A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.

PubMed

Caubel, Julien J; Cados, Troy E; Kirchstetter, Thomas W

2018-03-01

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).

A Hyper-Dense GNSS Receiver Network for Monitoring Time and Spatial Variations of Precipitable Water Vapor (PWV)

NASA Astrophysics Data System (ADS)

Tsuda, T.; Ito, N.; Takeda, Y.; Realini, E.; Shinbori, A.

2016-12-01

We employ the GNSS meteorology technique to measure precipitable water vapor (PWV) from the propagation delay of GNSS signal in the atmosphere. We installed a hyper-dense GNSS network using 15 receivers with a horizontal spacing of 1-2 km in Uji, Japan (Uji network). We also obtained precipitation with a rain gauge at a nearby operational weather station and rain cloud distribution by an X-band radar. We selected 40 days from April 2011 to March 2013, when considerable precipitation was detected. Difference in PWV within 10 km was 3-10 mm during a heavy rain. We found PWV increased 10-20 minutes before a passage of a rain cloud. The maximum value of PWV correlated well with the amount of precipitation on the ground. The variance of PWV between the GNSS sites was enhanced during a heavy rain. For a future practical hyper-dense GNSS network system with many receivers, we consider to use inexpensive single frequency (SF) receivers. Because SF receiver cannot eliminate the ionospheric delay by itself, we interpolate the delay referring the delay measured by the nearby dual frequency (DF) receivers. We investigated ionospheric delay by the Uji network, taking advantages of Quasi-Zenith Satellite System (QZSS) that gives signals at high elevation angles. During a travelling ionospheric disturbance (TID), a wavy structure with a horizontal scale of several tens km was recognized. The ionospheric delay was compensated by a linear and quadratic interpolation, then the resulting error of PWV compared with DF solution was about 1.50 mm in RMS. For a real-time estimation of PWV, we used real-time satellite clock information corrected by GEONET. Difference of PWV between the real-time analysis and the post processing with the final orbit was 0.7 mm in RMS. We estimated an overall error of PWV with a dense SF-receiver network on a real-time basis was 1.7 mm in RMS.

Monitoring of persistent organic pollutants in Africa. Part 2: design of a network to monitor the continental and intercontinental background.

PubMed

Lammel, G; Dobrovolný, P; Dvorská, A; Chromá, K; Brázdil, R; Holoubek, I; Hosek, J

2009-11-01

A network for the study of long-term trends of the continental background in Africa and the intercontinental background of persistent organic pollutants as resulting from long-range transport of contaminants from European, South Asian, and other potential source regions, as well as by watching supposedly pristine regions, i.e. the Southern Ocean and Antarctica is designed. The results of a pilot phase sampling programme in 2008 and meteorological and climatological information from the period 1961-2007 was used to apply objective criteria for the selection of stations for the monitoring network: out the original 26 stations six have been rejected because of suggested strong local sources of POPs and three others because of local meteorological effects, which may prevent part of the time long-range transported air to reach the sampling site. Representativeness of the meteorological patterns during the pilot phase with respect to climatology was assessed by comparison of the more local airflow situation as given by climatological vs. observed wind roses and by comparison of backward trajectories with the climatological wind (NCEP/NCAR re-analyses). With minor exceptions advection to nine inspected stations was typical for present-day climate during the pilot phase, 2008. Six to nine stations would cover satisfyingly large and densely populated regions of North-eastern, West and East Africa and its neighbouring seas, the Mediterranean, Northern and Equatorial Atlantic Ocean, the Western Indian Ocean and the Southern Ocean. Among the more densely populated areas Southern Cameroon, parts of the Abessinian plateau and most of the Great Lakes area would not be covered. The potential of the network is not hampered by on-going long-term changes of the advection to the selected stations, as these do hardly affect the coverage of target areas.

Evaluating the Reverse Time Migration Method on the dense Lapnet / Polenet seismic array in Europe

NASA Astrophysics Data System (ADS)

Dupont, Aurélien; Le Pichon, Alexis

2013-04-01

In this study, results are obtained using the reverse time migration method used as benchmark to evaluate the implemented method by Walker et al., (2010, 2011). Explosion signals recorded by the USArray and extracted from the TAIRED catalogue (TA Infrasound Reference Event Database user community / Vernon et al., 2012) are investigated. The first one is an explosion at Camp Minden, Louisiana (2012-10-16 04:25:00 UTC) and the second one is a natural gas explosion near Price, Utah (2012-11-20 15:20:00 UTC). We compare our results to automatic solutions (www.iris.edu/spud/infrasoundevent). The good agreement between both solutions validates our detection method. In a second time, we analyse data from the Lapnet / Polenet dense seismic network (Kozlovskaya et al., 2008). Detection and location in two-dimensional space and time of infrasound events presumably due to acoustic-to-seismic coupling, during the 2007-2009 period in Europe, are presented. The aim of this work is to integrate near-real time network performance predictions at regional scales to improve automatic detection of infrasonic sources. The use of dense seismic networks provides a valuable tool to monitor infrasonic phenomena, since seismic location has recently proved to be more accurate than infrasound locations due to the large number of seismic sensors.

Strain and ground-motion monitoring at magmatic areas: ultra-long and ultra-dense networks using fibre optic sensing systems

NASA Astrophysics Data System (ADS)

Jousset, Philippe; Reinsch, Thomas; Henninges, Jan; Blanck, Hanna; Ryberg, Trond

2016-04-01

The fibre optic distributed acoustic sensing technology (DAS) is a "new" sensing system for exploring earth crustal elastic properties and monitoring both strain and seismic waves with unprecedented acquisition characteristics. The DAS technology principle lies in sending successive and coherent pulses of light in an optical fibre and measuring the back-scattered light issued from elastic scattering at random defaults within the fibre. The read-out unit includes an interferometer, which measures light interference patterns continuously. The changes are related to the distance between such defaults and therefore the strain within the fibre can be detected. Along an optical fibre, DAS can be used to acquire acoustic signals with a high spatial (every meter over kilometres) and high temporal resolution (thousand of Hz). Fibre optic technologies were, up to now, mainly applied in perimeter surveillance applications and pipeline monitoring and in boreholes. Previous experiments in boreholes have shown that the DAS technology is well suited for probing subsurface elastic properties, showing new ways for cheaper VSP investigations of the Earth crust. Here, we demonstrate that a cable deployed at ground surface can also help in exploring subsurface properties at crustal scale and monitor earthquake activity in a volcanic environment. Within the framework of the EC funded project IMAGE, we observed a >15 km-long fibre optic cable at the surface connected to a DAS read-out unit. Acoustic data was acquired continuously for 9 days. Hammer shots were performed along the surface cable in order to locate individual acoustic traces and calibrate the spatial distribution of the acoustic information. During the monitoring period both signals from on- and offshore explosive sources and natural seismic events could be recorded. We compare the fibre optic data to conventional seismic records from a dense seismic network deployed on Reykjanes. We show that we can probe and monitor earth crust subsurface with dense acquisition of the ground motion, both in space and in time and over a broad band frequency range.

Measuring NO, NO2, CO2 and O3 with low-cost sensors

NASA Astrophysics Data System (ADS)

Müller, Michael; Graf, Peter; Hüglin, Christoph

2017-04-01

Inexpensive sensors measuring ambient gas concentrations can be integrated in sensor units forming dense sensor networks. The utilized sensors have to be sufficiently accurate as the value of such networks directly depends on the information they provide. Thus, thorough testing of sensors before bringing them into service and the application of effective strategies for performance monitoring and adjustments during service are key elements for operating the low-cost sensors that are currently available on the market. We integrated several types of low-cost sensors into sensor units (Alphasense NO2 B4/B42F/B43F, Alphasense NO B4, SensAir CO2 LP8, Aeroqual O3 SM50), run them in the field next to instruments of air quality monitoring stations and performed tests in the laboratory. The poster summarizes our findings regarding the achieved sensor accuracy, methods to improve sensor performance as well as strategies to monitor the current state of the sensor (drifts, sensitivity) within a sensor network.

On the feasibility of measuring urban air pollution by wireless distributed sensor networks.

PubMed

Moltchanov, Sharon; Levy, Ilan; Etzion, Yael; Lerner, Uri; Broday, David M; Fishbain, Barak

2015-01-01

Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Thunderstorm monitoring with VLF network and super dense meteorological observation system

NASA Astrophysics Data System (ADS)

Takahashi, Yukihiro; Sato, Mitsuteru

2015-04-01

It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a thunderstorm monitoring system consisting of the network of VLF radio wave receivers and the super dense meteorological observation system with simple and low cost plate-type sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge, adding to basic equipments for meteorological measurements. The plate-type sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan and surrounded by our VLF systems developed for detecting sferics from lightning discharge, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.

Dense module enumeration in biological networks

NASA Astrophysics Data System (ADS)

Tsuda, Koji; Georgii, Elisabeth

2009-12-01

Analysis of large networks is a central topic in various research fields including biology, sociology, and web mining. Detection of dense modules (a.k.a. clusters) is an important step to analyze the networks. Though numerous methods have been proposed to this aim, they often lack mathematical rigorousness. Namely, there is no guarantee that all dense modules are detected. Here, we present a novel reverse-search-based method for enumerating all dense modules. Furthermore, constraints from additional data sources such as gene expression profiles or customer profiles can be integrated, so that we can systematically detect dense modules with interesting profiles. We report successful applications in human protein interaction network analyses.

Real-time isotope monitoring network at the Biosphere 2 Landscape Evolution Observatory resolves meter-to-catchment scale flow dynamics

NASA Astrophysics Data System (ADS)

Volkmann, T. H. M.; Van Haren, J. L. M.; Kim, M.; Harman, C. J.; Pangle, L.; Meredith, L. K.; Troch, P. A.

2017-12-01

Stable isotope analysis is a powerful tool for tracking flow pathways, residence times, and the partitioning of water resources through catchments. However, the capacity of stable isotopes to characterize catchment hydrological dynamics has not been fully exploited as commonly used methodologies constrain the frequency and extent at which isotopic data is available across hydrologically-relevant compartments (e.g. soil, plants, atmosphere, streams). Here, building upon significant recent developments in laser spectroscopy and sampling techniques, we present a fully automated monitoring network for tracing water isotopes through the three model catchments of the Landscape Evolution Observatory (LEO) at the Biosphere 2, University of Arizona. The network implements state-of-the-art techniques for monitoring in great spatiotemporal detail the stable isotope composition of water in the subsurface soil, the discharge outflow, and the atmosphere above the bare soil surface of each of the 330-m2 catchments. The extensive valving and probing systems facilitate repeated isotope measurements from a total of more than five-hundred locations across the LEO domain, complementing an already dense array of hydrometric and other sensors installed on, within, and above each catchment. The isotope monitoring network is operational and was leveraged during several months of experimentation with deuterium-labelled rain pulse applications. Data obtained during the experiments demonstrate the capacity of the monitoring network to resolve sub-meter to whole-catchment scale flow and transport dynamics in continuous time. Over the years to come, the isotope monitoring network is expected to serve as an essential tool for collaborative interdisciplinary Earth science at LEO, allowing us to disentangle changes in hydrological behavior as the model catchments evolve in time through weathering and colonization by plant communities.

Dense power-law networks and simplicial complexes

NASA Astrophysics Data System (ADS)

Courtney, Owen T.; Bianconi, Ginestra

2018-05-01

There is increasing evidence that dense networks occur in on-line social networks, recommendation networks and in the brain. In addition to being dense, these networks are often also scale-free, i.e., their degree distributions follow P (k ) ∝k-γ with γ ∈(1 ,2 ] . Models of growing networks have been successfully employed to produce scale-free networks using preferential attachment, however these models can only produce sparse networks as the numbers of links and nodes being added at each time step is constant. Here we present a modeling framework which produces networks that are both dense and scale-free. The mechanism by which the networks grow in this model is based on the Pitman-Yor process. Variations on the model are able to produce undirected scale-free networks with exponent γ =2 or directed networks with power-law out-degree distribution with tunable exponent γ ∈(1 ,2 ) . We also extend the model to that of directed two-dimensional simplicial complexes. Simplicial complexes are generalization of networks that can encode the many body interactions between the parts of a complex system and as such are becoming increasingly popular to characterize different data sets ranging from social interacting systems to the brain. Our model produces dense directed simplicial complexes with power-law distribution of the generalized out-degrees of the nodes.

NY-uHMT: A dense hydro-meteorological network to characterize urban land-atmosphere interactions

NASA Astrophysics Data System (ADS)

Ramamurthy, P.; Lakhankar, T.; Khanbilvardi, R.; Devineni, N.

2016-12-01

Most people in the US live in large Metropolitan areas that have a dense urban core in the center, dominated by built surfaces and surrounded by residential/suburban areas that consist a mix of built, vegetated and permeable surfaces. This creates a gradient in the hydro-meteorological environment giving rise to complex land-atmosphere interactions. Current modeling platforms and observational techniques like tower measurements do not adequately account for the underlying heterogeneity. To address this critical gap in our understanding we have instituted a dense network of sensors in the New York Metropolitan area. This unique urban sensor network consists of instrumentation to monitor soil moisture at multiple depths along with air temperature, relative humidity and precipitation, with room to add additional sensors in the future. The network is autonomous and connected to a centralized server using cellular towers. Apart from describing the spatial variability in hydro-meteorological quantities the network will also aid in conducting high-resolution numerical simulations to study and forecast urban weather and climate. In one such simulation conducted to partition the influence of storage flux, wind pattern and circulation and soil moisture deficit on urban heat island intensity (UHI), we found that the daily variability in UHI in NYC was sensitive to available energy and wind pattern. The long-term trend in UHI was however related to soil moisture deficit. In fact a prolonged heat wave period witnessed during summer 2006 correlated well with an extended dry period and the daily UHI in NYC almost doubled. Moreover, the urban soils also suffered from high degree of dessication, owing to drier urban boundary layer.

Regional and transported aerosols during DRAGON-Japan experiment

NASA Astrophysics Data System (ADS)

Sano, I.; Holben, B. N.; Mukai, S.; Nakata, M.; Nakaguchi, Y.; Sugimoto, N.; Hatakeyama, S.; Nishizawa, T.; Takamura, T.; Takemura, T.; Yonemitsu, M.; Fujito, T.; Schafer, J.; Eck, T. F.; Sorokin, M.; Kenny, P.; Goto, M.; Hiraki, T.; Iguchi, N.; Kouzai, K.; KUJI, M.; Muramatsu, K.; Okada, Y.; Sadanaga, Y.; Tohno, S.; Toyazaki, Y.; Yamamoto, K.

2013-12-01

Aerosol properties over Japan have been monitored by AERONET sun / sky photometers since 2000. These measurements provides us with long term information of local aerosols, which are influenced by transported aerosols, such as Asian dusts or anthropogenic pollutants due to rapid increasing of energy consumption in Asian countries. A new aerosol monitoring experiment, Distributed Regional Aerosol Gridded Observation Networks (DRAGON) - Japan is operated in spring of 2012. The main instrument of DRAGON network is AERONET sun/sky radiometers. Some of them are sparsely set along the Japanese coast and some others make a dense network in Osaka, which is the second-largest city in Japan and famous for manufacturing town. Several 2ch NIES-LIDAR systems are also co-located with AERONET instrument to monitor Asian dusts throughout the campaign. The objects of Dragon-Japan are to characterize local aerosols as well as transported ones from the continent of China, and to acquire the detailed aerosol information for validating satellite data with high resolved spatial scale. This work presents the comprehensive results of aerosol properties with respect to regional- and/or transported- scale during DRAGON-Japan experiments.

Aerial Images and Convolutional Neural Network for Cotton Bloom Detection.

PubMed

Xu, Rui; Li, Changying; Paterson, Andrew H; Jiang, Yu; Sun, Shangpeng; Robertson, Jon S

2017-01-01

Monitoring flower development can provide useful information for production management, estimating yield and selecting specific genotypes of crops. The main goal of this study was to develop a methodology to detect and count cotton flowers, or blooms, using color images acquired by an unmanned aerial system. The aerial images were collected from two test fields in 4 days. A convolutional neural network (CNN) was designed and trained to detect cotton blooms in raw images, and their 3D locations were calculated using the dense point cloud constructed from the aerial images with the structure from motion method. The quality of the dense point cloud was analyzed and plots with poor quality were excluded from data analysis. A constrained clustering algorithm was developed to register the same bloom detected from different images based on the 3D location of the bloom. The accuracy and incompleteness of the dense point cloud were analyzed because they affected the accuracy of the 3D location of the blooms and thus the accuracy of the bloom registration result. The constrained clustering algorithm was validated using simulated data, showing good efficiency and accuracy. The bloom count from the proposed method was comparable with the number counted manually with an error of -4 to 3 blooms for the field with a single plant per plot. However, more plots were underestimated in the field with multiple plants per plot due to hidden blooms that were not captured by the aerial images. The proposed methodology provides a high-throughput method to continuously monitor the flowering progress of cotton.

Amperometric Gas Sensors as a Low Cost Emerging Technology Platform for Air Quality Monitoring Applications: A Review.

PubMed

Baron, Ronan; Saffell, John

2017-11-22

This review examines the use of amperometric electrochemical gas sensors for monitoring inorganic gases that affect urban air quality. First, we consider amperometric gas sensor technology including its development toward specifically designed air quality sensors. We then review recent academic and research organizations' studies where this technology has been trialed for air quality monitoring applications: early studies showed the potential of electrochemical gas sensors when colocated with reference Air Quality Monitoring (AQM) stations. Spatially dense networks with fast temporal resolution provide information not available from sparse AQMs with longer recording intervals. We review how this technology is being offered as commercial urban air quality networks and consider the remaining challenges. Sensors must be sensitive, selective, and stable; air quality monitors/nodes must be electronically and mechanically well designed. Data correction is required and models with differing levels of sophistication are being designed. Data analysis and validation is possibly the biggest remaining hurdle needed to deliver reliable concentration readings. Finally, this review also considers the roles of companies, urban infrastructure requirements, and public research in the development of this technology.

Development of real time monitor system displaying seismic waveform data observed at seafloor seismic network, DONET, for disaster management information

NASA Astrophysics Data System (ADS)

Horikawa, H.; Takaesu, M.; Sueki, K.; Takahashi, N.; Sonoda, A.; Miura, S.; Tsuboi, S.

2014-12-01

Mega-thrust earthquakes are anticipated to occur in the Nankai Trough in southwest Japan. In the source areas, we have deployed 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, including strong-motion seismometers　and quartz pressure gauges. Those stations are densely distributed with an average spatial interval of 15-20 km and cover near the trench axis to coastal areas. 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. After 2011 off the Pacific coast of Tohoku Earthquake, each local government close to Nankai Trough try to plan disaster prevention scheme. JAMSTEC will disseminate DONET data combined with research accomplishment so that they will be widely recognized as important earthquake information. In order to open DONET data observed for research to local government, we have developed a web application system, REIS　(Real-time Earthquake Information System). REIS is providing seismic waveform data to some local governments close to Nankai Trough as a pilot study. As soon as operation of DONET is ready, REIS will start full-scale operation. REIS can display seismic waveform data of DONET in real-time, users can select strong motion and pressure data, and configure the options of trace view arrangement, time scale, and amplitude. In addition to real-time monitoring, REIS can display past seismic waveform data and show earthquake epicenters on the map. In this presentation, we briefly introduce DONET system and then show our web　application system. We also discuss our future plans for further developments of REIS.

Deployment of 802.15.4 Sensor Networks for C4ISR Operations

DTIC Science & Technology

2006-06-01

43 Figure 20.MSP410CA Dense Grid Monitoring (Crossbow User’s Manual, 2005). ....................................44 Figure 21.(a)MICA2 without...Deployment of Sensor Grid (COASTS OPORD, 2006). ...56 Figure 27.Topology View of Two Nodes and Base Station .......57 Figure 28.Nodes Employing Multi...Random Access Memory TCP/IP Transmission Control Protocol/Internet Protocol TinyOS Tiny Micro Threading Operating System UARTs Universal

The Community Seismic Network: Enabling Observations Through Citizen Science Participation

NASA Astrophysics Data System (ADS)

Kohler, M. D.; Clayton, R. W.; Heaton, T. H.; Bunn, J.; Guy, R.; Massari, A.; Chandy, K. M.

2017-12-01

The Community Seismic Network is a dense accelerometer array deployed in the greater Los Angeles area and represents the future of densely instrumented urban cities where localized vibration measurements are collected continuously throughout the free-field and built environment. The hardware takes advantage of developments in the semiconductor industry in the form of inexpensive MEMS accelerometers that are each coupled with a single board computer. The data processing and archival architecture borrows from developments in cloud computing and network connectedness. The ability to deploy densely in the free field and in upper stories of mid/high-rise buildings is enabled by community hosts for sensor locations. To this end, CSN has partnered with the Los Angeles Unified School District (LAUSD), the NASA-Jet Propulsion Laboratory (JPL), and commercial and civic building owners to host sensors. At these sites, site amplification estimates from RMS noise measurements illustrate the lateral variation in amplification over length scales of 100 m or less, that correlate with gradients in the local geology such as sedimentary basins that abut crystalline rock foothills. This is complemented by high-resolution, shallow seismic velocity models obtained using an H/V method. In addition, noise statistics are used to determine the reliability of sites for ShakeMap and earthquake early warning data. The LAUSD and JPL deployments are examples of how situational awareness and centralized warning products such as ShakeMap and ShakeCast are enabled by citizen science participation. Several buildings have been instrumented with at least one triaxial accelerometer per floor, providing measurements for real-time structural health monitoring through local, customized displays. For real-time and post-event evaluation, the free-field and built environment CSN data and products illustrate the feasibility of order-of-magnitude higher spatial resolution mapping compared to what is currently possible with traditional, regional seismic networks. The JPL experiment in particular represents a miniature prototype for city-wide earthquake monitoring that combines free-field measurements for ground shaking intensities, with mid-rise building response through advanced fragility curve computations.

A dense microseismic monitoring network in Korea for uncovering relationship between seismic activity and neotectonic features

NASA Astrophysics Data System (ADS)

Kang, T.; Lee, J. M.; Kim, W.; Jo, B. G.; Chung, T.; Choi, S.

2012-12-01

A few tens of surface traces indicating movements in Quaternary were found in the southeastern part of the Korean Peninsula. Following both the geological and engineering definitions, those features are classified into "active", in geology, or "capable", in engineering, faults. On the other hand, the present-day seismicity of the region over a couple of thousand years is indistinguishable on the whole with the rest of the Korean Peninsula. It is therefore of great interest whether the present seismic activity is related to the neotectonic features or not. Either of conclusions is not intuitive in terms of the present state of seismic monitoring network in the region. Thus much interest in monitoring seismicity to provide an improved observation resolution and to lower the event-detection threshold has increased with many observations of the Quaternary faults. We installed a remote, wireless seismograph network which is composed of 20 stations with an average spacing of 10 km. Each station is equipped with a three-component Trillium Compact seismometer and Taurus digitizer. Instrumentation and analysis advancements are now offering better tools for this monitoring. This network is scheduled to be in operation over about one and a half year. In spite of the relatively short observation period, we expect that the high density of the network enables us to monitor seismic events with much lower magnitude threshold compared to the preexisting seismic network in the region. Following the Gutenberg-Richter relationship, the number of events with low magnitude is logarithmically larger than that with high magnitude. Following this rule, we can expect that many of microseismic events may reveal behavior of their causative faults, if any. We report the results of observation which has been performed over a year up to now.

Long-range acoustic observations of the Eyjafjallajökull eruption, Iceland, April-May 2010

NASA Astrophysics Data System (ADS)

Matoza, Robin S.; Vergoz, Julien; Le Pichon, Alexis; Ceranna, Lars; Green, David N.; Evers, Läslo G.; Ripepe, Maurizio; Campus, Paola; Liszka, Ludwik; Kvaerna, Tormod; Kjartansson, Einar; Höskuldsson, Ármann

2011-03-01

The April-May 2010 summit eruption of Eyjafjallajökull, Iceland, was recorded by 14 atmospheric infrasound sensor arrays at ranges between 1,700 and 3,700 km, indicating that infrasound from modest-size eruptions can propagate for thousands of kilometers in atmospheric waveguides. Although variations in both atmospheric propagation conditions and background noise levels at the sensors generate fluctuations in signal-to-noise ratios and signal detectability, array processing techniques successfully discriminate between volcanic infrasound and ambient coherent and incoherent noise. The current global infrasound network is significantly more dense and sensitive than any previously operated network and signals from large volcanic explosions are routinely recorded. Because volcanic infrasound is generated during the explosive release of fluid into the atmosphere, it is a strong indicator that an eruption has occurred. Therefore, long-range infrasonic monitoring may aid volcanic explosion detection by complementing other monitoring technologies, especially in remote regions with sparse ground-based instrument networks.

Decentralized System Identification Using Stochastic Subspace Identification for Wireless Sensor Networks

PubMed Central

Cho, Soojin; Park, Jong-Woong; Sim, Sung-Han

2015-01-01

Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model. PMID:25856325

Mahali: Space Weather Monitoring Using Multicore Mobile Devices

NASA Astrophysics Data System (ADS)

Pankratius, V.; Lind, F. D.; Coster, A. J.; Erickson, P. J.; Semeter, J. L.

2013-12-01

Analysis of Total Electron Content (TEC) measurements derived from Global Positioning System (GPS) signals has led to revolutionary new data products for space weather monitoring and ionospheric research. However, the current sensor network is sparse, especially over the oceans and in regions like Africa and Siberia, and the full potential of dense, global, real-time TEC monitoring remains to be realized. The Mahali project will prototype a revolutionary architecture that uses mobile devices, such as phones and tablets, to form a global space weather monitoring network. Mahali exploits the existing GPS infrastructure - more specifically, delays in multi-frequency GPS signals observed at the ground - to acquire a vast set of global TEC projections, with the goal of imaging multi-scale variability in the global ionosphere at unprecedented spatial and temporal resolution. With connectivity available worldwide, mobile devices are excellent candidates to establish crowd sourced global relays that feed multi-frequency GPS sensor data into a cloud processing environment. Once the data is within the cloud, it is relatively straightforward to reconstruct the structure of the space environment, and its dynamic changes. This vision is made possible owing to advances in multicore technology that have transformed mobile devices into parallel computers with several processors on a chip. For example, local data can be pre-processed, validated with other sensors nearby, and aggregated when transmission is temporarily unavailable. Intelligent devices can also autonomously decide the most practical way of transmitting data with in any given context, e.g., over cell networks or Wifi, depending on availability, bandwidth, cost, energy usage, and other constraints. In the long run, Mahali facilitates data collection from remote locations such as deserts or on oceans. For example, mobile devices on ships could collect time-tagged measurements that are transmitted at a later point in time when some connectivity is available. Our concept of the overall Mahali system will employ both auto-tuning and machine learning techniques to cope with the opportunistic nature of data collection, computational load distribution on mobile devices and in the cloud, and fault-tolerance in a dynamically changing network. "Kila Mahali" means "everywhere" in the Swahili language. This project will follow that spirit by enabling space weather data collection even in the most remote places, resulting in dramatic improvements in observational gaps that exist in space weather research today. The dense network may enable the use of the entire ionosphere as a sensor to monitor geophysical events from earthquakes to tsunamis, and other natural disasters.

Geodetic monitoring of subrosion-induced subsidence processes in urban areas

NASA Astrophysics Data System (ADS)

Kersten, Tobias; Kobe, Martin; Gabriel, Gerald; Timmen, Ludger; Schön, Steffen; Vogel, Detlef

2017-03-01

The research project SIMULTAN applies an advanced combination of geophysical, geodetic, and modelling techniques to gain a better understanding of the evolution and characteristics of sinkholes. Sinkholes are inherently related to surface deformation and, thus, of increasing societal relevance, especially in dense populated urban areas. One work package of SIMULTAN investigates an integrated approach to monitor sinkhole-related mass translations and surface deformations induced by salt dissolution. Datasets from identical and adjacent points are used for a consistent combination of geodetic and geophysical techniques. Monitoring networks are established in Hamburg and Bad Frankenhausen (Thuringia). Levelling surveys indicate subsidence rates of about 4-5 mm per year in the main subsidence areas of Bad Frankenhausen with a local maximum of 10 mm per year around the leaning church tower. Here, the concept of combining geodetic and gravimetric techniques to monitor and characterise geological processes on and below the Earth's surface is exemplary discussed for the focus area Bad Frankenhausen. For the different methods (levelling, GNSS, relative/absolute gravimetry) stable network results at identical points are obtained by the first campaigns, i.e., the results are generally in agreement.

Health monitoring of offshore structures using wireless sensor network: experimental investigations

NASA Astrophysics Data System (ADS)

Chandrasekaran, Srinivasan; Chitambaram, Thailammai

2016-04-01

This paper presents a detailed methodology of deploying wireless sensor network in offshore structures for structural health monitoring (SHM). Traditional SHM is carried out by visual inspections and wired systems, which are complicated and requires larger installation space to deploy while decommissioning is a tedious process. Wireless sensor networks can enhance the art of health monitoring with deployment of scalable and dense sensor network, which consumes lesser space and lower power consumption. Proposed methodology is mainly focused to determine the status of serviceability of large floating platforms under environmental loads using wireless sensors. Data acquired by the servers will analyze the data for their exceedance with respect to the threshold values. On failure, SHM architecture will trigger an alarm or an early warning in the form of alert messages to alert the engineer-in-charge on board; emergency response plans can then be subsequently activated, which shall minimize the risk involved apart from mitigating economic losses occurring from the accidents. In the present study, wired and wireless sensors are installed in the experimental model and the structural response, acquired is compared. The wireless system comprises of Raspberry pi board, which is programmed to transmit the acquired data to the server using Wi-Fi adapter. Data is then hosted in the webpage for further post-processing, as desired.

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System

PubMed Central

Bermudez, Sergio A.; Schrott, Alejandro G.; Tsukada, Masahiko; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F.; López, Vanessa; Leona, Marco

2017-01-01

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects. PMID:28858223

Wireless Sensor Platform for Cultural Heritage Monitoring and Modeling System.

PubMed

Klein, Levente J; Bermudez, Sergio A; Schrott, Alejandro G; Tsukada, Masahiko; Dionisi-Vici, Paolo; Kargere, Lucretia; Marianno, Fernando; Hamann, Hendrik F; López, Vanessa; Leona, Marco

2017-08-31

Results from three years of continuous monitoring of environmental conditions using a wireless sensor platform installed at The Cloisters, the medieval branch of the New York Metropolitan Museum of Art, are presented. The platform comprises more than 200 sensors that were distributed in five galleries to assess temperature and air flow and to quantify microclimate changes using physics-based and statistical models. The wireless sensor network data shows a very stable environment within the galleries, while the dense monitoring enables localized monitoring of subtle changes in air quality trends and impact of visitors on the microclimate conditions. The high spatial and temporal resolution data serves as a baseline study to understand the impact of visitors and building operations on the long-term preservation of art objects.

The investigation of using 5G millimeter-wave communications links for environmental monitoring

NASA Astrophysics Data System (ADS)

Han, Congzheng

2017-04-01

There has been significantly increasing recognition that millimeter waves from 30 GHz to 300 GHz as carriers for future 5G cellular networks. This is good for high speed, line-of-sight communication, potentially using very densely deployed infrastructure involving many small cells. High resolution, continuous and accurate monitoring of environmental conditions, such as rainfall and water vapor are of great important to meteorology, hydrology (e.g. flood warning), agriculture, environmental policy (e.g. pollution regulation) and weather forecasting. We have built a 28GHz measurement link at our research institute in central Beijing, China. This work will study the potential of using millimeter wave based wireless links to monitor environmental conditions including rainfall and water vapor.

Picking vs Waveform based detection and location methods for induced seismicity monitoring

NASA Astrophysics Data System (ADS)

Grigoli, Francesco; Boese, Maren; Scarabello, Luca; Diehl, Tobias; Weber, Bernd; Wiemer, Stefan; Clinton, John F.

2017-04-01

Microseismic monitoring is a common operation in various industrial activities related to geo-resouces, such as oil and gas and mining operations or geothermal energy exploitation. In microseismic monitoring we generally deal with large datasets from dense monitoring networks that require robust automated analysis procedures. The seismic sequences being monitored are often characterized by very many events with short inter-event times that can even provide overlapped seismic signatures. In these situations, traditional approaches that identify seismic events using dense seismic networks based on detections, phase identification and event association can fail, leading to missed detections and/or reduced location resolution. In recent years, to improve the quality of automated catalogues, various waveform-based methods for the detection and location of microseismicity have been proposed. These methods exploit the coherence of the waveforms recorded at different stations and do not require any automated picking procedure. Although this family of methods have been applied to different induced seismicity datasets, an extensive comparison with sophisticated pick-based detection and location methods is still lacking. We aim here to perform a systematic comparison in term of performance using the waveform-based method LOKI and the pick-based detection and location methods (SCAUTOLOC and SCANLOC) implemented within the SeisComP3 software package. SCANLOC is a new detection and location method specifically designed for seismic monitoring at local scale. Although recent applications have proved an extensive test with induced seismicity datasets have been not yet performed. This method is based on a cluster search algorithm to associate detections to one or many potential earthquake sources. On the other hand, SCAUTOLOC is more a "conventional" method and is the basic tool for seismic event detection and location in SeisComp3. This approach was specifically designed for regional and teleseismic applications, thus its performance with microseismic data might be limited. We analyze the performance of the three methodologies for a synthetic dataset with realistic noise conditions as well as for the first hour of continuous waveform data, including the Ml 3.5 St. Gallen earthquake, recorded by a microseismic network deployed in the area. We finally compare the results obtained all these three methods with a manually revised catalogue.

4onse: four times open & non-conventional technology for sensing the environment

NASA Astrophysics Data System (ADS)

Cannata, Massimiliano; Ratnayake, Rangageewa; Antonovic, Milan; Strigaro, Daniele; Cardoso, Mirko; Hoffmann, Marcus

2017-04-01

The availability of complete, quality and dense monitoring hydro-meteorological data is essential to address a number of practical issues including, but not limited to, flood-water and urban drainage management, climate change impact assessment, early warning and risk management, now-casting and weather predictions. Thanks to the recent technological advances such as Internet Of Things, Big Data and Ubiquitous Internet, non-conventional monitoring systems based on open technologies and low cost sensors may represent a great opportunity either as a complement of authoritative monitoring network or as a vital source of information wherever existing monitoring networks are in decline or completely missing. Nevertheless, scientific literature on such a kind of open and non-conventional monitoring systems is still limited and often relates to prototype engineering and testing in rather limited case studies. For this reason the 4onse project aims at integrating existing open technologies in the field of Free & Open Source Software, Open Hardware, Open Data, and Open Standards and evaluate this kind of system in a real case (about 30 stations) for a medium period of 2 years to better scientifically understand strengths, criticalities and applicabilities in terms of data quality; system durability; management costs; performances; sustainability. The ultimate objective is to contribute in non-conventional monitoring systems adoption based on four open technologies.

Flood Monitoring using X-band Dual-polarization Radar Network

NASA Astrophysics Data System (ADS)

Chandrasekar, V.; Wang, Y.; Maki, M.; Nakane, K.

2009-09-01

A dense weather radar network is an emerging concept advanced by the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA). Using multiple radars observing over a common will create different data outcomes depending on the characteristics of the radar units employed and the network topology. To define this a general framework is developed to describe the radar network space, and formulations are obtained that can be used for weather radar network characterization. Current weather radar surveillance networks are based upon conventional sensing paradigm of widely-separated, standalone sensing systems using long range radars that operate at wavelengths in 5-10 cm range. Such configuration has limited capability to observe close to the surface of the earth because of the earth's curvature but also has poorer resolution at far ranges. The dense network radar system, observes and measures weather phenomenon such as rainfall and severe weather close to the ground at higher spatial and temporal resolution compared to the current paradigm. In addition the dense network paradigm also is easily adaptable to complex terrain. Flooding is one of the most common natural hazards in the world. Especially, excessive development decreases the response time of urban watersheds and complex terrain to rainfall and increases the chance of localized flooding events over a small spatial domain. Successful monitoring of urban floods requires high spatiotemporal resolution, accurate precipitation estimation because of the rapid flood response as well as the complex hydrologic and hydraulic characteristics in an urban environment. This paper reviews various aspects in radar rainfall mapping in urban coverage using dense X-band dual-polarization radar networks. By reducing the maximum range and operating at X-band, one can ensure good azimuthal resolution with a small-size antenna and keep the radar beam closer to the ground. The networked topology helps to achieve satisfactory sensitivity and fast temporal update across the coverage. Strong clutter is expected from buildings in the neighborhood which act as perfect reflectors. The reduction in radar size enables flexible deployment, such as rooftop installation, with small infrastructure requirement, which is critical in a metropolitan region. Dual-polarization based technologies can be implemented for real-time mitigation of rain attenuations and accurate estimation of rainfall. The NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is developing the technologies and the systems for network centric weather observation. The Differential propagation phase (Kdp) has higher sensitivity at X-band compared to S and C band. It is attractive to use Kdp to derive Quantitative Precipitation Estimation (QPE) because it is immune to rain attenuation, calibration biases, partial beam blockage, and hail contamination. Despite the advantage of Kdp for radar QPE, the estimation of Kdp itself is a challenge as the range derivative of the differential propagation phase profiles. An adaptive Kdp algorithm was implemented in the CASA IP1 testbed that substantially reduces the fluctuation in light rain and the bias at heavy rain. The Kdp estimation also benefits from the higher resolution in the IP1 radar network. The performance of the IP1 QPE product was evaluated for all major rain events against the USDA Agriculture Research Service's gauge network (MicroNet) in the Little Washita watershed, which comprises 20 weather stations in the center of the test bed. The cross-comparison with gauge measurements shows excellent agreement for the storm events during the Spring Experiments of 2007 and 2008. The hourly rainfall estimates compared to the gauge measurements have a very small bias of few percent and a normalized standard error of 21%. The IP1 testbed was designed with overlapping coverage among its radar nodes. The study area is covered by multiple radars and the aspect of network composition is also evaluated. The independence of Kdp on the radar calibration enables flexibility in combining the collocated Kdp estimates from all the radar nodes. Radar QPE can be improved from the composite Kdp field from the radar with lowest beam height and nearest slant range, or from the radar with the best Kdp estimates. More importantly, the data availability is greatly enhanced by the overlapped topology in cases of heavy rainfall, demonstrating the operational strength of the network centric radar system. The National Research Institute for Earth Science and Disaster Prevention (NIED), Japan, is in the process of establishing an X-band radar network (X-Net) in Metropolitan Tokyo area. Colorado State University and NIED have formed a partnership to initiate a joint program for urban flood monitoring using X-band dual-polarization radar network. This paper will also present some preliminary plans for this program.

Bridge damage detection using spatiotemporal patterns extracted from dense sensor network

NASA Astrophysics Data System (ADS)

Liu, Chao; Gong, Yongqiang; Laflamme, Simon; Phares, Brent; Sarkar, Soumik

2017-01-01

The alarmingly degrading state of transportation infrastructures combined with their key societal and economic importance calls for automatic condition assessment methods to facilitate smart management of maintenance and repairs. With the advent of ubiquitous sensing and communication capabilities, scalable data-driven approaches is of great interest, as it can utilize large volume of streaming data without requiring detailed physical models that can be inaccurate and computationally expensive to run. Properly designed, a data-driven methodology could enable fast and automatic evaluation of infrastructures, discovery of causal dependencies among various sub-system dynamic responses, and decision making with uncertainties and lack of labeled data. In this work, a spatiotemporal pattern network (STPN) strategy built on symbolic dynamic filtering (SDF) is proposed to explore spatiotemporal behaviors in a bridge network. Data from strain gauges installed on two bridges are generated using finite element simulation for three types of sensor networks from a density perspective (dense, nominal, sparse). Causal relationships among spatially distributed strain data streams are extracted and analyzed for vehicle identification and detection, and for localization of structural degradation in bridges. Multiple case studies show significant capabilities of the proposed approach in: (i) capturing spatiotemporal features to discover causality between bridges (geographically close), (ii) robustness to noise in data for feature extraction, (iii) detecting and localizing damage via comparison of bridge responses to similar vehicle loads, and (iv) implementing real-time health monitoring and decision making work flow for bridge networks. Also, the results demonstrate increased sensitivity in detecting damages and higher reliability in quantifying the damage level with increase in sensor network density.

Multi-criteria anomaly detection in urban noise sensor networks.

PubMed

Dauwe, Samuel; Oldoni, Damiano; De Baets, Bernard; Van Renterghem, Timothy; Botteldooren, Dick; Dhoedt, Bart

2014-01-01

The growing concern of citizens about the quality of their living environment and the emergence of low-cost microphones and data acquisition systems triggered the deployment of numerous noise monitoring networks spread over large geographical areas. Due to the local character of noise pollution in an urban environment, a dense measurement network is needed in order to accurately assess the spatial and temporal variations. The use of consumer grade microphones in this context appears to be very cost-efficient compared to the use of measurement microphones. However, the lower reliability of these sensing units requires a strong quality control of the measured data. To automatically validate sensor (microphone) data, prior to their use in further processing, a multi-criteria measurement quality assessment model for detecting anomalies such as microphone breakdowns, drifts and critical outliers was developed. Each of the criteria results in a quality score between 0 and 1. An ordered weighted average (OWA) operator combines these individual scores into a global quality score. The model is validated on datasets acquired from a real-world, extensive noise monitoring network consisting of more than 50 microphones. Over a period of more than a year, the proposed approach successfully detected several microphone faults and anomalies.

Estimating National-scale Emissions using Dense Monitoring Networks

NASA Astrophysics Data System (ADS)

Ganesan, A.; Manning, A.; Grant, A.; Young, D.; Oram, D.; Sturges, W. T.; Moncrieff, J. B.; O'Doherty, S.

2014-12-01

The UK's DECC (Deriving Emissions linked to Climate Change) network consists of four greenhouse gas measurement stations that are situated to constrain emissions from the UK and Northwest Europe. These four stations are located in Mace Head (West Coast of Ireland), and on telecommunication towers at Ridge Hill (Western England), Tacolneston (Eastern England) and Angus (Eastern Scotland). With the exception of Angus, which currently only measures carbon dioxide (CO2) and methane (CH4), the remaining sites are additionally equipped to monitor nitrous oxide (N2O). We present an analysis of the network's CH4 and N2O observations from 2011-2013 and compare derived top-down regional emissions with bottom-up inventories, including a recently produced high-resolution inventory (UK National Atmospheric Emissions Inventory). As countries are moving toward national-level emissions estimation, we also address some of the considerations that need to be made when designing these national networks. One of the novel aspects of this work is that we use a hierarchical Bayesian inversion framework. This methodology, which has newly been applied to greenhouse gas emissions estimation, is designed to estimate temporally and spatially varying model-measurement uncertainties and correlation scales, in addition to fluxes. Through this analysis, we demonstrate the importance of characterizing these covariance parameters in order to properly use data from high-density monitoring networks. This UK case study highlights the ways in which this new inverse framework can be used to address some of the limitations of traditional Bayesian inverse methods.

2D PWV monitoring of a wide and orographically complex area with a low dense GNSS network

NASA Astrophysics Data System (ADS)

Ferrando, Ilaria; Federici, Bianca; Sguerso, Domenico

2018-04-01

This study presents an innovative procedure to monitor the precipitable water vapor (PWV) content of a wide and orographically complex area with low-density networks. The procedure, termed G4M (global navigation satellite system, GNSS, for Meteorology), has been developed in a geographic information system (GIS) environment using the free and open source GRASS GIS software (https://grass.osgeo.org). The G4M input data are zenith total delay estimates obtained from GNSS permanent stations network adjustment and pressure ( P) and temperature ( T) observations using existing infrastructure networks with different geographic distributions in the study area. In spite of the wide sensor distribution, the procedure produces 2D maps with high spatiotemporal resolution (up to 250 m and 6 min) based on a simplified mathematical model including data interpolation, which was conceived by the authors to describe the atmosphere's physics. In addition to PWV maps, the procedure provides ΔPWV and heterogeneity index maps: the former represents PWV variations with respect to a "calm" moment, which are useful for monitoring the PWV evolution; and the latter are promising indicators to localize severe meteorological events in time and space. This innovative procedure is compared with meteorological simulations in this paper; in addition, an application to a severe event that occurred in Genoa (Italy) is presented.[Figure not available: see fulltext.

Towards Integrated Marmara Strong Motion Network

NASA Astrophysics Data System (ADS)

Durukal, E.; Erdik, M.; Safak, E.; Ansal, A.; Ozel, O.; Alcik, H.; Mert, A.; Kafadar, N.; Korkmaz, A.; Kurtulus, A.

2009-04-01

Istanbul has a 65% chance of having a magnitude 7 or above earthquake within the next 30 years. As part of the preparations for the future earthquake, strong motion networks have been installed in and around Istanbul. The Marmara Strong Motion Network, operated by the Department of Earthquake Engineering of Kandilli Observatory and Earthquake Research Institute, encompasses permanent systems outlined below. It is envisaged that the networks will be run by a single entity responsible for technical management and maintanence, as well as for data management, archiving and dissemination through dedicated web-based interfaces. • Istanbul Earthquake Rapid Response and Early Warning System - IERREWS (one hundred 18-bit accelerometers for rapid response; ten 24-bit accelerometers for early warning) • IGDAŞ Gas Shutoff Network (100 accelerometers to be installed in 2010 and integrated with IERREWS) • Structural Monitoring Arrays - Fatih Sultan Mehmet Suspension Bridge (1200m-long suspension bridge across the Bosphorus, five 3-component accelerometers + GPS sensors) - Hagia Sophia Array (1500-year-old historical edifice, 9 accelerometers) - Süleymaniye Mosque Array (450-year-old historical edifice,9 accelerometers) - Fatih Mosque Array (237-year-old historical edifice, 9 accelerometers) - Kanyon Building Array (high-rise office building, 5 accelerometers) - Isbank Tower Array (high-rise office building, 5 accelerometers) - ENRON Array (power generation facility, 4 acelerometers) - Mihrimah Sultan Mosque Array (450-year-old historical edifice,9 accelerometers + tiltmeters, to be installed in 2009) - Sultanahmet Mosque Array, (390-year-old historical edifice, 9 accelerometers + tiltmeters, to be installed in 2009) • Special Arrays - Atakoy Vertical Array (four 3-component accelerometers at 25, 50, 75, and 150 m depths) - Marmara Tube Tunnel (1400 m long submerged tunnel, 128 ch. accelerometric data, 24 ch. strain data, to be installed in 2010) - Air-Force Academy Array (72 ch. dense accelerometric array to be installed in 2010) - Gemlik Array (a dense basin array of 8 stations, to be installed in 2010) The objectives of these systems and networks are: (1) to produce rapid earthquake intensity, damage and loss assessment information after an earthquake (in the case of IERREWS), (2) to monitor conditions of structural systems, (3) to develop real-time data processing, analysis, and damage detection and location tools (in the case of structural networks) after an extreme event, (4) to assess spatial properties of strong ground motion and ground strain, and to characterise basin response (in the case of special arrays), (5) to investigate site response and wave propagation (in the case of vertical array). Ground motion data obtained from these strong motion networks have and are being used for investigations of attenuation, spatial variation (coherence), simulation benchmarking, source modeling, site response, seismic microzonation, system identification and structural model verification and structural health control. In addition to the systems and networks outlined above there are two temporary networks: KIMNET - a dense urban noise and microtremor network consisting of 50 broadband stations expected to be operational in mid 2009, and SOSEWIN - a 20-station, self-organizing structural integrated array at Ataköy in Istanbul.

Data Verification Tools for Minimizing Management Costs of Dense Air-Quality Monitoring Networks.

PubMed

Miskell, Georgia; Salmond, Jennifer; Alavi-Shoshtari, Maryam; Bart, Mark; Ainslie, Bruce; Grange, Stuart; McKendry, Ian G; Henshaw, Geoff S; Williams, David E

2016-01-19

Aiming at minimizing the costs, both of capital expenditure and maintenance, of an extensive air-quality measurement network, we present simple statistical methods that do not require extensive training data sets for automated real-time verification of the reliability of data delivered by a spatially dense hybrid network of both low-cost and reference ozone measurement instruments. Ozone is a pollutant that has a relatively smooth spatial spread over a large scale although there can be significant small-scale variations. We take advantage of these characteristics and demonstrate detection of instrument calibration drift within a few days using a rolling 72 h comparison of hourly averaged data from the test instrument with that from suitably defined proxies. We define the required characteristics of the proxy measurements by working from a definition of the network purpose and specification, in this case reliable determination of the proportion of hourly averaged ozone measurements that are above a threshold in any given day, and detection of calibration drift of greater than ±30% in slope or ±5 parts-per-billion in offset. By analyzing results of a study of an extensive deployment of low-cost instruments in the Lower Fraser Valley, we demonstrate that proxies can be established using land-use criteria and that simple statistical comparisons can identify low-cost instruments that are not stable and therefore need replacing. We propose that a minimal set of compliant reference instruments can be used to verify the reliability of data from a much more extensive network of low-cost devices.

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

NASA Astrophysics Data System (ADS)

Beaufort, Aurélien; Lamouroux, Nicolas; Pella, Hervé; Datry, Thibault; Sauquet, Eric

2018-05-01

Headwater streams represent a substantial proportion of river systems and many of them have intermittent flows due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate over time the daily probability of drying (defined at the regional scale). Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using an independent, dense regional dataset of intermittence observations and observations of the year 2017 excluded from the calibration. The resulting models were used to extrapolate the daily regional probability of drying in France: (i) over the period 2011-2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989-2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level. The two empirical regression models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, the worst performances were obtained in mountainous regions. Finally, temporal projections (1989-2016) suggested the highest probabilities of intermittence (> 35 %) in 1989-1991, 2003 and 2005. A high density of intermittence observations improved the information provided by gauging stations and piezometers to extrapolate the temporal variability of intermittent rivers and ephemeral streams.

Tagging and tracking individual networks within a complex mitochondrial web with photoactivatable GFP.

PubMed

Twig, Gilad; Graf, Solomon A; Wikstrom, Jakob D; Mohamed, Hibo; Haigh, Sarah E; Elorza, Alvaro; Deutsch, Motti; Zurgil, Naomi; Reynolds, Nicole; Shirihai, Orian S

2006-07-01

Assembly of mitochondria into networks supports fuel metabolism and calcium transport and is involved in the cellular response to apoptotic stimuli. A mitochondrial network is defined as a continuous matrix lumen whose boundaries limit molecular diffusion. Observation of individual networks has proven challenging in live cells that possess dense populations of mitochondria. Investigation into the electrical and morphological properties of mitochondrial networks has therefore not yielded consistent conclusions. In this study we used matrix-targeted, photoactivatable green fluorescent protein to tag single mitochondrial networks. This approach, coupled with real-time monitoring of mitochondrial membrane potential, permitted the examination of matrix lumen continuity and fusion and fission events over time. We found that adjacent and intertwined mitochondrial structures often represent a collection of distinct networks. We additionally found that all areas of a single network are invariably equipotential, suggesting that a heterogeneous pattern of membrane potential within a cell's mitochondria represents differences between discrete networks. Interestingly, fission events frequently occurred without any gross morphological changes and particularly without fragmentation. These events, which are invisible under standard confocal microscopy, redefine the mitochondrial network boundaries and result in electrically disconnected daughter units.

Regional trend analysis of surface ozone observations from monitoring networks in eastern North America, Europe and East Asia

NASA Astrophysics Data System (ADS)

Chang, K. L.; Petropavlovskikh, I. V.; Cooper, O. R.; Schultz, M.; Wang, T.

2017-12-01

Surface ozone is a greenhouse gas and pollutant detrimental to human health and crop and ecosystem productivity. The Tropospheric Ozone Assessment Report (TOAR) is designed to provide the research community with an up-to-date observation-based overview of tropospheric ozone's global distribution and trends. The TOAR Surface Ozone Database contains ozone metrics at thousands of monitoring sites around the world, densely clustered across mid-latitude North America, western Europe and East Asia. Calculating regional ozone trends across these locations is challenging due to the uneven spacing of the monitoring sites across urban and rural areas. To meet this challenge we conducted a spatial and temporal trend analysis of several TOAR ozone metrics across these three regions for summertime (April-September) 2000-2014, using the generalized additive mixed model (GAMM). Our analysis indicates that East Asia has the greatest human and plant exposure to ozone pollution among investigating regions, with increasing ozone levels through 2014. The results also show that ozone mixing ratios continue to decline significantly over eastern North America and Europe, however, there is less evidence for decreases of daytime average ozone at urban sites. The present-day spatial coverage of ozone monitors in East Asia (South Korea and Japan) and eastern North America is adequate for estimating regional trends by simply taking the average of the individual trends at each site. However the European network is more sparsely populated across its northern and eastern regions and therefore a simple average of the individual trends at each site does not yield an accurate regional trend. This analysis demonstrates that the GAMM technique can be used to assess the regional representativeness of existing monitoring networks, indicating those networks for which a regional trend can be obtained by simply averaging the trends of all individual sites and those networks that require a more sophisticated statistical approach.

Wireless Concrete Strength Monitoring of Wind Turbine Foundations.

PubMed

Perry, Marcus; Fusiek, Grzegorz; Niewczas, Pawel; Rubert, Tim; McAlorum, Jack

2017-12-16

Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete's initial performance, and this can encourage both costly over-design and inaccurate prognoses of structural health. Here, we demonstrate the field application of a dense, wireless thermocouple network to monitor the strength development of an onshore, reinforced-concrete wind turbine foundation. Up-to-date methods in fly ash concrete strength and maturity modelling are used to estimate the distribution and evolution of foundation strength over 29 days of curing. Strength estimates are verified by core samples, extracted from the foundation base. In addition, an artificial neural network, trained using temperature data, is exploited to demonstrate that distributed concrete strengths can be estimated for foundations using only sparse thermocouple data. Our techniques provide a practical alternative to computational models, and could assist site operators in making more informed decisions about foundation design, construction, operation and maintenance.

Wireless Concrete Strength Monitoring of Wind Turbine Foundations

PubMed Central

Niewczas, Pawel; Rubert, Tim

2017-01-01

Wind turbine foundations are typically cast in place, leaving the concrete to mature under environmental conditions that vary in time and space. As a result, there is uncertainty around the concrete’s initial performance, and this can encourage both costly over-design and inaccurate prognoses of structural health. Here, we demonstrate the field application of a dense, wireless thermocouple network to monitor the strength development of an onshore, reinforced-concrete wind turbine foundation. Up-to-date methods in fly ash concrete strength and maturity modelling are used to estimate the distribution and evolution of foundation strength over 29 days of curing. Strength estimates are verified by core samples, extracted from the foundation base. In addition, an artificial neural network, trained using temperature data, is exploited to demonstrate that distributed concrete strengths can be estimated for foundations using only sparse thermocouple data. Our techniques provide a practical alternative to computational models, and could assist site operators in making more informed decisions about foundation design, construction, operation and maintenance. PMID:29258176

Monitoring of heavy metal concentrations in home outdoor air using moss bags.

PubMed

Rivera, Marcela; Zechmeister, Harald; Medina-Ramón, Mercedes; Basagaña, Xavier; Foraster, Maria; Bouso, Laura; Moreno, Teresa; Solanas, Pascual; Ramos, Rafael; Köllensperger, Gunda; Deltell, Alexandre; Vizcaya, David; Künzli, Nino

2011-04-01

One monitoring station is insufficient to characterize the high spatial variation of traffic-related heavy metals within cities. We tested moss bags (Hylocomium splendens), deployed in a dense network, for the monitoring of metals in outdoor air and characterized metals' long-term spatial distribution and its determinants in Girona, Spain. Mosses were exposed outside 23 homes for two months; NO₂ was monitored for comparison. Metals were not highly correlated with NO₂ and showed higher spatial variation than NO₂. Regression models explained 61-85% of Cu, Cr, Mo, Pb, Sb, Sn, and Zn and 72% of NO₂ variability. Metals were strongly associated with the number of bus lines in the nearest street. Heavy metals are an alternative traffic-marker to NO₂ given their toxicological relevance, stronger association with local traffic and higher spatial variability. Monitoring heavy metals with mosses is appealing, particularly for long-term exposure assessment, as mosses can remain on site many months without maintenance. Copyright © 2010 Elsevier Ltd. All rights reserved.

Assessing the detection capability of a dense infrasound network in the southern Korean Peninsula

NASA Astrophysics Data System (ADS)

Che, Il-Young; Le Pichon, Alexis; Kim, Kwangsu; Shin, In-Cheol

2017-08-01

The Korea Infrasound Network (KIN) is a dense seismoacoustic array network consisting of eight small-aperture arrays with an average interarray spacing of ∼100 km. The processing of the KIN historical recordings over 10 yr in the 0.05-5 Hz frequency band shows that the dominant sources of signals are microbaroms and human activities. The number of detections correlates well with the seasonal and daily variability of the stratospheric wind dynamics. The quantification of the spatiotemporal variability of the KIN detection performance is simulated using a frequency-dependent semi-empirical propagation modelling technique. The average detection thresholds predicted for the region of interest by using both the KIN arrays and the International Monitoring System (IMS) infrasound station network at a given frequency of 1.6 Hz are estimated to be 5.6 and 10.0 Pa for two- and three-station coverage, respectively, which was about three times lower than the thresholds predicted by using only the IMS stations. The network performance is significantly enhanced from May to August, with detection thresholds being one order of magnitude lower than the rest of the year due to prevailing steady stratospheric winds. To validate the simulations, the amplitudes of ground-truth repeated surface mining explosions at an open-pit limestone mine were measured over a 19-month period. Focusing on the spatiotemporal variability of the stratospheric winds which control to first order where infrasound signals are expected to be detected, the predicted detectable signal amplitude at the mine and the detection capability at one KIN array located at a distance of 175 km are found to be in good agreement with the observations from the measurement campaign. The detection threshold in summer is ∼2 Pa and increases up to ∼300 Pa in winter. Compared with the low and stable thresholds in summer, the high temporal variability of the KIN performance is well predicted throughout the year. Simulations show that the performance of the global infrasound network of the IMS is significantly improved by adding KIN. This study shows the usefulness of dense regional networks to enhance detection capability in regions of interest in the context of future verification of the Comprehensive Nuclear-Test-Ban Treaty.

An iterative network partition algorithm for accurate identification of dense network modules

PubMed Central

Sun, Siqi; Dong, Xinran; Fu, Yao; Tian, Weidong

2012-01-01

A key step in network analysis is to partition a complex network into dense modules. Currently, modularity is one of the most popular benefit functions used to partition network modules. However, recent studies suggested that it has an inherent limitation in detecting dense network modules. In this study, we observed that despite the limitation, modularity has the advantage of preserving the primary network structure of the undetected modules. Thus, we have developed a simple iterative Network Partition (iNP) algorithm to partition a network. The iNP algorithm provides a general framework in which any modularity-based algorithm can be implemented in the network partition step. Here, we tested iNP with three modularity-based algorithms: multi-step greedy (MSG), spectral clustering and Qcut. Compared with the original three methods, iNP achieved a significant improvement in the quality of network partition in a benchmark study with simulated networks, identified more modules with significantly better enrichment of functionally related genes in both yeast protein complex network and breast cancer gene co-expression network, and discovered more cancer-specific modules in the cancer gene co-expression network. As such, iNP should have a broad application as a general method to assist in the analysis of biological networks. PMID:22121225

Evaluation of High-Resolution Precipitation Estimates from Satellites during July 2012 Beijing Flood Event Using Dense Rain Gauge Observations

PubMed Central

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing. PMID:24691358

Evaluation of high-resolution precipitation estimates from satellites during July 2012 Beijing flood event using dense rain gauge observations.

PubMed

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.

Nanotwinned metal MEMS films with unprecedented strength and stability

PubMed Central

Sim, Gi-Dong; Krogstad, Jessica A.; Reddy, K. Madhav; Xie, Kelvin Y.; Valentino, Gianna M.; Weihs, Timothy P.; Hemker, Kevin J.

2017-01-01

Silicon-based microelectromechanical systems (MEMS) sensors have become ubiquitous in consumer-based products, but realization of an interconnected network of MEMS devices that allows components to be remotely monitored and controlled, a concept often described as the “Internet of Things,” will require a suite of MEMS materials and properties that are not currently available. We report on the synthesis of metallic nickel-molybdenum-tungsten films with direct current sputter deposition, which results in fully dense crystallographically textured films that are filled with nanotwins. These films exhibit linear elastic mechanical behavior and tensile strengths exceeding 3 GPa, which is unprecedented for materials that are compatible with wafer-level device fabrication processes. The ultrahigh strength is attributed to a combination of solid solution strengthening and the presence of dense nanotwins. These films also have excellent thermal and mechanical stability, high density, and electrical properties that are attractive for next-generation metal MEMS applications. PMID:28782015

Investigation of Alien Wavelength Quality in Live Multi-Domain, Multi-Vendor Link Using Advanced Simulation Tool

NASA Astrophysics Data System (ADS)

Nordal Petersen, Martin; Nuijts, Roeland; Lange Bjørn, Lars

2014-05-01

This article presents an advanced optical model for simulation of alien wavelengths in multi-domain and multi-vendor dense wavelength-division multiplexing networks. The model aids optical network planners with a better understanding of the non-linear effects present in dense wavelength-division multiplexing systems and better utilization of alien wavelengths in future applications. The limiting physical effects for alien wavelengths are investigated in relation to power levels, channel spacing, and other factors. The simulation results are verified through experimental setup in live multi-domain dense wavelength-division multiplexing systems between two national research networks: SURFnet in Holland and NORDUnet in Denmark.

Mitigation of the consequence of seismically induced damage on a utility water network by means of next generation SCADA

NASA Astrophysics Data System (ADS)

Robertson, Jamie; Shinozuka, Masanobu; Wu, Felix

2011-04-01

When a lifeline system such as a water delivery network is damaged due to a severe earthquake, it is critical to identify its location and extent of the damage in real time in order to minimize the potentially disastrous consequence such damage could otherwise entail. This paper demonstrates how the degree of such minimization can be estimated qualitatively by using the water delivery system of Irvine Water Ranch District (IRWD) as testbed, when it is subjected to magnitude 6.6 San Joaquin Hills Earthquake. In this demonstration, we consider two cases when the IRWD system is equipped or not equipped with a next generation SCADA which consists of a network of MEMS acceleration sensors densely populated and optimally located. These sensors are capable of identifying the location and extent of the damage as well as transmitting the data to the SCADA center for monitoring and control.

Decentralized system identification using stochastic subspace identification on wireless smart sensor networks

NASA Astrophysics Data System (ADS)

Sim, Sung-Han; Spencer, Billie F., Jr.; Park, Jongwoong; Jung, Hyungjo

2012-04-01

Wireless Smart Sensor Networks (WSSNs) facilitates a new paradigm to structural identification and monitoring for civil infrastructure. Conventional monitoring systems based on wired sensors and centralized data acquisition and processing have been considered to be challenging and costly due to cabling and expensive equipment and maintenance costs. WSSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. Thus, several system identification methods have been implemented to process sensor data and extract essential information, including Natural Excitation Technique with Eigensystem Realization Algorithm, Frequency Domain Decomposition (FDD), and Random Decrement Technique (RDT); however, Stochastic Subspace Identification (SSI) has not been fully utilized in WSSNs, while SSI has the strong potential to enhance the system identification. This study presents a decentralized system identification using SSI in WSSNs. The approach is implemented on MEMSIC's Imote2 sensor platform and experimentally verified using a 5-story shear building model.

Sensing Models and Sensor Network Architectures for Transport Infrastructure Monitoring in Smart Cities

NASA Astrophysics Data System (ADS)

Simonis, Ingo

2015-04-01

Transport infrastructure monitoring and analysis is one of the focus areas in the context of smart cities. With the growing number of people moving into densely populated urban metro areas, precise tracking of moving people and goods is the basis for profound decision-making and future planning. With the goal of defining optimal extensions and modifications to existing transport infrastructures, multi-modal transport has to be monitored and analysed. This process is performed on the basis of sensor networks that combine a variety of sensor models, types, and deployments within the area of interest. Multi-generation networks, consisting of a number of sensor types and versions, are causing further challenges for the integration and processing of sensor observations. These challenges are not getting any smaller with the development of the Internet of Things, which brings promising opportunities, but is currently stuck in a type of protocol war between big industry players from both the hardware and network infrastructure domain. In this paper, we will highlight how the OGC suite of standards, with the Sensor Web standards developed by the Sensor Web Enablement Initiative together with the latest developments by the Sensor Web for Internet of Things community can be applied to the monitoring and improvement of transport infrastructures. Sensor Web standards have been applied in the past to pure technical domains, but need to be broadened now in order to meet new challenges. Only cross domain approaches will allow to develop satisfying transport infrastructure approaches that take into account requirements coming form a variety of sectors such as tourism, administration, transport industry, emergency services, or private people. The goal is the development of interoperable components that can be easily integrated within data infrastructures and follow well defined information models to allow robust processing.

Application and API for Real-time Visualization of Ground-motions and Tsunami

NASA Astrophysics Data System (ADS)

Aoi, S.; Kunugi, T.; Suzuki, W.; Kubo, T.; Nakamura, H.; Azuma, H.; Fujiwara, H.

2015-12-01

Due to the recent progress of seismograph and communication environment, real-time and continuous ground-motion observation becomes technically and economically feasible. K-NET and KiK-net, which are nationwide strong motion networks operated by NIED, cover all Japan by about 1750 stations in total. More than half of the stations transmit the ground-motion indexes and/or waveform data in every second. Traditionally, strong-motion data were recorded by event-triggering based instruments with non-continues telephone line which is connected only after an earthquake. Though the data from such networks mainly contribute to preparations for future earthquakes, huge amount of real-time data from dense network are expected to directly contribute to the mitigation of ongoing earthquake disasters through, e.g., automatic shutdown plants and helping decision-making for initial response. By generating the distribution map of these indexes and uploading them to the website, we implemented the real-time ground motion monitoring system, Kyoshin (strong-motion in Japanese) monitor. This web service (www.kyoshin.bosai.go.jp) started in 2008 and anyone can grasp the current ground motions of Japan. Though this service provides only ground-motion map in GIF format, to take full advantage of real-time strong-motion data to mitigate the ongoing disasters, digital data are important. We have developed a WebAPI to provide real-time data and related information such as ground motions (5 km-mesh) and arrival times estimated from EEW (earthquake early warning). All response data from this WebAPI are in JSON format and are easy to parse. We also developed Kyoshin monitor application for smartphone, 'Kmoni view' using the API. In this application, ground motions estimated from EEW are overlapped on the map with the observed one-second-interval indexes. The application can playback previous earthquakes for demonstration or disaster drill. In mobile environment, data traffic and battery are limited and it is not practical to regularly visualize all the data. The application has automatic starting (pop-up) function triggered by EEW. Similar WebAPI and application for tsunami are being prepared using the pressure data recorded by dense offshore observation network (S-net), which is under construction along the Japan Trench.

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

PubMed

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

2016-07-18

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

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Chandy, M.; Krause, A.

2010-12-01

In collaboration with computer science and earthquake engineering, we are developing a dense network of low-cost accelerometers that send their data via the Internet to a cloud-based center. The goal is to make block-by-block measurements of ground shaking in urban areas, which will provide emergency response information in the case of large earthquakes, and an unprecedented high-frequency seismic array to study structure and the earthquake process with moderate shaking. When deployed in high-rise buildings they can be used to monitor the state of health of the structure. The sensors are capable of a resolution of approximately 80 micro-g, connect via USB ports to desktop computers, and cost about $100 each. The network will adapt to its environment by using network-wide machine learning to adjust the picking sensitivity. We are also looking into using other motion sensing devices such as cell phones. For a pilot project, we plan to deploy more than 1000 sensors in the greater Pasadena area. The system is easily adaptable to other seismically vulnerable urban areas.

Intra-Urban Movement Flow Estimation Using Location Based Social Networking Data

NASA Astrophysics Data System (ADS)

Kheiri, A.; Karimipour, F.; Forghani, M.

2015-12-01

In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook, which have attracted an increasing number of users and greatly enriched their urban experience. Location-based social network data, as a new travel demand data source, seems to be an alternative or complement to survey data in the study of mobility behavior and activity analysis because of its relatively high access and low cost. In this paper, three OD estimation models have been utilized in order to investigate their relative performance when using Location-Based Social Networking (LBSN) data. For this, the Foursquare LBSN data was used to analyze the intra-urban movement behavioral patterns for the study area, Manhattan, the most densely populated of the five boroughs of New York city. The outputs of models are evaluated using real observations based on different criterions including distance distribution, destination travel constraints. The results demonstrate the promising potential of using LBSN data for urban travel demand analysis and monitoring.

An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.

PubMed

Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun

2015-12-03

Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

Single-station monitoring of volcanoes using seismic ambient noise

NASA Astrophysics Data System (ADS)

De Plaen, Raphael S. M.; Lecocq, Thomas; Caudron, Corentin; Ferrazzini, Valérie; Francis, Olivier

2016-08-01

Seismic ambient noise cross correlation is increasingly used to monitor volcanic activity. However, this method is usually limited to volcanoes equipped with large and dense networks of broadband stations. The single-station approach may provide a powerful and reliable alternative to the classical "cross-station" approach when measuring variation of seismic velocities. We implemented it on the Piton de la Fournaise in Reunion Island, a very active volcano with a remarkable multidisciplinary continuous monitoring. Over the past decade, this volcano has been increasingly studied using the traditional cross-correlation technique and therefore represents a unique laboratory to validate our approach. Our results, tested on stations located up to 3.5 km from the eruptive site, performed as well as the classical approach to detect the volcanic eruption in the 1-2 Hz frequency band. This opens new perspectives to successfully forecast volcanic activity at volcanoes equipped with a single three-component seismometer.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement-The Promise and the Current Reality.

PubMed

Broday, David M

2017-10-02

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented.

Wireless Distributed Environmental Sensor Networks for Air Pollution Measurement—The Promise and the Current Reality

PubMed Central

2017-01-01

The evaluation of the effects of air pollution on public health and human-wellbeing requires reliable data. Standard air quality monitoring stations provide accurate measurements of airborne pollutant levels, but, due to their sparse distribution, they cannot capture accurately the spatial variability of air pollutant concentrations within cities. Dedicated in-depth field campaigns have dense spatial coverage of the measurements but are held for relatively short time periods. Hence, their representativeness is limited. Moreover, the oftentimes integrated measurements represent time-averaged records. Recent advances in communication and sensor technologies enable the deployment of dense grids of Wireless Distributed Environmental Sensor Networks for air quality monitoring, yet their capability to capture urban-scale spatiotemporal pollutant patterns has not been thoroughly examined to date. Here, we summarize our studies on the practicalities of using data streams from sensor nodes for air quality measurement and the required methods to tune the results to different stakeholders and applications. We summarize the results from eight cities across Europe, five sensor technologies-three stationary (with one tested also while moving) and two personal sensor platforms, and eight ambient pollutants. Overall, few sensors showed an exceptional and consistent performance, which can shed light on the fine spatiotemporal urban variability of pollutant concentrations. Stationary sensor nodes were more reliable than personal nodes. In general, the sensor measurements tend to suffer from the interference of various environmental factors and require frequent calibrations. This calls for the development of suitable field calibration procedures, and several such in situ field calibrations are presented. PMID:28974042

Monitoring the Restart of a High-Rate Wastewater Disposal Well in the Val d'Agri Oilfield (Italy)

NASA Astrophysics Data System (ADS)

De Gori, P.; Improta, L.; Moretti, M.; Colasanti, G.; Criscuoli, F.

2015-12-01

The Val d'Agri Quaternary basin in the Southern Apennine range of Italy hosts the largest inland oil field in Europe. Wastewater coming from the oil exploitation is re-injected by a high-rate disposal well into strongly fractured limestones of the hydrocarbon carbonate reservoir. Disposal activity has induced micro-seismicity since the beginning of injection in June 2006. Around 220 small magnitude events (ML < 2.3) were recorded between 2006 and 2013 by the trigger-mode monitoring local network managed by the oil company and by the National Seismic Network of Istituto Nazionale di Geofisica e Vulcanologia. The induced micro-seismicity illuminated a pre-existing high-angle fault located 1 km below the well. Since June 2006, wastewater has been re-injected with only short interruptions due acid stimulations. In January 2015 disposal activity was halted due to technical operations in the oil refinery and wastewater injection restarted after two weeks. We installed 5 short-period stations within 10 km of the disposal well to carefully monitor the re-start phase and the subsequent 3 months of disposal activity. This temporary network was complemented by stations of the National Seismic Network giving this final configuration:9 stations within 10 km of the well with the closest station 2 km apart, 13 stations within 20 km. Here we report on the preliminary analysis of the local earthquake recorded during the survey focusing on the events occurred in the injection area. The seismicity rate is compared with injection data.In spite of the dense network, we found that the rate of induced seismicity (both the number and energy of events) is very low when compared to the seismicity recorded during the first 5 years of injection activity carried out with comparable rate and pressure.

Using algebra for massively parallel processor design and utilization

NASA Technical Reports Server (NTRS)

Campbell, Lowell; Fellows, Michael R.

1990-01-01

This paper summarizes the author's advances in the design of dense processor networks. Within is reported a collection of recent constructions of dense symmetric networks that provide the largest know values for the number of nodes that can be placed in a network of a given degree and diameter. The constructions are in the range of current potential engineering significance and are based on groups of automorphisms of finite-dimensional vector spaces.

RESIF Seismology Datacentre : Recently Released Data and New Services. Computing with Dense Seisimic Networks Data.

NASA Astrophysics Data System (ADS)

Volcke, P.; Pequegnat, C.; Grunberg, M.; Lecointre, A.; Bzeznik, B.; Wolyniec, D.; Engels, F.; Maron, C.; Cheze, J.; Pardo, C.; Saurel, J. M.; André, F.

2015-12-01

RESIF is a nationwide french project aimed at building a high quality observation system to observe and understand the inner earth. RESIF deals with permanent seismic networks data as well as mobile networks data, including dense/semi-dense arrays. RESIF project is distributed among different nodes providing qualified data to the main datacentre in Université Grenoble Alpes, France. Data control and qualification is performed by each individual nodes : the poster will provide some insights on RESIF broadband seismic component data quality control. We will then present data that has been recently made publicly available. Data is distributed through worldwide FDSN and european EIDA standards protocols. A new web portal is now opened to explore and download seismic data and metadata. The RESIF datacentre is also now connected to Grenoble University High Performance Computing (HPC) facility : a typical use-case will be presented using iRODS technologies. The use of dense observation networks is increasing, bringing challenges in data growth and handling : we will present an example where HDF5 data format was used as an alternative to usual seismology data formats.

Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

PubMed

Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

2010-10-25

Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large-scale datasets. Software and data sets are available at http://www.sfu.ca/~ester/software/DECOB.zip.

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks

PubMed Central

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-01-01

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes. PMID:27649170

An automated method for finding molecular complexes in large protein interaction networks

PubMed Central

Bader, Gary D; Hogue, Christopher WV

2003-01-01

Background Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery. Results This paper describes a novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes. The method is based on vertex weighting by local neighborhood density and outward traversal from a locally dense seed protein to isolate the dense regions according to given parameters. The algorithm has the advantage over other graph clustering methods of having a directed mode that allows fine-tuning of clusters of interest without considering the rest of the network and allows examination of cluster interconnectivity, which is relevant for protein networks. Protein interaction and complex information from the yeast Saccharomyces cerevisiae was used for evaluation. Conclusion Dense regions of protein interaction networks can be found, based solely on connectivity data, many of which correspond to known protein complexes. The algorithm is not affected by a known high rate of false positives in data from high-throughput interaction techniques. The program is available from . PMID:12525261

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks.

PubMed

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-09-13

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.

Deploying Monitoring Trails for Fault Localization in All- Optical Networks and Radio-over-Fiber Passive Optical Networks

NASA Astrophysics Data System (ADS)

Maamoun, Khaled Mohamed

Fault localization is the process of realizing the true source of a failure from a set of collected failure notifications. Isolating failure recovery within the network optical domain is necessary to resolve alarm storm problems. The introduction of the monitoring trail (m-trail) has been proven to deliver better performance by employing monitoring resources in a form of optical trails - a monitoring framework that generalizes all the previously reported counterparts. In this dissertation, the m-trail design is explored and a focus is given to the analysis on using m-trails with established lightpaths to achieve fault localization. This process saves network resources by reducing the number of the m-trails required for fault localization and therefore the number of wavelengths used in the network. A novel approach based on Geographic Midpoint Technique, an adapted version of the Chinese Postman's Problem (CPP) solution and an adapted version of the Traveling Salesman's Problem (TSP) solution algorithms is introduced. The desirable features of network architectures and the enabling of innovative technologies for delivering future millimeter-waveband (mm-WB) Radio-over-Fiber (RoF) systems for wireless services integrated in a Dense Wavelength Division Multiplexing (DWDM) is proposed in this dissertation. For the conceptual illustration, a DWDM RoF system with channel spacing of 12.5 GHz is considered. The mm-WB Radio Frequency (RF) signal is obtained at each Optical Network Unit (ONU) by simultaneously using optical heterodyning photo detection between two optical carriers. The generated RF modulated signal has a frequency of 12.5 GHz. This RoF system is easy, cost-effective, resistant to laser phase noise and also reduces maintenance needs, in principle. A revision of related RoF network proposals and experiments is also included. A number of models for Passive Optical Networks (PON)/ RoF-PON that combine both innovative and existing ideas along with a number of solutions for m-trail design problem of these models are proposed. The comparison between these models uses the expected survivability function which proved that these models are liable to be implemented in the new and existing PON/ RoF-PON systems. This dissertation is followed by recommendation of possible directions for future research in this area.

Near-Real Time Monitoring of TEC Over Japan at NICT (RWC Tokyo OF ISES)

NASA Astrophysics Data System (ADS)

Miyake, W.; Jin, H.

2010-05-01

The world wide use of global navigation satellite systems such as GPS offers unique opportunities for a permanent monitoring of the total electron content (TEC) of the ionosphere. We have developed a system of the rapid derivation of TEC from GEONET (a dense GPS receiver network in Japan). In addition to a previous plot of TEC temporal variation over Japan, we have recently developed a near-real-time two-dimensional TEC map and have used it for the daily operation of Space Weather Forecast Center at NICT (Regional Warning Center Tokyo of International Space Environment Service). The TEC map can be used to continuously monitor the ionospheric disturbances over Japan, including spatial and temporal development of ionospheric storms, large-amplitude traveling ionospheric disturbances, and plasma bubbles intruding over Japan, with high time resolution. The development of the real-time monitoring system of TEC enables us to monitor large ionospheric disturbances, ranging from global- to small-scale disturbances, expected in the next solar maximum. The plot and maps are open to the public and are available on http://wdc.nict.go.jp/IONO/index_E.html.

Integration of Ground, Buoys, Satellite and Model data to map the Changes in Meteorological Parameters Associated with Harvey Hurricane

NASA Astrophysics Data System (ADS)

Chauhan, A.; Sarkar, S.; Singh, R. P.

2017-12-01

The coastal areas have dense onshore and marine observation network and are also routinely monitored by constellation of satellites. The monitoring of ocean, land and atmosphere through a range of meteorological parameters, provides information about the land and ocean surface. Satellite data also provide information at different pressure levels that help to access the development of tropical storms and formation of hurricanes at different categories. Integration of ground, buoys, satellite and model data showing the changes in meteorological parameters during the landfall stages of hurricane Harvey will be discussed. Hurricane Harvey was one of the deadliest hurricanes at the Gulf coast which caused intense flooding from the precipitation. The various observation networks helped city administrators to evacuate the coastal areas, that minimized the loss of lives compared to the Galveston hurricane of 1900 which took 10,000 lives. Comparison of meteorological parameters derived from buoys, ground stations and satellites associated with Harvey and 2005 Katrina hurricane present some of the interesting features of the two hurricanes.

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

Empirical Bayes conditional independence graphs for regulatory network recovery.

PubMed

Mahdi, Rami; Madduri, Abishek S; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R; Crystal, Ronald G; Mezey, Jason G

2012-08-01

Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary data are available at Bioinformatics online.

Tracking tracer breakthrough in the hyporheic zone using time‐lapse DC resistivity, Crabby Creek, Pennsylvania

USGS Publications Warehouse

Nyquist, Jonathan E.; Toran, Laura; Fang, Allison C.; Ryan, Robert J.; Rosenberry, Donald O.

2010-01-01

Characterization of the hyporheic zone is of critical importance for understanding stream ecology, contaminant transport, and groundwater‐surface water interaction. A salt water tracer test was used to probe the hyporheic zone of a recently re‐engineered portion of Crabby Creek, a stream located near Philadelphia, PA. The tracer solution was tracked through a 13.5 meter segment of the stream using both a network of 25 wells sampled every 5–15 minutes and time‐lapse electrical resistivity tomographs collected every 11 minutes for six hours, with additional tomographs collected every 100 minutes for an additional 16 hours. The comparison of tracer monitoring methods is of keen interest because tracer tests are one of the few techniques available for characterizing this dynamic zone, and logistically it is far easier to collect resistivity tomographs than to install and monitor a dense network of wells. Our results show that resistivity monitoring captured the essential shape of the breakthrough curve and may indicate portions of the stream where the tracer lingered in the hyporheic zone. Time‐lapse resistivity measurements, however, represent time averages over the period required to collect a tomographic data set, and spatial averages over a volume larger than captured by a well sample. Smoothing by the resistivity data inversion algorithm further blurs the resulting tomograph; consequently resistivity monitoring underestimates the degree of fine‐scale heterogeneity in the hyporheic zone.

Lake Ice Monitoring with Webcams

NASA Astrophysics Data System (ADS)

Xiao, M.; Rothermel, M.; Tom, M.; Galliani, S.; Baltsavias, E.; Schindler, K.

2018-05-01

Continuous monitoring of climate indicators is important for understanding the dynamics and trends of the climate system. Lake ice has been identified as one such indicator, and has been included in the list of Essential Climate Variables (ECVs). Currently there are two main ways to survey lake ice cover and its change over time, in-situ measurements and satellite remote sensing. The challenge with both of them is to ensure sufficient spatial and temporal resolution. Here, we investigate the possibility to monitor lake ice with video streams acquired by publicly available webcams. Main advantages of webcams are their high temporal frequency and dense spatial sampling. By contrast, they have low spectral resolution and limited image quality. Moreover, the uncontrolled radiometry and low, oblique viewpoints result in heavily varying appearance of water, ice and snow. We present a workflow for pixel-wise semantic segmentation of images into these classes, based on state-of-the-art encoder-decoder Convolutional Neural Networks (CNNs). The proposed segmentation pipeline is evaluated on two sequences featuring different ground sampling distances. The experiment suggests that (networks of) webcams have great potential for lake ice monitoring. The overall per-pixel accuracies for both tested data sets exceed 95 %. Furthermore, per-image discrimination between ice-on and ice-off conditions, derived by accumulating per-pixel results, is 100 % correct for our test data, making it possible to precisely recover freezing and thawing dates.

A measure of the denseness of a phylogenetic network. [by sequenced proteins from extant species

NASA Technical Reports Server (NTRS)

Holmquist, R.

1978-01-01

An objective measure of phylogenetic denseness is developed to examine various phylogenetic criteria: alpha- and beta-hemoglobin, myoglobin, cytochrome c, and the parvalbumin family. Attention is given to the number of nucleotide replacements separating homologous sequences, and to the topology of the network (in other words, to the qualitative nature of the network as defined by how closely the studied species are related). Applications include quantitative comparisons of species origin, relation, and rates of evolution.

Efficient large-scale graph data optimization for intelligent video surveillance

NASA Astrophysics Data System (ADS)

Shang, Quanhong; Zhang, Shujun; Wang, Yanbo; Sun, Chen; Wang, Zepeng; Zhang, Luming

2017-08-01

Society is rapidly accepting the use of a wide variety of cameras Location and applications: site traffic monitoring, parking Lot surveillance, car and smart space. These ones here the camera provides data every day in an analysis Effective way. Recent advances in sensor technology Manufacturing, communications and computing are stimulating.The development of new applications that can change the traditional Vision system incorporating universal smart camera network. This Analysis of visual cues in multi camera networks makes wide Applications ranging from smart home and office automation to large area surveillance and traffic surveillance. In addition, dense Camera networks, most of which have large overlapping areas of cameras. In the view of good research, we focus on sparse camera networks. One Sparse camera network using large area surveillance. As few cameras as possible, most cameras do not overlap Each other’s field of vision. This task is challenging Lack of knowledge of topology Network, the specific changes in appearance and movement Track different opinions of the target, as well as difficulties Understanding complex events in a network. In this review in this paper, we present a comprehensive survey of recent studies Results to solve the problem of topology learning, Object appearance modeling and global activity understanding sparse camera network. In addition, some of the current open Research issues are discussed.

Trans-African Hydro-Meteorological Observatory (TAHMO): A network to monitor weather, water, and climate in Africa

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Hut, R.; Andreini, M.; Selker, J. S.

2013-12-01

The Trans-African Hydro-Meteorological Observatory (TAHMO) has a goal to design, build, install and operate a dense network of hydro-meteorological monitoring stations in sub-Saharan Africa; one every 35 km. This corresponds to a total of 20,000 stations. By applying ICT and innovative sensors, each station should cost not more than $500. The stations would be placed at schools and integrated in the environmental curriculum. Data will be combined with models and satellite observations to obtain a very complete insight into the distribution of water and energy stocks and fluxes. Within this project, we have built a prototype of an acoustic disdrometer (rain gauge) that can be produced for much less than the cost of a commercial equivalent with the same specifications. The disdrometer was developed in The Netherlands and tested in Tanzania for a total project cost of Euro 5000. First tests have been run at junior high schools in Ghana to incorporate hydro-meteorological measurements in the science curriculum. The latest activity concerns the organization of a crowdsourcing competitions across Africa to address business development and the design and building of new robust sensors. This has resulted in a wide network throughout the continent to bring this program forward.

Locating overlapping dense subgraphs in gene (protein) association networks and predicting novel protein functional groups among these subgraphs

NASA Astrophysics Data System (ADS)

Palla, Gergely; Derenyi, Imre; Farkas, Illes J.; Vicsek, Tamas

2006-03-01

Most tasks in a cell are performed not by individual proteins, but by functional groups of proteins (either physically interacting with each other or associated in other ways). In gene (protein) association networks these groups show up as sets of densely connected nodes. In the yeast, Saccharomyces cerevisiae, known physically interacting groups of proteins (called protein complexes) strongly overlap: the total number of proteins contained by these complexes by far underestimates the sum of their sizes (2750 vs. 8932). Thus, most functional groups of proteins, both physically interacting and other, are likely to share many of their members with other groups. However, current algorithms searching for dense groups of nodes in networks usually exclude overlaps. With the aim to discover both novel functions of individual proteins and novel protein functional groups we combine in protein association networks (i) a search for overlapping dense subgraphs based on the Clique Percolation Method (CPM) (Palla, G., et.al. Nature 435, 814-818 (2005), http://angel.elte.hu/clustering), which explicitly allows for overlaps among the groups, and (ii) a verification and characterization of the identified groups of nodes (proteins) with the help of standard annotation databases listing known functions.

Extracting Communities from Complex Networks by the k-Dense Method

NASA Astrophysics Data System (ADS)

Saito, Kazumi; Yamada, Takeshi; Kazama, Kazuhiro

To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it produces only coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the three different types of networks assembled from real data, namely, from blog trackbacks, word associations and Wikipedia references, and demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method.

The Benefits of Using Dense Temperature Sensor Networks to Monitor Urban Warming

NASA Astrophysics Data System (ADS)

Twine, T. E.; Snyder, P. K.; Kucharik, C. J.; Schatz, J.

2015-12-01

Urban heat islands (UHIs) occur when urban and suburban areas experience temperatures that are elevated relative to their rural surroundings because of differences in the fraction of gray and green infrastructure. Studies have shown that communities most at risk for impacts from climate-related disasters (i.e., lower median incomes, higher poverty, lower education, and minorities) tend to live in the hottest areas of cities. Development of adequate climate adaptation tools for cities relies on knowledge of how temperature varies across space and time. Traditionally, a city's urban heat island has been quantified using near-surface air temperature measurements from a few sites. This methodology assumes (1) that the UHI can be characterized by the difference in air temperature from a small number of points, and (2) that these few points represent the urban and rural signatures of the region. This methodology ignores the rich information that could be gained from measurements across the urban to rural transect. This transect could traverse elevations, water bodies, vegetation fraction, and other land surface properties. Two temperature sensor networks were designed and implemented in the Minneapolis-Saint Paul, MN and Madison, WI metropolitan areas beginning in 2011 and 2012, respectively. Both networks use the same model sensor and record temperature every 15 minutes from ~150 sensors. Data from each network has produced new knowledge of how temperature varies diurnally and seasonally across the cities and how the UHI magnitude is influenced by weather phenomena (e.g., wind, snow cover, heat waves) and land surface characteristics such as proximity to inland lakes. However, the two metropolitan areas differ in size, population, structure, and orientation to water bodies. In addition, the sensor networks were established in very different manners. We describe these differences and present lessons learned from the design and ongoing efforts of these two dense networks located in the Midwest USA.

Pairwise graphical models for structural health monitoring with dense sensor arrays

NASA Astrophysics Data System (ADS)

Mohammadi Ghazi, Reza; Chen, Justin G.; Büyüköztürk, Oral

2017-09-01

Through advances in sensor technology and development of camera-based measurement techniques, it has become affordable to obtain high spatial resolution data from structures. Although measured datasets become more informative by increasing the number of sensors, the spatial dependencies between sensor data are increased at the same time. Therefore, appropriate data analysis techniques are needed to handle the inference problem in presence of these dependencies. In this paper, we propose a novel approach that uses graphical models (GM) for considering the spatial dependencies between sensor measurements in dense sensor networks or arrays to improve damage localization accuracy in structural health monitoring (SHM) application. Because there are always unobserved damaged states in this application, the available information is insufficient for learning the GMs. To overcome this challenge, we propose an approximated model that uses the mutual information between sensor measurements to learn the GMs. The study is backed by experimental validation of the method on two test structures. The first is a three-story two-bay steel model structure that is instrumented by MEMS accelerometers. The second experimental setup consists of a plate structure and a video camera to measure the displacement field of the plate. Our results show that considering the spatial dependencies by the proposed algorithm can significantly improve damage localization accuracy.

Dense Matching Comparison Between Census and a Convolutional Neural Network Algorithm for Plant Reconstruction

NASA Astrophysics Data System (ADS)

Xia, Y.; Tian, J.; d'Angelo, P.; Reinartz, P.

2018-05-01

3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.

Tracing Activity Across the Whole Brain Neural Network with Optogenetic Functional Magnetic Resonance Imaging

PubMed Central

Lee, Jin Hyung

2011-01-01

Despite the overwhelming need, there has been a relatively large gap in our ability to trace network level activity across the brain. The complex dense wiring of the brain makes it extremely challenging to understand cell-type specific activity and their communication beyond a few synapses. Recent development of the optogenetic functional magnetic resonance imaging (ofMRI) provides a new impetus for the study of brain circuits by enabling causal tracing of activities arising from defined cell types and firing patterns across the whole brain. Brain circuit elements can be selectively triggered based on their genetic identity, cell body location, and/or their axonal projection target with temporal precision while the resulting network response is monitored non-invasively with unprecedented spatial and temporal accuracy. With further studies including technological innovations to bring ofMRI to its full potential, ofMRI is expected to play an important role in our system-level understanding of the brain circuit mechanism. PMID:22046160

Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks

NASA Astrophysics Data System (ADS)

Yang, Xue; Sun, Hao; Fu, Kun; Yang, Jirui; Sun, Xian; Yan, Menglong; Guo, Zhi

2018-01-01

Ship detection has been playing a significant role in the field of remote sensing for a long time but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application scenarios, the difficulty of intensive object detection and the redundancy of detection region. In order to solve such problems above, we propose a framework called Rotation Dense Feature Pyramid Networks (R-DFPN) which can effectively detect ship in different scenes including ocean and port. Specifically, we put forward the Dense Feature Pyramid Network (DFPN), which is aimed at solving the problem resulted from the narrow width of the ship. Compared with previous multi-scale detectors such as Feature Pyramid Network (FPN), DFPN builds the high-level semantic feature-maps for all scales by means of dense connections, through which enhances the feature propagation and encourages the feature reuse. Additionally, in the case of ship rotation and dense arrangement, we design a rotation anchor strategy to predict the minimum circumscribed rectangle of the object so as to reduce the redundant detection region and improve the recall. Furthermore, we also propose multi-scale ROI Align for the purpose of maintaining the completeness of semantic and spatial information. Experiments based on remote sensing images from Google Earth for ship detection show that our detection method based on R-DFPN representation has a state-of-the-art performance.

Class network routing

DOEpatents

Bhanot, Gyan [Princeton, NJ; Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2009-09-08

Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

A Novel Characterization of Amalgamated Networks in Natural Systems

PubMed Central

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-01-01

Densely-connected networks are prominent among natural systems, exhibiting structural characteristics often optimized for biological function. To reveal such features in highly-connected networks, we introduce a new network characterization determined by a decomposition of network-connectivity into low-rank and sparse components. Based on these components, we discover a new class of networks we define as amalgamated networks, which exhibit large functional groups and dense connectivity. Analyzing recent experimental findings on cerebral cortex, food-web, and gene regulatory networks, we establish the unique importance of amalgamated networks in fostering biologically advantageous properties, including rapid communication among nodes, structural stability under attacks, and separation of network activity into distinct functional modules. We further observe that our network characterization is scalable with network size and connectivity, thereby identifying robust features significant to diverse physical systems, which are typically undetectable by conventional characterizations of connectivity. We expect that studying the amalgamation properties of biological networks may offer new insights into understanding their structure-function relationships. PMID:26035066

Chimera-like states in structured heterogeneous networks

NASA Astrophysics Data System (ADS)

Li, Bo; Saad, David

2017-04-01

Chimera-like states are manifested through the coexistence of synchronous and asynchronous dynamics and have been observed in various systems. To analyze the role of network topology in giving rise to chimera-like states, we study a heterogeneous network model comprising two groups of nodes, of high and low degrees of connectivity. The architecture facilitates the analysis of the system, which separates into a densely connected coherent group of nodes, perturbed by their sparsely connected drifting neighbors. It describes a synchronous behavior of the densely connected group and scaling properties of the induced perturbations.

Seismic monitoring at Cascade Volcanic Centers, 2004?status and recommendations

USGS Publications Warehouse

Moran, Seth C.

2004-01-01

The purpose of this report is to assess the current (May, 2004) status of seismic monitoring networks at the 13 major Cascade volcanic centers. Included in this assessment are descriptions of each network, analyses of the ability of each network to detect and to locate seismic activity, identification of specific weaknesses in each network, and a prioritized list of those networks that are most in need of additional seismic stations. At the outset it should be recognized that no Cascade volcanic center currently has an adequate seismic network relative to modern-day networks at Usu Volcano (Japan) or Etna and Stromboli volcanoes (Italy). For a system the size of Three Sisters, for example, a modern-day, cutting-edge seismic network would ideally consist of a minimum of 10 to 12 short-period three-component seismometers (for determining particle motions, reliable S-wave picks, moment tensor inversions, fault-plane solutions, and other important seismic parameters) and 7 to 10 broadband sensors (which, amongst other considerations, enable detection and location of very long period (VLP) and other low-frequency events, moment tensor inversions, and, because of their wide dynamic range, on-scale recording of large-amplitude events). Such a dense, multi component seismic network would give the ability to, for example, detect in near-real-time earthquake migrations over a distance of ~0.5km or less, locate tremor sources, determine the nature of a seismic source (that is, pure shear, implosive, explosive), provide on-scale recordings of very small and very large-amplitude seismic signals, and detect localized changes in seismic stress tensor orientations caused by movement of magma bodies. However, given that programmatic resources are currently limited, installation of such networks at this time is unrealistic. Instead, this report focuses on identifying what additional stations are needed to guarantee that anomalous seismicity associated with volcanic unrest will be detected in a timely manner and, in the case of magnitude = 1 earthquakes, reliably located.

Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands.

PubMed

Hiemstra, Paul H; Pebesma, Edzer J; Heuvelink, Gerard B M; Twenhöfel, Chris J W

2010-12-01

The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny decaying, which in turn is a balance between deposition of progeny by rainfall and radioactive decay. The increase in progeny is closely related to average rainfall intensity over the last 2.5h. We included decay of progeny by using weighted averaged rainfall intensity, where the weight decreases back in time. The decrease in weight is related to the half-life of radon progeny. In this paper we show for a rainstorm on the 20th of July 2007 that weighted averaged rainfall intensity estimated from rainfall radar images, collected every 5min, performs much better as a predictor of increases in dose rate than using the non-averaged rainfall intensity. In addition, we show through cross-validation that including weighted averaged rainfall intensity in an interpolated map using universal kriging (UK) does not necessarily lead to a more accurate map. This might be attributed to the high density of monitoring stations in comparison to the spatial extent of a typical rain event. Reducing the network density improved the accuracy of the map when universal kriging was used instead of ordinary kriging (no trend). Consequently, in a less dense network the positive influence of including a trend is likely to increase. Furthermore, we suspect that UK better reproduces the sharp boundaries present in rainfall maps, but that the lack of short-distance monitoring station pairs prevents cross-validation from revealing this effect. Copyright © 2010 Elsevier B.V. All rights reserved.

Earthquake Monitoring: SeisComp3 at the Swiss National Seismic Network

NASA Astrophysics Data System (ADS)

Clinton, J. F.; Diehl, T.; Cauzzi, C.; Kaestli, P.

2011-12-01

The Swiss Seismological Service (SED) has an ongoing responsibility to improve the seismicity monitoring capability for Switzerland. This is a crucial issue for a country with low background seismicity but where a large M6+ earthquake is expected in the next decades. With over 30 stations with spacing of ~25km, the SED operates one of the densest broadband networks in the world, which is complimented by ~ 50 realtime strong motion stations. The strong motion network is expected to grow with an additional ~80 stations over the next few years. Furthermore, the backbone of the network is complemented by broadband data from surrounding countries and temporary sub-networks for local monitoring of microseismicity (e.g. at geothermal sites). The variety of seismic monitoring responsibilities as well as the anticipated densifications of our network demands highly flexible processing software. We are transitioning all software to the SeisComP3 (SC3) framework. SC3 is a fully featured automated real-time earthquake monitoring software developed by GeoForschungZentrum Potsdam in collaboration with commercial partner, gempa GmbH. It is in its core open source, and becoming a community standard software for earthquake detection and waveform processing for regional and global networks across the globe. SC3 was originally developed for regional and global rapid monitoring of potentially tsunamagenic earthquakes. In order to fulfill the requirements of a local network recording moderate seismicity, SED has tuned configurations and added several modules. In this contribution, we present our SC3 implementation strategy, focusing on the detection and identification of seismicity on different scales. We operate several parallel processing "pipelines" to detect and locate local, regional and global seismicity. Additional pipelines with lower detection thresholds can be defined to monitor seismicity within dense subnets of the network. To be consistent with existing processing procedures, the nonlinloc algorithm was implemented for manual and automatic locations using 1D and 3D velocity models; plugins for improved automatic phase picking and Ml computation were developed; and the graphical user interface for manual review was extended (including pick uncertainty definition; first motion focal mechanisms; interactive review of station magnitude waveforms; full inclusion of strong motion data). SC3 locations are fully compatible with those derived from the existing in-house processing tools and are stored in a database derived from the QuakeML data model. The database is shared with the SED alerting software, which merges origins from both SC3 and external sources in realtime and handles the alerting procedure. With the monitoring software being transitioned to SeisComp3, acquisition, archival and dissemination of SED waveform data now conforms to the seedlink and ArcLink protocols and continuous archives can be accessed via SED and all EIDA (European Integrated Data Archives) web-sites. Further, a SC3 module for waveform parameterisation has been developed, allowing rapid computation of peak values of ground motion and other engineering parameters within minutes of a new event. An output of this module is USGS ShakeMap XML. n minutes of a new event. An output of this module is USGS ShakeMap XML.

HID-1 controls formation of large dense core vesicles by influencing cargo sorting and trans-Golgi network acidification

PubMed Central

Hummer, Blake H.; de Leeuw, Noah F.; Burns, Christian; Chen, Lan; Joens, Matthew S.; Hosford, Bethany; Fitzpatrick, James A. J.; Asensio, Cedric S.

2017-01-01

Large dense core vesicles (LDCVs) mediate the regulated release of neuropeptides and peptide hormones. They form at the trans-Golgi network (TGN), where their soluble content aggregates to form a dense core, but the mechanisms controlling biogenesis are still not completely understood. Recent studies have implicated the peripheral membrane protein HID-1 in neuropeptide sorting and insulin secretion. Using CRISPR/Cas9, we generated HID-1 KO rat neuroendocrine cells, and we show that the absence of HID-1 results in specific defects in peptide hormone and monoamine storage and regulated secretion. Loss of HID-1 causes a reduction in the number of LDCVs and affects their morphology and biochemical properties, due to impaired cargo sorting and dense core formation. HID-1 KO cells also exhibit defects in TGN acidification together with mislocalization of the Golgi-enriched vacuolar H+-ATPase subunit isoform a2. We propose that HID-1 influences early steps in LDCV formation by controlling dense core formation at the TGN. PMID:29074564

From sparse to dense and from assortative to disassortative in online social networks

PubMed Central

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-01-01

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks. PMID:24798703

From sparse to dense and from assortative to disassortative in online social networks.

PubMed

Li, Menghui; Guan, Shuguang; Wu, Chensheng; Gong, Xiaofeng; Li, Kun; Wu, Jinshan; Di, Zengru; Lai, Choy-Heng

2014-05-06

Inspired by the analysis of several empirical online social networks, we propose a simple reaction-diffusion-like coevolving model, in which individuals are activated to create links based on their states, influenced by local dynamics and their own intention. It is shown that the model can reproduce the remarkable properties observed in empirical online social networks; in particular, the assortative coefficients are neutral or negative, and the power law exponents γ are smaller than 2. Moreover, we demonstrate that, under appropriate conditions, the model network naturally makes transition(s) from assortative to disassortative, and from sparse to dense in their characteristics. The model is useful in understanding the formation and evolution of online social networks.

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.

Scaling an in situ network for high resolution modeling during SMAPVEX15

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.; Jacobs, J. M.; Jackson, T. J.; Crow, W. T.; Holifield Collins, C.; Goodrich, D. C.; Colliander, A.

2015-12-01

Among the greatest challenges within the field of soil moisture estimation is that of scaling sparse point measurements within a network to produce higher resolution map products. Large-scale field experiments present an ideal opportunity to develop methodologies for this scaling, by coupling in situ networks, temporary networks, and aerial mapping of soil moisture. During the Soil Moisture Active Passive Validation Experiments in 2015 (SMAPVEX15) in and around the USDA-ARS Walnut Gulch Experimental Watershed and LTAR site in southeastern Arizona, USA, a high density network of soil moisture stations was deployed across a sparse, permanent in situ network in coordination with intensive soil moisture sampling and an aircraft campaign. This watershed is also densely instrumented with precipitation gages (one gauge/0.57 km2) to monitor the North American Monsoon System, which dominates the hydrologic cycle during the summer months in this region. Using the precipitation and soil moisture time series values provided, a physically-based model is calibrated that will provide estimates at the 3km, 9km, and 36km scales. The results from this model will be compared with the point-scale gravimetric samples, aircraft-based sensor, and the satellite-based products retrieved from NASA's Soil Moisture Active Passive mission.

Social Networks, Social Circles, and Job Satisfaction.

ERIC Educational Resources Information Center

Hurlbert, Jeanne S.

1991-01-01

Tests the hypothesis that social networks serve as a social resource that effects job satisfaction through the provision of social support. Argues that three types of networks are likely to affect job satisfaction: dense networks, social circles composed of co-workers, and kin-centered networks. (JOW)

A dense camera network for cropland (CropInsight) - developing high spatiotemporal resolution crop Leaf Area Index (LAI) maps through network images and novel satellite data

NASA Astrophysics Data System (ADS)

Kimm, H.; Guan, K.; Luo, Y.; Peng, J.; Mascaro, J.; Peng, B.

2017-12-01

Monitoring crop growth conditions is of primary interest to crop yield forecasting, food production assessment, and risk management of individual farmers and agribusiness. Despite its importance, there are limited access to field level crop growth/condition information in the public domain. This scarcity of ground truth data also hampers the use of satellite remote sensing for crop monitoring due to the lack of validation. Here, we introduce a new camera network (CropInsight) to monitor crop phenology, growth, and conditions that are designed for the US Corn Belt landscape. Specifically, this network currently includes 40 sites (20 corn and 20 soybean fields) across southern half of the Champaign County, IL ( 800 km2). Its wide distribution and automatic operation enable the network to capture spatiotemporal variations of crop growth condition continuously at the regional scale. At each site, low-maintenance, and high-resolution RGB digital cameras are set up having a downward view from 4.5 m height to take continuous images. In this study, we will use these images and novel satellite data to construct daily LAI map of the Champaign County at 30 m spatial resolution. First, we will estimate LAI from the camera images and evaluate it using the LAI data collected from LAI-2200 (LI-COR, Lincoln, NE). Second, we will develop relationships between the camera-based LAI estimation and vegetation indices derived from a newly developed MODIS-Landsat fusion product (daily, 30 m resolution, RGB + NIR + SWIR bands) and the Planet Lab's high-resolution satellite data (daily, 5 meter, RGB). Finally, we will scale up the above relationships to generate high spatiotemporal resolution crop LAI map for the whole Champaign County. The proposed work has potentials to expand to other agro-ecosystems and to the broader US Corn Belt.

Characters of Vertical Variability with Geodetic Satellites and Ground-based Continuous GPS in Taiwan

NASA Astrophysics Data System (ADS)

Yang, C.-C.; Wu, Y.-H.; Chao, B. F.; Yu, S.-B.

2009-04-01

Present-day GPS network have been extensively used to monitor crustal deformation due to various geodynamic mechanisms. Situated among the Pacific Ring of Fire on the suture zone of Eurasian and Philippine Sea Plates, the island of Taiwan with a dense continuous GPS network since ~1996 and now over 300 stations sees plenty of geophysical phenomena including particularly prominent crustal motions. We assessed daily solution of each station's coordinate time series, and made the routine corrections, such as orbital, EOP, atmospheric and tidal corrections, using GAMIT/GLOBK software (with ITRF05). We then employ the Quasi-Observation Combination Analysis (QOCA) package to obtain the variability and trend after removing occasional earthquake "disruptions". Preliminary results show strong seasonal variations. We then utilize the numerical method of Empirical Orthogonal Function (EOF) to analysis the geophysical signals from the continuous and dense GPS vertical crustal motion observations. We wish to be able to characterize both the seasonal and non-seasonal variability in the vertical crustal motion, in terms of the EOF modes in the spatial domain over Taiwan (plus a few offshore islets) with time evolution spanning the entire period of time. Corraborating with time-variable gravity data from the geodetic satellite mission GRACE, we can further obtain vertical components of both mass-induced loading with respect to the precipitation minus evaporation and the crustal motion caused by the active tectonic processes on Taiwan.

Dense deconvolution net: Multi path fusion and dense deconvolution for high resolution skin lesion segmentation.

PubMed

He, Xinzi; Yu, Zhen; Wang, Tianfu; Lei, Baiying; Shi, Yiyan

2018-01-01

Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region. To handle these challenges, we propose a novel skin lesion segmentation network via a very deep dense deconvolution network based on dermoscopic images. Specifically, the deep dense layer and generic multi-path Deep RefineNet are combined to improve the segmentation performance. The deep representation of all available layers is aggregated to form the global feature maps using skip connection. Also, the dense deconvolution layer is leveraged to capture diverse appearance features via the contextual information. Finally, we apply the dense deconvolution layer to smooth segmentation maps and obtain final high-resolution output. Our proposed method shows the superiority over the state-of-the-art approaches based on the public available 2016 and 2017 skin lesion challenge dataset and achieves the accuracy of 96.0% and 93.9%, which obtained a 6.0% and 1.2% increase over the traditional method, respectively. By utilizing Dense Deconvolution Net, the average time for processing one testing images with our proposed framework was 0.253 s.

A dense Black Carbon network in the region of Paris, France: Implementation, objectives, and first results

NASA Astrophysics Data System (ADS)

Sciare, Jean; Petit, Jean-Eudes; Sarda-Esteve, Roland; Bonnaire, Nicolas; Gros, Valérie; Pernot, Pierre; Ghersi, Véronique; Ampe, Christophe; Songeur, Charlotte; Brugge, Benjamin; Debert, Christophe; Favez, Olivier; Le Priol, Tiphaine; Mocnik, Grisa

2013-04-01

Motivations. Road traffic and domestic wood burning emissions are two major contributors of particulate pollution in our cities. These two sources emit ultra-fine, soot containing, particles in the atmosphere, affecting health adversely, increasing morbidity and mortality from cardiovascular and respiratory conditions and casing lung cancer. A better characterization of soot containing aerosol sources in our major cities provides useful information for policy makers for assessment, implementation and monitoring of strategies to tackle air pollution issues affecting human health with additional benefits for climate change. Objectives. This study on local sources of primary Particulate Matter (PM) in the megacity of Paris is a follow-up of several programs (incl. EU-FP7-MEGAPOLI) that have shown that fine PM - in the Paris background atmosphere - is mostly secondary and imported. A network of 14 stations of Black Carbon has been implemented in the larger region of Paris to provide highly spatially resolved long term survey of local combustion aerosols. To our best knowledge, this is the first time that such densely BC network is operating over a large urban area, providing novel information on the spatial/temporal distribution of combustion aerosols within a post-industrialized megacity. Experimental. As part of the PRIMEQUAL "PREQUALIF" project, a dense Black Carbon network (of 14 stations) has been installed over the city of Paris beginning of 2012 in order to produce spatially resolved Equivalent Black Carbon (EBC) concentration maps with high time resolution through modeling and data assimilation. This network is composed of various real-time instruments (Multi-Angle Absorption Photometer, MAAP by THERMO; Multi-wavelength Aethalometers by MAGEE Scientific) implemented in contrasted sites (rural background, urban background, traffic) complementing the regulated measurements (PM, NOx) in the local air quality network AIRPARIF (http://www.airparif.asso.fr/). Contribution of imported versus local EBC is calculated using the "Lenschow" methodology (Lenschow et al., 2001), whereas the influence of domestic wood burning EBC (vs traffic) over the region of Paris is evaluated using the Aethalometer model developed by Sandradewi et al. (2008). Results and discussion. First results of this BC network are presented here including the temporal variations of EBC from wood burning (domestic heating) and fossil fuel (traffic) for the various sites (1-year observation for rural background and traffic sites; 4-year observations for urban background). The local versus imported contributions of EBC are also presented and discussed for these 2 sources. References. Lenschow, P., et al., Some ideas about the sources of PM10, Atmospheric Environment 35 Supplement No. 1 (2001) S23-S33 Sandradewi, J., et al., Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter, Environ. Sci. Technol., 42, 3316-3323, 2008

Deterministic quantum dense coding networks

NASA Astrophysics Data System (ADS)

Roy, Saptarshi; Chanda, Titas; Das, Tamoghna; Sen(De), Aditi; Sen, Ujjwal

2018-07-01

We consider the scenario of deterministic classical information transmission between multiple senders and a single receiver, when they a priori share a multipartite quantum state - an attempt towards building a deterministic dense coding network. Specifically, we prove that in the case of two or three senders and a single receiver, generalized Greenberger-Horne-Zeilinger (gGHZ) states are not beneficial for sending classical information deterministically beyond the classical limit, except when the shared state is the GHZ state itself. On the other hand, three- and four-qubit generalized W (gW) states with specific parameters as well as the four-qubit Dicke states can provide a quantum advantage of sending the information in deterministic dense coding. Interestingly however, numerical simulations in the three-qubit scenario reveal that the percentage of states from the GHZ-class that are deterministic dense codeable is higher than that of states from the W-class.

Automatic data processing and analysis system for monitoring region around a planned nuclear power plant

NASA Astrophysics Data System (ADS)

Kortström, Jari; Tiira, Timo; Kaisko, Outi

2016-03-01

The Institute of Seismology of University of Helsinki is building a new local seismic network, called OBF network, around planned nuclear power plant in Northern Ostrobothnia, Finland. The network will consist of nine new stations and one existing station. The network should be dense enough to provide azimuthal coverage better than 180° and automatic detection capability down to ML -0.1 within a radius of 25 km from the site.The network construction work began in 2012 and the first four stations started operation at the end of May 2013. We applied an automatic seismic signal detection and event location system to a network of 13 stations consisting of the four new stations and the nearest stations of Finnish and Swedish national seismic networks. Between the end of May and December 2013 the network detected 214 events inside the predefined area of 50 km radius surrounding the planned nuclear power plant site. Of those detections, 120 were identified as spurious events. A total of 74 events were associated with known quarries and mining areas. The average location error, calculated as a difference between the announced location from environment authorities and companies and the automatic location, was 2.9 km. During the same time period eight earthquakes between magnitude range 0.1-1.0 occurred within the area. Of these seven could be automatically detected. The results from the phase 1 stations of the OBF network indicates that the planned network can achieve its goals.

IrisDenseNet: Robust Iris Segmentation Using Densely Connected Fully Convolutional Networks in the Images by Visible Light and Near-Infrared Light Camera Sensors

PubMed Central

Arsalan, Muhammad; Naqvi, Rizwan Ali; Kim, Dong Seop; Nguyen, Phong Ha; Owais, Muhammad; Park, Kang Ryoung

2018-01-01

The recent advancements in computer vision have opened new horizons for deploying biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition is now much needed in unconstraint scenarios with accuracy. These environments make the acquired iris image exhibit occlusion, low resolution, blur, unusual glint, ghost effect, and off-angles. The prevailing segmentation algorithms cannot cope with these constraints. In addition, owing to the unavailability of near-infrared (NIR) light, iris recognition in visible light environment makes the iris segmentation challenging with the noise of visible light. Deep learning with convolutional neural networks (CNN) has brought a considerable breakthrough in various applications. To address the iris segmentation issues in challenging situations by visible light and near-infrared light camera sensors, this paper proposes a densely connected fully convolutional network (IrisDenseNet), which can determine the true iris boundary even with inferior-quality images by using better information gradient flow between the dense blocks. In the experiments conducted, five datasets of visible light and NIR environments were used. For visible light environment, noisy iris challenge evaluation part-II (NICE-II selected from UBIRIS.v2 database) and mobile iris challenge evaluation (MICHE-I) datasets were used. For NIR environment, the institute of automation, Chinese academy of sciences (CASIA) v4.0 interval, CASIA v4.0 distance, and IIT Delhi v1.0 iris datasets were used. Experimental results showed the optimal segmentation of the proposed IrisDenseNet and its excellent performance over existing algorithms for all five datasets. PMID:29748495

IrisDenseNet: Robust Iris Segmentation Using Densely Connected Fully Convolutional Networks in the Images by Visible Light and Near-Infrared Light Camera Sensors.

PubMed

Arsalan, Muhammad; Naqvi, Rizwan Ali; Kim, Dong Seop; Nguyen, Phong Ha; Owais, Muhammad; Park, Kang Ryoung

2018-05-10

The recent advancements in computer vision have opened new horizons for deploying biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition is now much needed in unconstraint scenarios with accuracy. These environments make the acquired iris image exhibit occlusion, low resolution, blur, unusual glint, ghost effect, and off-angles. The prevailing segmentation algorithms cannot cope with these constraints. In addition, owing to the unavailability of near-infrared (NIR) light, iris recognition in visible light environment makes the iris segmentation challenging with the noise of visible light. Deep learning with convolutional neural networks (CNN) has brought a considerable breakthrough in various applications. To address the iris segmentation issues in challenging situations by visible light and near-infrared light camera sensors, this paper proposes a densely connected fully convolutional network (IrisDenseNet), which can determine the true iris boundary even with inferior-quality images by using better information gradient flow between the dense blocks. In the experiments conducted, five datasets of visible light and NIR environments were used. For visible light environment, noisy iris challenge evaluation part-II (NICE-II selected from UBIRIS.v2 database) and mobile iris challenge evaluation (MICHE-I) datasets were used. For NIR environment, the institute of automation, Chinese academy of sciences (CASIA) v4.0 interval, CASIA v4.0 distance, and IIT Delhi v1.0 iris datasets were used. Experimental results showed the optimal segmentation of the proposed IrisDenseNet and its excellent performance over existing algorithms for all five datasets.

Birmingham Urban Climate Laboratory (BUCL): Experiences, Challenges and Applications of an Urban Temperature Network

NASA Astrophysics Data System (ADS)

Muller, Catherine; Chapman, Lee; Young, Duick; Grimmond, Sue; Cai, Xiaoming

2013-04-01

The Birmingham Urban Climate Laboratory (BUCL) has recently been established by the University of Birmingham. BUCL is an in-situ, real-time urban network that will incorporate 3 nested networks - a wide-array of 25 weather stations, a dense array of 131 low-cost air temperature sensors and a fine-array of temperature sensor across the city-centre (50/km^2) - with the primary aim of monitoring air temperatures across a morphologically-heterogeneous urban conurbation for a variety of applications. During its installation there have been a number of challenges to overcome, including siting equipment in suitable urban locations, ensuring that the measurements were 'representative' of the local-scale climate, managing a large, near real-time data set and implementing QA/QC procedures. From these experiences, the establishment of a standardised urban meteorological network metadata protocol has been proposed in order to improve data quality, to ensure the end-user has access to all the supplementary information they would require for conducting valid analyses and to encourage the adequate recording and documentation of any changes to in-situ urban networks over time. This paper will provide an introduction to the BUCL in-situ network, give an overview of the challenges and experiences gained from its implementation, and finally discuss the proposed applications of the network, including its use in remote sensing observations of urban temperatures, as well as health and infrastructure applications.

Dynamics of the middle atmosphere as observed by the ARISE project

NASA Astrophysics Data System (ADS)

Blanc, E.

2015-12-01

It has been strongly demonstrated that variations in the circulation of the middle atmosphere influence weather and climate all the way to the Earth's surface. A key part of this coupling occurs through the propagation and breaking of planetary and gravity waves. However, limited observations prevent to faithfully reproduce the dynamics of the middle atmosphere in numerical weather prediction and climate models. The main challenge of the ARISE (Atmospheric dynamics InfraStructure in Europe) project is to combine existing national and international observation networks including: the International infrasound monitoring system developed for the CTBT (Comprehensive nuclear-Test-Ban Treaty) verification, the NDACC (Network for the Detection of Atmospheric Composition Changes) lidar network, European observation infrastructures at mid latitudes (OHP observatory), tropics (Maïdo observatory), high latitudes (ALOMAR and EISCAT), infrasound stations which form a dense European network and satellites. The ARISE network is unique by its coverage (polar to equatorial regions in the European longitude sector), its altitude range (from troposphere to mesosphere and ionosphere) and the involved scales both in time (from seconds to tens of years) and space (from tens of meters to thousands of kilometers). Advanced data products are produced with the scope to assimilate data in the Weather Prediction models to improve future forecasts over weeks and seasonal time scales. ARISE observations are especially relevant for the monitoring of extreme events such as thunderstorms, volcanoes, meteors and at larger scales, deep convection and stratospheric warming events for physical processes description and study of long term evolution with climate change. Among the applications, ARISE fosters integration of innovative methods for remote detection of non-instrumented volcanoes including distant eruption characterization to provide notifications with reliable confidence indices to the civil aviation.

ClueNet: Clustering a temporal network based on topological similarity rather than denseness.

PubMed

Crawford, Joseph; Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of "topologically related" nodes, where the resulting topology-based clusters are expected to "correlate" well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data-their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance.

Dense modifiable interconnections utilizing photorefractive volume holograms

NASA Astrophysics Data System (ADS)

Psaltis, Demetri; Qiao, Yong

1990-11-01

This report describes an experimental two-layer optical neural network built at Caltech. The system uses photorefractive volume holograms to implement dense, modifiable synaptic interconnections and liquid crystal light valves (LCVS) to perform nonlinear thresholding operations. Kanerva's Sparse, Distributed Memory was implemented using this network and its ability to recognize handwritten character-alphabet (A-Z) has been demonstrated experimentally. According to Kanerva's model, the first layer has fixed, random weights of interconnections and the second layer is trained by sum-of-outer-products rule. After training, the recognition rates of the network on the training set (104 patterns) and test set (520 patterns) are 100 and 50 percent, respectively.

Enterprise virtual private network (VPN) with dense wavelength division multiplexing (DWDM) design

NASA Astrophysics Data System (ADS)

Carranza, Aparicio

An innovative computer simulation and modeling tool for metropolitan area optical data communication networks is presented. These models address the unique requirements of Virtual Private Networks for enterprise data centers, which may comprise a mixture of protocols including ESCON, FICON, Fibre Channel, Sysplex protocols (ETR, CLO, ISC); and other links interconnected over dark fiber using Dense Wavelength Division Multiplexing (DWDM). Our models have the capability of designing a network with minimal inputs; to compute optical link budgets; suggest alternative configurations; and also optimize the design based on user-defined performance metrics. The models make use of Time Division Multiplexing (TDM) wherever possible for lower data rate traffics. Simulation results for several configurations are presented and they have been validated by means of experiments conducted on the IBM enterprise network testbed in Poughkeepsie, N.Y.

The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.

PubMed

Tamminen, Jakke; Lambon Ralph, Matthew A; Lewis, Penelope A

2013-09-25

Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.

Towards to Resilience Science -Research on the Nankai trough seismogenic zone-

NASA Astrophysics Data System (ADS)

Kaneda, Yoshiyuki; Shiraki, Wataru; Fujisawa, Kazuhito; Tokozakura, Eiji

2017-04-01

For the last few decades, many destructive earthquakes and tsunamis occurred in the world. Based on lessons learnt from 2004 Sumatra Earthquake/Tsunamis, 2010 Chilean Earthquake/Tsunami and 2011 East Japan Earthquake/Tsunami, we recognized the importance of real time monitoring on Earthquakes and Tsunamis for disaster mitigation. Recently, Kumamoto Earthquake occurred in 2006. This destructive Earthquake indicated that multi strong motions including pre shock and main shock generated severe earthquake damages buildings. Furthermore, we recognize recovers/ revivals are very important and difficult. In Tohoku area damaged by large tsunamis, recovers/revivals have been under progressing after over 5 years passed after the 2011 Tohoku Earthquake. Therefore, we have to prepare the pre plan before next destructive disasters such as the Nankai trough mega thrust earthquake. As one of disaster countermeasures, we would like to propose that Disaster Mitigation Science. This disaster mitigation science is including engineering, science, medicine and social science such as sociology, informatics, law, literature, art, psychology etc. For Urgent evacuations, there are some kinds of real time monitoring system such as Dart buoy and ocean floor network. Especially, the real time monitoring system using multi kinds of sensors such as the accelerometer, broadband seismometer, pressure gauge, difference pressure gauge, hydrophone and thermometer is indispensable for Earthquakes/ Tsunamis monitoring. Furthermore, using multi kind of sensors, we can analyze and estimate broadband crustal activities around mega thrust earthquake seismogenic zones. Therefore, we deployed DONET1 and DONET2 which are dense ocean floor networks around the Nankai trough Southwestern Japan. We will explain about Resilience Science and real time monitoring systems around the Nankai trough seismogenic zone.

Shell-corona microgels from double interpenetrating networks.

PubMed

Rudyak, Vladimir Yu; Gavrilov, Alexey A; Kozhunova, Elena Yu; Chertovich, Alexander V

2018-04-18

Polymer microgels with a dense outer shell offer outstanding features as universal carriers for different guest molecules. In this paper, microgels formed by an interpenetrating network comprised of collapsed and swollen subnetworks are investigated using dissipative particle dynamics (DPD) computer simulations, and it is found that such systems can form classical core-corona structures, shell-corona structures, and core-shell-corona structures, depending on the subchain length and molecular mass of the system. The core-corona structures consisting of a dense core and soft corona are formed at small microgel sizes when the subnetworks are able to effectively separate in space. The most interesting shell-corona structures consist of a soft cavity in a dense shell surrounded with a loose corona, and are found at intermediate gel sizes; the area of their existence depends on the subchain length and the corresponding mesh size. At larger molecular masses the collapsing network forms additional cores inside the soft cavity, leading to the core-shell-corona structure.

Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations

PubMed Central

Zanimonskiy, Yevgen M.; Yampolski, Yuri M.; Figurski, Mariusz

2017-01-01

The technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate a special type of plasma inhomogeneities, called travelling ionospheric disturbances (TID). Such use of GNSS sensors allows us to reconstruct the main TID parameters, such as spatial dimensions, velocities, and directions of their movement. The paper gives examples of the restoration of dynamic characteristics of ionospheric irregularities for quiet and disturbed geophysical conditions. Special attention is paid to the dynamics of ionospheric disturbances stimulated by the magnetic storms of two St. Patrick’s Days (17 March 2013 and 2015). Additional opportunities for the remote sensing of the ionosphere with the use of dense regional networks of GNSS receiving sensors have been noted too. PMID:28994718

Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations.

PubMed

Nykiel, Grzegorz; Zanimonskiy, Yevgen M; Yampolski, Yuri M; Figurski, Mariusz

2017-10-10

The technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate a special type of plasma inhomogeneities, called travelling ionospheric disturbances (TID). Such use of GNSS sensors allows us to reconstruct the main TID parameters, such as spatial dimensions, velocities, and directions of their movement. The paper gives examples of the restoration of dynamic characteristics of ionospheric irregularities for quiet and disturbed geophysical conditions. Special attention is paid to the dynamics of ionospheric disturbances stimulated by the magnetic storms of two St. Patrick's Days (17 March 2013 and 2015). Additional opportunities for the remote sensing of the ionosphere with the use of dense regional networks of GNSS receiving sensors have been noted too.

Reservoir depletion at The Geysers geothermal area, California, shown by four-dimensional seismic tomography

USGS Publications Warehouse

Gunasekera, R.C.; Foulger, G.R.; Julian, B.R.

2003-01-01

Intensive geothermal exploitation at The Geysers geothermal area, California, induces myriads of small-magnitude earthquakes that are monitored by a dense, permanent, local seismometer network. Using this network, tomographic inversions were performed for the three-dimensional Vp and Vp/Vs structure of the reservoir for April 1991, February 1993, December 1994, October 1996, and August 1998. The extensive low-Vp/Vs anomaly that occupies the reservoir grew in strength from a maximum of 9% to a maximum of 13.4% during the 7-year study period. This is attributed to depletion of pore liquid water in the reservoir and replacement with steam. This decreases Vp by increasing compressibility, and increases Vs because of reduction in pore pressure and the drying of argillaceous minerals, e.g., illite, which increase the shear modulus. These effects serendipitously combine to lower Vp/Vs, resulting in a strong overall effect that provides a convenient tool for monitoring reservoir depletion. Variations in the Vp and Vs fields indicate that water depletion is the dominant process in the central part of the exploited reservoir, and pressure reduction and mineral drying in the northwest and southeast parts of the reservoir. The rate at which the Vp/Vs anomaly grew in strength in the period 1991-1998 suggests most of the original anomaly was caused by exploitation. Continuous monitoring of Vp, Vs, and Vp/Vs is an effective geothermal reservoir depletion monitoring tool and can potentially provide information about depletion in parts of the reservoir that have not been drilled.

Preliminary Obtained Data from Borehole Geodetic Measurements in Marmara Region, Turkey

NASA Astrophysics Data System (ADS)

Ozener, H.; Aktug, B.; Karabulut, H.; Ergintav, S.; Dogru, A.; Yilmaz, O.; Turgut, B.; Ahiska, B.; Mencin, D.; Mattioli, G. S.

2014-12-01

Dense continuous GPS networks quantify the time-dependent deformation field of the earthquake cycle. However the strainmeters can capture signals with superior precision at local spatial scales, in particular in the short-period, from minutes to a month. Many relatively small-scale events (e.i. SSEs, creeps) have been successfully determined on the subduction zones. Istanbul located near the most active parts of the North Anatolian Fault (NAF) has been monitored by different observing techniques such as seismic networks and continuous/survey-mode GPS networks for decades. However, it is still essential to observe deformation in a broad range of temporal and spatial scales (from seismology to geodesy and to geology). Borehole strainmeters are very sensitive to deformation in the range of less than a month. In this study, we present a new project, financially and technically supported by Istanbul Development Agency (ISTKA) and UNAVCO, respectively, which includes the installation of two borehole strainmeters are being deployed in European side of Istanbul in Marmara Region. Since these instruments can also respond to non-tectonic processes, it is necessary to have more instruments to increase spatial coherence and to have additional sensors to detect and model noise (such as barometric pressure, tides, or precipitation). The introduced monitoring system will provide significant insight about the creeping phenomenon and the possible SSE to our understanding of seismic hazards in active zones and possible precursors. Our long term objective is to build a borehole monitoring system in the region. By integrating various data obtained from borehole observations, we expect to get a better understanding of dynamics in the western NAF. In this presentation, we introduce data and ongoing analysis obtained with strainmeters.

On the reliability of Quake-Catcher Network earthquake detections

USGS Publications Warehouse

Yildirim, Battalgazi; Cochran, Elizabeth S.; Chung, Angela I.; Christensen, Carl M.; Lawrence, Jesse F.

2015-01-01

Over the past two decades, there have been several initiatives to create volunteer‐based seismic networks. The Personal Seismic Network, proposed around 1990, used a short‐period seismograph to record earthquake waveforms using existing phone lines (Cranswick and Banfill, 1990; Cranswicket al., 1993). NetQuakes (Luetgert et al., 2010) deploys triaxial Micro‐Electromechanical Systems (MEMS) sensors in private homes, businesses, and public buildings where there is an Internet connection. Other seismic networks using a dense array of low‐cost MEMS sensors are the Community Seismic Network (Clayton et al., 2012; Kohler et al., 2013) and the Home Seismometer Network (Horiuchi et al., 2009). One main advantage of combining low‐cost MEMS sensors and existing Internet connection in public and private buildings over the traditional networks is the reduction in installation and maintenance costs (Koide et al., 2006). In doing so, it is possible to create a dense seismic network for a fraction of the cost of traditional seismic networks (D’Alessandro and D’Anna, 2013; D’Alessandro, 2014; D’Alessandro et al., 2014).

Insights into failed lexical retrieval from network science.

PubMed

Vitevitch, Michael S; Chan, Kit Ying; Goldstein, Rutherford

2014-02-01

Previous network analyses of the phonological lexicon (Vitevitch, 2008) observed a web-like structure that exhibited assortative mixing by degree: words with dense phonological neighborhoods tend to have as neighbors words that also have dense phonological neighborhoods, and words with sparse phonological neighborhoods tend to have as neighbors words that also have sparse phonological neighborhoods. Given the role that assortative mixing by degree plays in network resilience, we examined instances of real and simulated lexical retrieval failures in computer simulations, analysis of a slips-of-the-ear corpus, and three psycholinguistic experiments for evidence of this network characteristic in human behavior. The results of the various analyses support the hypothesis that the structure of words in the mental lexicon influences lexical processing. The implications of network science for current models of spoken word recognition, language processing, and cognitive psychology more generally are discussed. Copyright © 2013 Elsevier Inc. All rights reserved.

Insights into failed lexical retrieval from network science

PubMed Central

Vitevitch, Michael S.; Chan, Kit Ying; Goldstein, Rutherford

2013-01-01

Previous network analyses of the phonological lexicon (Vitevitch, 2008) observed a web-like structure that exhibited assortative mixing by degree: words with dense phonological neighborhoods tend to have as neighbors words that also have dense phonological neighborhoods, and words with sparse phonological neighborhoods tend to have as neighbors words that also have sparse phonological neighborhoods. Given the role that assortative mixing by degree plays in network resilience, we examined instances of real and simulated lexical retrieval failures in computer simulations, analysis of a slips-of-the-ear corpus, and three psycholinguistic experiments for evidence of this network characteristic in human behavior. The results of the various analyses support the hypothesis that the structure of words in the mental lexicon influences lexical processing. The implications of network science for current models of spoken word recognition, language processing, and cognitive psychology more generally are discussed. PMID:24269488

Upgrading the seismic and geodetic network of the Popocatépetl volcano (Mexico).

NASA Astrophysics Data System (ADS)

Calò, Marco; Iglesias Mendoza, Arturo; Legrand, Denis; Valdés González, Carlos Miguel; Perez Campos, Xyoli

2017-04-01

The Popocatépetl is one of the most active volcanoes in Mexico and is located only 70 km from Mexico City, populated by more than 20 millions of people, and only 35 km from the Puebla municipality with almost 1.5 millions of people living. The recent activity of the volcano is generally marked by explosions emitting ash plumes often reaching the densely populated regions. In the framework of the Mexican Fund for Prevention of Natural Disasters (FOPREDEN) we are renovating and upgrading the existing geodetic and seismic networks monitoring the volcano. In this project we are installing 10 broadband seismic stations (120s-050Hz) in shallow boreholes (3-5m depth) and 4 GPS with real time sampling rate of 1 Hz. All instruments are equipped with continuous recording systems for real time monitoring purposes and research. The Popocatépetl exceeds 5400m, and the altitude of the stations ranges from 2200 m to 4300 m making it difficult their installation and maintenance. Because of ash emissions and the hard working condition, the real-time transmission is split into two systems in order to ensure the monitoring of the volcano also during the highest expected activity. Therefore we set up a network of "first order", consisting of four stations located about 20 km from the crater and equipped with satellite transmission. These stations, being far enough from the crater, ensure the real time monitoring of the major events also during intense periods of activity of the volcano. The remaining six stations are installed near to the crater (less than 10 km) and take part of the "second order" network equipped with a telemetered radio system transmitting the data either directly to the National Center of Disaster Prevention (CENAPRED) and National Seismological Service (SSN) or to the first order stations (for the sites that have not direct visible line with the monitoring centers). The four GPS sensors are all installed in the second order sites in order to monitor the largest deformations at the top of the volcano. In this work we show both the installation procedure of the boreholes seismometers in hard conditions and their improved performance with respect to the actual stations installed at surface and the scheme of the transmitting system for ensuring the monitoring of the Popocatépetl volcano in all the possible scenarios of its activity.

Nowcast of thunderstorm and typhoon activity based on lightning detection and flexible operation of micro-satellites

NASA Astrophysics Data System (ADS)

Takahashi, Y.

2016-12-01

It has become known that lightning activity represents the thunderstorm activity, namely, the intensity and area of precipitation and/or updraft. Thunderstorm is also important as a proxy of the energy input from ocean to atmosphere in typhoon, meaning that if we could monitor the thunderstorm with lightning we could predict the maximum wind velocity near the typhoon center by one or two days before. Constructing ELF and VLF radio wave observation network in Southeast Asia (AVON) and a regional dense network of automated weather station in a big city, we plan to establish the monitoring system for thunderstorm development in western pacific warm pool (WPWP) where typhoon is formed and in detail in big city area. On the other hand, some developing countries in SE-Asia are going to own micro-satellites dedicated to meteorological remote sensing. Making use of the lightning activity data measured by the ground-based networks, and information on 3-D structures of thunderclouds observed by the flexible on-demand operation of the remote-sensing micro-satellites, we would establish a new methodology to obtain very detail semi-real time information that cannot be achieved only with existing observation facilities, such as meteorological radar or large meteorological satellite. Using this new system we try to issue nowcast for the local thunderstorm and for typhoons. The first attempt will be carried out in Metro Manila in Philippines and WPWP as one of the SATREPS projects.

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units.

PubMed

van Beek, Adriana P A; Wagner, Cordula; Spreeuwenberg, Peter P M; Frijters, Dinnus H M; Ribbe, Miel W; Groenewegen, Peter P

2011-06-01

The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction. We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account. Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model. Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction.

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units

PubMed Central

2011-01-01

Background The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction. Methods We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account. Results Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model. Conclusions Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction. PMID:21631936

Groundwater contamination from waste management sites: The interaction between risk-based engineering design and regulatory policy: 2. Results

NASA Astrophysics Data System (ADS)

Massmann, Joel; Freeze, R. Allan

1987-02-01

The risk-cost-benefit analysis developed in the companion paper (J. Massmann and R. A. Freeze, this issue) is here applied to (1) an assessment of the relative worth of containment-construction activities, site-exploration activities, and monitoring activities as components of a design strategy for the owner/operator of a waste management facility; (2) an assessment of alternative policy options available to a regulatory agency; and (3) a case history. Sensitivity analyses designed to address the first issue show that the allocation of resources by the owner/operator is sensitive to the stochastic parameters used to describe the hydraulic conductivity field at a site. For the cases analyzed, the installation of a dense monitoring network is of less value to the owner/operator than a more conservative containment design. Sensitivity analyses designed to address the second issue suggest that from a regulatory perspective, design standards should be more effective than performance standards in reducing risk, and design specifications on the containment structure should be more effective than those on the monitoring network. Performance bonds posted before construction have a greater potential to influence design than prospective penalties to be imposed at the time of failure. Siting on low-conductivity deposits is a more effective method of risk reduction than any form of regulatory influence. Results of the case history indicate that the methodology can be successfully applied at field sites.

Measuring distance through dense weighted networks: The case of hospital-associated pathogens

PubMed Central

Smieszek, Timo; Henderson, Katherine L.; Johnson, Alan P.

2017-01-01

Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of hospital-associated pathogens. However, many studies only consider patients that are received directly from the initial hospital, without considering the effect of indirect trajectories through the network. We determine the optimal way to measure the distance between hospitals within the network, by reconstructing the English hospital network based on shared patients in 2014–2015, and simulating the spread of a hospital-associated pathogen between hospitals, taking into consideration that each intermediate hospital conveys a delay in the further spread of the pathogen. While the risk of transferring a hospital-associated pathogen between directly neighbouring hospitals is a direct reflection of the number of shared patients, the distance between two hospitals far-away in the network is determined largely by the number of intermediate hospitals in the network. Because the network is dense, most long distance transmission chains in fact involve only few intermediate steps, spreading along the many weak links. The dense connectivity of hospital networks, together with a strong regional structure, causes hospital-associated pathogens to spread from the initial outbreak in a two-step process: first, the directly surrounding hospitals are affected through the strong connections, second all other hospitals receive introductions through the multitude of weaker links. Although the strong connections matter for local spread, weak links in the network can offer ideal routes for hospital-associated pathogens to travel further faster. This hold important implications for infection prevention and control efforts: if a local outbreak is not controlled in time, colonised patients will appear in other regions, irrespective of the distance to the initial outbreak, making import screening ever more difficult. PMID:28771581

Earthquake Monitoring with the MyShake Global Smartphone Seismic Network

NASA Astrophysics Data System (ADS)

Inbal, A.; Kong, Q.; Allen, R. M.; Savran, W. H.

2017-12-01

Smartphone arrays have the potential for significantly improving seismic monitoring in sparsely instrumented urban areas. This approach benefits from the dense spatial coverage of users, as well as from communication and computational capabilities built into smartphones, which facilitate big seismic data transfer and analysis. Advantages in data acquisition with smartphones trade-off with factors such as the low-quality sensors installed in phones, high noise levels, and strong network heterogeneity, all of which limit effective seismic monitoring. Here we utilize network and array-processing schemes to asses event detectability with the MyShake global smartphone network. We examine the benefits of using this network in either triggered or continuous modes of operation. A global database of ground motions measured on stationary phones triggered by M2-6 events is used to establish detection probabilities. We find that the probability of detecting an M=3 event with a single phone located <10 km from the epicenter exceeds 70%. Due to the sensor's self-noise, smaller magnitude events at short epicentral distances are very difficult to detect. To increase the signal-to-noise ratio, we employ array back-projection techniques on continuous data recorded by thousands of phones. In this class of methods, the array is used as a spatial filter that suppresses signals emitted from shallow noise sources. Filtered traces are stacked to further enhance seismic signals from deep sources. We benchmark our technique against traditional location algorithms using recordings from California, a region with large MyShake user database. We find that locations derived from back-projection images of M 3 events recorded by >20 nearby phones closely match the regional catalog locations. We use simulated broadband seismic data to examine how location uncertainties vary with user distribution and noise levels. To this end, we have developed an empirical noise model for the metropolitan Los-Angeles (LA) area. We find that densities larger than 100 stationary phones/km2 are required to accurately locate M 2 events in the LA basin. Given the projected MyShake user distribution, that condition may be met within the next few years.

Weather monitoring and forecasting over eastern Attica (Greece) in the frame of FLIRE project

NASA Astrophysics Data System (ADS)

Kotroni, Vassiliki; Lagouvardos, Konstantinos; Chrysoulakis, Nektarios; Makropoulos, Christtos; Mimikou, Maria; Papathanasiou, Chrysoula; Poursanidis, Dimitris

2015-04-01

In the frame of FLIRE project a Decision Support System has been built with the aim to support decision making of Civil Protection Agencies and local stakeholders in the area of east Attica (Greece), in the cases of forest fires and floods. In this presentation we focus on a specific action that focuses on the provision of high resolution short-term weather forecasting data as well as of dense meteorological observations over the study area. Both weather forecasts and observations serve as an input in the Weather Information Management Tool (WIMT) of the Decision Support System. We focus on: (a) the description of the adopted strategy for setting-up the operational weather forecasting chain that provides the weather forecasts for the FLIRE project needs, (b) the presentation of the surface network station that provides real-time weather monitoring of the study area and (c) the strategy adopted for issuing smart alerts for thunderstorm forecasting based of real-time lightning observations as well as satellite observations.

Highly Adaptive Solid-Liquid Interfacing Triboelectric Nanogenerator for Harvesting Diverse Water Wave Energy.

PubMed

Zhao, Xue Jiao; Kuang, Shuang Yang; Wang, Zhong Lin; Zhu, Guang

2018-05-22

Harvesting water wave energy presents a significantly practical route to energy supply for self-powered wireless sensing networks. Here we report a networked integrated triboelectric nanogenerator (NI-TENG) as a highly adaptive means of harvesting energy from interfacing interactions with various types of water waves. Having an arrayed networking structure, the NI-TENG can accommodate diverse water wave motions and generate stable electric output regardless of how random the water wave is. Nanoscaled surface morphology consisting of dense nanowire arrays is the key for obtaining high electric output. A NI-TENG having an area of 100 × 70 mm 2 can produce a stable short-circuit current of 13.5 μA and corresponding electric power of 1.03 mW at a water wave height of 12 cm. This merit promises practical applications of the NI-TENG in real circumstances, where water waves are highly variable and unpredictable. After energy storage, the generated electric energy can drive wireless sensing by autonomously transmitting data at a period less than 1 min. This work proposes a viable solution for powering individual standalone nodes in a wireless sensor network. Potential applications include but are not limited to long-term environment monitoring, marine surveillance, and off-shore navigation.

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

PubMed Central

Jang, Min Jee; Nam, Yoonkey

2015-01-01

Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973

High Resolution Sensing and Control of Urban Water Networks

NASA Astrophysics Data System (ADS)

Bartos, M. D.; Wong, B. P.; Kerkez, B.

2016-12-01

We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.

ClueNet: Clustering a temporal network based on topological similarity rather than denseness

PubMed Central

Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of “topologically related” nodes, where the resulting topology-based clusters are expected to “correlate” well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data—their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance. PMID:29738568

Ultra-low power high precision magnetotelluric receiver array based customized computer and wireless sensor network

NASA Astrophysics Data System (ADS)

Chen, R.; Xi, X.; Zhao, X.; He, L.; Yao, H.; Shen, R.

2016-12-01

Dense 3D magnetotelluric (MT) data acquisition owns the benefit of suppressing the static shift and topography effect, can achieve high precision and high resolution inversion for underground structure. This method may play an important role in mineral exploration, geothermal resources exploration, and hydrocarbon exploration. It's necessary to reduce the power consumption greatly of a MT signal receiver for large-scale 3D MT data acquisition while using sensor network to monitor data quality of deployed MT receivers. We adopted a series of technologies to realized above goal. At first, we designed an low-power embedded computer which can couple with other parts of MT receiver tightly and support wireless sensor network. The power consumption of our embedded computer is less than 1 watt. Then we designed 4-channel data acquisition subsystem which supports 24-bit analog-digital conversion, GPS synchronization, and real-time digital signal processing. Furthermore, we developed the power supply and power management subsystem for MT receiver. At last, a series of software, which support data acquisition, calibration, wireless sensor network, and testing, were developed. The software which runs on personal computer can monitor and control over 100 MT receivers on the field for data acquisition and quality control. The total power consumption of the receiver is about 2 watts at full operation. The standby power consumption is less than 0.1 watt. Our testing showed that the MT receiver can acquire good quality data at ground with electrical dipole length as 3 m. Over 100 MT receivers were made and used for large-scale geothermal exploration in China with great success.

Near-field observations of an offshore Mw 6.0 earthquake from an integrated seafloor and subseafloor monitoring network at the Nankai Trough, southwest Japan

NASA Astrophysics Data System (ADS)

Wallace, L. M.; Araki, E.; Saffer, D.; Wang, X.; Roesner, A.; Kopf, A.; Nakanishi, A.; Power, W.; Kobayashi, R.; Kinoshita, C.; Toczko, S.; Kimura, T.; Machida, Y.; Carr, S.

2016-11-01

An Mw 6.0 earthquake struck 50 km offshore the Kii Peninsula of southwest Honshu, Japan on 1 April 2016. This earthquake occurred directly beneath a cabled offshore monitoring network at the Nankai Trough subduction zone and within 25-35 km of two borehole observatories installed as part of the International Ocean Discovery Program's NanTroSEIZE project. The earthquake's location close to the seafloor and subseafloor network offers a unique opportunity to evaluate dense seafloor geodetic and seismological data in the near field of a moderate-sized offshore earthquake. We use the offshore seismic network to locate the main shock and aftershocks, seafloor pressure sensors, and borehole observatory data to determine the detailed distribution of seafloor and subseafloor deformation, and seafloor pressure observations to model the resulting tsunami. Contractional strain estimated from formation pore pressure records in the borehole observatories (equivalent to 0.37 to 0.15 μstrain) provides a key to narrowing the possible range of fault plane solutions. Together, these data show that the rupture occurred on a landward dipping thrust fault at 9-10 km below the seafloor, most likely on the plate interface. Pore pressure changes recorded in one of the observatories also provide evidence for significant afterslip for at least a few days following the main shock. The earthquake and its aftershocks are located within the coseismic slip region of the 1944 Tonankai earthquake (Mw 8.0), and immediately downdip of swarms of very low frequency earthquakes in this region, illustrating the complex distribution of megathrust slip behavior at a dominantly locked seismogenic zone.

Pedestrian detection in video surveillance using fully convolutional YOLO neural network

NASA Astrophysics Data System (ADS)

Molchanov, V. V.; Vishnyakov, B. V.; Vizilter, Y. V.; Vishnyakova, O. V.; Knyaz, V. A.

2017-06-01

More than 80% of video surveillance systems are used for monitoring people. Old human detection algorithms, based on background and foreground modelling, could not even deal with a group of people, to say nothing of a crowd. Recent robust and highly effective pedestrian detection algorithms are a new milestone of video surveillance systems. Based on modern approaches in deep learning, these algorithms produce very discriminative features that can be used for getting robust inference in real visual scenes. They deal with such tasks as distinguishing different persons in a group, overcome problem with sufficient enclosures of human bodies by the foreground, detect various poses of people. In our work we use a new approach which enables to combine detection and classification tasks into one challenge using convolution neural networks. As a start point we choose YOLO CNN, whose authors propose a very efficient way of combining mentioned above tasks by learning a single neural network. This approach showed competitive results with state-of-the-art models such as FAST R-CNN, significantly overcoming them in speed, which allows us to apply it in real time video surveillance and other video monitoring systems. Despite all advantages it suffers from some known drawbacks, related to the fully-connected layers that obstruct applying the CNN to images with different resolution. Also it limits the ability to distinguish small close human figures in groups which is crucial for our tasks since we work with rather low quality images which often include dense small groups of people. In this work we gradually change network architecture to overcome mentioned above problems, train it on a complex pedestrian dataset and finally get the CNN detecting small pedestrians in real scenes.

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

2014-01-01

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277

Assessing the potential of reservoir outflow management to reduce sedimentation using continuous turbidity monitoring and reservoir modelling

USGS Publications Warehouse

Lee, Casey; Foster, Guy

2013-01-01

In-stream sensors are increasingly deployed as part of ambient water quality-monitoring networks. Temporally dense data from these networks can be used to better understand the transport of constituents through streams, lakes or reservoirs. Data from existing, continuously recording in-stream flow and water quality monitoring stations were coupled with the two-dimensional hydrodynamic CE-QUAL-W2 model to assess the potential of altered reservoir outflow management to reduce sediment trapping in John Redmond Reservoir, located in east-central Kansas. Monitoring stations upstream and downstream from the reservoir were used to estimate 5.6 million metric tons of sediment transported to John Redmond Reservoir from 2007 through 2010, 88% of which was trapped within the reservoir. The two-dimensional model was used to estimate the residence time of 55 equal-volume releases from the reservoir; sediment trapping for these releases varied from 48% to 97%. Smaller trapping efficiencies were observed when the reservoir was maintained near the normal operating capacity (relative to higher flood pool levels) and when average residence times were relatively short. An idealized, alternative outflow management scenario was constructed, which minimized reservoir elevations and the length of time water was in the reservoir, while continuing to meet downstream flood control end points identified in the reservoir water control manual. The alternative scenario is projected to reduce sediment trapping in the reservoir by approximately 3%, preventing approximately 45 000 metric tons of sediment from being deposited within the reservoir annually. This article presents an approach to quantify the potential of reservoir management using existing in-stream data; actual management decisions need to consider the effects on other reservoir benefits, such as downstream flood control and aquatic life.

Examining the Acquisition of Phonological Word Forms with Computational Experiments

ERIC Educational Resources Information Center

Vitevitch, Michael S.; Storkel, Holly L.

2013-01-01

It has been hypothesized that known words in the lexicon strengthen newly formed representations of novel words, resulting in words with dense neighborhoods being learned more quickly than words with sparse neighborhoods. Tests of this hypothesis in a connectionist network showed that words with dense neighborhoods were learned better than words…

Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury

PubMed Central

Dimitriadis, Stavros I.; Zouridakis, George; Rezaie, Roozbeh; Babajani-Feremi, Abbas; Papanicolaou, Andrew C.

2015-01-01

Mild traumatic brain injury (mTBI) may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI. PMID:26640764

Structural Transitions in Densifying Networks

NASA Astrophysics Data System (ADS)

Lambiotte, R.; Krapivsky, P. L.; Bhat, U.; Redner, S.

2016-11-01

We introduce a minimal generative model for densifying networks in which a new node attaches to a randomly selected target node and also to each of its neighbors with probability p . The networks that emerge from this copying mechanism are sparse for p <1/2 and dense (average degree increasing with number of nodes N ) for p ≥1/2 . The behavior in the dense regime is especially rich; for example, individual network realizations that are built by copying are disparate and not self-averaging. Further, there is an infinite sequence of structural anomalies at p =2/3 , 3/4 , 4/5 , etc., where the N dependences of the number of triangles (3-cliques), 4-cliques, undergo phase transitions. When linking to second neighbors of the target can occur, the probability that the resulting graph is complete—all nodes are connected—is nonzero as N →∞ .

Impact of branching on the elasticity of actin networks

PubMed Central

Pujol, Thomas; du Roure, Olivia; Fermigier, Marc; Heuvingh, Julien

2012-01-01

Actin filaments play a fundamental role in cell mechanics: assembled into networks by a large number of partners, they ensure cell integrity, deformability, and migration. Here we focus on the mechanics of the dense branched network found at the leading edge of a crawling cell. We develop a new technique based on the dipolar attraction between magnetic colloids to measure mechanical properties of branched actin gels assembled around the colloids. This technique allows us to probe a large number of gels and, through the study of different networks, to access fundamental relationships between their microscopic structure and their mechanical properties. We show that the architecture does regulate the elasticity of the network: increasing both capping and branching concentrations strongly stiffens the networks. These effects occur at protein concentrations that can be regulated by the cell. In addition, the dependence of the elastic modulus on the filaments’ flexibility and on increasing internal stress has been studied. Our overall results point toward an elastic regime dominated by enthalpic rather than entropic deformations. This result strongly differs from the elasticity of diluted cross-linked actin networks and can be explained by the dense dendritic structure of lamellipodium-like networks. PMID:22689953

The Continuous Generation of Equatorial Plasma Bubbles during the Passage of the Solar Terminator, Observed with a Densely-Clustered Network of GPS Receivers in Southeast Asia.

NASA Astrophysics Data System (ADS)

Buhari, S. M.; Tsunoda, R. T.; Abdullah, M.; Hasbi, A. M.; Otsuka, Y.; Yokoyama, T.; Nishioka, M.; Tsugawa, T.

2014-12-01

Equatorial plasma bubbles (EPBs) are three-dimensional structures of depleted plasma density that are often observed in the nighttime equatorial ionosphere. They are initiated near the magnetic dip equator, in the bottomside of the F layer, and develop with time, upward in altitude and poleward in latitude (into both hemispheres), taking the form of longitudinally-narrow, vertically-extended wedges that penetrate deep into the topside of the F layer. Moreover, these structures drift zonally as they evolve in time. Much of what is not yet known about EPBs stems from our inability (1) to capture spatial descriptions of these structures, and (2) to monitor their evolution as a function of time. An objective of this presentation is to report the existence and availability of total electron content (TEC) data from densely-clustered networks of GPS receivers that are capable of providing time-continuous descriptions of EPBs with both high spatial resolution and broad geographical coverage. The networks include the Malaysia Real-Time Kinematics GNSS Network (MyRTKnet), Sumatera GPS Array (SUGAR) network and International GNSS Service (IGS) located in Southeast Asia (SEA). These networks contain 127 GPS receivers with average spacing of about 50 to 100 km. With the ability to resolve space-time ambiguities, we are able to follow the temporal evolution of EPB structures over an extended longitude sector (90 to 120 degrees, East longitude). We will present results from a case study (April 5, 2011) in which 16 EPBs were detected in longitude and tracked in time. We show, for the first time, that the births of 10 out of 16 observed EPBs coincided with the time of passage of the solar terminator across the longitude of birth. The distance between birth locations varied between 100 and 550 km with 10-minute interval. These EPBs were found to persist for 50 minutes to 7 hours, while drifting eastward at a speed of 92 to 150 ms-1. The finding that as many as 16 EPBs can be generated in a continuous sequence over 30 degree of longitude is new. The implications of these findings in terms of seeding and amplification will be discussed.

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 snowfall in southern part of the country. There are presented as well: the evaluation of differences in 2D fields of ZTD and IWV obtained from ASG-EUPOS network only and from ASG-EUPOS and SmartNet networks, their validation using IWV from numerical weather model and CM-SAF (Satellite Application Facility on Climate Monitoring) data. The results are interpreted towards the increase of possibility to detect the meso-scale weather features with densification of GNSS sensors network.

Two Novel Rab2 Interactors Regulate Dense-core Vesicle Maturation

PubMed Central

Ailion, Michael; Hannemann, Mandy; Dalton, Susan; Pappas, Andrea; Watanabe, Shigeki; Hegermann, Jan; Liu, Qiang; Han, Hsiao-Fen; Gu, Mingyu; Goulding, Morgan Q.; Sasidharan, Nikhil; Schuske, Kim; Hullett, Patrick; Eimer, Stefan; Jorgensen, Erik M.

2014-01-01

Summary Peptide neuromodulators are released from a unique organelle: the dense-core vesicle. Dense-core vesicles are generated at the trans-Golgi, and then sort cargo during maturation before being secreted. To identify proteins that act in this pathway, we performed a genetic screen in Caenorhabditis elegans for mutants defective in dense-core vesicle function. We identified two conserved Rab2-binding proteins: RUND-1, a RUN domain protein, and CCCP-1, a coiled-coil protein. RUND-1 and CCCP-1 colocalize with RAB-2 at the Golgi, and rab-2, rund-1 and cccp-1 mutants have similar defects in sorting soluble and transmembrane dense-core vesicle cargos. RUND-1 also interacts with the Rab2 GAP protein TBC-8 and the BAR domain protein RIC-19, a RAB-2 effector. In summary, a new pathway of conserved proteins controls the maturation of dense-core vesicles at the trans-Golgi network. PMID:24698274

Semi-Automated Air-Coupled Impact-Echo Method for Large-Scale Parkade Structure.

PubMed

Epp, Tyler; Svecova, Dagmar; Cha, Young-Jin

2018-03-29

Structural Health Monitoring (SHM) has moved to data-dense systems, utilizing numerous sensor types to monitor infrastructure, such as bridges and dams, more regularly. One of the issues faced in this endeavour is the scale of the inspected structures and the time it takes to carry out testing. Installing automated systems that can provide measurements in a timely manner is one way of overcoming these obstacles. This study proposes an Artificial Neural Network (ANN) application that determines intact and damaged locations from a small training sample of impact-echo data, using air-coupled microphones from a reinforced concrete beam in lab conditions and data collected from a field experiment in a parking garage. The impact-echo testing in the field is carried out in a semi-autonomous manner to expedite the front end of the in situ damage detection testing. The use of an ANN removes the need for a user-defined cutoff value for the classification of intact and damaged locations when a least-square distance approach is used. It is postulated that this may contribute significantly to testing time reduction when monitoring large-scale civil Reinforced Concrete (RC) structures.

Semi-Automated Air-Coupled Impact-Echo Method for Large-Scale Parkade Structure

PubMed Central

Epp, Tyler; Svecova, Dagmar; Cha, Young-Jin

2018-01-01

Structural Health Monitoring (SHM) has moved to data-dense systems, utilizing numerous sensor types to monitor infrastructure, such as bridges and dams, more regularly. One of the issues faced in this endeavour is the scale of the inspected structures and the time it takes to carry out testing. Installing automated systems that can provide measurements in a timely manner is one way of overcoming these obstacles. This study proposes an Artificial Neural Network (ANN) application that determines intact and damaged locations from a small training sample of impact-echo data, using air-coupled microphones from a reinforced concrete beam in lab conditions and data collected from a field experiment in a parking garage. The impact-echo testing in the field is carried out in a semi-autonomous manner to expedite the front end of the in situ damage detection testing. The use of an ANN removes the need for a user-defined cutoff value for the classification of intact and damaged locations when a least-square distance approach is used. It is postulated that this may contribute significantly to testing time reduction when monitoring large-scale civil Reinforced Concrete (RC) structures. PMID:29596332

Localization Strategies in WSNs as applied to Landslide Monitoring (Invited)

NASA Astrophysics Data System (ADS)

Massa, A.; Robol, F.; Polo, A.; Giarola, E.; Viani, F.

2013-12-01

In the last years, heterogeneous integrated smart systems based on wireless sensor network (WSN) technology have been developed at the ELEDIA Research Center of the University of Trento [1]. One of the key features of WSNs as applied to distributed monitoring is that, while the capabilities of each single sensor node is limited, the implementation of cooperative schemes throughout the whole network enables the solution of even complex tasks, as the landslide monitoring. The capability of localizing targets respect to the position of the sensor nodes turns out to be fundamental in those application fields where relative movements arise. The main properties like the target typology, the movement characteristics, and the required localization resolution are different changing the reference scenario. However, the common key issue is still the localization of moving targets within the area covered by the sensor network. Many experiences were preparatory for the challenging activities in the field of landslide monitoring where the basic idea is mostly that of detecting slight soil movements. Among them, some examples of WSN-based systems experimentally applied to the localization of people [2] and wildlife [3] have been proposed. More recently, the WSN backbone as well as the investigated sensing technologies have been customized for monitoring superficial movements of the soil. The relative positions of wireless sensor nodes deployed where high probability of landslide exists is carefully monitored to forecast dangerous events. Multiple sensors like ultrasound, laser, high precision GPS, for the precise measurement of relative distances between the nodes of the network and the absolute positions respect to reference targets have been integrated in a prototype system. The millimeter accuracy in the position estimation enables the detection of small soil modifications and to infer the superficial evolution profile of the landslide. This information locally acquired also represent a fine tuning of large scale satellite acquisitions, usually adopted for remote sensing of landslides. The integration of dense and frequent WSN data within satellite image analysis will enhance the sensing capabilities leading to a multi-resolution and an highly space-time calibrated system. The WSN-based system has been preliminary tested in controlled environments in the ELEDIA laboratories and is now installed in a real test site where an active landslide is evolving. Preliminary data are here presented to assess the feasibility of the investigated solution in landslide monitoring and event forecasting. REFERENCES [1] M. Benedetti, L. Ioriatti, M. Martinelli, and F. Viani, 'Wireless sensor network: a pervasive technology for earth observation,' in IEEE Journal of Selected Topics in App. Earth Obs. And Remote Sens., vol. 3, no. 4, pp. 488-497, 2010. [2] F. Viani, M. Donelli, P. Rocca, G. Oliveri, D. Trinchero, and A. Massa, 'Localization, tracking and imaging of targets in wireless sensor networks,' Radio Science, vol. 46, no. 5, 2011. [3] F. Viani, F. Robol, M. Salucci, E. Giarola, S. De Vigili, M. Rocca, F. Boldrini, G. Benedetti, and A. Massa, 'WSN-based early alert system for preventing wildlife-vehicle collisions in Alps regions - From the laboratory test to the real-world implementation,' 7th European Conference on Antennas and Propagation 2013 (EUCAP2013), Gothenburg, Sweden, April 8-12, 2013.

A Multilevel Gamma-Clustering Layout Algorithm for Visualization of Biological Networks

PubMed Central

Hruz, Tomas; Lucas, Christoph; Laule, Oliver; Zimmermann, Philip

2013-01-01

Visualization of large complex networks has become an indispensable part of systems biology, where organisms need to be considered as one complex system. The visualization of the corresponding network is challenging due to the size and density of edges. In many cases, the use of standard visualization algorithms can lead to high running times and poorly readable visualizations due to many edge crossings. We suggest an approach that analyzes the structure of the graph first and then generates a new graph which contains specific semantic symbols for regular substructures like dense clusters. We propose a multilevel gamma-clustering layout visualization algorithm (MLGA) which proceeds in three subsequent steps: (i) a multilevel γ-clustering is used to identify the structure of the underlying network, (ii) the network is transformed to a tree, and (iii) finally, the resulting tree which shows the network structure is drawn using a variation of a force-directed algorithm. The algorithm has a potential to visualize very large networks because it uses modern clustering heuristics which are optimized for large graphs. Moreover, most of the edges are removed from the visual representation which allows keeping the overview over complex graphs with dense subgraphs. PMID:23864855

Enhanced Deployment Strategy for Role-based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

NASA Astrophysics Data System (ADS)

Gendreau, Audrey

Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing application had established the network traffic flow to the sink. The same scenario was repeated using a power-based IDS to compare it against the proposed model. To identify a clusterhead's ability to host monitoring agents after the temperature sensing application terminated, the deployed IDS utilized the communication history and other network factors in order to rank the nodes. Similarly, using the node's communication history, the deployed power-based IDS ranked nodes based on their remaining power. For each individual scenario, and after the IDS application was deployed, the temperature sensing application was run for a second time. This time, to monitor the temperature sensing agents as the data flowed towards the sink, the network traffic was rerouted through the new intrusion detection clusterheads. Consequently, if the clusterheads were shared, the re-routing step was not preformed. Experimental results in this research demonstrated the effectiveness of applying a robust deployment metric to improve upon the energy efficiency of a deployed application in a multi-application WSN. It was found that in the scenarios with the intrusion detection application that utilized the proposed model resulted in more remaining energy than in the scenarios that implemented the power-based IDS. The algorithm especially had a positive impact on the small, dense, and more homogeneous networks. This finding was reinforced by the smaller percentage of new clusterheads that was selected. Essentially, the energy cost of the route to the sink was reduced because the network traffic was rerouted through fewer new clusterheads. Additionally, it was found that the intrusion detection topology that used the proposed approach formed smaller and more connected sets of clusterheads than the power-based IDS. As a consequence, this proposed approach essentially achieved the research objective for enhancing energy use in a multi-application WSN.

Dense wavelength division multiplexing devices for metropolitan-area datacom and telecom networks

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.; Priest, David G.

2000-12-01

Large data processing environments in use today can require multi-gigabyte or terabyte capacity in the data communication infrastructure; these requirements are being driven by storage area networks with access to petabyte data bases, new architecture for parallel processing which require high bandwidth optical links, and rapidly growing network applications such as electronic commerce over the Internet or virtual private networks. These datacom applications require high availability, fault tolerance, security, and the capacity to recover from any single point of failure without relying on traditional SONET-based networking. These requirements, coupled with fiber exhaust in metropolitan areas, are driving the introduction of dense optical wavelength division multiplexing (DWDM) in data communication systems, particularly for large enterprise servers or mainframes. In this paper, we examine the technical requirements for emerging nextgeneration DWDM systems. Protocols for storage area networks and computer architectures such as Parallel Sysplex are presented, including their fiber bandwidth requirements. We then describe two commercially available DWDM solutions, a first generation 10 channel system and a recently announced next generation 32 channel system. Technical requirements, network management and security, fault tolerant network designs, new network topologies enabled by DWDM, and the role of time division multiplexing in the network are all discussed. Finally, we present a description of testing conducted on these networks and future directions for this technology.

Spatial analysis of storm depths from an Arizona raingage network

NASA Technical Reports Server (NTRS)

Fennessey, N. M.; Eagleson, P. S.; Qinliang, W.; Rodriguez-Iturbe, I.

1986-01-01

Eight years of summer rainstorm observations are analyzed by a dense network of 93 raingages operated by the U.S. Department of Agriculture, Agricultural Research Service, in the 150 km Walnut Gulch experimental catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon-to-noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storm days, the gage depths are interpolated onto a dense grid and the resulting random field analyzed to obtain moments, isohyetal plots, spatial correlation function, variance function, and the spatial distribution of storm depth.

Efficient Graph-Based Resource Allocation Scheme Using Maximal Independent Set for Randomly- Deployed Small Star Networks

PubMed Central

Zhou, Jian; Wang, Lusheng; Wang, Weidong; Zhou, Qingfeng

2017-01-01

In future scenarios of heterogeneous and dense networks, randomly-deployed small star networks (SSNs) become a key paradigm, whose system performance is restricted to inter-SSN interference and requires an efficient resource allocation scheme for interference coordination. Traditional resource allocation schemes do not specifically focus on this paradigm and are usually too time consuming in dense networks. In this article, a very efficient graph-based scheme is proposed, which applies the maximal independent set (MIS) concept in graph theory to help divide SSNs into almost interference-free groups. We first construct an interference graph for the system based on a derived distance threshold indicating for any pair of SSNs whether there is intolerable inter-SSN interference or not. Then, SSNs are divided into MISs, and the same resource can be repetitively used by all the SSNs in each MIS. Empirical parameters and equations are set in the scheme to guarantee high performance. Finally, extensive scenarios both dense and nondense are randomly generated and simulated to demonstrate the performance of our scheme, indicating that it outperforms the classical max K-cut-based scheme in terms of system capacity, utility and especially time cost. Its achieved system capacity, utility and fairness can be close to the near-optimal strategy obtained by a time-consuming simulated annealing search. PMID:29113109

Deployment of a seismic array for volcano monitoring during the ongoing submarine eruption at El Hierro, Canary Islands

NASA Astrophysics Data System (ADS)

Abella, R.; Almendros, J.; Carmona, E.; Martin, R.

2012-04-01

On 17 July 2011 there was an important increase of the seismic activity at El Hierro (Canary Islands, Spain). This increase was detected by the Volcano Monitoring Network (Spanish national seismic network) run by the Instituto Geográfico Nacional (IGN). As a consequence, the IGN immediately deployed a dense, complete monitoring network that included seismometers, GPS stations, geochemical equipment, magnetometers, and gravity meters. During the first three months of activity, the seismic network recorded over ten thousand volcano-tectonic earthquakes, with a maximum magnitude of 4.6. On 10 October 2011 an intense volcanic tremor started. It was a monochromatic signal, with variable amplitude and frequency content centered at about 1-2 Hz. The tremor onset was correlated with the initial stages of the submarine eruption that occurred from a vent located south of El Hierro island, near the village of La Restinga. At that point the IGN, in collaboration with the Instituto Andaluz de Geofísica, deployed a seismic array intended for volcanic tremor monitoring and analysis. The seismic array is located about 7 km NW of the submarine vent. It has a 12-channel, 24-bit data acquisition system sampling each channel at 100 sps. The array is composed by 1 three-component and 9 vertical-component seismometers, distributed in a flat area with an aperture of 360 m. The data provided by the seismic array are going to be processed using two different approaches: (1) near-real-time, to produce information that can be useful in the management of the volcanic crisis; and (2) detailed investigations, to study the volcanic tremor characteristics and relate them to the eruption dynamics. At this stage we are mostly dedicated to produce fast, near-real-time estimates. Preliminary results have been obtained using the maximum average cross-correlation method. They indicate that the tremor wavefronts are highly coherent among array stations and propagate across the seismic array with an apparent slowness of ~0.8 s/km and a back-azimuth of 135°N. These estimates have remained approximately constant since the onset of volcanic tremor, indicating a unique source and thus a single, continuing eruptive center.

The Detection of Very Low Frequency Earthquake using Broadband Seismic Array Data in South-Western Japan

NASA Astrophysics Data System (ADS)

Ishihara, Y.; Yamanaka, Y.; Kikuchi, M.

2002-12-01

The existences of variety of low-frequency seismic sources are obvious by the dense and equalized equipment_fs seismic network. Kikuchi(2000) and Kumagai et.al. (2001) analyzed about 50sec period ground motion excited by the volcanic activities Miyake-jima, Izu Islands. JMA is listing the low frequency earthquakes routinely in their hypocenter determination. Obara (2002) detected the low frequency, 2-4 Hz, tremor that occurred along subducting Philippine Sea plate by envelope analysis of high dense and short period seismic network (Hi-net). The monitoring of continuos long period waveform show us the existence of many unknown sources. Recently, the broadband seismic network of Japan (F-net, previous name is FREESIA) is developed and extends to linear array about 3,000 km. We reviewed the long period seismic data and earthquake catalogues. Many candidates, which are excited by unknown sources, are picked up manually. The candidates are reconfirmed in detail by the original seismograms and their rough frequency characteristics are evaluated. Most events have the very low frequency seismograms that is dominated period of 20 _E30 sec and smaller amplitude than ground noise level in shorter period range. We developed the hypocenter determination technique applied the grid search method. Moreover for the major events moment tensor inversion was performed. The most source locates at subducting plate and their depth is greater than 30km. However the location don_ft overlap the low frequency tremor source region. Major event_fs moment magnitude is 4 or greater and estimated source time is around 20 sec. We concluded that low frequency seismic event series exist in wide period range in subduction area. The very low frequency earthquakes occurred along Nankai and Ryukyu trough at southwestern Japan. We are planing to survey the very low frequency event systematically in wider western Pacific region.

Optoelectronic Integrated Circuits For Neural Networks

NASA Technical Reports Server (NTRS)

Psaltis, D.; Katz, J.; Kim, Jae-Hoon; Lin, S. H.; Nouhi, A.

1990-01-01

Many threshold devices placed on single substrate. Integrated circuits containing optoelectronic threshold elements developed for use as planar arrays of artificial neurons in research on neural-network computers. Mounted with volume holograms recorded in photorefractive crystals serving as dense arrays of variable interconnections between neurons.

Maturation State and Matrix Microstructure Regulate Interstitial Cell Migration in Dense Connective Tissues.

PubMed

Qu, Feini; Li, Qing; Wang, Xiao; Cao, Xuan; Zgonis, Miltiadis H; Esterhai, John L; Shenoy, Vivek B; Han, Lin; Mauck, Robert L

2018-02-19

Few regenerative approaches exist for the treatment of injuries to adult dense connective tissues. Compared to fetal tissues, adult connective tissues are hypocellular and show limited healing after injury. We hypothesized that robust repair can occur in fetal tissues with an immature extracellular matrix (ECM) that is conducive to cell migration, and that this process fails in adults due to the biophysical barriers imposed by the mature ECM. Using the knee meniscus as a platform, we evaluated the evolving micromechanics and microstructure of fetal and adult tissues, and interrogated the interstitial migratory capacity of adult meniscal cells through fetal and adult tissue microenvironments with or without partial enzymatic digestion. To integrate our findings, a computational model was implemented to determine how changing biophysical parameters impact cell migration through these dense networks. Our results show that the micromechanics and microstructure of the adult meniscus ECM sterically hinder cell mobility, and that modulation of these ECM attributes via an exogenous matrix-degrading enzyme permits migration through this otherwise impenetrable network. By addressing the inherent limitations to repair imposed by the mature ECM, these studies may define new clinical strategies to promote repair of damaged dense connective tissues in adults.

Wireless sensor network: an aimless gadget or a necessary tool for natural hazards warning systems

NASA Astrophysics Data System (ADS)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

The purpose of the current study is to review the current technical and scientific state of wireless sensor networks (WSNs) with application on natural hazards. WSN have received great attention from the research community in the last few years, mainly due to the theoretical and practical efforts from challenges that led to mature solutions and adoption of standards, such as Bluetooth [2] and ZigBee [3]. Wireless technology solutions allows Micro-ElectroMechanical Systems sensors (MEMS) to be integrated (with all the necessary circuitry) to small wireless capable devices, the nodes. Available MEMS today include pressure, temperature, humidity, inertial and strain-gauge sensors as well as transducers for velocity, acceleration, vibration, flow position and inclination [4]. A WSN is composed by a large number of nodes which are deployed densely adjacent to the area under monitoring. Each node collects data which transmitted to a gateway. The main requirements that WSNs must fulfilled are quite different than those of ad-hoc networks. WSNs have to be self-organized (since the positions of individual nodes are not known in advance), they must present cooperative processing of tasks (where groups of nodes cooperate in order to provide the gathered data to the user), they require security mechanisms that are adaptive to monitoring conditions and all algorithms must be energy optimized. In this paper, the state of the art in hardware, software, algorithms and protocols for WSNs, focused on natural hazards, is surveyed. Architectures for WSNs are investigated along with their advantages and drawbacks. Available research prototypes as well as commercially proposed solutions that can be used for natural hazards monitoring and early warning systems are listed and classified. [1] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, Wireless sensor networks: a survey, Comput. Networks (Elsevier) 38 (4) (2002) 393-422. [2] Dursch, A.; Yen, D.C.; Shih, D.H. Bluetooth technology: an exploratory study of the analysis and implementation frameworks. Comput. Stand. Interface. 2004, 26, 263-277. [3] Baronti, P.; Pillai, P.; Chook, V.W.C.; Chessa, S.; Gotta, A.; Hu, Y.F. Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Comput. Commun. 2007, 30, 1655-1695. [4] Arampatzis, T.; Lygeros, J.; Manesis, S. A survey of applications of wireless sensors and Wireless Sensor Networks. In 2005 IEEE International Symposium on Intelligent Control & 13th Mediterranean Conference on Control and Automation. Limassol, Cyprus, 2005, 1-2, 719-724.

Detection, location, and characterization of hydroacoustic signals using seafloor cable networks offshore Japan (Invited)

NASA Astrophysics Data System (ADS)

Sugioka, H.; Suyehiro, K.; Shinohara, M.

2009-12-01

The hydroacoustic monitoring by the International Monitoring System (IMS) for Comprehensive Nuclear-Test-Treaty (CTBT) verification system utilize hydrophone stations and seismic stations called T-phase stations for worldwide detection. Some signals of natural origin include those from earthquakes, submarine volcanic eruptions, or whale calls. Among artificial sources there are non-nuclear explosions and air-gun shots. It is important for IMS system to detect and locate hydroacoustic events with sufficient accuracy and correctly characterize the signals and identify the source. As there are a number of seafloor cable networks operated offshore Japanese islands basically facing the Pacific Ocean for monitoring regional seismicity, the data from these stations (pressures, hydrophones and seismic sensors) may be utilized to verify and increase the capability of the IMS. We use these data to compare some selected event parameters with those by Pacific in the time period of 2004-present. These anomalous examples and also dynamite shots used for seismic crustal structure studies and other natural sources will be presented in order to help improve the IMS verification capabilities for detection, location and characterization of anomalous signals. The seafloor cable networks composed of three hydrophones and six seismometers and a temporal dense seismic array detected and located hydroacoustic events offshore Japanese island on 12th of March in 2008, which had been reported by the IMS. We detected not only the reverberated hydroacoustic waves between the sea surface and the sea bottom but also the seismic waves going through the crust associated with the events. The determined source of the seismic waves is almost coincident with the one of hydroacoustic waves, suggesting that the seismic waves are converted very close to the origin of the hydroacoustic source. We also detected very similar signals on 16th of March in 2009 to the ones associated with the event of 12th of March in 2008.

EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

PubMed Central

Garcia, Fernando P.; Andrade, Rossana M. C.; Oliveira, Carina T.; de Souza, José Neuman

2014-01-01

Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios. PMID:24949639

Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Cazorla, Alberto; Andrés Casquero-Vera, Juan; Román, Roberto; Guerrero-Rascado, Juan Luis; Toledano, Carlos; Cachorro, Victoria E.; Orza, José Antonio G.; Cancillo, María Luisa; Serrano, Antonio; Titos, Gloria; Pandolfi, Marco; Alastuey, Andres; Hanrieder, Natalie; Alados-Arboledas, Lucas

2017-10-01

The interest in the use of ceilometers for optical aerosol characterization has increased in the last few years. They operate continuously almost unattended and are also much less expensive than lidars; hence, they can be distributed in dense networks over large areas. However, due to the low signal-to-noise ratio it is not always possible to obtain particle backscatter coefficient profiles, and the vast number of data generated require an automated and unsupervised method that ensures the quality of the profiles inversions. In this work we describe a method that uses aerosol optical depth (AOD) measurements from the AERONET network that it is applied for the calibration and automated quality assurance of inversion of ceilometer profiles. The method is compared with independent inversions obtained by co-located multiwavelength lidar measurements. A difference smaller than 15 % in backscatter is found between both instruments. This method is continuously and automatically applied to the Iberian Ceilometer Network (ICENET) and a case example during an unusually intense dust outbreak affecting the Iberian Peninsula between 20 and 24 February 2016 is shown. Results reveal that it is possible to obtain quantitative optical aerosol properties (particle backscatter coefficient) and discriminate the quality of these retrievals with ceilometers over large areas. This information has a great potential for alert systems and model assimilation and evaluation.

Towards a cross-platform software framework to support end-to-end hydrometeorological sensor network deployment

NASA Astrophysics Data System (ADS)

Celicourt, P.; Sam, R.; Piasecki, M.

2016-12-01

Global phenomena such as climate change and large scale environmental degradation require the collection of accurate environmental data at detailed spatial and temporal scales from which knowledge and actionable insights can be derived using data science methods. Despite significant advances in sensor network technologies, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome and expensive task. These factors demonstrate why environmental data collection remains a challenge especially in developing countries where technical infrastructure, expertise and pecuniary resources are scarce. In addition, they also demonstrate the reason why dense and long-term environmental data collection has been historically quite difficult. Moreover, hydrometeorological data collection efforts usually overlook the (critically important) inclusion of a standards-based system for storing, managing, organizing, indexing, documenting and sharing sensor data. We are developing a cross-platform software framework using the Python programming language that will allow us to develop a low cost end-to-end (from sensor to publication) system for hydrometeorological conditions monitoring. The software framework contains provision for sensor, sensor platforms, calibration and network protocols description, sensor programming, data storage, data publication and visualization and more importantly data retrieval in a desired unit system. It is being tested on the Raspberry Pi microcomputer as end node and a laptop PC as the base station in a wireless setting.

Autonomous telemetry system by using mobile networks for a long-term seismic observation

NASA Astrophysics Data System (ADS)

Hirahara, S.; Uchida, N.; Nakajima, J.

2012-04-01

When a large earthquake occurs, it is important to know the detailed distribution of aftershocks immediately after the main shock for the estimation of the fault plane. The large amount of seismic data is also required to determine the three-dimensional seismic velocity structure around the focal area. We have developed an autonomous telemetry system using mobile networks, which is specialized for aftershock observations. Because the newly developed system enables a quick installation and real-time data transmission by using mobile networks, we can construct a dense online seismic network even in mountain areas where conventional wired networks are not available. This system is equipped with solar panels that charge lead-acid battery, and enables a long-term seismic observation without maintenance. Furthermore, this system enables a continuous observation at low costs with flat-rate or prepaid Internet access. We have tried to expand coverage areas of mobile communication and back up Internet access by configuring plural mobile carriers. A micro server embedded with Linux consists of automatic control programs of the Internet connection and data transmission. A status monitoring and remote maintenance are available via the Internet. In case of a communication failure, an internal storage can back up data for two years. The power consumption of communication device ranges from 2.5 to 4.0 W. With a 50 Ah lead-acid battery, this system continues to record data for four days if the battery charging by solar panels is temporarily unavailable.

Developing a lower-cost atmospheric CO2 monitoring system using commercial NDIR sensor

NASA Astrophysics Data System (ADS)

Arzoumanian, E.; Bastos, A.; Gaynullin, B.; Laurent, O.; Vogel, F. R.

2017-12-01

Cities release to the atmosphere about 44 % of global energy-related CO2. It is clear that accurate estimates of the magnitude of anthropogenic and natural urban emissions are needed to assess their influence on the carbon balance. A dense ground-based CO2 monitoring network in cities would potentially allow retrieving sector specific CO2 emission estimates when combined with an atmospheric inversion framework using reasonably accurate observations (ca. 1 ppm for hourly means). One major barrier for denser observation networks can be the high cost of high precision instruments or high calibration cost of cheaper and unstable instruments. We have developed and tested a novel inexpensive NDIR sensors for CO2 measurements which fulfils cost and typical parameters requirements (i.e. signal stability, efficient handling, and connectivity) necessary for this task. Such sensors are essential in the market of emissions estimates in cities from continuous monitoring networks as well as for leak detection of MRV (monitoring, reporting, and verification) services for industrial sites. We conducted extensive laboratory tests (short and long-term repeatability, cross-sensitivities, etc.) on a series of prototypes and the final versions were also tested in a climatic chamber. On four final HPP prototypes the sensitivity to pressure and temperature were precisely quantified and correction&calibration strategies developed. Furthermore, we fully integrated these HPP sensors in a Raspberry PI platform containing the CO2 sensor and additional sensors (pressure, temperature and humidity sensors), gas supply pump and a fully automated data acquisition unit. This platform was deployed in parallel to Picarro G2401 instruments in the peri-urban site Saclay - next to Paris, and in the urban site Jussieu - Paris, France. These measurements were conducted over several months in order to characterize the long-term drift of our HPP instruments and the ability of the correction and calibration scheme to provide bias free observations. From the lessons learned in the laboratory tests and field measurements, we developed a specific correction and calibration strategy for our NDIR sensors. Latest results and calibration strategies will be shown.

A light and faster regional convolutional neural network for object detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Ding, Peng; Zhang, Ye; Deng, Wei-Jian; Jia, Ping; Kuijper, Arjan

2018-07-01

Detection of objects from satellite optical remote sensing images is very important for many commercial and governmental applications. With the development of deep convolutional neural networks (deep CNNs), the field of object detection has seen tremendous advances. Currently, objects in satellite remote sensing images can be detected using deep CNNs. In general, optical remote sensing images contain many dense and small objects, and the use of the original Faster Regional CNN framework does not yield a suitably high precision. Therefore, after careful analysis we adopt dense convoluted networks, a multi-scale representation and various combinations of improvement schemes to enhance the structure of the base VGG16-Net for improving the precision. We propose an approach to reduce the test-time (detection time) and memory requirements. To validate the effectiveness of our approach, we perform experiments using satellite remote sensing image datasets of aircraft and automobiles. The results show that the improved network structure can detect objects in satellite optical remote sensing images more accurately and efficiently.

Digital services using quadrature amplitude modulation (QAM) over CATV analog DWDM system

NASA Astrophysics Data System (ADS)

Yeh, JengRong; Selker, Mark D.; Trail, J.; Piehler, David; Levi, Israel

2000-04-01

Dense Wavelength Division Multiplexing (DWDM) has recently gained great popularity as it provides a cost effective way to increase the transmission capacity of the existing fiber cable plant. For a long time, Dense WDM was exclusively used for baseband digital applications, predominantly in terrestrial long haul networks and in some cases in metropolitan and enterprise networks. Recently, the performance of DWDM components and frequency-stabilized lasers has substantially improved while the costs have down significantly. This makes a variety of new optical network architectures economically viable. The first commercial 8- wavelength DWDM system designed for Hybrid Fiber Coax networks was reported in 1998. This type of DWDM system utilizes Sub-Carrier Multiplexing (SCM) of Quadrature Amplitude Modulated (QAM) signals to transport IP data digital video broadcast and Video on Demand on ITU grid lightwave carriers. The ability of DWDM to provide scalable transmission capacity in the optical layer with SCM granularity is now considered by many to be the most promising technology for future transport and distribution of broadband multimedia services.

Studies of infrasound propagation using the USArray seismic network (Invited)

NASA Astrophysics Data System (ADS)

Hedlin, M. A.; Degroot-Hedlin, C. D.; Walker, K. T.

2010-12-01

Although there are currently ~ 100 infrasound arrays worldwide, more than ever before, the station density is still insufficient to provide validation for detailed propagation modeling. Much structure in the atmosphere is short-lived and occurs at spatial scales much smaller than the average distance between infrasound stations. Relatively large infrasound signals can be observed on seismic channels due to coupling at the Earth's surface. Recent research, using data from the 70-km spaced 400-station USArray and other seismic network deployments, has shown the value of dense seismic network data for filling in the gaps between infrasound arrays. The dense sampling of the infrasound wavefield has allowed us to observe complete travel-time branches of infrasound signals and shed more light on the nature of infrasound propagation. We present early results from our studies of impulsive atmospheric sources, such as series of UTTR rocket motor detonations in Utah. The Utah blasts have been well recorded by USArray seismic stations and infrasound arrays in Nevada and Washington State. Recordings of seismic signals from a series of six events in 2007 are used to pinpoint the shot times to < 1 second. Variations in the acoustic branches and signal arrival times at the arrays are used to probe variations in atmospheric structure. Although we currently use coupled signals we anticipate studying dense acoustic network recordings as the USArray is currently being upgraded with infrasound microphones. These new sensors will allow us to make semi-continental scale network recordings of infrasound signals free of concerns about how the signals observed on seismic channels were modified when being coupled to seismic.

Interference Mitigation for Cyber-Physical Wireless Body Area Network System Using Social Networks.

PubMed

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

2013-06-01

Wireless body area networks (WBANs) are cyber-physical systems (CPS) that have emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance including depleting the energy of WBAN nodes more quickly, and even eventually jeopardize people's lives due to unreliable (caused by the interference) healthcare data collections. Therefore, It is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs due to their ignoring the social nature of WBANs. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people's social interaction information. Our major contributions include: (1) model the inter-WBANs interference, and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; (2) develop social interaction detection and prediction algorithms for people carrying WBANs; (3) develop a power control game based on the social interaction information to maximize the system's utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks.

Interference Mitigation for Cyber-Physical Wireless Body Area Network System Using Social Networks

PubMed Central

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

2014-01-01

Wireless body area networks (WBANs) are cyber-physical systems (CPS) that have emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance including depleting the energy of WBAN nodes more quickly, and even eventually jeopardize people’s lives due to unreliable (caused by the interference) healthcare data collections. Therefore, It is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs due to their ignoring the social nature of WBANs. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people’s social interaction information. Our major contributions include: (1) model the inter-WBANs interference, and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; (2) develop social interaction detection and prediction algorithms for people carrying WBANs; (3) develop a power control game based on the social interaction information to maximize the system’s utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks. PMID:25436180

What would dense atmospheric observation networks bring to the quantification of city CO2 emissions?

NASA Astrophysics Data System (ADS)

Wu, Lin; Broquet, Grégoire; Ciais, Philippe; Bellassen, Valentin; Vogel, Felix; Chevallier, Frédéric; Xueref-Remy, Irène; Wang, Yilong

2016-06-01

Cities currently covering only a very small portion ( < 3 %) of the world's land surface directly release to the atmosphere about 44 % of global energy-related CO2, but they are associated with 71-76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by the monitoring, reporting, and verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we analyze the potential of a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. This monitoring tool is configured for the quantification of the total and sectoral CO2 emissions in the Paris metropolitan area (˜ 12 million inhabitants and 11.4 TgC emitted in 2010) during the month of January 2011. Its performances are evaluated in terms of uncertainty reduction based on observing system simulation experiments (OSSEs). They are analyzed as a function of the number of sampling sites (measuring at 25 m a.g.l.) and as a function of the network design. The instruments presently used to measure CO2 concentrations at research stations are expensive (typically ˜ EUR 50 k per sensor), which has limited the few current pilot city networks to around 10 sites. Larger theoretical networks are studied here to assess the potential benefit of hypothetical operational lower-cost sensors. The setup of our inversion system is based on a number of diagnostics and assumptions from previous city-scale inversion experiences with real data. We find that, given our assumptions underlying the configuration of the OSSEs, with 10 stations only the uncertainty for the total city CO2 emission during 1 month is significantly reduced by the inversion by ˜ 42 %. It can be further reduced by extending the network, e.g., from 10 to 70 stations, which is promising for MRV applications in the Paris metropolitan area. With 70 stations, the uncertainties in the inverted emissions are reduced significantly over those obtained using 10 stations: by 32 % for commercial and residential buildings, by 33 % for road transport, by 18 % for the production of energy by power plants, and by 31 % for total emissions. These results indicate that such a high number of stations would be likely required for the monitoring of sectoral emissions in Paris using this observation-model framework. They demonstrate some high potential that atmospheric inversions can contribute to the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments) and the advantage that could be brought by the current developments of lower-cost medium precision (LCMP) sensors.

Core-periphery structure requires something else in the network

NASA Astrophysics Data System (ADS)

Kojaku, Sadamori; Masuda, Naoki

2018-04-01

A network with core-periphery structure consists of core nodes that are densely interconnected. In contrast to a community structure, which is a different meso-scale structure of networks, core nodes can be connected to peripheral nodes and peripheral nodes are not densely interconnected. Although core-periphery structure sounds reasonable, we argue that it is merely accounted for by heterogeneous degree distributions, if one partitions a network into a single core block and a single periphery block, which the famous Borgatti–Everett algorithm and many succeeding algorithms assume. In other words, there is a strong tendency that high-degree and low-degree nodes are judged to be core and peripheral nodes, respectively. To discuss core-periphery structure beyond the expectation of the node’s degree (as described by the configuration model), we propose that one needs to assume at least one block of nodes apart from the focal core-periphery structure, such as a different core-periphery pair, community or nodes not belonging to any meso-scale structure. We propose a scalable algorithm to detect pairs of core and periphery in networks, controlling for the effect of the node’s degree. We illustrate our algorithm using various empirical networks.

Nicergoline inhibits human platelet Ca2+ signalling through triggering a microtubule‐dependent reorganization of the platelet ultrastructure

PubMed Central

Walford, T; Musa, F I

2015-01-01

Background and Purpose Recently, we demonstrated that a pericellular Ca2+ recycling system potentiates agonist‐evoked Ca2+ signalling and granule secretion in human platelets and hypothesized a role for the membrane complex (MC) in orchestrating the accumulation of Ca2+ in the pericellular region. Previous work has demonstrated that treatment with high concentrations of nicergoline may disrupt the MC through an ability to trigger a re‐organization of the dense tubular system. Experiments were therefore performed to assess whether nicergoline‐induced changes in platelet ultrastructure affects thrombin‐evoked Ca2+ fluxes and dense granule secretion. Experimental Approach Thrombin‐evoked Ca2+ fluxes were monitored in Fura‐2‐ or Fluo‐5N‐loaded human platelets, or using platelet suspensions containing Fluo‐4 or Rhod‐5N K+ salts. Fluorescence microscopy was utilized to monitor microtubule structure and intracellular Ca2+ store distribution in TubulinTracker‐ and Fluo‐5N‐loaded platelets respectively. Dense granule secretion was monitored using luciferin–luciferase. Key Results Nicergoline treatment inhibited thrombin‐evoked Ca2+ signalling and induced alterations in the microtubule structure and the distribution of intracellular Ca2+ stores in platelets. Nicergoline altered the generation and spreading of thrombin‐induced pericellular Ca2+ signals and almost completely prevented dense granule secretion. Stabilization of microtubules using taxol reversed most effects of nicergoline on platelet Ca2+ signalling and partially reversed its effects on dense granule secretion. Conclusions and Implications Nicergoline‐induced alterations to platelet ultrastructure disrupt platelet Ca2+ signalling in a manner that would be predicted if the MC had been disrupted. These data suggest that nicergoline may be a useful prototype for the discovery of novel MC‐disrupting anti‐thrombotics. PMID:26450366

Nicergoline inhibits human platelet Ca(2+) signalling through triggering a microtubule-dependent reorganization of the platelet ultrastructure.

PubMed

Walford, T; Musa, F I; Harper, A G S

2016-01-01

Recently, we demonstrated that a pericellular Ca(2+) recycling system potentiates agonist-evoked Ca(2+) signalling and granule secretion in human platelets and hypothesized a role for the membrane complex (MC) in orchestrating the accumulation of Ca(2+) in the pericellular region. Previous work has demonstrated that treatment with high concentrations of nicergoline may disrupt the MC through an ability to trigger a re-organization of the dense tubular system. Experiments were therefore performed to assess whether nicergoline-induced changes in platelet ultrastructure affects thrombin-evoked Ca(2+) fluxes and dense granule secretion. Thrombin-evoked Ca(2+) fluxes were monitored in Fura-2- or Fluo-5N-loaded human platelets, or using platelet suspensions containing Fluo-4 or Rhod-5N K(+) salts. Fluorescence microscopy was utilized to monitor microtubule structure and intracellular Ca(2+) store distribution in TubulinTracker- and Fluo-5N-loaded platelets respectively. Dense granule secretion was monitored using luciferin-luciferase. Nicergoline treatment inhibited thrombin-evoked Ca(2+) signalling and induced alterations in the microtubule structure and the distribution of intracellular Ca(2+) stores in platelets. Nicergoline altered the generation and spreading of thrombin-induced pericellular Ca(2+) signals and almost completely prevented dense granule secretion. Stabilization of microtubules using taxol reversed most effects of nicergoline on platelet Ca(2+) signalling and partially reversed its effects on dense granule secretion. Nicergoline-induced alterations to platelet ultrastructure disrupt platelet Ca(2+) signalling in a manner that would be predicted if the MC had been disrupted. These data suggest that nicergoline may be a useful prototype for the discovery of novel MC-disrupting anti-thrombotics. © 2015 The British Pharmacological Society.

Global Seismic Monitoring: Past, Present, and Future

NASA Astrophysics Data System (ADS)

Zoback, M.; Benz, H.; Oppenheimer, D.

2007-12-01

Global seismological observations began in April 1889 when an earthquake in Tokyo, Japan was accurately recorded in Germany on two different horizontal pendulum instruments. However, modern global observational seismology really began 46 years ago when the 120-station World Wide Standard Seismograph Network was installed by the US to monitor underground nuclear tests and earthquakes using well-calibrated short- and long- period stations. At the same time rapid advances in computing technology enabled researchers to begin sophisticated analysis of the increasing amount of seismic data, which led to better understanding of earthquake source properties and their use in establishing plate tectonics. Today, global seismic networks are operated by German (Geophon), France (Geoscope), the United States (Global Seismograph Network) and the International Monitoring System. Presently, the Federation of Digital Seismograph Networks registers more than 1,000 broadband stations world-wide, a small percentage of the total number of digital seismic stations around the world. Following the devastating Kobe, Japan and Northridge, California earthquakes, Japan and the US have led the world in the integration of existing seismic sensor systems (weak and strong motion) into development of near-real-time, post-earthquake response products like ShakeMap, detailing the spatial distribution of strong shaking. Future challenges include expanding real-time integration of both seismic and geodetic sensor systems to produce early warning of strong shaking, rapid source determination, as well as near-realtime post- earthquake damage assessment. Seismic network data, hydro-acoustic arrays, deep water tide gauges, and satellite imagery of wave propagation should be integrated in real-time to provide input for hydrodynamic modeling yielding the distribution, timing and size of tsunamis runup--which would then be available instantly on the web, e.g. in a Google Earth format. Dense arrays of strong motion sensors together with deployment of MEMS-type accelerometers in buildings and equipment routinely connected to the Web could potentially provide thousands of measurements of damaging strong ground motion. This technology could ultimately become part of smart building design enabling critical facilities to change their structural response to imminent strong shaking. Looking further forward, it is likely that a continuously observing spaceborne system could image the occurrence of "silent" or "slow" earthquakes as well as the propagation of ground displacement by surface waves at scales of continents.

Landslide monitoring using Geocubes, a wireless network of low-cost GPS receivers

NASA Astrophysics Data System (ADS)

Benoit, Lionel; Thom, Christian; Martin, Olivier

2013-04-01

Many geophysical structures such as landslides, glaciers or even volcanoes are features characterized by small extend area and deformation rate in the order of 1 to 10cm per day. Their study needs ever more accurate positioning data with an increased space and time resolution. Using an ublox LEA-6T GPS receiver, the French national mapping agency IGN developed its own wireless multi-sensor geo-monitoring system named Geocube. The basic device is equipped with a GPS and a wireless communication media and can be completed with various sensor modules such as meteorological sensors, ground humidity and pressure or seismograph. Due to the low cost of each receiver, spatial dense surveying networks are deployed. Data are then continuously collected and transmitted to a processing computer in real-time as well as saved in situ on a Micro-SD card. Among them, raw GPS carrier phase data give access to real-time accurate relative positioning on all mesh nodes if small baselines are used. In order to achieve a high accuracy, a dedicated GPS data processing method based on a Kalman filter is proposed. It allows an epoch by epoch positioning providing a high time resolution. Special attention is paid on two points : adaptation to wireless networks of low-cost GPS and real-time ability. A first test of Geocubes usability under field conditions was carried out during summer 2012. A fifteen receivers network was deployed on the landslide of Super-Sauze (French Alps) for a two months trial. The experimental area, the deployed network and the acquisition protocol are presented. Position time series with a 30 seconds sampling rate are then derived from raw data for 10 mobile receivers on a forty days session. A sub-centimetric accuracy on an epoch by epoch positioning is reached despite difficult field conditions due to a 40° elevation mask in the south direction. Then, the measured deformations are compared with in situ rainfall measurements collected by a dedicated sensor added to a Geocube on a network's node.

Landslide monitoring using Geocubes, a wireless network of low-cost GPS receivers.

NASA Astrophysics Data System (ADS)

Benoit, Lionel; Thom, Christian; Martin, Olivier

2013-04-01

Many geophysical structures such as landslides, glaciers or even volcanoes are features characterized by small extend area and deformation rate in the order of 1 to 10cm per day. Their study needs ever more accurate positioning data with an increased space and time resolution. Using an Ublox LEA-6T GPS receiver, the French national mapping agency IGN developed its own wireless multi-sensor geo-monitoring system named Geocube. The basic device is equipped with a GPS and a wireless communication media and can be completed with various sensor modules such as meteorological sensors, ground humidity and pressure or seismograph. Due to the low cost of each receiver, spatial dense surveying networks are deployed. Data are then continuously collected and transmitted to a processing computer in real-time as well as saved in situ on a Micro-SD card. Among them, raw GPS carrier phase data give access to real-time accurate relative positioning on all mesh nodes if small baselines are used. In order to achieve a high accuracy, a dedicated GPS data processing method based on a Kalman filter is proposed. It allows an epoch by epoch positioning providing a high time resolution. Special attention is paid on two points : adaptation to wireless networks of low-cost GPS and real-time ability. A first test of Geocubes usability under field conditions was carried out during summer 2012. A fifteen receivers network was deployed on the landslide of Super-Sauze (French Alps) for a two months trial. The experimental area, the deployed network and the acquisition protocol are presented. Position time series with a 30 seconds sampling rate are then derived from raw data for 10 mobile receivers on a forty days session. A sub-centimetric accuracy on an epoch by epoch positioning is reached despite difficult field conditions due to a 40° elevation mask in the south direction. Then, the measured deformations are compared with in situ rainfall measurements collected by a dedicated sensor added to a Geocube on a network's node.

Clustering-based energy-saving algorithm in ultra-dense network

NASA Astrophysics Data System (ADS)

Huang, Junwei; Zhou, Pengguang; Teng, Deyang; Zhang, Renchi; Xu, Hao

2017-06-01

In Ultra-dense Networks (UDN), dense deployment of low power small base stations will cause serious small cells interference and a large amount of energy consumption. The purpose of this paper is to explore the method of reducing small cells interference and energy saving system in UDN, and we innovatively propose a sleep-waking-active (SWA) scheme. The scheme decreases the user outage causing by failure to detect users’ service requests, shortens the opening time of active base stations directly switching to sleep mode; we further proposes a Vertex Surrounding Clustering(VSC) algorithm, which first colours the small cells with the most strongest interference and next extends to the adjacent small cells. VSC algorithm can use the least colour to stain the small cell, reduce the number of iterations and promote the efficiency of colouring. The simulation results show that SWA scheme can effectively improve the system Energy Efficiency (EE), the VSC algorithm can reduce the small cells interference and optimize the users’ Spectrum Efficiency (SE) and throughput.

Detection of mass regions in mammograms by bilateral analysis adapted to breast density using similarity indexes and convolutional neural networks.

PubMed

Bandeira Diniz, João Otávio; Bandeira Diniz, Pedro Henrique; Azevedo Valente, Thales Levi; Corrêa Silva, Aristófanes; de Paiva, Anselmo Cardoso; Gattass, Marcelo

2018-03-01

The processing of medical image is an important tool to assist in minimizing the degree of uncertainty of the specialist, while providing specialists with an additional source of detect and diagnosis information. Breast cancer is the most common type of cancer that affects the female population around the world. It is also the most deadly type of cancer among women. It is the second most common type of cancer among all others. The most common examination to diagnose breast cancer early is mammography. In the last decades, computational techniques have been developed with the purpose of automatically detecting structures that maybe associated with tumors in mammography examination. This work presents a computational methodology to automatically detection of mass regions in mammography by using a convolutional neural network. The materials used in this work is the DDSM database. The method proposed consists of two phases: training phase and test phase. The training phase has 2 main steps: (1) create a model to classify breast tissue into dense and non-dense (2) create a model to classify regions of breast into mass and non-mass. The test phase has 7 step: (1) preprocessing; (2) registration; (3) segmentation; (4) first reduction of false positives; (5) preprocessing of regions segmented; (6) density tissue classification (7) second reduction of false positives where regions will be classified into mass and non-mass. The proposed method achieved 95.6% of accuracy in classify non-dense breasts tissue and 97,72% accuracy in classify dense breasts. To detect regions of mass in non-dense breast, the method achieved a sensitivity value of 91.5%, and specificity value of 90.7%, with 91% accuracy. To detect regions in dense breasts, our method achieved 90.4% of sensitivity and 96.4% of specificity, with accuracy of 94.8%. According to the results achieved by CNN, we demonstrate the feasibility of using convolutional neural networks on medical image processing techniques for classification of breast tissue and mass detection. Copyright © 2018 Elsevier B.V. All rights reserved.

A bandwidth-efficient service for local information dissemination in sparse to dense roadways.

PubMed

Garcia-Lozano, Estrella; Campo, Celeste; Garcia-Rubio, Carlos; Cortes-Martin, Alberto; Rodriguez-Carrion, Alicia; Noriega-Vivas, Patricia

2013-07-05

Thanks to the research on Vehicular Ad Hoc Networks (VANETs), we will be able to deploy applications on roadways that will contribute to energy efficiency through a better planning of long trips. With this goal in mind, we have designed a gas/charging station advertising system, which takes advantage of the broadcast nature of the network. We have found that reducing the number of total sent packets is important, as it allows for a better use of the available bandwidth. We have designed improvements for a distance-based flooding scheme, so that it can support the advertising application with good results in sparse to dense roadway scenarios.

A Bandwidth-Efficient Service for Local Information Dissemination in Sparse to Dense Roadways

PubMed Central

Garcia-Lozano, Estrella; Campo, Celeste; Garcia-Rubio, Carlos; Cortes-Martin, Alberto; Rodriguez-Carrion, Alicia; Noriega-Vivas, Patricia

2013-01-01

Thanks to the research on Vehicular Ad Hoc Networks (VANETs), we will be able to deploy applications on roadways that will contribute to energy efficiency through a better planning of long trips. With this goal in mind, we have designed a gas/charging station advertising system, which takes advantage of the broadcast nature of the network. We have found that reducing the number of total sent packets is important, as it allows for a better use of the available bandwidth. We have designed improvements for a distance-based flooding scheme, so that it can support the advertising application with good results in sparse to dense roadway scenarios. PMID:23881130

The preparatory phase of the April 6th 2009, Mw 6.3, L’Aquila earthquake: Seismological observations

NASA Astrophysics Data System (ADS)

Lucente, F. P.; de Gori, P.; Margheriti, L.; Piccinini, D.; Dibona, M.; Chiarabba, C.; Piana Agostinetti, N.

2009-12-01

Few decades ago, the dilatancy-diffusion hypothesis held great promise as a physical basis for developing earthquakes prediction techniques, but the potential never become reality, as the result of too few observations consistent with the theory. One of the main problems has been the lack of detailed monitoring records of small earthquakes swarms spatio-temporally close to the incoming major earthquakes. In fact, the recognition of dilatancy-related effects requires the use of very dense network of three-component seismographs, which, in turn, implies the a-priori knowledge of major earthquakes location, i.e., actually a paradox. The deterministic prediction of earthquakes remains a long time, hard task to accomplish. Nevertheless, for seismologists, the understanding of the processes that preside over the earthquakes nucleation and the mechanics of faulting represents a big step toward the ability to predict earthquakes. Here we describe a set of seismological observations done on the foreshock sequence that preceded the April 6th 2009, Mw 6.3, L’Aquila earthquake. In this occasion, the dense configuration of the seismic network in the area gave us the unique opportunity for a detailed reconstruction of the preparatory phase of the main shock. We show that measurable precursory effects, as changes of the seismic waves velocity and of the anisotropic parameters in the crust, occurred before the main shock. From our observations we infer that fluids play a key role in the fault failure process, and, most significantly, that the elastic properties of the rock volume surrounding the main shock nucleation area undergo a dramatic change about a week before the main shock occurrence.

Interactions among human behavior, social networks, and societal infrastructures: A Case Study in Computational Epidemiology

NASA Astrophysics Data System (ADS)

Barrett, Christopher L.; Bisset, Keith; Chen, Jiangzhuo; Eubank, Stephen; Lewis, Bryan; Kumar, V. S. Anil; Marathe, Madhav V.; Mortveit, Henning S.

Human behavior, social networks, and the civil infrastructures are closely intertwined. Understanding their co-evolution is critical for designing public policies and decision support for disaster planning. For example, human behaviors and day to day activities of individuals create dense social interactions that are characteristic of modern urban societies. These dense social networks provide a perfect fabric for fast, uncontrolled disease propagation. Conversely, people’s behavior in response to public policies and their perception of how the crisis is unfolding as a result of disease outbreak can dramatically alter the normally stable social interactions. Effective planning and response strategies must take these complicated interactions into account. In this chapter, we describe a computer simulation based approach to study these issues using public health and computational epidemiology as an illustrative example. We also formulate game-theoretic and stochastic optimization problems that capture many of the problems that we study empirically.

A spatiotemporal analysis of hydrological patterns based on a wireless sensor network system

NASA Astrophysics Data System (ADS)

Plaza, F.; Slater, T. A.; Zhong, X.; Li, Y.; Liang, Y.; Liang, X.

2017-12-01

Understanding complicated spatiotemporal patterns of eco-hydrological variables at a small scale plays a profound role in improving predictability of high resolution distributed hydrological models. However, accurate and continuous monitoring of these complex patterns has become one of the main challenges in the environmental sciences. Wireless sensor networks (WSNs) have emerged as one of the most widespread potential solutions to achieve this. This study presents a spatiotemporal analysis of hydrological patterns (e.g., soil moisture, soil water potential, soil temperature and transpiration) based on observational data collected from a dense multi-hop wireless sensor network (WSN) in a steep-forested testbed located in Southwestern Pennsylvania, USA. At this WSN testbed with an approximate area of 3000 m2, environmental variables are collected from over 240 sensors that are connected to more than 100 heterogeneous motes. The sensors include the soil moisture of EC-5, soil temperature and soil water potential of MPS-1 and MPS-2, and sap flow sensors constructed in house. The motes consist of MICAz, IRIS and TelosB. In addition, several data loggers have been installed along the site to provide a comparative reference to the WSN measurements for the purpose of checking the WSN data quality. The edaphic properties monitored by the WSN sensors show strong agreement with the data logger measurements. Moreover, sap flow measurements, scaled to tree stand transpiration, are found to be reasonable. This study also investigates the feasibility and roles that these sensor measurements play in improving the performance of high-resolution distributed hydrological models. In particular, we explore this using a modified version of the Distributed Hydrological Soil Vegetation Model (DHSVM).

Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things.

PubMed

Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

2015-09-18

With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified.

Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things

PubMed Central

Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

2015-01-01

With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified. PMID:26393617

Life of Lambda

ERIC Educational Resources Information Center

Futhey, Tracy

2005-01-01

In this column, the author discusses the four key questions related to the National LambdaRail (NLR) networking technology. NLR uses Dense Wave Division Multiplexing (DWDM) to enable multiple networks to coexist on a national fiber footprint, and is owned and operated not by carriers, but by the research and education community. The NLR Board…

GRA12, a Toxoplasma dense granule protein associated with the intravacuolar membranous nanotubular network.

PubMed

Michelin, Adeline; Bittame, Amina; Bordat, Yann; Travier, Laetitia; Mercier, Corinne; Dubremetz, Jean-François; Lebrun, Maryse

2009-02-01

The intracellular protozoan parasite Toxoplasma gondii develops within the parasitophorous vacuole (PV), an intracellular niche in which it secretes proteins from secretory organelles named dense granules and rhoptries. Here, we describe a new dense granule protein that should now be referred to as GRA12, and that displays no homology with other proteins. Immunofluorescence and immuno-electron microscopy showed that GRA12 behaves similarly to both GRA2 and GRA6. It is secreted into the PV from the anterior pole of the parasite soon after the beginning of invasion, transits to the posterior invaginated pocket of the parasite where a membranous tubulovesicular network is first assembled, and finally resides throughout the vacuolar space, associated with the mature membranous nanotubular network. GRA12 fails to localise at the parasite posterior end in the absence of GRA2. Within the vacuolar space, like the other GRA proteins, GRA12 exists in both a soluble and a membrane-associated form. Using affinity chromatography experiments, we showed that in both the parasite and the PV soluble fractions, GRA12 is purified with the complex of GRA proteins associated with a tagged version of GRA2 and that this association is lost in the PV membranous fraction.

Modeling propagation of infrasound signals observed by a dense seismic network.

PubMed

Chunchuzov, I; Kulichkov, S; Popov, O; Hedlin, M

2014-01-01

The long-range propagation of infrasound from a surface explosion with an explosive yield of about 17.6 t TNT that occurred on June 16, 2008 at the Utah Test and Training Range (UTTR) in the western United States is simulated using an atmospheric model that includes fine-scale layered structure of the wind velocity and temperature fields. Synthetic signal parameters (waveforms, amplitudes, and travel times) are calculated using parabolic equation and ray-tracing methods for a number of ranges between 100 and 800 km from the source. The simulation shows the evolution of several branches of stratospheric and thermospheric signals with increasing range from the source. Infrasound signals calculated using a G2S (ground-to-space) atmospheric model perturbed by small-scale layered wind velocity and temperature fluctuations are shown to agree well with recordings made by the dense High Lava Plains seismic network located at an azimuth of 300° from UTTR. The waveforms of calculated infrasound arrivals are compared with those of seismic recordings. This study illustrates the utility of dense seismic networks for mapping an infrasound field with high spatial resolution. The parabolic equation calculations capture both the effect of scattering of infrasound into geometric acoustic shadow zones and significant temporal broadening of the arrivals.

Experimental wind tunnel study of a smart sensing skin for condition evaluation of a wind turbine blade

NASA Astrophysics Data System (ADS)

Downey, Austin; Laflamme, Simon; Ubertini, Filippo

2017-12-01

Condition evaluation of wind turbine blades is difficult due to their large size, complex geometry and lack of economic and scalable sensing technologies capable of detecting, localizing, and quantifying faults over a blade’s global area. A solution is to deploy inexpensive large area electronics over strategic areas of the monitored component, analogous to sensing skin. The authors have previously proposed a large area electronic consisting of a soft elastomeric capacitor (SEC). The SEC is highly scalable due to its low cost and ease of fabrication, and can, therefore, be used for monitoring large-scale components. A single SEC is a strain sensor that measures the additive strain over a surface. Recently, its application in a hybrid dense sensor network (HDSN) configuration has been studied, where a network of SECs is augmented with a few off-the-shelf strain gauges to measure boundary conditions and decompose the additive strain to obtain unidirectional surface strain maps. These maps can be analyzed to detect, localize, and quantify faults. In this work, we study the performance of the proposed sensing skin at conducting condition evaluation of a wind turbine blade model in an operational environment. Damage in the form of changing boundary conditions and cuts in the monitored substrate are induced into the blade. An HDSN is deployed onto the interior surface of the substrate, and the blade excited in a wind tunnel. Results demonstrate the capability of the HDSN and associated algorithms to detect, localize, and quantify damage. These results show promise for the future deployment of fully integrated sensing skins deployed inside wind turbine blades for condition evaluation.

CAOS: the nested catchment soil-vegetation-atmosphere observation platform

NASA Astrophysics Data System (ADS)

Weiler, Markus; Blume, Theresa

2016-04-01

Most catchment based observations linking hydrometeorology, ecohydrology, soil hydrology and hydrogeology are typically not integrated with each other and lack a consistent and appropriate spatial-temporal resolution. Within the research network CAOS (Catchments As Organized Systems), we have initiated and developed a novel and integrated observation platform in several catchments in Luxembourg. In 20 nested catchments covering three distinct geologies the subscale processes at the bedrock-soil-vegetation-atmosphere interface are being monitored at 46 sensor cluster locations. Each sensor cluster is designed to observe a variety of different fluxes and state variables above and below ground, in the saturated and unsaturated zone. The numbers of sensors are chosen to capture the spatial variability as well the average dynamics. At each of these sensor clusters three soil moisture profiles with sensors at different depths, four soil temperature profiles as well as matric potential, air temperature, relative humidity, global radiation, rainfall/throughfall, sapflow and shallow groundwater and stream water levels are measured continuously. In addition, most sensors also measure temperature (water, soil, atmosphere) and electrical conductivity. This setup allows us to determine the local water and energy balance at each of these sites. The discharge gauging sites in the nested catchments are also equipped with automatic water samplers to monitor water quality and water stable isotopes continuously. Furthermore, water temperature and electrical conductivity observations are extended to over 120 locations distributed across the entire stream network to capture the energy exchange between the groundwater, stream water and atmosphere. The measurements at the sensor clusters are complemented by hydrometeorological observations (rain radar, network of distrometers and dense network of precipitation gauges) and linked with high resolution meteorological models. In this presentation, we will highlight the potential of this integrated observation platform to estimate energy and water exchange between the terrestrial and aquatic systems and the atmosphere, to trace water flow pathways in the unsaturated and saturated zone, and to understand the organization of processes and fluxes and thus runoff generation at different temporal and spatial scales.

Markov Networks of Collateral Resistance: National Antimicrobial Resistance Monitoring System Surveillance Results from Escherichia coli Isolates, 2004-2012

PubMed Central

Love, William J.; Zawack, Kelson A.; Booth, James G.; Grӧhn, Yrjo T.

2016-01-01

Surveillance of antimicrobial resistance (AMR) is an important component of public health. Antimicrobial drug use generates selective pressure that may lead to resistance against to the administered drug, and may also select for collateral resistances to other drugs. Analysis of AMR surveillance data has focused on resistance to individual drugs but joint distributions of resistance in bacterial populations are infrequently analyzed and reported. New methods are needed to characterize and communicate joint resistance distributions. Markov networks are a class of graphical models that define connections, or edges, between pairs of variables with non-zero partial correlations and are used here to describe AMR resistance relationships. The graphical least absolute shrinkage and selection operator is used to estimate sparse Markov networks from AMR surveillance data. The method is demonstrated using a subset of Escherichia coli isolates collected by the National Antimicrobial Resistance Monitoring System between 2004 and 2012 which included AMR results for 16 drugs from 14418 isolates. Of the 119 possible unique edges, 33 unique edges were identified at least once during the study period and graphical density ranged from 16.2% to 24.8%. Two frequent dense subgraphs were noted, one containing the five β-lactam drugs and the other containing both sulfonamides, three aminoglycosides, and tetracycline. Density did not appear to change over time (p = 0.71). Unweighted modularity did not appear to change over time (p = 0.18), but a significant decreasing trend was noted in the modularity of the weighted networks (p < 0.005) indicating relationships between drugs of different classes tended to increase in strength and frequency over time compared to relationships between drugs of the same class. The current method provides a novel method to study the joint resistance distribution, but additional work is required to unite the underlying biological and genetic characteristics of the isolates with the current results derived from phenotypic data. PMID:27851767

Markov Networks of Collateral Resistance: National Antimicrobial Resistance Monitoring System Surveillance Results from Escherichia coli Isolates, 2004-2012.

PubMed

Love, William J; Zawack, Kelson A; Booth, James G; Grӧhn, Yrjo T; Lanzas, Cristina

2016-11-01

Surveillance of antimicrobial resistance (AMR) is an important component of public health. Antimicrobial drug use generates selective pressure that may lead to resistance against to the administered drug, and may also select for collateral resistances to other drugs. Analysis of AMR surveillance data has focused on resistance to individual drugs but joint distributions of resistance in bacterial populations are infrequently analyzed and reported. New methods are needed to characterize and communicate joint resistance distributions. Markov networks are a class of graphical models that define connections, or edges, between pairs of variables with non-zero partial correlations and are used here to describe AMR resistance relationships. The graphical least absolute shrinkage and selection operator is used to estimate sparse Markov networks from AMR surveillance data. The method is demonstrated using a subset of Escherichia coli isolates collected by the National Antimicrobial Resistance Monitoring System between 2004 and 2012 which included AMR results for 16 drugs from 14418 isolates. Of the 119 possible unique edges, 33 unique edges were identified at least once during the study period and graphical density ranged from 16.2% to 24.8%. Two frequent dense subgraphs were noted, one containing the five β-lactam drugs and the other containing both sulfonamides, three aminoglycosides, and tetracycline. Density did not appear to change over time (p = 0.71). Unweighted modularity did not appear to change over time (p = 0.18), but a significant decreasing trend was noted in the modularity of the weighted networks (p < 0.005) indicating relationships between drugs of different classes tended to increase in strength and frequency over time compared to relationships between drugs of the same class. The current method provides a novel method to study the joint resistance distribution, but additional work is required to unite the underlying biological and genetic characteristics of the isolates with the current results derived from phenotypic data.

Near Fault Observatories: multidisciplinary research infrastructures, high resolution data and scientific products available through dedicated services implemented within the EPOS-IP project

NASA Astrophysics Data System (ADS)

Festa, Gaetano; Chiaraluce, Lauro; Ergintav, Semih; Bernard, Pascal; Clinton, John; Marmureanu, Alexandru; Tataru, Dragos; Vogfjord, Kristin

2017-04-01

Near Fault Observatories (NFOs) are innovative research infrastructures based on dense, state of the art networks of multi-parametric sensors that continuously monitor the underlying Earth instability processes over a broad time interval. They aim at understanding the physical/chemical processes responsible for earthquakes and faulting and tracking their evolution over time by enabling advancements in ground shaking prediction. EPOS-IP is aimed at contributing in creating and harmonizing data and products distributors from seven NFOs, operating on different tectonic regimes and different areas of Europe. They include plate boundary systems at South Iceland Seismic Zone, the Marmara Sea and the Corinth rift. In mountain settings, NFOs monitor the Alto Tiberina and Irpinia faults in the Apennine mountain range, the Valais region in the Alps, and the Vrancea fault in the Carpathian Mountains. They monitor diverse faulting mechanisms (strike-slip, normal and thrust), high to low angle faults, shallow and deep faults, as well as regions with fast and slow strain rate accumulation. The focus of the observatories varies, ranging from small- to large-scale seismicity and includes the role of different parameters such as fluid playing in fault initiation, the internal structure of fault systems, site effects and derived processes such as earthquake generated landslides and tsunamis. In response to their specific objectives, the NFOs operate a diverse set of monitoring instrumentation using seismic, deformation, strain, geochemical and electromagnetic equipment. Since NFO methodological approach is based on extremely dense networks and less common instruments deserving multi-parameter data description, a main goal of this group is to build inclusive and harmonised services supporting the installation over the next decade of tens of near-fault observatories monitoring active faults in different tectonic environments in Europe. The NFO Thematic Core Service (TCS) relies on external platforms and services for accessing to standard data (e.g. seismic and geodetic) and on the direct access to the e-infrastructures of individual NFOs for distribution of non standard data (e.g. strain- and tilt-meters, geochemical data, electro- magneto-telluric data) and high-level data products. To define standards for formats and metadata, the TCS actively participates into the several harmonization groups across EPOS. Two main specific services are under implementation at the TCS level. FRIDGE (EU - NFO Specific Data and Products Gateway and Virtual Laboratory) is a NFO common gateway that enables the specific data and high-level data products availability also furnishing simple visualization tools. CREW (EU - Testing Centre for Early Warning and Source characterization) is a testing facility built on real-time and offline high-resolution data, whose focus is on operating and benchmarking various existing Earthquake Early Warning (EEW) methodologies. The backbone of the testing centre is the Irpinia NFO.

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

PubMed

Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

A global satellite assisted precipitation climatology

USGS Publications Warehouse

Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

2015-01-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0,http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

A global satellite-assisted precipitation climatology

NASA Astrophysics Data System (ADS)

Funk, C.; Verdin, A.; Michaelsen, J.; Peterson, P.; Pedreros, D.; Husak, G.

2015-10-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high-resolution (0.05°) global precipitation climatologies that perform reasonably well in data-sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, doi:10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

L(p) approximation capabilities of sum-of-product and sigma-pi-sigma neural networks.

PubMed

Long, Jinling; Wu, Wei; Nan, Dong

2007-10-01

This paper studies the L(p) approximation capabilities of sum-of-product (SOPNN) and sigma-pi-sigma (SPSNN) neural networks. It is proved that the set of functions that are generated by the SOPNN with its activation function in $L_{loc};p(\\mathcal{R})$ is dense in $L;p(\\mathcal{K})$ for any compact set $\\mathcal{K}\\subset \\mathcal{R};N$, if and only if the activation function is not a polynomial almost everywhere. It is also shown that if the activation function of the SPSNN is in ${L_{loc};\\infty(\\mathcal{R})}$, then the functions generated by the SPSNN are dense in $L;p(\\mathcal{K})$ if and only if the activation function is not a constant (a.e.).

Connectome sensitivity or specificity: which is more important?

PubMed

Zalesky, Andrew; Fornito, Alex; Cocchi, Luca; Gollo, Leonardo L; van den Heuvel, Martijn P; Breakspear, Michael

2016-11-15

Connectomes with high sensitivity and high specificity are unattainable with current axonal fiber reconstruction methods, particularly at the macro-scale afforded by magnetic resonance imaging. Tensor-guided deterministic tractography yields sparse connectomes that are incomplete and contain false negatives (FNs), whereas probabilistic methods steered by crossing-fiber models yield dense connectomes, often with low specificity due to false positives (FPs). Densely reconstructed probabilistic connectomes are typically thresholded to improve specificity at the cost of a reduction in sensitivity. What is the optimal tradeoff between connectome sensitivity and specificity? We show empirically and theoretically that specificity is paramount. Our evaluations of the impact of FPs and FNs on empirical connectomes indicate that specificity is at least twice as important as sensitivity when estimating key properties of brain networks, including topological measures of network clustering, network efficiency and network modularity. Our asymptotic analysis of small-world networks with idealized modular structure reveals that as the number of nodes grows, specificity becomes exactly twice as important as sensitivity to the estimation of the clustering coefficient. For the estimation of network efficiency, the relative importance of specificity grows linearly with the number of nodes. The greater importance of specificity is due to FPs occurring more prevalently between network modules rather than within them. These spurious inter-modular connections have a dramatic impact on network topology. We argue that efforts to maximize the sensitivity of connectome reconstruction should be realigned with the need to map brain networks with high specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

Sexual networks, surveillance, and geographical space during syphilis outbreaks in rural North Carolina.

PubMed

Doherty, Irene A; Serre, Marc L; Gesink, Dionne; Adimora, Adaora A; Muth, Stephen Q; Leone, Peter A; Miller, William C

2012-11-01

Sexually transmitted infections (STIs) spread along sexual networks whose structural characteristics promote transmission that routine surveillance may not capture. Cases who have partners from multiple localities may operate as spatial network bridges, thereby facilitating geographical dissemination. We investigated how surveillance, sexual networks, and spatial bridges relate to each other for syphilis outbreaks in rural counties of North Carolina. We selected from the state health department's surveillance database cases diagnosed with primary, secondary, or early latent syphilis during October 1998 to December 2002 and who resided in central and southeastern North Carolina, along with their sex partners and their social contacts irrespective of infection status. We applied matching algorithms to eliminate duplicate names and create a unique roster of partnerships from which networks were compiled and graphed. Network members were differentiated by disease status and county of residence. In the county most affected by the outbreak, densely connected networks indicative of STI outbreaks were consistent with increased incidence and a large case load. In other counties, the case loads were low with fluctuating incidence, but network structures suggested the presence of outbreaks. In a county with stable, low incidence and a high number of cases, the networks were sparse and dendritic, indicative of endemic spread. Outbreak counties exhibited densely connected networks within well-defined geographic boundaries and low connectivity between counties; spatial bridges did not seem to facilitate transmission. Simple visualization of sexual networks can provide key information to identify communities most in need of resources for outbreak investigation and disease control.

VISIONET: intuitive visualisation of overlapping transcription factor networks, with applications in cardiogenic gene discovery.

PubMed

Nim, Hieu T; Furtado, Milena B; Costa, Mauro W; Rosenthal, Nadia A; Kitano, Hiroaki; Boyd, Sarah E

2015-05-01

Existing de novo software platforms have largely overlooked a valuable resource, the expertise of the intended biologist users. Typical data representations such as long gene lists, or highly dense and overlapping transcription factor networks often hinder biologists from relating these results to their expertise. VISIONET, a streamlined visualisation tool built from experimental needs, enables biologists to transform large and dense overlapping transcription factor networks into sparse human-readable graphs via numerically filtering. The VISIONET interface allows users without a computing background to interactively explore and filter their data, and empowers them to apply their specialist knowledge on far more complex and substantial data sets than is currently possible. Applying VISIONET to the Tbx20-Gata4 transcription factor network led to the discovery and validation of Aldh1a2, an essential developmental gene associated with various important cardiac disorders, as a healthy adult cardiac fibroblast gene co-regulated by cardiogenic transcription factors Gata4 and Tbx20. We demonstrate with experimental validations the utility of VISIONET for expertise-driven gene discovery that opens new experimental directions that would not otherwise have been identified.

U.S. Geological Survey continuous monitoring workshop—Workshop summary report

USGS Publications Warehouse

Sullivan, Daniel J.; Joiner, John K.; Caslow, Kerry A.; Landers, Mark N.; Pellerin, Brian A.; Rasmussen, Patrick P.; Sheets, Rodney A.

2018-04-20

Executive SummaryThe collection of high-frequency (in other words, “continuous”) water data has been made easier over the years because of advances in technologies to measure, transmit, store, and query large, temporally dense datasets. Commercially available, in-situ sensors and data-collection platforms—together with new techniques for data analysis—provide an opportunity to monitor water quantity and quality at time scales during which meaningful changes occur. The U.S. Geological Survey (USGS) Continuous Monitoring Workshop was held to build stronger collaboration within the Water Mission Area on the collection, interpretation, and application of continuous monitoring data; share technical approaches for the collection and management of continuous data that improves consistency and efficiency across the USGS; and explore techniques and tools for the interpretation of continuous monitoring data, which increases the value to cooperators and the public. The workshop was organized into three major themes: Collecting Continuous Data, Understanding and Using Continuous Data, and Observing and Delivering Continuous Data in the Future. Presentations each day covered a variety of related topics, with a special session at the end of each day designed to bring discussion and problem solving to the forefront.The workshop brought together more than 70 USGS scientists and managers from across the Water Mission Area and Water Science Centers. Tools to manage, assure, control quality, and explore large streams of continuous water data are being developed by the USGS and other organizations and will be critical to making full use of these high-frequency data for research and monitoring. Disseminating continuous monitoring data and findings relevant to critical cooperator and societal issues is central to advancing the USGS networks and mission. Several important outcomes emerged from the presentations and breakout sessions.

Recent crustal deformation of İzmir, Western Anatolia and surrounding regions as deduced from repeated GPS measurements and strain field

NASA Astrophysics Data System (ADS)

Aktuğ, Bahadır; Kılıçoğlu, Ali

2006-07-01

To investigate contemporary neotectonic deformation in İzmir, Western Anatolia and in its neighborhood, a relatively dense Global Positioning System (GPS) monitoring network was established in 2001. Combination of three spatially dense GPS campaigns in 2001, 2003 and 2004 with temporally dense campaigns between 1992 and 2004 resulted in a combined velocity field representing active deformation rate in the region. We computed horizontal and vertical velocity fields with respect to Earth-centered, Earth-fixed ITRF2000, to Eurasia and to Anatolia as well. The rates of principal and shear strains along with rigid-body rotation rates were derived from velocity field. Results show east-west shortening between Karaburun Peninsula and northern part of İzmir Bay together with the extension of İzmir Bay in accordance with general extension regime of Western Anatolia and Eastern Agea. East-west shortening and north-south extension of Karaburun Peninsula are closely related to right-lateral faulting and a clockwise rotation. There exists a block in the middle of the peninsula with a differential motion at a rate of 3-5 ± 1 mm/year and 5-6 ± 1 mm/year to the east and south, respectively. As is in Western Anatolia, north-south extension is dominant in almost all parts of the region despite the fact that they exhibit significantly higher rates in the middle of the peninsula. Extensional rates along Tuzla Fault lying nearly perpendicular to İzmir Bay and in its west are maximum in the region with an extension rate of 300-500 ± 80-100 nanostrain/year and confirm its active state. Extensional rates in other parts of the region are at level of 50-150 nanostrain/year as expected in the other parts of Western Anatolia.

Polymer-Based Dense Fluidic Networks for High Throughput Screening with Ultrasensitive Fluorescence Detection

PubMed Central

Okagbare, Paul I.; Soper, Steven A.

2011-01-01

Microfluidics represents a viable platform for performing High Throughput Screening (HTS) due to its ability to automate fluid handling and generate fluidic networks with high number densities over small footprints appropriate for the simultaneous optical interrogation of many screening assays. While most HTS campaigns depend on fluorescence, readers typically use point detection and serially address the assay results significantly lowering throughput or detection sensitivity due to a low duty cycle. To address this challenge, we present here the fabrication of a high density microfluidic network packed into the imaging area of a large field-of-view (FoV) ultrasensitive fluorescence detection system. The fluidic channels were 1, 5 or 10 μm (width), 1 μm (depth) with a pitch of 1–10 μm and each fluidic processor was individually addressable. The fluidic chip was produced from a molding tool using hot embossing and thermal fusion bonding to enclose the fluidic channels. A 40X microscope objective (numerical aperture = 0.75) created a FoV of 200 μm, providing the ability to interrogate ~25 channels using the current fluidic configuration. An ultrasensitive fluorescence detection system with a large FoV was used to transduce fluorescence signals simultaneously from each fluidic processor onto the active area of an electron multiplying charge-coupled device (EMCCD). The utility of these multichannel networks for HTS was demonstrated by carrying out the high throughput monitoring of the activity of an enzyme, APE1, used as a model screening assay. PMID:20872611

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Monitoring network completion. 58.13... (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a) The network of NCore multipollutant sites must be physically established no later than January 1, 2011...

Talking the talk, walking the walk: social network norms, communication patterns, and condom use among the male partners of female sex workers in La Romana, Dominican Republic.

PubMed

Barrington, Clare; Latkin, Carl; Sweat, Michael D; Moreno, Luis; Ellen, Jonathan; Kerrigan, Deanna

2009-06-01

Male partners of female sex workers are rarely targeted by HIV prevention interventions in the commercial sex industry, despite recognition of their central role and power in condom use negotiation. Social networks offer a naturally existing social structure to increase male participation in preventing HIV. The purpose of this study was to explore the relationship between social network norms and condom use among male partners of female sex workers in La Romana, Dominican Republic. Male partners (N =318) were recruited from 36 sex establishments to participate in a personal network survey. Measures of social network norms included 1) perceived condom use by male social network members and 2) encouragement to use condoms from social network members. Other social network characteristics included composition, density, social support, and communication. The primary behavioral outcome was consistent condom use by male partners with their most recent female sex worker partner during the last 3 months. In general, men reported small, dense networks with high levels of communication about condoms and consistent condom use. Multivariate logistic regression revealed consistent condom use was significantly more likely among male partners who perceived that some or all of their male social network members used condoms consistently. Perceived condom use was, in turn, significantly associated with dense networks, expressing dislike for condoms, and encouragement to use condoms from social network members. Findings suggest that the tight social networks of male partners may help to explain the high level of condom use and could provide an entry point for HIV prevention efforts with men. Such efforts should tap into existing social dynamics and patterns of communication to promote pro-condom norms and reduce HIV-related vulnerability among men and their sexual partners.

Gauge-adjusted rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Rieckermann, Jörg; Bareš, Vojtěch

2017-01-01

Increasing urbanization makes it more and more important to have accurate stormwater runoff predictions, especially with potentially severe weather and climatic changes on the horizon. Such stormwater predictions in turn require reliable rainfall information. Especially for urban centres, the problem is that the spatial and temporal resolution of rainfall observations should be substantially higher than commonly provided by weather services with their standard rainfall monitoring networks. Commercial microwave links (CMLs) are non-traditional sensors, which have been proposed about a decade ago as a promising solution. CMLs are line-of-sight radio connections widely used by operators of mobile telecommunication networks. They are typically very dense in urban areas and can provide path-integrated rainfall observations at sub-minute resolution. Unfortunately, quantitative precipitation estimates (QPEs) from CMLs are often highly biased due to several epistemic uncertainties, which significantly limit their usability. In this manuscript we therefore suggest a novel method to reduce this bias by adjusting QPEs to existing rain gauges. The method has been specifically designed to produce reliable results even with comparably distant rain gauges or cumulative observations. This eliminates the need to install reference gauges and makes it possible to work with existing information. First, the method is tested on data from a dedicated experiment, where a CML has been specifically set up for rainfall monitoring experiments, as well as operational CMLs from an existing cellular network. Second, we assess the performance for several experimental layouts of ground truth from rain gauges (RGs) with different spatial and temporal resolutions. The results suggest that CMLs adjusted by RGs with a temporal aggregation of up to 1 h (i) provide precise high-resolution QPEs (relative error < 7 %, Nash-Sutcliffe efficiency coefficient > 0.75) and (ii) that the combination of both sensor types clearly outperforms each individual monitoring system. Unfortunately, adjusting CML observations to RGs with longer aggregation intervals of up to 24 h has drawbacks. Although it substantially reduces bias, it unfavourably smoothes out rainfall peaks of high intensities, which is undesirable for stormwater management. A similar, but less severe, effect occurs due to spatial averaging when CMLs are adjusted to remote RGs. Nevertheless, even here, adjusted CMLs perform better than RGs alone. Furthermore, we provide first evidence that the joint use of multiple CMLs together with RGs also reduces bias in their QPEs. In summary, we believe that our adjustment method has great potential to improve the space-time resolution of current urban rainfall monitoring networks. Nevertheless, future work should aim to better understand the reason for the observed systematic error in QPEs from CMLs.

Protein complexes and functional modules in molecular networks

NASA Astrophysics Data System (ADS)

Spirin, Victor; Mirny, Leonid A.

2003-10-01

Proteins, nucleic acids, and small molecules form a dense network of molecular interactions in a cell. Molecules are nodes of this network, and the interactions between them are edges. The architecture of molecular networks can reveal important principles of cellular organization and function, similarly to the way that protein structure tells us about the function and organization of a protein. Computational analysis of molecular networks has been primarily concerned with node degree [Wagner, A. & Fell, D. A. (2001) Proc. R. Soc. London Ser. B 268, 1803-1810; Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. & Barabasi, A. L. (2000) Nature 407, 651-654] or degree correlation [Maslov, S. & Sneppen, K. (2002) Science 296, 910-913], and hence focused on single/two-body properties of these networks. Here, by analyzing the multibody structure of the network of protein-protein interactions, we discovered molecular modules that are densely connected within themselves but sparsely connected with the rest of the network. Comparison with experimental data and functional annotation of genes showed two types of modules: (i) protein complexes (splicing machinery, transcription factors, etc.) and (ii) dynamic functional units (signaling cascades, cell-cycle regulation, etc.). Discovered modules are highly statistically significant, as is evident from comparison with random graphs, and are robust to noise in the data. Our results provide strong support for the network modularity principle introduced by Hartwell et al. [Hartwell, L. H., Hopfield, J. J., Leibler, S. & Murray, A. W. (1999) Nature 402, C47-C52], suggesting that found modules constitute the "building blocks" of molecular networks.

Optimal river monitoring network using optimal partition analysis: a case study of Hun River, Northeast China.

PubMed

Wang, Hui; Liu, Chunyue; Rong, Luge; Wang, Xiaoxu; Sun, Lina; Luo, Qing; Wu, Hao

2018-01-09

River monitoring networks play an important role in water environmental management and assessment, and it is critical to develop an appropriate method to optimize the monitoring network. In this study, an effective method was proposed based on the attainment rate of National Grade III water quality, optimal partition analysis and Euclidean distance, and Hun River was taken as a method validation case. There were 7 sampling sites in the monitoring network of the Hun River, and 17 monitoring items were analyzed once a month during January 2009 to December 2010. The results showed that the main monitoring items in the surface water of Hun River were ammonia nitrogen (NH 4 + -N), chemical oxygen demand, and biochemical oxygen demand. After optimization, the required number of monitoring sites was reduced from seven to three, and 57% of the cost was saved. In addition, there were no significant differences between non-optimized and optimized monitoring networks, and the optimized monitoring networks could correctly represent the original monitoring network. The duplicate setting degree of monitoring sites decreased after optimization, and the rationality of the monitoring network was improved. Therefore, the optimal method was identified as feasible, efficient, and economic.

Evolution of NO2 levels in Spain from 1996 to 2012

PubMed Central

Cuevas, Carlos A.; Notario, Alberto; Adame, José Antonio; Hilboll, Andreas; Richter, Andreas; Burrows, John P.; Saiz-Lopez, Alfonso

2014-01-01

We report on the evolution of tropospheric nitrogen dioxide (NO2) over Spain, focusing on the densely populated cities of Barcelona, Bilbao, Madrid, Sevilla and Valencia, during 17 years, from 1996 to 2012. This data series combines observations from in-situ air quality monitoring networks and the satellite-based instruments GOME and SCIAMACHY. The results in these five cities show a smooth decrease in the NO2 concentrations of ~2% per year in the period 1996–2008, due to the implementation of emissions control environmental legislation, and a more abrupt descend of ~7% per year from 2008 to 2012 as a consequence of the economic recession. In the whole Spanish territory the NO2 levels have decreased by ~22% from 1996 to 2012. Statistical analysis of several economic indicators is used to investigate the different factors driving the NO2 concentration trends over Spain during the last two decades. PMID:25074028

Macrofouling of deep-sea instrumentation after three years at 3690 m depth in the Charlie Gibbs fracture zone, mid-Atlantic ridge, with emphasis on hydroids (Cnidaria: Hydrozoa)

NASA Astrophysics Data System (ADS)

Blanco, R.; Shields, M. A.; Jamieson, A. J.

2013-12-01

Macrofouling is a common problem when deploying underwater instrumentation for long periods of time. It is a problem which can effect scientific experiments and monitoring missions though the creation of artificial reefs (thus increasing local biological activity) and reduce the quality of scientific data. Macrofouling is an issue typically considered to be restricted to the photic zones and is absent or negligible in the deep sea. To the contrary, the recovery of an accidentally lost deep-sea lander after 3 years submergence at 3960 m on the Mid-Atlantic Ridge (North Atlantic) revealed dense colonisation of macrofouling organisms. These organisms were found attached to all surfaces of the lander regardless of orientation and materials. The occurrence of such deep-sea macrofouling should be carefully investigated given the recent developments in long-term deep-sea observatory networks.

Ionospheric modifications detected by a dense network of single frequency GNSS receivers

NASA Astrophysics Data System (ADS)

Mrak, S.; Semeter, J. L.

2017-12-01

It has been predicted that the region of totality during a total solar eclipse can launch atmospheric gravity waves with large enough amplitude to cause traveling ionospheric disturbances (TIDs). We report initial results from a remote sensing campaign involving a dense hybrid network of single- and dual-frequency GNSS receivers deployed underneath the 21 August 2017 solar eclipse. The campaign took place in central Missouri, involving 84 Trimble dual-frequency receivers, complemented by 2 additional 50 Hz dual-frequency receivers and 15 single-frequency receivers, together constructing 100 receivers with average mutual separation of less than 25 km and with a time resolution of 1 second or better. The initial results show a crescent shaped enhancement bulge in front of region of totality, extending all the way from Canada to Gulf of Mexico. In addition, in the path of totality is noticed a great depletion region, followed by a pair of transverse waves propagating in west-east direction. In the following months, we will explore the transition region carried by the totality by a virtue of hyper dense network of GNSS receivers with 1 second resolution. In addition to TEC data decomposition we will explore effects of the totality on the raw measurements (phase, code and signal intensity), and to the navigation solution which is likely to be effected by a different propagation conditions with respect to other days.

Carbon aerogels by pyrolysis of TEMPO-oxidized cellulose

NASA Astrophysics Data System (ADS)

Zhang, Sizhao; Feng, Jian; Feng, Junzong; Jiang, Yonggang; Ding, Feng

2018-05-01

Although carbon aerogels derived from naturally occurring materials have been developed extensively, a reasonable synthetic approach using cellulose-resource remains unclear. Here, we report a strategy to prepare carbon aerogels originated from cellulose position-selectively oxidized by TEMPO-oxidized process. Contrary to non-TEMPO-oxidized cellulose-derived carbon aerogels (NCCA) with relative loose structure, TEMPO-oxidized cellulose-derived carbon aerogels (TCCA) with tight fibrillar-continuous network are monitored, suggesting the importance of TEMPO-oxidized modification towards creating the architecture of subsequently produced carbon aerogels. TCCA endows a higher BET area despite owning slightly dense bulk density comparing with that of NCCA. The structural texture of TCCA could be maintained in a way in comparison to TEMPO-oxidized cellulose-derived aerogel, due to the integration and aggregation effect by losing the electric double layer repulsion via ionization of the surface carboxyl groups. FTIR and XPS analyses signify the evidence of non-functionalized carbon-skeleton network formation in terms of TCCA. Further, the mechanism concerning the creation of carbon aerogels is also established. These findings not only provide new insights into the production of carbon aerogels but also open up a new opportunity in the field of functional carbon materials.

Coherent ultra dense wavelength division multiplexing passive optical networks

NASA Astrophysics Data System (ADS)

Shahpari, Ali; Ferreira, Ricardo; Ribeiro, Vitor; Sousa, Artur; Ziaie, Somayeh; Tavares, Ana; Vujicic, Zoran; Guiomar, Fernando P.; Reis, Jacklyn D.; Pinto, Armando N.; Teixeira, António

2015-12-01

In this paper, we firstly review the progress in ultra-dense wavelength division multiplexing passive optical network (UDWDM-PON), by making use of the key attributes of this technology in the context of optical access and metro networks. Besides the inherit properties of coherent technology, we explore different modulation formats and pulse shaping. The performance is experimentally demonstrated through a 12 × 10 Gb/s bidirectional UDWDM-PON over hybrid 80 km standard single mode fiber (SSMF) and optical wireless link. High density, 6.25 GHz grid, Nyquist shaped 16-ary quadrature amplitude modulation (16QAM) and digital frequency shifting are some of the properties exploited together in the tests. Also, bidirectional transmission in fiber, relevant in the context, is analyzed in terms of nonlinear and back-reflection effects on receiver sensitivity. In addition, as a basis for the discussion on market readiness, we experimentally demonstrate real-time detection of a Nyquist-shaped quaternary phase-shift keying (QPSK) signal using simple 8-bit digital signal processing (DSP) on a field-programmable gate array (FPGA).

Dense fibrillar collagen is a potent inducer of invadopodia via a specific signaling network

PubMed Central

Swatkoski, Stephen; Matsumoto, Kazue; Campbell, Catherine B.; Petrie, Ryan J.; Dimitriadis, Emilios K.; Li, Xin; Mueller, Susette C.; Bugge, Thomas H.; Gucek, Marjan

2015-01-01

Cell interactions with the extracellular matrix (ECM) can regulate multiple cellular activities and the matrix itself in dynamic, bidirectional processes. One such process is local proteolytic modification of the ECM. Invadopodia of tumor cells are actin-rich proteolytic protrusions that locally degrade matrix molecules and mediate invasion. We report that a novel high-density fibrillar collagen (HDFC) matrix is a potent inducer of invadopodia, both in carcinoma cell lines and in primary human fibroblasts. In carcinoma cells, HDFC matrix induced formation of invadopodia via a specific integrin signaling pathway that did not require growth factors or even altered gene and protein expression. In contrast, phosphoproteomics identified major changes in a complex phosphosignaling network with kindlin2 serine phosphorylation as a key regulatory element. This kindlin2-dependent signal transduction network was required for efficient induction of invadopodia on dense fibrillar collagen and for local degradation of collagen. This novel phosphosignaling mechanism regulates cell surface invadopodia via kindlin2 for local proteolytic remodeling of the ECM. PMID:25646088

A Framework for Real-Time Collection, Analysis, and Classification of Ubiquitous Infrasound Data

NASA Astrophysics Data System (ADS)

Christe, A.; Garces, M. A.; Magana-Zook, S. A.; Schnurr, J. M.

2015-12-01

Traditional infrasound arrays are generally expensive to install and maintain. There are ~10^3 infrasound channels on Earth today. The amount of data currently provided by legacy architectures can be processed on a modest server. However, the growing availability of low-cost, ubiquitous, and dense infrasonic sensor networks presents a substantial increase in the volume, velocity, and variety of data flow. Initial data from a prototype ubiquitous global infrasound network is already pushing the boundaries of traditional research server and communication systems, in particular when serving data products over heterogeneous, international network topologies. We present a scalable, cloud-based approach for capturing and analyzing large amounts of dense infrasonic data (>10^6 channels). We utilize Akka actors with WebSockets to maintain data connections with infrasound sensors. Apache Spark provides streaming, batch, machine learning, and graph processing libraries which will permit signature classification, cross-correlation, and other analytics in near real time. This new framework and approach provide significant advantages in scalability and cost.

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 6 2012-07-01 2012-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 6 2014-07-01 2014-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...

40 CFR 58.13 - Monitoring network completion.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 6 2013-07-01 2013-07-01 false Monitoring network completion. 58.13 Section 58.13 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.13 Monitoring network completion. (a...

Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

NASA Technical Reports Server (NTRS)

Wang, Shin-Ywan

2012-01-01

The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

Isotopic Recorders of Pollution in Heterogeneous Urban Areas

NASA Astrophysics Data System (ADS)

Pataki, D. E.; Cobley, L.; Smith, R. M.; Ehleringer, J. R.; Chritz, K.

2017-12-01

A significant difficulty in quantifying urban pollution lies in the extreme spatial and temporal heterogeneity of cities. Dense sources of both point and non-point source pollution as well as the dynamic role of human activities, which vary over very short time scales and small spatial scales, complicate efforts to establish long-term urban monitoring networks that are relevant at neighborhood, municipal, and regional scales. Fortunately, the natural abundance of isotopes of carbon, nitrogen, and other elements provides a wealth of information about the sources and fate of urban atmospheric pollution. In particular, soils and plant material integrate pollution sources and cycling over space and time, and have the potential to provide long-term records of pollution dynamics that extend back before atmospheric monitoring data are available. Similarly, sampling organic material at high spatial resolution can provide "isoscapes" that shed light on the spatial heterogeneity of pollutants in different urban parcels and neighborhoods, along roads of varying traffic density, and across neighborhoods of varying affluence and sociodemographic composition. We have compiled numerous datasets of the isotopic composition of urban organic matter that illustrate the potential for isotopic monitoring of urban areas as a means of understanding hot spots and hot moments in urban atmospheric biogeochemistry. Findings to date already reveal the critical role of affluence, economic activity, demographic change, and land management practices in influencing urban pollution sources and sinks, and suggest an important role of stable isotope and radioisotope measurements in urban atmospheric and biogeochemical monitoring.

An Enhanced Monitoring Network at the Central Nevada Test Area (CNTA) Work performed under U.S. Department of Energy Office of Legacy Management contract #DE-AM01-07LM00060

NASA Astrophysics Data System (ADS)

Hodges, R.; Findlay, R.; Kautsky, M.

2009-12-01

On January 19, 1968 the Atomic Energy Commission detonated a 200-1000 kt nuclear device at a depth of 975 meters at CNTA, approximately 100 miles north of the Nevada Test Site. Details of the detonation remain classified, including the specific yield and the size of the resultant cavity. Therefore, using the rough, generic relationships between yield and cavity size, yield and depth of burial, and cancelling out yield, leads to an estimated cavity radius of 100 meters for this detonation in the volcanic section. A collapse chimney subsequently formed that extended several hundred meters above the detonation into the overlying alluvium. The detonation reactivated several faults at the site and created a 2 km2 graben at the surface. The radionuclides in the detonation zone are a potential source of groundwater contamination. The most permeable unit near the detonation zone through which transport might occur is believed to be a densely welded tuff unit (DWT) below the detonation level. A three-well monitoring network was designed using a numerical model, and data were collected from the wells for comparison with model predictions. The head data from the wells were not in agreement with those predicted by the model, and the model was not validated. In a positive finding for radionuclide containment, aquifer test results from the new wells indicate that the DWT is less permeable than previously expected and suggest that the contaminant boundary developed from the model is likely conservative for predicting transport within the volcanic section. The overlying alluvial aquifer is not believed to be a migration pathway for significant quantities of radionuclides, though it is the most likely pathway to potential receptors in that it is the primary groundwater source in the area. To enhance the CNTA monitoring network, two new alluvial wells were installed in 2009, downgradient (east-southeast and south-southeast) of the detonation. The dual-completion alluvial wells were designed to not only monitor for radionuclides but also to determine if a southeast-bounding graben fault acts as a flow barrier. A seismic survey was conducted to optimally locate the wells with respect to the fault. The survey imaged the water table and showed offsets of the water table reflector at numerous faults; some of the faults were known and others had not been previously recognized. Water levels from the new alluvial wells and piezometers compare well with existing well data and support the conjecture that the southeast-bounding graben fault is a flow barrier. Over the last five years, a monitoring network at CNTA has been developed that monitors both the most likely migration pathway and the most likely pathway to potential receptors. The site investigation processes discussed here have also identified factors that affect groundwater flow at the site, and the methods employed can be used in similar hydrogeologic environments.

A Multi-Walled Carbon Nanotube-based Biosensor for Monitoring Microcystin-LR in Sources of Drinking Water Supplies

EPA Science Inventory

A multi-walled carbon nanotube-based electrochemical biosensor is developed for monitoring microcystin-LR (MC-LR), a toxic cyanobacterial toxin, in sources of drinking water supplies. The biosensor electrodes are fabricated using dense, mm-long multi-walled CNT (MWCNT) arrays gro...

Self Sealing Magmas

NASA Astrophysics Data System (ADS)

von Aulock, Felix W.; Wadsworth, Fabian B.; Kennedy, Ben M.; Lavallee, Yan

2015-04-01

During ascent of magma, pressure decreases and bubbles form. If the volume increases more rapidly than the relaxation timescale, the magma fragments catastrophically. If a permeable network forms, the magma degasses non-violently. This process is generally assumed to be unidirectional, however, recent studies have shown how shear and compaction can drive self sealing. Here, we additionally constrain skin formation during degassing and sintering. We heated natural samples of obsidian in a dry atmosphere and monitored foaming and impermeable skin formation. We suggest a model for skin formation that is controlled by diffusional loss of water and bubble collapse at free surfaces. We heated synthetic glass beads in a hydrous atmosphere to measure the timescale of viscous sintering. The beads sinter at drastically shorter timescales as water vapour rehydrates an otherwise degassed melt, reducing viscosity and glass transition temperatures. Both processes can produce dense inhomogeneities within the timescales of magma ascent and effectively disturb permeabilities and form barriers, particularly at the margins of the conduit, where strain localisation takes place. Localised ash in failure zones (i.e. Tuffisite) then becomes associated with water vapour fluxes and alow rapid rehydration and sintering. When measuring permeabilities in laboratory and field, and when discussing shallow degassing in volcanoes, local barriers for degassing should be taken into account. Highlighting the processes that lead to the formation of such dense skins and sintered infills of cavities can help understanding the bulk permeabilities of volcanic systems.

Sources of high frequency seismic noise: insights from a dense network of ~250 stations in northern Alsace (France)

NASA Astrophysics Data System (ADS)

Vergne, Jerome; Blachet, Antoine; Lehujeur, Maximilien

2015-04-01

Monitoring local or regional seismic activity requires stations having a low level of background seismic noise at frequencies higher than few tenths of Hertz. Network operators are well aware that the seismic quality of a site depends on several aspects, among them its geological setting and the proximity of roads, railways, industries or trees. Often, the impact of each noise source is only qualitatively known which precludes estimating the quality of potential future sites before they are tested or installed. Here, we want to take advantage of a very dense temporary network deployed in Northern Alsace (France) to assess the effect of various kinds of potential sources on the level of seismic noise observed in the frequency range 0.2-50 Hz. In September 2014, more than 250 seismic stations (FairfieldNodal@ Zland nodes with 10Hz vertical geophone) have been installed every 1.5 km over a ~25km diameter disc centred on the deep geothermal sites of Soultz-sous-Forêts and Rittershoffen. This region exhibits variable degrees of human imprints from quite remote areas to sectors with high traffic roads and big villages. It also encompasses both the deep sedimentary basin of the Rhine graben and the piedmont of the Vosges massif with exposed bedrock. For each site we processed the continuous data to estimate probability density functions of the power spectral densities. At frequencies higher than 1 Hz most sites show a clear temporal modulation of seismic noise related to human activity with the well-known variations between day and night and between weekdays and weekends. Moreover we observe a clear evolution of the spatial distribution of seismic noise levels with frequency. Basically, between 0.5 and 4 Hz the geological setting modulates the level of seismic noise. At higher frequencies, the amplitude of seismic noise appears mostly related to the distance to nearby roads. Based on road maps and traffic estimation, a forward approach is performed to model the induced seismic noise. Effects of other types of seismic sources, such as industries or wind, are also observed but usually have a more limited spatial extension and a specific signature in the spectrograms.

Wireless structural monitoring for homeland security applications

NASA Astrophysics Data System (ADS)

Kiremidjian, Garo K.; Kiremidjian, Anne S.; Lynch, Jerome P.

2004-07-01

This paper addresses the development of a robust, low-cost, low power, and high performance autonomous wireless monitoring system for civil assets such as large facilities, new construction, bridges, dams, commercial buildings, etc. The role of the system is to identify the onset, development, location and severity of structural vulnerability and damage. The proposed system represents an enabling infrastructure for addressing structural vulnerabilities specifically associated with homeland security. The system concept is based on dense networks of "intelligent" wireless sensing units. The fundamental properties of a wireless sensing unit include: (a) interfaces to multiple sensors for measuring structural and environmental data (such as acceleration, displacements, pressure, strain, material degradation, temperature, gas agents, biological agents, humidity, corrosion, etc.); (b) processing of sensor data with embedded algorithms for assessing damage and environmental conditions; (c) peer-to-peer wireless communications for information exchange among units(thus enabling joint "intelligent" processing coordination) and storage of data and processed information in servers for information fusion; (d) ultra low power operation; (e) cost-effectiveness and compact size through the use of low-cost small-size off-the-shelf components. An integral component of the overall system concept is a decision support environment for interpretation and dissemination of information to various decision makers.

Global Mapping of the Yeast Genetic Interaction Network

NASA Astrophysics Data System (ADS)

Tong, Amy Hin Yan; Lesage, Guillaume; Bader, Gary D.; Ding, Huiming; Xu, Hong; Xin, Xiaofeng; Young, James; Berriz, Gabriel F.; Brost, Renee L.; Chang, Michael; Chen, YiQun; Cheng, Xin; Chua, Gordon; Friesen, Helena; Goldberg, Debra S.; Haynes, Jennifer; Humphries, Christine; He, Grace; Hussein, Shamiza; Ke, Lizhu; Krogan, Nevan; Li, Zhijian; Levinson, Joshua N.; Lu, Hong; Ménard, Patrice; Munyana, Christella; Parsons, Ainslie B.; Ryan, Owen; Tonikian, Raffi; Roberts, Tania; Sdicu, Anne-Marie; Shapiro, Jesse; Sheikh, Bilal; Suter, Bernhard; Wong, Sharyl L.; Zhang, Lan V.; Zhu, Hongwei; Burd, Christopher G.; Munro, Sean; Sander, Chris; Rine, Jasper; Greenblatt, Jack; Peter, Matthias; Bretscher, Anthony; Bell, Graham; Roth, Frederick P.; Brown, Grant W.; Andrews, Brenda; Bussey, Howard; Boone, Charles

2004-02-01

A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

A network monitor for HTTPS protocol based on proxy

NASA Astrophysics Data System (ADS)

Liu, Yangxin; Zhang, Lingcui; Zhou, Shuguang; Li, Fenghua

2016-10-01

With the explosive growth of harmful Internet information such as pornography, violence, and hate messages, network monitoring is essential. Traditional network monitors is based mainly on bypass monitoring. However, we can't filter network traffic using bypass monitoring. Meanwhile, only few studies focus on the network monitoring for HTTPS protocol. That is because HTTPS data is in the encrypted traffic, which makes it difficult to monitor. This paper proposes a network monitor for HTTPS protocol based on proxy. We adopt OpenSSL to establish TLS secure tunes between clients and servers. Epoll is used to handle a large number of concurrent client connections. We also adopt Knuth- Morris-Pratt string searching algorithm (or KMP algorithm) to speed up the search process. Besides, we modify request packets to reduce the risk of errors and modify response packets to improve security. Experiments show that our proxy can monitor the content of all tested HTTPS websites efficiently with little loss of network performance.

Shear-induced organization of forces in dense suspensions: signatures of discontinuous shear thickening

NASA Astrophysics Data System (ADS)

Sarkar, Sumantra; Shatoff, Elan; Ramola, Kabir; Mari, Romain; Morris, Jeffrey; Chakraborty, Bulbul

2017-06-01

Dense suspensions can exhibit an abrupt change in their viscosity in response to increasing shear rate. The origin of this discontinuous shear thickening (DST) has been ascribed to the transformation of lubricated contacts to frictional, particle-on-particle contacts. Recent research on the flowing and jamming behavior of dense suspensions has explored the intersection of ideas from granular physics and Stokesian fluid dynamics to better understand this transition from lubricated to frictional rheology. DST is reminiscent of classical phase transitions, and a key question is how interactions between the microscopic constituents give rise to a macroscopic transition. In this paper, we extend a formalism that has proven to be successful in understanding shear jamming of dry grains to dense suspensions. Quantitative analysis of the collective evolution of the contactforce network accompanying the DST transition demonstrates clear changes in the distribution of microscopic variables, and leads to the identification of an "order parameter" characterizing DST.

Local Crystalline Structure in an Amorphous Protein Dense Phase

PubMed Central

Greene, Daniel G.; Modla, Shannon; Wagner, Norman J.; Sandler, Stanley I.; Lenhoff, Abraham M.

2015-01-01

Proteins exhibit a variety of dense phases ranging from gels, aggregates, and precipitates to crystalline phases and dense liquids. Although the structure of the crystalline phase is known in atomistic detail, little attention has been paid to noncrystalline protein dense phases, and in many cases the structures of these phases are assumed to be fully amorphous. In this work, we used small-angle neutron scattering, electron microscopy, and electron tomography to measure the structure of ovalbumin precipitate particles salted out with ammonium sulfate. We found that the ovalbumin phase-separates into core-shell particles with a core radius of ∼2 μm and shell thickness of ∼0.5 μm. Within this shell region, nanostructures comprised of crystallites of ovalbumin self-assemble into a well-defined bicontinuous network with branches ∼12 nm thick. These results demonstrate that the protein gel is comprised in part of nanocrystalline protein. PMID:26488663

Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons

PubMed Central

Setareh, Hesam; Deger, Moritz; Petersen, Carl C. H.; Gerstner, Wulfram

2017-01-01

Experimental measurements of pairwise connection probability of pyramidal neurons together with the distribution of synaptic weights have been used to construct randomly connected model networks. However, several experimental studies suggest that both wiring and synaptic weight structure between neurons show statistics that differ from random networks. Here we study a network containing a subset of neurons which we call weight-hub neurons, that are characterized by strong inward synapses. We propose a connectivity structure for excitatory neurons that contain assemblies of densely connected weight-hub neurons, while the pairwise connection probability and synaptic weight distribution remain consistent with experimental data. Simulations of such a network with generalized integrate-and-fire neurons display regular and irregular slow oscillations akin to experimentally observed up/down state transitions in the activity of cortical neurons with a broad distribution of pairwise spike correlations. Moreover, stimulation of a model network in the presence or absence of assembly structure exhibits responses similar to light-evoked responses of cortical layers in optogenetically modified animals. We conclude that a high connection probability into and within assemblies of excitatory weight-hub neurons, as it likely is present in some but not all cortical layers, changes the dynamics of a layer of cortical microcircuitry significantly. PMID:28690508

A Gap-Filling Procedure for Hydrologic Data Based on Kalman Filtering and Expectation Maximization: Application to Data from the Wireless Sensor Networks of the Sierra Nevada

NASA Astrophysics Data System (ADS)

Coogan, A.; Avanzi, F.; Akella, R.; Conklin, M. H.; Bales, R. C.; Glaser, S. D.

2017-12-01

Automatic meteorological and snow stations provide large amounts of information at dense temporal resolution, but data quality is often compromised by noise and missing values. We present a new gap-filling and cleaning procedure for networks of these stations based on Kalman filtering and expectation maximization. Our method utilizes a multi-sensor, regime-switching Kalman filter to learn a latent process that captures dependencies between nearby stations and handles sharp changes in snowfall rate. Since the latent process is inferred using observations across working stations in the network, it can be used to fill in large data gaps for a malfunctioning station. The procedure was tested on meteorological and snow data from Wireless Sensor Networks (WSN) in the American River basin of the Sierra Nevada. Data include air temperature, relative humidity, and snow depth from dense networks of 10 to 12 stations within 1 km2 swaths. Both wet and dry water years have similar data issues. Data with artificially created gaps was used to quantify the method's performance. Our multi-sensor approach performs better than a single-sensor one, especially with large data gaps, as it learns and exploits the dominant underlying processes in snowpack at each site.

Fast algorithm for automatically computing Strahler stream order

USGS Publications Warehouse

Lanfear, Kenneth J.

1990-01-01

An efficient algorithm was developed to determine Strahler stream order for segments of stream networks represented in a Geographic Information System (GIS). The algorithm correctly assigns Strahler stream order in topologically complex situations such as braided streams and multiple drainage outlets. Execution time varies nearly linearly with the number of stream segments in the network. This technique is expected to be particularly useful for studying the topology of dense stream networks derived from digital elevation model data.

Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment

NASA Astrophysics Data System (ADS)

Johnson, Nicholas E.; Bonczak, Bartosz; Kontokosta, Constantine E.

2018-07-01

The increased availability and improved quality of new sensing technologies have catalyzed a growing body of research to evaluate and leverage these tools in order to quantify and describe urban environments. Air quality, in particular, has received greater attention because of the well-established links to serious respiratory illnesses and the unprecedented levels of air pollution in developed and developing countries and cities around the world. Though numerous laboratory and field evaluation studies have begun to explore the use and potential of low-cost air quality monitoring devices, the performance and stability of these tools has not been adequately evaluated in complex urban environments, and further research is needed. In this study, we present the design of a low-cost air quality monitoring platform based on the Shinyei PPD42 aerosol monitor and examine the suitability of the sensor for deployment in a dense heterogeneous urban environment. We assess the sensor's performance during a field calibration campaign from February 7th to March 25th 2017 with a reference instrument in New York City, and present a novel calibration approach using a machine learning method that incorporates publicly available meteorological data in order to improve overall sensor performance. We find that while the PPD42 performs well in relation to the reference instrument using linear regression (R2 = 0.36-0.51), a gradient boosting regression tree model can significantly improve device calibration (R2 = 0.68-0.76). We discuss the sensor's performance and reliability when deployed in a dense, heterogeneous urban environment during a period of significant variation in weather conditions, and important considerations when using machine learning techniques to improve the performance of low-cost air quality monitors.

Regional and local variations in atmospheric aerosols using ground-based sun photometry during Distributed Regional Aerosol Gridded Observation Networks (DRAGON) in 2012

NASA Astrophysics Data System (ADS)

Sano, Itaru; Mukai, Sonoyo; Nakata, Makiko; Holben, Brent N.

2016-11-01

Aerosol mass concentrations are affected by local emissions as well as long-range transboundary (LRT) aerosols. This work investigates regional and local variations of aerosols based on Distributed Regional Aerosol Gridded Observation Networks (DRAGON). We constructed DRAGON-Japan and DRAGON-Osaka in spring of 2012. The former network covers almost all of Japan in order to obtain aerosol information in regional scale over Japanese islands. It was determined from the DRAGON-Japan campaign that the values of aerosol optical thickness (AOT) decrease from west to east during an aerosol episode. In fact, the highest AOT was recorded at Fukue Island at the western end of the network, and the value was much higher than that of urban areas. The latter network (DRAGON-Osaka) was set as a dense instrument network in the megalopolis of Osaka, with a population of 12 million, to better understand local aerosol dynamics in urban areas. AOT was further measured with a mobile sun photometer attached to a car. This transect information showed that aerosol concentrations rapidly changed in time and space together when most of the Osaka area was covered with moderate LRT aerosols. The combined use of the dense instrument network (DRAGON-Osaka) and high-frequency measurements provides the motion of aerosol advection, which coincides with the wind vector around the layer between 700 and 850 hPa as provided by the reanalysis data of the National Centers for Environmental Prediction (NCEP).

Regional and Local Variations in Atmospheric Aerosols Using Ground-Based Sun Photometry During Distributed Regional Aerosol Gridded Observation Networks (DRAGON) in 2012

NASA Technical Reports Server (NTRS)

Sano, Itaru; Mukai, Sonoyo; Nakata, Makiko; Holben, Brent N.

2016-01-01

Aerosol mass concentrations are affected by local emissions as well as long-range transboundary (LRT) aerosols. This work investigates regional and local variations of aerosols based on Distributed Regional Aerosol Gridded Observation Networks (DRAGON).We constructed DRAGON-Japan and DRAGON-Osaka in spring of 2012. The former network covers almost all of Japan in order to obtain aerosol information in regional scale over Japanese islands. It was determined from the DRAGON-Japan campaign that the values of aerosol optical thickness (AOT) decrease from west to east during an aerosol episode. In fact, the highest AOT was recorded at Fukue Island at the western end of the network, and the value was much higher than that of urban areas. The latter network (DRAGON-Osaka) was set as a dense instrument network in the megalopolis of Osaka, with a population of 12 million, to better understand local aerosol dynamics in urban areas. AOT was further measured with a mobile sun photometer attached to a car. This transect information showed that aerosol concentrations rapidly changed in time and space together when most of the Osaka area was covered with moderate LRT aerosols. The combined use of the dense instrument network (DRAGON-Osaka) and high-frequency measurements provides the motion of aerosol advection, which coincides with the wind vector around the layer between 700 and 850 hPa as provided by the reanalysis data of the National Centers for Environmental Prediction (NCEP).

Dense-HOG-based drift-reduced 3D face tracking for infant pain monitoring

NASA Astrophysics Data System (ADS)

Saeijs, Ronald W. J. J.; Tjon A Ten, Walther E.; de With, Peter H. N.

2017-03-01

This paper presents a new algorithm for 3D face tracking intended for clinical infant pain monitoring. The algorithm uses a cylinder head model and 3D head pose recovery by alignment of dynamically extracted templates based on dense-HOG features. The algorithm includes extensions for drift reduction, using re-registration in combination with multi-pose state estimation by means of a square-root unscented Kalman filter. The paper reports experimental results on videos of moving infants in hospital who are relaxed or in pain. Results show good tracking behavior for poses up to 50 degrees from upright-frontal. In terms of eye location error relative to inter-ocular distance, the mean tracking error is below 9%.

Memory-Efficient Analysis of Dense Functional Connectomes.

PubMed

Loewe, Kristian; Donohue, Sarah E; Schoenfeld, Mircea A; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download.

Memory-Efficient Analysis of Dense Functional Connectomes

PubMed Central

Loewe, Kristian; Donohue, Sarah E.; Schoenfeld, Mircea A.; Kruse, Rudolf; Borgelt, Christian

2016-01-01

The functioning of the human brain relies on the interplay and integration of numerous individual units within a complex network. To identify network configurations characteristic of specific cognitive tasks or mental illnesses, functional connectomes can be constructed based on the assessment of synchronous fMRI activity at separate brain sites, and then analyzed using graph-theoretical concepts. In most previous studies, relatively coarse parcellations of the brain were used to define regions as graphical nodes. Such parcellated connectomes are highly dependent on parcellation quality because regional and functional boundaries need to be relatively consistent for the results to be interpretable. In contrast, dense connectomes are not subject to this limitation, since the parcellation inherent to the data is used to define graphical nodes, also allowing for a more detailed spatial mapping of connectivity patterns. However, dense connectomes are associated with considerable computational demands in terms of both time and memory requirements. The memory required to explicitly store dense connectomes in main memory can render their analysis infeasible, especially when considering high-resolution data or analyses across multiple subjects or conditions. Here, we present an object-based matrix representation that achieves a very low memory footprint by computing matrix elements on demand instead of explicitly storing them. In doing so, memory required for a dense connectome is reduced to the amount needed to store the underlying time series data. Based on theoretical considerations and benchmarks, different matrix object implementations and additional programs (based on available Matlab functions and Matlab-based third-party software) are compared with regard to their computational efficiency. The matrix implementation based on on-demand computations has very low memory requirements, thus enabling analyses that would be otherwise infeasible to conduct due to insufficient memory. An open source software package containing the created programs is available for download. PMID:27965565

Spatial and temporal variation of water temperature regimes on the Snoqualmie River network

Treesearch

Ashley E. Steel; Colin Sowder; Erin E. Peterson

2016-01-01

Although mean temperatures change annually and are highly correlated with elevation, the entire thermal regime on the Snoqualmie River, Washington, USA does not simply shift with elevation or season. Particular facets of the thermal regime have unique spatial patterns on the river network and at particular times of the year. We used a spatially and temporally dense...

Weak Ties and Self-Regulation in Job Search: The Effects of Goal Orientation on Networking

ERIC Educational Resources Information Center

Hatala, John-Paul; Yamkovenko, Bogdan

2016-01-01

The purpose of this study is to empirically investigate the relationship between the self-regulatory variable of goal orientation and the extent to which job seekers reach out to and use weak ties in their job search. Weak ties, as defined by Granovettor, are connections to densely knit networks outside the individual's direct contacts who could…

3D morphometry of valley networks on Mars from HRSC/MEX DEMs: Implications for climatic evolution through time

NASA Astrophysics Data System (ADS)

Ansan, V.; Mangold, N.

2013-09-01

valley networks have been identified mainly in the Noachian heavily cratered uplands. Eight dense branching valley networks were studied in Noachian terrains of Huygens, Newcomb and Kepler craters, south Tyrrhena Terra, and Thaumasia, in Hesperian terrains of Echus Plateau and west Eberswalde craters, and in Amazonian terrains of Alba Patera, using images and digital elevation models from the Mars Express High Resolution Stereo Camera to determine 2D and 3D morphometric parameters. Extracted geomorphic parameters show similar geometry to terrestrial valleys: drainage densities, organization from bifurcation ratios and lengths ratios, Hack exponent consistent with terrestrial values of ~0.6, and progressive deepening of valleys with increasing Strahler order. In addition, statistics on valley depths indicate a deeper incision of Noachian valleys compared to younger post-Noachian valleys (<25 m for Amazonian ones compared to >100 m for Noachian ones), showing a strong difference in fluvial erosion. These characteristics show that dense Martian valley networks formed by overland flows in relation to a global atmospheric water cycle in Noachian epoch and confirm that the later stages of activity may be related to shorter duration of activity, distinct climatic conditions, and/or regional processes, or conditions.

A conceptual ground-water-quality monitoring network for San Fernando Valley, California

USGS Publications Warehouse

Setmire, J.G.

1985-01-01

A conceptual groundwater-quality monitoring network was developed for San Fernando Valley to provide the California State Water Resources Control Board with an integrated, basinwide control system to monitor the quality of groundwater. The geology, occurrence and movement of groundwater, land use, background water quality, and potential sources of pollution were described and then considered in designing the conceptual monitoring network. The network was designed to monitor major known and potential point and nonpoint sources of groundwater contamination over time. The network is composed of 291 sites where wells are needed to define the groundwater quality. The ideal network includes four specific-purpose networks to monitor (1) ambient water quality, (2) nonpoint sources of pollution, (3) point sources of pollution, and (4) line sources of pollution. (USGS)

Overlapping communities from dense disjoint and high total degree clusters

NASA Astrophysics Data System (ADS)

Zhang, Hongli; Gao, Yang; Zhang, Yue

2018-04-01

Community plays an important role in the field of sociology, biology and especially in domains of computer science, where systems are often represented as networks. And community detection is of great importance in the domains. A community is a dense subgraph of the whole graph with more links between its members than between its members to the outside nodes, and nodes in the same community probably share common properties or play similar roles in the graph. Communities overlap when nodes in a graph belong to multiple communities. A vast variety of overlapping community detection methods have been proposed in the literature, and the local expansion method is one of the most successful techniques dealing with large networks. The paper presents a density-based seeding method, in which dense disjoint local clusters are searched and selected as seeds. The proposed method selects a seed by the total degree and density of local clusters utilizing merely local structures of the network. Furthermore, this paper proposes a novel community refining phase via minimizing the conductance of each community, through which the quality of identified communities is largely improved in linear time. Experimental results in synthetic networks show that the proposed seeding method outperforms other seeding methods in the state of the art and the proposed refining method largely enhances the quality of the identified communities. Experimental results in real graphs with ground-truth communities show that the proposed approach outperforms other state of the art overlapping community detection algorithms, in particular, it is more than two orders of magnitude faster than the existing global algorithms with higher quality, and it obtains much more accurate community structure than the current local algorithms without any priori information.

Saltwater intrusion monitoring in Florida

USGS Publications Warehouse

Prinos, Scott T.

2016-01-01

Florida's communities are largely dependent on freshwater from groundwater aquifers. Existing saltwater in the aquifers, or seawater that intrudes parts of the aquifers that were fresh, can make the water unusable without additional processing. The quality of Florida's saltwater intrusion monitoring networks varies. In Miami-Dade and Broward Counties, for example, there is a well-designed network with recently constructed short open-interval monitoring wells that bracket the saltwater interface in the Biscayne aquifer. Geochemical analyses of water samples from the network help scientists evaluate pathways of saltwater intrusion and movement of the saltwater interface. Geophysical measurements, collected in these counties, aid the mapping of the saltwater interface and the design of monitoring networks. In comparison, deficiencies in the Collier County monitoring network include the positioning of monitoring wells, reliance on wells with long open intervals that when sampled might provide questionable results, and the inability of existing analyses to differentiate between multiple pathways of saltwater intrusion. A state-wide saltwater intrusion monitoring network is being planned; the planned network could improve saltwater intrusion monitoring by adopting the applicable strategies of the networks of Miami-Dade and Broward Counties, and by addressing deficiencies such as those described for the Collier County network.

Optimization of water-level monitoring networks in the eastern Snake River Plain aquifer using a kriging-based genetic algorithm method

USGS Publications Warehouse

Fisher, Jason C.

2013-01-01

Long-term groundwater monitoring networks can provide essential information for the planning and management of water resources. Budget constraints in water resource management agencies often mean a reduction in the number of observation wells included in a monitoring network. A network design tool, distributed as an R package, was developed to determine which wells to exclude from a monitoring network because they add little or no beneficial information. A kriging-based genetic algorithm method was used to optimize the monitoring network. The algorithm was used to find the set of wells whose removal leads to the smallest increase in the weighted sum of the (1) mean standard error at all nodes in the kriging grid where the water table is estimated, (2) root-mean-squared-error between the measured and estimated water-level elevation at the removed sites, (3) mean standard deviation of measurements across time at the removed sites, and (4) mean measurement error of wells in the reduced network. The solution to the optimization problem (the best wells to retain in the monitoring network) depends on the total number of wells removed; this number is a management decision. The network design tool was applied to optimize two observation well networks monitoring the water table of the eastern Snake River Plain aquifer, Idaho; these networks include the 2008 Federal-State Cooperative water-level monitoring network (Co-op network) with 166 observation wells, and the 2008 U.S. Geological Survey-Idaho National Laboratory water-level monitoring network (USGS-INL network) with 171 wells. Each water-level monitoring network was optimized five times: by removing (1) 10, (2) 20, (3) 40, (4) 60, and (5) 80 observation wells from the original network. An examination of the trade-offs associated with changes in the number of wells to remove indicates that 20 wells can be removed from the Co-op network with a relatively small degradation of the estimated water table map, and 40 wells can be removed from the USGS-INL network before the water table map degradation accelerates. The optimal network designs indicate the robustness of the network design tool. Observation wells were removed from high well-density areas of the network while retaining the spatial pattern of the existing water-table map.

Techno-Economic Analysis of FiWi Access Networks Based on 802.11ac WLAN and NG-PON2 Networks

NASA Astrophysics Data System (ADS)

Breskovic, Damir; Begusic, Dinko

2017-05-01

In this article, techno-economic analysis of a fiber-wireless access network is presented. With high bandwidth capacity of the gigabit passive optical network and with cost-effectiveness of very high throughput 802.11ac wireless local area networks that enable user mobility in the wireless segment, fiber-wireless access networks can be considered as an alternative to the fiber-to-the-home architecture for next generation access networks. Analysis based on the proposed scenario here, shows that a fiber-wireless access network is a more cost-effective solution in densely populated areas, but with some introduced improvements, even other geotypes can be considered as a commercially-viable solution.

Data analysis of a dense GPS network operated during the ESCOMPTE campaign: first results

NASA Astrophysics Data System (ADS)

Walpersdorf, A.; Bock, O.; Doerflinger, E.; Masson, F.; van Baelen, J.; Somieski, A.; Bürki, B.

The experiment GPS/H 2O involving 17 GPS receivers has been operated for two weeks in June 2001 in a dense network around Marseille. This project was integrated into the ESCOMPTE campaign. This paper will focus on the GPS analysis in preparation of the tomographic inversion of GPS slant delays. As first results, GPS tropospheric parameters zenith delays and horizontal gradients have been extracted. For a first visualization of the humidity field overlying the network, zenith delays have been transformed into precipitable water. Successive humidity fields are presented for a period of sudden drop in humidity, indicating some spatial resolution in the small network. The time series of horizontal gradients evaluated at individual sites are compared to correlated zenith delay variations over the whole network (horizontal gradient of zenith delays), showing that in the small size network horizontal atmospheric structure is reflected by both types of parameters. To compare these two quantities, scaling of zenith delays due to different station altitudes was necessary. In this way, a GPS internal validation of the individual gradients by comparison with the horizontal gradient of zenith delays has been established. Differential features along transects across the network indicate a good spatial resolution of tropospheric phenomena, encouraging for the further tomographic exploitation of the data. Moreover, individual and zenith delay gradients weight differently atmospheric horizontal gradients occurring at different heights. This different sensitivity has been used for a first identification of a vertical atmospheric structure from GPS tropospheric delays, by observing an inclined frontal zone crossing the network.

Monitoring crop and vegetation condition using the fused dense time-series landsat-like imagery

USDA-ARS?s Scientific Manuscript database

Since the launch of the first Landsat satellite in the early 1970s, Landsat has been widely used in many applications such as land cover and land use change monitoring, crop yield estimation, forest fire detection, and global ecosystem carbon cycle studies. Medium resolution sensors like Landsat hav...

High resolution remote sensing of densely urbanised regions: a case study of Hong Kong.

PubMed

Nichol, Janet E; Wong, Man Sing

2009-01-01

Data on the urban environment such as climate or air quality is usually collected at a few point monitoring stations distributed over a city. However, the synoptic viewpoint of satellites where a whole city is visible on a single image permits the collection of spatially comprehensive data at city-wide scale. In spite of rapid developments in remote sensing systems, deficiencies in image resolution and algorithm development still exist for applications such as air quality monitoring and urban heat island analysis. This paper describes state-of-the-art techniques for enhancing and maximising the spatial detail available from satellite images, and demonstrates their applications to the densely urbanised environment of Hong Kong. An Emissivity Modulation technique for spatial enhancement of thermal satellite images permits modelling of urban microclimate in combination with other urban structural parameters at local scale. For air quality monitoring, a Minimum Reflectance Technique (MRT) has been developed for MODIS 500 m images. The techniques described can promote the routine utilization of remotely sensed images for environmental monitoring in cities of the 21(st) century.

High Resolution Remote Sensing of Densely Urbanised Regions: a Case Study of Hong Kong

PubMed Central

Nichol, Janet E.; Wong, Man Sing

2009-01-01

Data on the urban environment such as climate or air quality is usually collected at a few point monitoring stations distributed over a city. However, the synoptic viewpoint of satellites where a whole city is visible on a single image permits the collection of spatially comprehensive data at city-wide scale. In spite of rapid developments in remote sensing systems, deficiencies in image resolution and algorithm development still exist for applications such as air quality monitoring and urban heat island analysis. This paper describes state-of-the-art techniques for enhancing and maximising the spatial detail available from satellite images, and demonstrates their applications to the densely urbanised environment of Hong Kong. An Emissivity Modulation technique for spatial enhancement of thermal satellite images permits modelling of urban microclimate in combination with other urban structural parameters at local scale. For air quality monitoring, a Minimum Reflectance Technique (MRT) has been developed for MODIS 500 m images. The techniques described can promote the routine utilization of remotely sensed images for environmental monitoring in cities of the 21st century. PMID:22408549

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 5 2011-07-01 2011-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...

40 CFR 58.10 - Annual monitoring network plan and periodic network assessment.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false Annual monitoring network plan and periodic network assessment. 58.10 Section 58.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.10 Annual...

Improving rainfall estimation from commercial microwave links using METEOSAT SEVIRI cloud cover information

NASA Astrophysics Data System (ADS)

Boose, Yvonne; Doumounia, Ali; Chwala, Christian; Moumouni, Sawadogo; Zougmoré, François; Kunstmann, Harald

2017-04-01

The number of rain gauges is declining worldwide. A recent promising method for alternative precipitation measurements is to derive rain rates from the attenuation of the microwave signal between remote antennas of mobile phone base stations, so called commercial microwave links (CMLs). In European countries, such as Germany, the CML technique can be used as a complementary method to the existing gauge and radar networks improving their products, for example, in mountainous terrain and urban areas. In West African countries, where a dense gauge or radar network is absent, the number of mobile phone users is rapidly increasing and so are the CML networks. Hence, the CML-derived precipitation measurements have high potential for applications such as flood warning and support of agricultural planning in this region. For typical CML bandwidths (10-40 GHz), the relationship of attenuation to rain rate is quasi-linear. However, also humidity, wet antennas or electronic noise can lead to signal interference. To distinguish these fluctuations from actual attenuation due to rain, a temporal wet (rain event occurred)/ dry (no rain event) classification is usually necessary. In dense CML networks this is possible by correlating neighboring CML time series. Another option is to use the correlation between signal time series of different frequencies or bidirectional signals. The CML network in rural areas is typically not dense enough for correlation analysis and often only one polarization and one frequency are available along a CML. In this work we therefore use cloud cover information derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer onboard the geostationary satellite METEOSAT for a wet (pixels along link are cloud covered)/ dry (no cloud along link) classification. We compare results for CMLs in Burkina Faso and Germany, which differ meteorologically (rain rate and duration, droplet size distributions) and technically (CML frequencies, lengths, signal level) and use rain gauge data as ground truth for validation.

Strategy of thunderstorm measurement with super dense ground-based observation network

NASA Astrophysics Data System (ADS)

Takahashi, Y.; Sato, M.

2014-12-01

It's not easy to understand the inside structure and developing process of thunderstorm only with existing meteorological instruments since its horizontal extent of the storm cell is sometimes smaller than an order of 10 km while one of the densest ground network in Japan, AMEDAS, consists of sites located every 17 km in average and the resolution of meteorological radar is 1-2 km in general. Even the X-band radar realizes the resolution of 250 m or larger. Here we suggest a new super dense observation network with simple and low cost sensors that can be used for measurement both of raindrop and vertical electric field change caused by cloud-to-ground lightning discharge. This sensor consists of two aluminum plates with a diameter of 10-20 cm. We carried out an observation campaign in summer of 2013 in the foothills of Mt. Yastugatake, Yamanashi and Nagano prefectures in Japan, installing 6 plate-type sensors at a distance of about 4 km. Horizontal location, height and charge amount of each lightning discharge are estimated successfully based on the information of electric field changes at several observing sites. Moreover, it was found that the thunderstorm has a very narrow structure well smaller than 300 m that cannot be measured by any other ways, counting the positive and negative pulses caused by attachment of raindrop to the sensor plate, respectively. We plan to construct a new super dense observation network in the north Kanto region, Japan, where the lightning activity is most prominent in summer Japan, distributing more than several tens of sensors at every 4 km or shorter, such as an order of 100 m at minimum. This kind of new type network will reveal the unknown fine structures of thunderstorms and open the door for constructing real time alert system of torrential rainfall and lightning stroke especially in the city area.

Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products

NASA Astrophysics Data System (ADS)

Tang, Guoqiang; Behrangi, Ali; Long, Di; Li, Changming; Hong, Yang

2018-04-01

Rain gauge observations are commonly used to evaluate the quality of satellite precipitation products. However, the inherent difference between point-scale gauge measurements and areal satellite precipitation, i.e. a point of space in time accumulation v.s. a snapshot of time in space aggregation, has an important effect on the accuracy and precision of qualitative and quantitative evaluation results. This study aims to quantify the uncertainty caused by various combinations of spatiotemporal scales (0.1°-0.8° and 1-24 h) of gauge network designs in the densely gauged and relatively flat Ganjiang River basin, South China, in order to evaluate the state-of-the-art satellite precipitation, the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG). For comparison with the dense gauge network serving as "ground truth", 500 sparse gauge networks are generated through random combinations of gauge numbers at each set of spatiotemporal scales. Results show that all sparse gauge networks persistently underestimate the performance of IMERG according to most metrics. However, the probability of detection is overestimated because hit and miss events are more likely fewer than the reference numbers derived from dense gauge networks. A nonlinear error function of spatiotemporal scales and the number of gauges in each grid pixel is developed to estimate the errors of using gauges to evaluate satellite precipitation. Coefficients of determination of the fitting are above 0.9 for most metrics. The error function can also be used to estimate the required minimum number of gauges in each grid pixel to meet a predefined error level. This study suggests that the actual quality of satellite precipitation products could be better than conventionally evaluated or expected, and hopefully enables non-subject-matter-expert researchers to have better understanding of the explicit uncertainties when using point-scale gauge observations to evaluate areal products.

Community structure and scale-free collections of Erdős-Rényi graphs.

PubMed

Seshadhri, C; Kolda, Tamara G; Pinar, Ali

2012-05-01

Community structure plays a significant role in the analysis of social networks and similar graphs, yet this structure is little understood and not well captured by most models. We formally define a community to be a subgraph that is internally highly connected and has no deeper substructure. We use tools of combinatorics to show that any such community must contain a dense Erdős-Rényi (ER) subgraph. Based on mathematical arguments, we hypothesize that any graph with a heavy-tailed degree distribution and community structure must contain a scale-free collection of dense ER subgraphs. These theoretical observations corroborate well with empirical evidence. From this, we propose the Block Two-Level Erdős-Rényi (BTER) model, and demonstrate that it accurately captures the observable properties of many real-world social networks.

Studies Of Infrasonic Propagation Using Dense Seismic Networks

NASA Astrophysics Data System (ADS)

Hedlin, M. A.; deGroot-Hedlin, C. D.; Drob, D. P.

2011-12-01

Although there are approximately 100 infrasonic arrays worldwide, more than ever before, the station density is still insufficient to provide validation for detailed propagation modeling. Relatively large infrasonic signals can be observed on seismic channels due to coupling at the Earth's surface. Recent research, using data from the 70-km spaced 400-station USArray and other seismic network deployments, has shown the value of dense seismic network data for filling in the gaps between infrasonic arrays. The dense sampling of the infrasonic wavefield has allowed us to observe complete travel-time branches of infrasound and address important research problems in infrasonic propagation. We present our analysis of infrasound created by a series of rocket motor detonations that occurred at the UTTR facility in Utah in 2007. These data were well recorded by the USArray seismometers. We use the precisely located blasts to assess the utility of G2S mesoscale models and methods to synthesize infrasonic propagation. We model the travel times of the branches using a ray-based approach and the complete wavefield using a FDTD algorithm. Although results from both rays and FDTD approaches predict the travel times to within several seconds, only about 40% of signals are predicted using rays largely due to penetration of sound into shadow zones. FDTD predicts some sound penetration into the shadow zone, but the observed shadow zones, as defined by the seismic data, have considerably narrower spatial extent than either method predicts, perhaps due to un-modeled small-scale structure in the atmosphere.

Deployment of a Testbed in a Brazilian Research Network using IPv6 and Optical Access Technologies

NASA Astrophysics Data System (ADS)

Martins, Luciano; Ferramola Pozzuto, João; Olimpio Tognolli, João; Chaves, Niudomar Siqueira De A.; Reggiani, Atilio Eduardo; Hortêncio, Claudio Antonio

2012-04-01

This article presents the implementation of a testbed and the experimental results obtained with it on the Brazilian Experimental Network of the government-sponsored "GIGA Project." The use of IPv6 integrated to current and emerging optical architectures and technologies, such as dense wavelength division multiplexing and 10-gigabit Ethernet on the core and gigabit capable passive optical network and optical distribution network on access, were tested. These protocols, architectures, and optical technologies are promising and part of a brand new worldwide technological scenario that has being fairly adopted in the networks of enterprises and providers of the world.

Star polymers as unit cells for coarse-graining cross-linked networks

NASA Astrophysics Data System (ADS)

Molotilin, Taras Y.; Maduar, Salim R.; Vinogradova, Olga I.

2018-03-01

Reducing the complexity of cross-linked polymer networks by preserving their main macroscale properties is key to understanding them, and a crucial issue is to relate individual properties of the polymer constituents to those of the reduced network. Here we study polymer networks in a good solvent, by considering star polymers as their unit elements, and first quantify the interaction between their centers of masses. We then reduce the complexity of a network by replacing sets of its bridged star polymers by equivalent effective soft particles with dense cores. Our coarse graining allows us to approximate complex polymer networks by much simpler ones, keeping their relevant mechanical properties, as illustrated in computer experiments.

Design of a ground-water-quality monitoring network for the Salinas River basin, California

USGS Publications Warehouse

Showalter, P.K.; Akers, J.P.; Swain, L.A.

1984-01-01

A regional ground-water quality monitoring network for the entire Salinas River drainage basin was designed to meet the needs of the California State Water Resources Control Board. The project included phase 1--identifying monitoring networks that exist in the region; phase 2--collecting information about the wells in each network; and phase 3--studying the factors--such as geology, land use, hydrology, and geohydrology--that influence the ground-water quality, and designing a regional network. This report is the major product of phase 3. Based on the authors ' understanding of the ground-water-quality monitoring system and input from local offices, an ideal network was designed. The proposed network includes 317 wells and 8 stream-gaging stations. Because limited funds are available to implement the monitoring network, the proposed network is designed to correspond to the ideal network insofar as practicable, and is composed mainly of 214 wells that are already being monitored by a local agency. In areas where network wells are not available, arrangements will be made to add wells to local networks. The data collected by this network will be used to assess the ground-water quality of the entire Salinas River drainage basin. After 2 years of data are collected, the network will be evaluated to test whether it is meeting the network objectives. Subsequent network evaluations will be done very 5 years. (USGS)

Progress and lessons learned from water-quality monitoring networks

USGS Publications Warehouse

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

Geostatistics-based groundwater-level monitoring network design and its application to the Upper Floridan aquifer, USA.

PubMed

Bhat, Shirish; Motz, Louis H; Pathak, Chandra; Kuebler, Laura

2015-01-01

A geostatistical method was applied to optimize an existing groundwater-level monitoring network in the Upper Floridan aquifer for the South Florida Water Management District in the southeastern United States. Analyses were performed to determine suitable numbers and locations of monitoring wells that will provide equivalent or better quality groundwater-level data compared to an existing monitoring network. Ambient, unadjusted groundwater heads were expressed as salinity-adjusted heads based on the density of freshwater, well screen elevations, and temperature-dependent saline groundwater density. The optimization of the numbers and locations of monitoring wells is based on a pre-defined groundwater-level prediction error. The newly developed network combines an existing network with the addition of new wells that will result in a spatial distribution of groundwater monitoring wells that better defines the regional potentiometric surface of the Upper Floridan aquifer in the study area. The network yields groundwater-level predictions that differ significantly from those produced using the existing network. The newly designed network will reduce the mean prediction standard error by 43% compared to the existing network. The adoption of a hexagonal grid network for the South Florida Water Management District is recommended to achieve both a uniform level of information about groundwater levels and the minimum required accuracy. It is customary to install more monitoring wells for observing groundwater levels and groundwater quality as groundwater development progresses. However, budget constraints often force water managers to implement cost-effective monitoring networks. In this regard, this study provides guidelines to water managers concerned with groundwater planning and monitoring.

Seismicity and Crustal Anisotropy Beneath the Western Segment of the North Anatolian Fault: Results from a Dense Seismic Array

NASA Astrophysics Data System (ADS)

Turkelli, N.; Teoman, U.; Altuncu Poyraz, S.; Cambaz, D.; Mutlu, A. K.; Kahraman, M.; Houseman, G. A.; Rost, S.; Thompson, D. A.; Cornwell, D. G.; Utkucu, M.; Gülen, L.

2013-12-01

The North Anatolian Fault (NAF) is one of the major strike slip fault systems on Earth comparable to San Andreas Fault in some ways. Devastating earthquakes have occurred along this system causing major damage and casualties. In order to comprehensively investigate the shallow and deep crustal structure beneath the western segment of NAF, a temporary dense seismic network for North Anatolia (DANA) consisting of 73 broadband sensors was deployed in early May 2012 surrounding a rectangular grid of by 70 km and a nominal station spacing of 7 km with the aim of further enhancing the detection capability of this dense seismic array. This joint project involves researchers from University of Leeds, UK, Bogazici University Kandilli Observatory and Earthquake Research Institute (KOERI), and University of Sakarya and primarily focuses on upper crustal studies such as earthquake locations (especially micro-seismic activity), receiver functions, moment tensor inversions, shear wave splitting, and ambient noise correlations. To begin with, we obtained the hypocenter locations of local earthquakes that occured within the DANA network. The dense 2-D grid geometry considerably enhanced the earthquake detection capability which allowed us to precisely locate events with local magnitudes (Ml) less than 1.0. Accurate earthquake locations will eventually lead to high resolution images of the upper crustal structure beneath the northern and southern branches of NAF in Sakarya region. In order to put additional constraints on the active tectonics of the western part of NAF, we also determined fault plane solutions using Regional Moment Tensor Inversion (RMT) and P wave first motion methods. For the analysis of high quality fault plane solutions, data from KOERI and the DANA project were merged. Furthermore, with the aim of providing insights on crustal anisotropy, shear wave splitting parameters such as lag time and fast polarization direction were obtained for local events recorded within the seismic network with magnitudes larger than 2.5.

Optical Network Virtualisation Using Multitechnology Monitoring and SDN-Enabled Optical Transceiver

NASA Astrophysics Data System (ADS)

Ou, Yanni; Davis, Matthew; Aguado, Alejandro; Meng, Fanchao; Nejabati, Reza; Simeonidou, Dimitra

2018-05-01

We introduce the real-time multi-technology transport layer monitoring to facilitate the coordinated virtualisation of optical and Ethernet networks supported by optical virtualise-able transceivers (V-BVT). A monitoring and network resource configuration scheme is proposed to include the hardware monitoring in both Ethernet and Optical layers. The scheme depicts the data and control interactions among multiple network layers under the software defined network (SDN) background, as well as the application that analyses the monitored data obtained from the database. We also present a re-configuration algorithm to adaptively modify the composition of virtual optical networks based on two criteria. The proposed monitoring scheme is experimentally demonstrated with OpenFlow (OF) extensions for a holistic (re-)configuration across both layers in Ethernet switches and V-BVTs.

Availability Issues in Wireless Visual Sensor Networks

PubMed Central

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

2014-01-01

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

A decade of passive seismic monitoring experiments with local networks in four Italian regions

NASA Astrophysics Data System (ADS)

Chiaraluce, L.; Valoroso, L.; Anselmi, M.; Bagh, S.; Chiarabba, C.

2009-10-01

We report on four seismic monitoring experiments that in the past ten years we carried out with dense local networks in seismically active Italian areas where for at least a year, tens of three component seismic stations were set up to record microseismicity. The areas observed are Alpago-Cansiglio, located in the Venetian Alps, Città di Castello in the Northern Apennines, Marsica in the Central Apennines and Val d'Agri located in the Southern Apennines. We produced homogeneous catalogues regarding earthquake locations and local magnitudes to investigate seismicity patterns during an inter-seismic period. The four regions are characterised by different kinematics, strain rates and historical/recent seismicity. We investigate earthquake distribution in space, time and size obtaining reference seismic rates and parameters of the Gutenberg and Richter law. We declustered the catalogues to look for coherent signs in the background seismic activity. Despite a difference in the catalogues magnitudes of completeness due both to the diverse detection threshold of the local networks and different seismic release, we detect and observe two common main behaviours: a) The Alpago-Cansiglio and Marsica regions are characterised by a relatively lower rate of seismic release associated to the episodic occurrence of seismic sequences with the largest event being 3 < ML < 4. In these areas the seismicity is not localised around the main faults. b) The Città di Castello and Val d'Agri regions have a relatively high rate of seismicity release almost continuously with time, and the increase in earthquake production is not clearly related to seismic sequences. In these areas the seismicity nucleates around defined fault systems and is usually lower than ML < 3. We suggest that the presence of over-pressured fluids in the Città di Castello and Val d'Agri uppermost crustal volume may favour and mould the higher rate of microseismic release.

Effective contaminant detection networks in uncertain groundwater flow fields.

PubMed

Hudak, P F

2001-01-01

A mass transport simulation model tested seven contaminant detection-monitoring networks under a 40 degrees range of groundwater flow directions. Each monitoring network contained five wells located 40 m from a rectangular landfill. The 40-m distance (lag) was measured in different directions, depending upon the strategy used to design a particular monitoring network. Lagging the wells parallel to the central flow path was more effective than alternative design strategies. Other strategies allowed higher percentages of leaks to migrate between monitoring wells. Results of this study suggest that centrally lagged groundwater monitoring networks perform most effectively in uncertain groundwater-flow fields.

Comparison of unmanned aircraft systems (UAS) to LiDAR for streambank erosion measurement at the site-specific and river network scales

NASA Astrophysics Data System (ADS)

Hamshaw, S. D.; Dewoolkar, M. M.; Rizzo, D.; ONeil-Dunne, J.; Frolik, J.

2016-12-01

Measurement of rates and extent of streambank erosion along river corridors is an important component of many catchment studies and necessary for engineering projects such as river restoration, hazard assessment, and total maximum daily load (TMDL) development. A variety of methods have been developed to quantify streambank erosion, including bank pins, ground surveys, photogrammetry, LiDAR, and analytical models. However, these methods are not only resource intensive, but many are feasible and appropriate only for site-specific studies and not practical for erosion estimates at larger scales. Recent advancements in unmanned aircraft systems (UAS) and photogrammetry software provide capabilities for more rapid and economical quantification of streambank erosion and deposition at multiple scales (from site-specific to river network). At the site-specific scale, the capability of UAS to quantify streambank erosion was compared to terrestrial laser scanning (TLS) and RTK-GPS ground survey and assessed at seven streambank monitoring sites in central Vermont. Across all sites, the UAS-derived bank topography had mean errors of 0.21 m compared to TLS and GPS data. Highest accuracies were achieved in early spring conditions where mean errors approached 10 cm. The cross sectional area of bank erosion at a typical, vegetated streambank site was found to be reliably calculated within 10% of actual for erosion areas greater than 3.5 m2. At the river network-level scale, 20 km of river corridor along the New Haven, Winooski, and Mad Rivers was flown on multiple dates with UAS and used to generate digital elevation models (DEMs) that were then compared for change detection analysis. Airborne LiDAR data collected prior to UAS surveys was also compared to UAS data to determine multi-year rates of bank erosion. UAS-based photogrammetry for generation of fine scale topographic data shows promise for the monitoring of streambank erosion both at the individual site scale and river-network scale in areas that are not densely covered with vegetation year-round.

Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.

PubMed

Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon

2018-04-03

Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

Two-dimensional plasmons in lateral carbon nanotube network structures and their effect on the terahertz radiation detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryzhii, V.; Institute of Ultra High Frequency Semiconductor Electronics of RAS, Moscow 117105; Center for Photonics and Infrared Engineering, Bauman Moscow State Technical University, Moscow 111005

2016-07-28

We consider the carrier transport and plasmonic phenomena in the lateral carbon nanotube (CNT) networks forming the device channel with asymmetric electrodes. One electrode is the Ohmic contact to the CNT network and the other contact is the Schottky contact. These structures can serve as detectors of the terahertz (THz) radiation. We develop the device model for collective response of the lateral CNT networks which comprise a mixture of randomly oriented semiconductor CNTs (s-CNTs) and quasi-metal CNTs (m-CNTs). The proposed model includes the concept of the collective two-dimensional (2D) plasmons in relatively dense networks of randomly oriented CNTs (CNT “felt”)more » and predicts the detector responsivity spectral characteristics exhibiting sharp resonant peaks at the signal frequencies corresponding to the 2D plasmonic resonances. The detection mechanism is the rectification of the ac current due the nonlinearity of the Schottky contact current-voltage characteristics under the conditions of a strong enhancement of the potential drop at this contact associated with the plasmon excitation. The detector responsivity depends on the fractions of the s- and m-CNTs. The burning of the near-contact regions of the m-CNTs or destruction of these CNTs leads to a marked increase in the responsivity in agreement with our experimental data. The resonant THz detectors with sufficiently dense lateral CNT networks can compete and surpass other THz detectors using plasmonic effects at room temperatures.« less

A scrutiny of heterogeneity at the TCE Source Area BioREmediation (SABRE) test site

NASA Astrophysics Data System (ADS)

Rivett, M.; Wealthall, G. P.; Mcmillan, L. A.; Zeeb, P.

2015-12-01

A scrutiny of heterogeneity at the UK's Source Area BioREmediation (SABRE) test site is presented to better understand how spatial heterogeneity in subsurface properties and process occurrence may constrain performance of enhanced in-situ bioremediation (EISB). The industrial site contained a 25 to 45 year old trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) that was exceptionally well monitored via a network of multilevel samplers and high resolution core sampling. Moreover, monitoring was conducted within a 3-sided sheet-pile cell that allowed a controlled streamtube of flow to be drawn through the source zone by an extraction well. We primarily focus on the longitudinal transect of monitoring along the length of the cell that provides a 200 groundwater point sample slice along the streamtube of flow through the DNAPL source zone. TCE dechlorination is shown to be significant throughout the cell domain, but spatially heterogeneous in occurrence and progress of dechlorination to lesser chlorinated ethenes - it is this heterogeneity in dechlorination that we primarily scrutinise. We illustrate the diagnostic use of the relative occurrence of TCE parent and daughter compounds to confirm: dechlorination in close proximity to DNAPL and enhanced during the bioremediation; persistent layers of DNAPL into which gradients of dechlorination products are evident; fast flowpaths through the source zone where dechlorination is less evident; and, the importance of underpinning flow regime understanding on EISB performance. Still, even with such spatial detail, there remains uncertainty over the dataset interpretation. These includes poor closure of mass balance along the cell length for the multilevel sampler based monitoring and points to needs to still understand lateral flows (even in the constrained cell), even greater spatial resolution of point monitoring and potentially, not easily proven, ethene degradation loss.

Two problems in multiphase biological flows: Blood flow and particulate transport in microvascular network, and pseudopod-driven motility of amoeboid cells

NASA Astrophysics Data System (ADS)

Bagchi, Prosenjit

2016-11-01

In this talk, two problems in multiphase biological flows will be discussed. The first is the direct numerical simulation of whole blood and drug particulates in microvascular networks. Blood in microcirculation behaves as a dense suspension of heterogeneous cells. The erythrocytes are extremely deformable, while inactivated platelets and leukocytes are nearly rigid. A significant progress has been made in recent years in modeling blood as a dense cellular suspension. However, many of these studies considered the blood flow in simple geometry, e.g., straight tubes of uniform cross-section. In contrast, the architecture of a microvascular network is very complex with bifurcating, merging and winding vessels, posing a further challenge to numerical modeling. We have developed an immersed-boundary-based method that can consider blood cell flow in physiologically realistic and complex microvascular network. In addition to addressing many physiological issues related to network hemodynamics, this tool can be used to optimize the transport properties of drug particulates for effective organ-specific delivery. Our second problem is pseudopod-driven motility as often observed in metastatic cancer cells and other amoeboid cells. We have developed a multiscale hydrodynamic model to simulate such motility. We study the effect of cell stiffness on motility as the former has been considered as a biomarker for metastatic potential. Funded by the National Science Foundation.

Community Seismic Network (CSN)

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Heaton, T. H.; Kohler, M. D.; Cheng, M.; Guy, R.; Chandy, M.; Krause, A.; Bunn, J.; Olson, M.; Faulkner, M.

2011-12-01

The CSN is a network of low-cost accelerometers deployed in the Pasadena, CA region. It is a prototype network with the goal of demonstrating the importance of dense measurements in determining the rapid lateral variations in ground motion due to earthquakes. The main product of the CSN is a map of peak ground produced within seconds of significant local earthquakes that can be used as a proxy for damage. Examples of this are shown using data from a temporary network in Long Beach, CA. Dense measurements in buildings are also being used to determine the state of health of structures. In addition to fixed sensors, portable sensors such as smart phones are also used in the network. The CSN has necessitated several changes in the standard design of a seismic network. The first is that the data collection and processing is done in the "cloud" (Google cloud in this case) for robustness and the ability to handle large impulsive loads (earthquakes). Second, the database is highly de-normalized (i.e. station locations are part of waveform and event-detection meta data) because of the mobile nature of the sensors. Third, since the sensors are hosted and/or owned by individuals, the privacy of the data is very important. The location of fixed sensors is displayed on maps as sensor counts in block-wide cells, and mobile sensors are shown in a similar way, with the additional requirement to inhibit tracking that at least two must be present in a particular cell before any are shown. The raw waveform data are only released to users outside of the network after a felt earthquake.

A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.

PubMed

Naveros, Francisco; Luque, Niceto R; Garrido, Jesús A; Carrillo, Richard R; Anguita, Mancia; Ros, Eduardo

2015-07-01

Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural networks. Nevertheless, they still have drawbacks when simulating large-scale systems. Conversely, event-driven simulation methods in CPUs and time-driven simulation methods in graphic processing units (GPUs) can outperform CPU time-driven methods under certain conditions. With this performance improvement in mind, we have developed an event-and-time-driven spiking neural network simulator suitable for a hybrid CPU-GPU platform. Our neural simulator is able to efficiently simulate bio-inspired spiking neural networks consisting of different neural models, which can be distributed heterogeneously in both small layers and large layers or subsystems. For the sake of efficiency, the low-activity parts of the neural network can be simulated in CPU using event-driven methods while the high-activity subsystems can be simulated in either CPU (a few neurons) or GPU (thousands or millions of neurons) using time-driven methods. In this brief, we have undertaken a comparative study of these different simulation methods. For benchmarking the different simulation methods and platforms, we have used a cerebellar-inspired neural-network model consisting of a very dense granular layer and a Purkinje layer with a smaller number of cells (according to biological ratios). Thus, this cerebellar-like network includes a dense diverging neural layer (increasing the dimensionality of its internal representation and sparse coding) and a converging neural layer (integration) similar to many other biologically inspired and also artificial neural networks.

ASSESSING THE COMPARABILITY OF AMMONIUM, NITRATE AND SULFATE CONCENTRATIONS MEASURED BY THREE AIR QUALITY MONITORING NETWORKS

EPA Science Inventory

Airborne fine particulate matter across the United States is monitored by different networks, the three prevalent ones presently being the Clean Air Status and Trend Network (CASTNet), the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE) and the Speciati...

Dense Nonaqueous Phase Liquids

EPA Pesticide Factsheets

This issue paper is a literature evaluation focusing on DNAPLs and provides an overview from a conceptual fate and transport point of view of DNAPL phase distribution, monitoring, site characterization, remediation, and modeling.

Association of childhood abuse with homeless women's social networks.

PubMed

Green, Harold D; Tucker, Joan S; Wenzel, Suzanne L; Golinelli, Daniela; Kennedy, David P; Ryan, Gery W; Zhou, Annie J

2012-01-01

Childhood abuse has been linked to negative sequelae for women later in life including drug and alcohol use and violence as victim or perpetrator and may also affect the development of women's social networks. Childhood abuse is prevalent among at-risk populations of women (such as the homeless) and thus may have a stronger impact on their social networks. We conducted a study to: (a) develop a typology of sheltered homeless women's social networks; (b) determine whether childhood abuse was associated with the social networks of sheltered homeless women; and (c) determine whether those associations remained after accounting for past-year substance abuse and recent intimate partner abuse. A probability sample of 428 homeless women from temporary shelter settings in Los Angeles County completed a personal network survey that provided respondent information as well as information about their network members' demographics and level of interaction with each other. Cluster analyses identified groups of women who shared specific social network characteristics. Multinomial logistic regressions revealed variables associated with group membership. We identified three groups of women with differing social network characteristics: low-risk networks, densely connected risky networks (dense, risky), and sparsely connected risky networks (sparse, risky). Multinomial logistic regressions indicated that membership in the sparse, risky network group, when compared to the low-risk group, was associated with history of childhood physical abuse (but not sexual or emotional abuse). Recent drug abuse was associated with membership in both risky network groups; however, the association of childhood physical abuse with sparse, risky network group membership remained. Although these findings support theories proposing that the experience of childhood abuse can shape women's social networks, they suggest that it may be childhood physical abuse that has the most impact among homeless women. The effects of childhood physical abuse should be more actively investigated in clinical settings, especially those frequented by homeless women, particularly with respect to the formation of social networks in social contexts that may expose these women to greater risks. Copyright © 2012. Published by Elsevier Ltd.

Comparison of Calibration Techniques for Low-Cost Air Quality Monitoring

NASA Astrophysics Data System (ADS)

Malings, C.; Ramachandran, S.; Tanzer, R.; Kumar, S. P. N.; Hauryliuk, A.; Zimmerman, N.; Presto, A. A.

2017-12-01

Assessing the intra-city spatial distribution and temporal variability of air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if high-quality but high-cost monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) sensor package has been developed at the Center for Atmospheric Particle Studies of Carnegie Mellon University, in collaboration with SenSevere LLC. This self-contained unit can measure up to five gases out of CO, SO2, NO, NO2, O3, VOCs, and CO2, along with temperature and relative humidity. Responses of individual gas sensors can vary greatly even when exposed to the same ambient conditions. Those of VOC sensors in particular were observed to vary by a factor-of-8, which suggests that each sensor requires its own calibration model. To this end, we apply and compare two different calibration methods to data collected by RAMP sensors collocated with a reference monitor station. The first method, random forest (RF) modeling, is a rule-based method which maps sensor responses to pollutant concentrations by implementing a trained sequence of decision rules. RF modeling has previously been used for other RAMP gas sensors by the group, and has produced precise calibrated measurements. However, RF models can only predict pollutant concentrations within the range observed in the training data collected during the collocation period. The second method, Gaussian process (GP) modeling, is a probabilistic Bayesian technique whereby broad prior estimates of pollutant concentrations are updated using sensor responses to generate more refined posterior predictions, as well as allowing predictions beyond the range of the training data. The accuracy and precision of these techniques are assessed and compared on VOC data collected during the summer of 2017 in Pittsburgh, PA. By combining pollutant data gathered by each RAMP sensor and applying appropriate calibration techniques, the potentially noisy or biased responses of individual sensors can be mapped to pollutant concentration values which are comparable to those of reference instruments.

Scalable Probabilistic Inference for Global Seismic Monitoring

NASA Astrophysics Data System (ADS)

Arora, N. S.; Dear, T.; Russell, S.

2011-12-01

We describe a probabilistic generative model for seismic events, their transmission through the earth, and their detection (or mis-detection) at seismic stations. We also describe an inference algorithm that constructs the most probable event bulletin explaining the observed set of detections. The model and inference are called NET-VISA (network processing vertically integrated seismic analysis) and is designed to replace the current automated network processing at the IDC, the SEL3 bulletin. Our results (attached table) demonstrate that NET-VISA significantly outperforms SEL3 by reducing the missed events from 30.3% down to 12.5%. The difference is even more dramatic for smaller magnitude events. NET-VISA has no difficulty in locating nuclear explosions as well. The attached figure demonstrates the location predicted by NET-VISA versus other bulletins for the second DPRK event. Further evaluation on dense regional networks demonstrates that NET-VISA finds many events missed in the LEB bulletin, which is produced by the human analysts. Large aftershock sequences, as produced by the 2004 December Sumatra earthquake and the 2011 March Tohoku earthquake, can pose a significant load for automated processing, often delaying the IDC bulletins by weeks or months. Indeed these sequences can overload the serial NET-VISA inference as well. We describe an enhancement to NET-VISA to make it multi-threaded, and hence take full advantage of the processing power of multi-core and -cpu machines. Our experiments show that the new inference algorithm is able to achieve 80% efficiency in parallel speedup.

Far-Field Effects of Large Earthquakes on South Florida's Confined Aquifer

NASA Astrophysics Data System (ADS)

Voss, N. K.; Wdowinski, S.

2012-12-01

The similarity between a seismometer and a well hydraulic head record during the passage of a seismic wave has long been documented. This is true even at large distances from earthquake epicenters. South Florida lacks a dense seismic array but does contain a comparably dense network of monitoring wells. The large spatial distribution of deep monitoring wells in South Florida provides an opportunity to study the variance of aquifer response to the passage of seismic waves. We conducted a preliminary study of hydraulic head data, provided by the South Florida Water Management District, from 9 deep wells in South Florida's confined Floridian Aquifer in response to 27 main shock events (January 2010- April 2012) with magnitude 6.9 or greater. Coseismic hydraulic head response was observed in 7 of the 27 events. In order to determine what governs aquifer response to seismic events, earthquake parameters were compared for the 7 positive events. Seismic energy density (SED), an empirical relationship between distance and magnitude, was also used to compare the relative energy between the events at each well site. SED is commonly used as a parameter for establishing thresholds for hydrologic events in the near and intermediate fields. Our analysis yielded a threshold SED for well response in South Florida as 8 x 10-3 J m-3, which is consistent with other studies. Deep earthquakes, with SED above this threshold, did not appear to trigger hydraulic head oscillations. The amplitude of hydraulic head oscillations had no discernable relationship to SED levels. Preliminary results indicate a need for a modification of the SED equation to better accommodate depth in order to be of use in the study of hydrologic response in the far field. We plan to conduct a more comprehensive study incorporating a larger subset (~60) of wells in South Florida in order to further examine the spatial variance of aquifers to the passing of seismic waves as well as better confine the relationship between earthquake depth and aquifer response.

Building a Successful Technology Cluster

EPA Science Inventory

Silicon Valley is the iconic cluster—a dense regional network of companies, universities, research institutions, and other stakeholders involved in a single industry. Many regions have sought to replicate the success of Silicon Valley, which has produced technological innov...

Effect of soil temperature on optical frequency transfer through unidirectional dense-wavelength-division-multiplexing fiber-optic links.

PubMed

Pinkert, T J; Böll, O; Willmann, L; Jansen, G S M; Dijck, E A; Groeneveld, B G H M; Smets, R; Bosveld, F C; Ubachs, W; Jungmann, K; Eikema, K S E; Koelemeij, J C J

2015-02-01

Results of optical frequency transfer over a carrier-grade dense-wavelength-division-multiplexing (DWDM) optical fiber network are presented. The relation between soil temperature changes on a buried optical fiber and frequency changes of an optical carrier through the fiber is modeled. Soil temperatures, measured at various depths by the Royal Netherlands Meteorology Institute (KNMI) are compared with observed frequency variations through this model. A comparison of a nine-day record of optical frequency measurements through the 2×298  km fiber link with soil temperature data shows qualitative agreement. A soil temperature model is used to predict the link stability over longer periods (days-months-years). We show that optical frequency dissemination is sufficiently stable to distribute and compare, e.g., rubidium frequency standards over standard DWDM optical fiber networks using unidirectional fibers.

Statistical approaches used to assess and redesign surface water-quality-monitoring networks.

PubMed

Khalil, B; Ouarda, T B M J

2009-11-01

An up-to-date review of the statistical approaches utilized for the assessment and redesign of surface water quality monitoring (WQM) networks is presented. The main technical aspects of network design are covered in four sections, addressing monitoring objectives, water quality variables, sampling frequency and spatial distribution of sampling locations. This paper discusses various monitoring objectives and related procedures used for the assessment and redesign of long-term surface WQM networks. The appropriateness of each approach for the design, contraction or expansion of monitoring networks is also discussed. For each statistical approach, its advantages and disadvantages are examined from a network design perspective. Possible methods to overcome disadvantages and deficiencies in the statistical approaches that are currently in use are recommended.

Serial Network Flow Monitor

NASA Technical Reports Server (NTRS)

Robinson, Julie A.; Tate-Brown, Judy M.

2009-01-01

Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

Discovering Social Circles in Ego Networks (Author’s Manuscript)

DTIC Science & Technology

2013-01-10

ego-network. We expect that circles are formed by densely-connected sets of alters ( Newman , 2006). However, different circles overlap heavily, i.e...umbrella of community detection (Lancichinetti and Fortunato, 2009a; Schaeffer, 2007; Leskovec et al., 2010; Porter et al., 2009; Newman , 2004). While...MCMC) sampler ( Newman and Barkema, 1999) which efficiently updates node-community memberships by ‘collapsing’ nodes that have common features and

Nonvolatile Ionic Two-Terminal Memory Device

NASA Technical Reports Server (NTRS)

Williams, Roger M.

1990-01-01

Conceptual solid-state memory device nonvolatile and erasable and has only two terminals. Proposed device based on two effects: thermal phase transition and reversible intercalation of ions. Transfer of sodium ions between source of ions and electrical switching element increases or decreases electrical conductance of element, turning switch "on" or "off". Used in digital computers and neural-network computers. In neural networks, many small, densely packed switches function as erasable, nonvolatile synaptic elements.

Exploration of the integration of care for persons with a traumatic brain injury using social network analysis methodology.

PubMed

Lamontagne, Marie-Eve

2013-01-01

Integration is a popular strategy to increase the quality of care within systems of care. However, there is no common language, approach or tool allowing for a valid description, comparison and evaluation of integrated care. Social network analysis could be a viable methodology to provide an objective picture of integrated networks. To illustrate social network analysis use in the context of systems of care for traumatic brain injury. We surveyed members of a network using a validated questionnaire to determine the links between them. We determined the density, centrality, multiplexity, and quality of the links reported. The network was described as moderately dense (0.6), the most prevalent link was knowledge, and four organisation members of a consortium were central to the network. Social network analysis allowed us to create a graphic representation of the network. Social network analysis is a useful methodology to objectively characterise integrated networks.

A large-scale measurement, analysis and modelling of electromagnetic radiation levels in the vicinity of GSM/UMTS base stations in an urban area.

PubMed

Karadağ, Teoman; Yüceer, Mehmet; Abbasov, Teymuraz

2016-01-01

The present study analyses the electric field radiating from the GSM/UMTS base stations located in central Malatya, a densely populated urban area in Turkey. The authors have conducted both instant and continuous measurements of high-frequency electromagnetic fields throughout their research by using non-ionising radiation-monitoring networks. Over 15,000 instant and 13,000,000 continuous measurements were taken throughout the process. The authors have found that the normal electric field radiation can increase ∼25% during daytime, depending on mobile communication traffic. The authors' research work has also demonstrated the fact that the electric field intensity values can be modelled for each hour, day or week with the results obtained from continuous measurements. The authors have developed an estimation model based on these values, including mobile communication traffic (Erlang) values obtained from mobile phone base stations and the temperature and humidity values in the environment. The authors believe that their proposed artificial neural network model and multivariable least-squares regression analysis will help predict the electric field intensity in an environment in advance. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multi-Dimensional Prioritization of Dental Caries Candidate Genes and Its Enriched Dense Network Modules

PubMed Central

Wang, Quan; Jia, Peilin; Cuenco, Karen T.; Feingold, Eleanor; Marazita, Mary L.; Wang, Lily; Zhao, Zhongming

2013-01-01

A number of genetic studies have suggested numerous susceptibility genes for dental caries over the past decade with few definite conclusions. The rapid accumulation of relevant information, along with the complex architecture of the disease, provides a challenging but also unique opportunity to review and integrate the heterogeneous data for follow-up validation and exploration. In this study, we collected and curated candidate genes from four major categories: association studies, linkage scans, gene expression analyses, and literature mining. Candidate genes were prioritized according to the magnitude of evidence related to dental caries. We then searched for dense modules enriched with the prioritized candidate genes through their protein-protein interactions (PPIs). We identified 23 modules comprising of 53 genes. Functional analyses of these 53 genes revealed three major clusters: cytokine network relevant genes, matrix metalloproteinases (MMPs) family, and transforming growth factor-beta (TGF-β) family, all of which have been previously implicated to play important roles in tooth development and carious lesions. Through our extensive data collection and an integrative application of gene prioritization and PPI network analyses, we built a dental caries-specific sub-network for the first time. Our study provided insights into the molecular mechanisms underlying dental caries. The framework we proposed in this work can be applied to other complex diseases. PMID:24146904

Finding Hierarchical and Overlapping Dense Subgraphs using Nucleus Decompositions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seshadhri, Comandur; Pinar, Ali; Sariyuce, Ahmet Erdem

Finding dense substructures in a graph is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasiclique, k-densest subgraph) are NP-hard. Furthermore, the goal is rarely to nd the \\true optimum", but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine a hierarchical structure among them. Current dense subgraph nding algorithms usually optimize some objective, and only nd a few such subgraphs without providing any hierarchy. It is also not clear how to account formore » overlaps in dense substructures. We de ne the nucleus decomposition of a graph, which represents the graph as a forest of nuclei. Each nucleus is a subgraph where smaller cliques are present in many larger cliques. The forest of nuclei is a hierarchy by containment, where the edge density increases as we proceed towards leaf nuclei. Sibling nuclei can have limited intersections, which allows for discovery of overlapping dense subgraphs. With the right parameters, the nuclear decomposition generalizes the classic notions of k-cores and k-trusses. We give provable e cient algorithms for nuclear decompositions, and empirically evaluate their behavior in a variety of real graphs. The tree of nuclei consistently gives a global, hierarchical snapshot of dense substructures, and outputs dense subgraphs of higher quality than other state-of-theart solutions. Our algorithm can process graphs with tens of millions of edges in less than an hour.« less

Clustering and Flow Conservation Monitoring Tool for Software Defined Networks

PubMed Central

Puente Fernández, Jesús Antonio

2018-01-01

Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches. PMID:29614049

Water quality monitoring for high-priority water bodies in the Sonoran Desert network

Treesearch

Terry W. Sprouse; Robert M. Emanuel; Sara A. Strorrer

2005-01-01

This paper describes a network monitoring program for “high priority” water bodies in the Sonoran Desert Network of the National Park Service. Protocols were developed for monitoring selected waters for ten of the eleven parks in the Network. Park and network staff assisted in identifying potential locations of testing sites, local priorities, and how water quality...

Network Monitoring and Fault Detection on the University of Illinois at Urbana-Champaign Campus Computer Network.

ERIC Educational Resources Information Center

Sng, Dennis Cheng-Hong

The University of Illinois at Urbana-Champaign (UIUC) has a large campus computer network serving a community of about 20,000 users. With such a large network, it is inevitable that there are a wide variety of technologies co-existing in a multi-vendor environment. Effective network monitoring tools can help monitor traffic and link usage, as well…

First demonstration and field trial on multi-user UDWDM-PON full duplex PSK-PSK with single monolithic integrated dual-output-DFB-SOA based ONUs.

PubMed

Chu, GuangYong; Maho, Anaëlle; Cano, Iván; Polo, Victor; Brenot, Romain; Debrégeas, Hélène; Prat, Josep

2016-10-15

We demonstrate a monolithically integrated dual-output DFB-SOA, and conduct the field trial on a multi-user bidirectional coherent ultradense wavelength division multiplexing-passive optical network (UDWDM-PON). To the best of our knowledge, this is the first achievement of simplified single integrated laser-based neighboring coherent optical network units (ONUs) with a 12.5 GHz channel spaced ultra-dense access network, including both downstream and upstream, taking the benefits of low footprint and low-temperature dependence.

Georgia's Stream-Water-Quality Monitoring Network, 2006

USGS Publications Warehouse

Nobles, Patricia L.; ,

2006-01-01

The USGS stream-water-quality monitoring network for Georgia is an aggregation of smaller networks and individual monitoring stations that have been established in cooperation with Federal, State, and local agencies. These networks collectively provide data from 130 sites, 62 of which are monitored continuously in real time using specialized equipment that transmits these data via satellite to a centralized location for processing and storage. These data are made available on the Web in near real time at http://waterdata.usgs.gov/ga/nwis/ Ninety-eight stations are sampled periodically for a more extensive suite of chemical and biological constituents that require laboratory analysis. Both the continuous and the periodic water-quality data are archived and maintained in the USGS National Water Information System and are available to cooperators, water-resource managers, and the public. The map at right shows the USGS stream-water-quality monitoring network for Georgia and major watersheds. The network represents an aggregation of smaller networks and individual monitoring stations that collectively provide data from 130 sites.

European network infrastructures of observatories for terrestrial Global Change research

NASA Astrophysics Data System (ADS)

Vereecken, H.; Bogena, H.; Lehning, M.

2009-04-01

The earth's climate is significantly changing (e.g. IPCC, 2007) and thus directly affecting the terrestrial systems. The number and intensity hydrological extremes, such as floods and droughts, are continually increasing, resulting in major economical and social impacts. Furthermore, the land cover in Europe has been modified fundamentally by conversions for agriculture, forest and for other purposes such as industrialisation and urbanisation. Additionally, water resources are more than ever used for human development, especially as a key resource for agricultural and industrial activities. As a special case, the mountains of the world are of significant importance in terms of water resources supply, biodiversity, economy, agriculture, traffic and recreation but particularly vulnerable to environmental change. The Alps are unique because of the pronounced small scale variability they contain, the high population density they support and their central position in Europe. The Alps build a single coherent physical and natural environment, artificially cut by national borders. The scientific community and governmental bodies have responded to these environmental changes by performing dedicated experiments and by establishing environmental research networks to monitor, analyse and predict the impact of Global Change on different terrestrial systems of the Earths' environment. Several European network infrastructures for terrestrial Global Change research are presently immerging or upgrading, such as ICOS, ANAEE, LifeWatch or LTER-Europe. However, the strongest existing networks are still operating on a regional or national level and the historical growth of such networks resulted in a very heterogeneous landscape of observation networks. We propose therefore the establishment of two complementary networks: The NetwOrk of Hydrological observAtories, NOHA. NOHA aims to promote the sustainable management of water resources in Europe, to support the prediction of hydrological system changes, and to develop and implement tools and technologies for monitoring, prevention and mitigation of environmental risks and pressures. In addition, NOHA will provide long-term statistical series of hydrological state variables and fluxes for the analysis and prognosis of Global Change consequences using integrated model systems. These data will support the development and establishment of efficient prevention, mitigation and adaptation strategies (E.g. EU-Water Framework Directive) and spur the development and validation of hydrological theories and models. The second network, ALPS, - the Alpine Observing System - will create an unique infrastructure for environmental and climate research and observation for the whole Alpine region, providing a common platform for the benefit of the society in Europe as a whole. The initiative will build on existing infrastructure in the participating countries and on new and emerging technology, allowing an unprecedented coverage of observation systems at affordable cost. ALPS will create a new collaboration between scientists, engineers, monitoring agencies, public and decision makers, with the aim to gain an integrated understanding of complex environmental systems. The ALPS effort will be structured along three major axes: (i) harmonize and strengthen the backbone of permanent measurement infrastructures and complement these with dense deployments of intelligent networks, to improve the recording of environmental parameters overcoming disciplinary and national borders, (ii) link the main data centres to create a distributed cyber-infrastructure with the final aim to enable effective data access and retrieval to all science and society users, and (iii) invest in data assimilation and exploitation toward scientific and practical results in particular with respect to dealing with extreme events and natural hazards. In this presentation, we will focus on the motivation, the concept and the scientific and organizational challenges of ALPS and NOHA.

Integrating Near Fault Observatories (NFO) for EPOS Implementation Phase

NASA Astrophysics Data System (ADS)

Chiaraluce, Lauro

2015-04-01

Following the European Plate Observing System (EPOS) project vision aimed at creating a pan-European infrastructure for Earth sciences to support science for a more sustainable society, we are working on the integration of Near-Fault Observatories (NFOs). NFOs are state of the art research infrastructures consisting of advanced networks of multi-parametric sensors continuously monitoring the chemical and physical processes related to the common underlying earth instabilities governing active faults evolution and the genesis of earthquakes. Such a methodological approach, currently applicable only at the local scale (areas of tens to few hundreds of kilometres), is based on extremely dense networks and less common instruments deserving an extraordinary work on data quality control and multi-parameter data description. These networks in fact usually complement regional seismic and geodetic networks (typically with station spacing of 50-100km) with high-density distributions of seismic, geodetic, geochemical and geophysical sensors located typically within 10-20 km of active faults where large earthquakes are expected in the future. In the initial phase of EPOS-IP, seven NFO nodes will be linked: the Alto Tiberina and Irpinia Observatories in Italy, the Corinth Observatory in Greece, the South-Iceland Seismic Zone, the Valais Observatory in Switzerland, Marmara Sea GEO Supersite in Turkey (EU MARSite) and the Vrancea Observatory in Romania. Our work is aimed at establishing standards and integration within this first core group of NFOs while other NFOs are expected to be installed in the next years adopting the standards established and developed within the EPOS Thematic Core Services (TCS). The goal of our group is to build upon the initial development supported by these few key national observatories coordinated under previous EU projects (NERA and REAKT), inclusive and harmonised TCS supporting the installation over the next decade of tens of near-fault observatories monitoring active faults in different tectonic environments in Europe. We will assist these new NFOs in their design, installation and inclusion in EPOS. These infrastructures will substantially enable advancements in our fundamental understanding of earthquakes generation processes and associated ground shaking due to their high quality near source multidisciplinary data retrieval. While guaranteeing the continuous acquisition and storage of long time-series of such data, we will allow also an easy and direct data discovery and access to the whole community. This implies to strengthen the collaborations with other related EU and global initiatives devoted to the multidisciplinary monitoring and study of active fault zones (such as the GEO Geohazards Supersites initiative). Another key goal is the establishment of a legal governance for such a young community to ensure the long-term sustainability of the services and data access to databases to be used for scientific investigations and accessible via the Integrated Services that will be implemented within the EPOS IP project. The availability of real-time data retrieved by dense and multi-parametric networks located at close distance from the fault provides the unique opportunity of observing all phase of preparation, nucleation and propagation of the earthquake rupture. It is thus of crucial importance to develop methodologies that follow in real-time the evolution of the event. Hence the NFO is the unique and ideal infrastructure for hosting testing centers where a variety of scientific algorithms for real-time monitoring can be operated side-by-side and their performance independently evaluated. Besides the high interest for fundamental science, such developments have obvious societal impact, as they allow precise and timely release of alerts as the seismic event develops, and can attract new stakeholders such as industry partners who are interested in adopting and investing in early warning technologies and evolutionary ground shaking maps. Finally, we will describe how we intend to implement novel tools for visualization and analysis of multidisciplinary data and products to describe the anatomy of active faults and the physical processes governing earthquake generation and faulting. A sort of virtual laboratory aimed at promoting and disseminating Earth sciences at different levels.

COMPARISON OF DATA FROM THE STN AND IMPROVE NETWORKS

EPA Science Inventory

Two national chemical speciation-monitoring networks operate currently within the United States. The Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network operates primarily in rural areas collecting aerosol and optical data to better understand th...

Epidemic spreading on complex networks with community structures

PubMed Central

Stegehuis, Clara; van der Hofstad, Remco; van Leeuwaarden, Johan S. H.

2016-01-01

Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities. PMID:27440176

Ambient seismic noise monitoring of the Super-Sauze landslide from a very dense temporary seismic array

NASA Astrophysics Data System (ADS)

Chtouki, Toufik; Vergne, Jerome; Provost, Floriane; Malet, Jean-Philippe; Burtin, Arnaud; Hibert, Clément

2017-04-01

The Super-Sauze landslide is located on the southern part of the Barcelonnette Basin (French Alps) and has developed in a soft clay-shale environment. It is one of the four sites continuously monitored through a wide variety of geophysical and hydro-geological techniques in the framework of the OMIV French national landslide observatory. From early June to mid-July 2016, a temporary dense seismic array has been installed in the most active part of the landslide and at its surroundings. 50 different sites with an average inter-station distance of 50m have been instrumented with 150 miniaturized and autonomous seismic stations (Zland nodes), allowing a continuous record of the seismic signal at frequencies higher than 0.2Hz over an almost regular grid. Concurrently, a Ground-Based InSAR device allowed for a precise and continuous monitoring of the surface deformation. Overall, this experiment is intended to better characterize the spatio-temporal evolution of the deformation processes related to various type of forcing. We analyze the continuous records of ambient seismic noise recorded by the dense array. Using power spectral densities, we characterize the various types of natural and anthropogenic seismic sources, including the effect of water turbulence and bedload transport in the small nearby torrents. We also compute the correlation of the ambient diffuse seismic noise in various frequency bands for the 2448 station pairs to recover the empirical Green functions between them. The temporal evolution of the coda part of these noise correlation functions allows monitoring and localizing shear wave velocity variations in the sliding mass. Here we present some preliminary results of this analysis and compare the seismic variations to meteorological data and surface deformation.

Continuous Seismic Threshold Monitoring

DTIC Science & Technology

1992-05-31

Continuous threshold monitoring is a technique for using a seismic network to monitor a geographical area continuously in time. The method provides...area. Two approaches are presented. Site-specific monitoring: By focusing a seismic network on a specific target site, continuous threshold monitoring...recorded events at the site. We define the threshold trace for the network as the continuous time trace of computed upper magnitude limits of seismic

Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations

PubMed Central

Wang, Junxiao; Wang, Xiaorui; Zhou, Shenglu; Wu, Shaohua; Zhu, Yan; Lu, Chunfeng

2016-01-01

With China’s rapid economic development, the reduction in arable land has emerged as one of the most prominent problems in the nation. The long-term dynamic monitoring of arable land quality is important for protecting arable land resources. An efficient practice is to select optimal sample points while obtaining accurate predictions. To this end, the selection of effective points from a dense set of soil sample points is an urgent problem. In this study, data were collected from Donghai County, Jiangsu Province, China. The number and layout of soil sample points are optimized by considering the spatial variations in soil properties and by using an improved simulated annealing (SA) algorithm. The conclusions are as follows: (1) Optimization results in the retention of more sample points in the moderate- and high-variation partitions of the study area; (2) The number of optimal sample points obtained with the improved SA algorithm is markedly reduced, while the accuracy of the predicted soil properties is improved by approximately 5% compared with the raw data; (3) With regard to the monitoring of arable land quality, a dense distribution of sample points is needed to monitor the granularity. PMID:27706051

Estimating seismic site response in Christchurch City (New Zealand) from dense low-cost aftershock arrays

USGS Publications Warehouse

Kaiser, Anna E.; Benites, Rafael A.; Chung, Angela I.; Haines, A. John; Cochran, Elizabeth S.; Fry, Bill

2011-01-01

The Mw 7.1 September 2010 Darfield earthquake, New Zealand, produced widespread damage and liquefaction ~40 km from the epicentre in Christchurch city. It was followed by the even more destructive Mw 6.2 February 2011 Christchurch aftershock directly beneath the city’s southern suburbs. Seismic data recorded during the two large events suggest that site effects contributed to the variations in ground motion observed throughout Christchurch city. We use densely-spaced aftershock recordings of the Darfield earthquake to investigate variations in local seismic site response within the Christchurch urban area. Following the Darfield main shock we deployed a temporary array of ~180 low-cost 14-bit MEMS accelerometers linked to the global Quake-Catcher Network (QCN). These instruments provided dense station coverage (spacing ~2 km) to complement existing New Zealand national network strong motion stations (GeoNet) within Christchurch city. Well-constrained standard spectral ratios were derived for GeoNet stations using a reference station on Miocene basalt rock in the south of the city. For noisier QCN stations, the method was adapted to find a maximum likelihood estimate of spectral ratio amplitude taking into account the variance of noise at the respective stations. Spectral ratios for QCN stations are similar to nearby GeoNet stations when the maximum likelihood method is used. Our study suggests dense low-cost accelerometer aftershock arrays can provide useful information on local-scale ground motion properties for use in microzonation. Preliminary results indicate higher amplifications north of the city centre and strong high-frequency amplification in the small, shallower basin of Heathcote Valley.

Directed network modules

NASA Astrophysics Data System (ADS)

Palla, Gergely; Farkas, Illés J.; Pollner, Péter; Derényi, Imre; Vicsek, Tamás

2007-06-01

A search technique locating network modules, i.e. internally densely connected groups of nodes in directed networks is introduced by extending the clique percolation method originally proposed for undirected networks. After giving a suitable definition for directed modules we investigate their percolation transition in the Erdos-Rényi graph both analytically and numerically. We also analyse four real-world directed networks, including Google's own web-pages, an email network, a word association graph and the transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The obtained directed modules are validated by additional information available for the nodes. We find that directed modules of real-world graphs inherently overlap and the investigated networks can be classified into two major groups in terms of the overlaps between the modules. Accordingly, in the word-association network and Google's web-pages, overlaps are likely to contain in-hubs, whereas the modules in the email and transcriptional regulatory network tend to overlap via out-hubs.

Setting up a new CZO in the Ganga basin: instrumentation, stakeholder engagement and preliminary observations

NASA Astrophysics Data System (ADS)

Gupta, S.; Tripathi, S.; Sinha, R.; Karumanchi, S. H.; Paul, D.; Tripathi, S. N.; Sen, I. S.; Dash, S. K.

2017-12-01

The Ganga plains represent the abode of more than 400 million people and a region of severe anthropogenic disturbance to natural processes. Changing agricultural practices, inefficient use of water, contamination of groundwater systems, and decrease in soil fertility are some of the issues that have affected the long-term resilience of hydrological processes. The quantification of these processes demands a network of hydro-meteorological instrumentation, low-cost sensors, continuous engagement of stakeholders and real time data transmission at a fine interval. We have therefore set up a Critical Zone Observatory (CZO) in a small watershed (35km2) that forms an intensively managed rural landscape consisting of 92% of agricultural land in the Pandu River Basin (a small tributary of the Ganga River). Apart from setting up a hydro-meteorological observatory, the major science questions we want to address relate to development of water balance model, understanding the soil-water interaction and estimation of nutrient fluxes in the watershed. This observatory currently has various types of sensors that are divided into three categories: (a) spatially not dense but temporally fine data, (b) spatially dense but temporally not fine data and(c) spatially dense and temporally fine data. The first category represent high-cost sensors namely automatic weather stations that are deployed at two locations and provide data at 15-minute interval. The second category includes portable soil moisture, discharge and groundwater level at weekly/ biweekly interval. The third category comprises low-cost sensors including automatic surface and groundwater level sensors installed on open wells to monitor the continuous fluctuation of water level at every 15 minutes. In addition to involving the local communities in data collection (e.g. manual rainfall measurement, water and soil sampling), this CZO also aims to provide relevant information to them for improving their sustainability. The preliminary results show significant heterogeneity in soil type, cropping system, fertilizer application, water quality, irrigation source etc. within a small catchment.

The effects of volcanoes on health: preparedness in Mexico.

PubMed

Zeballos, J L; Meli, R; Vilchis, A; Barrios, L

1996-01-01

The article reviews the most important aspects of volcanic eruptions and presents a summary of the harmful materials they emit. The main health effects can be classified as either physical (trauma, respiratory diseases, etc.) or psychological (depression, anxiety, nightmares, neurosis, etc.). Popocatépetl, the most famous active volcano in Mexico, lies on the borders of the States of Mexico, Puebla and Morelos. In 1993, seismic activity intensified, as did as the emission of fumaroles, followed in December 1994 by moderate tremors and strong emissions of gases and ash. In 1996, a number of seismic events led to an unexpected explosion. A daily emission of 8,000 to 15,000 tonnes of sulfur dioxide has been measured. Popocatépetl is located in a densely populated region of Mexico. A complex network to monitor the volcano using sophisticated equipment has been set up, including visual surveillance, seismic, geochemical and geodesic monitoring. An early warning system (SINAPROC/CENAPRED) has been developed to keep the population permanently informed. The warning system uses colour codes: green for normal, yellow for alert, and red for warning and evacuation. An emergency plan has been prepared, including evacuation and preparation for medical centres and hospitals in the region, as well as intense public information campaigns.

Experiments on Adaptive Self-Tuning of Seismic Signal Detector Parameters

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Chael, E. P.; Peterson, M. G.; Lawry, B.; Phillips-Alonge, K. E.; Balch, R. S.; Ziegler, A.

2016-12-01

Scientific applications, including underground nuclear test monitoring and microseismic monitoring can benefit enormously from data-driven dynamic algorithms for tuning seismic and infrasound signal detection parameters since continuous streams are producing waveform archives on the order of 1TB per month. Tuning is a challenge because there are a large number of data processing parameters that interact in complex ways, and because the underlying populating of true signal detections is generally unknown. The largely manual process of identifying effective parameters, often performed only over a subset of stations over a short time period, is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. We present improvements to an Adaptive Self-Tuning algorithm for continuously adjusting detection parameters based on consistency with neighboring sensors. Results are shown for 1) data from a very dense network ( 120 stations, 10 km radius) deployed during 2008 on Erebus Volcano, Antarctica, and 2) data from a continuous downhole seismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project. Performance is assessed in terms of missed detections and false detections relative to human analyst detections, simulated waveforms where ground-truth detections exist and visual inspection.

Prediction-based association control scheme in dense femtocell networks.

PubMed

Sung, Nak Woon; Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

2017-01-01

The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system's effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective.

Comparison of Fiber Optic Strain Demodulation Implementations

NASA Technical Reports Server (NTRS)

Quach, Cuong C.; Vazquez, Sixto L.

2005-01-01

NASA Langley Research Center is developing instrumentation based upon principles of Optical Frequency-Domain Reflectometry (OFDR) for the provision of large-scale, dense distribution of strain sensors using fiber optics embedded with Bragg gratings. Fiber Optic Bragg Grating technology enables the distribution of thousands of sensors immune to moisture and electromagnetic interference with negligible weight penalty. At Langley, this technology provides a key component for research and development relevant to comprehensive aerospace vehicle structural health monitoring. A prototype system is under development that includes hardware and software necessary for the acquisition of data from an optical network and conversion of the data into strain measurements. This report documents the steps taken to verify the software that implements the algorithm for calculating the fiber strain. Brief descriptions of the strain measurement system and the test article are given. The scope of this report is the verification of software implementations as compared to a reference model. The algorithm will be detailed along with comparison results.

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Brad

2014-01-01

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Propeller, Light and Dark

NASA Image and Video Library

2013-06-24

NASA Cassini spacecraft has been monitoring propeller features such as Bleriot since their discovery. The bright dash-like features are regions where a small moonlet has caused ring particles to cluster together more densely than normal.

GROUND WATER ISSUE: DENSE NONAQUEOUS PHASE LIQUIDS

EPA Science Inventory

This issue paper is a literature evaluation focusing on DNAPLs and provides an overview from a conceptual fate and transport point of view of DNAPL phase distribution, monitoring, site characterization, remediation, and modeling.

Optimal Design of River Monitoring Network in Taizihe River by Matter Element Analysis

PubMed Central

Wang, Hui; Liu, Zhe; Sun, Lina; Luo, Qing

2015-01-01

The objective of this study is to optimize the river monitoring network in Taizihe River, Northeast China. The situation of the network and water characteristics were studied in this work. During this study, water samples were collected once a month during January 2009 - December 2010 from seventeen sites. Futhermore, the 16 monitoring indexes were analyzed in the field and laboratory. The pH value of surface water sample was found to be in the range of 6.83 to 9.31, and the average concentrations of NH4 +-N, chemical oxygen demand (COD), volatile phenol and total phosphorus (TP) were found decreasing significantly. The water quality of the river has been improved from 2009 to 2010. Through the calculation of the data availability and the correlation between adjacent sections, it was found that the present monitoring network was inefficient as well as the optimization was indispensable. In order to improve the situation, the matter element analysis and gravity distance were applied in the optimization of river monitoring network, which were proved to be a useful method to optimize river quality monitoring network. The amount of monitoring sections were cut from 17 to 13 for the monitoring network was more cost-effective after being optimized. The results of this study could be used in developing effective management strategies to improve the environmental quality of Taizihe River. Also, the results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems. PMID:26023785

Controllability of structural brain networks

NASA Astrophysics Data System (ADS)

Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K.; Yu, Alfred B.; Kahn, Ari E.; Medaglia, John D.; Vettel, Jean M.; Miller, Michael B.; Grafton, Scott T.; Bassett, Danielle S.

2015-10-01

Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.

CNT-cement based composites: fabrication, self-sensing properties, and prospective applications to structural health monitoring

NASA Astrophysics Data System (ADS)

Rainieri, Carlo; Song, Yi; Fabbrocino, Giovanni; Schulz, Mark J.; Shanov, Vesselin

2013-08-01

Degradation phenomena can affect civil structures over their lifespan. The recent advances in nanotechnology and sensing allow to monitor the behaviour of a structure, assess its performance and identify damage at an early stage. Thus, maintenance actions can be carried out in a timely manner, improving structural reliability and safety. Structural Health Monitoring (SHM) is traditionally performed at a global level, with a limited number of sensors distributed over a relatively large area of a structure. Thus, only major damage conditions are detectable. Dense sensor networks and innovative structural neural systems, reproducing the structure and the function of the human nervous system, may overcome this drawback of current SHM systems. Miniaturization and embedment are key requirements for successful implementation of structural neural systems. Carbon nanotubes (CNTs) can play an attractive role in the development of embedded sensors and smart structural materials, since they can provide to traditional cement based materials both structural capability and measurable response to applied stresses, strains, cracks and other flaws. In this paper investigations about CNT/cement composites and their self-sensing capabilities are summarized and critically revised. The analysis of available experimental results and theoretical developments provides useful design criteria for the fabrication of CNT/cement composites optimized for SHM applications in civil engineering. Specific attention is paid to the opportunities provided by new RF plasma technologies for the functionalization of CNTs in view of sensor development and SHM applications.

Extensive validation of CM SAF surface radiation products over Europe.

PubMed

Urraca, Ruben; Gracia-Amillo, Ana M; Koubli, Elena; Huld, Thomas; Trentmann, Jörg; Riihelä, Aku; Lindfors, Anders V; Palmer, Diane; Gottschalg, Ralph; Antonanzas-Torres, Fernando

2017-09-15

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8-13 W/m 2 , whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements.

Understanding processes that generate flash floods in the arid Judean Desert to the Dead Sea - a measurement network

NASA Astrophysics Data System (ADS)

Hennig, Hanna; Rödiger, Tino; Laronne, Jonathan B.; Geyer, Stefan; Merz, Ralf

2016-04-01

Flash floods in (semi-) arid regions are fascinating in their suddenness and can be harmful for humans, infrastructure, industry and tourism. Generated within minutes, an early warning system is essential. A hydrological model is required to quantify flash floods. Current models to predict flash floods are often based on simplified concepts and/or on concepts which were developed for humid regions. To more closely relate such models to local conditions, processes within catchments where flash floods occur require consideration. In this study we present a monitoring approach to decipher different flash flood generating processes in the ephemeral Wadi Arugot on the western side of the Dead Sea. To understand rainfall input a dense rain gauge network was installed. Locations of rain gauges were chosen based on land use, slope and soil cover. The spatiotemporal variation of rain intensity will also be available from radar backscatter. Level pressure sensors located at the outlet of major tributaries have been deployed to analyze in which part of the catchment water is generated. To identify the importance of soil moisture preconditions, two cosmic ray sensors have been deployed. At the outlet of the Arugot water is sampled and level is monitored. To more accurately determine water discharge, water velocity is measured using portable radar velocimetry. A first analysis of flash flood processes will be presented following the FLEX-Topo concept .(Savenije, 2010), where each landscape type is represented using an individual hydrological model according to the processes within the three hydrological response units: plateau, desert and outlet. References: Savenije, H. H. G.: HESS Opinions "Topography driven conceptual modelling (FLEX-Topo)", Hydrol. Earth Syst. Sci., 14, 2681-2692, doi:10.5194/hess-14-2681-2010, 2010.

Sensor Network Architectures for Monitoring Underwater Pipelines

PubMed Central

Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

2011-01-01

This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring. PMID:22346669

Sensor network architectures for monitoring underwater pipelines.

PubMed

Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

2011-01-01

This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (radio frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring.

MAJOR MONITORING NETWORKS: A FOUNDATION TO PRESERVE, PROTECT AND RESTORE

EPA Science Inventory

MAJOR MONITORING NETWORKS: A FOUNDATION TO PRESERVE, PROTECT, AND RESTORE

Ideally, major human and environmental monitoring networks should provide the scientific information needed for policy and management decision-making processes. It is widely recognized that reliable...

Mesonet Programs - Needs and Best Practices

NASA Astrophysics Data System (ADS)

Usher, J.; Doherty, J.

2010-09-01

Authors: Jeremy Usher Managing Director, Europe WeatherBug® Professional John Doherty Senior Vice President Sales & Marketing WeatherBug® Professional There are many well documented and compelling needs for significant improvements in mesoscale meteorological observations throughout many parts of the world. This is evidenced by the fact that the vast majority of severe weather impacts and related life, property and economic losses are associated with mesoscale events such as tornados, thunderstorms, fronts, squall lines, etc. Additionally, the looming impacts of climate change are likely to vary substantially on a regional basis requiring more detailed information on a finer scale. Hence, development of comprehensive densely spaced observing systems can establish the critical information repositories needed to improve: short- and medium-term weather and wind forecasting down to local scales, climate monitoring on a regional basis, as well as decision support capabilities including plume dispersion modeling and air quality forecasting, to name a few. It is imperative that governmental/public/private/academic partnerships are formed to leverage the collective expertise, assets and technological know-how of each sector. Collaboration of this type is particularly germane given that many existing mesonets (weather networks) have been deployed by local organizations with local considerations in mind. These stakeholders maintain the capacity to react quickly and efficiently and are best positioned to recommend future network evolution within their domains. Additionally, coordination will go a long way toward avoiding duplication of effort and promote both a robust private sector and wise expenditure of public funds. This presentation will outline the major building blocks of a mesonet program and discuss best practices for a multi-tiered, multi-faceted "network of networks" approach that maximizes the value derived from leveraging existing assets and serves multiple needs. On-going activities within the U.S. National Mesonet Program will be highlighted.

Ionospheric variation observed in Oregon Real-time GNSS network during the total eclipse of 21 August 2017

NASA Astrophysics Data System (ADS)

Shahbazi, A.; Park, J.; Kim, S.; Oberg, R.

2017-12-01

As the ionospheric behavior is highly related to the solar activity, the total eclipse passing across the North America on 21 August 2017 is expected to significantly affect the electron density in the ionosphere along the path. Taking advantage of GNSS capability for observing total electron content (TEC), this study demonstrates the impact of the total eclipse not only on the TEC variation during the period of the event but also on GNSS positioning. Oregon Department of Transportation (ODOT) runs a dense real time GNSS network, referred to as Oregon Real-time GNSS network (ORGN). From the dual frequency GPS and GLONASS observations in ORGN, the TEC over the network area can be extracted. We observe the vertical TEC (VTEC) from the ORGN for analyzing the ionospheric condition in the local area affected by the eclipse. To observe the temporal variation, we also observe the slant TEC (STEC) in each ray path and analyze the short term variation in different geometry of each ray path. Although the STEC is dependent quantity upon the changing geometry of a satellite, this approach provides insight to the ionospheric behavior of the total eclipse because the STEC does not involve the projection error, which is generated by VTEC computation. During the period of eclipse, the abnormal variations on VTEC and STEC are expected. The experimental results will be presented in time series plots for selected stations as well as the regional TEC map in Oregon. In addition to the TEC monitoring, we also test the positioning result of ORGN stations through Precise Point Positioning (PPP) and relative positioning. The expected result is that the both positioning results are degraded during the solar eclipse due to the instable ionospheric condition over short time.

Rapid changes in synaptic vesicle cytochemistry after depolarization of cultured cholinergic sympathetic neurons

PubMed Central

1985-01-01

Sympathetic neurons taken from rat superior cervical ganglia and grown in culture acquire cholinergic function under certain conditions. These cholinergic sympathetic neurons, however, retain a number of adrenergic properties, including the enzymes involved in the synthesis of norepinephrine (NE) and the storage of measurable amounts of NE. These neurons also retain a high affinity uptake system for NE; despite this, the majority of the synaptic vesicles remain clear even after incubation in catecholamines. The present study shows, however, that if these neurons are depolarized before incubation in catecholamine, the synaptic vesicles acquire dense cores indicative of amine storage. These manipulations are successful when cholinergic function is induced with either a medium that contains human placental serum and embryo extract or with heart-conditioned medium, and when the catecholamine is either NE or 5-hydroxydopamine. In some experiments, neurons are grown at low densities and shown to have cholinergic function by electrophysiological criteria. After incubation in NE, only 6% of the synaptic vesicles have dense cores. In contrast, similar neurons depolarized (80 mM K+) before incubation in catecholamine contain 82% dense-cored vesicles. These results are confirmed in network cultures where the percentage of dense-cored vesicles is increased 2.5 to 6.5 times by depolarizing the neurons before incubation with catecholamine. In both single neurons and in network cultures, the vesicle reloading is inhibited by reducing vesicle release during depolarization with an increased Mg++/Ca++ ratio or by blocking NE uptake either at the plasma membrane (desipramine) or at the vesicle membrane (reserpine). In addition, choline appears to play a competitive role because its presence during incubation in NE or after reloading results in decreased numbers of dense-cored vesicles. We conclude that the depolarization step preceding catecholamine incubation acts to empty the vesicles of acetylcholine, thus allowing them to reload with catecholamine. These data also suggest that the same vesicles may contain both neurotransmitters simultaneously. PMID:4008529

Monitoring groundwater: optimising networks to take account of cost effectiveness, legal requirements and enforcement realities

NASA Astrophysics Data System (ADS)

Allan, A.; Spray, C.

2013-12-01

The quality of monitoring networks and modeling in environmental regulation is increasingly important. This is particularly true with respect to groundwater management, where data may be limited, physical processes poorly understood and timescales very long. The powers of regulators may be fatally undermined by poor or non-existent networks, primarily through mismatches between the legal standards that networks must meet, actual capacity and the evidentiary standards of courts. For example, in the second and third implementation reports on the Water Framework Directive, the European Commission drew attention to gaps in the standards of mandatory monitoring networks, where the standard did not meet the reality. In that context, groundwater monitoring networks should provide a reliable picture of groundwater levels and a ';coherent and comprehensive' overview of chemical status so that anthropogenically influenced long-term upward trends in pollutant levels can be tracked. Confidence in this overview should be such that 'the uncertainty from the monitoring process should not add significantly to the uncertainty of controlling the risk', with densities being sufficient to allow assessment of the impact of abstractions and discharges on levels in groundwater bodies at risk. The fact that the legal requirements for the quality of monitoring networks are set out in very vague terms highlights the many variables that can influence the design of monitoring networks. However, the quality of a monitoring network as part of the armory of environmental regulators is potentially of crucial importance. If, as part of enforcement proceedings, a regulator takes an offender to court and relies on conclusions derived from monitoring networks, a defendant may be entitled to question those conclusions. If the credibility, reliability or relevance of a monitoring network can be undermined, because it is too sparse, for example, this could have dramatic consequences on the ability of a regulator to ensure compliance with legal standards. On the other hand, it can be ruinously expensive to set up a monitoring network in remote areas and regulators must therefore balance the cost effectiveness of these networks against the chance that a court might question their fitness for purpose. This presentation will examine how regulators can balance legal standards for monitoring against the cost of developing and maintaining the requisite networks, while still producing observable improvements in water and ecosystem quality backed by legally enforceable sanctions for breaches. Reflecting the findings from the EU-funded GENESIS project, it will look at case law from around the world to assess how tribunals balance competing models, and the extent to which decisions may be revisited in the light of new scientific understanding. Finally, it will make recommendations to assist regulators in optimising their network designs for enforcement.

Satellite relay telemetry in the surveillance of active volcanoes and major fault zones

NASA Technical Reports Server (NTRS)

Eaton, J. P.; Ward, P. L.

1972-01-01

A review was made of efforts to develop a dense telemetered microearthquake network to study earthquake mechanics along the San Andreas fault and the strain mechanics of the Kilauea Volcano. The principle elements and objectives of the ERTS-A proposal are outlined. Some of the aspects of the earthquake network and the results obtained from it as well as some promising experiments in computerized record processing are discussed.

A Dynamic Optimization Technique for Siting the NASA-Clark Atlanta Urban Rain Gauge Network (NCURN)

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Taylor, Layi

2003-01-01

NASA satellites and ground instruments have indicated that cities like Atlanta, Georgia may create or alter rainfall. Scientists speculate that the urban heat island caused by man-made surfaces in cities impact the heat and wind patterns that form clouds and rainfall. However, more conclusive evidence is required to substantiate findings from satellites. NASA, along with scientists at Clark Atlanta University, are implementing a dense, urban rain gauge network in the metropolitan Atlanta area to support a satellite validation program called Studies of PRecipitation Anomalies from Widespread Urban Landuse (SPRAWL). SPRAWL will be conducted during the summer of 2003 to further identify and understand the impact of urban Atlanta on precipitation variability. The paper provides an. overview of SPRAWL, which represents one of the more comprehensive efforts in recent years to focus exclusively on urban-impacted rainfall. The paper also introduces a novel technique for deploying rain gauges for SPRAWL. The deployment of the dense Atlanta network is unique because it utilizes Geographic Information Systems (GIS) and Decision Support Systems (DSS) to optimize deployment of the rain gauges. These computer aided systems consider access to roads, drainage systems, tree cover, and other factors in guiding the deployment of the gauge network. GIS and DSS also provide decision-makers with additional resources and flexibility to make informed decisions while considering numerous factors. Also, the new Atlanta network and SPRAWL provide a unique opportunity to merge the high-resolution, urban rain gauge network with satellite-derived rainfall products to understand how cities are changing rainfall patterns, and possibly climate.

Energy-efficient STDP-based learning circuits with memristor synapses

NASA Astrophysics Data System (ADS)

Wu, Xinyu; Saxena, Vishal; Campbell, Kristy A.

2014-05-01

It is now accepted that the traditional von Neumann architecture, with processor and memory separation, is ill suited to process parallel data streams which a mammalian brain can efficiently handle. Moreover, researchers now envision computing architectures which enable cognitive processing of massive amounts of data by identifying spatio-temporal relationships in real-time and solving complex pattern recognition problems. Memristor cross-point arrays, integrated with standard CMOS technology, are expected to result in massively parallel and low-power Neuromorphic computing architectures. Recently, significant progress has been made in spiking neural networks (SNN) which emulate data processing in the cortical brain. These architectures comprise of a dense network of neurons and the synapses formed between the axons and dendrites. Further, unsupervised or supervised competitive learning schemes are being investigated for global training of the network. In contrast to a software implementation, hardware realization of these networks requires massive circuit overhead for addressing and individually updating network weights. Instead, we employ bio-inspired learning rules such as the spike-timing-dependent plasticity (STDP) to efficiently update the network weights locally. To realize SNNs on a chip, we propose to use densely integrating mixed-signal integrate-andfire neurons (IFNs) and cross-point arrays of memristors in back-end-of-the-line (BEOL) of CMOS chips. Novel IFN circuits have been designed to drive memristive synapses in parallel while maintaining overall power efficiency (<1 pJ/spike/synapse), even at spike rate greater than 10 MHz. We present circuit design details and simulation results of the IFN with memristor synapses, its response to incoming spike trains and STDP learning characterization.

A network model framework for prioritizing wetland conservation in the Great Plains

USGS Publications Warehouse

Albanese, Gene; Haukos, David A.

2017-01-01

ContextPlaya wetlands are the primary habitat for numerous wetland-dependent species in the Southern Great Plains of North America. Plant and wildlife populations that inhabit these wetlands are reciprocally linked through the dispersal of individuals, propagules and ultimately genes among local populations.ObjectiveTo develop and implement a framework using network models for conceptualizing, representing and analyzing potential biological flows among 48,981 spatially discrete playa wetlands in the Southern Great Plains.MethodsWe examined changes in connectivity patterns and assessed the relative importance of wetlands to maintaining these patterns by targeting wetlands for removal based on network centrality metrics weighted by estimates of habitat quality and probability of inundation.ResultsWe identified several distinct, broad-scale sub networks and phase transitions among playa wetlands in the Southern Plains. In particular, for organisms that can disperse >2 km a dense and expansive wetland sub network emerges in the Southern High Plains. This network was characterized by localized, densely connected wetland clusters at link distances (h) >2 km but <5 km and was most sensitive to changes in wetland availability (p) and configuration when h = 4 km, and p = 0.2–0.4. It transitioned to a single, large connected wetland system at broader spatial scales even when the proportion of inundated wetland was relatively low (p = 0.2).ConclusionsOur findings suggest that redundancy in the potential for broad and fine-scale movements insulates this system from damage and facilitates system-wide connectivity among populations with different dispersal capacities.

Reduction of streamflow monitoring networks by a reference point approach

NASA Astrophysics Data System (ADS)

Cetinkaya, Cem P.; Harmancioglu, Nilgun B.

2014-05-01

Adoption of an integrated approach to water management strongly forces policy and decision-makers to focus on hydrometric monitoring systems as well. Existing hydrometric networks need to be assessed and revised against the requirements on water quantity data to support integrated management. One of the questions that a network assessment study should resolve is whether a current monitoring system can be consolidated in view of the increased expenditures in time, money and effort imposed on the monitoring activity. Within the last decade, governmental monitoring agencies in Turkey have foreseen an audit on all their basin networks in view of prevailing economic pressures. In particular, they question how they can decide whether monitoring should be continued or terminated at a particular site in a network. The presented study is initiated to address this question by examining the applicability of a method called “reference point approach” (RPA) for network assessment and reduction purposes. The main objective of the study is to develop an easily applicable and flexible network reduction methodology, focusing mainly on the assessment of the “performance” of existing streamflow monitoring networks in view of variable operational purposes. The methodology is applied to 13 hydrometric stations in the Gediz Basin, along the Aegean coast of Turkey. The results have shown that the simplicity of the method, in contrast to more complicated computational techniques, is an asset that facilitates the involvement of decision makers in application of the methodology for a more interactive assessment procedure between the monitoring agency and the network designer. The method permits ranking of hydrometric stations with regard to multiple objectives of monitoring and the desired attributes of the basin network. Another distinctive feature of the approach is that it also assists decision making in cases with limited data and metadata. These features of the RPA approach highlight its advantages over the existing network assessment and reduction methods.

Towards an integrated European strong motion data distribution

NASA Astrophysics Data System (ADS)

Luzi, Lucia; Clinton, John; Cauzzi, Carlo; Puglia, Rodolfo; Michelini, Alberto; Van Eck, Torild; Sleeman, Reinhoud; Akkar, Sinan

2013-04-01

Recent decades have seen a significant increase in the quality and quantity of strong motion data collected in Europe, as dense and often real-time and continuously monitored broadband strong motion networks have been constructed in many nations. There has been a concurrent increase in demand for access to strong motion data not only from researchers for engineering and seismological studies, but also from civil authorities and seismic networks for the rapid assessment of ground motion and shaking intensity following significant earthquakes (e.g. ShakeMaps). Aside from a few notable exceptions on the national scale, databases providing access to strong motion data has not appeared to keep pace with these developments. In the framework of the EC infrastructure project NERA (2010 - 2014), that integrates key research infrastructures in Europe for monitoring earthquakes and assessing their hazard and risk, the network activity NA3 deals with the networking of acceleration networks and SM data. Within the NA3 activity two infrastructures are being constructed: i) a Rapid Response Strong Motion (RRSM) database, that following a strong event, automatically parameterises all available on-scale waveform data within the European Integrated waveform Data Archives (EIDA) and makes the waveforms easily available to the seismological community within minutes of an event; and ii) a European Strong Motion (ESM) database of accelerometric records, with associated metadata relevant to earthquake engineering and seismology research communities, using standard, manual processing that reflects the state of the art and research needs in these fields. These two separate repositories form the core infrastructures being built to distribute strong motion data in Europe in order to guarantee rapid and long-term availability of high quality waveform data to both the international scientific community and the hazard mitigation communities. These infrastructures will provide the access to strong motion data in an eventual EPOS seismological service. A working group on Strong Motion data is being created at ORFEUS in 2013. This body, consisting of experts in strong motion data collection, processing and research from across Europe, will provide the umbrella organisation that will 1) have the political clout to negotiate data sharing agreements with strong motion data providers and 2) manage the software during a transition from the end of NERA to the EPOS community. We expect the community providing data to the RRSM and ESM will gradually grow, under the supervision of ORFEUS, and eventually include strong motion data from networks from all European countries that can have an open data policy.

Designing a low-cost effective network for monitoring large scale regional seismicity in a soft-soil region (Alsace, France)

NASA Astrophysics Data System (ADS)

Bès de Berc, M.; Doubre, C.; Wodling, H.; Jund, H.; Hernandez, A.; Blumentritt, H.

2015-12-01

The Seismological Observatory of the North-East of France (ObSNEF) is developing its monitoring network within the framework of several projects. Among these project, RESIF (Réseau sismologique et géodésique français) allows the instrumentation of broad-band seismic stations, separated by 50-100 km. With the recent and future development of geothermal industrial projects in the Alsace region, the ObSNEF is responsible for designing, building and operating a dense regional seismic network in order to detect and localize earthquakes with both a completeness magnitude of 1.5 and no clipping for M6.0. The realization of the project has to be done prior to the summer 2016Several complex technical and financial constraints constitute such a projet. First, most of the Alsace Région (150x150 km2), particularly the whole Upper Rhine Graben, is a soft-soil plain where seismic signals are dominated by a high frequency noise level. Second, all the signals have to be transmitted in near real-time. And finally, the total cost of the project must not exceed $450,000.Regarding the noise level in Alsace, in order to make a reduction of 40 dB for frequencies above 1Hz, we program to instrument into 50m deep well with post-hole sensor for 5 stations out of 8 plane new stations. The 3 remaining would be located on bedrock along the Vosges piedmont. In order to be sensitive to low-magnitude regional events, we plan to install a low-noise short-period post-hole velocimeter. In order to avoid saturation for high potentiel local events (M6.0 at 10km), this velocimeter will be coupled with a surface strong-motion sensor. Regarding the connectivity, these stations will have no wired network, which reduces linking costs and delays. We will therefore use solar panels and a 3G/GPRS network. The infrastructure will be minimal and reduced to an outdoor box on a secured parcel of land. In addition to the data-logger, we will use a 12V ruggedized computer, hosting a seed-link server for near real-time transmission and a rsync daemon for delayed-time transmission.We plan to install and validate our first pilot station during the fall of 2015, and have an effective network by the summer of 2016.

A biological approach to assembling tissue modules through endothelial capillary network formation.

PubMed

Riesberg, Jeremiah J; Shen, Wei

2015-09-01

To create functional tissues having complex structures, bottom-up approaches to assembling small tissue modules into larger constructs have been emerging. Most of these approaches are based on chemical reactions or physical interactions at the interface between tissue modules. Here we report a biological assembly approach to integrate small tissue modules through endothelial capillary network formation. When adjacent tissue modules contain appropriate extracellular matrix materials and cell types that support robust endothelial capillary network formation, capillary tubules form and grow across the interface, resulting in assembly of the modules into a single, larger construct. It was shown that capillary networks formed in modules of dense fibrin gels seeded with human umbilical vein endothelial cells (HUVECs) and mesenchymal stem cells (MSCs); adjacent modules were firmly assembled into an integrated construct having a strain to failure of 117 ± 26%, a tensile strength of 2208 ± 83 Pa and a Young's modulus of 2548 ± 574 Pa. Under the same culture conditions, capillary networks were absent in modules of dense fibrin gels seeded with either HUVECs or MSCs alone; adjacent modules disconnected even when handled gently. This biological assembly approach eliminates the need for chemical reactions or physical interactions and their associated limitations. In addition, the integrated constructs are prevascularized, and therefore this bottom-up assembly approach may also help address the issue of vascularization, another key challenge in tissue engineering. Copyright © 2015 John Wiley & Sons, Ltd.

Electrical conductivity modeling and experimental study of densely packed SWCNT networks.

PubMed

Jack, D A; Yeh, C-S; Liang, Z; Li, S; Park, J G; Fielding, J C

2010-05-14

Single-walled carbon nanotube (SWCNT) networks have become a subject of interest due to their ability to support structural, thermal and electrical loadings, but to date their application has been hindered due, in large part, to the inability to model macroscopic responses in an industrial product with any reasonable confidence. This paper seeks to address the relationship between macroscale electrical conductivity and the nanostructure of a dense network composed of SWCNTs and presents a uniquely formulated physics-based computational model for electrical conductivity predictions. The proposed model incorporates physics-based stochastic parameters for the individual nanotubes to construct the nanostructure such as: an experimentally obtained orientation distribution function, experimentally derived length and diameter distributions, and assumed distributions of chirality and registry of individual CNTs. Case studies are presented to investigate the relationship between macroscale conductivity and nanostructured variations in the bulk stochastic length, diameter and orientation distributions. Simulation results correspond nicely with those available in the literature for case studies of conductivity versus length and conductivity versus diameter. In addition, predictions for the increasing anisotropy of the bulk conductivity as a function of the tube orientation distribution are in reasonable agreement with our experimental results. Examples are presented to demonstrate the importance of incorporating various stochastic characteristics in bulk conductivity predictions. Finally, a design consideration for industrial applications is discussed based on localized network power emission considerations and may lend insight to the design engineer to better predict network failure under high current loading applications.

Hiding earthquakes from scrupulous monitoring eyes of dense local seismic networks

NASA Astrophysics Data System (ADS)

Bogiatzis, P.; Ishii, M.; Kiser, E.

2012-12-01

Accurate and complete cataloguing of aftershocks is essential for a variety of purposes, including the estimation of the mainshock rupture area, the identification of seismic gaps, and seismic hazard assessment. However, immediately following large earthquakes, the seismograms recorded by local networks are noisy, with energy arriving from hundreds of aftershocks, in addition to different seismic phases interfering with one another. This causes deterioration in the performance of detection and location of earthquakes using conventional methods such as the S-P approach. This is demonstrated by results of back-projection analysis of teleseismic data showing that a significant number of events are undetected by the Japan Meteorological Agency, within the first twenty-four hours after the Mw9.0 Tohoku-oki, Japan earthquake. The spatial distribution of the hidden events is not arbitrary. Most of these earthquakes are located close to the trench, while some are located at the outer rise. Furthermore, there is a relatively sharp trench-parallel boundary separating the detected and undetected events. We investigate the cause of these hidden earthquakes using forward modeling. The calculation of raypaths for various source locations and takeoff angles with the "shooting" method suggests that this phenomenon is a consequence of the complexities associated with subducting slab. Laterally varying velocity structure defocuses the seismic energy from shallow earthquakes located near the trench and makes the observation of P and S arrivals difficult at stations situated on mainland Japan. Full waveform simulations confirm these results. Our forward calculations also show that the probability of detection is sensitive to the depth of the event. Shallower events near the trench are more difficult to detect than deeper earthquakes that are located inside the subducting plate for which the shadow-zone effect diminishes. The modeling effort is expanded to include three-dimensional structure in velocity and intrinsic attenuation to evaluate possible laterally varying patterns. Our study suggests that the phenomenon of hidden earthquakes could be present at other regions around the world with active subductions. Considering that many of these subduction zones are not as well monitored as Japan, the number of missed events, especially after large earthquakes, could be significant. The results of this work can help to identify "blind spots" of present seismic networks, and can contribute to improving monitoring activities.

Wireless in-situ Sensor Network for Agriculture and Water Monitoring on a River Basin Scale in Southern Finland: Evaluation from a Data User’s Perspective

PubMed Central

Kotamäki, Niina; Thessler, Sirpa; Koskiaho, Jari; Hannukkala, Asko O.; Huitu, Hanna; Huttula, Timo; Havento, Jukka; Järvenpää, Markku

2009-01-01

Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications. PMID:22574050

Community structure in networks

NASA Astrophysics Data System (ADS)

Newman, Mark

2004-03-01

Many networked systems, including physical, biological, social, and technological networks, appear to contain ``communities'' -- groups of nodes within which connections are dense, but between which they are sparser. The ability to find such communities in an automated fashion could be of considerable use. Communities in a web graph for instance might correspond to sets of web sites dealing with related topics, while communities in a biochemical network or an electronic circuit might correspond to functional units of some kind. We present a number of new methods for community discovery, including methods based on ``betweenness'' measures and methods based on modularity optimization. We also give examples of applications of these methods to both computer-generated and real-world network data, and show how our techniques can be used to shed light on the sometimes dauntingly complex structure of networked systems.

Reorganization of a dense granular assembly: The unjamming response function

NASA Astrophysics Data System (ADS)

Kolb, Évelyne; Cviklinski, Jean; Lanuza, José; Claudin, Philippe; Clément, Éric

2004-03-01

We investigate the mechanical properties of a static dense granular assembly in response to a local forcing. To this end, a small cyclic displacement is applied on a grain in the bulk of a two-dimensional disordered packing under gravity and the displacement fields are monitored. We evidence a dominant long range radial response in the upper half part above the solicitation and after a large number of cycles the response is “quasireversible” with a remanent dissipation field exhibiting long range streams and vortexlike symmetry.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network.

PubMed

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; Fellows, Katie; King, Galatea; Lugo, Humberto; Jerrett, Michael; Meltzer, Dan; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-03-15

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach.

Combining Community Engagement and Scientific Approaches in Next-Generation Monitor Siting: The Case of the Imperial County Community Air Network

PubMed Central

Wong, Michelle; Bejarano, Esther; Carvlin, Graeme; King, Galatea; Lugo, Humberto; Jerrett, Michael; Northcross, Amanda; Olmedo, Luis; Seto, Edmund; Wilkie, Alexa; English, Paul

2018-01-01

Air pollution continues to be a global public health threat, and the expanding availability of small, low-cost air sensors has led to increased interest in both personal and crowd-sourced air monitoring. However, to date, few low-cost air monitoring networks have been developed with the scientific rigor or continuity needed to conduct public health surveillance and inform policy. In Imperial County, California, near the U.S./Mexico border, we used a collaborative, community-engaged process to develop a community air monitoring network that attains the scientific rigor required for research, while also achieving community priorities. By engaging community residents in the project design, monitor siting processes, data dissemination, and other key activities, the resulting air monitoring network data are relevant, trusted, understandable, and used by community residents. Integration of spatial analysis and air monitoring best practices into the network development process ensures that the data are reliable and appropriate for use in research activities. This combined approach results in a community air monitoring network that is better able to inform community residents, support research activities, guide public policy, and improve public health. Here we detail the monitor siting process and outline the advantages and challenges of this approach. PMID:29543726

Structure of the Social Support Network of Patients with Severe and Persistent Psychiatric Disorders in Follow-Ups to Primary Health Care.

PubMed

de Souza, Jacqueline; de Almeida, Letícia Yamawaka; Moll, Marciana Fernandes; Silva, Lucas Duarte; Ventura, Carla Aparecida Arena

2016-02-01

The objective of this study is to analyze the characteristics of social support networks of patients with psychiatric disorders at follow-up to primary care. This is a cross-sectional qualitative research study. Forty-five interviews were held with patients and their supporters. The results showed small and dense networks, with a strong emphasis on the bonds with formal supporters and a scant network of informal supporters. It is recommended to develop strategies to improve social support networks and use this as an outcome indicator related to social integration of these patients and to the quality of services involved with outpatient healthcare. Copyright © 2015 Elsevier Inc. All rights reserved.

Real Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie (Inventor); Oliver, Brett D. (Inventor); Brickner, Christopher (Inventor)

2013-01-01

A method for clock monitoring in a network is provided. The method comprises receiving a first network clock signal at a network device and comparing the first network clock signal to a local clock signal from a primary oscillator coupled to the network device.

Discovering Network Structure Beyond Communities

NASA Astrophysics Data System (ADS)

Nishikawa, Takashi; Motter, Adilson E.

2011-11-01

To understand the formation, evolution, and function of complex systems, it is crucial to understand the internal organization of their interaction networks. Partly due to the impossibility of visualizing large complex networks, resolving network structure remains a challenging problem. Here we overcome this difficulty by combining the visual pattern recognition ability of humans with the high processing speed of computers to develop an exploratory method for discovering groups of nodes characterized by common network properties, including but not limited to communities of densely connected nodes. Without any prior information about the nature of the groups, the method simultaneously identifies the number of groups, the group assignment, and the properties that define these groups. The results of applying our method to real networks suggest the possibility that most group structures lurk undiscovered in the fast-growing inventory of social, biological, and technological networks of scientific interest.

An empirical evaluation of lightweight random walk based routing protocol in duty cycle aware wireless sensor networks.

PubMed

Mian, Adnan Noor; Fatima, Mehwish; Khan, Raees; Prakash, Ravi

2014-01-01

Energy efficiency is an important design paradigm in Wireless Sensor Networks (WSNs) and its consumption in dynamic environment is even more critical. Duty cycling of sensor nodes is used to address the energy consumption problem. However, along with advantages, duty cycle aware networks introduce some complexities like synchronization and latency. Due to their inherent characteristics, many traditional routing protocols show low performance in densely deployed WSNs with duty cycle awareness, when sensor nodes are supposed to have high mobility. In this paper we first present a three messages exchange Lightweight Random Walk Routing (LRWR) protocol and then evaluate its performance in WSNs for routing low data rate packets. Through NS-2 based simulations, we examine the LRWR protocol by comparing it with DYMO, a widely used WSN protocol, in both static and dynamic environments with varying duty cycles, assuming the standard IEEE 802.15.4 in lower layers. Results for the three metrics, that is, reliability, end-to-end delay, and energy consumption, show that LRWR protocol outperforms DYMO in scalability, mobility, and robustness, showing this protocol as a suitable choice in low duty cycle and dense WSNs.

A high-resolution ambient seismic noise model for Europe

NASA Astrophysics Data System (ADS)

Kraft, Toni

2014-05-01

In the past several years, geological energy technologies receive growing attention and have been initiated in or close to urban areas. Some of these technologies involve injecting fluids into the subsurface (e.g., oil and gas development, waste disposal, and geothermal energy development) and have been found or suspected to cause small to moderate sized earthquakes. These earthquakes, which may have gone unnoticed in the past when they occurred in remote sparsely populated areas, are now posing a considerable risk for the public acceptance of these technologies in urban areas. The permanent termination of the EGS project in Basel, Switzerland after a number of induced ML~3 (minor) earthquakes in 2006 is one prominent example. It is therefore essential to the future development and success of these geological energy technologies to develop strategies for managing induced seismicity and keeping the size of induced earthquake at a level that is acceptable to all stakeholders. Most guidelines and recommendations on induced seismicity published since the 1970ies conclude that an indispensable component of such a strategy is the establishment of seismic monitoring in an early stage of a project. This is because an appropriate seismic monitoring is the only way to detect and locate induced microearthquakes with sufficient certainty to develop an understanding of the seismic and geomechanical response of the reservoir to the geotechnical operation. In addition, seismic monitoring lays the foundation for the establishment of advanced traffic light systems and is therefore an important confidence building measure towards the local population and authorities. Due to this development an increasing number of seismic monitoring networks are being installed in densely populated areas with strongly heterogeneous, and unfavorable ambient noise conditions. This poses a major challenge on the network design process, which aims to find the sensor geometry that optimizes the measurement precision (i.e. earthquake location), while considering this extremely complex boundary condition. To solve this problem I have developed a high-resolution ambient seismic noise model for Europe. The model is based on land-use data derived from satellite imagery by the EU-project CORINE in a resolution of 100x100m. The the CORINE data consists of several land-use classes, which, besides others, contain: industrial areas, mines, urban fabric, agricultural areas, permanent corps, forests and open spaces. Additionally, open GIS data for highways, and major and minor roads and railway lines were included from the OpenStreetMap project (www.openstreetmap.org). This data was divided into three classes that represent good, intermediate and bad ambient conditions of the corresponding land-use class based on expert judgment. To account for noise propagation away from its source a smoothing operator was applied to individual land-use noise-fields. Finally, the noise-fields were stacked to obtain an European map of ambient noise conditions. A calibration of this map with data of existing seismic stations Europe allowed me to estimate the expected noise level in actual ground motion units for the three ambient noise condition classes of the map. The result is a high-resolution ambient seismic noise map, that allows the network designer to make educated predictions on the expected noise level for arbitrary location in Europe. The ambient noise model was successfully tested in several network optimization projects in Switzerland and surrounding countries and will hopefully be a valuable contribution to improving the data quality of microseismic monitoring networks in Europe.

Region 7 States Air Quality Monitoring Plans - Iowa

EPA Pesticide Factsheets

National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo

Region 7 States Air Quality Monitoring Plans - Missouri

EPA Pesticide Factsheets

National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo

Region 7 States Air Quality Monitoring Plans - Nebraska

EPA Pesticide Factsheets

National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo

Region 7 States Air Quality Monitoring Plans - Kansas

EPA Pesticide Factsheets

National Ambient Air Quality Standard (NAAQS) - Iowa, Kansas, Missouri, and Nebraska; Annual Monitoring Network Plans, Five-Year Monitoring Network Assessments, and approval documentation. Each year, states are required to submit an annual monitoring netwo

Remote Energy Monitoring System via Cellular Network

NASA Astrophysics Data System (ADS)

Yunoki, Shoji; Tamaki, Satoshi; Takada, May; Iwaki, Takashi

Recently, improvement on power saving and cost efficiency by monitoring the operation status of various facilities over the network has gained attention. Wireless network, especially cellular network, has advantage in mobility, coverage, and scalability. On the other hand, it has disadvantage of low reliability, due to rapid changes in the available bandwidth. We propose a transmission control scheme based on data priority and instantaneous available bandwidth to realize a highly reliable remote monitoring system via cellular network. We have developed our proposed monitoring system and evaluated the effectiveness of our scheme, and proved it reduces the maximum transmission delay of sensor status to 1/10 compared to best effort transmission.

A network security monitor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heberlein, L.T.; Dias, G.V.; Levitt, K.N.

1989-11-01

The study of security in computer networks is a rapidly growing area of interest because of the proliferation of networks and the paucity of security measures in most current networks. Since most networks consist of a collection of inter-connected local area networks (LANs), this paper concentrates on the security-related issues in a single broadcast LAN such as Ethernet. Specifically, we formalize various possible network attacks and outline methods of detecting them. Our basic strategy is to develop profiles of usage of network resources and then compare current usage patterns with the historical profile to determine possible security violations. Thus, ourmore » work is similar to the host-based intrusion-detection systems such as SRI's IDES. Different from such systems, however, is our use of a hierarchical model to refine the focus of the intrusion-detection mechanism. We also report on the development of our experimental LAN monitor currently under implementation. Several network attacks have been simulated and results on how the monitor has been able to detect these attacks are also analyzed. Initial results demonstrate that many network attacks are detectable with our monitor, although it can surely be defeated. Current work is focusing on the integration of network monitoring with host-based techniques. 20 refs., 2 figs.« less

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.

PubMed

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.

Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks

PubMed Central

Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

2016-01-01

Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance. PMID:27006977

Optimal Base Station Density of Dense Network: From the Viewpoint of Interference and Load.

PubMed

Feng, Jianyuan; Feng, Zhiyong

2017-09-11

Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.

A user exposure based approach for non-structural road network vulnerability analysis

PubMed Central

Jin, Lei; Wang, Haizhong; Yu, Le; Liu, Lin

2017-01-01

Aiming at the dense urban road network vulnerability without structural negative consequences, this paper proposes a novel non-structural road network vulnerability analysis framework. Three aspects of the framework are mainly described: (i) the rationality of non-structural road network vulnerability, (ii) the metrics for negative consequences accounting for variant road conditions, and (iii) the introduction of a new vulnerability index based on user exposure. Based on the proposed methodology, a case study in the Sioux Falls network which was usually threatened by regular heavy snow during wintertime is detailedly discussed. The vulnerability ranking of links of Sioux Falls network with respect to heavy snow scenario is identified. As a result of non-structural consequences accompanied by conceivable degeneration of network, there are significant increases in generalized travel time costs which are measurements for “emotionally hurt” of topological road network. PMID:29176832

Locating sources within a dense sensor array using graph clustering

NASA Astrophysics Data System (ADS)

Gerstoft, P.; Riahi, N.

2017-12-01

We develop a model-free technique to identify weak sources within dense sensor arrays using graph clustering. No knowledge about the propagation medium is needed except that signal strengths decay to insignificant levels within a scale that is shorter than the aperture. We then reinterpret the spatial coherence matrix of a wave field as a matrix whose support is a connectivity matrix of a graph with sensors as vertices. In a dense network, well-separated sources induce clusters in this graph. The geographic spread of these clusters can serve to localize the sources. The support of the covariance matrix is estimated from limited-time data using a hypothesis test with a robust phase-only coherence test statistic combined with a physical distance criterion. The latter criterion ensures graph sparsity and thus prevents clusters from forming by chance. We verify the approach and quantify its reliability on a simulated dataset. The method is then applied to data from a dense 5200 element geophone array that blanketed of the city of Long Beach (CA). The analysis exposes a helicopter traversing the array and oil production facilities.

NSI operations center

NASA Technical Reports Server (NTRS)

Zanley, Nancy L.

1991-01-01

The NASA Science Internet (NSI) Network Operations Staff is responsible for providing reliable communication connectivity for the NASA science community. As the NSI user community expands, so does the demand for greater interoperability with users and resources on other networks (e.g., NSFnet, ESnet), both nationally and internationally. Coupled with the science community's demand for greater access to other resources is the demand for more reliable communication connectivity. Recognizing this, the NASA Science Internet Project Office (NSIPO) expands its Operations activities. By January 1990, Network Operations was equipped with a telephone hotline, and its staff was expanded to six Network Operations Analysts. These six analysts provide 24-hour-a-day, 7-day-a-week coverage to assist site managers with problem determination and resolution. The NSI Operations staff monitors network circuits and their associated routers. In most instances, NSI Operations diagnoses and reports problems before users realize a problem exists. Monitoring of the NSI TCP/IP Network is currently being done with Proteon's Overview monitoring system. The Overview monitoring system displays a map of the NSI network utilizing various colors to indicate the conditions of the components being monitored. Each node or site is polled via the Simple Network Monitoring Protocol (SNMP). If a circuit goes down, Overview alerts the Network Operations staff with an audible alarm and changes the color of the component. When an alert is received, Network Operations personnel immediately verify and diagnose the problem, coordinate repair with other networking service groups, track problems, and document problem and resolution into a trouble ticket data base. NSI Operations offers the NSI science community reliable connectivity by exercising prompt assessment and resolution of network problems.

Overview of the new National Near-Road Air Quality Monitoring Network

EPA Science Inventory

In 2010, EPA promulgated new National Ambient Air Quality Standards (NAAQS) for nitrogen dioxide (NO2). As part of this new NAAQS, EPA required the establishment of a national near-road air quality monitoring network. This network will consist of one NO2 near-road monitoring st...

Remote Sensing of Terrestrial Water Storage and Application to Drought Monitoring

NASA Technical Reports Server (NTRS)

Rodell, Matt

2007-01-01

Terrestrial water storage (TWS) consists of groundwater, soil moisture and permafrost, surface water, snow and ice, and wet biomass. TWS variability tends to be dominated by snow and ice in polar and alpine regions, by soil moisture in mid-latitudes, and by surface water in wet, tropical regions such as the Amazon (Rodell and Famiglietti, 2001; Bates et al., 2007). Drought may be defined as a period of abnormally dry weather long enough to cause significant deficits in one or more of the TWS components. Thus, along with observations of the agricultural and socioeconomic impacts, measurements of TWS and its components enable quantification of drought severity. Each of the TWS components exhibits significant spatial variability, while installation and maintenance of sufficiently dense monitoring networks is costly and labor-intensive. Thus satellite remote sensing is an appealing alternative to traditional measurement techniques. Several current remote sensing instruments are able to detect variations in one or more TWS variables, including the Advanced Microwave Scanning Radiometer (AMSR) on NASA's Aqua satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra and Aqua. Future satellite missions have been proposed to improve this capability, including the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and the Soil Moisture Active Passive (SMAP), Surface Water Ocean Topography (SWOT), and Snow and Cold Land Processes (SCLP) missions recommended by the US National Academy of Science's Decadal Survey for Earth Science (NRC, 2007). However, only one remote sensing technology is able to monitor changes in TWS from the land surface to the base of the deepest aquifer: satellite gravimetry. This paper focuses on NASA's Gravity Recovery and Climate Experiment mission (GRACE; http://www.csr.utexas.edu/grace/) and its potential as a tool for drought monitoring.

Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

PubMed Central

Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

2014-01-01

In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

A New Network Modeling Tool for the Ground-based Nuclear Explosion Monitoring Community

NASA Astrophysics Data System (ADS)

Merchant, B. J.; Chael, E. P.; Young, C. J.

2013-12-01

Network simulations have long been used to assess the performance of monitoring networks to detect events for such purposes as planning station deployments and network resilience to outages. The standard tool has been the SAIC-developed NetSim package. With correct parameters, NetSim can produce useful simulations; however, the package has several shortcomings: an older language (FORTRAN), an emphasis on seismic monitoring with limited support for other technologies, limited documentation, and a limited parameter set. Thus, we are developing NetMOD (Network Monitoring for Optimal Detection), a Java-based tool designed to assess the performance of ground-based networks. NetMOD's advantages include: coded in a modern language that is multi-platform, utilizes modern computing performance (e.g. multi-core processors), incorporates monitoring technologies other than seismic, and includes a well-validated default parameter set for the IMS stations. NetMOD is designed to be extendable through a plugin infrastructure, so new phenomenological models can be added. Development of the Seismic Detection Plugin is being pursued first. Seismic location and infrasound and hydroacoustic detection plugins will follow. By making NetMOD an open-release package, it can hopefully provide a common tool that the monitoring community can use to produce assessments of monitoring networks and to verify assessments made by others.

Compliance Groundwater Monitoring of Nonpoint Sources - Emerging Approaches

NASA Astrophysics Data System (ADS)

Harter, T.

2008-12-01

Groundwater monitoring networks are typically designed for regulatory compliance of discharges from industrial sites. There, the quality of first encountered (shallow-most) groundwater is of key importance. Network design criteria have been developed for purposes of determining whether an actual or potential, permitted or incidental waste discharge has had or will have a degrading effect on groundwater quality. The fundamental underlying paradigm is that such discharge (if it occurs) will form a distinct contamination plume. Networks that guide (post-contamination) mitigation efforts are designed to capture the shape and dynamics of existing, finite-scale plumes. In general, these networks extend over areas less than one to ten hectare. In recent years, regulatory programs such as the EU Nitrate Directive and the U.S. Clean Water Act have forced regulatory agencies to also control groundwater contamination from non-incidental, recharging, non-point sources, particularly agricultural sources (fertilizer, pesticides, animal waste application, biosolids application). Sources and contamination from these sources can stretch over several tens, hundreds, or even thousands of square kilometers with no distinct plumes. A key question in implementing monitoring programs at the local, regional, and national level is, whether groundwater monitoring can be effectively used as a landowner compliance tool, as is currently done at point-source sites. We compare the efficiency of such traditional site-specific compliance networks in nonpoint source regulation with various designs of regional nonpoint source monitoring networks that could be used for compliance monitoring. We discuss advantages and disadvantages of the site vs. regional monitoring approaches with respect to effectively protecting groundwater resources impacted by nonpoint sources: Site-networks provide a tool to enforce compliance by an individual landowner. But the nonpoint source character of the contamination and its typically large spatial extend requires extensive networks at an individual site to accurately and fairly monitor individual compliance. In contrast, regional networks seemingly fail to hold individual landowners accountable. But regional networks can effectively monitor large-scale impacts and water quality trends; and thus inform regulatory programs that enforce management practices tied to nonpoint source pollution. Regional monitoring networks for compliance purposes can face significant challenges in the implementation due to a regulatory and legal landscape that is exclusively structured to address point sources and individual liability, and due to the non-intensive nature of a regional monitoring program (lack of control of hot spots; lack of accountability of individual landowners).

Computation and Learning in Neural Networks With Binary Weights

DTIC Science & Technology

1992-11-28

alternatively, the total number of component updates before convergence is 0(n 3 ). We follow this with an average case analysis, similar in flavour to...anecdotal evidence in support of it in ’Well, maybe an imp. I I situations where the network has a more "distributed" flavour with relatively dense...Within the hipocampus, there is a three stage sequence of processing consisting of granule cells (which 3 receive from the entorhinal cortex), the CA3

Network monitoring in the Tier2 site in Prague

NASA Astrophysics Data System (ADS)

Eliáš, Marek; Fiala, Lukáš; Horký, Jiří; Chudoba, Jiří; Kouba, Tomáš; Kundrát, Jan; Švec, Jan

2011-12-01

Network monitoring provides different types of view on the network traffic. It's output enables computing centre staff to make qualified decisions about changes in the organization of computing centre network and to spot possible problems. In this paper we present network monitoring framework used at Tier-2 in Prague in Institute of Physics (FZU). The framework consists of standard software and custom tools. We discuss our system for hardware failures detection using syslog logging and Nagios active checks, bandwidth monitoring of physical links and analysis of NetFlow exports from Cisco routers. We present tool for automatic detection of network layout based on SNMP. This tool also records topology changes into SVN repository. Adapted weathermap4rrd is used to visualize recorded data to get fast overview showing current bandwidth usage of links in network.

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of monitoring network design.

Self-diffusion in dense granular shear flows.

PubMed

Utter, Brian; Behringer, R P

2004-03-01

Diffusivity is a key quantity in describing velocity fluctuations in granular materials. These fluctuations are the basis of many thermodynamic and hydrodynamic models which aim to provide a statistical description of granular systems. We present experimental results on diffusivity in dense, granular shear flows in a two-dimensional Couette geometry. We find that self-diffusivities D are proportional to the local shear rate gamma; with diffusivities along the direction of the mean flow approximately twice as large as those in the perpendicular direction. The magnitude of the diffusivity is D approximately gamma;a(2), where a is the particle radius. However, the gradient in shear rate, coupling to the mean flow, and strong drag at the moving boundary lead to particle displacements that can appear subdiffusive or superdiffusive. In particular, diffusion appears to be superdiffusive along the mean flow direction due to Taylor dispersion effects and subdiffusive along the perpendicular direction due to the gradient in shear rate. The anisotropic force network leads to an additional anisotropy in the diffusivity that is a property of dense systems and has no obvious analog in rapid flows. Specifically, the diffusivity is suppressed along the direction of the strong force network. A simple random walk simulation reproduces the key features of the data, such as the apparent superdiffusive and subdiffusive behavior arising from the mean velocity field, confirming the underlying diffusive motion. The additional anisotropy is not observed in the simulation since the strong force network is not included. Examples of correlated motion, such as transient vortices, and Lévy flights are also observed. Although correlated motion creates velocity fields which are qualitatively different from collisional Brownian motion and can introduce nondiffusive effects, on average the system appears simply diffusive.

Implementation of medical monitor system based on networks

NASA Astrophysics Data System (ADS)

Yu, Hui; Cao, Yuzhen; Zhang, Lixin; Ding, Mingshi

2006-11-01

In this paper, the development trend of medical monitor system is analyzed and portable trend and network function become more and more popular among all kinds of medical monitor devices. The architecture of medical network monitor system solution is provided and design and implementation details of medical monitor terminal, monitor center software, distributed medical database and two kind of medical information terminal are especially discussed. Rabbit3000 system is used in medical monitor terminal to implement security administration of data transfer on network, human-machine interface, power management and DSP interface while DSP chip TMS5402 is used in signal analysis and data compression. Distributed medical database is designed for hospital center according to DICOM information model and HL7 standard. Pocket medical information terminal based on ARM9 embedded platform is also developed to interactive with center database on networks. Two kernels based on WINCE are customized and corresponding terminal software are developed for nurse's routine care and doctor's auxiliary diagnosis. Now invention patent of the monitor terminal is approved and manufacture and clinic test plans are scheduled. Applications for invention patent are also arranged for two medical information terminals.

Prediction-based association control scheme in dense femtocell networks

PubMed Central

Pham, Ngoc-Thai; Huynh, Thong; Hwang, Won-Joo; You, Ilsun; Choo, Kim-Kwang Raymond

2017-01-01

The deployment of large number of femtocell base stations allows us to extend the coverage and efficiently utilize resources in a low cost manner. However, the small cell size of femtocell networks can result in frequent handovers to the mobile user, and consequently throughput degradation. Thus, in this paper, we propose predictive association control schemes to improve the system’s effective throughput. Our design focuses on reducing handover frequency without impacting on throughput. The proposed schemes determine handover decisions that contribute most to the network throughput and are proper for distributed implementations. The simulation results show significant gains compared with existing methods in terms of handover frequency and network throughput perspective. PMID:28328992

Network Monitor and Control of Disruption-Tolerant Networks

NASA Technical Reports Server (NTRS)

Torgerson, J. Leigh

2014-01-01

For nearly a decade, NASA and many researchers in the international community have been developing Internet-like protocols that allow for automated network operations in networks where the individual links between nodes are only sporadically connected. A family of Disruption-Tolerant Networking (DTN) protocols has been developed, and many are reaching CCSDS Blue Book status. A NASA version of DTN known as the Interplanetary Overlay Network (ION) has been flight-tested on the EPOXI spacecraft and ION is currently being tested on the International Space Station. Experience has shown that in order for a DTN service-provider to set up a large scale multi-node network, a number of network monitor and control technologies need to be fielded as well as the basic DTN protocols. The NASA DTN program is developing a standardized means of querying a DTN node to ascertain its operational status, known as the DTN Management Protocol (DTNMP), and the program has developed some prototypes of DTNMP software. While DTNMP is a necessary component, it is not sufficient to accomplish Network Monitor and Control of a DTN network. JPL is developing a suite of tools that provide for network visualization, performance monitoring and ION node control software. This suite of network monitor and control tools complements the GSFC and APL-developed DTN MP software, and the combined package can form the basis for flight operations using DTN.

Contagion on complex networks with persuasion

NASA Astrophysics Data System (ADS)

Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

2016-03-01

The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

Contagion on complex networks with persuasion

PubMed Central

Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

2016-01-01

The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense. PMID:27029498

Contagion on complex networks with persuasion.

PubMed

Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

2016-03-31

The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

Exploration of the integration of care for persons with a traumatic brain injury using social network analysis methodology

PubMed Central

Lamontagne, Marie-Eve

2013-01-01

Introduction Integration is a popular strategy to increase the quality of care within systems of care. However, there is no common language, approach or tool allowing for a valid description, comparison and evaluation of integrated care. Social network analysis could be a viable methodology to provide an objective picture of integrated networks. Goal of the article To illustrate social network analysis use in the context of systems of care for traumatic brain injury. Method We surveyed members of a network using a validated questionnaire to determine the links between them. We determined the density, centrality, multiplexity, and quality of the links reported. Results The network was described as moderately dense (0.6), the most prevalent link was knowledge, and four organisation members of a consortium were central to the network. Social network analysis allowed us to create a graphic representation of the network. Conclusion Social network analysis is a useful methodology to objectively characterise integrated networks. PMID:24250281

Glyph-based generic network visualization

NASA Astrophysics Data System (ADS)

Erbacher, Robert F.

2002-03-01

Network managers and system administrators have an enormous task set before them in this day of growing network usage. This is particularly true of e-commerce companies and others dependent on a computer network for their livelihood. Network managers and system administrators must monitor activity for intrusions and misuse while at the same time monitoring performance of the network. In this paper, we describe our visualization techniques for assisting in the monitoring of networks for both of these tasks. The goal of these visualization techniques is to integrate the visual representation of both network performance/usage as well as data relevant to intrusion detection. The main difficulties arise from the difference in the intrinsic data and layout needs of each of these tasks. Glyph based techniques are additionally used to indicate the representative values of the necessary data parameters over time. Additionally, our techniques are geared towards providing an environment that can be used continuously for constant real-time monitoring of the network environment.

Software Defined Network Monitoring Scheme Using Spectral Graph Theory and Phantom Nodes

DTIC Science & Technology

2014-09-01

networks is the emergence of software - defined networking ( SDN ) [1]. SDN has existed for the...Chapter III for network monitoring. A. SOFTWARE DEFINED NETWORKS SDNs provide a new and innovative method to simplify network hardware by logically...and R. Giladi, “Performance analysis of software - defined networking ( SDN ),” in Proc. of IEEE 21st International Symposium on Modeling, Analysis

Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.

Active volcanoes observed through Art: the contribution offered by the social networks

NASA Astrophysics Data System (ADS)

Neri, Marco; Neri, Emilia

2015-04-01

Volcanoes have always fascinated people for the wild beauty of their landscapes and also for the fear that they arouse with their eruptive actions, sometimes simply spectacular, but other times terrifying and catastrophic for human activities. In the past, volcanoes were sometimes imagined as a metaphysical gateway to the otherworld; they have inspired the creation of myths and legends ever since three thousand years ago, also represented by paintings of great artistic impact. Modern technology today offers very sophisticated and readily accessed digital tools, and volcanoes continue to be frequently photographed and highly appreciated natural phenomena. Moreover, in recent years, the spread of social networks (Facebook, Twitter, YouTube, Instagram, etc.) have made the widespread dissemination of graphic contributions even easier. The result is that very active and densely inhabited volcanoes such as Etna, Vesuvius and Aeolian Islands, in Italy, have become among the most photographed subjects in the world, providing a popular science tool with formidable influence and usefulness. The beauty of these landscapes have inspired both professional artists and photographers, as well as amateurs, who compete in the social networks for the publication of the most spectacular, artistic or simply most informative images. The end result of this often frantic popular scientific activity is at least two-fold: on one hand, it provides geoscientists and science communicators a quantity of documentation that is almost impossible to acquire through the normal systems of volcano monitoring, while on the other it raises awareness and respect for the land among the civil community.

Ground Motion Prediction Equations for Western Saudi Arabia from a Reference Model

NASA Astrophysics Data System (ADS)

Kiuchi, R.; Mooney, W. D.; Mori, J. J.; Zahran, H. M.; Al-Raddadi, W.; Youssef, S.

2017-12-01

Western Saudi Arabia is surrounded by several active seismic zones such as the Red Sea and the Gulf of Aqaba where a destructive magnitude 7.3 event occurred in 1995. Over the last decade, the Saudi Geological Survey (SGS) has deployed a dense seismic network that has made it possible to monitor seismic activity more accurately. For example, the network has detected multiple seismic swarms beneath the volcanic fields in western Saudi Arabia. The most recent damaging event was a M5.7 earthquake that occurred in 2009 at Harrat Lunayyir. In terms of seismic hazard assessment, Zahran et al. (2015; 2016) presented a Probabilistic Seismic Hazard Assessment (PSHA) for western Saudi Arabia that was developed using published Ground Motion Prediction Equations (GMPEs) from areas outside of Saudi Arabia. In this study, we consider 41 earthquakes of M 3.0 - 5.4, recorded on 124 stations of the SGS network, to create a set of 442 peak ground acceleration (PGA) and peak ground velocity (PGV) records with a range of epicentral distances from 3 km to 400 km. We use the GMPE model BSSA14 (Boore et al., 2014) as a reference model to estimate our own best-fitting coefficients from a regression analysis using the events occurred in western Saudi Arabia. For epicentral distances less than 100 km, our best fitting model has different source scaling in comparison with the GMPE of BSSA14 adjusted for the California region. In addition, our model indicates that the peak amplitudes have less attenuation in western Saudi Arabia than in California.

Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission

NASA Astrophysics Data System (ADS)

Coopersmith, E. J.; Cosh, M. H.

2014-12-01

NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each ­in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.

A Great Lakes atmospheric mercury monitoring network: evaluation and design

USGS Publications Warehouse

Risch, Martin R.; Kenski, Donna M.; ,; David, A.

2014-01-01

As many as 51 mercury (Hg) wet-deposition-monitoring sites from 4 networks were operated in 8 USA states and Ontario, Canada in the North American Great Lakes Region from 1996 to 2010. By 2013, 20 of those sites were no longer in operation and approximately half the geographic area of the Region was represented by a single Hg-monitoring site. In response, a Great Lakes Atmospheric Mercury Monitoring (GLAMM) network is needed as a framework for regional collaboration in Hg-deposition monitoring. The purpose of the GLAMM network is to detect changes in regional atmospheric Hg deposition related to changes in Hg emissions. An optimized design for the network was determined to be a minimum of 21 sites in a representative and approximately uniform geographic distribution. A majority of the active and historic Hg-monitoring sites in the Great Lakes Region are part of the National Atmospheric Deposition Program (NADP) Mercury Deposition Network (MDN) in North America and the GLAMM network is planned to be part of the MDN. To determine an optimized network design, active and historic Hg-monitoring sites in the Great Lakes Region were evaluated with a rating system of 21 factors that included characteristics of the monitoring locations and interpretations of Hg data. Monitoring sites were rated according to the number of Hg emissions sources and annual Hg emissions in a geographic polygon centered on each site. Hg-monitoring data from the sites were analyzed for long-term averages in weekly Hg concentrations in precipitation and weekly Hg-wet deposition, and on significant temporal trends in Hg concentrations and Hg deposition. A cluster analysis method was used to group sites with similar variability in their Hg data in order to identify sites that were unique for explaining Hg data variability in the Region. The network design included locations in protected natural areas, urban areas, Great Lakes watersheds, and in proximity to areas with a high density of annual Hg emissions and areas with high average weekly Hg wet deposition. In a statistical analysis, relatively strong, positive correlations in the wet deposition of Hg and sulfate were shown for co-located NADP Hg-monitoring and acid-rain monitoring sites in the Region. This finding indicated that efficiency in regional Hg monitoring can be improved by adding new Hg monitoring to existing NADP acid-rain monitoring sites. Implementation of the GLAMM network design will require Hg-wet-deposition monitoring to be: (a) continued at 12 MDN sites active in 2013 and (b) restarted or added at 9 NADP sites where it is absent in 2013. Ongoing discussions between the states in the Great Lakes Region, the Lake Michigan Air Directors Consortium (a regional planning entity), the NADP, the U.S. Environmental Protection Agency, and the U.S. Geological Survey are needed for coordinating the GLAMM network.

Evaluating Dense 3d Reconstruction Software Packages for Oblique Monitoring of Crop Canopy Surface

NASA Astrophysics Data System (ADS)

Brocks, S.; Bareth, G.

2016-06-01

Crop Surface Models (CSMs) are 2.5D raster surfaces representing absolute plant canopy height. Using multiple CMSs generated from data acquired at multiple time steps, a crop surface monitoring is enabled. This makes it possible to monitor crop growth over time and can be used for monitoring in-field crop growth variability which is useful in the context of high-throughput phenotyping. This study aims to evaluate several software packages for dense 3D reconstruction from multiple overlapping RGB images on field and plot-scale. A summer barley field experiment located at the Campus Klein-Altendorf of University of Bonn was observed by acquiring stereo images from an oblique angle using consumer-grade smart cameras. Two such cameras were mounted at an elevation of 10 m and acquired images for a period of two months during the growing period of 2014. The field experiment consisted of nine barley cultivars that were cultivated in multiple repetitions and nitrogen treatments. Manual plant height measurements were carried out at four dates during the observation period. The software packages Agisoft PhotoScan, VisualSfM with CMVS/PMVS2 and SURE are investigated. The point clouds are georeferenced through a set of ground control points. Where adequate results are reached, a statistical analysis is performed.

Ambient changes in tracer concentrations from a multilevel monitoring system in Basalt

USGS Publications Warehouse

Bartholomay, Roy C.; Twining, Brian V.; Rose, Peter E.

2014-01-01

Starting in 2008, a 4-year tracer study was conducted to evaluate ambient changes in groundwater concentrations of a 1,3,6-naphthalene trisulfonate tracer that was added to drill water. Samples were collected under open borehole conditions and after installing a multilevel groundwater monitoring system completed with 11 discrete monitoring zones within dense and fractured basalt and sediment layers in the eastern Snake River aquifer. The study was done in cooperation with the U.S. Department of Energy to test whether ambient fracture flow conditions were sufficient to remove the effects of injected drill water prior to sample collection. Results from thief samples indicated that the tracer was present in minor concentrations 28 days after coring, but was not present 6 months after coring or 7 days after reaming the borehole. Results from sampling the multilevel monitoring system indicated that small concentrations of the tracer remained in 5 of 10 zones during some period after installation. All concentrations were several orders of magnitude lower than the initial concentrations in the drill water. The ports that had remnant concentrations of the tracer were either located near sediment layers or were located in dense basalt, which suggests limited groundwater flow near these ports. The ports completed in well-fractured and vesicular basalt had no detectable concentrations.

Dyadic Interactions in Service Encounter: Bayesian SEM Approach

NASA Astrophysics Data System (ADS)

Sagan, Adam; Kowalska-Musiał, Magdalena

Dyadic interactions are an important aspects in service encounters. They may be observed in B2B distribution channels, professional services, buying centers, family decision making or WOM communications. The networks consist of dyadic bonds that form dense but weak ties among the actors.

Application distribution model and related security attacks in VANET

NASA Astrophysics Data System (ADS)

Nikaein, Navid; Kanti Datta, Soumya; Marecar, Irshad; Bonnet, Christian

2013-03-01

In this paper, we present a model for application distribution and related security attacks in dense vehicular ad hoc networks (VANET) and sparse VANET which forms a delay tolerant network (DTN). We study the vulnerabilities of VANET to evaluate the attack scenarios and introduce a new attacker`s model as an extension to the work done in [6]. Then a VANET model has been proposed that supports the application distribution through proxy app stores on top of mobile platforms installed in vehicles. The steps of application distribution have been studied in detail. We have identified key attacks (e.g. malware, spamming and phishing, software attack and threat to location privacy) for dense VANET and two attack scenarios for sparse VANET. It has been shown that attacks can be launched by distributing malicious applications and injecting malicious codes to On Board Unit (OBU) by exploiting OBU software security holes. Consequences of such security attacks have been described. Finally, countermeasures including the concepts of sandbox have also been presented in depth.

Using Network Theory to Understand Seismic Noise in Dense Arrays

NASA Astrophysics Data System (ADS)

Riahi, N.; Gerstoft, P.

2015-12-01

Dense seismic arrays offer an opportunity to study anthropogenic seismic noise sources with unprecedented detail. Man-made sources typically have high frequency, low intensity, and propagate as surface waves. As a result attenuation restricts their measurable footprint to a small subset of sensors. Medium heterogeneities can further introduce wave front perturbations that limit processing based on travel time. We demonstrate a non-parametric technique that can reliably identify very local events within the array as a function of frequency and time without using travel-times. The approach estimates the non-zero support of the array covariance matrix and then uses network analysis tools to identify clusters of sensors that are sensing a common source. We verify the method on simulated data and then apply it to the Long Beach (CA) geophone array. The method exposes a helicopter traversing the array, oil production facilities with different characteristics, and the fact that noise sources near roads tend to be around 10-20 Hz.

Low latency network and distributed storage for next generation HPC systems: the ExaNeSt project

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Cretaro, P.; Frezza, O.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Paolucci, P. S.; Pastorelli, E.; Pisani, F.; Simula, F.; Vicini, P.; Navaridas, J.; Chaix, F.; Chrysos, N.; Katevenis, M.; Papaeustathiou, V.

2017-10-01

With processor architecture evolution, the HPC market has undergone a paradigm shift. The adoption of low-cost, Linux-based clusters extended the reach of HPC from its roots in modelling and simulation of complex physical systems to a broader range of industries, from biotechnology, cloud computing, computer analytics and big data challenges to manufacturing sectors. In this perspective, the near future HPC systems can be envisioned as composed of millions of low-power computing cores, densely packed — meaning cooling by appropriate technology — with a tightly interconnected, low latency and high performance network and equipped with a distributed storage architecture. Each of these features — dense packing, distributed storage and high performance interconnect — represents a challenge, made all the harder by the need to solve them at the same time. These challenges lie as stumbling blocks along the road towards Exascale-class systems; the ExaNeSt project acknowledges them and tasks itself with investigating ways around them.

Spatial evolutionary public goods game on complete graph and dense complex networks

NASA Astrophysics Data System (ADS)

Kim, Jinho; Chae, Huiseung; Yook, Soon-Hyung; Kim, Yup

2015-03-01

We study the spatial evolutionary public goods game (SEPGG) with voluntary or optional participation on a complete graph (CG) and on dense networks. Based on analyses of the SEPGG rate equation on finite CG, we find that SEPGG has two stable states depending on the value of multiplication factor r, illustrating how the ``tragedy of the commons'' and ``an anomalous state without any active participants'' occurs in real-life situations. When r is low (), the state with only loners is stable, and the state with only defectors is stable when r is high (). We also derive the exact scaling relation for r*. All of the results are confirmed by numerical simulation. Furthermore, we find that a cooperator-dominant state emerges when the number of participants or the mean degree, , decreases. We also investigate the scaling dependence of the emergence of cooperation on r and . These results show how ``tragedy of the commons'' disappears when cooperation between egoistic individuals without any additional socioeconomic punishment increases.

Low, slow, small target recognition based on spatial vision network

NASA Astrophysics Data System (ADS)

Cheng, Zhao; Guo, Pei; Qi, Xin

2018-03-01

Traditional photoelectric monitoring is monitored using a large number of identical cameras. In order to ensure the full coverage of the monitoring area, this monitoring method uses more cameras, which leads to more monitoring and repetition areas, and higher costs, resulting in more waste. In order to reduce the monitoring cost and solve the difficult problem of finding, identifying and tracking a low altitude, slow speed and small target, this paper presents spatial vision network for low-slow-small targets recognition. Based on camera imaging principle and monitoring model, spatial vision network is modeled and optimized. Simulation experiment results demonstrate that the proposed method has good performance.

A Model for Field Deployment of Wireless Sensor Networks (WSNs) within the Domain of Microclimate Habitat Monitoring

ERIC Educational Resources Information Center

Sanborn, Mark

2011-01-01

Wireless sensor networks (WSNs) represent a class of miniaturized information systems designed to monitor physical environments. These smart monitoring systems form collaborative networks utilizing autonomous sensing, data-collection, and processing to provide real-time analytics of observed environments. As a fundamental research area in…

An Intelligent Monitoring Network for Detection of Cracks in Anvils of High-Press Apparatus.

PubMed

Tian, Hao; Yan, Zhaoli; Yang, Jun

2018-04-09

Due to the endurance of alternating high pressure and temperature, the carbide anvils of the high-press apparatus, which are widely used in the synthetic diamond industry, are prone to crack. In this paper, an acoustic method is used to monitor the crack events, and the intelligent monitoring network is proposed to classify the sound samples. The pulse sound signals produced by such cracking are first extracted based on a short-time energy threshold. Then, the signals are processed with the proposed intelligent monitoring network to identify the operation condition of the anvil of the high-pressure apparatus. The monitoring network is an improved convolutional neural network that solves the problems that may occur in practice. The length of pulse sound excited by the crack growth is variable, so a spatial pyramid pooling layer is adopted to solve the variable-length input problem. An adaptive weighted algorithm for loss function is proposed in this method to handle the class imbalance problem. The good performance regarding the accuracy and balance of the proposed intelligent monitoring network is validated through the experiments finally.

Development of Download System for Waveform Data Observed at Long-Term Borehole Monitoring System installed in the Nankai Trough

NASA Astrophysics Data System (ADS)

Tsuboi, Seiji; Horikawa, Hiroki; Takaesu, Morifumi; Sueki, Kentaro; Araki, Eiichiro; Sonoda, Akira; Takahashi, Narumi

2016-04-01

The Nankai Trough in southwest Japan is one of most active subduction zone in the world. Great mega-thrust earthquakes repeatedly occurred every 100 to 150 years in this area, it's anticipated to occur in the not distant future. For the purpose of elucidation of the history of mega-splay fault activity, the physical properties of the geological strata and the internal structure of the accretionary prism, and monitoring of diastrophism in this area, we have a plan, Nankai Trough Seismogenic Zone Experiments (NanTroSEIZE), as a part of Integrated Ocean Drilling Program (IODP). We have a plan to install the borehole observation system in a few locations by the NanTroSEIZE. This system is called Long-Term Borehole Monitoring System, it consists of various sensors in the borehole such as a broadband seismometer, a tiltmeter, a strainmeter, geophones and accelerometer, thermometer array as well as pressure ports for pore-fluid pressure monitoring. The signal from sensors is transmitted to DONET (Dense Ocean-floor Network System for Earthquake and Tsunamis) in real time. During IODP Exp. 332 in December 2010, the first Long-Term Borehole Monitoring System was installed into the C0002 borehole site located 80 km off the Kii Peninsula, 1938 m water depth in the Nankai Trough. We have developed a web application system for data download, Long-Term Borehole Monitoring Data Site. Based on a term and sensors which user selected on this site, user can download monitoring waveform data (e.g. broadband seismometer data, accelerometer data, strainmeter data, tiltmeter data) in near real-time. This system can make the arbitrary data which user selected a term and sensors, and download it simply. Downloadable continuous data is provided in seed format, which includes sensor informations. In addition, before data download, user can check that data is abailable or not by data check function. In this presentation, we show our web application system and discuss our future plans for developments of monitoring data download system.

Promoting Social Network Awareness: A Social Network Monitoring System

ERIC Educational Resources Information Center

Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

2010-01-01

To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

Research and realization implementation of monitor technology on illegal external link of classified computer

NASA Astrophysics Data System (ADS)

Zhang, Hong

2017-06-01

In recent years, with the continuous development and application of network technology, network security has gradually entered people's field of vision. The host computer network external network of violations is an important reason for the threat of network security. At present, most of the work units have a certain degree of attention to network security, has taken a lot of means and methods to prevent network security problems such as the physical isolation of the internal network, install the firewall at the exit. However, these measures and methods to improve network security are often not comply with the safety rules of human behavior damage. For example, the host to wireless Internet access and dual-network card to access the Internet, inadvertently formed a two-way network of external networks and computer connections [1]. As a result, it is possible to cause some important documents and confidentiality leak even in the the circumstances of user unaware completely. Secrecy Computer Violation Out-of-band monitoring technology can largely prevent the violation by monitoring the behavior of the offending connection. In this paper, we mainly research and discuss the technology of secret computer monitoring.

Sociometric network structure and its association with methamphetamine use norms among homeless youth

PubMed Central

Barman-Adhikari, Anamika; Begun, Stephanie; Rice, Eric; Yoshioka-Maxwell, Amanda; Perez-Portillo, Andrea

2016-01-01

Homeless youths' social networks are consistently linked with their substance use. Social networks influence behavior through several mechanisms, especially social norms. This study used sociometric analyses to understand whether social norms of drug use behaviors are clustered in network structures and whether these perceived norms (descriptive and injunctive) influence youths' drug use behaviors. An event-based approach was used to delineate boundaries of the two sociometric networks of homeless youth, one in Los Angeles, CA (n = 160) and the other in Santa Monica, CA (n = 130). Network characteristics included centrality (i.e., popularity) and cohesiveness (location in dense subnetworks). The primary outcome was recent methamphetamine use. Results revealed that both descriptive and injunctive norms influenced methamphetamine use. Network cohesion was found to be associated with perception of both descriptive and injunctive norms in both networks, however in opposite directions. Network interventions therefore might be effective if designed to capitalize on social influence that naturally occurs in cohesive parts of networks. PMID:27194667

Short-term memory capacity in networks via the restricted isometry property.

PubMed

Charles, Adam S; Yap, Han Lun; Rozell, Christopher J

2014-06-01

Cortical networks are hypothesized to rely on transient network activity to support short-term memory (STM). In this letter, we study the capacity of randomly connected recurrent linear networks for performing STM when the input signals are approximately sparse in some basis. We leverage results from compressed sensing to provide rigorous nonasymptotic recovery guarantees, quantifying the impact of the input sparsity level, the input sparsity basis, and the network characteristics on the system capacity. Our analysis demonstrates that network memory capacities can scale superlinearly with the number of nodes and in some situations can achieve STM capacities that are much larger than the network size. We provide perfect recovery guarantees for finite sequences and recovery bounds for infinite sequences. The latter analysis predicts that network STM systems may have an optimal recovery length that balances errors due to omission and recall mistakes. Furthermore, we show that the conditions yielding optimal STM capacity can be embodied in several network topologies, including networks with sparse or dense connectivities.

Network for minimizing current imbalances in a faradaic battery

DOEpatents

Wozniak, Walter; Haskins, Harold J.

1994-01-01

A circuit for connecting a faradaic battery with circuitry for monitoring the condition of the battery includes a plurality of voltage divider networks providing battery voltage monitoring nodes and includes compensating resistors connected with the networks to maintain uniform discharge currents through the cells of the battery. The circuit also provides a reduced common mode voltage requirement for the monitoring circuitry by referencing the divider networks to one-half the battery voltage.

Optimal design of monitoring networks for multiple groundwater quality parameters using a Kalman filter: application to the Irapuato-Valle aquifer.

PubMed

Júnez-Ferreira, H E; Herrera, G S; González-Hita, L; Cardona, A; Mora-Rodríguez, J

2016-01-01

A new method for the optimal design of groundwater quality monitoring networks is introduced in this paper. Various indicator parameters were considered simultaneously and tested for the Irapuato-Valle aquifer in Mexico. The steps followed in the design were (1) establishment of the monitoring network objectives, (2) definition of a groundwater quality conceptual model for the study area, (3) selection of the parameters to be sampled, and (4) selection of a monitoring network by choosing the well positions that minimize the estimate error variance of the selected indicator parameters. Equal weight for each parameter was given to most of the aquifer positions and a higher weight to priority zones. The objective for the monitoring network in the specific application was to obtain a general reconnaissance of the water quality, including water types, water origin, and first indications of contamination. Water quality indicator parameters were chosen in accordance with this objective, and for the selection of the optimal monitoring sites, it was sought to obtain a low-uncertainty estimate of these parameters for the entire aquifer and with more certainty in priority zones. The optimal monitoring network was selected using a combination of geostatistical methods, a Kalman filter and a heuristic optimization method. Results show that when monitoring the 69 locations with higher priority order (the optimal monitoring network), the joint average standard error in the study area for all the groundwater quality parameters was approximately 90 % of the obtained with the 140 available sampling locations (the set of pilot wells). This demonstrates that an optimal design can help to reduce monitoring costs, by avoiding redundancy in data acquisition.

Discriminating different type waves from pressure and ground motion observation in the seafloor by DONET cabled observation network.

NASA Astrophysics Data System (ADS)

Araki, E.; Kawaguchi, K.; Kaneda, Y.

2011-12-01

We developed and deployed seafloor cabled observatory called "Dense Ocean-floor Network for Earthquake and Tsunamis (DONET)" in the Nankai Trough, south of Japan. The main purpose of the DONET network is to observe large earthquake such as Tonankai earthquake in the deployed seafloor and associate Tsunamis in real-time to help disaster mitigation, and as well to monitor inter-seismic crustal activities such as micro earthquakes, very low frequency earthquakes, and slower crustal deformation. In each DONET seafloor observatory, high-sensitive broadband set of instruments for seismic and seafloor pressure monitoring, consisted from Guralp CMG3T broadband seismometer, Metrozet TSA100S accelerometer, Paroscientific 8B7000-2 pressure gauge, a deep-sea differential pressure gauge, a hydrophone, and a seawater thermometer, are installed. The density of seafloor observatories are 20 observatories distributed in 15-30 km interval which is optimized for monitoring of events in the plate boundary beneath the network. DONET may be regarded as a large-scale, high sensitive high density seismic array for monitoring teleseismic events in the Philippine Sea and the Pacific Ocean. The DONET seafloor observatories are situated in wide range of seafloor depth between 1800m and 4500m, from the seafloor basin about 50 km off Japanese Island through the slope of accerecionary prism to the deep trench axis 150 km off the coast, that may also regarded as a vertical array in the 4.5km thick ocean. This variation of depths helps identify T-phases from the array record. In data analysis, it is necessary to identify propagation mode of each observed wave which may often be mixed together. In our design of DONET observation system, we took care to help identification of seismic phase by obtaining both ground motion and seafloor pressure in the same location. This is simply achieved by combining seafloor pressure gauges and seismometer in a single observatory package, but care was taken to observe both in the similar level of sensitivity and dynamic range in wide frequencies from near DC to over 100 Hz. In the case of DONET, the broadband seismometer and the differential pressure gauge have similar level of sensitivity in 0.005 - 10 Hz, and similarly the accelerometer and the hydrophone cover between 1-100Hz, in total covering most frequencies of our interest, 0.005 Hz to 100 Hz. With both ground motion and seafloor pressure measurement, we may distinguish types of waves relatively easily, and it is also possible to filter particular types of waves from the array dataset to help our data analysis. For example, it has been commonly practiced to distinguish up-going and down-going seismic phases from pressure and ground motion, but this is relatively difficult only with sparse seismometer array. This technique may also be applied to correct teleseismic record with sea surface reflection in receiver function analysis for exploring deep crustal structure.

Tsunami Modeling and Prediction Using a Data Assimilation Technique with Kalman Filters

NASA Astrophysics Data System (ADS)

Barnier, G.; Dunham, E. M.

2016-12-01

Earthquake-induced tsunamis cause dramatic damages along densely populated coastlines. It is difficult to predict and anticipate tsunami waves in advance, but if the earthquake occurs far enough from the coast, there may be enough time to evacuate the zones at risk. Therefore, any real-time information on the tsunami wavefield (as it propagates towards the coast) is extremely valuable for early warning systems. After the 2011 Tohoku earthquake, a dense tsunami-monitoring network (S-net) based on cabled ocean-bottom pressure sensors has been deployed along the Pacific coast in Northeastern Japan. Maeda et al. (GRL, 2015) introduced a data assimilation technique to reconstruct the tsunami wavefield in real time by combining numerical solution of the shallow water wave equations with additional terms penalizing the numerical solution for not matching observations. The penalty or gain matrix is determined though optimal interpolation and is independent of time. Here we explore a related data assimilation approach using the Kalman filter method to evolve the gain matrix. While more computationally expensive, the Kalman filter approach potentially provides more accurate reconstructions. We test our method on a 1D tsunami model derived from the Kozdon and Dunham (EPSL, 2014) dynamic rupture simulations of the 2011 Tohoku earthquake. For appropriate choices of model and data covariance matrices, the method reconstructs the tsunami wavefield prior to wave arrival at the coast. We plan to compare the Kalman filter method to the optimal interpolation method developed by Maeda et al. (GRL, 2015) and then to implement the method for 2D.

Minimal camera networks for 3D image based modeling of cultural heritage objects.

PubMed

Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

2014-03-25

3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue "Lamassu". Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883-859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm.

Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

PubMed Central

Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

2014-01-01

3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue “Lamassu”. Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883–859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm. PMID:24670718

Design of a stateless low-latency router architecture for green software-defined networking

NASA Astrophysics Data System (ADS)

Saldaña Cercós, Silvia; Ramos, Ramon M.; Ewald Eller, Ana C.; Martinello, Magnos; Ribeiro, Moisés. R. N.; Manolova Fagertun, Anna; Tafur Monroy, Idelfonso

2015-01-01

Expanding software defined networking (SDN) to transport networks requires new strategies to deal with the large number of flows that future core networks will have to face. New south-bound protocols within SDN have been proposed to benefit from having control plane detached from the data plane offering a cost- and energy-efficient forwarding engine. This paper presents an overview of a new approach named KeyFlow to simultaneously reduce latency, jitter, and power consumption in core network nodes. Results on an emulation platform indicate that round trip time (RTT) can be reduced above 50% compared to the reference protocol OpenFlow, specially when flow tables are densely populated. Jitter reduction has been demonstrated experimentally on a NetFPGA-based platform, and 57.3% power consumption reduction has been achieved.

On the sufficiency of pairwise interactions in maximum entropy models of networks

NASA Astrophysics Data System (ADS)

Nemenman, Ilya; Merchan, Lina

Biological information processing networks consist of many components, which are coupled by an even larger number of complex multivariate interactions. However, analyses of data sets from fields as diverse as neuroscience, molecular biology, and behavior have reported that observed statistics of states of some biological networks can be approximated well by maximum entropy models with only pairwise interactions among the components. Based on simulations of random Ising spin networks with p-spin (p > 2) interactions, here we argue that this reduction in complexity can be thought of as a natural property of some densely interacting networks in certain regimes, and not necessarily as a special property of living systems. This work was supported in part by James S. McDonnell Foundation Grant No. 220020321.

Information jet: Handling noisy big data from weakly disconnected network

NASA Astrophysics Data System (ADS)

Aurongzeb, Deeder

Sudden aggregation (information jet) of large amount of data is ubiquitous around connected social networks, driven by sudden interacting and non-interacting events, network security threat attacks, online sales channel etc. Clustering of information jet based on time series analysis and graph theory is not new but little work is done to connect them with particle jet statistics. We show pre-clustering based on context can element soft network or network of information which is critical to minimize time to calculate results from noisy big data. We show difference between, stochastic gradient boosting and time series-graph clustering. For disconnected higher dimensional information jet, we use Kallenberg representation theorem (Kallenberg, 2005, arXiv:1401.1137) to identify and eliminate jet similarities from dense or sparse graph.

Sonification of network traffic flow for monitoring and situational awareness

PubMed Central

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543

Sonification of network traffic flow for monitoring and situational awareness.

PubMed

Debashi, Mohamed; Vickers, Paul

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.

The Imperial County Community Air Monitoring Network: A Model for Community-based Environmental Monitoring for Public Health Action

PubMed Central

Olmedo, Luis; Bejarano, Ester; Lugo, Humberto; Murillo, Eduardo; Seto, Edmund; Wong, Michelle; King, Galatea; Wilkie, Alexa; Meltzer, Dan; Carvlin, Graeme; Jerrett, Michael; Northcross, Amanda

2017-01-01

Summary: The Imperial County Community Air Monitoring Network (the Network) is a collaborative group of community, academic, nongovernmental, and government partners designed to fill the need for more detailed data on particulate matter in an area that often exceeds air quality standards. The Network employs a community-based environmental monitoring process in which the community and researchers have specific, well-defined roles as part of an equitable partnership that also includes shared decision-making to determine study direction, plan research protocols, and conduct project activities. The Network is currently producing real-time particulate matter data from 40 low-cost sensors throughout Imperial County, one of the largest community-based air networks in the United States. Establishment of a community-led air network involves engaging community members to be citizen-scientists in the monitoring, siting, and data collection process. Attention to technical issues regarding instrument calibration and validation and electronic transfer and storage of data is also essential. Finally, continued community health improvements will be predicated on facilitating community ownership and sustainability of the network after research funds have been expended. https://doi.org/10.1289/EHP1772 PMID:28886604

Intercontinental Multi-Domain Monitoring for LHC with perfSONAR

NASA Astrophysics Data System (ADS)

Vicinanza, D.

2012-12-01

The Large Hadron Collider (LHC) is currently running at CERN in Geneva, Switzerland. Physicists are using LHC to recreate the conditions just after the Big Bang, by colliding two beams of particles and heavy ions head-on at very high energy. The project is generating more than 15 TB of raw data per year, plus 10 TB of “event summary data”. This data is sent out from CERN to eleven Tier 1 research centres in Europe, Asia, and North America using a multi-gigabits Optical Private Network (OPN), the LHCOPN. Tier 1 sites are then connected to 100+ academic and research institutions in the world (the Tier 2s) through a Multipoint to Multipoint network, the LHC Open Network Environment (LHCONE). Network monitoring on such complex network architecture to ensure robust and reliable operation is of crucial importance. The chosen approach for monitoring the OPN and ONE is based on the perfSONAR framework, which is designed for multi-domain monitoring environments. perfSONAR (www.perfsonar.net) is an infrastructure for performance monitoring data exchange between networks, making it easier to solve performance problems occurring between network measurement points interconnected through several network domains.

Home medical monitoring network based on embedded technology

NASA Astrophysics Data System (ADS)

Liu, Guozhong; Deng, Wenyi; Yan, Bixi; Lv, Naiguang

2006-11-01

Remote medical monitoring network for long-term monitoring of physiological variables would be helpful for recovery of patients as people are monitored at more comfortable conditions. Furthermore, long-term monitoring would be beneficial to investigate slowly developing deterioration in wellness status of a subject and provide medical treatment as soon as possible. The home monitor runs on an embedded microcomputer Rabbit3000 and interfaces with different medical monitoring module through serial ports. The network based on asymmetric digital subscriber line (ADSL) or local area network (LAN) is established and a client - server model, each embedded home medical monitor is client and the monitoring center is the server, is applied to the system design. The client is able to provide its information to the server when client's request of connection to the server is permitted. The monitoring center focuses on the management of the communications, the acquisition of medical data, and the visualization and analysis of the data, etc. Diagnosing model of sleep apnea syndrome is built basing on ECG, heart rate, respiration wave, blood pressure, oxygen saturation, air temperature of mouth cavity or nasal cavity, so sleep status can be analyzed by physiological data acquired as people in sleep. Remote medical monitoring network based on embedded micro Internetworking technology have advantages of lower price, convenience and feasibility, which have been tested by the prototype.

NCCN Mountain Lakes Monitoring Strategy: Guidelines to Resolution

USGS Publications Warehouse

Hoffman, Robert L.; Huff, Mark H.

2008-01-01

The North Coast and Cascades Network (NCCN) Inventory and Monitoring Program provides funds to its Network Parks to plan and implement the goals and objectives of the National Park Services? (NPS) Inventory and Monitoring (I&M) Program. The primary purpose of the I&M program is to develop and implement a long-term monitoring program in each network. The purpose of this document is to describe the outcome of a meeting held to find solutions to obstacles inhibiting development of a unified core design and methodology for mountain lake monitoring.

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Abas, Faizulsalihin bin; Takayama, Shigeru

2015-02-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

Describing the Neuron Axons Network of the Human Brain by Continuous Flow Models

NASA Astrophysics Data System (ADS)

Hizanidis, J.; Katsaloulis, P.; Verganelakis, D. A.; Provata, A.

2014-12-01

The multifractal spectrum Dq (Rényi dimensions) is used for the analysis and comparison between the Neuron Axons Network (NAN) of healthy and pathological human brains because it conveys information about the statistics in many scales, from the very rare to the most frequent network configurations. Comparison of the Fractional Anisotropy Magnetic Resonance Images between healthy and pathological brains is performed with and without noise reduction. Modelling the complex structure of the NAN in the human brain is undertaken using the dynamics of the Lorenz model in the chaotic regime. The Lorenz multifractal spectra capture well the human brain characteristics in the large negative q's which represent the rare network configurations. In order to achieve a closer approximation in the positive part of the spectrum (q > 0) two independent modifications are considered: a) redistribution of the dense parts of the Lorenz model's phase space into their neighbouring areas and b) inclusion of additive uniform noise in the Lorenz model. Both modifications, independently, drive the Lorenz spectrum closer to the human NAN one in the positive q region without destroying the already good correspondence of the negative spectra. The modelling process shows that the unmodified Lorenz model in its full chaotic regime has a phase space distribution with high fluctuations in its dense parts, while the fluctuations in the human brain NAN are smoother. The induced modifications (phase space redistribution or additive noise) moderate the fluctuations only in the positive part of the Lorenz spectrum leading to a faithful representation of the human brain axons network in all scales.

The Longitudinal Effect of Self-Monitoring and Locus of Control on Social Network Position in Friendship Networks

DTIC Science & Technology

2006-03-01

equally essential to examine the antecedents that bring a person to a particular network location. The previous body of knowledge in social networks...Locus of Control on Social Network Position in Friendship Networks THESIS Gary J. Moore, Captain, USAF AFIT/GEM/ENV/06M-11 DEPARTMENT OF THE AIR...THE LONGITUDINAL EFFECTS OF SELF-MONITORING AND LOCUS OF CONTROL ON SOCIAL NETWORK POSITION IN FRIENDSHIP NETWORKS THESIS Presented to the

Grass-Roots Leadership in Appalachia: A Contradiction in Terms?

ERIC Educational Resources Information Center

Salstrom, Paul

1991-01-01

The cultural values of rural Appalachia have been antithetical to the explicit leadership needed in activist movements for social change. "Subsistence, barter, and borrow" economic systems, pervasive in Appalachia, are based on nonmonetary, voluntary reciprocity within dense insider networks, not the formal contracts of both capitalist…

Understanding the influence of all nodes in a network

PubMed Central

Lawyer, Glenn

2015-01-01

Centrality measures such as the degree, k-shell, or eigenvalue centrality can identify a network's most influential nodes, but are rarely usefully accurate in quantifying the spreading power of the vast majority of nodes which are not highly influential. The spreading power of all network nodes is better explained by considering, from a continuous-time epidemiological perspective, the distribution of the force of infection each node generates. The resulting metric, the expected force, accurately quantifies node spreading power under all primary epidemiological models across a wide range of archetypical human contact networks. When node power is low, influence is a function of neighbor degree. As power increases, a node's own degree becomes more important. The strength of this relationship is modulated by network structure, being more pronounced in narrow, dense networks typical of social networking and weakening in broader, looser association networks such as the Internet. The expected force can be computed independently for individual nodes, making it applicable for networks whose adjacency matrix is dynamic, not well specified, or overwhelmingly large. PMID:25727453

Structure and function of complex brain networks

PubMed Central

Sporns, Olaf

2013-01-01

An increasing number of theoretical and empirical studies approach the function of the human brain from a network perspective. The analysis of brain networks is made feasible by the development of new imaging acquisition methods as well as new tools from graph theory and dynamical systems. This review surveys some of these methodological advances and summarizes recent findings on the architecture of structural and functional brain networks. Studies of the structural connectome reveal several modules or network communities that are interlinked by hub regions mediating communication processes between modules. Recent network analyses have shown that network hubs form a densely linked collective called a “rich club,” centrally positioned for attracting and dispersing signal traffic. In parallel, recordings of resting and task-evoked neural activity have revealed distinct resting-state networks that contribute to functions in distinct cognitive domains. Network methods are increasingly applied in a clinical context, and their promise for elucidating neural substrates of brain and mental disorders is discussed. PMID:24174898

Evaluation of groundwater levels in the South Platte River alluvial aquifer, Colorado, 1953-2012, and design of initial well networks for monitoring groundwater levels

USGS Publications Warehouse

Wellman, Tristan

2015-01-01

A network of candidate monitoring wells was proposed to initiate a regional monitoring program. Consistent monitoring and analysis of groundwater levels will be needed for informed decisions to optimize beneficial use of water and to limit high groundwater levels in susceptible areas. Finalization of the network will require future field reconnaissance to assess local site conditions and discussions with State authorities.

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China

PubMed Central

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R.

2017-01-01

PM2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM2.5 in grid cells with a resolution of 10 km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R2 of 0.95 and 0.94, respectively and PM2.5 was overestimated by WRF-Chem (R2=0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM2.5. Current monitoring network in North China was dense enough to provide a reliable PM2.5 prediction by interpolation technique. PMID:28599195

Evaluation of a data fusion approach to estimate daily PM2.5 levels in North China.

PubMed

Liang, Fengchao; Gao, Meng; Xiao, Qingyang; Carmichael, Gregory R; Pan, Xiaochuan; Liu, Yang

2017-10-01

PM 2.5 air pollution has been a growing concern worldwide. Previous studies have conducted several techniques to estimate PM 2.5 exposure spatiotemporally in China, but all these have limitations. This study was to develop a data fusion approach and compare it with kriging and Chemistry Module. Two techniques were applied to create daily spatial cover of PM 2.5 in grid cells with a resolution of 10km in North China in 2013, respectively, which was kriging with an external drift (KED) and Weather Research and Forecast Model with Chemistry Module (WRF-Chem). A data fusion technique was developed by fusing PM 2.5 concentration predicted by KED and WRF-Chem, accounting for the distance from the central of grid cell to the nearest ground observations and daily spatial correlations between WRF-Chem and observations. Model performances were evaluated by comparing them with ground observations and the spatial prediction errors. KED and data fusion performed better at monitoring sites with a daily model R 2 of 0.95 and 0.94, respectively and PM 2.5 was overestimated by WRF-Chem (R 2 =0.51). KED and data fusion performed better around the ground monitors, WRF-Chem performed relative worse with high prediction errors in the central of study domain. In our study, both KED and data fusion technique provided highly accurate PM 2.5 . Current monitoring network in North China was dense enough to provide a reliable PM 2.5 prediction by interpolation technique. Copyright © 2017. Published by Elsevier Inc.

Ground-water resources of the Laura area, Majuro Atoll, Marshall Islands

USGS Publications Warehouse

Hamlin, S.N.; Anthony, S.S.

1987-01-01

The water system that supplies the heavily populated Dalap-Uliga-Darrit (DUD) area of Majuro atoll, Marshall Island, relies almost entirely upon airstrip catchment of rain water. Droughts cause severe water supply problems and water rationing is required, even during periods of normal rainfall. The Laura area contains a substantial lens of fresh groundwater that could be developed for export to the DUD area 30 mi to the east. Study of the groundwater resource at Laura involved a survey of existing wells, installation of monitoring wells and test holes, compilation of continuous records of rainfall and water level fluctuations, and collection of water quality data. Test hole data permitted the definition of three geohydrologic units which correlate well with similar units in Bikini and Enewetak atolls. The units consist of two layers of unconsolidated reef and lagoon sediments resting on a dense, highly permeable limestone. The potable water zone, or freshwater nucleus, of the lens is contained mostly within the unconsolidated layers, which are much less permeable than the basal limestone. Recharge to the Laura freshwater lens is estimated to be 1.8 mil gal/day, based on an average annual rainfall of 140 in. Sustainable yield is estimated to be about 400,000 gal/day. Shallow skimming wells or infiltration galleries similar to those used on Kwajalein atoll would be appropriate to develop the freshwater lens. The impact of development on the lens can be determined by monitoring the salinity in developed water and in a network of monitor wells. (Author 's abstract)

Design of cold chain logistics remote monitoring system based on ZigBee and GPS location

NASA Astrophysics Data System (ADS)

Zong, Xiaoping; Shao, Heling

2017-03-01

This paper designed a remote monitoring system based on Bee Zig wireless sensor network and GPS positioning, according to the characteristics of cold chain logistics. The system consisted of the ZigBee network, gateway and monitoring center. ZigBee network temperature acquisition modules and GPS positioning acquisition module were responsible for data collection, and then send the data to the host computer through the GPRS network and Internet to realize remote monitoring of vehicle with functions of login permissions, temperature display, latitude and longitude display, historical data, real-time alarm and so on. Experiments showed that the system is stable, reliable and effective to realize the real-time remote monitoring of the vehicle in the process of cold chain transport.

Web Information Systems for Monitoring and Control of Indoor Air Quality at Subway Stations

NASA Astrophysics Data System (ADS)

Choi, Gi Heung; Choi, Gi Sang; Jang, Joo Hyoung

In crowded subway stations indoor air quality (IAQ) is a key factor for ensuring the safety, health and comfort of passengers. In this study, a framework for web-based information system in VDN environment for monitoring and control of IAQ in subway stations is suggested. Since physical variables that describing IAQ need to be closely monitored and controlled in multiple locations in subway stations, concept of distributed monitoring and control network using wireless media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated, distributed monitoring and control performance, making a web-based information system possible.

An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

2017-02-01

Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

WDM PONs based on colorless technology

NASA Astrophysics Data System (ADS)

Saliou, Fabienne; Simon, Gael; Chanclou, Philippe; Pizzinat, Anna; Lin, Huafeng; Zhou, Enyu; Xu, Zhiguang

2015-12-01

Wavelength Division Multiplexing (WDM) Passive Optical Network (PON) is foreseen to be part of the Next Generation Passive Optical Networks. Business and mobile fronthaul networks already express the need to develop WDM PONs in the access segment. Fixed wavelength transceivers based on Coarse WDM are already available to respond to today's market needs but Dense WDM technologies will be needed and colorless technologies are essential to provide simple and cost-effective WDM PON systems. We propose in this paper to demonstrate the capabilities of a DWDM PON system prototype based on self-seeded RSOAs and designed to transmit CPRI over 60 km of fiber at 2.5 Gbit/s.

Livermore Big Artificial Neural Network Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Essen, Brian Van; Jacobs, Sam; Kim, Hyojin

2016-07-01

LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.

40 CFR 58.14 - System modification.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where... monitoring network that complies with the findings of the network assessments required every 5 years by § 58... schedule with respect to the SLAMS network are subject to the approval of the EPA Regional Administrator...

40 CFR 58.14 - System modification.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) AMBIENT AIR QUALITY SURVEILLANCE Monitoring Network § 58.14 System modification. (a) The State, or where... monitoring network that complies with the findings of the network assessments required every 5 years by § 58... schedule with respect to the SLAMS network are subject to the approval of the EPA Regional Administrator...

A global interaction network maps a wiring diagram of cellular function

PubMed Central

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

Enhancement of Beaconless Location-Based Routing with Signal Strength Assistance for Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Chen, Guowei; Itoh, Kenichi; Sato, Takuro

Routing in Ad-hoc networks is unreliable due to the mobility of the nodes. Location-based routing protocols, unlike other protocols which rely on flooding, excel in network scalability. Furthermore, new location-based routing protocols, like, e. g. BLR [1], IGF [2], & CBF [3] have been proposed, with the feature of not requiring beacons in MAC-layer, which improve more in terms of scalability. Such beaconless routing protocols can work efficiently in dense network areas. However, these protocols' algorithms have no ability to avoid from routing into sparse areas. In this article, historical signal strength has been added as a factor into the BLR algorithm, which avoids routing into sparse area, and consequently improves the global routing efficiency.

Water quality in riparian boreal forest: a multi-method approach to scale biogeochemical drivers from groundwater hotspots to catchment outlets.

NASA Astrophysics Data System (ADS)

Ploum, Stefan; Kuglerová, Lenka; Leach, Jason; Laudon, Hjalmar

2017-04-01

Stream chemistry in boreal regions is for a large degree defined by the riparian zone. Within the riparian zone, groundwater hotspots represent a very small area, but likely play a major role in controlling stream water quality. Hotspots have shown to be unique in their plant species richness, soil texture and biogeochemistry. Also in terms of stream metabolism, hotspots show different responses, either due to local biotic or abiotic conditions. Readily available hydrological mapping tools, combined with biogeochemical data (stream temperature and stable water isotopes) show that there is great potential in predicting groundwater hotspots using terrain-based approaches. However, the role of individual hotspots varies in time. Presumably their hydrological regime is highly dependent on landscape properties of the upstream area. To improve the predictability of hotspots in space and time, a mechanistic understanding is needed. We achieve this by a combined approach including a damming experiment, high resolution optic fiber stream temperature measurements (DTS), a dense groundwater well network, stream and groundwater trace element analysis, frost monitoring and infrared (IR) imagery. This field-based strategy sheds light on the underlying drivers of groundwater hotspots and links them to landscape characteristics. This allows to move away from highly monitored reaches, and evaluate the relation between upland landscape features and the temporal variability of groundwater exfiltration rates on a catchment scale.

The use of existing environmental networks for the post-market monitoring of GM crop cultivation in the EU.

PubMed

Smets, G; Alcalde, E; Andres, D; Carron, D; Delzenne, P; Heise, A; Legris, G; Martinez Parrilla, M; Verhaert, J; Wandelt, C; Ilegems, M; Rüdelsheim, P

2014-07-01

The European Union (EU) Directive 2001/18/EC on the deliberate release of genetically modified organisms (GMOs) into the environment requires that both Case-Specific Monitoring (CSM) and General Surveillance (GS) are considered as post-market implementing measures. Whereas CSM is directed to monitor potential adverse effects of GMOs or their use identified in the environmental risk assessment, GS aims to detect un-intended adverse effects of GMOs or their use on human and animal health or the environment. Guidance documents on the monitoring of genetically modified (GM) plants from the Commission and EFSA clarify that, as appropriate, GS can make use of established routine surveillance practices. Networks involved in routine surveillance offer recognised expertise in a particular domain and are designed to collect information on important environmental aspects over a large geographical area. However, as the suitability of existing monitoring networks to provide relevant data for monitoring impacts of GMOs is not known, plant biotechnology companies developed an approach to describe the processes and criteria that will be used for selecting and evaluating existing monitoring systems. In this paper, the availability of existing monitoring networks for this purpose is evaluated. By cataloguing the existing environmental monitoring networks in the EU, it can be concluded that they can only be used, in the context of GMO cultivation monitoring, as secondary tools to collect baseline information.

Physical parameters collection based on wireless senor network

NASA Astrophysics Data System (ADS)

Chen, Xin; Wu, Hong; Ji, Lei

2013-12-01

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

Enabling end-user network monitoring via the multicast consolidated proxy monitor

NASA Astrophysics Data System (ADS)

Kanwar, Anshuman; Almeroth, Kevin C.; Bhattacharyya, Supratik; Davy, Matthew

2001-07-01

The debugging of problems in IP multicast networks relies heavily on an eclectic set of stand-alone tools. These tools traditionally neither provide a consistent interface nor do they generate readily interpretable results. We propose the ``Multicast Consolidated Proxy Monitor''(MCPM), an integrated system for collecting, analyzing and presenting multicast monitoring results to both the end user and the network operator at the user's Internet Service Provider (ISP). The MCPM accesses network state information not normally visible to end users and acts as a proxy for disseminating this information. Functionally, through this architecture, we aim to a) provide a view of the multicast network at varying levels of granularity, b) provide end users with a limited ability to query the multicast infrastructure in real time, and c) protect the infrastructure from overwhelming amount of monitoring load through load control. Operationally, our scheme allows scaling to the ISPs dimensions, adaptability to new protocols (introduced as multicast evolves), threshold detection for crucial parameters and an access controlled, customizable interface design. Although the multicast scenario is used to illustrate the benefits of consolidated monitoring, the ultimate aim is to scale the scheme to unicast IP networks.

DS Sentry: an acquisition ASIC for smart, micro-power sensing applications

NASA Astrophysics Data System (ADS)

Liobe, John; Fiscella, Mark; Moule, Eric; Balon, Mark; Bocko, Mark; Ignjatovic, Zeljko

2011-06-01

Unattended ground monitoring that combines seismic and acoustic information can be a highly valuable tool in intelligence gathering; however there are several prerequisites for this approach to be viable. The first is high sensitivity as well as the ability to discriminate real threats from noise and other spurious signals. By combining ground sensing with acoustic and image monitoring this requirement may be achieved. Moreover, the DS Sentry®provides innate spurious signal rejection by the "active-filtering" technique employed as well as embedding some basic statistical analysis. Another primary requirement is spatial and temporal coverage. The ideal is uninterrupted, long-term monitoring of an area. Therefore, sensors should be densely deployed and consume very little power. Furthermore, sensors must be inexpensive and easily deployed to allow dense placements in critical areas. The ADVIS DS Sentry®, which is a fully-custom integrated circuit that enables smart, micro-power monitoring of dynamic signals, is the foundation of the proposed system. The core premise behind this technology is the use of an ultra-low power front-end for active monitoring of dynamic signals in conjunction with a highresolution, Σ Δ-based analog-to-digital converter, which utilizes a novel noise rejection technique and is only employed when a potential threat has been detected. The DS Sentry® can be integrated with seismic accelerometers and microphones and user-programmed to continuously monitor for signals with specific signatures such as impacts, footsteps, excavation noise, vehicle-induced ground vibrations, or speech, while consuming only microwatts of power. This will enable up to several years of continuous monitoring on a single small battery while concurrently mitigating false threats.

A Modeling Framework for Inference of Surface Emissions Using Mobile Observations

NASA Astrophysics Data System (ADS)

Fasoli, B.; Mitchell, L.; Crosman, E.; Mendoza, D. L.; Lin, J. C.

2016-12-01

Our ability to quantify surface emissions depends on the precision of observations and the spatial density of measurement networks. Mobile measurement techniques offer a cost effective strategy for quantifying atmospheric conditions over space without requiring a dense network of in-situ sites. However, interpretation of these data and inversion of dispersed measurements to estimate surface emissions can be difficult. We introduce a framework using the Stochastic Time-Inverted Lagrangian Transport (STILT) model that assimilates both spatially resolved observations and an emissions inventory to better estimate surface fluxes. Salt Lake City is a unique laboratory for the study of urban carbon emissions. It is the only U.S. city that utilizes light-rail trains to continuously measure high frequency carbon dioxide (CO2) and methane (CH4); it is home to one of the longest and most spatially resolved high precision CO2 measurement networks (air.utah.edu); and it is one of four cities in the world for which the Hestia anthropogenic emissions inventory has been produced which characterizes CO2 emissions at the scale of individual buildings and roadways. Using these data and modeling resources, we evaluate spatially resolved CO2 measurements and transported CO2 emissions on hourly timescales at a dense spatial resolution across Salt Lake City.

SPECTRE (www.noveltis.fr/spectre): a web Service for Ionospheric Products

NASA Astrophysics Data System (ADS)

Jeansou, E.; Crespon, F.; Garcia, R.; Helbert, J.; Moreaux, G.; Lognonne, P.

2005-12-01

The dense GPS networks developed for geodesic applications appear to be very efficient ionospheric sensors because of interaction between plasma and electromagnetic waves. Indeed, the dual frequency receivers provide data from which the Slant Total Electron Content (STEC) can be easily extracted to compute Vertical Total Electron Content (VTEC) maps. The SPECTRE project, Service and Products for ionospheric Electron Content and Tropospheric Refractivity over Europe, is currently a pre-operational service providing VTEC maps with high time and space resolution after 3 days time delay (http://www.noveltis.fr/spectre and http://ganymede.ipgp.jussieu.fr/spectre). This project is a part of SWENET, SpaceWeather European Network, initiated by the European Space Agency. The SPECTRE data products are useful for many applications. We will present these applications in term of interest for the scientific community with a special focus on spaceweather and transient ionospheric perturbations related to Earthquakes. Moreover, the pre-operational extensions of SPECTRE to the californian (SCIGN/BARD) and japanese (GEONET) dense GPS networks will be presented. Then the method of 3D tomography of the electron density from GPS data will be presented and its resolution discussed. The expected improvements of the 3D tomographic images by new tomographic reconstruction algorithms and by the advent of the Galileo system will conclude the presentation.

Assessing community exposure to hazardous air pollutants by combining optical remote sensing and "low-cost" sensor technologies

NASA Astrophysics Data System (ADS)

Pikelnaya, O.; Polidori, A.; Wimmer, R.; Mellqvist, J.; Samuelsson, J.; Marianne, E.; Andersson, P.; Brohede, S.; Izos, O.

2017-12-01

Industrial facilities such as refineries and oil processing facilities can be sources of chemicals adversely affecting human health, for example aromatic hydrocarbons and formaldehyde. In an urban setting, such as the South Coast Air Basin (SCAB), exposure to harmful air pollutants (HAP's) for residents of communities neighboring such facilities is of serious concern. Traditionally, exposure assessments are performed by modeling a community exposure using emission inventories and data collected at fixed air monitoring sites. However, recent field measurements found that emission inventories may underestimate HAP emissions from refineries; and HAP measurements data from fixed sites is lacking spatial resolution; as a result, the impact of HAP emissions on communities is highly uncertain. The next generation air monitoring technologies can help address these challenges. For example, dense "low-cost" sensors allow continuous monitoring of concentrations of pollutants within communities with high temporal- and spatial- resolution, and optical remote sensing (ORS) technologies offer measurements of emission fluxes and real-time ground-concentration mapping of HAPs. South Coast Air Quality Management District (SCAQMD) is currently conducting a multi-year study using ORS methods and "low-cost" Volatile Organic Compounds (VOCs) sensors to monitor HAP emissions from selected industrial facilities in the SCAB and their ambient concentrations in neighboring communities. For this purpose, quarterly mobile ORS surveys are conducted to quantify facility-wide emissions for VOCs, aromatic hydrocarbons and HCHO, and to collect ground-concentration profiles of these pollutants inside neighboring communities. Additionally, "low-cost" sensor nodes for deployment in neighborhood(s) downwind of the facilities have been developed in order to obtain long-term, granular data on neighborhood VOC concentrations, During this presentation we will discuss initial results of quarterly ORS surveys and pilot "low-cost" sensor deployments. We will also outline benefits of using a combination of mobile ORS surveys and "low-cost" sensor networks for community exposure monitoring.

Embedded 100 Gbps Photonic Components

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuznia, Charlie

This innovation to fiber optic component technology increases the performance, reduces the size and reduces the power consumption of optical communications within dense network systems, such as advanced distributed computing systems and data centers. VCSEL technology is enabling short-reach (< 100 m) and >100 Gbps optical interconnections over multi-mode fiber in commercial applications.

Deaf Sociality and the Deaf Lutheran Church in Adamorobe, Ghana

ERIC Educational Resources Information Center

Kusters, Annelies

2014-01-01

This article provides an ethnographic analysis of "deaf sociality" in Adamorobe, a village in Ghana, where the relatively high prevalence of hereditary deafness has led to dense social and spatial connections. Deaf people are part of their hearing environment particularly through family networks, and produce deaf sociality through many…

Class, Kinship Density, and Conjugal Role Segregation.

ERIC Educational Resources Information Center

Hill, Malcolm D.

1988-01-01

Studied conjugal role segregation in 150 married women from intact families in working-class community. Found that, although involvement in dense kinship networks was associated with conjugal role segregation, respondents' attitudes toward marital roles and phase of family cycle when young children were present were more powerful predictors of…

Synopsis of the D- and E-regions during the energy budget campaign

NASA Technical Reports Server (NTRS)

Friedrich, M.; Baker, K. D.; Dickinson, P. H. G.; Dumbs, A.; Grandal, B.; Andreassen, O.; Thrane, E. V.; Smith, L. G.; Stauning, P.; Torkar, K. M.

1985-01-01

Electron density profiles derived from rocket-borne measurements are presented. These data were obtained at two different sites in northern Scandinavia under various degrees of geophysical disturbance. The observed electron density profiles are related to ionospheric absorption as observed with the dense riometer network in that area.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friedrich, M.; Baker, K.D.; Brekke, A.

Electron density profiles from ground-based and rocket-borne measurements conducted at three sites in northern Scandinavia under various degrees of geophysical disturbances are presented. These data are checked against an instantaneous picture of the ionospheric absorption obtained via the dense riometer network. A map of the riometer absorption and measured electron densities over Scandinavia is given.

Integrating wireless sensor network for monitoring subsidence phenomena

NASA Astrophysics Data System (ADS)

Marturià, Jordi; Lopez, Ferran; Gigli, Giovanni; Intrieri, Emanuele; Mucchi, Lorenzo; Fornaciai, Alessandro

2016-04-01

An innovative wireless sensor network (WSN) for the 3D superficial monitoring of deformations (such as landslides and subsidence) is being developed in the frame of the Wi-GIM project (Wireless sensor network for Ground Instability Monitoring - LIFE12 ENV/IT/001033). The surface movement is detected acquiring the position (x, y and z) by integrating large bandwidth technology able to detect the 3D coordinates of the sensor with a sub-meter error, with continuous wave radar, which allows decreasing the error down to sub-cm. The Estació neighborhood in Sallent is located over the old potassium mine Enrique. This zone has been affected by a subsidence process over more than twenty years. The implementation of a wide network for ground auscultation has allowed monitoring the process of subsidence since 1997. This network consists of: i) a high-precision topographic leveling network to control the subsidence in surface; ii) a rod extensometers network to monitor subsurface deformation; iii) an automatic Leica TCA Total Station to monitor building movements; iv) an inclinometers network to measure the horizontal displacements on subsurface and v) a piezometer to measure the water level. Those networks were implemented within an alert system for an organized an efficient response of the civil protection authorities in case of an emergency. On 23rd December 2008, an acceleration of subsoil movements (of approx. 12-18 cm/year) provoked the activation of the emergency plan by the Catalan Civil Protection. This implied the preventive and scheduled evacuation of the neighbours (January 2009) located in the area with a higher risk of collapse: around 120 residents of 43 homes. As a consequence, the administration implemented a compensation plan for the evacuation of the whole neighbourhood residents and the demolition of 405 properties. In this work, the adaptation and integration process of Wi-GIM system with those conventional monitoring network are presented for its testing and evaluation. The knowledge gained in the subsidence process, complemented by the huge availability of data from existing networks constitutes a solid foundation for achieving those objectives. New monitoring points have been identified, constructed, prepared to integrate the conventional monitoring system with Wi-GIM system to build a robust system compatible with WI-GIM requirements.

Some applications of remote sensing in atmospheric monitoring programs

NASA Technical Reports Server (NTRS)

Heller, A. N.; Bryson, J. C.; Vasuki, N. C.

1972-01-01

The applications of remote sensing in atmospheric monitoring programs are described. The organization, operations, and functions of an air quality monitoring network at New Castle County, Delaware is discussed. The data obtained by the air quality monitoring network ground stations and the equipment used to obtain atmospheric data are explained. It is concluded that correlation of the information obtained by the network will make it possible to anticipate air pollution problems in the Chesapeake Bay area before a crisis develops.

An approach to online network monitoring using clustered patterns

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jinoh; Sim, Alex; Suh, Sang C.

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

An approach to online network monitoring using clustered patterns

DOE PAGES

Kim, Jinoh; Sim, Alex; Suh, Sang C.; ...

2017-03-13

Network traffic monitoring is a core element in network operations and management for various purposes such as anomaly detection, change detection, and fault/failure detection. In this study, we introduce a new approach to online monitoring using a pattern-based representation of the network traffic. Unlike the past online techniques limited to a single variable to summarize (e.g., sketch), the focus of this study is on capturing the network state from the multivariate attributes under consideration. To this end, we employ clustering with its benefit of the aggregation of multidimensional variables. The clustered result represents the state of the network with regardmore » to the monitored variables, which can also be compared with the previously observed patterns visually and quantitatively. Finally, we demonstrate the proposed method with two popular use cases, one for estimating state changes and the other for identifying anomalous states, to confirm its feasibility.« less

Cross-Disciplinary Network Comparison: Matchmaking Between Hairballs

PubMed Central

Yan, Koon-Kiu; Wang, Daifeng; Sethi, Anurag; Muir, Paul; Kitchen, Robert; Cheng, Chao; Gerstein, Mark

2016-01-01

Biological systems are complex. In particular, the interactions between molecular components often form dense networks that, more often than not, are criticized for being inscrutable ‘hairballs’. We argue that one way of untangling these hairballs is through cross-disciplinary network comparison—leveraging advances in other disciplines to obtain new biological insights. In some cases, such comparisons enable the direct transfer of mathematical formalism between disciplines, precisely describing the abstract associations between entities and allowing us to apply a variety of sophisticated formalisms to biology. In cases where the detailed structure of the network does not permit the transfer of complete formalisms between disciplines, comparison of mechanistic interactions in systems for which we have significant day-to-day experience can provide analogies for interpreting relatively more abstruse biological networks. Here, we illustrate how these comparisons benefit the field with a few specific examples related to network growth, organizational hierarchies, and the evolution of adaptive systems. PMID:27047991

Unveiling the molecular mechanism of self-healing in a telechelic, supramolecular polymer network

PubMed Central

Yan, Tingzi; Schröter, Klaus; Herbst, Florian; Binder, Wolfgang H.; Thurn-Albrecht, Thomas

2016-01-01

Reversible polymeric networks can show self-healing properties due to their ability to reassemble after application of stress and fracture, but typically the relation between equilibrium molecular dynamics and self-healing kinetics has been difficult to disentangle. Here we present a well-characterized, self-assembled bulk network based on supramolecular assemblies, that allows a clear distinction between chain dynamics and network relaxation. Small angle x-ray scattering and rheological measurements provide evidence for a structurally well-defined, dense network of interconnected aggregates giving mechanical strength to the material. Different from a covalent network, the dynamic character of the supramolecular bonds enables macroscopic flow on a longer time scale and the establishment of an equilibrium structure. A combination of linear and nonlinear rheological measurements clearly identifies the terminal relaxation process as being responsible for the process of self-healing. PMID:27581380

Relating Topological Determinants of Complex Networks to Their Spectral Properties: Structural and Dynamical Effects

NASA Astrophysics Data System (ADS)

Castellano, Claudio; Pastor-Satorras, Romualdo

2017-10-01

The largest eigenvalue of a network's adjacency matrix and its associated principal eigenvector are key elements for determining the topological structure and the properties of dynamical processes mediated by it. We present a physically grounded expression relating the value of the largest eigenvalue of a given network to the largest eigenvalue of two network subgraphs, considered as isolated: the hub with its immediate neighbors and the densely connected set of nodes with maximum K -core index. We validate this formula by showing that it predicts, with good accuracy, the largest eigenvalue of a large set of synthetic and real-world topologies. We also present evidence of the consequences of these findings for broad classes of dynamics taking place on the networks. As a by-product, we reveal that the spectral properties of heterogeneous networks built according to the linear preferential attachment model are qualitatively different from those of their static counterparts.

Network analysis of physics discussion forums and links to course success

NASA Astrophysics Data System (ADS)

Traxler, Adrienne; Gavrin, Andrew; Lindell, Rebecca

2017-01-01

Large introductory science courses tend to isolate students, with negative consequences for long-term retention in college. Many active learning courses build collaboration and community among students as an explicit goal, and social network analysis has been used to track the development and beneficial effects of these collaborations. Here we supplement such work by conducting network analysis of online course discussion forums in two semesters of an introductory physics class. Online forums provide a tool for engaging students with each other outside of class, and offer new opportunities to commuter or non-traditional students with limited on-campus time. We look for correlations between position in the forum network (centrality) and final course grades. Preliminary investigation has shown weak correlations in the very dense full-semester network, so we will consider reduced ''backbone'' networks that highlight the most consistent links between students. Future work and implications for instruction will also be discussed.

Monitoring Malware Activity on the LAN Network

NASA Astrophysics Data System (ADS)

Skrzewski, Mirosław

Many security related organizations periodically publish current network and systems security information, with the lists of top malware programs. These lists raises the question how these threats spreads out, if the worms (the only threat with own communication abilities) are low or missing on these lists. The paper discuss the research on malware network activity, aimed to deliver the answer to the question, what is the main infection channel of modern malware, done with the usage of virtual honeypot systems on dedicated, unprotected network. Systems setup, network and systems monitoring solutions, results of over three months of network traffic and malware monitoring are presented, along with the proposed answer to our research question.

Weighted networks as randomly reinforced urn processes

NASA Astrophysics Data System (ADS)

Caldarelli, Guido; Chessa, Alessandro; Crimaldi, Irene; Pammolli, Fabio

2013-02-01

We analyze weighted networks as randomly reinforced urn processes, in which the edge-total weights are determined by a reinforcement mechanism. We develop a statistical test and a procedure based on it to study the evolution of networks over time, detecting the “dominance” of some edges with respect to the others and then assessing if a given instance of the network is taken at its steady state or not. Distance from the steady state can be considered as a measure of the relevance of the observed properties of the network. Our results are quite general, in the sense that they are not based on a particular probability distribution or functional form of the random weights. Moreover, the proposed tool can be applied also to dense networks, which have received little attention by the network community so far, since they are often problematic. We apply our procedure in the context of the International Trade Network, determining a core of “dominant edges.”

Modeling the coevolution of topology and traffic on weighted technological networks

NASA Astrophysics Data System (ADS)

Xie, Yan-Bo; Wang, Wen-Xu; Wang, Bing-Hong

2007-02-01

For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.

Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China

PubMed Central

Chen, Kai; Ni, Minjie; Wang, Jun; Huang, Dongren; Chen, Huorong; Wang, Xiao; Liu, Mengyang

2016-01-01

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO4-P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas. PMID:27777951

Optimization of a Coastal Environmental Monitoring Network Based on the Kriging Method: A Case Study of Quanzhou Bay, China.

PubMed

Chen, Kai; Ni, Minjie; Cai, Minggang; Wang, Jun; Huang, Dongren; Chen, Huorong; Wang, Xiao; Liu, Mengyang

2016-01-01

Environmental monitoring is fundamental in assessing environmental quality and to fulfill protection and management measures with permit conditions. However, coastal environmental monitoring work faces many problems and challenges, including the fact that monitoring information cannot be linked up with evaluation, monitoring data cannot well reflect the current coastal environmental condition, and monitoring activities are limited by cost constraints. For these reasons, protection and management measures cannot be developed and implemented well by policy makers who intend to solve this issue. In this paper, Quanzhou Bay in southeastern China was selected as a case study; and the Kriging method and a geographic information system were employed to evaluate and optimize the existing monitoring network in a semienclosed bay. This study used coastal environmental monitoring data from 15 sites (including COD, DIN, and PO 4 -P) to adequately analyze the water quality from 2009 to 2012 by applying the Trophic State Index. The monitoring network in Quanzhou Bay was evaluated and optimized, with the number of sites increased from 15 to 24, and the monitoring precision improved by 32.9%. The results demonstrated that the proposed advanced monitoring network optimization was appropriate for environmental monitoring in Quanzhou Bay. It might provide technical support for coastal management and pollutant reduction in similar areas.

Concentrations of hormones, pharmaceuticals and other micropollutants in groundwater affected by septic systems in New England and New York.

PubMed

Phillips, P J; Schubert, C; Argue, D; Fisher, I; Furlong, E T; Foreman, W; Gray, J; Chalmers, A

2015-04-15

Septic-system discharges can be an important source of micropollutants (including pharmaceuticals and endocrine active compounds) to adjacent groundwater and surface water systems. Groundwater samples were collected from well networks tapping glacial till in New England (NE) and sandy surficial aquifer New York (NY) during one sampling round in 2011. The NE network assesses the effect of a single large septic system that receives discharge from an extended health care facility for the elderly. The NY network assesses the effect of many small septic systems used seasonally on a densely populated portion of Fire Island. The data collected from these two networks indicate that hydrogeologic and demographic factors affect micropollutant concentrations in these systems. The highest micropollutant concentrations from the NE network were present in samples collected from below the leach beds and in a well downgradient of the leach beds. Total concentrations for personal care/domestic use compounds, pharmaceutical compounds and plasticizer compounds generally ranged from 1 to over 20 μg/L in the NE network samples. High tris(2-butoxyethyl phosphate) plasticizer concentrations in wells beneath and downgradient of the leach beds (>20 μg/L) may reflect the presence of this compound in cleaning agents at the extended health-care facility. The highest micropollutant concentrations for the NY network were present in the shoreline wells and reflect groundwater that is most affected by septic system discharges. One of the shoreline wells had personal care/domestic use, pharmaceutical, and plasticizer concentrations ranging from 0.4 to 5.7 μg/L. Estradiol equivalency quotient concentrations were also highest in a shoreline well sample (3.1 ng/L). Most micropollutant concentrations increase with increasing specific conductance and total nitrogen concentrations for shoreline well samples. These findings suggest that septic systems serving institutional settings and densely populated areas in coastal settings may be locally important sources of micropollutants to adjacent aquifer and marine systems. Published by Elsevier B.V.

A symmetric multivariate leakage correction for MEG connectomes

PubMed Central

Colclough, G.L.; Brookes, M.J.; Smith, S.M.; Woolrich, M.W.

2015-01-01

Ambiguities in the source reconstruction of magnetoencephalographic (MEG) measurements can cause spurious correlations between estimated source time-courses. In this paper, we propose a symmetric orthogonalisation method to correct for these artificial correlations between a set of multiple regions of interest (ROIs). This process enables the straightforward application of network modelling methods, including partial correlation or multivariate autoregressive modelling, to infer connectomes, or functional networks, from the corrected ROIs. Here, we apply the correction to simulated MEG recordings of simple networks and to a resting-state dataset collected from eight subjects, before computing the partial correlations between power envelopes of the corrected ROItime-courses. We show accurate reconstruction of our simulated networks, and in the analysis of real MEGresting-state connectivity, we find dense bilateral connections within the motor and visual networks, together with longer-range direct fronto-parietal connections. PMID:25862259

A flexible system for vital signs monitoring in hospital general care wards based on the integration of UNIX-based workstations, standard networks and portable vital signs monitors.

PubMed

Welch, J P; Sims, N; Ford-Carlton, P; Moon, J B; West, K; Honore, G; Colquitt, N

1991-01-01

The article describes a study conducted on general surgical and thoracic surgical floors of a 1000-bed hospital to assess the impact of a new network for portable patient care devices. This network was developed to address the needs of hospital patients who need constant, multi-parameter, vital signs surveillance, but do not require intensive nursing care. Bedside wall jacks were linked to UNIX-based workstations using standard digital network hardware, creating a flexible system (for general care floors of the hospital) that allowed the number of monitored locations to increase and decrease as patient census and acuity levels varied. It also allowed the general care floors to provide immediate, centralized vital signs monitoring for patients who unexpectedly became unstable, and permitted portable monitors to travel with patients as they were transferred between hospital departments. A disk-based log within the workstation automatically collected performance data, including patient demographics, monitor alarms, and network status for analysis. The log has allowed the developers to evaluate the use and performance of the system.

Vital signs monitoring plan for the Klamath Network: Phase I report

USGS Publications Warehouse

Sarr, Daniel; Odion, Dennis; Truitt, Robert E.; Beever, Erik A.; Shafer, Sarah; Duff, Andrew; Smith, Sean B.; Bunn, Windy; Rocchio, Judy; Sarnat, Eli; Alexander, John; Jessup, Steve

2004-01-01

This report chronicles the Phase 1 stage of the vital signs monitoring program for the Klamath Network. It consists of two chapters and eleven appendixes. The purposes of Chapter One are to 1) describe the network administrative structure and approach to planning; 2) introduce the Klamath Network parks, their resources, and environmental settings; 3) explain the need for monitoring changes in resources and supporting environments; 4) identify key information gaps that limit understanding of how to best achieve these monitoring goals. The purpose of Chapter Two is to develop the descriptive information provided in Chapter One into a conceptual basis for vital signs monitoring and to present the Network’s initial suite of conceptual models. The Report Appendices provide in-depth information on a variety of topics researched in preparation of the report, including: detailed natural resource profiles for each park, supporting policies and guidelines, regional fire regimes, vegetation types of the parks, exotic species threats, interagency monitoring programs, air issues, water quality (Phase 1 Report), Network vital signs (Scoping Summary Report), rare species, and rare habitats of the parks.

A novel hybrid approach for estimating total deposition in the United States

NASA Astrophysics Data System (ADS)

Schwede, Donna B.; Lear, Gary G.

2014-08-01

Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Network (NTN) to develop values of total deposition of sulfur and nitrogen. Data developed using this method are made available via the CASTNET website.

The “NetBoard”: Network Monitoring Tools Integration for INFN Tier-1 Data Center

NASA Astrophysics Data System (ADS)

De Girolamo, D.; dell'Agnello and, L.; Zani, S.

2012-12-01

The monitoring and alert system is fundamental for the management and the operation of the network in a large data center such as an LHC Tier-1. The network of the INFN Tier-1 at CNAF is a multi-vendor environment: for its management and monitoring several tools have been adopted and different sensors have been developed. In this paper, after an overview on the different aspects to be monitored and the tools used for them (i.e. MRTG, Nagios, Arpwatch, NetFlow, Syslog, etc), we will describe the “NetBoard”, a monitoring toolkit developed at the INFN Tier-1. NetBoard, developed for a multi-vendor network, is able to install and auto-configure all tools needed for its monitoring, either via network devices discovery mechanism or via configuration file or via wizard. In this way, we are also able to activate different types of sensors and Nagios checks according to the equipment vendor specifications. Moreover, when a new device is connected in the LAN, NetBoard can detect where it is plugged. Finally the NetBoard web interface allows to have the overall status of the entire network “at a glance”, both the local and the geographical (including the LHCOPN and the LHCONE) link utilization, health status of network devices (with active alerts) and flow analysis.

Cascadia, an ultracompact seismic instrument with over 200dB of dynamic range

NASA Astrophysics Data System (ADS)

Parker, Tim; Devanney, Peter; Bainbridge, Geoff; Townsend, Bruce

2017-04-01

Integration of geophysical instrumentation is clearly a way to lower overall station cost, make installations less complex, reduce installation time, increase station utility and value to a wider group of researchers, data miners and monitoring groups. Initiatives to expand early earthquake warning networks and observatories can use these savings for increasing station density. Integration of mature instrument systems such as broadband sensors and accelerometers used in strong motion studies has to be done with care to preserve the low noise and low frequency performance while providing over 200dB of dynamic range. Understanding the instrument complexities and deployment challenges allows the engineering teams to optimize the packaging to make installation and servicing cost effective, simple, routine and ultimately more reliable. We discuss early results from testing both in the lab and in the field of a newly released instrument called the Cascadia that integrates a broadband seismometer with a class A (USGS rating) accelerometer in a small stainless steel sonde suited for dense arrays in either ad hoc direct bury field deployments or in observatory quality shallow boreholes.

Satellite Relay Telemetry of Seismic Data in Earthquake Prediction and Control

NASA Technical Reports Server (NTRS)

Jackson, W. H.; Eaton, J. P.

1971-01-01

The Satellite Telemetry Earthquake Monitoring Program was started to evaluate the applicability of satellite relay telemetry in the collection of seismic data from a large number of dense seismograph clusters laid out along the major fault systems of western North America. Prototype clusters utilizing phone-line telemetry were then being installed by the National Center for Earthquake Research in 3 regions along the San Andreas fault in central California; and the experience of installing and operating the clusters and in reducing and analyzing the seismic data from them was to provide the raw materials for evaluation in the satellite relay telemetry project. The principal advantages of the satellite relay system over commercial telephone or microwave systems were: (1) it could be made less prone to massive failure during a major earthquake; (2) it could be extended readily into undeveloped regions; and (3) it could provide flexible, uniform communications over large sections of major global tectonic zones. Fundamental characteristics of a communications system to cope with the large volume of raw data collected by a short-period seismograph network are discussed.

Network challenges for cyber physical systems with tiny wireless devices: a case study on reliable pipeline condition monitoring.

PubMed

Ali, Salman; Qaisar, Saad Bin; Saeed, Husnain; Khan, Muhammad Farhan; Naeem, Muhammad; Anpalagan, Alagan

2015-03-25

The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs). CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed.

Network Challenges for Cyber Physical Systems with Tiny Wireless Devices: A Case Study on Reliable Pipeline Condition Monitoring

PubMed Central

Ali, Salman; Qaisar, Saad Bin; Saeed, Husnain; Farhan Khan, Muhammad; Naeem, Muhammad; Anpalagan, Alagan

2015-01-01

The synergy of computational and physical network components leading to the Internet of Things, Data and Services has been made feasible by the use of Cyber Physical Systems (CPSs). CPS engineering promises to impact system condition monitoring for a diverse range of fields from healthcare, manufacturing, and transportation to aerospace and warfare. CPS for environment monitoring applications completely transforms human-to-human, human-to-machine and machine-to-machine interactions with the use of Internet Cloud. A recent trend is to gain assistance from mergers between virtual networking and physical actuation to reliably perform all conventional and complex sensing and communication tasks. Oil and gas pipeline monitoring provides a novel example of the benefits of CPS, providing a reliable remote monitoring platform to leverage environment, strategic and economic benefits. In this paper, we evaluate the applications and technical requirements for seamlessly integrating CPS with sensor network plane from a reliability perspective and review the strategies for communicating information between remote monitoring sites and the widely deployed sensor nodes. Related challenges and issues in network architecture design and relevant protocols are also provided with classification. This is supported by a case study on implementing reliable monitoring of oil and gas pipeline installations. Network parameters like node-discovery, node-mobility, data security, link connectivity, data aggregation, information knowledge discovery and quality of service provisioning have been reviewed. PMID:25815444

Geohydrology of the Antelope Valley Area, California and design for a ground-water-quality monitoring network

USGS Publications Warehouse

Duell, L.F.

1987-01-01

A basinwide ideal network and an actual network were designed to identify ambient groundwater quality, trends in groundwater quality, and degree of threat from potential pollution sources in Antelope Valley, California. In general, throughout the valley groundwater quality has remained unchanged, and no specific trends are apparent. The main source of groundwater for the valley is generally suitable for domestic, irrigation, and most industrial uses. Water quality data for selected constituents of some network wells and surface-water sites are presented. The ideal network of 77 sites was selected on the basis of site-specific criteria, geohydrology, and current land use (agricultural, residential, and industrial). These sites were used as a guide in the design of the actual network consisting of 44 existing wells. Wells are currently being monitored and were selected whenever possible because of budgetary constraints. Of the remaining ideal sites, 20 have existing wells not part of a current water quality network, and 13 are locations where no wells exist. The methodology used for the selection of sites, constituents monitored, and frequency of analysis will enable network users to make appropriate future changes to the monitoring network. (USGS)

Peeking Network States with Clustered Patterns

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jinoh; Sim, Alex

2015-10-20

Network traffic monitoring has long been a core element for effec- tive network management and security. However, it is still a chal- lenging task with a high degree of complexity for comprehensive analysis when considering multiple variables and ever-increasing traffic volumes to monitor. For example, one of the widely con- sidered approaches is to scrutinize probabilistic distributions, but it poses a scalability concern and multivariate analysis is not gen- erally supported due to the exponential increase of the complexity. In this work, we propose a novel method for network traffic moni- toring based on clustering, one of the powerful deep-learningmore » tech- niques. We show that the new approach enables us to recognize clustered results as patterns representing the network states, which can then be utilized to evaluate “similarity” of network states over time. In addition, we define a new quantitative measure for the similarity between two compared network states observed in dif- ferent time windows, as a supportive means for intuitive analysis. Finally, we demonstrate the clustering-based network monitoring with public traffic traces, and show that the proposed approach us- ing the clustering method has a great opportunity for feasible, cost- effective network monitoring.« less

Physiologic monitoring. A guide to networking your monitoring systems.

PubMed

2011-10-01

There are many factors to consider when choosing a physiologic monitoring system. not only should these systems perform well clinically, but they should also be able to exchange data with other information systems. We discuss some of the ins and outs of physiologic monitoring system networking and highlight eight product lines from seven suppliers.

Atmospheric Mercury Deposition Monitoring – National Atmospheric Deposition Program (NADP)

EPA Science Inventory

The National Atmospheric Deposition Program (NADP) developed and operates a collaborative network of atmospheric mercury monitoring sites based in North America – the Atmospheric Mercury Network (AMNet). The justification for the network was growing interest and demand from many ...

Establishment of a hydrological monitoring network in a tropical African catchment: An integrated participatory approach

NASA Astrophysics Data System (ADS)

Gomani, M. C.; Dietrich, O.; Lischeid, G.; Mahoo, H.; Mahay, F.; Mbilinyi, B.; Sarmett, J.

Sound decision making for water resources management has to be based on good knowledge of the dominant hydrological processes of a catchment. This information can only be obtained through establishing suitable hydrological monitoring networks. Research catchments are typically established without involving the key stakeholders, which results in instruments being installed at inappropriate places as well as at high risk of theft and vandalism. This paper presents an integrated participatory approach for establishing a hydrological monitoring network. We propose a framework with six steps beginning with (i) inception of idea; (ii) stakeholder identification; (iii) defining the scope of the network; (iv) installation; (v) monitoring; and (vi) feedback mechanism integrated within the participatory framework. The approach is illustrated using an example of the Ngerengere catchment in Tanzania. In applying the approach, the concept of establishing the Ngerengere catchment monitoring network was initiated in 2008 within the Resilient Agro-landscapes to Climate Change in Tanzania (ReACCT) research program. The main stakeholders included: local communities; Sokoine University of Agriculture; Wami Ruvu Basin Water Office and the ReACCT Research team. The scope of the network was based on expert experience in similar projects and lessons learnt from literature review of similar projects from elsewhere integrated with local expert knowledge. The installations involved reconnaissance surveys, detailed surveys, and expert consultations to identify best sites. First, a Digital Elevation Model, land use, and soil maps were used to identify potential monitoring sites. Local and expert knowledge was collected on flow regimes, indicators of shallow groundwater plant species, precipitation pattern, vegetation, and soil types. This information was integrated and used to select sites for installation of an automatic weather station, automatic rain gauges, river flow gauging stations, flow measurement sites and shallow groundwater wells. The network is now used to monitor hydro-meteorological parameters in collaboration with key stakeholders in the catchment. Preliminary results indicate that the network is working well. The benefits of this approach compared to conventional narrow scientific/technical approaches have been shown by gaining rapid insight into the hydrology of the catchment, identifying best sites for the instruments; and voluntary participation of stakeholders in installation, monitoring and safeguarding the installations. This approach has proved simple yet effective and yielded good results. Based on this experience gained in applying the approach in establishing the Ngerengere catchment monitoring network, we conclude that the integrated participatory approach helps to assimilate local and expert knowledge in catchments monitoring which consequently results in: (i) identifying best sites for the hydrologic monitoring; (ii) instilling the sense of ownership; (iii) providing security of the installed network; and (iv) minimizing costs for installation and monitoring.

Web-Based Interface for Command and Control of Network Sensors

NASA Technical Reports Server (NTRS)

Wallick, Michael N.; Doubleday, Joshua R.; Shams, Khawaja S.

2010-01-01

This software allows for the visualization and control of a network of sensors through a Web browser interface. It is currently being deployed for a network of sensors monitoring Mt. Saint Helen s volcano; however, this innovation is generic enough that it can be deployed for any type of sensor Web. From this interface, the user is able to fully control and monitor the sensor Web. This includes, but is not limited to, sending "test" commands to individual sensors in the network, monitoring for real-world events, and reacting to those events

Fault tree analysis for data-loss in long-term monitoring networks.

PubMed

Dirksen, J; ten Veldhuis, J A E; Schilperoort, R P S

2009-01-01

Prevention of data-loss is an important aspect in the design as well as the operational phase of monitoring networks since data-loss can seriously limit intended information yield. In the literature limited attention has been paid to the origin of unreliable or doubtful data from monitoring networks. Better understanding of causes of data-loss points out effective solutions to increase data yield. This paper introduces FTA as a diagnostic tool to systematically deduce causes of data-loss in long-term monitoring networks in urban drainage systems. In order to illustrate the effectiveness of FTA, a fault tree is developed for a monitoring network and FTA is applied to analyze the data yield of a UV/VIS submersible spectrophotometer. Although some of the causes of data-loss cannot be recovered because the historical database of metadata has been updated infrequently, the example points out that FTA still is a powerful tool to analyze the causes of data-loss and provides useful information on effective data-loss prevention.

On the Inference of the Cosmic-ray Ionization Rate ζ from the HCO+-to-DCO+ Abundance Ratio: The Effect of Nuclear Spin

NASA Astrophysics Data System (ADS)

Shingledecker, Christopher N.; Bergner, Jennifer B.; Le Gal, Romane; Öberg, Karin I.; Hincelin, Ugo; Herbst, Eric

2016-10-01

The chemistry of dense interstellar regions was analyzed using a time-dependent gas-grain astrochemical simulation and a new chemical network that incorporates deuterated chemistry, taking into account nuclear spin states for the hydrogen chemistry and its deuterated isotopologues. With this new network, the utility of the [HCO+]/[DCO+] abundance ratio as a probe of the cosmic-ray ionization rate has been re-examined, with special attention paid to the effect of the initial value of the ortho-to-para ratio (OPR) of molecular hydrogen. After discussing the use of the probe for cold cores, we compare our results with previous theoretical and observational results for a molecular cloud close to the supernova remnant W51C, which is thought to have an enhanced cosmic-ray ionization rate ζ caused by the nearby γ-ray source. In addition, we attempt to use our approach to estimate the cosmic-ray ionization rate for L1174, a dense core with an embedded star. Beyond the previously known sensitivity of [HCO+]/[DCO+] to ζ, we demonstrate its additional dependence on the initial OPR and, secondarily, on the age of the source, its temperature, and its density. We conclude that the usefulness of the [HCO+]/[DCO+] abundance ratio in constraining the cosmic-ray ionization rate in dense regions increases with the age of the source and the ionization rate as the ratio becomes far less sensitive to the initial value of the OPR.

Effect of Grain Size on Differential Desorption of Volatile Species and on Non-ideal MHD Diffusivity

NASA Astrophysics Data System (ADS)

Zhao, Bo; Caselli, Paola; Li, Zhi-Yun

2018-05-01

We developed a chemical network for modeling the chemistry and non-ideal MHD effects from the collapsing dense molecular clouds to protostellar disks. First, we re-formulated the cosmic-ray desorption rate by considering the variations of desorption rate over the grain size distribution. We find that the differential desorption of volatile species is amplified by the grains larger than 0.1 μm, because larger grains are heated to a lower temperature by cosmic-rays and hence more sensitive to the variations in binding energies. As a result, atomic nitrogen N is ˜2 orders of magnitude more abundant than CO; N2H+ also becomes a few times more abundant than HCO+ due to the increased gas-phase N2. However, the changes in ionization fraction due to freeze-out and desorption only have minor effects on the non-ideal MHD diffusivities. Our chemical network confirms that the very small grains (VSGs: below a few 100 Å) weakens the efficiency of both ambipolar diffusion and Hall effect. In collapsing dense cores, a maximum ambipolar diffusion is achieved when truncating the MRN size distribution at 0.1 μm, and for a maximum Hall effect, the truncation occurs at 0.04 μm. We conclude that the grain size distribution is crucial to the differential depletion between CO and N2 related molecules, as well as to the non-ideal MHD diffusivities in dense cores.

Characterization of Localized Filament Corrosion Products at the Anodic Head on a Model Mg-Zn-Zr Alloy Surface

DOE PAGES

Rossouw, David; Fu, Dong; Leonard, Donovan N.; ...

2017-02-15

In this study, localized filament corrosion products at the anodic head on a model Mg-1%Zn-0.4%Zr alloy surface were characterized by electron microscopy techniques of site-specific lamella prepared by focused ion beam milling. It is revealed that the anodic head propagates underneath a largely intact thin and dense MgO surface film and comprises dense aggregates of nano-crystalline MgO within a nano-porous Mg(OH) 2 network. In conclusion, the findings contribute new supportive direct imaging insight into the source of the enhanced H 2 evolution that accompanies anodic dissolution of Mg and its alloys.

Characterization of Localized Filament Corrosion Products at the Anodic Head on a Model Mg-Zn-Zr Alloy Surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossouw, David; Fu, Dong; Leonard, Donovan N.

In this study, localized filament corrosion products at the anodic head on a model Mg-1%Zn-0.4%Zr alloy surface were characterized by electron microscopy techniques of site-specific lamella prepared by focused ion beam milling. It is revealed that the anodic head propagates underneath a largely intact thin and dense MgO surface film and comprises dense aggregates of nano-crystalline MgO within a nano-porous Mg(OH) 2 network. In conclusion, the findings contribute new supportive direct imaging insight into the source of the enhanced H 2 evolution that accompanies anodic dissolution of Mg and its alloys.

Sociometric network structure and its association with methamphetamine use norms among homeless youth.

PubMed

Barman-Adhikari, Anamika; Begun, Stephanie; Rice, Eric; Yoshioka-Maxwell, Amanda; Perez-Portillo, Andrea

2016-07-01

Homeless youths' social networks are consistently linked with their substance use. Social networks influence behavior through several mechanisms, especially social norms. This study used sociometric analyses to understand whether social norms of drug use behaviors are clustered in network structures and whether these perceived norms (descriptive and injunctive) influence youths' drug use behaviors. An event-based approach was used to delineate boundaries of the two sociometric networks of homeless youth, one in Los Angeles, CA (n = 160) and the other in Santa Monica, CA (n = 130). Network characteristics included centrality (i.e., popularity) and cohesiveness (location in dense subnetworks). The primary outcome was recent methamphetamine use. Results revealed that both descriptive and injunctive norms influenced methamphetamine use. Network cohesion was found to be associated with perception of both descriptive and injunctive norms in both networks, however in opposite directions. Network interventions therefore might be effective if designed to capitalize on social influence that naturally occurs in cohesive parts of networks. Copyright © 2016 Elsevier Inc. All rights reserved.

Motif formation and industry specific topologies in the Japanese business firm network

NASA Astrophysics Data System (ADS)

Maluck, Julian; Donner, Reik V.; Takayasu, Hideki; Takayasu, Misako

2017-05-01

Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.

A Hybrid Approach for Estimating Total Deposition in the ...

EPA Pesticide Factsheets

Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Networ

A Novel Hybrid Approach for Estimating Total Deposition in ...

EPA Pesticide Factsheets

Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Networ

Definition of air quality measurements for monitoring space shuttle launches

NASA Technical Reports Server (NTRS)

Thorpe, R. D.

1978-01-01

A description of a recommended air quality monitoring network to characterize the impact on ambient air quality in the Kennedy Space Center (KSC) (area) of space shuttle launch operations is given. Analysis of ground cloud processes and prevalent meteorological conditions indicates that transient HCl depositions can be a cause for concern. The system designed to monitor HCl employs an extensive network of inexpensive detectors combined with a central analysis device. An acid rain network is also recommended. A quantitative measure of projected minimal long-term impact involves the limited monitoring of NOx and particulates. All recommended monitoring is confined ti KSC property.

Development of on-line monitoring system for Nuclear Power Plant (NPP) using neuro-expert, noise analysis, and modified neural networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Subekti, M.; Center for Development of Reactor Safety Technology, National Nuclear Energy Agency of Indonesia, Puspiptek Complex BO.80, Serpong-Tangerang, 15340; Ohno, T.

2006-07-01

The neuro-expert has been utilized in previous monitoring-system research of Pressure Water Reactor (PWR). The research improved the monitoring system by utilizing neuro-expert, conventional noise analysis and modified neural networks for capability extension. The parallel method applications required distributed architecture of computer-network for performing real-time tasks. The research aimed to improve the previous monitoring system, which could detect sensor degradation, and to perform the monitoring demonstration in High Temperature Engineering Tested Reactor (HTTR). The developing monitoring system based on some methods that have been tested using the data from online PWR simulator, as well as RSG-GAS (30 MW research reactormore » in Indonesia), will be applied in HTTR for more complex monitoring. (authors)« less

Predicting the cumulative effect of multiple disturbances on seagrass connectivity.

PubMed

Grech, Alana; Hanert, Emmanuel; McKenzie, Len; Rasheed, Michael; Thomas, Christopher; Tol, Samantha; Wang, Mingzhu; Waycott, Michelle; Wolter, Jolan; Coles, Rob

2018-03-15

The rate of exchange, or connectivity, among populations effects their ability to recover after disturbance events. However, there is limited information on the extent to which populations are connected or how multiple disturbances affect connectivity, especially in coastal and marine ecosystems. We used network analysis and the outputs of a biophysical model to measure potential functional connectivity and predict the impact of multiple disturbances on seagrasses in the central Great Barrier Reef World Heritage Area (GBRWHA), Australia. The seagrass networks were densely connected, indicating that seagrasses are resilient to the random loss of meadows. Our analysis identified discrete meadows that are important sources of seagrass propagules and that serve as stepping stones connecting various different parts of the network. Several of these meadows were close to urban areas or ports and likely to be at risk from coastal development. Deep water meadows were highly connected to coastal meadows and may function as a refuge, but only for non-foundation species. We evaluated changes to the structure and functioning of the seagrass networks when one or more discrete meadows were removed due to multiple disturbance events. The scale of disturbance required to disconnect the seagrass networks into two or more components was on average >245 km, about half the length of the metapopulation. The densely connected seagrass meadows of the central GBRWHA are not limited by the supply of propagules; therefore, management should focus on improving environmental conditions that support natural seagrass recruitment and recovery processes. Our study provides a new framework for assessing the impact of global change on the connectivity and persistence of coastal and marine ecosystems. Without this knowledge, management actions, including coastal restoration, may prove unnecessary and be unsuccessful. © 2018 John Wiley & Sons Ltd.