nontrivial communication patterns through the embedding social network.

  11. Integrative network analysis reveals time-dependent molecular events underlying left ventricular remodeling in post-myocardial infarction patients.

    PubMed

    Pinet, Florence; Cuvelliez, Marie; Kelder, Thomas; Amouyel, Philippe; Radonjic, Marijana; Bauters, Christophe

    2017-02-03

    To elucidate the time-resolved molecular events underlying the LV remodeling (LVR) process, we developed a large-scale network model that integrates the 24 molecular variables (plasma proteins and non-coding RNAs) collected in the REVE-2 study at four time points (baseline, 1month, 3months and 1year) after MI. The REVE-2 network model was built by extending the set of REVE-2 variables with their mechanistic context based on known molecular interactions (1310 nodes and 8639 edges). Changes in the molecular variables between the group of patients with high LVR (>20%) and low LVR (<20%) were used to identify active network modules within the clusters associated with progression of LVR, enabling assessment of time-resolved molecular changes. Although the majority of molecular changes occur at the baseline, two network modules specifically show an increasing number of active molecules throughout the post-MI follow up: one involved in muscle filament sliding, containing the major troponin forms and tropomyosin proteins, and the other associated with extracellular matrix disassembly, including matrix metalloproteinases, tissue inhibitors of metalloproteinases and laminin proteins. For the first time, integrative network analysis of molecular variables collected in REVE-2 patients with known molecular interactions allows insight into time-dependent mechanisms associated with LVR following MI, linking specific processes with LV structure alteration. In addition, the REVE-2 network model provides a shortlist of prioritized putative novel biomarker candidates for detection of LVR after MI event associated with a high risk of heart failure and is a valuable resource for further hypothesis generation.

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

    NASA Astrophysics Data System (ADS)

    Zhang, Wenbing; Wang, Zidong; Liu, Yurong; Ding, Derui; Alsaadi, Fuad E.

    2017-01-01

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

  13. The spatiotemporal substrates of autobiographical recollection: Using event-related ICA to study cognitive networks in action.

    PubMed

    Tailby, Chris; Rayner, Genevieve; Wilson, Sarah; Jackson, Graeme

    2017-03-02

    Higher cognitive functions depend upon dynamically unfolding brain network interactions. Autobiographical recollection - the autonoetic re-experiencing of context rich, emotionally laden, personally experienced episodes - is an excellent example of such a process. Autobiographical recollection unfolds over time, with different cognitive processes engaged at different times throughout. In this paper we apply a recently developed analysis technique - event related independent components analysis (eICA) - to study the spatiotemporal dynamics of neural activity supporting autobiographical recollection. Participants completed an in-scanner autobiographical recollection paradigm in which the recalled episodes varied in chronological age and emotional content. By combining eICA with these cognitive manipulations we show that the brain-wide response to autobiographical recollection comprises brain networks with (i) different sensitivities to psychological aspects of the to-be-recollected material and (ii) distinct temporal profiles of activity during recollection. We identified networks with transient activations (in language and cognitive control related regions) and deactivations (in auditory and sensorimotor regions) to each autobiographical probe question, as well as networks with responses that are sustained over the course of the recollection period. These latter networks together overlapped spatially with the broader default mode network (DMN), indicating subspecialisation within the DMN. The vividness of participants' recollection was associated with the magnitude of activation in left dorsolateral prefrontal cortex and deactivation in visual association cortices. We interpret our results in the context of current theories of the spatial and temporal organisation of the human autobiographical memory system. Our findings demonstrate the utility of eICA as a tool for studying higher cognitive functions. The application of eICA to high spatial and temporal resolution

  14. Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates.

    PubMed

    Tan, Francisca M; Caballero-Gaudes, César; Mullinger, Karen J; Cho, Siu-Yeung; Zhang, Yaping; Dryden, Ian L; Francis, Susan T; Gowland, Penny A

    2017-08-16

    Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information, but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of activation likelihood estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the sensorimotor network (SMN) to six motor functions (left/right fingers, left/right toes, swallowing, and eye blinks). We validated the framework using simultaneous electromyography (EMG)-fMRI experiments and motor tasks with short and long duration, and random interstimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events were 77 ± 13% and 74 ± 16%, respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55% and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this article discusses methodological implications and improvements to increase the decoding performance. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

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

    PubMed

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

    2017-01-01

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

  16. Friend me or you'll strain us: understanding negative events that occur over social networking sites.

    PubMed

    Tokunaga, Robert S

    2011-01-01

    Social networking sites (SNSs) provide the ideal infrastructure for the maintenance of existing relationships and the development of new contacts. Although these Web-based technologies supplement offline relationships, several of their characteristics have the potential to provoke negative experiences. The interpersonal strain and other relational problems stemming from negative events have recently gained notoriety. This investigation examines personal accounts of users who have experienced these negative events, which are described as any encounter or behavior exercised by others that instigates interpersonal strain, on SNSs to understand better the nature of this phenomenon. Using a mixed-methods approach, open coding of open-ended responses revealed 10 negative event types that surface during participation on SNSs. Quantitative coding was then used to identify a cut-off point for the most frequently experienced negative events. The findings reveal that the three most commonly experienced negative event types include ignoring or denying friend requests, deleting public messages or identification tags, and identifying ranking disparities on Top Friends applications. The practical, theoretical, and negative social implications of participation on SNSs are discussed.

  17. 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.

  18. 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.

  19. An Application of Exponential Neural Networks to Event-Train Recognition.

    DTIC Science & Technology

    1992-05-08

    The purpose of this project is to investigate neural networks for specific applications in passive electronic warfare (EW) involving restoration of...was determined that back propagation neural networks did not represent a logistically supportable means of training. Gaussian radial basis functions...were found to be far superior. This report is composed of three chapters: (1) summary of early experiments, (2) introduction to exponential neural

  20. Transitioning to High Performance Homes: Successes and Lessons Learned From Seven Builders

    SciTech Connect

    Widder, Sarah H.; Kora, Angela R.; Baechler, Michael C.; Fonorow, Ken; Jenkins, David W.; Stroer, Dennis

    2013-03-01

    As homebuyers are becoming increasingly concerned about rising energy costs and the impact of fossil fuels as a major source of greenhouse gases, the returning new home market is beginning to demand energy-efficient and comfortable high-performance homes. In response to this, some innovative builders are gaining market share because they are able to market their homes’ comfort, better indoor air quality, and aesthetics, in addition to energy efficiency. The success and marketability of these high-performance homes is creating a builder demand for house plans and information about how to design, build, and sell their own low-energy homes. To help make these and other builders more successful in the transition to high-performance construction techniques, Pacific Northwest National Laboratory (PNNL) partnered with seven interested builders in the hot humid and mixed humid climates to provide technical and design assistance through two building science firms, Florida Home Energy and Resources Organization (FL HERO) and Calcs-Plus, and a designer that offers a line of stock plans designed specifically for energy efficiency, called Energy Smart Home Plans (ESHP). This report summarizes the findings of research on cost-effective high-performance whole-house solutions, focusing on real-world implementation and challenges and identifying effective solutions. The ensuing sections provide project background, profile each of the builders who participated in the program, and describe their houses’ construction characteristics, key challenges the builders encountered during the construction and transaction process); and present primary lessons learned to be applied to future projects. As a result of this technical assistance, 17 homes have been built featuring climate-appropriate efficient envelopes, ducts in conditioned space, and correctly sized and controlled heating, ventilation, and air-conditioning systems. In addition, most builders intend to integrate high

  1. Canadian paediatricians’ approaches to managing patients with adverse events following immunization: The role of the Special Immunization Clinic network

    PubMed Central

    Top, Karina A; Zafack, Joseline; De Serres, Gaston; Halperin, Scott A

    2014-01-01

    BACKGROUND: When moderate or severe adverse events occur after vaccination, physicians and patients may have concerns about future immunizations. Similar concerns arise in patients with underlying conditions whose risk for adverse events may differ from the general population. The Special Immunization Clinic (SIC) network was established in 2013 at 13 sites in Canada to provide expertise in the clinical evaluation and vaccination of these patients. OBJECTIVES: To assess referral patterns for patients with vaccine adverse events or potential vaccine contraindications among paediatricians and to assess the anticipated utilization of an SIC. METHODS: A 12-item questionnaire was distributed to paediatricians and subspecialists participating in the Canadian Paediatric Surveillance Program through monthly e-mail and mail contacts. RESULTS: The response rate was 24% (586 of 2490). Fifty-three percent of respondents practiced general paediatrics exclusively and 52% reported that they administer vaccines. In the previous 12 months, 26% of respondents had encountered children with challenging adverse events or potential vaccine contraindications in their practice and 29% had received referrals for such patients, including 27% of subspecialists. Overall, 69% of respondents indicated that they would be likely or very likely to refer patients to an SIC, and 34% indicated that they would have referred at least one patient to an SIC in the previous 12 months. CONCLUSIONS: Patients who experience challenging adverse events following immunization or potential vaccine contraindications are encountered by paediatricians and subspecialists in all practice settings. The SIC network will be able to respond to a clinical need and support paediatricians in managing these patients. PMID:25332661

  2. Automated 3D Damaged Cavity Model Builder for Lower Surface Acreage Tile on Orbiter

    NASA Technical Reports Server (NTRS)

    Belknap, Shannon; Zhang, Michael

    2013-01-01

    The 3D Automated Thermal Tool for Damaged Acreage Tile Math Model builder was developed to perform quickly and accurately 3D thermal analyses on damaged lower surface acreage tiles and structures beneath the damaged locations on a Space Shuttle Orbiter. The 3D model builder created both TRASYS geometric math models (GMMs) and SINDA thermal math models (TMMs) to simulate an idealized damaged cavity in the damaged tile(s). The GMMs are processed in TRASYS to generate radiation conductors between the surfaces in the cavity. The radiation conductors are inserted into the TMMs, which are processed in SINDA to generate temperature histories for all of the nodes on each layer of the TMM. The invention allows a thermal analyst to create quickly and accurately a 3D model of a damaged lower surface tile on the orbiter. The 3D model builder can generate a GMM and the correspond ing TMM in one or two minutes, with the damaged cavity included in the tile material. A separate program creates a configuration file, which would take a couple of minutes to edit. This configuration file is read by the model builder program to determine the location of the damage, the correct tile type, tile thickness, structure thickness, and SIP thickness of the damage, so that the model builder program can build an accurate model at the specified location. Once the models are built, they are processed by the TRASYS and SINDA.

  3. Glucose tolerance and insulin response to glucose load in body builders.

    PubMed

    Szczypaczewska, M; Nazar, K; Kaciuba-Uscilko, H

    1989-02-01

    To find out to what extent body composition affects glucose tolerance, blood glucose (BG) and insulin (IRI) responses to a 100-g oral glucose tolerance test (OGTT) were compared in 10 male body builders, 11 untrained lean control subjects, and 11 mildly obese men, all of similar age (19-35 years). In comparison with the remaining two groups, the body builders had the lowest percentage of fat, although their lean body mass (LBM) in absolute terms did not differ from that in obese subjects. Both BG and IRI concentrations during the OGTT were the lowest in body builders, medium in controls, and the highest in obese men. The differences in glucose tolerance between the groups were also demonstrated by comparison of the subjects' BG levels during the OGTT with the respective mean BG values obtained in a reference group of 42 healthy nonobese men aged from 20 to 55 years. The data indicate that body builders show better glucose tolerance and improved insulin action in comparison with untrained, nonobese subjects of similar age and body weight. Lean body mass in absolute terms cannot, however, be considered as a sole determinant of the insulin action in the body since in mildly obese subjects glucose tolerance was considerably reduced in spite of the fact that their LBM was similar to that in body builders. Either muscle hypertrophy or reduced adiposity may account for the beneficial effects of body building on glucose metabolism.

  4. Application of gene expression programming and neural networks to predict adverse events of radical hysterectomy in cervical cancer patients.

    PubMed

    Kusy, Maciej; Obrzut, Bogdan; Kluska, Jacek

    2013-12-01

    The aim of this article was to compare gene expression programming (GEP) method with three types of neural networks in the prediction of adverse events of radical hysterectomy in cervical cancer patients. One-hundred and seven patients treated by radical hysterectomy were analyzed. Each record representing a single patient consisted of 10 parameters. The occurrence and lack of perioperative complications imposed a two-class classification problem. In the simulations, GEP algorithm was compared to a multilayer perceptron (MLP), a radial basis function network neural, and a probabilistic neural network. The generalization ability of the models was assessed on the basis of their accuracy, the sensitivity, the specificity, and the area under the receiver operating characteristic curve (AUROC). The GEP classifier provided best results in the prediction of the adverse events with the accuracy of 71.96 %. Comparable but slightly worse outcomes were obtained using MLP, i.e., 71.87 %. For each of measured indices: accuracy, sensitivity, specificity, and the AUROC, the standard deviation was the smallest for the models generated by GEP classifier.

  5. Restoration and Humanitarian Aid Delivery on Interdependent Transportation and Communication Networks After an Extreme Event

    DTIC Science & Technology

    2015-03-26

    seek to maximize the satisfaction of geographically distributed demands for relief items over time by scheduling work crews to selected restoration...extreme event, we seek to maximize the satisfaction of geographically distributed demands for relief items over time by scheduling work crews to selected...extreme event. Namely, in- dividuals at a demand point need some way of learning where to go to collect relief items. We model the satisfaction of this

  6. Observer-Based Non-PDC Control for Networked T-S Fuzzy Systems With an Event-Triggered Communication.

    PubMed

    Peng, Chen; Ma, Shaodong; Xie, Xiangpeng

    2017-02-07

    This paper addresses the problem of an event-triggered non-parallel distribution compensation (PDC) control for networked Takagi-Sugeno (T-S) fuzzy systems, under consideration of the limited data transmission bandwidth and the imperfect premise matching membership functions. First, a unified event-triggered T-S fuzzy model is provided, in which: 1) a fuzzy observer with the imperfect premise matching is constructed to estimate the unmeasurable states of the studied system; 2) a fuzzy controller is designed following the same premise as the observer; and 3) an output-based event-triggering transmission scheme is designed to economize the restricted network resources. Different from the traditional PDC method, the synchronous premise between the fuzzy observer and the T-S fuzzy system are no longer needed in this paper. Second, by use of Lyapunov theory, a stability criterion and a stabilization condition are obtained for ensuring asymptotically stable of the studied system. On account of the imperfect premise matching conditions are well considered in the derivation of the above criteria, less conservation can be expected to enhance the design flexibility. Compared with some existing emulation-based methods, the controller gains are no longer required to be known a priori. Finally, the availability of proposed non-PDC design scheme is illustrated by the backing-up control of a truck-trailer system.

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

    PubMed

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

    2017-01-01

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

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

    PubMed

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

    2017-01-01

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

  9. 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.

  10. Interpreting the Marine Calcium Isotope Record: Influence of Reef Builders

    NASA Astrophysics Data System (ADS)

    Boehm, F.; Eisenhauer, A.; Farkas, J.; Kiessling, W.; Veizer, J.; Wallmann, K.

    2008-12-01

    The calcium isotopic composition of seawater as recorded in brachiopod shells varied substantially during the Paleozoic (Farkas et al. 2007, Geochim. Cosmochim. Acta, 71, 5117-5134). The most prominent feature of the record is an excursion to higher 44Ca/40Ca values that started during the Early Carboniferous and lasted until the Permian. The shift occurred shortly after the transition from a calcite-sea to an aragonite-sea (Sandberg 1983, Nature 305, 19-22; Stanley and Hardie 1998, Pal3, 144, 3-19). It therefore has been interpreted to reflect a change in the average calcium isotope fractionation of carbonates produced in the oceans. Aragonite is depleted by about 0.6 permil in 44Ca/40Ca compared to calcite (Gussone et al. 2005, Geochim. Cosmochim. Acta, 69, 4485-4494). Consequently a transient shift from calcite dominated to an aragonite dominated calcium carbonate sedimentation could have caused the observed 0.5 permil isotope shift. We compare the marine calcium isotope record with a new compilation of the Phanerozoic trends in the skeletal mineralogy of marine invertebrates (Kiessling et al. 2008, Nature Geoscience, 1, 527-530). The compilation is based on data collected in the PaleoReef database and the Paleobiology Database, which include information on Phanerozoic reef complexes and taxonomic collection data of Phanerozoic biota, respectively. We find a strong positive correlation between the calcium isotope ratios and the abundance of aragonitic reef builders from the Silurian until the Permian at a sample resolution of about 10 million years. The two records, however, diverge in the Triassic, when reefs were dominated by aragonite but the calcium isotope values remained at a relatively low level. We also find a good correlation between calcium isotopes and the proportion of aragonite in the general record of Phanerozoic biota. However, in this case the records start to diverge already in the latest Carboniferous. The observations suggest that the

  11. 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.

  12. Spill accident modeling: a critical survey of the event-decision network in the context of IMO's formal safety assessment.

    PubMed

    Ventikos, Nikolaos P; Psaraftis, Harilaos N

    2004-02-27

    In this paper, we present the relationship between an oil spill-assessing approach, namely the event-decision network (EDN) and the formal safety assessment (FSA) of the International Maritime Organization (IMO). We focus on various points at which the Network incorporates basic features of the FSA in order to formulate a state-of-the-art, original strategic tool. In keeping with a safety-friendly effort, we developed the EDN, which implements a scenario-driven, generic tree framework. Moreover, the IMO, under the umbrella of decision-making, has introduced FSA, which is a systematic methodology for enhanced maritime safety by using risk and cost/benefit criteria. It is of interest to describe the introduced spill-scenario analysis/simulation and to pinpoint its interconnections with the aforementioned official instrument. Among other things, the goal of such a task is the enhancement of marine safety and the subsequent protection of seas from oil spills.

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

    PubMed

    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

    2014-06-19

    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. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. NasoNet, modeling the spread of nasopharyngeal cancer with networks of probabilistic events in discrete time.

    PubMed

    Galán, S F; Aguado, F; Díez, F J; Mira, J

    2002-07-01

    The spread of cancer is a non-deterministic dynamic process. As a consequence, the design of an assistant system for the diagnosis and prognosis of the extent of a cancer should be based on a representation method that deals with both uncertainty and time. The ultimate goal is to know the stage of development of a cancer in a patient before selecting the appropriate treatment. A network of probabilistic events in discrete time (NPEDT) is a type of Bayesian network for temporal reasoning that models the causal mechanisms associated with the time evolution of a process. This paper describes NasoNet, a system that applies NPEDTs to the diagnosis and prognosis of nasopharyngeal cancer. We have made use of temporal noisy gates to model the dynamic causal interactions that take place in the domain. The methodology we describe is general enough to be applied to any other type of cancer.

  15. 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.

  16. 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.

  17. Detecting event-related changes of multivariate phase coupling in dynamic brain networks.

    PubMed

    Canolty, Ryan T; Cadieu, Charles F; Koepsell, Kilian; Ganguly, Karunesh; Knight, Robert T; Carmena, Jose M

    2012-04-01

    Oscillatory phase coupling within large-scale brain networks is a topic of increasing interest within systems, cognitive, and theoretical neuroscience. Evidence shows that brain rhythms play a role in controlling neuronal excitability and response modulation (Haider B, McCormick D. Neuron 62: 171-189, 2009) and regulate the efficacy of communication between cortical regions (Fries P. Trends Cogn Sci 9: 474-480, 2005) and distinct spatiotemporal scales (Canolty RT, Knight RT. Trends Cogn Sci 14: 506-515, 2010). In this view, anatomically connected brain areas form the scaffolding upon which neuronal oscillations rapidly create and dissolve transient functional networks (Lakatos P, Karmos G, Mehta A, Ulbert I, Schroeder C. Science 320: 110-113, 2008). Importantly, testing these hypotheses requires methods designed to accurately reflect dynamic changes in multivariate phase coupling within brain networks. Unfortunately, phase coupling between neurophysiological signals is commonly investigated using suboptimal techniques. Here we describe how a recently developed probabilistic model, phase coupling estimation (PCE; Cadieu C, Koepsell K Neural Comput 44: 3107-3126, 2010), can be used to investigate changes in multivariate phase coupling, and we detail the advantages of this model over the commonly employed phase-locking value (PLV; Lachaux JP, Rodriguez E, Martinerie J, Varela F. Human Brain Map 8: 194-208, 1999). We show that the N-dimensional PCE is a natural generalization of the inherently bivariate PLV. Using simulations, we show that PCE accurately captures both direct and indirect (network mediated) coupling between network elements in situations where PLV produces erroneous results. We present empirical results on recordings from humans and nonhuman primates and show that the PCE-estimated coupling values are different from those using the bivariate PLV. Critically on these empirical recordings, PCE output tends to be sparser than the PLVs, indicating fewer

  18. Self inflicted death following inhalation and ingestion of Builders Polyurethane expandable foam.

    PubMed

    Morgan, D R; Musa, M

    2010-11-01

    Builders Polyurethane (PU) expandable foam is a product used to fill voids and provide insulation in the building industry. It is easily available from DIY and hardware stores. Other uses include pest control. It can produce fumes, while curing, which can be toxic to humans, or induce asthma and there are reports of polyurethane foam being combustible unless a fire retardant is incorporated. Death due to can explosion when heated has occurred. A literature review revealed one definite case of attempted suicide, one possible attempt by ingestion of Builders PU expandable foam and one accidental non fatal injection of such foam into the lower urinary tract. There is one report of accidental non fatal inhalation of foam. To our knowledge this is the first case of fatal inhalation and ingestion of Builders Polyurethane expandable foam. Copyright © 2010 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  19. Use of anabolic-androgenic steroids among body builders--frequency and attitudes.

    PubMed

    Lindström, M; Nilsson, A L; Katzman, P L; Janzon, L; Dymling, J F

    1990-06-01

    A total of 138 male body builders who regularly attended a gym participated anonymously in a study of the use of anabolic-androgenic steroids in relation to side-effects, blood pressure, body mass index (BMI; kg m-2), training frequency, social background, occupation, knowledge and attitudes to steroid use. Fifty-three of the 138 body builders had used anabolic-androgenic steroids for a median duration of 2 years. Steroid use was linked to a higher BMI and more frequent training. Seventy-five per cent (n = 18) of those attending body building for competition, and 24% (n = 11) of those attending to improve their sense of well-being, used anabolic-androgenic steroids. Of all body builders, 94% considered anabolic-androgenic steroids to be dangerous. Of the users, 81% experienced side-effects, but 74% still intended to continue steroid medication.

  20. Conditioning of sewage sludge by Fenton's reagent combined with skeleton builders.

    PubMed

    Liu, Huan; Yang, Jiakuan; Shi, Yafei; Li, Ye; He, Shu; Yang, Changzhu; Yao, Hong

    2012-06-01

    Physical conditioners, often known as skeleton builders, are commonly used to improve the dewaterability of sewage sludge. This study evaluated a novel joint usage of Fenton's reagent and skeleton builders, referred to as the F-S inorganic composite conditioner, focusing on their efficacies and the optimization of the major operational parameters. The results demonstrate that the F-S composite conditioner for conditioning sewage sludge is a viable alternative to conventional organic polymers, especially when ordinary Portland cement (OPC) and lime are used as the skeleton builders. Experimental investigations confirmed that Fenton reaction required sufficient time (80 min in this study) to degrade organics in the sludge. The optimal condition of this process was at pH=5, Fe(2+)=40 mg g(-1) (dry solids), H(2)O(2)=32 mg g(-1), OPC=300 mg g(-1) and lime=400 mg g(-1), in which the specific resistance to filtration reduction efficiency of 95% was achieved.

  1. Cellulose-builder: a toolkit for building crystalline structures of cellulose.

    PubMed

    Gomes, Thiago C F; Skaf, Munir S

    2012-05-30

    Cellulose-builder is a user-friendly program that builds crystalline structures of cellulose of different sizes and geometries. The program generates Cartesian coordinates for all atoms of the specified structure in the Protein Data Bank format, suitable for using as starting configurations in molecular dynamics simulations and other calculations. Crystalline structures of cellulose polymorphs Iα, Iβ, II, and III(I) of practically any size are readily constructed which includes parallelepipeds, plant cell wall cellulose elementary fibrils of any length, and monolayers. Periodic boundary conditions along the crystallographic directions are easily imposed. The program also generates atom connectivity file in PSF format, required by well-known simulation packages such as NAMD, CHARMM, and others. Cellulose-builder is based on the Bash programming language and should run on practically any Unix-like platform, demands very modest hardware, and is freely available for download from ftp://ftp.iqm.unicamp.br/pub/cellulose-builder.

  2. Widespread prevalence of cryptic Symbiodinium D in the key Caribbean reef builder, Orbicella annularis

    NASA Astrophysics Data System (ADS)

    Kennedy, Emma V.; Foster, Nicola L.; Mumby, Peter J.; Stevens, Jamie R.

    2015-06-01

    Symbiodinium D, a relatively rare clade of algal endosymbiont with a global distribution, has attracted interest as some of its sub-cladal types induce increased thermal tolerance and associated trade-offs, including reduced growth rate in its coral hosts. Members of Symbiodinium D are increasingly reported to comprise low-abundance `cryptic' (<10 %) proportions of mixed coral endosymbiont communities, with unknown ecological implications. Real-time PCR (RT-PCR) targeted to specific types is sufficiently sensitive to detect these background symbiont levels. In this study, RT-PCR was employed to screen 552 colonies of the key Caribbean reef builder Orbicella annularis sampled across a 5.4 million km2 range for the presence of cryptic Symbiodinium `D1' (i.e., the principal Caribbean ITS2 variants, D1 and D1-4). All but one out of 33 populations analysed were shown to host low abundances of Symbiodinium D1, with an average of >30 % of corals per site found to harbour the symbiont. When the same samples were analysed using the conventional screening technique, denaturing gradient gel electrophoresis, Symbiodinium D1 was only detected in 12 populations and appeared to be hosted by <12 % of colonies where present (in agreement with other reported low prevalence/absences in O. annularis). Cryptic Symbiodinium D1 showed a mainly uniform distribution across the wider Caribbean region, although significantly more Mesoamerican Barrier Reef corals hosted cryptic Symbiodinium D1 than might be expected by chance, possibly as a consequence of intense warming in the region in 1998. Widespread prevalence of thermally tolerant Symbiodinium in O. annularis may potentially reflect a capacity for the coral to temporarily respond to warming events through symbiont shuffling. However, association with reduced coral calcification means that the ubiquitous nature of Symbiodinium D1 in O. annularis populations is unlikely to prevent long-term declines in reef health, at a time when

  3. 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.

  4. Event-Triggered H∞ State Estimation for Delayed Stochastic Memristive Neural Networks With Missing Measurements: The Discrete Time Case.

    PubMed

    Liu, Hongjian; Wang, Zidong; Shen, Bo; Liu, Xiaohui

    2017-09-01

    In this paper, the event-triggered H∞ state estimation problem is investigated for a class of discrete-time stochastic memristive neural networks (DSMNNs) with time-varying delays and missing measurements. The DSMNN is subject to both the additive deterministic disturbances and the multiplicative stochastic noises. The missing measurements are governed by a sequence of random variables obeying the Bernoulli distribution. For the purpose of energy saving, an event-triggered communication scheme is used for DSMNNs to determine whether the measurement output is transmitted to the estimator or not. The problem addressed is to design an event-triggered H∞ estimator such that the dynamics of the estimation error is exponentially mean-square stable and the prespecified H∞ disturbance rejection attenuation level is also guaranteed. By utilizing a Lyapunov-Krasovskii functional and stochastic analysis techniques, sufficient conditions are derived to guarantee the existence of the desired estimator, and then, the estimator gains are characterized in terms of the solution to certain matrix inequalities. Finally, a numerical example is used to demonstrate the usefulness of the proposed event-triggered state estimation scheme.

  5. 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…

  6. 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…

  7. Interfaces for knowledge-base builders control knowledge and application-specific procedures

    SciTech Connect

    Hirsch, P.; Katke, W.; Meier, M.; Snyder, S.; Stillman, R.

    1986-01-01

    Expert System Environment/VM is an expert system shell-a general-purpose system for constructing and executing expert system applications. An application expert has both factual knowledge about an application and knowledge about how that factual knowledge should be organized and processed. In addition, many applications require application-dependent procedures to access databases or to do specialized processing. An important and novel part of Expert System Environment/VM is the technique used to allow the expert or knowledge-base builder to enter the control knowledge and to interface with application-dependent procedures. This paper discusses these high-level interfaces for the knowledge-base builder.

  8. DOE Zero Energy Ready Home Case Study: New Town Builders — The ArtiZEN Plan, Denver, CO

    SciTech Connect

    none,

    2014-09-01

    The Grand Winner in the Production Builder category of the 2014 Housing Innovation Awards, this builder plans to convert all of its product lines to DOE Zero Energy Ready Home construction by the end of 2015. This home achieves HERS 38 without photovoltaics (PV) and HERS -3 with 8.0 kW of PV.

  9. 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…

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

    PubMed Central

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

    2017-01-01

    This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications. PMID:28197065

  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. 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...

  13. New Whole-House Solutions Case Study: New Town Builders' Power of Zero Energy Center - Denver, Colorado

    SciTech Connect

    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. 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. This case study also contains customer and realtor testimonials related to the effectiveness of the Center in influencing homebuyers to purchase a zero energy home.

  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

    Wu, Chengkun; Schwartz, Jean-Marc; Brabant, Georg; Peng, Shao-Liang; Nenadic, Goran

    2015-01-01

    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. 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. 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.

  16. 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

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

    DTIC Science & Technology

    2012-12-01

    a Microhard radio to forward the ToAs to the mule-UAV. Two Procerus Unicorn UAVs were used with different payloads. The imaging- UAV was equipped...particularly useful when the regions overlap. We present results from a field test in Section IV and conclude in Section V. II. MULTIPLE EVENT LOCALIZATION...Path taken by mule-UAV during tests . The desired path was sent to autopilot via square waypoints. The sensors and communication regions are

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

    PubMed Central

    Murty, Vishnu P.; Adcock, R. Alison

    2014-01-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical–hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions—a potentially unique contribution of the hippocampus to reward learning. PMID:23529005

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

    PubMed

    Murty, Vishnu P; Adcock, R Alison

    2014-08-01

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

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

    PubMed

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

    2017-05-13

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

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

    DOE PAGES

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

    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

  2. Event-Based Variance-Constrained H∞ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

    PubMed

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

    2017-03-06

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

  3. Finite-Time State Estimation for Recurrent Delayed Neural Networks With Component-Based Event-Triggering Protocol.

    PubMed

    Wang, Licheng; Wang, Zidong; Wei, Guoliang; Alsaadi, Fuad E

    2017-02-06

    This paper deals with the event-based finite-time state estimation problem for a class of discrete-time stochastic neural networks with mixed discrete and distributed time delays. In order to mitigate the burden of data communication, a general component-based event-triggered transmission mechanism is proposed to determine whether the measurement output should be released to the estimator at certain time-point according to a specific triggering condition. A new concept of finite-time boundedness in the mean square is put forward to quantify the estimation performance by introducing a settling-like time function. The objective of the addressed problem is to construct an event-based state estimator to estimate the neuron states such that, in the presence of both mixed time delays and external noise disturbances, the dynamics of the estimation error is finite-time bounded in the mean square with a prescribed error upper bound. Sufficient conditions are established, via stochastic analysis techniques, to guarantee the desired estimation performance. By solving an optimization problem with some inequality constraints, the explicit expression of the estimator gain matrix is characterized to minimize the settling-like time. Finally, a numerical simulation example is exploited to demonstrate the effectiveness of the proposed estimator design scheme.

  4. SR proteins control a complex network of RNA-processing events.

    PubMed

    Bradley, Todd; Cook, Malcolm E; Blanchette, Marco

    2015-01-01

    SR proteins are a well-conserved class of RNA-binding proteins that are essential for regulation of splice-site selection, and have also been implicated as key regulators during other stages of RNA metabolism. For many SR proteins, the complexity of the RNA targets and specificity of RNA-binding location are poorly understood. It is also unclear if general rules governing SR protein alternative pre-mRNA splicing (AS) regulation uncovered for individual SR proteins on few model genes, apply to the activity of all SR proteins on endogenous targets. Using RNA-seq, we characterize the global AS regulation of the eight Drosophila SR protein family members. We find that a majority of AS events are regulated by multiple SR proteins, and that all SR proteins can promote exon inclusion, but also exon skipping. Most coregulated targets exhibit cooperative regulation, but some AS events are antagonistically regulated. Additionally, we found that SR protein levels can affect alternative promoter choices and polyadenylation site selection, as well as overall transcript levels. Cross-linking and immunoprecipitation coupled with high-throughput sequencing (iCLIP-seq), reveals that SR proteins bind a distinct and functionally diverse class of RNAs, which includes several classes of noncoding RNAs, uncovering possible novel functions of the SR protein family. Finally, we find that SR proteins exhibit positional RNA binding around regulated AS events. Therefore, regulation of AS by the SR proteins is the result of combinatorial regulation by multiple SR protein family members on most endogenous targets, and SR proteins have a broader role in integrating multiple layers of gene expression regulation. © 2014 Bradley et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  5. SR proteins control a complex network of RNA-processing events

    PubMed Central

    Bradley, Todd; Cook, Malcolm E.

    2015-01-01

    SR proteins are a well-conserved class of RNA-binding proteins that are essential for regulation of splice-site selection, and have also been implicated as key regulators during other stages of RNA metabolism. For many SR proteins, the complexity of the RNA targets and specificity of RNA-binding location are poorly understood. It is also unclear if general rules governing SR protein alternative pre-mRNA splicing (AS) regulation uncovered for individual SR proteins on few model genes, apply to the activity of all SR proteins on endogenous targets. Using RNA-seq, we characterize the global AS regulation of the eight Drosophila SR protein family members. We find that a majority of AS events are regulated by multiple SR proteins, and that all SR proteins can promote exon inclusion, but also exon skipping. Most coregulated targets exhibit cooperative regulation, but some AS events are antagonistically regulated. Additionally, we found that SR protein levels can affect alternative promoter choices and polyadenylation site selection, as well as overall transcript levels. Cross-linking and immunoprecipitation coupled with high-throughput sequencing (iCLIP-seq), reveals that SR proteins bind a distinct and functionally diverse class of RNAs, which includes several classes of noncoding RNAs, uncovering possible novel functions of the SR protein family. Finally, we find that SR proteins exhibit positional RNA binding around regulated AS events. Therefore, regulation of AS by the SR proteins is the result of combinatorial regulation by multiple SR protein family members on most endogenous targets, and SR proteins have a broader role in integrating multiple layers of gene expression regulation. PMID:25414008

  6. Builder 3 & 2. Naval Education and Training Command Rate Training Manual and Nonresident Career Course. Revised.

    ERIC Educational Resources Information Center

    Countryman, Gene L.

    This Rate Training Manual (Textbook) and Nonresident Career Course form a correspondence, self-study package to provide information related to tasks assigned to Builders Third and Second Class. Focus is on constructing, maintaining, and repairing wooden, concrete, and masonry structures, concrete pavement, and waterfront and underwater structures;…

  7. HVAC Design Strategy for a Hot-Humid Production Builder, Houston, Texas (Fact Sheet)

    SciTech Connect

    Not Available

    2014-03-01

    BSC worked directly with the David Weekley Homes - Houston division to redesign three floor plans in order to locate the HVAC system in conditioned space. The purpose of this project is to develop a cost effective design for moving the HVAC system into conditioned space. In addition, BSC conducted energy analysis to calculate the most economical strategy for increasing the energy performance of future production houses. This is in preparation for the upcoming code changes in 2015. The builder wishes to develop an upgrade package that will allow for a seamless transition to the new code mandate. The following research questions were addressed by this research project: 1. What is the most cost effective, best performing and most easily replicable method of locating ducts inside conditioned space for a hot-humid production home builder that constructs one and two story single family detached residences? 2. What is a cost effective and practical method of achieving 50% source energy savings vs. the 2006 International Energy Conservation Code for a hot-humid production builder? 3. How accurate are the pre-construction whole house cost estimates compared to confirmed post construction actual cost? BSC and the builder developed a duct design strategy that employs a system of dropped ceilings and attic coffers for moving the ductwork from the vented attic to conditioned space. The furnace has been moved to either a mechanical closet in the conditioned living space or a coffered space in the attic.

  8. Landscape Builder: software for the creation of initial landscapes for LANDIS from FIA data

    Treesearch

    William. Dijak

    2013-01-01

    I developed Landscape Builder to create spatially explicit landscapes as starting conditions for LANDIS Pro 7.0 and LANDIS II landscape forest simulation models from classified satellite imagery and Forest Inventory and Analysis (FIA) data collected over multiple years. LANDIS Pro and LANDIS II models project future landscapes by simulating tree growth, tree species...

  9. Captivate MenuBuilder: Creating an Online Tutorial for Teaching Software

    ERIC Educational Resources Information Center

    Yelinek, Kathryn; Tarnowski, Lynn; Hannon, Patricia; Oliver, Susan

    2008-01-01

    In this article, the authors, students in an instructional technology graduate course, describe a process to create an online tutorial for teaching software. They created the tutorial for a cyber school's use. Five tutorial modules were linked together through one menu screen using the MenuBuilder feature in the Adobe Captivate program. The…

  10. CHARMM-GUI HMMM Builder for Membrane Simulations with the Highly Mobile Membrane-Mimetic Model.

    PubMed

    Qi, Yifei; Cheng, Xi; Lee, Jumin; Vermaas, Josh V; Pogorelov, Taras V; Tajkhorshid, Emad; Park, Soohyung; Klauda, Jeffery B; Im, Wonpil

    2015-11-17

    Slow diffusion of the lipids in conventional all-atom simulations of membrane systems makes it difficult to sample large rearrangements of lipids and protein-lipid interactions. Recently, Tajkhorshid and co-workers developed the highly mobile membrane-mimetic (HMMM) model with accelerated lipid motion by replacing the lipid tails with small organic molecules. The HMMM model provides accelerated lipid diffusion by one to two orders of magnitude, and is particularly useful in studying membrane-protein associations. However, building an HMMM simulation system is not easy, as it requires sophisticated treatment of the lipid tails. In this study, we have developed CHARMM-GUI HMMM Builder (http://www.charmm-gui.org/input/hmmm) to provide users with ready-to-go input files for simulating HMMM membrane systems with/without proteins. Various lipid-only and protein-lipid systems are simulated to validate the qualities of the systems generated by HMMM Builder with focus on the basic properties and advantages of the HMMM model. HMMM Builder supports all lipid types available in CHARMM-GUI and also provides a module to convert back and forth between an HMMM membrane and a full-length membrane. We expect HMMM Builder to be a useful tool in studying membrane systems with enhanced lipid diffusion. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  11. Improving Water Management: Applying ModelBuilder to site water impoundments using AEM survey data

    SciTech Connect

    Sams, J.I.; Lipinski, B.A.; Harbert, W.P.; Ackman, T.E.

    2007-01-01

    ArcGIS ModelBuilder was used to create a GIS-based decision support model that incorporated digital elevation data and electromagnetic geophysical results gathered by helicopter to screen potential sites for water disposal impoundments produced from coal bed natural gas.

  12. DOE Zero Energy Ready Home Case Study: BPC Green Builders, New Fairfield, Connecticut

    SciTech Connect

    none,

    2013-09-01

    This LEED Platinum home was built on the site of a 60-year-old bungalow that was demolished. It boasts views of Candlewood Lake, a great deal of daylight, and projected annual energy savings of almost $3,000. This home was awarded a 2013 Housing Innovation Award in the custom builder category.

  13. Enacting Social Justice to Teach Social Justice: The Pedagogy of Bridge Builders

    ERIC Educational Resources Information Center

    Eifler, Karen E.; Kerssen-Griep, Jeff; Thacker, Peter

    2008-01-01

    This article describes a particular endeavor, the Bridge Builders Academic Mentoring Program (BAMP), a partnership between a school of education in a Catholic university in the Northwest and a community-based rites of passage program for adolescent African American males. The partnership exemplifies tenets of Catholic social teaching, in that it…

  14. Heating, Ventilation, and Air Conditioning Design Strategy for a Hot-Humid Production Builder

    SciTech Connect

    Kerrigan, P.

    2014-03-01

    BSC worked directly with the David Weekley Homes - Houston division to redesign three floor plans in order to locate the HVAC system in conditioned space. The purpose of this project is to develop a cost effective design for moving the HVAC system into conditioned space. In addition, BSC conducted energy analysis to calculate the most economical strategy for increasing the energy performance of future production houses. This is in preparation for the upcoming code changes in 2015. The builder wishes to develop an upgrade package that will allow for a seamless transition to the new code mandate. The following research questions were addressed by this research project: 1. What is the most cost effective, best performing and most easily replicable method of locating ducts inside conditioned space for a hot-humid production home builder that constructs one and two story single family detached residences? 2. What is a cost effective and practical method of achieving 50% source energy savings vs. the 2006 International Energy Conservation Code for a hot-humid production builder? 3. How accurate are the pre-construction whole house cost estimates compared to confirmed post construction actual cost? BSC and the builder developed a duct design strategy that employs a system of dropped ceilings and attic coffers for moving the ductwork from the vented attic to conditioned space. The furnace has been moved to either a mechanical closet in the conditioned living space or a coffered space in the attic.

  15. Family Builders Approach: Enhancing the Well-Being of Children through Family-School Partnerships.

    ERIC Educational Resources Information Center

    Sar, Bibhuti K.; Wulff, Daniel P.

    2003-01-01

    Article describes the inception, development, and implementation of the Family Builders model. This model addresses children's problematic behaviors and promotes their social and academic competencies through a deliberate process of stimulating and nurturing school-based collaborations between families and schools. (Contains 14 references.)

  16. Initial Behavior Outcomes for the PeaceBuilders Universal School-Based Violence Prevention Program.

    ERIC Educational Resources Information Center

    Flannery, Daniel J.; And Others

    2003-01-01

    Assigned elementary schools to either immediate postbaseline intervention (PBI) with PeaceBuilders, a school-based violence prevention program, or to intervention 1 year later (PBD). Found significant gains in social competence for kindergarten through second-graders in Year 1, in peace-building behavior in Grades K to 5, and reduced aggression in…

  17. A NOVEL SEARCH BUILDER TO EXPEDITE SEARCH STRATEGIES FOR SYSTEMATIC REVIEWS.

    PubMed

    Kamdar, Biren B; Shah, Pooja A; Sakamuri, Sruthi; Kamdar, Bharat S; Oh, Jiwon

    2015-01-01

    Developing a search strategy for use in a systematic review is a time-consuming process requiring construction of detailed search strings using complicated syntax, followed by iterative fine-tuning and trial-and-error testing of these strings in online biomedical search engines. Building upon limitations of existing online-only search builders, a user-friendly computer-based tool was created to expedite search strategy development as part of production of a systematic review. Search Builder 1.0 is a Microsoft Excel®-based tool that automatically assembles search strategy text strings for PubMed (www.pubmed.com) and Embase (www.embase.com), based on a list of user-defined search terms and preferences. With the click of a button, Search Builder 1.0 automatically populates the syntax needed for functional search strings, and copies the string to the clipboard for pasting into Pubmed or Embase. The offline file-based interface of Search Builder 1.0 also allows for searches to be easily shared and saved for future reference. This novel, user-friendly tool can save considerable time and streamline a cumbersome step in the systematic review process.

  18. Implementing HCI Design Patterns as Widget/Templates for GUI Builders

    DTIC Science & Technology

    2008-03-01

    our research has uncovered a potential new method for pattern implementation, based on the Glade User Interface Builder. Glade seems to have the...1] Gamma, Erich, Richard Helm, Ralph Johnson, and John Vlissides. Design Patterns: Elements of Reusable Object-Oriented Software [2] Alexander

  19. 77 FR 35708 - Notice of Submission of Proposed Information Collection to OMB; Builder's Certification of Plans...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-14

    ... approved. HUD requires the builder to complete the certification (form HUD-92541) noting adverse site... to complete the certification (form HUD-92541) noting adverse site/location factor(s) of the property... URBAN DEVELOPMENT Notice of Submission of Proposed Information Collection to OMB;...

  20. BioBuilder as a database development and functional annotation platform for proteins

    PubMed Central

    Navarro, J Daniel; Talreja, Naveen; Peri, Suraj; Vrushabendra, BM; Rashmi, BP; Padma, N; Surendranath, Vineeth; Jonnalagadda, Chandra Kiran; Kousthub, PS; Deshpande, Nandan; Shanker, K; Pandey, Akhilesh

    2004-01-01

    Background The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. Results BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database , a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. Conclusions As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL. PMID:15099404

  1. Three Adapted Science Skill Builders for Junior and Senior High School Orthopaedically Handicapped Students.

    ERIC Educational Resources Information Center

    Cardullias, Peter J.; And Others

    The study was designed to determine how standard science skill builder activities can be modified or adapted for use by orthopedically handicapped students. Nine secondary level science experiments were selected for initial review and from these, three were selected for adaptation--use of the microscope, use of graduated cylinders, and use of the…

  2. 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.

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

    DOE PAGES

    Pilger, Christoph; Ceranna, Lars; Ross, J. Ole; ...

    2015-03-18

    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 individualmore » 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. As a result, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.« less

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

    SciTech Connect

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

    2015-03-18

    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. As a result, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.

  5. Body composition estimations by BIA versus anthropometric equations in body builders and other power athletes.

    PubMed

    Huygens, W; Claessens, A L; Thomis, M; Loos, R; Van Langendonck, L; Peeters, M; Philippaerts, R; Meynaerts, E; Vlietinck, R; Beunen, G

    2002-03-01

    Two main questions are stated: 1) are BIA and anthropometric equations accurate in estimating body composition in male power athletes and more specifically in body builders and 2) is there a difference in body composition when body builders are compared to weight and power lifters? this is a descriptive, comparative study on a selected sample of power athletes. 49 Belgian elite and sub-top male power athletes (34 body builders and 15 weight and power lifters) were included in this sample. More than 70% was in preparation of competition at time of data collection. an extended set of anthropometric measures was taken. Body composition was estimated by BIA (Bioelectrical Impedance Analysis) and by regression equations of skinfolds. Somatotype and muscle+bone areas were calculated. Factor analysis on all anthropometric measures was carried out to determine the body structure of the athletes. Compared to external visual criteria, the equations of Durnin and Womersley and Lohman (skinfolds) and the Guo-equation (BIA) were the only equations that could accurately estimate the body composition for this specific group of athletes. However, the sum of skinfolds attains the most accurate estimate of subcutaneous fatness. Body builders have significantly (p<0.01) larger arm and thigh circumferences and are more mesomorfic than the other power athletes (5.9 vs 3.8). This study shows that to estimate body composition in extreme power athletes BIA is not as accurate as compared to anthropometric equations. Moreover, the sum of a larger set of skinfolds is preferred to anthropometric prediction equations. In addition, body builders are more muscular and leaner than other power athletes.

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

    USGS Publications Warehouse

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

    2013-01-01

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

  7. A Statistical Discrimination Experiment for Eurasian Events Using a Twenty-Seven-Station Network

    DTIC Science & Technology

    1980-07-08

    RtGlON EV’INT 2 ANMO ANiO ATAK BFAK 3ÜC0 CHTO CNAK CTAO GJMO HNME IP7 KAAO KONO KSRS If 147 Hi o.ao 0.6 0 0.20 o.ao 0.30 0. 20 0. 30...10 0.90 ANTO 0. 30 ATAK UFAK o.ao 0.70 0.30 o.ao I10CÜ CM TO 0. 20 0. 3 0 CNAK o.ao o.ao o.ao 0. 30 CTAO o.ao G’lMO HNME...0.375 0.050 o.aoo 0.0 0.200 0.001 0.267 0.058 0. 150 0.071 0.550 0.35a REGION EVENT a ANMO ANTO ATAK DFAK nnco nrro CNAK CTAO GUMO

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

    NASA Astrophysics Data System (ADS)

    Chatrchyan, S.; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Aguilo, E.; Bergauer, T.; Dragicevic, M.; Erö, J.; Fabjan, C.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Pernicka, M.; Rabady, D.; Rahbaran, B.; Rohringer, C.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Taurok, A.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Luyckx, S.; Mucibello, L.; Ochesanu, S.; Roland, B.; Rougny, R.; Selvaggi, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Gonzalez Suarez, R.; Kalogeropoulos, A.; Maes, M.; Olbrechts, A.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Clerbaux, B.; De Lentdecker, G.; Dero, V.; Gay, A. P. R.; Hreus, T.; Léonard, A.; Marage, P. E.; Mohammadi, A.; Reis, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Adler, V.; Beernaert, K.; Cimmino, A.; Costantini, S.; Garcia, G.; Grunewald, M.; Klein, B.; Lellouch, J.; Marinov, A.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Walsh, S.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Bruno, G.; Castello, R.; Ceard, L.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Lemaitre, V.; Liao, J.; Militaru, O.; Nuttens, C.; Pagano, D.; Pin, A.; Piotrzkowski, K.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Alves, G. A.; Correa Martins Junior, M.; Martins, T.; Pol, M. E.; Souza, M. H. G.; Aldá Júnior, W. L.; Carvalho, W.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Malek, M.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Soares Jorge, L.; Sznajder, A.; Vilela Pereira, A.; Anjos, T. S.; Bernardes, C. A.; Dias, F. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Lagana, C.; Marinho, F.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Genchev, V.; Iaydjiev, P.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Tcholakov, V.; Trayanov, R.; Vutova, M.; Dimitrov, A.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Jiang, C. H.; Liang, D.; Liang, S.; Meng, X.; Tao, J.; Wang, J.; Wang, X.; Wang, Z.; Xiao, H.; Xu, M.; Zang, J.; Zhang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Guo, Y.; Li, W.; Liu, S.; Mao, Y.; Qian, S. J.; Teng, H.; Wang, D.; Zhang, L.; Zou, W.; Avila, C.; Gomez, J. P.; Gomez Moreno, B.; Osorio Oliveros, A. F.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Plestina, R.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Duric, S.; Kadija, K.; Luetic, J.; Mekterovic, D.; Morovic, S.; Attikis, A.; Galanti, M.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Finger, M.; Finger, M., Jr.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Mahmoud, M. A.; Mahrous, A.; Radi, A.; Kadastik, M.; Müntel, M.; Murumaa, M.; Raidal, M.; Rebane, L.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Heikkinen, A.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Ungaro, D.; Wendland, L.; Banzuzi, K.; Karjalainen, A.; Korpela, A.; Tuuva, T.; Besancon, M.; Choudhury, S.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Millischer, L.; Nayak, A.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Benhabib, L.; Bianchini, L.; Bluj, M.; Busson, P.; Charlot, C.; Daci, N.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Florent, A.; Granier de Cassagnac, R.; Haguenauer, M.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Sabes, D.; Salerno, R.; Sirois, Y.; Veelken, C.; Zabi, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Bodin, D.; Brom, J.-M.; Cardaci, M.; Chabert, E. C.; Collard, C.; Conte, E.; Drouhin, F.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Juillot, P.; Le Bihan, A.-C.; Van Hove, P.; Fassi, F.; Mercier, D.; Beauceron, S.; Beaupere, N.; Bondu, O.; Boudoul, G.; Brochet, S.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Sgandurra, L.; Sordini, V.; Tschudi, Y.; Verdier, P.; Viret, S.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Calpas, B.; Edelhoff, M.; Feld, L.; Heracleous, N.; Hindrichs, O.; Jussen, R.; Klein, K.

    2013-04-01

    In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from a standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4.98fb-1 of proton-proton collisions at the center-of-mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (E̸T>40GeV) and total hadronic transverse energy (HT>120GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observations, yielding limits in the context of the constrained minimal supersymmetric standard model and on a set of simplified models.

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

    PubMed

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

    2010-01-01

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

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

    PubMed Central

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

    2010-01-01

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

  11. Structuring the Future: Anticipated Life Events, Peer Networks, and Adolescent Sexual Behavior

    PubMed Central

    Soller, Brian; Haynie, Dana L.

    2013-01-01

    While prior research has established associations between individual expectations of future events and risk behavior among adolescents, the potential effects of peers’ future perceptions on risk-taking have been overlooked. We extend prior research by testing whether peers’ anticipation of college completion is associated with adolescent sexual risk-taking. We also examine whether adolescents’ perceptions of the negative consequences of pregnancy and idealized romantic relationship scripts mediate the association between peers’ anticipation of college completion and sexual risk-taking. Results from multivariate regression models with data from the National Longitudinal Study of Adolescent Health (Add Health) indicate peers’ anticipation of college completion is negatively associated with a composite measure of sexual risk-taking and positively associated with the odds of abstaining from sexual intercourse and only engaging in intercourse with a romantic partner (compared to having intercourse with a non-romantic partner). In addition, perceptions of the negative consequences of pregnancy and sexualized relationship scripts appear to mediate a large portion of the association between peers’ anticipation of future success and sexual risk-taking and the likelihood of abstaining (but not engaging in romantic-only intercourse). Results from our study underscore the importance of peers in shaping adolescent sexual behavior. PMID:24223438

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

    NASA Astrophysics Data System (ADS)

    Schmidt, F.; Liu, S.

    2016-12-01

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

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

    PubMed

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

    2016-07-07

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

  14. Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems.

    PubMed

    Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

    2016-01-01

    This paper presents a novel adaptive neural network (NN) control of single-input and single-output uncertain nonlinear discrete-time systems under event sampled NN inputs. In this control scheme, the feedback signals are transmitted, and the NN weights are tuned in an aperiodic manner at the event sampled instants. After reviewing the NN approximation property with event sampled inputs, an adaptive state estimator (SE), consisting of linearly parameterized NNs, is utilized to approximate the unknown system dynamics in an event sampled context. The SE is viewed as a model and its approximated dynamics and the state vector, during any two events, are utilized for the event-triggered controller design. An adaptive event-trigger condition is derived by using both the estimated NN weights and a dead-zone operator to determine the event sampling instants. This condition both facilitates the NN approximation and reduces the transmission of feedback signals. The ultimate boundedness of both the NN weight estimation error and the system state vector is demonstrated through the Lyapunov approach. As expected, during an initial online learning phase, events are observed more frequently. Over time with the convergence of the NN weights, the inter-event times increase, thereby lowering the number of triggered events. These claims are illustrated through the simulation results.

  15. Implementation of GlycanBuilder to draw a wide variety of ambiguous glycans.

    PubMed

    Tsuchiya, Shinichiro; Aoki, Nobuyuki P; Shinmachi, Daisuke; Matsubara, Masaaki; Yamada, Issaku; Aoki-Kinoshita, Kiyoko F; Narimatsu, Hisashi

    2017-06-05

    GlyTouCan version 1.0 was released in 2015 as the international glycan structure repository, and a new sequence format called WURCS (Web3 Unique Representation of Carbohydrate Structures) was proposed during the early stages of the GlyTouCan project. GlyTouCan uses WURCS as its base representation for glycans because existing formats were insufficient in their flexibility to represent any and all glycans universally. Therefore, in order to obtain WURCS strings for existing or new glycan structures, conversion tools or glycan structure editors that can export WURCS became necessary. GlycanBuilder was an obvious choice to extend due to its wide usage by the community. However, GlycanBuilder was limited because it was originally developed to support mammalian glycans. It also did not support the newly proposed monosaccharide symbol standard called Symbol Nomenclature for Glycans (SNFG). Therefore in this work, we implemented a new version of GlycanBuilder to greatly increase its usability. The glycan rendering system was refactored so that cyclic glycans, nested repeating units, monosaccharide compositions and cross-linked glycan structures can be represented. Both import and export utilities for WURCS were also implemented and SNFG symbols were incorporated to allow glycans to be exported as graphics using the latest glycan symbol nomenclature. This new version of GlycanBuilder called "GlycanBuilder2", is able to support a wide variety of ambiguous glycans, including structures containing monosaccharides from bacteria and plants. These glycans can also be displayed using the new SNFG symbols. This tool can aid researchers in communicating about the complex, diverse, and ambiguous structures of glycans more rapidly. Moreover, the new GlycanBuilder can now easily output WURCS sequences from glycans drawn on the canvas. Most importantly, because GlyTouCan employs WURCS as the basic format for registration and searching of glycan information, a wider variety of glycans

  16. HIV-1 Subtype F1 Epidemiological Networks among Italian Heterosexual Males Are Associated with Introduction Events from South America

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2012-10-01

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

  18. Heating, Ventilation, and Air Conditioning Design Strategy for a Hot-Humid Production Builder

    SciTech Connect

    Kerrigan, P.

    2014-03-01

    Building Science Corporation (BSC) worked directly with the David Weekley Homes - Houston division to develop a cost-effective design for moving the HVAC system into conditioned space. In addition, BSC conducted energy analysis to calculate the most economical strategy for increasing the energy performance of future production houses in preparation for the upcoming code changes in 2015. This research project addressed the following questions: 1. What is the most cost effective, best performing and most easily replicable method of locating ducts inside conditioned space for a hot-humid production home builder that constructs one and two story single family detached residences? 2. What is a cost effective and practical method of achieving 50% source energy savings vs. the 2006 International Energy Conservation Code for a hot-humid production builder? 3. How accurate are the pre-construction whole house cost estimates compared to confirmed post construction actual cost?

  19. VQone MATLAB toolbox: A graphical experiment builder for image and video quality evaluations: VQone MATLAB toolbox.

    PubMed

    Nuutinen, Mikko; Virtanen, Toni; Rummukainen, Olli; Häkkinen, Jukka

    2016-03-01

    This article presents VQone, a graphical experiment builder, written as a MATLAB toolbox, developed for image and video quality ratings. VQone contains the main elements needed for the subjective image and video quality rating process. This includes building and conducting experiments and data analysis. All functions can be controlled through graphical user interfaces. The experiment builder includes many standardized image and video quality rating methods. Moreover, it enables the creation of new methods or modified versions from standard methods. VQone is distributed free of charge under the terms of the GNU general public license and allows code modifications to be made so that the program's functions can be adjusted according to a user's requirements. VQone is available for download from the project page (http://www.helsinki.fi/psychology/groups/visualcognition/).

  20. Experimental evidence of the synergistic effects of warming and invasive algae on a temperate reef-builder coral.

    PubMed

    Kersting, Diego K; Cebrian, Emma; Casado, Clara; Teixidó, Núria; Garrabou, Joaquim; Linares, Cristina

    2015-12-22

    In the current global climate change scenario, stressors overlap in space and time, and knowledge on the effects of their interaction is highly needed to understand and predict the response and resilience of organisms. Corals, among many other benthic organisms, are affected by an increasing number of global change-related stressors including warming and invasive species. In this study, the cumulative effects between warming and invasive algae were experimentally assessed on the temperate reef-builder coral Cladocora caespitosa. We first investigated the potential local adaptation to thermal stress in two distant populations subjected to contrasting thermal and necrosis histories. No significant differences were found between populations. Colonies from both populations suffered no necrosis after long-term exposure to temperatures up to 29 °C. Second, we tested the effects of the interaction of both warming and the presence of invasive algae. The combined exposure triggered critical synergistic effects on photosynthetic efficiency and tissue necrosis. At the end of the experiment, over 90% of the colonies subjected to warming and invasive algae showed signs of necrosis. The results are of particular concern when considering the predicted increase of extreme climatic events and the spread of invasive species in the Mediterranean and other seas in the future.

  1. Development of a beam builder for automatic fabrication of large composite space structures

    NASA Technical Reports Server (NTRS)

    Bodle, J. G.

    1979-01-01

    The composite material beam builder which will produce triangular beams from pre-consolidated graphite/glass/thermoplastic composite material through automated mechanical processes is presented, side member storage, feed and positioning, ultrasonic welding, and beam cutoff are formed. Each process lends itself to modular subsystem development. Initial development is concentrated on the key processes for roll forming and ultrasonic welding composite thermoplastic materials. The construction and test of an experimental roll forming machine and ultrasonic welding process control techniques are described.

  2. OpenSesame: an open-source, graphical experiment builder for the social sciences.

    PubMed

    Mathôt, Sebastiaan; Schreij, Daniel; Theeuwes, Jan

    2012-06-01

    In the present article, we introduce OpenSesame, a graphical experiment builder for the social sciences. OpenSesame is free, open-source, and cross-platform. It features a comprehensive and intuitive graphical user interface and supports Python scripting for complex tasks. Additional functionality, such as support for eyetrackers, input devices, and video playback, is available through plug-ins. OpenSesame can be used in combination with existing software for creating experiments.

  3. DOE Zero Energy Ready Home Case Study: BPC Green Builders — Trolle Residence, Danbury, CT

    SciTech Connect

    none,

    2014-09-01

    The builder of this 1,650-ft2 cabin won a Custom Home honor in the 2014 Housing Innovations Awards. The home meets Passive House Standards with 5.5-in. of foil-faced polysiocyanurate foam boards lining the outside walls, R-55 of rigid EPS foam under the slab, R-86 of blown cellulose in the attic, triple-pane windows, and a single ductless heat pump to heat and cool the entire home.

  4. CHARMM-GUI micelle builder for pure/mixed micelle and protein/micelle complex systems.

    PubMed

    Cheng, Xi; Jo, Sunhwan; Lee, Hui Sun; Klauda, Jeffery B; Im, Wonpil

    2013-08-26

    Micelle Builder in CHARMM-GUI, http://www.charmm-gui.org/input/micelle , is a web-based graphical user interface to build pure/mixed micelle and protein/micelle complex systems for molecular dynamics (MD) simulation. The robustness of Micelle Builder is tested by simulating four detergent-only homogeneous micelles of DHPC (dihexanoylphosphatidylcholine), DPC (dodecylphosphocholine), TPC (tetradecylphosphocholine), and SDS (sodium dodecyl sulfate) and comparing the calculated micelle properties with experiments and previous simulations. As a representative protein/micelle model, Pf1 coat protein is modeled and simulated in DHPC micelles with three different numbers of DHPC molecules. While the number of DHPC molecules in direct contact with Pf1 protein converges during the simulation, distinct behavior and geometry of micelles lead to different protein conformations in comparison to that in bilayers. It is our hope that CHARMM-GUI Micelle Builder can be used for simulation studies of various protein/micelle systems to better understand the protein structure and dynamics in micelles as well as distribution of detergents and their dynamics around proteins.

  5. CHARMM-GUI PACE CG Builder for solution, micelle, and bilayer coarse-grained simulations.

    PubMed

    Qi, Yifei; Cheng, Xi; Han, Wei; Jo, Sunhwan; Schulten, Klaus; Im, Wonpil

    2014-03-24

    Coarse-grained (CG) and multiscale simulations are widely used to study large biological systems. However, preparing the simulation system is time-consuming when the system has multiple components, because each component must be arranged carefully as in protein/micelle or protein/bilayer systems. We have developed CHARMM-GUI PACE CG Builder for building solution, micelle, and bilayer systems using the PACE force field, a united-atom (UA) model for proteins, and the Martini CG force field for water, ions, and lipids. The robustness of PACE CG Builder is validated by simulations of various systems in solution (α3D, fibronectin, and lysozyme), micelles (Pf1, DAP12-NKG2C, OmpA, and DHPC-only micelle), and bilayers (GpA, OmpA, VDAC, MscL, OmpF, and lipid-only bilayers for six lipids). The micelle's radius of gyration, the bilayer thickness, and the per-lipid area in bilayers are comparable to the values from previous all-atom and CG simulations. Most tested proteins have root-mean squared deviations of less than 3 Å. We expect PACE CG Builder to be a useful tool for modeling/refining large, complex biological systems at the mixed UA/CG level.

  6. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

    NASA Astrophysics Data System (ADS)

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-01

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  7. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems.

    PubMed

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-12

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  8. Time-Resolved Human Kinome RNAi Screen Identifies a Network Regulating Mitotic-Events as Early Regulators of Cell Proliferation

    PubMed Central

    Bechtel, Stephanie; Bender, Christian; Keklikoglou, Ioanna; Schmidt, Christian; Irsigler, Anja; Ernst, Ute; Sahin, Özgür; Wiemann, Stefan; Tschulena, Ulrich

    2011-01-01

    Analysis of biological processes is frequently performed with the help of phenotypic assays where data is mostly acquired in single end-point analysis. Alternative phenotypic profiling techniques are desired where time-series information is essential to the biological question, for instance to differentiate early and late regulators of cell proliferation in loss-of-function studies. So far there is no study addressing this question despite of high unmet interests, mostly due to the limitation of conventional end-point assaying technologies. We present the first human kinome screen with a real-time cell analysis system (RTCA) to capture dynamic RNAi phenotypes, employing time-resolved monitoring of cell proliferation via electrical impedance. RTCA allowed us to investigate the dynamics of phenotypes of cell proliferation instead of using conventional end-point analysis. By introducing data transformation with first-order derivative, i.e. the cell-index growth rate, we demonstrate this system suitable for high-throughput screenings (HTS). The screen validated previously identified inhibitor genes and, additionally, identified activators of cell proliferation. With the information of time kinetics available, we could establish a network of mitotic-event related genes to be among the first displaying inhibiting effects after RNAi knockdown. The time-resolved screen captured kinetics of cell proliferation caused by RNAi targeting human kinome, serving as a resource for researchers. Our work establishes RTCA technology as a novel robust tool with biological and pharmacological relevance amenable for high-throughput screening. PMID:21765947

  9. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

    PubMed Central

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-01

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems. PMID:28079187

  10. Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks.

    PubMed

    Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

    2017-04-01

    Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites' operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95 . 1 % of the cases.

  11. Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks

    PubMed Central

    Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

    2017-01-01

    Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites’ operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95.1% of the cases. PMID:28368319

  12. Neuroticism, social network, stressful life events: association with mood disorders, depressive symptoms and suicidal ideation in a community sample of women.

    PubMed

    Mandelli, Laura; Nearchou, Finiki A; Vaiopoulos, Chrysostomos; Stefanis, Costas N; Vitoratou, Silia; Serretti, Alessandro; Stefanis, Nicholas C

    2015-03-30

    According to the stress-diathesis hypothesis, depression and suicidal behavior may be precipitated by psychosocial stressors in vulnerable individuals. However, risk factors for mental health are often gender-specific. In the present study, we evaluated common risk factors for female depression in association with depressive symptoms and suicidal ideation in a community sample of women. The sample was composed by 415 women evaluated for mood disorders (MDs), depressive symptoms and suicidal ideation by structured interviews and the Beck depression inventory II (BDI II). All women also filled in the Eysenck personality questionnaire to evaluate neuroticism and were interviewed for social contact frequency and stressful life events (SLEs). In the whole sample, 19% of the women satisfied criteria for MD and suicidal ideation was reported by 12% of the women. Though stressful life events, especially personal and interpersonal problems, and poor social network were associated with all the outcome variables (mood disorder, depressive symptomatology and suicidal ideation), neuroticism survived to all multivariate analyses. Social network, together with neuroticism, also showed strong association with depressive severity, independently from current depressive state. Though we were unable to compare women and men, data obtained from the present study suggest that in women neurotic traits are strongly related to depression and suicidal ideation, and potentially mediate reporting of stressful life events and impaired social network. Independently from a current diagnosis of depression, impaired social network increases depressive symptoms in the women. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  13. The Strategic Paradox of Social Networks

    DTIC Science & Technology

    2011-03-18

    cause long-lasting effects. For example, a recent Career Builder survey found the number of civilian employers who used social networking sites as...Service members discussing political subjects on social networking sites can quickly attract negative attention. In March 2010, Marine Corps Sergeant...on social networking sites . In March 2010, stories surfaced reporting the Israeli army canceled a mission after a soldier “disclosed the name of the

  14. Impaired target detection in schizophrenia and the ventral attentional network: Findings from a joint event-related potential–functional MRI analysis

    PubMed Central

    Wynn, Jonathan K.; Jimenez, Amy M.; Roach, Brian J.; Korb, Alexander; Lee, Junghee; Horan, William P.; Ford, Judith M.; Green, Michael F.

    2015-01-01

    Schizophrenia patients have abnormal neural responses to salient, infrequent events. We integrated event-related potentials (ERP) and fMRI to examine the contributions of the ventral (salience) and dorsal (sustained) attention networks to this dysfunctional neural activation. Twenty-one schizophrenia patients and 22 healthy controls were assessed in separate sessions with ERP and fMRI during a visual oddball task. Visual P100, N100, and P300 ERP waveforms and fMRI activation were assessed. A joint independent components analysis (jICA) on the ERP and fMRI data were conducted. Patients exhibited reduced P300, but not P100 or N100, amplitudes to targets and reduced fMRI neural activation in both dorsal and ventral attentional networks compared with controls. However, the jICA revealed that the P300 was linked specifically to activation in the ventral (salience) network, including anterior cingulate, anterior insula, and temporal parietal junction, with patients exhibiting significantly lower activation. The P100 and N100 were linked to activation in the dorsal (sustained) network, with no group differences in level of activation. This joint analysis approach revealed the nature of target detection deficits that were not discernable by either imaging methodology alone, highlighting the utility of a multimodal fMRI and ERP approach to understand attentional network deficits in schizophrenia. PMID:26448909

  15. Impaired target detection in schizophrenia and the ventral attentional network: Findings from a joint event-related potential-functional MRI analysis.

    PubMed

    Wynn, Jonathan K; Jimenez, Amy M; Roach, Brian J; Korb, Alexander; Lee, Junghee; Horan, William P; Ford, Judith M; Green, Michael F

    2015-01-01

    Schizophrenia patients have abnormal neural responses to salient, infrequent events. We integrated event-related potentials (ERP) and fMRI to examine the contributions of the ventral (salience) and dorsal (sustained) attention networks to this dysfunctional neural activation. Twenty-one schizophrenia patients and 22 healthy controls were assessed in separate sessions with ERP and fMRI during a visual oddball task. Visual P100, N100, and P300 ERP waveforms and fMRI activation were assessed. A joint independent components analysis (jICA) on the ERP and fMRI data were conducted. Patients exhibited reduced P300, but not P100 or N100, amplitudes to targets and reduced fMRI neural activation in both dorsal and ventral attentional networks compared with controls. However, the jICA revealed that the P300 was linked specifically to activation in the ventral (salience) network, including anterior cingulate, anterior insula, and temporal parietal junction, with patients exhibiting significantly lower activation. The P100 and N100 were linked to activation in the dorsal (sustained) network, with no group differences in level of activation. This joint analysis approach revealed the nature of target detection deficits that were not discernable by either imaging methodology alone, highlighting the utility of a multimodal fMRI and ERP approach to understand attentional network deficits in schizophrenia.

  16. Development of the BUILDER Engineered Management System for Building Maintenance: Initial Decision and Concept Report

    DTIC Science & Technology

    1990-07-01

    Laboratory AD- A225 950 Development of the BUILDER Engineered Management System for Building Maintenance: Initial Decision and Concept Report DT C by ELECTE...identification of the MDR value and the subcomponent condition ratings, the computer assigns a building component Condition Rating ( CR ) based on the...8217 CR = 3 F2.2 WALLS $ 0 CR = 4 F2.3 PAINTING S 9000 CR = 3 F2.4 DOORS/HARDWARE S 1000 CR = 3 F2.5 WINDOWS $ 0 CR = 4 F2.6 ROOF S 100000 CR = 2 F2.7 SITE

  17. The organic builder: a public experiment in artificial chemistries and self-replication.

    PubMed

    Hutton, Tim J

    2009-01-01

    We describe some results submitted by users of the Organic Builder, a Java applet where the rules of an artificial chemistry can be chosen in order to achieve a desired behavior. Though it was initially intended as a set of challenges to be tackled as a game, the users experimented with the system far beyond this and discovered several novel forms of self-replicators. When searching for a system with certain properties such asself-replication, making the system accessible to the public through a Web site is an unusual but effective way of making scientific discoveries, credit for which must go to the users themselves for their tireless experimentation and innovation.

  18. Building America Solution Center Shows Builders How to Save Materials Costs While Saving Energy

    SciTech Connect

    Gilbride, Theresa L.

    2015-06-15

    This short article was prepared for the U.S. Department of Energy's Building America Update newsletter. The article identifies energy and cost-saving benefits of using advanced framing techniques in new construction identified by research teams working with the DOE's Building America program. The article also provides links to guides in the Building America Solution Center that give how-to instructions for builders who want to implement advanced framing construction. The newsletter is issued monthly and can be accessed at http://energy.gov/eere/buildings/building-america-update-newsletter

  19. New Whole-House Solutions Case Study: A Production Builder's Passive House - Denver, Colorado

    SciTech Connect

    2015-05-01

    Brookfield Home’s first project is in a community called Midtown in Denver, Colorado, in which the builder took on the challenge of increased energy efficiency by creating a Passive House (PH)-certified model home. Brookfield worked with the U.S. Department of Energy’s Building America research team IBACOS to create the home, evaluate advanced building technologies, and use the home as a marketing tool for potential homebuyers. Brookfield also worked with KGA studio architects to create a new floor plan that would be constructed to the PH standard as an upgrade option.

  20. PBIT: pipeline builder for identification of drug targets for infectious diseases.

    PubMed

    Shende, Gauri; Haldankar, Harshala; Barai, Ram Shankar; Bharmal, Mohammed Husain; Shetty, Vinit; Idicula-Thomas, Susan

    2016-12-30

    PBIT (Pipeline Builder for Identification of drug Targets) is an online webserver that has been developed for screening of microbial proteomes for critical features of human drug targets such as being non-homologous to human proteome as well as the human gut microbiota, essential for the pathogen's survival, participation in pathogen-specific pathways etc. The tool has been validated by analyzing 57 putative targets of Candida albicans documented in literature. PBIT integrates various in silico approaches known for drug target identification and will facilitate high-throughput prediction of drug targets for infectious diseases, including multi-pathogenic infections.

  1. Regional seismic event identification and improved locations with small arrays and networks. Final report, 7 May 1993-30 September 1995

    SciTech Connect

    Vernon, F.L.; Minster, J.B.; Orcutt, J.A.

    1995-09-20

    This final report contains a summary of our work on the use of seismic networks and arrays to improve locations and identify small seismic event. We have developed techniques to migrate 3-component array records of local, regional and teleseismic wavetrains to directly image buried two- and three-dimensional heterogeneities (e.g. layer irregularities, volumetric heterogeneities) in the vicinity of the array. We have developed a technique to empirically characterize local and regional seismic code by binning and stacking network recordings of dense aftershock sequences. The principle motivation for this work was to look for robust coda phases dependent on source depth. We have extended our ripple-fired event discriminant (based on the time-independence of coda produced by ripple firing) by looking for an independence of the coda from the recording direction (also indicative of ripple-firing).

  2. Advanced Decentralized Water/Energy Network Design for Sustainable Infrastructure presentation at the 2012 National Association of Home Builders (NAHB) International Builders'Show

    EPA Science Inventory

    A university/industry panel will report on the progress and findings of a fivesteve-year project funded by the US Environmental Protection Agency. The project's end product will be a Web-based, 3D computer-simulated residential environment with a decision support system to assist...

  3. Advanced Decentralized Water/Energy Network Design for Sustainable Infrastructure presentation at the 2012 National Association of Home Builders (NAHB) International Builders'Show

    EPA Science Inventory

    A university/industry panel will report on the progress and findings of a fivesteve-year project funded by the US Environmental Protection Agency. The project's end product will be a Web-based, 3D computer-simulated residential environment with a decision support system to assist...

  4. Reporting adverse events in a surgical trial for complex congenital heart disease: The Pediatric Heart Network experience

    PubMed Central

    Virzi, Lisa; Pemberton, Victoria; Ohye, Richard G.; Tabbutt, Sarah; Lu, Minmin; Atz, Teresa C.; Barnard, Teresa; Dunbar-Masterson, Carolyn; Ghanayem, Nancy S.; Jacobs, Jeffrey P.; Lambert, Linda M.; Lewis, Alan; Pike, Nancy; Pizarro, Christian; Radojewski, Elizabeth; Teitel, David; Xu, Mingfen; Pearson, Gail D.

    2011-01-01

    Objective The purpose of this analysis was to evaluate a novel strategy for reporting adverse events in the Pediatric Heart Network’s randomized surgical trial of systemic–pulmonary artery shunt versus right ventricle–pulmonary artery conduit in infants with hypoplastic left heart syndrome. The strategy was developed to align the reporting process with the needs of a surgical trial while maintaining participant safety. Methods Adverse event reporting was analyzed for 2 groups of study subjects: those randomized to a trial arm during a period in which a standard adverse event reporting system was used (period 1) and those randomized after institution of a system that focused serious adverse event reporting on 6 sentinel events (period 2). The analysis encompassed the period from randomization (Norwood surgery) to hospital discharge from stage II surgery. Adverse event rates were compared using a Poisson regression model for the number of events per subject. Results From period 1 to period 2, the rate of serious adverse events requiring expedited reporting decreased as expected (0.42 vs 0.14/subject/month of follow-up; P < .001). Subjects with a serious (sentinel) adverse event in period 2 had a significantly higher rate of death and cardiac transplantation. Conclusions The new adverse event reporting system successfully targeted subjects at highest risk, while decreasing the administrative burden associated with adverse event reports. This methodology may be of benefit in trials evaluating surgical or device-based interventions and in critically ill populations where many common clinical events would qualify as serious adverse events in the context of a drug trial. PMID:21397260

  5. A multi-station matched filter and coherent network processing approach to the automatic detection and relative location of seismic events

    NASA Astrophysics Data System (ADS)

    Gibbons, Steven J.; Näsholm, Sven Peter; Kværna, Tormod

    2014-05-01

    Correlation detectors facilitate seismic monitoring in the near vicinity of previously observed events at far lower detection thresholds than are possible using the methods applied in most existing processing pipelines. The use of seismic arrays has been demonstrated to be highly beneficial in pressing down the detection threshold, due to superior noise suppression, and also in eliminating vast numbers of false alarms by performing array processing on the multi-channel output of the correlation detectors. This last property means that it is highly desirable to run continuous detectors for sites of repeating seismic events on a single-array basis for many arrays across a global network. Spurious detections for a given signal template on a single array can however still occur when an unrelated wavefront crosses the array from a very similar direction to that of the master event wavefront. We present an algorithm which scans automatically the output from multiple stations - both array and 3-component - for coherence between the individual station correlator outputs that is consistent with a disturbance in the vicinity of the master event. The procedure results in a categorical rejection of an event hypothesis in the absence of support from stations other than the one generating the trigger and provides a fully automatic relative event location estimate when patterns in the correlation detector outputs are found to be consistent with a common event. This coherence-based approach removes the need to make explicit measurements of the time-differences for single stations and this eliminates a potential source of error. The method is demonstrated for the North Korea nuclear test site and the relative event location estimates obtained for the 2006, 2009, and 2013 events are compared with previous estimates from different station configurations.

  6. The effect of social networks and social support on mental health services use, following a life event, among the Baltimore Epidemiologic Catchment Area cohort.

    PubMed

    Maulik, Pallab K; Eaton, William W; Bradshaw, Catherine P

    2011-01-01

    The study examined the association between life events and mental health services use, accounting for social networks and social support. Main and stress-buffering effects were estimated using longitudinal data from the Baltimore Epidemiologic Catchment Area cohort (1,920 participants in 1993-1996, of whom 1,071 were re-interviewed in 2004-2005). Following a life event, the odds of using general medical services were increased by almost 50% when there was increased social support from spouse/partner (referral function). The odds of using mental health services within general health setup were reduced by 60% when there was increased support from relatives (stress-reduction function). Increased social support from friends and relatives was associated with a 40-60% decreased odds of using specialty psychiatric services after experiencing different life events (stress-reduction function). Overall, social support rather than social networks were more strongly associated with increased mental health service use following a life event. The implications for service delivery and program development are discussed.

  7. Career Builders

    ERIC Educational Resources Information Center

    Weinstein, Margery

    2012-01-01

    While a main goal for corporate trainers traditionally has been to train employees to reach organizational goals, many trainers may find their roles expanding. With companies cutting back on staffing and consolidating multiple job roles into single positions, career development has taken on a much larger significance. At forward-thinking…

  8. Career Builders

    ERIC Educational Resources Information Center

    Weinstein, Margery

    2012-01-01

    While a main goal for corporate trainers traditionally has been to train employees to reach organizational goals, many trainers may find their roles expanding. With companies cutting back on staffing and consolidating multiple job roles into single positions, career development has taken on a much larger significance. At forward-thinking…

  9. University Builders.

    ERIC Educational Resources Information Center

    Pearce, Martin

    This publication explores a diverse collection of new university buildings. Ranging from the design of vast new campuses, such as that by Wilford and Stirling at Temasek, Singapore, through to the relatively modest yet strategically important, such as the intervention by Allies and Morrison at Southampton, this book examines the new higher…

  10. Energy Builders.

    ERIC Educational Resources Information Center

    Instructor, 1982

    1982-01-01

    Due to increasing energy demands and decreasing supplies, it is important for teachers to provide students with a solid foundation for energy decision making. Activities are presented which offer hands-on experiences with four sources of energy: wind, water, sun, and fossil fuels. (JN)

  11. Energy Builders.

    ERIC Educational Resources Information Center

    Instructor, 1982

    1982-01-01

    Due to increasing energy demands and decreasing supplies, it is important for teachers to provide students with a solid foundation for energy decision making. Activities are presented which offer hands-on experiences with four sources of energy: wind, water, sun, and fossil fuels. (JN)

  12. BioPartsBuilder: a synthetic biology tool for combinatorial assembly of biological parts.

    PubMed

    Yang, Kun; Stracquadanio, Giovanni; Luo, Jingchuan; Boeke, Jef D; Bader, Joel S

    2016-03-15

    Combinatorial assembly of DNA elements is an efficient method for building large-scale synthetic pathways from standardized, reusable components. These methods are particularly useful because they enable assembly of multiple DNA fragments in one reaction, at the cost of requiring that each fragment satisfies design constraints. We developed BioPartsBuilder as a biologist-friendly web tool to design biological parts that are compatible with DNA combinatorial assembly methods, such as Golden Gate and related methods. It retrieves biological sequences, enforces compliance with assembly design standards and provides a fabrication plan for each fragment. BioPartsBuilder is accessible at http://public.biopartsbuilder.org and an Amazon Web Services image is available from the AWS Market Place (AMI ID: ami-508acf38). Source code is released under the MIT license, and available for download at https://github.com/baderzone/biopartsbuilder joel.bader@jhu.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  13. BioPartsBuilder: a synthetic biology tool for combinatorial assembly of biological parts

    PubMed Central

    Yang, Kun; Stracquadanio, Giovanni; Luo, Jingchuan; Boeke, Jef D.; Bader, Joel S.

    2016-01-01

    Summary: Combinatorial assembly of DNA elements is an efficient method for building large-scale synthetic pathways from standardized, reusable components. These methods are particularly useful because they enable assembly of multiple DNA fragments in one reaction, at the cost of requiring that each fragment satisfies design constraints. We developed BioPartsBuilder as a biologist-friendly web tool to design biological parts that are compatible with DNA combinatorial assembly methods, such as Golden Gate and related methods. It retrieves biological sequences, enforces compliance with assembly design standards and provides a fabrication plan for each fragment. Availability and implementation: BioPartsBuilder is accessible at http://public.biopartsbuilder.org and an Amazon Web Services image is available from the AWS Market Place (AMI ID: ami-508acf38). Source code is released under the MIT license, and available for download at https://github.com/baderzone/biopartsbuilder. Contact: joel.bader@jhu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26568632

  14. Bio-logic builder: a non-technical tool for building dynamical, qualitative models.

    PubMed

    Helikar, Tomáš; Kowal, Bryan; Madrahimov, Alex; Shrestha, Manish; Pedersen, Jay; Limbu, Kahani; Thapa, Ishwor; Rowley, Thaine; Satalkar, Rahul; Kochi, Naomi; Konvalina, John; Rogers, Jim A

    2012-01-01

    Computational modeling of biological processes is a promising tool in biomedical research. While a large part of its potential lies in the ability to integrate it with laboratory research, modeling currently generally requires a high degree of training in mathematics and/or computer science. To help address this issue, we have developed a web-based tool, Bio-Logic Builder, that enables laboratory scientists to define mathematical representations (based on a discrete formalism) of biological regulatory mechanisms in a modular and non-technical fashion. As part of the user interface, generalized "bio-logic" modules have been defined to provide users with the building blocks for many biological processes. To build/modify computational models, experimentalists provide purely qualitative information about a particular regulatory mechanisms as is generally found in the laboratory. The Bio-Logic Builder subsequently converts the provided information into a mathematical representation described with Boolean expressions/rules. We used this tool to build a number of dynamical models, including a 130-protein large-scale model of signal transduction with over 800 interactions, influenza A replication cycle with 127 species and 200+ interactions, and mammalian and budding yeast cell cycles. We also show that any and all qualitative regulatory mechanisms can be built using this tool.

  15. Bio-Logic Builder: A Non-Technical Tool for Building Dynamical, Qualitative Models

    PubMed Central

    Helikar, Tomáš; Kowal, Bryan; Madrahimov, Alex; Shrestha, Manish; Pedersen, Jay; Limbu, Kahani; Thapa, Ishwor; Rowley, Thaine; Satalkar, Rahul; Kochi, Naomi; Konvalina, John; Rogers, Jim A.

    2012-01-01

    Computational modeling of biological processes is a promising tool in biomedical research. While a large part of its potential lies in the ability to integrate it with laboratory research, modeling currently generally requires a high degree of training in mathematics and/or computer science. To help address this issue, we have developed a web-based tool, Bio-Logic Builder, that enables laboratory scientists to define mathematical representations (based on a discrete formalism) of biological regulatory mechanisms in a modular and non-technical fashion. As part of the user interface, generalized “bio-logic” modules have been defined to provide users with the building blocks for many biological processes. To build/modify computational models, experimentalists provide purely qualitative information about a particular regulatory mechanisms as is generally found in the laboratory. The Bio-Logic Builder subsequently converts the provided information into a mathematical representation described with Boolean expressions/rules. We used this tool to build a number of dynamical models, including a 130-protein large-scale model of signal transduction with over 800 interactions, influenza A replication cycle with 127 species and 200+ interactions, and mammalian and budding yeast cell cycles. We also show that any and all qualitative regulatory mechanisms can be built using this tool. PMID:23082121

  16. Multiple surface wetting events in the greater Meridiani Planum region, Mars: Evidence from valley networks within ancient cratered highlands

    NASA Astrophysics Data System (ADS)

    Williams, R. M. E.; Chuang, F. C.; Berman, D. C.

    2017-02-01

    Morphological characterization of valley networks in three exposures of ancient cratered highlands (Nhc1) in the greater Meridiani Planum region yields insight into the Martian aqueous history. From our mapping, key regional differences are apparent in fine-scale valley network attributes including morphologic type, planimetric form, density, and links to candidate paleolakes. This information, combined with crater retention age (inferred exposure age), provides new details on the relative timing and nature of aqueous processes in the region. Newly identified pitted-type valley networks have morphological similarity to terrestrial pitted landforms in an evaporite setting. We interpret the pitted valley networks to reflect late-stage groundwater processes concentrated along the former fluvial conduits. Evidence from this study indicates that localized reactivation of valley networks occurred during or after exhumation of eastern Nhc1 unit.

  17. Performance evaluation of the retrieval of a two hours rainfall event through microwave tomography applied to a network of radio-base stations

    NASA Astrophysics Data System (ADS)

    Facheris, L.; Cuccoli, F.; Baldini, L.

    2012-04-01

    Critical precipitation events occurred over the Italian territory have been often characterized by high intensity and very fast development, frequently over small catchment areas. The detection of this kind of phenomena is a major issue that poses remarkable problems that cannot be tackled completely only with 'standard' instrumentation (even when available), such as a weather radars or raingauges. Indeed, the rainfall sampling modalities of these instruments may jeopardize the attempts to provide a sufficiently fast risk alert: - the point-like, time-integrated way of sampling of raingauges can completely/partially miss local rainfall cores of high intensity developing in the neighborhoods. Moreover, raingauges provide cumulated rainfall measurements intrinsically affected by a time delay. - In the case of weather radars, several factors may limit the advantages brought by range resolution and instantaneous sampling: precipitation might be sampled at an excessive height due to the distance of the radar site and/or the orography surrounding the valleys/catchments where the aforementioned kind of events is more likely to form up; distance may limit the resolution in the cross-range direction; beam screening due to orography causes a loss of power that is interpreted in the farther range bins as a reduced precipitation intensity. In this context, a positive role for flagging the criticality of a precipitation event can be played by signal attenuation measurements made along microwave links, as available through the infrastructure of a mobile communications network. Three are the interesting features of such networks: 1) the communications among radio-base stations occur where point-to-point electromagnetic visibility is guaranteed, namely along valleys or between tops/flanks of hills or mountains; 2) the extension of these links (few kilometres) is perfectly compatible with the detection of severe but localized precipitation events; 3) measurements can be made on a

  18. Readability Analysis of SRA Power Builders; An Examination of the Readability Levels of the Power Builder Component of the SRA Reading Laboratory IIIB as Measured by the Dale-Chall Readability Formula.

    ERIC Educational Resources Information Center

    Rosen, Ellen Unell

    This study evaluates the readability levels of frequently used literacy materials, the power builder component of the SRA Reading Laboratory IIIB. A review of the readability literature reveals numerous studies performed on content area textbooks but relatively few studies performed on literacy materials. Three questions are asked: (1) What is the…

  19. News CPD Event: Teaching day gives new perspectives Workshop: IOP network devolops its ideas Conference: Conference offers much to teachers Event: Physics is made easy in Liverpool Communication: IOSTE debates the complexities of STE Conference: Teaching event excites in Exeter Meeting Invitation: Wales physics meeting invites bookings CPD Event: Science teachers get hands on with development Research: Conference highlights liquid crytstal research in teaching Education: Teachers give positive feedback Science Fair: Science fair brings physics to students Teaching: Conference explores trends in teaching Forthcoming events

    NASA Astrophysics Data System (ADS)

    2010-09-01

    CPD Event: Teaching day gives new perspectives Workshop: IOP network devolops its ideas Conference: Conference offers much to teachers Event: Physics is made easy in Liverpool Communication: IOSTE debates the complexities of STE Conference: Teaching event excites in Exeter Meeting Invitation: Wales physics meeting invites bookings CPD Event: Science teachers get hands on with development Research: Conference highlights liquid crytstal research in teaching Education: Teachers give positive feedback Science Fair: Science fair brings physics to students Teaching: Conference explores trends in teaching Forthcoming events

  20. Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method.

    PubMed

    Cao, Youfang; Liang, Jie

    2013-07-14

    Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively

  1. Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

    PubMed Central

    Cao, Youfang; Liang, Jie

    2013-01-01

    Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively

  2. Adaptively biased sequential importance sampling for rare events in reaction networks with comparison to exact solutions from finite buffer dCME method

    NASA Astrophysics Data System (ADS)

    Cao, Youfang; Liang, Jie

    2013-07-01

    Critical events that occur rarely in biological processes are of great importance, but are challenging to study using Monte Carlo simulation. By introducing biases to reaction selection and reaction rates, weighted stochastic simulation algorithms based on importance sampling allow rare events to be sampled more effectively. However, existing methods do not address the important issue of barrier crossing, which often arises from multistable networks and systems with complex probability landscape. In addition, the proliferation of parameters and the associated computing cost pose significant problems. Here we introduce a general theoretical framework for obtaining optimized biases in sampling individual reactions for estimating probabilities of rare events. We further describe a practical algorithm called adaptively biased sequential importance sampling (ABSIS) method for efficient probability estimation. By adopting a look-ahead strategy and by enumerating short paths from the current state, we estimate the reaction-specific and state-specific forward and backward moving probabilities of the system, which are then used to bias reaction selections. The ABSIS algorithm can automatically detect barrier-crossing regions, and can adjust bias adaptively at different steps of the sampling process, with bias determined by the outcome of exhaustively generated short paths. In addition, there are only two bias parameters to be determined, regardless of the number of the reactions and the complexity of the network. We have applied the ABSIS method to four biochemical networks: the birth-death process, the reversible isomerization, the bistable Schlögl model, and the enzymatic futile cycle model. For comparison, we have also applied the finite buffer discrete chemical master equation (dCME) method recently developed to obtain exact numerical solutions of the underlying discrete chemical master equations of these problems. This allows us to assess sampling results objectively

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

    PubMed Central

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

    2017-01-01

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

  4. On the impact of RN network coverage on event selection and data fusion during the 2009 National Data Centres Preparedness Exercise

    NASA Astrophysics Data System (ADS)

    Becker, Andreas; Krysta, Monika; Auer, Matthias; Brachet, Nicolas; Ceranna, Lars; Gestermann, Nicolai; Nikkinen, Mika; Zähringer, Matthias

    2010-05-01

    The so-called National Data Centres (NDCs) to the Provisional Technical Secretariat of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty (CTBT) Organization are in charge to provide for the final judgement on the CTBT relevance of explosion events encountered in the PTS International Monitoring System (IMS). The latter is a 321 stations network set-up by the PTS (to date completion level: 80%) in order to globally monitor for occurrence of CTBT relevant seismo-acoustic and radionuclide signals. In doing so, NDCs learn about any seismo-acoustic or radionuclide event by active retrieval or subscription to corresponding event lists and products provided by the International Data Centre (IDC) to the PTS. To prepare for their instrumental role in case of a CTBT relevant event, the NDCs jointly conduct annually so-called NDC Preparedness Exercises. In 2009, NDC Germany was in charge to lead the exercise and to choose a seismo-acoustic event out of the list of events provided by the PTS (Gestermann et al., EGU2010-13067). The novelty in this procedure was that also the infrasound readings and the monitoring coverage of existing (certified) radionuclide stations into the area of consideration were taken into account during the event selection process (Coyne et al., EGU2010-12660). Hence, the event finally chosen and examined took place near Kara-Zhyra mine in Eastern Kazakhstan on 28 November 2009 around 07:20:31 UTC (Event-ID 5727516). NDC Austria performed forward atmospheric transport modelling in order to predict RN measurements that should have occurred in the radionuclide IMS. In doing so the fictitious case that there would have been a release of radionuclides taking place at the same location (Wotawa and Schraik, 2010; EGU2010-4907) in a strength being typical for a non-contained nuclear explosion is examined. The stations indicated should then be analysed for their actual radionuclide readings in order to confirm the non nuclear character of

  5. Single muscle fibre contractile properties differ between body-builders, power athletes and control subjects.

    PubMed

    Meijer, J P; Jaspers, R T; Rittweger, J; Seynnes, O R; Kamandulis, S; Brazaitis, M; Skurvydas, A; Pišot, R; Šimunič, B; Narici, M V; Degens, H

    2015-11-01

    What is the central question of this study? Do the contractile properties of single muscle fibres differ between body-builders, power athletes and control subjects? What is the main finding and its importance? Peak power normalized for muscle fibre volume in power athletes is higher than in control subjects. Compared with control subjects, maximal isometric tension (normalized for muscle fibre cross-sectional area) is lower in body-builders. Although this difference may be caused in part by an apparent negative effect of hypertrophy, these results indicate that the training history of power athletes may increase muscle fibre quality, whereas body-building may be detrimental. We compared muscle fibre contractile properties of biopsies taken from the vastus lateralis of 12 body-builders (BBs; low- to moderate-intensity high-volume resistance training), six power athletes (PAs; high-intensity, low-volume combined with aerobic training) and 14 control subjects (Cs). Maximal isotonic contractions were performed in single muscle fibres, typed with SDS-PAGE. Fibre cross-sectional area was 67 and 88% (P < 0.01) larger in BBs than in PAs and Cs, respectively, with no significant difference in fibre cross-sectional area between PAs and Cs. Fibres of BBs and PAs developed a higher maximal isometric tension (32 and 50%, respectively, P < 0.01) than those of Cs. The specific tension of BB fibres was 62 and 41% lower than that of PA and C fibres (P < 0.05), respectively. Irrespective of fibre type, the peak power (PP) of PA fibres was 58% higher than that of BB fibres (P < 0.05), whereas BB fibres, despite considerable hypertrophy, had similar PP to the C fibres. This work suggests that high-intensity, low-volume resistance training with aerobic exercise improves PP, while low- to moderate-intensity high-volume resistance training does not affect PP and results in a reduction in specific tension. We postulate that the decrease in specific tension is caused by differences

  6. Car Builder: Design, Construct and Test Your Own Cars. School Version with Lesson Plans. [CD-ROM].

    ERIC Educational Resources Information Center

    Highsmith, Joni Bitman

    Car Builder is a scientific CD-ROM-based simulation program that lets students design, construct, modify, test, and compare their own cars. Students can design sedans, four-wheel-drive vehicles, vans, sport cars, and hot rods. They may select for aerodynamics, power, and racing ability, or economic and fuel efficiency. It is a program that teaches…

  7. Car Builder: Design, Construct and Test Your Own Cars. School Version with Lesson Plans. [CD-ROM].

    ERIC Educational Resources Information Center

    Highsmith, Joni Bitman

    Car Builder is a scientific CD-ROM-based simulation program that lets students design, construct, modify, test, and compare their own cars. Students can design sedans, four-wheel-drive vehicles, vans, sport cars, and hot rods. They may select for aerodynamics, power, and racing ability, or economic and fuel efficiency. It is a program that teaches…

  8. Effect of densifying the GNSS GBAS network on monitoring the troposphere zenith total delay and precipitable water vapour content during severe weather events

    NASA Astrophysics Data System (ADS)

    Kapłon, Jan; Stankunavicius, Gintautas

    2016-04-01

    The dense ground based augmentation networks can provide the important information for monitoring the state of neutral atmosphere. The GNSS&METEO research group at Wroclaw University of Environmental and Life Sciences (WUELS) is operating the self-developed near real-time service estimating the troposphere parameters from GNSS data for the area of Poland. The service is operational since December 2012 and it's results calculated from ASG-EUPOS GBAS network (120 stations) data are supporting the EGVAP (http://egvap.dmi.dk) project. At first the zenith troposphere delays (ZTD) were calculated in hourly intervals, but since September 2015 the service was upgraded to include SmartNet GBAS network (Leica Geosystems Polska - 150 stations). The upgrade included as well: increasing the result interval to 30 minutes, upgrade from Bernese GPS Software v. 5.0 to Bernese GNSS Software v. 5.2 and estimation of the ZTD and it's horizontal gradients. Processing includes nowadays 270 stations. The densification of network from 70 km of mean distance between stations to 40 km created the opportunity to investigate on it's impact on resolution of estimated ZTD and integrated water vapour content (IWV) fields during the weather events of high intensity. Increase in density of ZTD measurements allows to define better the meso-scale features within different synoptic systems (e.g. frontal waves, meso-scale convective systems, squall lines etc). These meso-scale structures, as a rule are short living but fast developing and hardly predictable by numerical models. Even so, such limited size systems can produce very hazardous phenomena - like widespread squalls and thunderstorms, tornadoes, heavy rains, snowfalls, hail etc. because of prevalence of Cb clouds with high concentration of IWV. Study deals with two meteorological events: 2015-09-01 with the devastating squalls and rainfall bringing 2M Euro loss of property in northern Poland and 2015-10-12 with the very active front bringing

  9. [Effects of stressful life events which cause depression in the elderly, and the role of the social support network--a longitudinal study in Hokkaido prefecture].

    PubMed

    Kishi, Reiko; Urata, Yasunari; Saijo, Yasuaki; Horikawa, Naoko; Sato, Tetsuro; Yoshioka, Eiji

    2005-01-01

    The effects of stressful life events which cause depression in the elderly and the role of the social support network--a longitudinal study in Hokkaido prefecture It has been reported that various stressful life events experienced by the elderly increase the risk of depression, and that a support network mitigates the effects. However, reports in our country are still lacking. This research was a longitudinal study in a former coal mining area, conducting a baseline survey on 1991. Every three to four years, we followed-up the elderly in the area. The questionnaire included :1) base attributes 2) stressful life events 3) networks, 4) instrumental/emotional support, support provided themselves, 4) Zung's Self Rating Depression Scale, 5) subjective health/number of illness/hospital admission/body aches/vision and hearing/urinary incontinence/signs of dementia, 6) hobbies and motivation in life/ADL/IADL. Whether male or female, SDS scores after three years were significantly high in cases of poor health, body aches, and signs of dementia. Females who did not participate in social activities scored significantly high after three years. In cross-sectional analysis, both males and females who were not working had significantly high scores. The effect of networks on SDS scores in females was significantly recognized for items regarding children living separately, neighborhood, close friends/relatives, and groups. However, it was not significant for males. Thus, a gender difference was found. In females, the level of depression was low when there were supports, though it was not significant in males. The subjective health condition was significantly different from SDS scores in both male and female groups. Admission to hospital, existence of body aches and vision disturbance were significantly different in females. Nevertheless, those were not significant in the male group. For social activity, whether the persons possessed hobbies and motivation in life or not created a

  10. Networks.

    ERIC Educational Resources Information Center

    Maughan, George R.; Petitto, Karen R.; McLaughlin, Don

    2001-01-01

    Describes the connectivity features and options of modern campus communication and information system networks, including signal transmission (wire-based and wireless), signal switching, convergence of networks, and network assessment variables, to enable campus leaders to make sound future-oriented decisions. (EV)

  11. Energy conservation manual for builders in the Mid-Columbia Basin area

    SciTech Connect

    Mazzucchi, R.P.; Nieves, L.A.; Hopp, W.J.

    1981-03-01

    Results of a comprehensive cost-effectiveness evaluation of energy conservation measures currently available for use in typical residential buildings are presented. Section 2 discusses construction techniques for energy-efficient buildings and presents estimates of the cost of incorporating the conservation measures in the prototype building, the resultant annual energy savings, and the value of that annual energy savings based upon typical regional fuel prices. In Section 3 this information is summarized to prioritize conservation investments according to their economic effectiveness and offer general recommendations to home builders. Appendix A contains detailed information pertaining to the energy consumption calculations. Appendix B presents the methodology, assumptions, and results of a detail cash flow analysis of each of the conservation items for which sufficient performance and cost data are currently available. (MCW)

  12. Indoor air quality handbook for designers, builders and users of energy efficient residences

    NASA Astrophysics Data System (ADS)

    1982-09-01

    The purpose of the handbook is to assist designers, builders, and users of energy efficient residences to achieve the goals of energy efficiency and maintenance of high indoor air quality simultaneously. Basic concepts of contaminants and their concentrations, sources and removal mechanisms, contaminant distribution, heat transfer, and air exchange are discussed. The effects of the building system on indoor air quality are examined. The effects of the external environment, building envelope, environmental control systems, interior design, furnishings, and inhabitants on the emission, dispersion, and removal of indoor air contaminants as well as direct and indirect effects of energy efficient features are discussed. The health effects of specific air contaminants and the health standards developed for them are examined. Available methods for predicting and measuring contaminants and for evaluating human responses are discussed. Methods and equipment available for the control of indoor air pollution once the contaminants have been identified are also evaluated. The potential legal aspects control indoor air pollution are discussed.

  13. Running CMS remote analysis builder jobs on advanced resource connector middleware

    NASA Astrophysics Data System (ADS)

    Edelmann, E.; Happonen, K.; Koivumäki, J.; Lindén, T.; Välimaa, J.

    2011-12-01

    CMS user analysis jobs are distributed over the grid with the CMS Remote Analysis Builder application (CRAB). According to the CMS computing model the applications should run transparently on the different grid flavours in use. In CRAB this is handled with different plugins that are able to submit to different grids. Recently a CRAB plugin for submitting to the Advanced Resource Connector (ARC) middleware has been developed. The CRAB ARC plugin enables simple and fast job submission with full job status information available. CRAB can be used with a server which manages and monitors the grid jobs on behalf of the user. In the presentation we will report on the CRAB ARC plugin and on the status of integrating it with the CRAB server and compare this with using the gLite ARC interoperability method for job submission.

  14. Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

    USGS Publications Warehouse

    Bolker, Benjamin M.; Gardner, Beth; Maunder, Mark; Berg, Casper W.; Brooks, Mollie; Comita, Liza; Crone, Elizabeth; Cubaynes, Sarah; Davies, Trevor; de Valpine, Perry; Ford, Jessica; Gimenez, Olivier; Kéry, Marc; Kim, Eun Jung; Lennert-Cody, Cleridy; Magunsson, Arni; Martell, Steve; Nash, John; Nielson, Anders; Regentz, Jim; Skaug, Hans; Zipkin, Elise

    2013-01-01

    1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

  15. FragBuilder: an efficient Python library to setup quantum chemistry calculations on peptides models.

    PubMed

    Christensen, Anders S; Hamelryck, Thomas; Jensen, Jan H

    2014-01-01

    We present a powerful Python library to quickly and efficiently generate realistic peptide model structures. The library makes it possible to quickly set up quantum mechanical calculations on model peptide structures. It is possible to manually specify a specific conformation of the peptide. Additionally the library also offers sampling of backbone conformations and side chain rotamer conformations from continuous distributions. The generated peptides can then be geometry optimized by the MMFF94 molecular mechanics force field via convenient functions inside the library. Finally, it is possible to output the resulting structures directly to files in a variety of useful formats, such as XYZ or PDB formats, or directly as input files for a quantum chemistry program. FragBuilder is freely available at https://github.com/jensengroup/fragbuilder/ under the terms of the BSD open source license.

  16. FragBuilder: an efficient Python library to setup quantum chemistry calculations on peptides models

    PubMed Central

    Hamelryck, Thomas; Jensen, Jan H.

    2014-01-01

    We present a powerful Python library to quickly and efficiently generate realistic peptide model structures. The library makes it possible to quickly set up quantum mechanical calculations on model peptide structures. It is possible to manually specify a specific conformation of the peptide. Additionally the library also offers sampling of backbone conformations and side chain rotamer conformations from continuous distributions. The generated peptides can then be geometry optimized by the MMFF94 molecular mechanics force field via convenient functions inside the library. Finally, it is possible to output the resulting structures directly to files in a variety of useful formats, such as XYZ or PDB formats, or directly as input files for a quantum chemistry program. FragBuilder is freely available at https://github.com/jensengroup/fragbuilder/ under the terms of the BSD open source license. PMID:24688855

  17. Measurement of sediment loads during flash flood events: 14 years of results from a six stream monitoring network on the southern Colorado Plateau

    NASA Astrophysics Data System (ADS)

    Griffiths, R. E.; Topping, D. J.

    2015-12-01

    In in arid and semi-arid environments, short-duration, high-intensity rainfall events—flash floods—are the primary driver of sediment transport in ephemeral streams. The spatial and temporal variability of these rainfall events results in episodic and irregular stream flow and resultant sediment transport. As a result of limited-flow durations, measuring discharge and collecting suspended-sediment samples on ephemeral streams in arid regions is difficult and time-consuming. Because of these limitations, few sediment-monitoring programs on ephemeral streams have been developed; some examples of sediment-monitoring gages and gaging networks constructed on arid ephemeral streams include Walnut Gulch, United States, Nahal Yael, Israel, and the Luni River Basin, India. The difficulty in making measurements of discharge and suspended-sediment concentration on arid ephemeral streams has led many researchers to use methods such as regional sediment-yield equations, sediment-rating curves, and peak discharge to total-sediment load relations. These methods can provide a cost-effective estimation of sediment yield from ungaged tributaries. However, these approaches are limited by, among other factors, time averaging, hysteresis, and differences in local and regional geology, rainfall, and vegetation. A monitoring network was established in 2000 on six ephemeral tributaries of the Colorado River in lower Glen and upper Marble canyons. Results from this monitoring network show that annual suspended-sediment loads for individual streams can vary by 5 orders of magnitude while the annual suspended-sediment load for the entire network may vary annually by 2 orders of magnitude, suspended-sediment loads during an individual flood event do not typically correlate with discharge, and local geology has a strong control on the sediment yield of a drainage basin. Comparing our results to previous estimates of sediment load from these drainages found that previous, indirect, methods

  18. Testing the global capabilities of the Antelope software suite: fast location and Mb determination of teleseismic events using the ASAIN and GSN seismic networks

    NASA Astrophysics Data System (ADS)

    Pesaresi, D.; Russi, M.; Plasencia, M.; Cravos, C.

    2009-04-01

    The Italian National Institute for Oceanography and Experimental Geophysics (Istituto Nazionale di Oceanografia e di Geofisica Sperimentale, OGS) is running the Antarctic Seismographic Argentinean Italian Network (ASAIN), made of 5 seismic stations located in the Scotia Sea region in Antarctica and in Argentina: data from these stations are transferred in real time to the OGS headquarters in Trieste (Italy) via satellite links. OGS is also running, in close cooperation with the Friuli-Venezia Giulia Civil Defense, the North East (NI) Italy seismic network, making use of the Antelope commercial software suite from BRTT as the main acquisition system. As a test to check the global capabilities of Antelope, we set up an instance of Antelope acquiring data in real time from both the regional ASAIN seismic network in Antarctica and a subset of the Global Seismic Network (GSN) funded by the Incorporated Research Institution for Seismology (IRIS). The facilities of the IRIS Data Management System, and specifically the IRIS Data Management Center, were used for real time access to waveform required in this study. Preliminary results over 1 month period indicated that about 82% of the earthquakes with magnitude M>5.0 listed in the PDE catalogue of the National Earthquake Information Center (NEIC) of the United States Geological Survey (USGS) were also correctly detected by Antelope, with an average location error of 0.05 degrees and average body wave magnitude Mb estimation error below 0.1. The average time difference between event origin time and the actual time of event determination by Antelope was of about 45': the comparison with 20', the IASPEI91 P-wave travel time for 180 degrees distance, and 25', the estimate of our test system data latency, indicate that Antelope is a serious candidate for regional and global early warning systems. Updated figures calculated over a longer period of time will be presented and discussed.

  19. Amphetamine use and its associated factors in body builders: a study from Tehran, Iran

    PubMed Central

    Narenjiha, Hooman; Tayyebi, Behnoosh; Ghassabian, Akhgar; Ahmadi, Gelareh; Assari, Shervin

    2012-01-01

    Introduction Epidemiological studies on all types of illicit drug use among athletes are essential for both the sport community and drug control achievements. Here, we investigated the prevalence and associated factors of amphetamine use in body builders in Tehran, Iran, 2007. Material and methods This study is a secondary analysis of a substance use survey done in 103 randomly selected gymnasia in Tehran (capital city of Iran). The survey was conducted from November 2007 to January 2008 and included 843 randomly selected bodybuilders (aged 40 years or less). By interviews via questionnaires the following data were obtained: age, job, marital status, education level, housing status, average monthly family income, number of family members, gymnasium area (m2), number of trainers, number of gymnasium members, initiation time (months), weekly duration of the sporting activity (h), monthly cost of the sporting activity, purpose of participating in sporting activity, and history of anabolic steroid and amphetamine use. Results One hundred twenty (13.3%) body builders reported a history of amphetamine use. According to the results of regression analysis, being married (risk ratio – RR = 0.540), and participating in body building to enhance self-esteem (RR = 0.423) or to enhance sport performance (RR = 0.545) had protective effects on amphetamine use. However, having university qualifications (RR = 1.843), using anabolic steroids (RR = 1.803) and participating in sport to maintain fitness (RR = 2.472) were linked to increased risk of amphetamine use. Conclusions Well-educated bodybuilders were more likely to use amphetamines, and why this is so needs to be discovered. If further studies show that they are not aware of the dangers associated with amphetamine use, providing them with information should be considered. PMID:22662012

  20. Ocean acidification causes bleaching and productivity loss in coral reef builders

    PubMed Central

    Anthony, K. R. N.; Kline, D. I.; Diaz-Pulido, G.; Dove, S.; Hoegh-Guldberg, O.

    2008-01-01

    Ocean acidification represents a key threat to coral reefs by reducing the calcification rate of framework builders. In addition, acidification is likely to affect the relationship between corals and their symbiotic dinoflagellates and the productivity of this association. However, little is known about how acidification impacts on the physiology of reef builders and how acidification interacts with warming. Here, we report on an 8-week study that compared bleaching, productivity, and calcification responses of crustose coralline algae (CCA) and branching (Acropora) and massive (Porites) coral species in response to acidification and warming. Using a 30-tank experimental system, we manipulated CO2 levels to simulate doubling and three- to fourfold increases [Intergovernmental Panel on Climate Change (IPCC) projection categories IV and VI] relative to present-day levels under cool and warm scenarios. Results indicated that high CO2 is a bleaching agent for corals and CCA under high irradiance, acting synergistically with warming to lower thermal bleaching thresholds. We propose that CO2 induces bleaching via its impact on photoprotective mechanisms of the photosystems. Overall, acidification impacted more strongly on bleaching and productivity than on calcification. Interestingly, the intermediate, warm CO2 scenario led to a 30% increase in productivity in Acropora, whereas high CO2 lead to zero productivity in both corals. CCA were most sensitive to acidification, with high CO2 leading to negative productivity and high rates of net dissolution. Our findings suggest that sensitive reef-building species such as CCA may be pushed beyond their thresholds for growth and survival within the next few decades whereas corals will show delayed and mixed responses. PMID:18988740