European Marine Observation and Data Network EMODnet Physics

Directory of Open Access Journals (Sweden)

Antonio Novellino

2014-10-01

period, temperature of the water column, wind speed and direction, salinity of the water column, horizontal velocity of the water column, light attenuation, and sea level provided mainly by fixed stations and ferry-box platforms, discovering related data sets (both near real time and historical data sets, viewing and downloading of the data from about 2100 platforms (www.emodnetphysics.eu/map and thus contributing towards the definition of an operational European Marine Observation and Data Network (EMODnet.

European Marine Observation and Data Network EMODnet Physics

Directory of Open Access Journals (Sweden)

Antonio Novellino

2014-10-01

Full Text Available Recently the European Commission undertook steps towards a European Marine Observation and Data Network (EMODnet in order to standardize method for observing and assessing the grade of the Member States seas and improve access to high quality data. Since 2008-2009, European Commission, represented by the Directorate-General for Maritime Affairs and Fisheries (DG MARE, is running several service contracts for creating pilot thematic components of the ur-EMODNET: Biology, Bathymetry, Chemistry, Geology, Habitats, and Physics.The existing EMODnet-Physics portal (www.emodnet-physics.eu is based on a strong collaboration between EuroGOOS member institutes and its regional operational oceanographic systems (ROOSs, and the National Oceanographic Data Centres (NODCs, and it is a marine observation information system. It includes systems for physical data from the whole Europe (wave height andperiod, temperature of the water column, wind speed and direction, salinity of the water column, horizontal velocity of the water column, light attenuation, and sea level provided mainly by fixed stations and ferry-box platforms, discovering related data sets (both near real time and historical data sets, viewing and downloading of the data from about 2100 platforms (www.emodnetphysics.eu/map and thus contributing towards the definition of an operational European Marine Observation and Data Network (EMODnet.

Sensitivity of the Action Observation Network to Physical and Observational Learning

NARCIS (Netherlands)

Cross, E.S.; Kraemer, D.J.M.; Hamilton, A.F.D.C.; Kelley, W.M.; Grafton, S.T.

2009-01-01

Human motor skills can be acquired by observation without the benefit of immediate physical practice. The current study tested if physical rehearsal and observational learning share common neural substrates within an action observation network (AON) including premotor and inferior parietal regions,

Observability of Automata Networks: Fixed and Switching Cases.

Science.gov (United States)

Li, Rui; Hong, Yiguang; Wang, Xingyuan

2018-04-01

Automata networks are a class of fully discrete dynamical systems, which have received considerable interest in various different areas. This brief addresses the observability of automata networks and switched automata networks in a unified framework, and proposes simple necessary and sufficient conditions for observability. The results are achieved by employing methods from symbolic computation, and are suited for implementation using computer algebra systems. Several examples are presented to demonstrate the application of the results.

SONG-China Project: A Global Automated Observation Network

Science.gov (United States)

Yang, Z. Z.; Lu, X. M.; Tian, J. F.; Zhuang, C. G.; Wang, K.; Deng, L. C.

2017-09-01

Driven by advancements in technology and scientific objectives, data acquisition in observational astronomy has been changed greatly in recent years. Fully automated or even autonomous ground-based network of telescopes has now become a tendency for time-domain observational projects. The Stellar Observations Network Group (SONG) is an international collaboration with the participation and contribution of the Chinese astronomy community. The scientific goal of SONG is time-domain astrophysics such as asteroseismology and open cluster research. The SONG project aims to build a global network of 1 m telescopes equipped with high-precision and high-resolution spectrographs, and two-channel lucky-imaging cameras. It is the Chinese initiative to install a 50 cm binocular photometry telescope at each SONG node sharing the network platform and infrastructure. This work is focused on design and implementation in technology and methodology of SONG/50BiN, a typical ground-based network composed of multiple sites and a variety of instruments.

Code 672 observational science branch computer networks

Science.gov (United States)

Hancock, D. W.; Shirk, H. G.

1988-01-01

In general, networking increases productivity due to the speed of transmission, easy access to remote computers, ability to share files, and increased availability of peripherals. Two different networks within the Observational Science Branch are described in detail.

Energy Efficient Four Level Cooperative Opportunistic Communication for Wireless Personal Area Networks (WPAN)

DEFF Research Database (Denmark)

Rohokale, Vandana M.; Inamdar, Sandeep; Prasad, Neeli R.

2013-01-01

For wireless sensor networks (WSN),energy is a scarce resource. Due to limited battery resources, the energy consumption is the critical issue for the transmission as well as reception of the signals in the wireless communication. WSNs are infrastructure-less shared network demanding more energy...... consumption due to collaborative transmissions. This paper proposes a new cooperative opportunistic four level model for IEEE 802.15.4 Wireless Personal Area Network (WPAN).The average per node energy consumption is observed merely about 0.17mJ for the cooperative wireless communication which proves...... the proposed mechanism to be energy efficient. This paper further proposes four levels of cooperative data transmission from source to destination to improve network coverage with energy efficiency....

Social networks predict selective observation and information spread in ravens

Science.gov (United States)

Rubenstein, Daniel I.; Bugnyar, Thomas; Hoppitt, William; Mikus, Nace; Schwab, Christine

2016-01-01

Animals are predicted to selectively observe and learn from the conspecifics with whom they share social connections. Yet, hardly anything is known about the role of different connections in observation and learning. To address the relationships between social connections, observation and learning, we investigated transmission of information in two raven (Corvus corax) groups. First, we quantified social connections in each group by constructing networks on affiliative interactions, aggressive interactions and proximity. We then seeded novel information by training one group member on a novel task and allowing others to observe. In each group, an observation network based on who observed whose task-solving behaviour was strongly correlated with networks based on affiliative interactions and proximity. Ravens with high social centrality (strength, eigenvector, information centrality) in the affiliative interaction network were also central in the observation network, possibly as a result of solving the task sooner. Network-based diffusion analysis revealed that the order that ravens first solved the task was best predicted by connections in the affiliative interaction network in a group of subadult ravens, and by social rank and kinship (which influenced affiliative interactions) in a group of juvenile ravens. Our results demonstrate that not all social connections are equally effective at predicting the patterns of selective observation and information transmission. PMID:27493780

Results of Joint Observations of Jupiter's Atmosphere by Juno and a Network of Earth-Based Observing Stations

Science.gov (United States)

Orton, Glenn; Momary, Thomas; Bolton, Scott; Levin, Steven; Hansen, Candice; Janssen, Michael; Adriani, Alberto; Gladstone, G. Randall; Bagenal, Fran; Ingersoll, Andrew

2017-04-01

The Juno mission has promoted and coordinated a network of Earth-based observations, including both Earth-proximal and ground-based facilities, to extend and enhance observations made by the Juno mission. The spectral region and timeline of all of these observations are summarized in the web site: https://www.missionjuno.swri.edu/planned-observations. Among the earliest of these were observation of Jovian auroral phenomena at X-ray, ultraviolet and infrared wavelengths and measurements of Jovian synchrotron radiation from the Earth simultaneously with the measurement of properties of the upstream solar wind. Other observations of significance to the magnetosphere measured the mass loading from Io by tracking its observed volcanic activity and the opacity of its torus. Observations of Jupiter's neutral atmosphere included observations of reflected sunlight from the near-ultraviolet through the near-infrared and thermal emission from 5 μm through the radio region. The point of these measurements is to relate properties of the deep atmosphere that are the focus of Juno's mission to the state of the "weather layer" at much higher atmospheric levels. These observations cover spectral regions not included in Juno's instrumentation, provide spatial context for Juno's often spatially limited coverage of Jupiter, and they describe the evolution of atmospheric features in time that are measured only once by Juno. We will summarize the results of measurements during the approach phase of the mission that characterized the state of the atmosphere, as well as observations made by Juno and the supporting campaign during Juno's perijoves 1 (2016 August 27), 3 (2016 December 11), 4 (2017 February 2) and possibly "early" results from 5 (2017 March 27). Besides a global network of professional astronomers, the Juno mission also benefited from the enlistment of a network of dedicated amateur astronomers who provided a quasi-continuous picture of the evolution of features observed by

Analysis of stationary availability factor of two-level backbone computer networks with arbitrary topology

Science.gov (United States)

Rahman, P. A.

2018-05-01

This scientific paper deals with the two-level backbone computer networks with arbitrary topology. A specialized method, offered by the author for calculation of the stationary availability factor of the two-level backbone computer networks, based on the Markov reliability models for the set of the independent repairable elements with the given failure and repair rates and the methods of the discrete mathematics, is also discussed. A specialized algorithm, offered by the author for analysis of the network connectivity, taking into account different kinds of the network equipment failures, is also observed. Finally, this paper presents an example of calculation of the stationary availability factor for the backbone computer network with the given topology.

NEON, Establishing a Standardized Network for Groundwater Observations

Science.gov (United States)

Fitzgerald, M.; Schroeter, N.; Goodman, K. J.; Roehm, C. L.

2013-12-01

The National Ecological Observatory Network (NEON) is establishing a standardized set of data collection systems comprised of in-situ sensors and observational sampling to obtain data fundamental to the analysis of environmental change at a continental scale. NEON will be collecting aquatic, terrestrial, and atmospheric data using Observatory-wide standardized designs and methods via a systems engineering approach. This approach ensures a wealth of high quality data, data algorithms, and models that will be freely accessible to all communities such as academic researchers, policy makers, and the general public. The project is established to provide 30 years of data which will enable prediction and forecasting of drivers and responses of ecological change at scales ranging from localized responses through regional gradients and up to the continental scale. The Observatory is a distributed system of sites spread across the United States, including Alaska, Hawaii, and Puerto Rico, which is subdivided into 20 statistically unique domains, based on a set of 18 ecologically important parameters. Each domain contains at least one core aquatic and terrestrial site which are located in unmanaged lands, and up to 2 additional sites selected to study domain specific questions such as nitrogen deposition gradients and responses of land use change activities on the ecosystem. Here, we present the development of NEON's groundwater observation well network design and the timing strategy for sampling groundwater chemistry. Shallow well networks, up to 100 feet in depth, will be installed at NEON aquatic sites and will allow for observation of localized ecohydrologic site conditions, by providing basic spatio-temporal near-real time data on groundwater parameters (level, temperature, conductivity) collected from in situ high-resolution instrumentation positioned in each well; and biannual sampling of geochemical and nutrient (N and P) concentrations in a subset of wells for each

Remote observing with NASA's Deep Space Network

Science.gov (United States)

Kuiper, T. B. H.; Majid, W. A.; Martinez, S.; Garcia-Miro, C.; Rizzo, J. R.

2012-09-01

The Deep Space Network (DSN) communicates with spacecraft as far away as the boundary between the Solar System and the interstellar medium. To make this possible, large sensitive antennas at Canberra, Australia, Goldstone, California, and Madrid, Spain, provide for constant communication with interplanetary missions. We describe the procedures for radioastronomical observations using this network. Remote access to science monitor and control computers by authorized observers is provided by two-factor authentication through a gateway at the Jet Propulsion Laboratory (JPL) in Pasadena. To make such observations practical, we have devised schemes based on SSH tunnels and distributed computing. At the very minimum, one can use SSH tunnels and VNC (Virtual Network Computing, a remote desktop software suite) to control the science hosts within the DSN Flight Operations network. In this way we have controlled up to three telescopes simultaneously. However, X-window updates can be slow and there are issues involving incompatible screen sizes and multi-screen displays. Consequently, we are now developing SSH tunnel-based schemes in which instrument control and monitoring, and intense data processing, are done on-site by the remote DSN hosts while data manipulation and graphical display are done at the observer's host. We describe our approaches to various challenges, our experience with what worked well and lessons learned, and directions for future development.

Network-level accident-mapping: Distance based pattern matching using artificial neural network.

Science.gov (United States)

Deka, Lipika; Quddus, Mohammed

2014-04-01

The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily 'transferable' as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in "learning" the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that

Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

Science.gov (United States)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Towards the creation of a European Network of Earth Observation Networks within GEO. The ConnectinGEO project.

Science.gov (United States)

Masó, Joan; Serral, Ivette; Menard, Lionel; Wald, Lucien; Nativi, Stefano; Plag, Hans-Peter; Jules-Plag, Shelley; Nüst, Daniel; Jirka, Simon; Pearlman, Jay; De Maziere, Martine

2015-04-01

ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is a new H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. ConnectinGEO aims to facilitate a broader and more accessible knowledge base to support the needs of GEO, its Societal Benefit Areas (SBAs) and the users of the Global Earth Observing System of Systems (GEOSS). A broad range of subjects from climate, natural resources and raw materials, to the emerging UN Sustainable Development Goals (SDGs) will be addressed. The project will generate a prioritized list of critical gaps within available observation data and models to translate observations into practice-relevant knowledge, based on stakeholder consultation and systematic analysis. Ultimately, it will increase coherency of European observation networks, increase the use of Earth observations for assessments and forecasts and inform the planning for future observation systems. ConnectinGEO will initiate a European Network of Earth Observation Networks (ENEON) that will encompass space-based, airborne and in-situ observations networks. ENEON will be composed by project partners representing thematic observation networks along with the GEOSS Science and Technology Stakeholder Network, GEO Communities of Practices, Copernicus services, Sentinel missions and in-situ support data representatives, representatives of the space-based, airborne and in-situ observations European networks (e.g. EPOS, EMSO and GROOM, etc), representatives of the industry sector and European and national funding agencies, in particular those participating in the future ERA-PlaNET. At the beginning, the ENEON will be created and managed by the project. Then the management will be transferred to the network itself to ensure

The Network Structure Underlying the Earth Observation Assessment

Science.gov (United States)

Vitkin, S.; Doane, W. E. J.; Mary, J. C.

2017-12-01

The Earth Observations Assessment (EOA 2016) is a multiyear project designed to assess the effectiveness of civil earth observation data sources (instruments, sensors, models, etc.) on societal benefit areas (SBAs) for the United States. Subject matter experts (SMEs) provided input and scored how data sources inform products, product groups, key objectives, SBA sub-areas, and SBAs in an attempt to quantify the relationships between data sources and SBAs. The resulting data were processed by Integrated Applications Incorporated (IAI) using MITRE's PALMA software to create normalized relative impact scores for each of these relationships. However, PALMA processing obscures the natural network representation of the data. Any network analysis that might identify patterns of interaction among data sources, products, and SBAs is therefore impossible. Collaborating with IAI, we cleaned and recreated a network from the original dataset. Using R and Python we explore the underlying structure of the network and apply frequent itemset mining algorithms to identify groups of data sources and products that interact. We reveal interesting patterns and relationships in the EOA dataset that were not immediately observable from the EOA 2016 report and provide a basis for further exploration of the EOA network dataset.

Russian State Leveling Network (present and future)

Science.gov (United States)

Mazurova, Elena; Kopeikin, Sergei; Karpik, Aleksander

2017-04-01

In August 2016 the sixth session of the United Nations Committee of Experts of Global Geospatial Information Management (UN-GGIM) endorsed the roadmap for the development of a Global Geodetic Reference Frame (GGRF) and urged countries to join efforts for its creation. In response to the UN appeal in this article describes the current state of the high-precision Leveling Network in Russia and prospects of its development. In this paper, we consider projects related to the construction of new high-precision leveling lines by the classical methods, as well as issues of creating high-precision leveling network, associated with the development and implementation of a fundamentally new method of determining heights in geodesy - chronometric leveling based on the application of quantum metrology of time and the fundamental laws of general relativity. Keywords: leveling network, chronometric leveling, quantum metrology of time, the general theory of relativity.

Constructing level-2 phylogenetic networks from triplets

OpenAIRE

Iersel, Leo; Keijsper, J.C.M.; Kelk, Steven; Stougie, Leen; Hagen, F.; Boekhout, T.; Vingron, M.; Wong, L.

2009-01-01

htmlabstractJansson and Sung showed that, given a dense set of input triplets T (representing hypotheses about the local evolutionary relationships of triplets of taxa), it is possible to determine in polynomial time whether there exists a level-1 network consistent with T, and if so to construct such a network (Inferring a Level-1 Phylogenetic Network from a Dense Set of Rooted Triplets, Theoretical Computer Science, 363, pp. 60-68 (2006)). Here we extend this work by showing that this probl...

Recent Progress of Seismic Observation Networks in Japan

Science.gov (United States)

Okada, Y.

2013-04-01

Before the occurrence of disastrous Kobe earthquake in 1995, the number of high sensitivity seismograph stations operated in Japan was nearly 550 and was concentrated in the Kanto and Tokai districts, central Japan. In the wake of the Kobe earthquake, Japanese government has newly established the Headquarters for Earthquake Research Promotion and started the reconstruction of seismic networks to evenly cover the whole Japan. The basic network is composed of three seismographs, i.e. high sensitivity seismograph (Hi-net), broadband seismograph (F-net), and strong motion seismograph (K-NET). A large majority of Hi-net stations are also equipped with a pair of strong motion sensors at the bottom of borehole and the ground surface (KiK-net). A plenty of high quality data obtained from these networks are circulated at once and is producing several new seismological findings as well as providing the basis for the Earthquake Early Warning system. In March 11, 2011, "Off the Pacific coast of Tohoku Earthquake" was generated with magnitude 9.0, which records the largest in the history of seismic observation in Japan. The greatest disaster on record was brought by huge tsunami with nearly 20 thousand killed or missing people. We are again noticed that seismic observation system is quite poor in the oceanic region compared to the richness of it in the inland region. In 2012, NIED has started the construction of ocean bottom seismic and tsunami observation network along the Japan Trench. It is planned to layout 154 stations with an average spacing of 30km, each of which is equipped with an accelerometer for seismic observation and a water pressure gauge for tsunami observation. We are expecting that more rapid and accurate warning of earthquake and tsunami becomes possible by this observing network.

Recent Progress of Seismic Observation Networks in Japan

International Nuclear Information System (INIS)

Okada, Y

2013-01-01

Before the occurrence of disastrous Kobe earthquake in 1995, the number of high sensitivity seismograph stations operated in Japan was nearly 550 and was concentrated in the Kanto and Tokai districts, central Japan. In the wake of the Kobe earthquake, Japanese government has newly established the Headquarters for Earthquake Research Promotion and started the reconstruction of seismic networks to evenly cover the whole Japan. The basic network is composed of three seismographs, i.e. high sensitivity seismograph (Hi-net), broadband seismograph (F-net), and strong motion seismograph (K-NET). A large majority of Hi-net stations are also equipped with a pair of strong motion sensors at the bottom of borehole and the ground surface (KiK-net). A plenty of high quality data obtained from these networks are circulated at once and is producing several new seismological findings as well as providing the basis for the Earthquake Early Warning system. In March 11, 2011, 'Off the Pacific coast of Tohoku Earthquake' was generated with magnitude 9.0, which records the largest in the history of seismic observation in Japan. The greatest disaster on record was brought by huge tsunami with nearly 20 thousand killed or missing people. We are again noticed that seismic observation system is quite poor in the oceanic region compared to the richness of it in the inland region. In 2012, NIED has started the construction of ocean bottom seismic and tsunami observation network along the Japan Trench. It is planned to layout 154 stations with an average spacing of 30km, each of which is equipped with an accelerometer for seismic observation and a water pressure gauge for tsunami observation. We are expecting that more rapid and accurate warning of earthquake and tsunami becomes possible by this observing network.

System-level Modeling of Wireless Integrated Sensor Networks

DEFF Research Database (Denmark)

Virk, Kashif M.; Hansen, Knud; Madsen, Jan

2005-01-01

Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

Friendship network position and salivary cortisol levels.

Science.gov (United States)

Kornienko, Olga; Clemans, Katherine H; Out, Dorothée; Granger, Douglas A

2013-01-01

We employed a social network analysis approach to examine the associations between friendship network position and cortisol levels. The sample consisted of 74 first-year students (93% female, ages 22-38 years, M = 27) from a highly competitive, accelerated Nursing program. Participants completed questionnaires online, and the entire group met at one time to complete a series of sociometric nominations and donated a saliva sample. Saliva was later assayed for cortisol. Metrics derived from directed friendship nominations indexed each student's friendship network status regarding popularity, gregariousness, and degree of interconnectedness. Results revealed that (1) individuals with lower gregariousness status (i.e., lowest number of outgoing ties) had higher cortisol levels, and (2) individuals with higher popularity status (i.e., higher numbers of incoming ties) had higher cortisol levels. Popularity and gregariousness-based network status is significantly associated with hypothalamic-pituitary-adrenal axis activity. Implications for prevailing theories of the social determinants of individual differences in biological sensitivity and susceptibility to context are discussed.

The wireless networking system of Earthquake precursor mobile field observation

Science.gov (United States)

Wang, C.; Teng, Y.; Wang, X.; Fan, X.; Wang, X.

2012-12-01

The mobile field observation network could be real-time, reliably record and transmit large amounts of data, strengthen the physical signal observations in specific regions and specific period, it can improve the monitoring capacity and abnormal tracking capability. According to the features of scatter everywhere, a large number of current earthquake precursor observation measuring points, networking technology is based on wireless broadband accessing McWILL system, the communication system of earthquake precursor mobile field observation would real-time, reliably transmit large amounts of data to the monitoring center from measuring points through the connection about equipment and wireless accessing system, broadband wireless access system and precursor mobile observation management center system, thereby implementing remote instrument monitoring and data transmition. At present, the earthquake precursor field mobile observation network technology has been applied to fluxgate magnetometer array geomagnetic observations of Tianzhu, Xichang,and Xinjiang, it can be real-time monitoring the working status of the observational instruments of large area laid after the last two or three years, large scale field operation. Therefore, it can get geomagnetic field data of the local refinement regions and provide high-quality observational data for impending earthquake tracking forecast. Although, wireless networking technology is very suitable for mobile field observation with the features of simple, flexible networking etc, it also has the phenomenon of packet loss etc when transmitting a large number of observational data due to the wireless relatively weak signal and narrow bandwidth. In view of high sampling rate instruments, this project uses data compression and effectively solves the problem of data transmission packet loss; Control commands, status data and observational data transmission use different priorities and means, which control the packet loss rate within

A Network Model of Observation and Imitation of Speech

Science.gov (United States)

Mashal, Nira; Solodkin, Ana; Dick, Anthony Steven; Chen, E. Elinor; Small, Steven L.

2012-01-01

Much evidence has now accumulated demonstrating and quantifying the extent of shared regional brain activation for observation and execution of speech. However, the nature of the actual networks that implement these functions, i.e., both the brain regions and the connections among them, and the similarities and differences across these networks has not been elucidated. The current study aims to characterize formally a network for observation and imitation of syllables in the healthy adult brain and to compare their structure and effective connectivity. Eleven healthy participants observed or imitated audiovisual syllables spoken by a human actor. We constructed four structural equation models to characterize the networks for observation and imitation in each of the two hemispheres. Our results show that the network models for observation and imitation comprise the same essential structure but differ in important ways from each other (in both hemispheres) based on connectivity. In particular, our results show that the connections from posterior superior temporal gyrus and sulcus to ventral premotor, ventral premotor to dorsal premotor, and dorsal premotor to primary motor cortex in the left hemisphere are stronger during imitation than during observation. The first two connections are implicated in a putative dorsal stream of speech perception, thought to involve translating auditory speech signals into motor representations. Thus, the current results suggest that flow of information during imitation, starting at the posterior superior temporal cortex and ending in the motor cortex, enhances input to the motor cortex in the service of speech execution. PMID:22470360

Observing Arctic Ecology using Networked Infomechanical Systems

Science.gov (United States)

Healey, N. C.; Oberbauer, S. F.; Hollister, R. D.; Tweedie, C. E.; Welker, J. M.; Gould, W. A.

2012-12-01

Understanding ecological dynamics is important for investigation into the potential impacts of climate change in the Arctic. Established in the early 1990's, the International Tundra Experiment (ITEX) began observational inquiry of plant phenology, plant growth, community composition, and ecosystem properties as part of a greater effort to study changes across the Arctic. Unfortunately, these observations are labor intensive and time consuming, greatly limiting their frequency and spatial coverage. We have expanded the capability of ITEX to analyze ecological phenomenon with improved spatial and temporal resolution through the use of Networked Infomechanical Systems (NIMS) as part of the Arctic Observing Network (AON) program. The systems exhibit customizable infrastructure that supports a high level of versatility in sensor arrays in combination with information technology that allows for adaptable configurations to numerous environmental observation applications. We observe stereo and static time-lapse photography, air and surface temperature, incoming and outgoing long and short wave radiation, net radiation, and hyperspectral reflectance that provides critical information to understanding how vegetation in the Arctic is responding to ambient climate conditions. These measurements are conducted concurrent with ongoing manual measurements using ITEX protocols. Our NIMS travels at a rate of three centimeters per second while suspended on steel cables that are ~1 m from the surface spanning transects ~50 m in length. The transects are located to span soil moisture gradients across a variety of land cover types including dry heath, moist acidic tussock tundra, shrub tundra, wet meadows, dry meadows, and water tracks. We have deployed NIMS at four locations on the North Slope of Alaska, USA associated with 1 km2 ARCSS vegetation study grids including Barrow, Atqasuk, Toolik Lake, and Imnavait Creek. A fifth system has been deployed in Thule, Greenland beginning in

Robotic movement preferentially engages the action observation network

NARCIS (Netherlands)

Cross, E.S.; Liepelt, R.; Hamilton, A.F.D.C.; Parkinson, J.; Ramsey, R.; Stadler, W.; Prinz, W.G.

2012-01-01

As humans, we gather a wide range of information about other people from watching them move. A network of parietal, premotor, and occipitotemporal regions within the human brain, termed the action observation network (AON), has been implicated in understanding others' actions by means of an

Software defined network inference with evolutionary optimal observation matrices

OpenAIRE

Malboubi, M; Gong, Y; Yang, Z; Wang, X; Chuah, CN; Sharma, P

2017-01-01

© 2017 Elsevier B.V. A key requirement for network management is the accurate and reliable monitoring of relevant network characteristics. In today's large-scale networks, this is a challenging task due to the scarcity of network measurement resources and the hard constraints that this imposes. This paper proposes a new framework, called SNIPER, which leverages the flexibility provided by Software-Defined Networking (SDN) to design the optimal observation or measurement matrix that can lead t...

System-Level Design Methodologies for Networked Multiprocessor Systems-on-Chip

DEFF Research Database (Denmark)

Virk, Kashif Munir

2008-01-01

is the first such attempt in the published literature. The second part of the thesis deals with the issues related to the development of system-level design methodologies for networked multiprocessor systems-on-chip at various levels of design abstraction with special focus on the modeling and design...... at the system-level. The multiprocessor modeling framework is then extended to include models of networked multiprocessor systems-on-chip which is then employed to model wireless sensor networks both at the sensor node level as well as the wireless network level. In the third and the final part, the thesis...... to the transaction-level model. The thesis, as a whole makes contributions by describing a design methodology for networked multiprocessor embedded systems at three layers of abstraction from system-level through transaction-level to the cycle accurate level as well as demonstrating it practically by implementing...

The Meso-level Structure of F/OSS Collaboration Network

DEFF Research Database (Denmark)

Conald, Guido; Rullani, Francesco

2010-01-01

Social networks in Free/Open Source Software (F/OSS) have been usually analyzed at the level of the single project e.g., [6], or at the level of a whole ecology of projects, e.g., [33]. In this paper, we also investigate the social network generated by developers who collaborate to one or multiple...... F/OSS projects, but we focus on the less-studied meso-level structure emerging when applying to this network a community-detection technique. The network of ‘communities’ emerging from this analysis links sub-groups of densely connected developers, sub-groups that are smaller than the components...... of the network but larger than the teams working on single projects. Our results reveal the complexity of this meso-level structure, where several dense sub-groups of developers are connected by sparse collaboration among different sub-groups. We discuss the theoretical implications of our findings...

Interaction Networks: Generating High Level Hints Based on Network Community Clustering

Science.gov (United States)

Eagle, Michael; Johnson, Matthew; Barnes, Tiffany

2012-01-01

We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…

Harmonising and semantically linking key variables from in-situ observing networks of an Integrated Atlantic Ocean Observing System, AtlantOS

Science.gov (United States)

Darroch, Louise; Buck, Justin

2017-04-01

Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements at regional, national and international scales. The EU Horizon 2020 AtlantOS project aims to deliver an advanced framework for the development of an Integrated Atlantic Ocean Observing System that strengthens the Global Ocean Observing System (GOOS) and contributes to the aims of the Galway Statement on Atlantic Ocean Cooperation. One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to a wider community, including the international ocean science community and other stakeholders in this field. To help achieve this goal, the British Oceanographic Data Centre (BODC) produced a parameter matrix to harmonise data exchange, data flow and data integration for the key variables acquired by multiple in-situ AtlantOS observing networks such as ARGO, Seafloor Mapping and OceanSITES. Our solution used semantic linking of controlled vocabularies and metadata for parameters that were "mappable" to existing EU and international standard vocabularies. An AtlantOS Essential Variables list of terms (aggregated level) based on Global Climate Observing System (GCOS) Essential Climate Variables (ECV), GOOS Essential Ocean Variables (EOV) and other key network variables was defined and published on the Natural Environment Research Council (NERC) Vocabulary Server (version 2.0) as collection A05 (http://vocab.nerc.ac.uk/collection/A05/current/). This new vocabulary was semantically linked to standardised metadata for observed properties and units that had been validated by the AtlantOS community: SeaDataNet parameters (P01), Climate and Forecast (CF) Standard Names (P07) and SeaDataNet units (P06). Observed properties were mapped to biological entities from the internationally assured AphiaID from the WOrld Register of Marine Species (WoRMS), http

Caribbean Sea Level Network

Science.gov (United States)

von Hillebrandt-Andrade, C.; Crespo Jones, H.

2012-12-01

requirements and factors have been considered for the sustainability of the stations. The sea level stations have to potentially sustain very aggressive conditions of not only tsunamis, but on a more regular basis, hurricanes. Given the requirement that the data be available in near real time, for tsunami and other coastal hazard application, robust communication systems are also essential. For the local operator, the ability to be able to visualize the data is critical and tools like the IOC Sea level Monitoring Facility and the Tide Tool program are very useful. It has also been emphasized the need for these stations to serve multiple purposes. For climate and other research applications the data need to be archived, QC'd and analyzed. Increasing the user base for the sea level data has also been seen as an important goal to gain the local buy in; local weather and meteorological offices are considered as key stakeholders but for whom applications still need to be developed. The CARIBE EWS continues to look forward to working with other IOC partners including the Global Sea Level Observing System (GLOSS) and Sub-Commission for the Caribbean and Adjacent Regions (IOCARIBE)/GOOS, as well as with local, national and global sea level station operators and agencies for the development of a sustainable sea level network.

Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

Science.gov (United States)

Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

2011-01-01

Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a

Toward a national animal telemetry network for aquatic observations in the United States

Science.gov (United States)

Block, Barbara A.; Holbrook, Christopher; Simmons, Samantha E; Holland, Kim N; Ault, Jerald S.; Costa, Daniel P.; Mate, Bruce R; Seitz, Andrew C.; Arendt, Michael D.; Payne, John; Mahmoudi, Behzad; Moore, Peter L.; Price, James; J. J. Levenson,; Wilson, Doug; Kochevar, Randall E

2016-01-01

Animal telemetry is the science of elucidating the movements and behavior of animals in relation to their environment or habitat. Here, we focus on telemetry of aquatic species (marine mammals, sharks, fish, sea birds and turtles) and so are concerned with animal movements and behavior as they move through and above the world’s oceans, coastal rivers, estuaries and great lakes. Animal telemetry devices (“tags”) yield detailed data regarding animal responses to the coupled ocean–atmosphere and physical environment through which they are moving. Animal telemetry has matured and we describe a developing US Animal Telemetry Network (ATN) observing system that monitors aquatic life on a range of temporal and spatial scales that will yield both short- and long-term benefits, fill oceanographic observing and knowledge gaps and advance many of the U.S. National Ocean Policy Priority Objectives. ATN has the potential to create a huge impact for the ocean observing activities undertaken by the U.S. Integrated Ocean Observing System (IOOS) and become a model for establishing additional national-level telemetry networks worldwide.

A review on the impact of embedded generation to network fault level

Science.gov (United States)

Yahaya, M. S.; Basar, M. F.; Ibrahim, Z.; Nasir, M. N. N.; Lada, M. Y.; Bukhari, W. M.

2015-05-01

The line of Embedded Generation (EG) in power systems especially for renewable energy has increased markedly in recent years. The interconnection of EG has a technical impact which needs to considered. One of the technical challenges faced by the Distribution Network Operator (DNO) is the network fault level. In this paper, the different methods of interconnection with and without EG on the network is analyze by looking at the impact of network fault level. This comparative study made to determine the most effective method to reduce fault level or fault current. This paper will gives basic understanding on the fault level effect when synchronous generator connected to network by different method of interconnection. A three phase fault is introduced at one network bus bar. By employ it to simple network configuration of network configurations which is normal interconnection and splitting network connection with and without EG, the fault level has been simulated and analyzed. Developing the network model by using PSS-Viper™ software package, the fault level for both networks will be showed and the difference is defines. From the review, network splitting was found the best interconnection method and greatest potential for reducing the fault level in the network.

Network-level architecture and the evolutionary potential of underground metabolism.

Science.gov (United States)

Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

2014-08-12

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

Levels, Linkages, and Networks in Cross-Cultural Innovation.

Science.gov (United States)

Kennedy, Judith; Kennedy, Chris

1998-01-01

Individuals belong to different cultural networks, and these networks and connections between them play an important role in success or failure of educational innovation and should be included in any model of the management or evaluation of innovation. Looks at functions of the different networks to which individuals belong at three levels,…

Results from Joint Observations of Jupiter's Atmosphere by Juno and a Network of Earth-Based Observing Stations

Science.gov (United States)

Orton, G. S.; Bolton, S. J.; Levin, S.; Hansen, C. J.; Janssen, M. A.; Adriani, A.; Gladstone, R.; Bagenal, F.; Ingersoll, A. P.; Momary, T.; Payne, A.

2016-12-01

The Juno mission has promoted and coordinated a network of Earth-based observations, including both space- and ground-based facilities, to extend and enhance observations made by the Juno mission. The spectral region and timeline of all of these observations are summarized in the web site: https://www.missionjuno.swri.edu/planned-observations. Among the earliest of these were observation of Jovian auroral phenomena at X-ray, ultraviolet and infrared wavelengths and measurements of Jovian synchrotron radiation from the Earth simultaneously with the measurement of properties of the upstream solar wind described elsewhere in this meeting. Other observations of significance to the magnetosphere measured the mass loading from Io by tracking its observed volcanic activity and the opacity of its torus. Observations of Jupiter's neutral atmosphere included observations of reflected sunlight from the near-ultraviolet through the near-infrared and thermal emission from 5 microns through the radio region. The point of these measurements is to relate properties of the deep atmosphere that are the focus of Juno's mission to the state of the "weather layer" at much higher atmospheric levels. These observations cover spectral regions not included in Juno's instrumentation, provide spatial context for Juno's often spatially limited coverage of Jupiter, and they describe the evolution of atmospheric features in time that are measured only once by Juno. We will summarize the results of measurements during the approach phase of the mission that characterized the state of the atmosphere, as well as observations made by Juno and the supporting campaign during Juno's perijoves 1 (August 27), 2 (October 19), 3 (November 2), 4 (November 15), and 5 (November 30). The Juno mission also benefited from the enlistment of a network of dedicated amateur astronomers who, besides providing input needed for public operation of the JunoCam visible camera, tracked the evolution of features in Jupiter

USA National Phenology Network observational data documentation

Science.gov (United States)

Rosemartin, Alyssa H.; Denny, Ellen G.; Gerst, Katharine L.; Marsh, R. Lee; Posthumus, Erin E.; Crimmins, Theresa M.; Weltzin, Jake F.

2018-04-25

The goals of the USA National Phenology Network (USA-NPN, www.usanpn.org) are to advance science, inform decisions, and communicate and connect with the public regarding phenology and species’ responses to environmental variation and climate change. The USA-NPN seeks to advance the science of phenology and facilitate ecosystem stewardship by providing phenological information freely and openly. To accomplish these goals, the USA-NPN National Coordinating Office (NCO) delivers observational data on plant and animal phenology in several formats, including minimally processed status and intensity datasets and derived phenometrics for individual plants, sites, and regions. This document describes the suite of observational data products delivered by the USA National Phenology Network, covering the period 2009–present for the United States and accessible via the Phenology Observation Portal (http://dx.doi.org/10.5066/F78S4N1V) and via an Application Programming Interface. The data described here have been used in diverse research and management applications, including over 30 publications in fields such as remote sensing, plant evolution, and resource management.

The Unified Levelling Network of Sarawak and its Adjustment

Science.gov (United States)

Som, Z. A. M.; Yazid, A. M.; Ming, T. K.; Yazid, N. M.

2016-09-01

The height reference network of Sarawak has seen major improvement in over the past two decades. The most significant improvement was the establishment of extended precise leveling network of which is now able to connect all three major datum points at Pulau Lakei, Original and Bintulu. Datum by following the major accessible routes across Sarawak. This means the leveling network in Sarawak has now been inter-connected and unified. By having such a unified network leads to the possibility of having a common single least squares adjustment been performed for the first time. The least squares adjustment of this unified levelling network was attempted in order to compute the height of all Bench Marks established in the entire levelling network. The adjustment was done by using MoreFix levelling adjustment package developed at FGHT UTM. The computational procedure adopted is linear parametric adjustment by minimum constraint. Since Sarawak has three separate datums therefore three separate adjustments were implemented by utilizing datum at Pulau Lakei, Original Miri and Bintulu Datum respectively. Results of the MoreFix unified adjustment agreed very well with adjustment repeated using Starnet. Further the results were compared with solution given by Jupem and they are in good agreement as well. The difference in height analysed were within 10mm for the case of minimum constraint at Pulau Lakei datum and with much better agreement in the case of Original Miri Datum.

THE UNIFIED LEVELLING NETWORK OF SARAWAK AND ITS ADJUSTMENT

Directory of Open Access Journals (Sweden)

Z. A. M. Som

2016-09-01

Full Text Available The height reference network of Sarawak has seen major improvement in over the past two decades. The most significant improvement was the establishment of extended precise leveling network of which is now able to connect all three major datum points at Pulau Lakei, Original and Bintulu. Datum by following the major accessible routes across Sarawak. This means the leveling network in Sarawak has now been inter-connected and unified. By having such a unified network leads to the possibility of having a common single least squares adjustment been performed for the first time. The least squares adjustment of this unified levelling network was attempted in order to compute the height of all Bench Marks established in the entire levelling network. The adjustment was done by using MoreFix levelling adjustment package developed at FGHT UTM. The computational procedure adopted is linear parametric adjustment by minimum constraint. Since Sarawak has three separate datums therefore three separate adjustments were implemented by utilizing datum at Pulau Lakei, Original Miri and Bintulu Datum respectively. Results of the MoreFix unified adjustment agreed very well with adjustment repeated using Starnet. Further the results were compared with solution given by Jupem and they are in good agreement as well. The difference in height analysed were within 10mm for the case of minimum constraint at Pulau Lakei datum and with much better agreement in the case of Original Miri Datum.

Determining the confidence levels of sensor outputs using neural networks

Energy Technology Data Exchange (ETDEWEB)

Broten, G S; Wood, H C [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Electrical Engineering

1996-12-31

This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network`s ability to determine the confidence level is influenced by the complexity of the sensor`s response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

Multi-Level Secure Local Area Network

OpenAIRE

Naval Postgraduate School (U.S.); Center for Information Systems Studies Security and Research (CISR)

2011-01-01

Multi-Level Secure Local Area Network is a cost effective, multi-level, easy to use office environment leveraging existing high assurance technology. The Department of Defense and U.S. Government have an identified need to securely share information classified at differing security levels. Because there exist no commercial solutions to this problem, NPS is developing a MLS LAN. The MLS LAN extends high assurance capabilities of an evaluated multi-level secure system to commercial personal com...

A Neural-Network-Based Nonlinear Adaptive State-Observer for Pressurized Water Reactors

Directory of Open Access Journals (Sweden)

Zhe Dong

2013-10-01

Full Text Available Although there have been some severe nuclear accidents such as Three Mile Island (USA, Chernobyl (Ukraine and Fukushima (Japan, nuclear fission energy is still a source of clean energy that can substitute for fossil fuels in a centralized way and in a great amount with commercial availability and economic competitiveness. Since the pressurized water reactor (PWR is the most widely used nuclear fission reactor, its safe, stable and efficient operation is meaningful to the current rebirth of the nuclear fission energy industry. Power-level regulation is an important technique which can deeply affect the operation stability and efficiency of PWRs. Compared with the classical power-level controllers, the advanced power-level regulators could strengthen both the closed-loop stability and control performance by feeding back the internal state-variables. However, not all of the internal state variables of a PWR can be obtained directly by measurements. To implement advanced PWR power-level control law, it is necessary to develop a state-observer to reconstruct the unmeasurable state-variables. Since a PWR is naturally a complex nonlinear system with parameters varying with power-level, fuel burnup, xenon isotope production, control rod worth and etc., it is meaningful to design a nonlinear observer for the PWR with adaptability to system uncertainties. Due to this and the strong learning capability of the multi-layer perceptron (MLP neural network, an MLP-based nonlinear adaptive observer is given for PWRs. Based upon Lyapunov stability theory, it is proved theoretically that this newly-built observer can provide bounded and convergent state-observation. This observer is then applied to the state-observation of a special PWR, i.e., the nuclear heating reactor (NHR, and numerical simulation results not only verify its feasibility but also give the relationship between the observation performance and observer parameters.

Impact of additional surface observation network on short range ...

Indian Academy of Sciences (India)

has recently deployed a high-density network of. AWS over whole of India ... Weather with Observational Meso-Network and. Atmospheric Modeling .... of data assimilation in cyclic mode. In the cyclic data assimilation, model integrates forward in time and the information content propagates with the model flow. Advection of ...

Polarity-specific high-level information propagation in neural networks.

Science.gov (United States)

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

A practical algorithm for reconstructing level-1 phylogenetic networks

NARCIS (Netherlands)

Huber, K.T.; Iersel, van L.J.J.; Kelk, S.M.; Suchecki, R.

2011-01-01

Recently, much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here, we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks-a type of network

Source parameters for the 1952 Kern County earthquake, California: A joint inversion of leveling and triangulation observations

OpenAIRE

Bawden, Gerald W.

2001-01-01

Coseismic leveling and triangulation observations are used to determine the faulting geometry and slip distribution of the July 21, 1952, Mw 7.3 Kern County earthquake on the White Wolf fault. A singular value decomposition inversion is used to assess the ability of the geodetic network to resolve slip along a multisegment fault and shows that the network is sufficient to resolve slip along the surface rupture to a depth of 10 km. Below 10 km, the network can only resolve dip slip near the fa...

The US Arctic Observing Network - Mobilizing Interagency Observing Actions in an Era of Rapid Change

Science.gov (United States)

Starkweather, S.

2017-12-01

US agencies have long relied upon sustained Arctic observing to achieve their missions, be they in support of long-term monitoring, operationalized forecasts, or long-term process studies. One inventory of Arctic observing activities (arcticobservingviewer.org) suggests that there are more than 10,000 sustained data collection sites that have been supported by US agencies. Yet despite calls from academia (e.g. National Research Council, 2006) and agency leadership (e.g. IARPC, 2007) for more integrated approaches, such coherence - in the form of a US Arctic Observing Network (US AON) - has been slow and ad hoc in emerging. Two approaches have been invoked in systematically creating networks of greater coherence. One involves solving the "backward problem" or drawing existing observations into interoperable, multi-sensor, value-added data products. These approaches have the benefit that they build from existing assets and extend observations over greater time and space scales than individual efforts can approach. They suffer from being high-energy undertakings, often proceeding through voluntary efforts, and are limited by the observational assets already in place. Solving the "forward problem", or designing the network that is "needed" entails its own challenges of aligning multiple agency needs and capabilities into coordinated frameworks, often tied into a societal benefit structure. The solutions to the forward problem are greatly constrained by financial and technical feasibility. The benefit of such approaches is that interoperability and user-needs are baked into the network design, and some critical prioritization has been invoked. In September 2016, NOAA and other US agencies advanced plans to formally establish and fund the coordination of a US AON initiative. This US AON initiative brings new coordination capabilities on-line to support and strengthen US engagement in sustained and coordinated pan-Arctic observing and data sharing systems that serve

Determining the confidence levels of sensor outputs using neural networks

International Nuclear Information System (INIS)

Broten, G.S.; Wood, H.C.

1995-01-01

This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network's ability to determine the confidence level is influenced by the complexity of the sensor's response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

Principles of data integration and interoperability in the GEO Biodiversity Observation Network

Science.gov (United States)

Saarenmaa, Hannu; Ó Tuama, Éamonn

2010-05-01

The goal of the Global Earth Observation System of Systems (GEOSS) is to link existing information systems into a global and flexible network to address nine areas of critical importance to society. One of these "societal benefit areas" is biodiversity and it will be supported by a GEOSS sub-system known as the GEO Biodiversity Observation Network (GEO BON). In planning the GEO BON, it was soon recognised that there are already a multitude of existing networks and initiatives in place worldwide. What has been lacking is a coordinated framework that allows for information sharing and exchange between the networks. Traversing across the various scales of biodiversity, in particular from the individual and species levels to the ecosystems level has long been a challenge. Furthermore, some of the major regions of the world have already taken steps to coordinate their efforts, but links between the regions have not been a priority until now. Linking biodiversity data to that of the other GEO societal benefit areas, in particular ecosystems, climate, and agriculture to produce useful information for the UN Conventions and other policy-making bodies is another need that calls for integration of information. Integration and interoperability are therefore a major theme of GEO BON, and a "system of systems" is very much needed. There are several approaches to integration that need to be considered. Data integration requires harmonising concepts, agreeing on vocabularies, and building ontologies. Semantic mediation of data using these building blocks is still not easy to achieve. Agreements on, or mappings between, the metadata standards that will be used across the networks is a major requirement that will need to be addressed early on. With interoperable metadata, service integration will be possible through registry of registries systems such as GBIF's forthcoming GBDRS and the GEO Clearinghouse. Chaining various services that build intermediate products using workflow

Robustness analysis of geodetic networks in the case of correlated observations

Directory of Open Access Journals (Sweden)

Mevlut Yetkin

Full Text Available GPS (or GNSS networks are invaluable tools for monitoring natural hazards such as earthquakes. However, blunders in GPS observations may be mistakenly interpreted as deformation. Therefore, robust networks are needed in deformation monitoring using GPS networks. Robustness analysis is a natural merger of reliability and strain and defined as the ability to resist deformations caused by the maximum undetecle errors as determined from internal reliability analysis. However, to obtain rigorously correct results; the correlations among the observations must be considered while computing maximum undetectable errors. Therefore, we propose to use the normalized reliability numbers instead of redundancy numbers (Baarda's approach in robustness analysis of a GPS network. A simple mathematical relation showing the ratio between uncorrelated and correlated cases for maximum undetectable error is derived. The same ratio is also valid for the displacements. Numerical results show that if correlations among observations are ignored, dramatically different displacements can be obtained depending on the size of multiple correlation coefficients. Furthermore, when normalized reliability numbers are small, displacements get large, i.e., observations with low reliability numbers cause bigger displacements compared to observations with high reliability numbers.

Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

Directory of Open Access Journals (Sweden)

Yeqiang Shu

2012-01-01

Full Text Available The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results.

Multi-level Control Framework for Enhanced Flexibility of Active Distribution Network

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identifie......-ordination and management of the network assets at different voltage levels and geographical locations. The paper finally shows the applicability of the multi-level control architecture to some of the key challenges in the distribution system operation by relevant scenarios....... to be hosting capacity improvement, high reliable operation and cost effective network management. Based on this review and a state of the art review concerning future distribution network control methods, a multi-level control architecture is constructed for an active distribution network, which satisfies...... the selected control objectives and provides enhanced flexibility. The control architecture is supported by generation/load forecasting and distribution state estimation techniques to improve the controllability of the network. The multi-level control architecture consists of three levels of hierarchical...

Sensitivity of surface meteorological analyses to observation networks

Science.gov (United States)

Tyndall, Daniel Paul

A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.

Achieving Network Level Privacy in Wireless Sensor Networks†

Science.gov (United States)

Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2010-01-01

Full network level privacy has often been categorized into four sub-categories: Identity, Route, Location and Data privacy. Achieving full network level privacy is a critical and challenging problem due to the constraints imposed by the sensor nodes (e.g., energy, memory and computation power), sensor networks (e.g., mobility and topology) and QoS issues (e.g., packet reach-ability and timeliness). In this paper, we proposed two new identity, route and location privacy algorithms and data privacy mechanism that addresses this problem. The proposed solutions provide additional trustworthiness and reliability at modest cost of memory and energy. Also, we proved that our proposed solutions provide protection against various privacy disclosure attacks, such as eavesdropping and hop-by-hop trace back attacks. PMID:22294881

Sensitivity of the action observation network to physical and observational learning.

Science.gov (United States)

Cross, Emily S; Kraemer, David J M; Hamilton, Antonia F de C; Kelley, William M; Grafton, Scott T

2009-02-01

Human motor skills can be acquired by observation without the benefit of immediate physical practice. The current study tested if physical rehearsal and observational learning share common neural substrates within an action observation network (AON) including premotor and inferior parietal regions, that is, areas activated both for execution and observation of similar actions. Participants trained for 5 days on dance sequences set to music videos. Each day they physically rehearsed one set of dance sequences ("danced"), and passively watched a different set of sequences ("watched"). Functional magnetic resonance imaging was obtained prior to and immediately following the 5 days of training. After training, a subset of the AON showed a degree of common activity for observational and physical learning. Activity in these premotor and parietal regions was sustained during observation of sequences that were danced or watched, but declined for unfamiliar sequences relative to the pretraining scan session. These imaging data demonstrate the emergence of action resonance processes in the human brain based on observational learning without physical practice and identify commonalities in the neural substrates for physical and observational learning.

A flow level model for wireless multihop ad hoc network throughput

NARCIS (Netherlands)

Coenen, Tom Johannes Maria; van den Berg, Hans Leo; Boucherie, Richardus J.

2005-01-01

A flow level model for multihop wireless ad hoc networks is presented in this paper. Using a flow level view, we show the main properties and modeling challenges for ad hoc networks. Considering different scenarios, a multihop WLAN and a serial network with a TCP-like flow control protocol, we

Network Communication for Low Level RF Control

International Nuclear Information System (INIS)

Liu Weiqing; Yin Chengke; Zhang Tongxuan; Fu Zechuan; Liu Jianfei

2009-01-01

Low Level RF (LLRF) control system for storage ring of Shanghai Synchrotron Radiation Facility (SSRF) has been built by digital technology. The settings of parameters and the feedback loop status are carried out through the network communication interface, and the local oscillation and clock, which is the important component of the digital LLRF control system, are also configured through network communication. NIOS II processor was employed as a core to build the embedded system with a real-time operating system MicroC/OS-II, finally Lightweight TCP/IP (LwIP) was used to achieve the communication interface. The communication network is stable after a long-term operation. (authors)

The Global Geodetic Observing System: Space Geodesy Networks for the Future

Science.gov (United States)

Pearlman, Michael; Pavlis, Erricos; Ma, Chopo; Altamini, Zuheir; Noll, Carey; Stowers, David

2011-01-01

Ground-based networks of co-located space geodetic techniques (VLBI, SLR, GNSS. and DORIS) are the basis for the development and maintenance of the International Terrestrial Reference frame (ITRF), which is our metric of reference for measurements of global change, The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) has established a task to develop a strategy to design, integrate and maintain the fundamental geodetic network and supporting infrastructure in a sustainable way to satisfy the long-term requirements for the reference frame. The GGOS goal is an origin definition at 1 mm or better and a temporal stability on the order of 0.1 mm/y, with similar numbers for the scale and orientation components. These goals are based on scientific requirements to address sea level rise with confidence, but other applications are not far behind. Recent studies including one by the US National Research Council has strongly stated the need and the urgency for the fundamental space geodesy network. Simulations are underway to examining accuracies for origin, scale and orientation of the resulting ITRF based on various network designs and system performance to determine the optimal global network to achieve this goal. To date these simulations indicate that 24 - 32 co-located stations are adequate to define the reference frame and a more dense GNSS and DORIS network will be required to distribute the reference frame to users anywhere on Earth. Stations in the new global network will require geologically stable sites with good weather, established infrastructure, and local support and personnel. GGOS wil seek groups that are interested in participation. GGOS intends to issues a Call for Participation of groups that would like to contribute in the network implementation and operation. Some examples of integrated stations currently in operation or under development will be presented. We will examine necessary conditions and challenges in

Enhancement of the FDOT's project level and network level bridge management analysis tools

Science.gov (United States)

2011-02-01

Over several years, the Florida Department of Transportation (FDOT) has been implementing the AASHTO Pontis Bridge Management System to support network-level and project-level decision making in the headquarters and district offices. Pontis is an int...

Network Physics anounces first product to provide business-level management of the most complex and dynamic networks

CERN Multimedia

2003-01-01

Network Physics, provider of business-level, traffic flow-based network management solutions, today announced the introduction of the Network Physics NP/BizFlow-1000. With the NP/BizFlow-1000, Fortune 1000 companies with complex and dynamic networks can analyze the flows that link business groups, critical applications, and network software and hardware (1 page).

PolNet: A Tool to Quantify Network-Level Cell Polarity and Blood Flow in Vascular Remodeling.

Science.gov (United States)

Bernabeu, Miguel O; Jones, Martin L; Nash, Rupert W; Pezzarossa, Anna; Coveney, Peter V; Gerhardt, Holger; Franco, Claudio A

2018-05-08

In this article, we present PolNet, an open-source software tool for the study of blood flow and cell-level biological activity during vessel morphogenesis. We provide an image acquisition, segmentation, and analysis protocol to quantify endothelial cell polarity in entire in vivo vascular networks. In combination, we use computational fluid dynamics to characterize the hemodynamics of the vascular networks under study. The tool enables, to our knowledge for the first time, a network-level analysis of polarity and flow for individual endothelial cells. To date, PolNet has proven invaluable for the study of endothelial cell polarization and migration during vascular patterning, as demonstrated by two recent publications. Additionally, the tool can be easily extended to correlate blood flow with other experimental observations at the cellular/molecular level. We release the source code of our tool under the Lesser General Public License. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Estrategic prospecting for the network of weather observers

International Nuclear Information System (INIS)

Pulgarin Calle, David Esteban; Jimenez, Jose Fernando

2011-01-01

The Network of Weather Observers (RedOTA) is a reticulate system with technical and social nodes that interact to produce and share information about the weather and, to support cultural and educational dynamics, on these issues. This article describes the process of formulating a development strategy to bring the network to grow and, improving the quality of environmental information. First there is an account of the history to this initiative. Then is the definition of the ethical and operational principles underlying the network, and the description of its main actors. Finally, we present the collective exercise of strategic exploration, the definition of the action plans, the indicators to assess performance and some conclusions about the possibilities of RedOTA in the social and natural environment of the Aburra Valley.

A Practical Algorithm for Reconstructing Level-1 Phylogenetic Networks

NARCIS (Netherlands)

K.T. Huber; L.J.J. van Iersel (Leo); S.M. Kelk (Steven); R. Suchecki

2010-01-01

htmlabstractRecently much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks - a type of

Integrated Meteorological Observation Network in Castile-León (Spain)

Science.gov (United States)

Merino, A.; Guerrero-Higueras, A. M.; Ortiz de Galisteo, J. P.; López, L.; García-Ortega, E.; Nafría, D. A.; Sánchez, J. L.

2012-04-01

In the region of Castile-Leon, in the northwest of Spain, the study of weather risks is extremely complex because of the topography, the large land area of the region and the variety of climatic features involved. Therefore, as far as the calibration and validation of the necessary tools for the identification and nowcasting of these risks are concerned, one of the most important difficulties is the lack of observed data. The same problem arises, for example, in the analysis of particularly relevant case studies. It was hence deemed necessary to create an INTEGRATED METEOROLOGICAL OBSERVATION NETWORK FOR CASTILE-LEON. The aim of this network is to integrate within one single platform all the ground truth data available. These data enable us to detect a number of weather risks in real time. The various data sources should include the networks from the weather stations run by different public institutions - national and regional ones (AEMET, Junta de Castilla y León, Universities, etc.) -, as well as the stations run by voluntary observers. The platform will contain real or cuasi-real time data from the ground weather stations, but it will also have applications to enable voluntary observers to indicate the presence or absence of certain meteors (snow, hail) or even provide detailed information about them (hailstone size, graupel, etc.). The data managed by this network have a high scientific potential, as they may be used for a number of different purposes: calibration and validation of remote sensing tools, assimilation of observation data from numerical models, study of extreme weather events, etc. An additional aim of the network is the drawing of maps of weather risks in real time. These maps are of great importance for the people involved in risk management in each region, as well as for the general public. Finally, one of the first applications developed has been the creation of observation maps in real time. These applications have been constructed using NCL

Usage of link-level performance indicators for HSDPA network-level simulations in E-UMTS

NARCIS (Netherlands)

Brouwer, Frank; de Bruin, I.C.C.; Silva, João Carlos; Souto, Nuno; Cercas, Francisco; Correia, Américo

2004-01-01

The paper describes integration of HSDPA (high-speed downlink packet access) link-level simulation results into network-level simulations for enhanced UMTS. The link-level simulations model all physical layer features depicted in the 3GPP standards. These include: generation of transport blocks;

Observability and Controllability of Networks: Symmetry in Representations of Brains and Controllers for Epidemics

Science.gov (United States)

Schiff, Steven

Observability and controllability are essential concepts to the design of predictive observer models and feedback controllers of networked systems. We present a numerical and group representational framework, to quantify the observability and controllability of nonlinear networks with explicit symmetries that shows the connection between symmetries and nonlinear measures of observability and controllability. In addition to the topology of brain networks, we have advanced our ability to represent network nodes within the brain using conservation principles and more accurate biophysics that unifies the dynamics of spikes, seizures, and spreading depression. Lastly, we show how symmetries in controller design can be applied to infectious disease epidemics. NIH Grants 1R01EB014641, 1DP1HD086071.

Analytic tools for investigating the structure of network reliability measures with regard to observation correlations

Science.gov (United States)

Prószyński, W.; Kwaśniak, M.

2018-03-01

A global measure of observation correlations in a network is proposed, together with the auxiliary indices related to non-diagonal elements of the correlation matrix. Based on the above global measure, a specific representation of the correlation matrix is presented, being the result of rigorously proven theorem formulated within the present research. According to the theorem, each positive definite correlation matrix can be expressed by a scale factor and a so-called internal weight matrix. Such a representation made it possible to investigate the structure of the basic reliability measures with regard to observation correlations. Numerical examples carried out for two test networks illustrate the structure of those measures that proved to be dependent on global correlation index. Also, the levels of global correlation are proposed. It is shown that one can readily find an approximate value of the global correlation index, and hence the correlation level, for the expected values of auxiliary indices being the only knowledge about a correlation matrix of interest. The paper is an extended continuation of the previous study of authors that was confined to the elementary case termed uniform correlation. The extension covers arbitrary correlation matrices and a structure of correlation effect.

Applications of network analysis for adaptive management of artificial drainage systems in landscapes vulnerable to sea level rise

Science.gov (United States)

Poulter, Benjamin; Goodall, Jonathan L.; Halpin, Patrick N.

2008-08-01

SummaryThe vulnerability of coastal landscapes to sea level rise is compounded by the existence of extensive artificial drainage networks initially built to lower water tables for agriculture, forestry, and human settlements. These drainage networks are found in landscapes with little topographic relief where channel flow is characterized by bi-directional movement across multiple time-scales and related to precipitation, wind, and tidal patterns. The current configuration of many artificial drainage networks exacerbates impacts associated with sea level rise such as salt-intrusion and increased flooding. This suggests that in the short-term, drainage networks might be managed to mitigate sea level rise related impacts. The challenge, however, is that hydrologic processes in regions where channel flow direction is weakly related to slope and topography require extensive parameterization for numerical models which is limited where network size is on the order of a hundred or more kilometers in total length. Here we present an application of graph theoretic algorithms to efficiently investigate network properties relevant to the management of a large artificial drainage system in coastal North Carolina, USA. We created a digital network model representing the observation network topology and four types of drainage features (canal, collector and field ditches, and streams). We applied betweenness-centrality concepts (using Dijkstra's shortest path algorithm) to determine major hydrologic flowpaths based off of hydraulic resistance. Following this, we identified sub-networks that could be managed independently using a community structure and modularity approach. Lastly, a betweenness-centrality algorithm was applied to identify major shoreline entry points to the network that disproportionately control water movement in and out of the network. We demonstrate that graph theory can be applied to solving management and monitoring problems associated with sea level rise

Shortwave surface radiation network for observing small-scale cloud inhomogeneity fields

Science.gov (United States)

Lakshmi Madhavan, Bomidi; Kalisch, John; Macke, Andreas

2016-03-01

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of 99 silicon photodiode pyranometers was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. In this paper, we provide the details of this unique setup of the pyranometer network, data processing, quality control, and uncertainty assessment under variable conditions. Some exemplary days with clear, broken cloudy, and overcast skies were explored to assess the spatiotemporal observations from the network along with other collocated radiation and sky imager measurements available during the HOPE period.

Towards a Community Environmental Observation Network

Science.gov (United States)

Mertl, Stefan; Lettenbichler, Anton

2014-05-01

The Community Environmental Observation Network (CEON) is dedicated to the development of a free sensor network to collect and distribute environmental data (e.g. ground shaking, climate parameters). The data collection will be done with contributions from citizens, research institutions and public authorities like communities or schools. This will lead to a large freely available data base which can be used for public information, research, the arts,..... To start a free sensor network, the most important step is to provide easy access to free data collection and -distribution tools. The initial aims of the project CEON are dedicated to the development of these tools. A high quality data logger based on open hardware and free software is developed and a software suite of already existing free software for near-real time data communication and data distribution over the Internet will be assembled. Foremost, the development focuses on the collection of data related to the deformation of the earth (such as ground shaking, surface displacement of mass movements and glaciers) and the collection of climate data. The extent to other measurements will be considered in the design. The data logger is built using open hardware prototyping platforms like BeagleBone Black and Arduino. Main features of the data logger are: a 24Bit analog-to-digital converter; a GPS module for time reference and positioning; wireless mesh networking using Optimized Link State Routing; near real-time data transmission and communication; and near real-time differential GNSS positioning using the RTKLIB software. The project CEON is supported by the Internet Foundation Austria (IPA) within the NetIdee 2013 call.

Mining Community-Level Influence in Microblogging Network: A Case Study on Sina Weibo

Directory of Open Access Journals (Sweden)

Yufei Liu

2017-01-01

Full Text Available Social influence analysis is important for many social network applications, including recommendation and cybersecurity analysis. We observe that the influence of community including multiple users outweighs the individual influence. Existing models focus on the individual influence analysis, but few studies estimate the community influence that is ubiquitous in online social network. A major challenge lies in that researchers need to take into account many factors, such as user influence, social trust, and user relationship, to model community-level influence. In this paper, aiming to assess the community-level influence effectively and accurately, we formulate the problem of modeling community influence and construct a community-level influence analysis model. It first eliminates the zombie fans and then calculates the user influence. Next, it calculates the user final influence by combining the user influence and the willingness of diffusing theme information. Finally, it evaluates the community influence by comprehensively studying the user final influence, social trust, and relationship tightness between intrausers of communities. To handle real-world applications, we propose a community-level influence analysis algorithm called CIAA. Empirical studies on a real-world dataset from Sina Weibo demonstrate the superiority of the proposed model.

Gap analysis of the European Earth Observation Networks

Science.gov (United States)

Closa, Guillem; Serral, Ivette; Maso, Joan

2016-04-01

Earth Observations (EO) are fundamental to enhance the scientific understanding of the current status of the Earth. Nowadays, there are a lot of EO services that provide large volume of data, and the number of datasets available for different geosciences areas is increasing by the day. Despite this coverage, a glance of the European EO networks reveals that there are still some issues that are not being met; some gaps in specific themes or some thematic overlaps between different networks. This situation requires a clarification process of the actual status of the EO European networks in order to set priorities and propose future actions that will improve the European EO networks. The aim of this work is to detect the existing gaps and overlapping problems among the European EO networks. The analytical process has been done by studying the availability and the completeness of the Essential Variables (EV) data captured by the European EO networks. The concept of EVs considers that there are a number of parameters that are essential to characterize the state and trends of a system without losing significant information. This work generated a database of the existing gaps in the European EO network based on the initial GAIA-CLIM project data structure. For each theme the missing or incomplete data about each EV was indentified. Then, if incomplete, the gap was described by adding its type (geographical extent, vertical extent, temporal extent, spatial resolution, etc), the cost, the remedy, the feasibility, the impact and the priority, among others. Gaps in EO are identified following the ConnectinGEO methodology structured in 5 threads; identification of observation requirements, incorporation of international research programs material, consultation process within the current EO actors, GEOSS Discovery and Access Broker analysis, and industry-driven challenges implementation. Concretely, the presented work focuses on the second thread, which is based on

Relationships Between Long-Range Lightning Networks and TRMM/LIS Observations

Science.gov (United States)

Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cummins, Kenneth L.; Cummins, Kenneth L.; Blakeslee, Richard J.; Goodman, Steven J.

2012-01-01

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. The present study intercompares long-range lightning data with observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study examines network detection efficiency and location accuracy relative to LIS observations, describes spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by the long-range networks. Improved knowledge of relationships between these datasets will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

How to most effectively expand the global surface ozone observing network

Directory of Open Access Journals (Sweden)

E. D. Sofen

2016-02-01

Full Text Available Surface ozone observations with modern instrumentation have been made around the world for more than 40 years. Some of these observations have been made as one-off activities with short-term, specific science objectives and some have been made as part of wider networks which have provided a foundational infrastructure of data collection, calibration, quality control, and dissemination. These observations provide a fundamental underpinning to our understanding of tropospheric chemistry, air quality policy, atmosphere–biosphere interactions, etc. brought together eight of these networks to provide a single data set of surface ozone observations. We investigate how representative this combined data set is of global surface ozone using the output from a global atmospheric chemistry model. We estimate that on an area basis, 25 % of the globe is observed (34 % land, 21 % ocean. Whereas Europe and North America have almost complete coverage, other continents, Africa, South America, Australia, and Asia (12–17 % show significant gaps. Antarctica is surprisingly well observed (78 %. Little monitoring occurs over the oceans, with the tropical and southern oceans particularly poorly represented. The surface ozone over key biomes such as tropical forests and savanna is almost completely unmonitored. A chemical cluster analysis suggests that a significant number of observations are made of polluted air masses, but cleaner air masses whether over the land or ocean (especially again in the tropics are significantly under-observed. The current network is unlikely to see the impact of the El Niño–Southern Oscillation (ENSO but may be capable of detecting other planetary-scale signals. Model assessment and validation activities are hampered by a lack of observations in regions where the models differ substantially, as is the ability to monitor likely changes in surface ozone over the next century. Using our methodology we are able to suggest new

How to most effectively expand the global surface ozone observing network

Science.gov (United States)

Sofen, E. D.; Bowdalo, D.; Evans, M. J.

2016-02-01

Surface ozone observations with modern instrumentation have been made around the world for more than 40 years. Some of these observations have been made as one-off activities with short-term, specific science objectives and some have been made as part of wider networks which have provided a foundational infrastructure of data collection, calibration, quality control, and dissemination. These observations provide a fundamental underpinning to our understanding of tropospheric chemistry, air quality policy, atmosphere-biosphere interactions, etc. brought together eight of these networks to provide a single data set of surface ozone observations. We investigate how representative this combined data set is of global surface ozone using the output from a global atmospheric chemistry model. We estimate that on an area basis, 25 % of the globe is observed (34 % land, 21 % ocean). Whereas Europe and North America have almost complete coverage, other continents, Africa, South America, Australia, and Asia (12-17 %) show significant gaps. Antarctica is surprisingly well observed (78 %). Little monitoring occurs over the oceans, with the tropical and southern oceans particularly poorly represented. The surface ozone over key biomes such as tropical forests and savanna is almost completely unmonitored. A chemical cluster analysis suggests that a significant number of observations are made of polluted air masses, but cleaner air masses whether over the land or ocean (especially again in the tropics) are significantly under-observed. The current network is unlikely to see the impact of the El Niño-Southern Oscillation (ENSO) but may be capable of detecting other planetary-scale signals. Model assessment and validation activities are hampered by a lack of observations in regions where the models differ substantially, as is the ability to monitor likely changes in surface ozone over the next century. Using our methodology we are able to suggest new sites which would help to close

Influence of rainfall observation network on model calibration and application

Directory of Open Access Journals (Sweden)

A. Bárdossy

2008-01-01

Full Text Available The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as

Coastal Ocean Observing Network - Open Source Architecture for Data Management and Web-Based Data Services

Science.gov (United States)

Pattabhi Rama Rao, E.; Venkat Shesu, R.; Udaya Bhaskar, T. V. S.

2012-07-01

The observations from the oceans are the backbone for any kind of operational services, viz. potential fishing zone advisory services, ocean state forecast, storm surges, cyclones, monsoon variability, tsunami, etc. Though it is important to monitor open Ocean, it is equally important to acquire sufficient data in the coastal ocean through coastal ocean observing systems for re-analysis, analysis and forecast of coastal ocean by assimilating different ocean variables, especially sub-surface information; validation of remote sensing data, ocean and atmosphere model/analysis and to understand the processes related to air-sea interaction and ocean physics. Accurate information and forecast of the state of the coastal ocean at different time scales is vital for the wellbeing of the coastal population as well as for the socio-economic development of the country through shipping, offshore oil and energy etc. Considering the importance of ocean observations in terms of understanding our ocean environment and utilize them for operational oceanography, a large number of platforms were deployed in the Indian Ocean including coastal observatories, to acquire data on ocean variables in and around Indian Seas. The coastal observation network includes HF Radars, wave rider buoys, sea level gauges, etc. The surface meteorological and oceanographic data generated by these observing networks are being translated into ocean information services through analysis and modelling. Centralized data management system is a critical component in providing timely delivery of Ocean information and advisory services. In this paper, we describe about the development of open-source architecture for real-time data reception from the coastal observation network, processing, quality control, database generation and web-based data services that includes on-line data visualization and data downloads by various means.

Neural Network with Local Memory for Nuclear Reactor Power Level Control

International Nuclear Information System (INIS)

Uluyol, Oender; Ragheb, Magdi; Tsoukalas, Lefteri

2001-01-01

A methodology is introduced for a neural network with local memory called a multilayered local output gamma feedback (LOGF) neural network within the paradigm of locally-recurrent globally-feedforward neural networks. It appears to be well-suited for the identification, prediction, and control tasks in highly dynamic systems; it allows for the presentation of different timescales through incorporation of a gamma memory. A learning algorithm based on the backpropagation-through-time approach is derived. The spatial and temporal weights of the network are iteratively optimized for a given problem using the derived learning algorithm. As a demonstration of the methodology, it is applied to the task of power level control of a nuclear reactor at different fuel cycle conditions. The results demonstrate that the LOGF neural network controller outperforms the classical as well as the state feedback-assisted classical controllers for reactor power level control by showing a better tracking of the demand power, improving the fuel and exit temperature responses, and by performing robustly in different fuel cycle and power level conditions

Developing a network-level structural capacity index for structural evaluation of pavements.

Science.gov (United States)

2013-03-01

The objective of this project was to develop a structural index for use in network-level pavement evaluation to facilitate : the inclusion of the pavements structural condition in pavement management applications. The primary goal of network-level...

Technical and economic evaluation of voltage level in transmission network expansion planning using GA

International Nuclear Information System (INIS)

Jalilzadeh, S.; Kazemi, A.; Shayeghi, H.; Madavi, M.

2008-01-01

Transmission network expansion planning is an important part of power system planning. Its task is to determine an optimal network configuration according to load growth. It determines where, when and how many new transmission lines should be installed. Up to now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem, but in all of these methods, the STNEP problem has been solved regardless of voltage level of the lines. In this paper, due to different voltage levels in the transmission network, which cause different annual losses, STNEP has been studied considering the voltage level of the transmission lines and the network loss using the genetic algorithm (GA). Finally, the proposed idea has been examined on Garvers 6 bus network. The results show that considering the loss in a network with different voltage levels decreases the operational costs considerably, and the network satisfies the requirement of delivering electric power more safely and reliably to load centers

Observations and analysis of self-similar branching topology in glacier networks

Science.gov (United States)

Bahr, D.B.; Peckham, S.D.

1996-01-01

Glaciers, like rivers, have a branching structure which can be characterized by topological trees or networks. Probability distributions of various topological quantities in the networks are shown to satisfy the criterion for self-similarity, a symmetry structure which might be used to simplify future models of glacier dynamics. Two analytical methods of describing river networks, Shreve's random topology model and deterministic self-similar trees, are applied to the six glaciers of south central Alaska studied in this analysis. Self-similar trees capture the topological behavior observed for all of the glaciers, and most of the networks are also reasonably approximated by Shreve's theory. Copyright 1996 by the American Geophysical Union.

A Network Perspective on Individual-Level Ambidexterity in Organizations

DEFF Research Database (Denmark)

Rogan, Michelle; Mors, Marie Louise

2014-01-01

in the internal and external networks of 79 senior managers in a management consulting firm revealed significant differences in the density, contact heterogeneity, and informality of ties in the networks of senior managers who engaged in both exploration and exploitation compared with managers that predominately......Addressing the call for a deeper understanding of ambidexterity at the individual level, we propose that managers’ networks are an important yet understudied factor in the ability to balance the trade-off between exploring for new business and exploiting existing business. Analyses of 1,449 ties...... explored or exploited. The findings suggest that managers’ networks are important levers for their ability to behave ambidextrously and offer insights into the microfoundations of organizational ambidexterity....

Structural Observability and Sensor Node Selection for Complex Networks Governed by Nonlinear Balance Equations

NARCIS (Netherlands)

Kawano, Yu; Cao, Ming

2017-01-01

We define and then study the structural observability for a class of complex networks whose dynamics are governed by the nonlinear balance equations. Although related notions of observability of such complex networks have been studied before and in particular, necessary conditions have been reported

Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling

Directory of Open Access Journals (Sweden)

R. Baatz

2018-05-01

Full Text Available Advancing our understanding of Earth system dynamics (ESD depends on the development of models and other analytical tools that apply physical, biological, and chemical data. This ambition to increase understanding and develop models of ESD based on site observations was the stimulus for creating the networks of Long-Term Ecological Research (LTER, Critical Zone Observatories (CZOs, and others. We organized a survey, the results of which identified pressing gaps in data availability from these networks, in particular for the future development and evaluation of models that represent ESD processes, and provide insights for improvement in both data collection and model integration. From this survey overview of data applications in the context of LTER and CZO research, we identified three challenges: (1 widen application of terrestrial observation network data in Earth system modelling, (2 develop integrated Earth system models that incorporate process representation and data of multiple disciplines, and (3 identify complementarity in measured variables and spatial extent, and promoting synergies in the existing observational networks. These challenges lead to perspectives and recommendations for an improved dialogue between the observation networks and the ESD modelling community, including co-location of sites in the existing networks and further formalizing these recommendations among these communities. Developing these synergies will enable cross-site and cross-network comparison and synthesis studies, which will help produce insights around organizing principles, classifications, and general rules of coupling processes with environmental conditions.

Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling

Science.gov (United States)

Baatz, Roland; Sullivan, Pamela L.; Li, Li; Weintraub, Samantha R.; Loescher, Henry W.; Mirtl, Michael; Groffman, Peter M.; Wall, Diana H.; Young, Michael; White, Tim; Wen, Hang; Zacharias, Steffen; Kühn, Ingolf; Tang, Jianwu; Gaillardet, Jérôme; Braud, Isabelle; Flores, Alejandro N.; Kumar, Praveen; Lin, Henry; Ghezzehei, Teamrat; Jones, Julia; Gholz, Henry L.; Vereecken, Harry; Van Looy, Kris

2018-05-01

Advancing our understanding of Earth system dynamics (ESD) depends on the development of models and other analytical tools that apply physical, biological, and chemical data. This ambition to increase understanding and develop models of ESD based on site observations was the stimulus for creating the networks of Long-Term Ecological Research (LTER), Critical Zone Observatories (CZOs), and others. We organized a survey, the results of which identified pressing gaps in data availability from these networks, in particular for the future development and evaluation of models that represent ESD processes, and provide insights for improvement in both data collection and model integration. From this survey overview of data applications in the context of LTER and CZO research, we identified three challenges: (1) widen application of terrestrial observation network data in Earth system modelling, (2) develop integrated Earth system models that incorporate process representation and data of multiple disciplines, and (3) identify complementarity in measured variables and spatial extent, and promoting synergies in the existing observational networks. These challenges lead to perspectives and recommendations for an improved dialogue between the observation networks and the ESD modelling community, including co-location of sites in the existing networks and further formalizing these recommendations among these communities. Developing these synergies will enable cross-site and cross-network comparison and synthesis studies, which will help produce insights around organizing principles, classifications, and general rules of coupling processes with environmental conditions.

Dual-Level Game-Based Energy Efficiency and Fairness for Green Cellular Networks

Directory of Open Access Journals (Sweden)

Sungwook Kim

2016-01-01

Full Text Available In the recent decades, cellular networks have revolutionized the way of next generation communication networks. However, due to the global climate change, reducing the energy consumption of cellular infrastructures is an important and urgent problem. In this study, we propose a novel two-level cooperative game framework for improving the energy efficiency and fairness in cellular networks. For the energy efficiency, base stations (BSs constantly monitor the current traffic load and cooperate with each other to maximize the energy saving. For the energy fairness, renewable energy can be shared dynamically while ensuring the fairness among BSs. To achieve an excellent cellular network performance, the concepts of the Raiffa Bargaining Solution and Jain’s fairness are extended and practically applied to our dual-level cooperative game model. Through system level simulations, the proposed scheme is evaluated and compared with other existing schemes. The simulation results show that our two-level game approach outperforms the existing schemes in providing a better fair-efficient system performance.

A High-Level Petri Net Framework for Genetic Regulatory Networks

Directory of Open Access Journals (Sweden)

Banks Richard

2007-12-01

Full Text Available To understand the function of genetic regulatory networks in the development of cellular systems, we must not only realise the individual network entities, but also the manner by which they interact. Multi-valued networks are a promising qualitative approach for modelling such genetic regulatory networks, however, at present they have limited formal analysis techniques and tools. We present a flexible formal framework for modelling and analysing multi-valued genetic regulatory networks using high-level Petri nets and logic minimization techniques. We demonstrate our approach with a detailed case study in which part of the genetic regulatory network responsible for the carbon starvation stress response in Escherichia coli is modelled and analysed. We then compare and contrast this multivalued model to a corresponding Boolean model and consider their formal relationship.

Present day sea level changes: observation and causes

International Nuclear Information System (INIS)

Lombard, A.

2005-11-01

Whereas sea level has changed little over the last 2000 years, it has risen at a rate of about 2 mm/year during the 20. century. This unexpected sea level rise has been attributed to the anthropogenic global warming, recorded over several decades. Sea level variations have been measured globally and precisely for about 12 years due to satellite altimeter missions Topex/Poseidon and Jason-1. These observations indicate a global mean sea level rise of about 3 mm/year since 1993, a value significantly larger than observed during previous decades. Recent observations have allowed us to quantify the various climatic factors contributing to observed sea level change: thermal expansion of sea water due to ocean warming, melting of mountain glaciers and ice sheets, and changes in the land water reservoirs. A water budget based on these new observations allows us to partly explain the observed sea level rise. In particular, we show that the thermal expansion explains only 25% of the secular sea level rise as recorded by tide-gauges over the last 50 years, while it contributes about 50% of sea level rise observed over the last decade. Meanwhile, recent studies show that glacier and ice sheet melting could contribute the equivalent of 1 mm/year in sea level rise over the last decade. In addition, the high regional variability of sea level trends revealed by satellite altimetry is mainly due to thermal expansion. There is also an important decadal spatio-temporal variability in the ocean thermal expansion over the last 50 years, which seems to be controlled by natural climate fluctuations. We question for the first time the link between the decadal fluctuations in the ocean thermal expansion and in the land reservoirs, and indeed their climatic contribution to sea level change. Finally a preliminary analysis of GRACE spatial gravimetric observations over the oceans allows us to estimate the seasonal variations in mean sea level due to ocean water mass balance variations

Convolutional Neural Networks for Text Categorization: Shallow Word-level vs. Deep Character-level

OpenAIRE

Johnson, Rie; Zhang, Tong

2016-01-01

This paper reports the performances of shallow word-level convolutional neural networks (CNN), our earlier work (2015), on the eight datasets with relatively large training data that were used for testing the very deep character-level CNN in Conneau et al. (2016). Our findings are as follows. The shallow word-level CNNs achieve better error rates than the error rates reported in Conneau et al., though the results should be interpreted with some consideration due to the unique pre-processing o...

Distributed estimation based on observations prediction in wireless sensor networks

KAUST Repository

Bouchoucha, Taha; Ahmed, Mohammed F A; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2015-01-01

We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process

Regulatory networks, legal federalism, and multi-level regulatory systems

OpenAIRE

Kerber, Wolfgang; Wendel, Julia

2016-01-01

Transnational regulatory networks play important roles in multi-level regulatory regimes, as e.g, the European Union. In this paper we analyze the role of regulatory networks from the perspective of the economic theory of legal federalism. Often sophisticated intermediate institutional solutions between pure centralisation and pure decentralisation can help to solve complex tradeoff problems between the benefits and problems of centralised and decentralised solutions. Drawing upon the insight...

The GEO Handbook on Biodiversity Observation Networks

CSIR Research Space (South Africa)

Walters, Michele

2017-01-01

Full Text Available across the planet. I congratulate GEO BON on creating this powerful mechanism and wish the GEO BON community great success in each of its future endeavours. Geneva, Switzerland Barbara J. Ryan Executive Director: Group on Earth Observations viii Foreword... of biodiversity data is the desired goal, it would be hard to achieve except via the mechanism of a network, simply because 6 R.J. Scholes et al. sampling and species identification is more cost-effective and situation-appropriate if conducted using local...

Evaluation on surface current observing network of high frequency ground wave radars in the Gulf of Thailand

Science.gov (United States)

Yin, Xunqiang; Shi, Junqiang; Qiao, Fangli

2018-05-01

Due to the high cost of ocean observation system, the scientific design of observation network becomes much important. The current network of the high frequency radar system in the Gulf of Thailand has been studied using a three-dimensional coastal ocean model. At first, the observations from current radars have been assimilated into this coastal model and the forecast results have improved due to the data assimilation. But the results also show that further optimization of the observing network is necessary. And then, a series of experiments were carried out to assess the performance of the existing high frequency ground wave radar surface current observation system. The simulated surface current data in three regions were assimilated sequentially using an efficient ensemble Kalman filter data assimilation scheme. The experimental results showed that the coastal surface current observation system plays a positive role in improving the numerical simulation of the currents. Compared with the control experiment without assimilation, the simulation precision of surface and subsurface current had been improved after assimilated the surface currents observed at current networks. However, the improvement for three observing regions was quite different and current observing network in the Gulf of Thailand is not effective and a further optimization is required. Based on these evaluations, a manual scheme has been designed by discarding the redundant and inefficient locations and adding new stations where the performance after data assimilation is still low. For comparison, an objective scheme based on the idea of data assimilation has been obtained. Results show that all the two schemes of observing network perform better than the original network and optimal scheme-based data assimilation is much superior to the manual scheme that based on the evaluation of original observing network in the Gulf of Thailand. The distributions of the optimal network of radars could be a

Japanese VLBI Network Observations of a Gamma-Ray Narrow ...

Indian Academy of Sciences (India)

J. Astrophys. Astr. (2014) 35, 215–218 c Indian Academy of Sciences. Japanese VLBI Network Observations of a Gamma-Ray. Narrow-Line Seyfert 1 Galaxy 1H 0323+342. Kiyoaki Wajima1,∗. , Kenta Fujisawa2, Masaaki Hayashida3. & Naoki Isobe4. 1Shanghai Astronomical Observatory, Chinese Academy of Sciences,.

Experimental observation of chimera and cluster states in a minimal globally coupled network

Energy Technology Data Exchange (ETDEWEB)

Hart, Joseph D. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Bansal, Kanika [Department of Mathematics, University at Buffalo, SUNY Buffalo, New York 14260 (United States); US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005 (United States); Murphy, Thomas E. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742 (United States); Roy, Rajarshi [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742 (United States)

2016-09-15

A “chimera state” is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.

Distributed estimation based on observations prediction in wireless sensor networks

KAUST Repository

Bouchoucha, Taha

2015-03-19

We consider wireless sensor networks (WSNs) used for distributed estimation of unknown parameters. Due to the limited bandwidth, sensor nodes quantize their noisy observations before transmission to a fusion center (FC) for the estimation process. In this letter, the correlation between observations is exploited to reduce the mean-square error (MSE) of the distributed estimation. Specifically, sensor nodes generate local predictions of their observations and then transmit the quantized prediction errors (innovations) to the FC rather than the quantized observations. The analytic and numerical results show that transmitting the innovations rather than the observations mitigates the effect of quantization noise and hence reduces the MSE. © 2015 IEEE.

Uniqueness, intractability and exact algorithms: reflections on level-k phylogenetic networks

NARCIS (Netherlands)

L.J.J. van Iersel (Leo); S.M. Kelk (Steven); M. Mnich

2009-01-01

htmlabstractPhylogenetic networks provide a way to describe and visualize evolutionary histories that have undergone so-called reticulate evolutionary events such as recombination, hybridization or horizontal gene transfer. The level k of a network determines how non-treelike the evolution can be,

Cities, Europeanization and Multi-level Governance: Governing Climate Change through Transnational Municipal Networks

NARCIS (Netherlands)

Kern, K.; Bulkeley, H.

2009-01-01

This article focuses on a variant of multi-level governance and Europeanization, i.e. the transnational networking of local authorities. Focusing on local climate change policy, the article examines how transnational municipal networks (TMNs) govern in the context of multi-level European governance.

Networked web-cameras monitor congruent seasonal development of birches with phenological field observations

Science.gov (United States)

Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Kubin, Eero; Linkosalmi, Maiju; Melih Tanis, Cemal; Nadir Arslan, Ali

2017-04-01

Ecosystems' potential to provide services, e.g. to sequester carbon is largely driven by the phenological cycle of vegetation. Timing of phenological events is required for understanding and predicting the influence of climate change on ecosystems and to support various analyses of ecosystem functioning. We established a network of cameras for automated monitoring of phenological activity of vegetation in boreal ecosystems of Finland. Cameras were mounted on 14 sites, each site having 1-3 cameras. In this study, we used cameras at 11 of these sites to investigate how well networked cameras detect phenological development of birches (Betula spp.) along the latitudinal gradient. Birches are interesting focal species for the analyses as they are common throughout Finland. In our cameras they often appear in smaller quantities within dominant species in the images. Here, we tested whether small scattered birch image elements allow reliable extraction of color indices and changes therein. We compared automatically derived phenological dates from these birch image elements to visually determined dates from the same image time series, and to independent observations recorded in the phenological monitoring network from the same region. Automatically extracted season start dates based on the change of green color fraction in the spring corresponded well with the visually interpreted start of season, and field observed budburst dates. During the declining season, red color fraction turned out to be superior over green color based indices in predicting leaf yellowing and fall. The latitudinal gradients derived using automated phenological date extraction corresponded well with gradients based on phenological field observations from the same region. We conclude that already small and scattered birch image elements allow reliable extraction of key phenological dates for birch species. Devising cameras for species specific analyses of phenological timing will be useful for

Controlling Voltage Levels of Distribution Network-Radial Feeder after Connecting Wind Turbines to the Network

Directory of Open Access Journals (Sweden)

Muhammad Al Badri

2017-11-01

Full Text Available Several factors in power generation and supply need to be taken into account such as shortages of energy supply, system stability, and energy quality and system disruption due to network losses, industrial development and population expansion. The addition of wind turbines to the distribution network is of great benefit in providing additional power and solving these problems, but this addition is accompanied by the problem of low voltage network. This research found optimal solutions to the problem of low voltage distribution network after connecting wind turbines. The main idea of this paper is to optimize the low-voltage problem as a result of connecting the wind turbines to the "far end" of the radial feeder for a distribution network and to obtain a voltage level within an acceptable and stable range. The problem of low voltage solved by using the load-drop compensation, capacitor-bank and “doubly-fed” induction generators. The results of this study were based on the operation of the entire design of the simulation system which would be compatible with the reality of the energy flow of all network components by using the PSCAD program. The present analysis program revealed an optimum solution for the low voltage profile of the distribution network after connecting the wind turbine.

Sea Levels Online: Sea Level Variations of the United States Derived from National Water Level Observation Network Stations

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Water level records are a combination of the fluctuations of the ocean and the vertical land motion at the location of the station. Monthly mean sea level (MSL)...

Mean-field level analysis of epidemics in directed networks

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiazeng [School of Mathematical Sciences, Peking University, Beijing 100871 (China); Liu, Zengrong [Mathematics Department, Shanghai University, Shanghai 200444 (China)], E-mail: wangjiazen@yahoo.com.cn, E-mail: zrongliu@online.sh.cn

2009-09-04

The susceptible-infected-removed spreading model in a directed graph is studied. The mean-field level rate equations are built with the degree-degree connectivity correlation element and the (in, out)-degree distribution. And the outbreak threshold is obtained analytically-it is determined by the combination of connectivity probability and the degree distribution. Furthermore, the methods of calculating the degree-degree correlations in directed networks are presented. The numerical results of the discrete epidemic processes in networks verify our analyses.

Mean-field level analysis of epidemics in directed networks

International Nuclear Information System (INIS)

Wang, Jiazeng; Liu, Zengrong

2009-01-01

The susceptible-infected-removed spreading model in a directed graph is studied. The mean-field level rate equations are built with the degree-degree connectivity correlation element and the (in, out)-degree distribution. And the outbreak threshold is obtained analytically-it is determined by the combination of connectivity probability and the degree distribution. Furthermore, the methods of calculating the degree-degree correlations in directed networks are presented. The numerical results of the discrete epidemic processes in networks verify our analyses.

Combining region- and network-level brain-behavior relationships in a structural equation model.

Science.gov (United States)

Bolt, Taylor; Prince, Emily B; Nomi, Jason S; Messinger, Daniel; Llabre, Maria M; Uddin, Lucina Q

2018-01-15

Brain-behavior associations in fMRI studies are typically restricted to a single level of analysis: either a circumscribed brain region-of-interest (ROI) or a larger network of brain regions. However, this common practice may not always account for the interdependencies among ROIs of the same network or potentially unique information at the ROI-level, respectively. To account for both sources of information, we combined measurement and structural components of structural equation modeling (SEM) approaches to empirically derive networks from ROI activity, and to assess the association of both individual ROIs and their respective whole-brain activation networks with task performance using three large task-fMRI datasets and two separate brain parcellation schemes. The results for working memory and relational tasks revealed that well-known ROI-performance associations are either non-significant or reversed when accounting for the ROI's common association with its corresponding network, and that the network as a whole is instead robustly associated with task performance. The results for the arithmetic task revealed that in certain cases, an ROI can be robustly associated with task performance, even when accounting for its associated network. The SEM framework described in this study provides researchers additional flexibility in testing brain-behavior relationships, as well as a principled way to combine ROI- and network-levels of analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

Information Extraction with Character-level Neural Networks and Free Noisy Supervision

OpenAIRE

Meerkamp, Philipp; Zhou, Zhengyi

2016-01-01

We present an architecture for information extraction from text that augments an existing parser with a character-level neural network. The network is trained using a measure of consistency of extracted data with existing databases as a form of noisy supervision. Our architecture combines the ability of constraint-based information extraction systems to easily incorporate domain knowledge and constraints with the ability of deep neural networks to leverage large amounts of data to learn compl...

Optimization of observation plan based on the stochastic characteristics of the geodetic network

Directory of Open Access Journals (Sweden)

Pachelski Wojciech

2016-06-01

Full Text Available Optimal design of geodetic network is a basic subject of many engineering projects. An observation plan is a concluding part of the process. Any particular observation within the network has through adjustment a different contribution and impact on values and accuracy characteristics of unknowns. The problem of optimal design can be solved by means of computer simulation. This paper presents a new method of simulation based on sequential estimation of individual observations in a step-by-step manner, by means of the so-called filtering equations. The algorithm aims at satisfying different criteria of accuracy according to various interpretations of the covariance matrix. Apart of them, the optimization criterion is also amount of effort, defined as the minimum number of observations required.

Forbush decreases on November 6-12, 2004 observed by the Muon Detector Network

Energy Technology Data Exchange (ETDEWEB)

Savian, Jairo Francisco; Schuch, Nelson Jorge [Southern Regional Space Research Center, CRSPE/INPE-MCT, Santa Maria, RS (Brazil); Silva, Marlos Rockenbach da; Lago, Alisson dal; Echer, Ezequiel; Vieira, Luis Eduardo Antunes; Gonzalez, Walter Demetrio [National Institute for Space Research, INPE-MCT, Sao Jose dos Campos, SP (Brazil); Munakata, Kazuoki, E-mail: savian@lacesm.ufsm.br, E-mail: njschuch@lacesm.ufsm.br, E-mail: marlos@dge.inpe.br, E-mail: dallago@dge.inpe.br, E-mail: eecher@dge.inpe.br, E-mail: vieira-le@uol.com.br, E-mail: gonzalez@dge.inpe.br, E-mail: kmuna00@shinshu-u.ac.jp [Physics Department, Shinshu University, Matsumoto, (Japan)

2007-07-01

In this paper we study the relationship between interplanetary coronal mass ejections (ICMEs) and the muon count rate decreases detected of the muon detector network on November 6-12, 2004. The muon detector network is composed by the detectors installed at Nagoya (Japan), Hobart (Australia) and the prototype detector installed at the 'Observatorio Espacial do Sul - OES/CRSPE/INPE-MCT', located in Sao Martinho da Serra, RS, Brazil. With the muon count rate observed by the muon detector network, we will be able to observe, in the future, the direction in which a given ICME moves, and with that, we will be able to calculate their angle of incidence on the Earth. Also, with this muon network, we will be able to send alerts of up to 12 hours before the arrival of a shock or an ICME. The space weather forecast method using cosmic rays will be a very important tool because it provides a forecast with good antecedence. (author)

Estimating interevent time distributions from finite observation periods in communication networks

Science.gov (United States)

Kivelä, Mikko; Porter, Mason A.

2015-11-01

A diverse variety of processes—including recurrent disease episodes, neuron firing, and communication patterns among humans—can be described using interevent time (IET) distributions. Many such processes are ongoing, although event sequences are only available during a finite observation window. Because the observation time window is more likely to begin or end during long IETs than during short ones, the analysis of such data is susceptible to a bias induced by the finite observation period. In this paper, we illustrate how this length bias is born and how it can be corrected without assuming any particular shape for the IET distribution. To do this, we model event sequences using stationary renewal processes, and we formulate simple heuristics for determining the severity of the bias. To illustrate our results, we focus on the example of empirical communication networks, which are temporal networks that are constructed from communication events. The IET distributions of such systems guide efforts to build models of human behavior, and the variance of IETs is very important for estimating the spreading rate of information in networks of temporal interactions. We analyze several well-known data sets from the literature, and we find that the resulting bias can lead to systematic underestimates of the variance in the IET distributions and that correcting for the bias can lead to qualitatively different results for the tails of the IET distributions.

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

Science.gov (United States)

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.

Development of a Ground-Based Atmospheric Monitoring Network for the Global Mercury Observation System (GMOS

Directory of Open Access Journals (Sweden)

Sprovieri F.

2013-04-01

Full Text Available Consistent, high-quality measurements of atmospheric mercury (Hg are necessary in order to better understand Hg emissions, transport, and deposition on a global scale. Although the number of atmospheric Hg monitoring stations has increased in recent years, the available measurement database is limited and there are many regions of the world where measurements have not been extensively performed. Long-term atmospheric Hg monitoring and additional ground-based monitoring sites are needed in order to generate datasets that will offer new insight and information about the global scale trends of atmospheric Hg emissions and deposition. In the framework of the Global Mercury Observation System (GMOS project, a coordinated global observational network for atmospheric Hg is being established. The overall research strategy of GMOS is to develop a state-of-the-art observation system able to provide information on the concentration of Hg species in ambient air and precipitation on the global scale. This network is being developed by integrating previously established ground-based atmospheric Hg monitoring stations with newly established GMOS sites that are located both at high altitude and sea level locations, as well as in climatically diverse regions. Through the collection of consistent, high-quality atmospheric Hg measurement data, we seek to create a comprehensive assessment of atmospheric Hg concentrations and their dependence on meteorology, long-range atmospheric transport and atmospheric emissions.

Critical network effect induces business oscillations in multi-level marketing systems

OpenAIRE

Juanico, Dranreb Earl

2012-01-01

The "social-networking revolution" of late (e.g., with the advent of social media, Facebook, and the like) has been propelling the crusade to elucidate the embedded networks that underlie economic activity. An unexampled synthesis of network science and economics uncovers how the web of human interactions spurred by familiarity and similarity could potentially induce the ups and downs ever so common to our economy. Zeroing in on the million-strong global industry known as multi-level marketin...

GLM Proxy Data Generation: Methods for Stroke/Pulse Level Inter-Comparison of Ground-Based Lightning Reference Networks

Science.gov (United States)

Cummins, Kenneth L.; Carey, Lawrence D.; Schultz, Christopher J.; Bateman, Monte G.; Cecil, Daniel J.; Rudlosky, Scott D.; Petersen, Walter Arthur; Blakeslee, Richard J.; Goodman, Steven J.

2011-01-01

In order to produce useful proxy data for the GOES-R Geostationary Lightning Mapper (GLM) in regions not covered by VLF lightning mapping systems, we intend to employ data produced by ground-based (regional or global) VLF/LF lightning detection networks. Before using these data in GLM Risk Reduction tasks, it is necessary to have a quantitative understanding of the performance of these networks, in terms of CG flash/stroke DE, cloud flash/pulse DE, location accuracy, and CLD/CG classification error. This information is being obtained through inter-comparison with LMAs and well-quantified VLF/LF lightning networks. One of our approaches is to compare "bulk" counting statistics on the spatial scale of convective cells, in order to both quantify relative performance and observe variations in cell-based temporal trends provided by each network. In addition, we are using microsecond-level stroke/pulse time correlation to facilitate detailed inter-comparisons at a more-fundamental level. The current development status of our ground-based inter-comparison and evaluation tools will be presented, and performance metrics will be discussed through a comparison of Vaisala s Global Lightning Dataset (GLD360) with the NLDN at locations within and outside the U.S.

The relationship between structure and function in locally observed complex networks

International Nuclear Information System (INIS)

Comin, Cesar H; Viana, Matheus P; Costa, Luciano da F

2013-01-01

Recently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or differentiated) by the structure of the underlying system. Here we define a new measure that, based on the dynamical characteristics obtained for a large set of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measure, we find that the geographic and Barabási–Albert models have a high capacity for generating networks that exhibit groups of nodes with distinct dynamics compared to the rest of the network. The application of our methodology is illustrated with respect to two real systems. In the first we use the neuronal network of the nematode Caenorhabditis elegans to show that the interneurons of the ventral cord of the nematode present a very large dynamical differentiation when compared to the rest of the network. The second application concerns the SIS epidemic model on an airport network, where we quantify how different the distribution of infection times of high and low degree nodes can be, when compared to the expected value for the network. (paper)

DReAM: Demand Response Architecture for Multi-level District Heating and Cooling Networks

Energy Technology Data Exchange (ETDEWEB)

Bhattacharya, Saptarshi; Chandan, Vikas; Arya, Vijay; Kar, Koushik

2017-05-19

In this paper, we exploit the inherent hierarchy of heat exchangers in District Heating and Cooling (DHC) networks and propose DReAM, a novel Demand Response (DR) architecture for Multi-level DHC networks. DReAM serves to economize system operation while still respecting comfort requirements of individual consumers. Contrary to many present day DR schemes that work on a consumer level granularity, DReAM works at a level of hierarchy above buildings, i.e. substations that supply heat to a group of buildings. This improves the overall DR scalability and reduce the computational complexity. In the first step of the proposed approach, mathematical models of individual substations and their downstream networks are abstracted into appropriately constructed low-complexity structural forms. In the second step, this abstracted information is employed by the utility to perform DR optimization that determines the optimal heat inflow to individual substations rather than buildings, in order to achieve the targeted objectives across the network. We validate the proposed DReAM framework through experimental results under different scenarios on a test network.

Biodiversity monitoring in Europe: the EU FP7 EBONE project. European biodiversity observation NEtwork

CSIR Research Space (South Africa)

Lück-Vogel, Melanie

2008-09-01

Full Text Available submission Presentation Poster presentation A) Title Biodiversity Monitoring in Europe: The EU FP7 EBONE project European Biodiversity Observation NEtwork B) Short title EBONE - European Biodiversity Observation NEtwork C) Author(s) Vogel, M. (1... stream_source_info Vogel_2008.pdf.txt stream_content_type text/plain stream_size 3055 Content-Encoding UTF-8 stream_name Vogel_2008.pdf.txt Content-Type text/plain; charset=UTF-8 BIOTA AFRICA Congress 2008 Abstract...

Integrating Micro-level Interactions with Social Network Analysis in Tie Strength Research

DEFF Research Database (Denmark)

Torre, Osku; Gupta, Jayesh Prakash; Kärkkäinen, Hannu

2017-01-01

of tie strength based on reciprocal interaction from publicly available Facebook data, and suggest that this approach could work as a basis for further tie strength studies. Our approach makes use of weak tie theory, and enables researchers to study micro-level interactions (i.e. discussions, messages......A social tie is a target for ongoing, high-level scientific debate. Measuring the tie strength in social networks has been an important topic for academic studies since Mark Granovetter's seminal papers in 1970's. However, it is still a problematic issue mainly for two reasons: 1) existing tie...... strengthening process in online social networks. Therefore, we suggest a new approach to tie strength research, which focuses on studying communication patterns (edges) more rather than actors (nodes) in a social network. In this paper we build a social network analysis-based approach to enable the evaluation...

Ground level cosmic ray observations

Energy Technology Data Exchange (ETDEWEB)

Stephens, S.A. [Tata Institute of Fundamental Research, Bombay (International Commission on Radiation Units and Measurements); Grimani, C.; Brunetti, M.T.; Codino, A. [Perugia Univ. (Italy)]|[INFN, Perugia (Italy); Papini, P.; Massimo Brancaccio, F.; Piccardi, S. [Florence Univ. (Italy)]|[INFN, Florence (Italy); Basini, G.; Bongiorno, F. [INFN, Laboratori Nazionali di Frascati, Rome (Italy); Golden, R.L. [New Mexico State Univ., Las Cruces, NM (United States). Particle Astrophysics Lab.; Hof, M. [Siegen Univ. (Germany). Fachbereich Physik

1995-09-01

Cosmic rays at ground level have been collected using the NMSU/Wizard - MASS2 instrument. The 17-hr observation run was made on September 9. 1991 in Fort Sumner, New Mexico, Usa. Fort Sumner is located at 1270 meters a.s.l., corresponding to an atmospheric depth of about 887 g/cm{sup 2}. The geomagnetic cutoff is 4.5 GV/c. The charge ratio of positive and negative muons and the proton to muon ratio have been determined. These observations will also be compared with data collected at a higher latitude using the same basic apparatus.

Water Level Station History

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Images contain station history information for 175 stations in the National Water Level Observation Network (NWLON). The NWLON is a network of long-term,...

Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

Directory of Open Access Journals (Sweden)

Yuqi Guo

2017-08-01

Full Text Available In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM, the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.

SHORT-TERM SOLAR FLARE LEVEL PREDICTION USING A BAYESIAN NETWORK APPROACH

International Nuclear Information System (INIS)

Yu Daren; Huang Xin; Hu Qinghua; Zhou Rui; Wang Huaning; Cui Yanmei

2010-01-01

A Bayesian network approach for short-term solar flare level prediction has been proposed based on three sequences of photospheric magnetic field parameters extracted from Solar and Heliospheric Observatory/Michelson Doppler Imager longitudinal magnetograms. The magnetic measures, the maximum horizontal gradient, the length of neutral line, and the number of singular points do not have determinate relationships with solar flares, so the solar flare level prediction is considered as an uncertainty reasoning process modeled by the Bayesian network. The qualitative network structure which describes conditional independent relationships among magnetic field parameters and the quantitative conditional probability tables which determine the probabilistic values for each variable are learned from the data set. Seven sequential features-the maximum, the mean, the root mean square, the standard deviation, the shape factor, the crest factor, and the pulse factor-are extracted to reduce the dimensions of the raw sequences. Two Bayesian network models are built using raw sequential data (BN R ) and feature extracted data (BN F ), respectively. The explanations of these models are consistent with physical analyses of experts. The performances of the BN R and the BN F appear comparable with other methods. More importantly, the comprehensibility of the Bayesian network models is better than other methods.

Letter to Editor: RESITA NETWORK - ACADEMIC ENTREPRENEURSHIP AND INNOVATION NETWORK OF SOUTH EASTERN EUROPEAN UNIVERSITIES: AN EXAMPLE OF SUCCESSFUL NETWORKING IN ENTREPRENEURSHIP AND INNOVATION AT ACADEMIC LEVEL

Directory of Open Access Journals (Sweden)

Peter Schulte

2013-05-01

Full Text Available The foundation, development, activities, and wider social impact of the AcademicEntrepreneurship and Innovation Network of South Eastern European Universities, or shortlyRESITA Network, is presented in this paper as a positive example of successful networking inentrepreneurship and innovation at academic level.

Managing coopetition through horizontal supply chain relations : Linking dyadic and network levels of analysis

NARCIS (Netherlands)

Wilhelm, Miriam M.

2011-01-01

A growing research stream has expanded the level of analysis beyond single buyer-supplier relations to the network, including supplier-supplier relations. These supplier-supplier relations may constitute a missing link between the traditional analysis of the dyadic and the network level of analysis

Managing coopetition through horizontal supply chain relations : Linking dyadic and network levels of analysis

NARCIS (Netherlands)

Wilhelm, Miriam M.

A growing research stream has expanded the level of analysis beyond single buyer-supplier relations to the network, including supplier-supplier relations. These supplier-supplier relations may constitute a missing link between the traditional analysis of the dyadic and the network level of analysis

Equipment Management for Sensor Networks: Linking Physical Infrastructure and Actions to Observational Data

Science.gov (United States)

Jones, A. S.; Horsburgh, J. S.; Matos, M.; Caraballo, J.

2015-12-01

Networks conducting long term monitoring using in situ sensors need the functionality to track physical equipment as well as deployments, calibrations, and other actions related to site and equipment maintenance. The observational data being generated by sensors are enhanced if direct linkages to equipment details and actions can be made. This type of information is typically recorded in field notebooks or in static files, which are rarely linked to observations in a way that could be used to interpret results. However, the record of field activities is often relevant to analysis or post-processing of the observational data. We have developed an underlying database schema and deployed a web interface for recording and retrieving information on physical infrastructure and related actions for observational networks. The database schema for equipment was designed as an extension to the Observations Data Model 2 (ODM2), a community-developed information model for spatially discrete, feature based earth observations. The core entities of ODM2 describe location, observed variable, and timing of observations, and the equipment extension contains entities to provide additional metadata specific to the inventory of physical infrastructure and associated actions. The schema is implemented in a relational database system for storage and management with an associated web interface. We designed the web-based tools for technicians to enter and query information on the physical equipment and actions such as site visits, equipment deployments, maintenance, and calibrations. These tools were implemented for the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) ecohydrologic observatory, and we anticipate that they will be useful for similar large-scale monitoring networks desiring to link observing infrastructure to observational data to increase the quality of sensor-based data products.

Three-Level Z-Source Inverters Using a Single LC Impedance Network

DEFF Research Database (Denmark)

Loh, Poh Chiang; Lim, Sok Wei; Gao, Feng

2007-01-01

two LC impedance networks and two isolated dc sources, which can significantly increase the overall system cost and require a more complex modulator for balancing the network inductive voltage boosting. Offering a number of less costly alternatives, this letter presents the design and control of two...... three-level Z-source inverters, whose output voltage can be stepped down or up using only a single LC impedance network connected between the dc input source and either a neutral-point-clamped (NPC) or dc-link cascaded inverter circuitry. Through careful design of their modulation scheme, both inverters...

Thunderstorm monitoring with VLF network and super dense meteorological observation system

Science.gov (United States)

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

Overview of gas flux measurements from volcanoes of the global Network for Observation of Volcanic and Atmospheric Change (NOVAC)

Science.gov (United States)

Galle, Bo; Arellano, Santiago; Conde, Vladimir

2015-04-01

NOVAC, the Network for Observation of Volcanic and Atmospheric Change, was initiated in 2005 as a 5-years-long project financed by the European Union. Its main purpose is to create a global network for the study of volcanic atmospheric plumes and related geophysical phenomena by using state-of-the-art spectroscopic remote sensing technology. Up to 2014, 67 instruments have been installed at 25 volcanoes in 13 countries of Latin America, Italy, Democratic Republic of Congo, Reunion, Iceland, and Philippines, and efforts are being done to expand the network to other active volcanic zones. NOVAC has been a pioneer initiative in the community of volcanologists and embraces the objectives of the Word Organization of Volcano Observatories (WOVO) and the Global Earth Observation System of Systems (GEOSS). In this contribution, we present the results of the measurements of SO2 gas fluxes carried out within NOVAC, which for some volcanoes represent a record of more than 8 years of semi-continuous monitoring. The network comprises some of the most strongly degassing volcanoes in the world, covering a broad range of tectonic settings, levels of unrest, and potential risk. Examples of correlations with seismicity and other geophysical phenomena, environmental impact studies and comparisons with previous global estimates will be discussed as well as the significance of the database for further studies in volcanology and other geosciences.

Inventory of gas flux measurements from volcanoes of the global Network for Observation of Volcanic and Atmospheric Change (NOVAC)

Science.gov (United States)

Galle, B.; Arellano, S.; Norman, P.; Conde, V.

2012-04-01

NOVAC, the Network for Observation of Volcanic and Atmospheric Change, was initiated in 2005 as a 5-year-long project financed by the European Union. Its main purpose is to create a global network for the monitoring and research of volcanic atmospheric plumes and related geophysical phenomena by using state-of-the-art spectroscopic remote sensing technology. Up to 2012, 64 instruments have been installed at 24 volcanoes in 13 countries of Latin America, Italy, Democratic Republic of Congo, Reunion, Iceland, and Philippines, and efforts are being done to expand the network to other active volcanic zones. NOVAC has been a pioneer initiative in the community of volcanologists and embraces the objectives of the Word Organization of Volcano Observatories (WOVO) and the Global Earth Observation System of Systems (GEOSS). In this contribution, we present the results of the measurements of SO2 gas fluxes carried out within NOVAC, which for some volcanoes represent a record of more than 7 years of continuous monitoring. The network comprises some of the most strongly degassing volcanoes in the world, covering a broad range of tectonic settings, levels of unrest, and potential risk. We show a global perspective of the output of volcanic gas from the covered regions, specific trends of degassing for a few selected volcanoes, and the significance of the database for further studies in volcanology and other geosciences.

The Dynamics of network and dyad level supply management

DEFF Research Database (Denmark)

Ellegaard, Chris

-supplier relation and its immediate network context, are presented. In analysing the data, the dynamic interdependency between management of one level and management of the other, will be demonstrated. The analysis reveals a need for an alternating approach to supply management, which takes the dynamic complexity...

Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks

KAUST Repository

Douik, Ahmed

2016-03-28

In the context of resource allocation in cloud- radio access networks, recent studies assume either signal-level or scheduling-level coordination. This paper, instead, considers a hybrid level of coordination for the scheduling problem in the downlink of a multi-cloud radio- access network, so as to benefit from both scheduling policies. Consider a multi-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and therefore allows joint signal processing between them. Across the multiple clouds, however, only scheduling-level coordination is permitted, as it requires a lower level of backhaul communication. The frame structure of every BS is composed of various time/frequency blocks, called power- zones (PZs), and kept at fixed power level. The paper addresses the problem of maximizing a network-wide utility by associating users to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled, at most, to a single cloud, but possibly to many BSs within the cloud, and can be served by one or more distinct PZs within the BSs\\' frame. The paper solves the problem using graph theory techniques by constructing the conflict graph. The scheduling problem is, then, shown to be equivalent to a maximum- weight independent set problem in the constructed graph, in which each vertex symbolizes an association of cloud, user, BS and PZ, with a weight representing the utility of that association. Simulation results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

The Vigil Network: A means of observing landscape change in drainage basins

Science.gov (United States)

Osterkamp, W.R.; Emmett, W.W.; Leopold, Luna Bergere

1991-01-01

Long-term monitoring of geomorphic, hydrological, and biological characteristics of landscapes provides an effective means of relating observed change to possible causes of the change. Identification of changes in basin characteristics, especially in arid areas where the response to altered climate or land use is generally rapid and readily apparent, might provide the initial direct indications that factors such as global warming and cultural impacts have affected the environment. The Vigil Network provides an opportunity for earth and life scientists to participate in a systematic monitoring effort to detect landscape changes over time, and to relate such changes to possible causes. The Vigil Network is an ever-increasing group of sites and basins used to monitor landscape features with as much as 50 years of documented geomorphic and related observations.

Gap Filling of Daily Sea Levels by Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Lyubka Pashova

2013-06-01

Full Text Available In the recent years, intelligent methods as artificial neural networks are successfully applied for data analysis from different fields of the geosciences. One of the encountered practical problems is the availability of gaps in the time series that prevent their comprehensive usage for the scientific and practical purposes. The article briefly describes two types of the artificial neural network (ANN architectures - Feed-Forward Backpropagation (FFBP and recurrent Echo state network (ESN. In some cases, the ANN can be used as an alternative on the traditional methods, to fill in missing values in the time series. We have been conducted several experiments to fill the missing values of daily sea levels spanning a 5-years period using both ANN architectures. A multiple linear regression for the same purpose has been also applied. The sea level data are derived from the records of the tide gauge Burgas, which is located on the western Black Sea coast. The achieved results have shown that the performance of ANN models is better than that of the classical one and they are very promising for the real-time interpolation of missing data in the time series.

European Marine Observation Data Network - EMODnet Physics

Science.gov (United States)

Manzella, Giuseppe M. R.; Novellino, Antonio; D'Angelo, Paolo; Gorringe, Patrick; Schaap, Dick; Pouliquen, Sylvie; Loubrieu, Thomas; Rickards, Lesley

2015-04-01

The EMODnet-Physics portal (www.emodnet-physics.eu) makes layers of physical data and their metadata available for use and contributes towards the definition of an operational European Marine Observation and Data Network (EMODnet). It is based on a strong collaboration between EuroGOOS associates and its regional operational systems (ROOSs), and it is bringing together two very different marine communities: the "real time" ocean observing institute/centers and the National Oceanographic Data Centres (NODCs) that are in charge of ocean data validation, quality check and update for marine environmental monitoring. The EMODnet-Physics is a Marine Observation and Data Information System that provides a single point of access to near real time and historical achieved data (www.emodnet-physics.eu/map) it is built on existing infrastructure by adding value and avoiding any unless complexity, it provides data access to users, it is aimed at attracting new data holders, better and more data. With a long-term vision for a pan European Ocean Observation System sustainability, the EMODnet-Physics is supporting the coordination of the EuroGOOS Regional components and the empowerment and improvement of their data management infrastructure. In turn, EMODnet-Physics already implemented high-level interoperability features (WMS, Web catalogue, web services, etc…) to facilitate connection and data exchange with the ROOS and the Institutes within the ROOSs (www.emodnet-physics.eu/services). The on-going EMODnet-Physics structure delivers environmental marine physical data from the whole Europe (wave height and period, temperature of the water column, wind speed and direction, salinity of the water column, horizontal velocity of the water column, light attenuation, and sea level) as monitored by fixed stations, ARGO floats, drifting buoys, gliders, and ferry-boxes. It does provide discovering of data sets (both NRT - near real time - and Historical data sets), visualization and free

Robust Synchronization in an E/I Network with Medium Synaptic Delay and High Level of Heterogeneity

International Nuclear Information System (INIS)

Han Fang; Wang Zhi-Jie; Gong Tao; Fan Hong

2015-01-01

It is known that both excitatory and inhibitory neuronal networks can achieve robust synchronization only under certain conditions, such as long synaptic delay or low level of heterogeneity. In this work, robust synchronization can be found in an excitatory/inhibitory (E/I) neuronal network with medium synaptic delay and high level of heterogeneity, which often occurs in real neuronal networks. Two effects of post-synaptic potentials (PSP) to network synchronization are presented, and the synaptic contribution of excitatory and inhibitory neurons to robust synchronization in this E/I network is investigated. It is found that both excitatory and inhibitory neurons may contribute to robust synchronization in E/I networks, especially the excitatory PSP has a more positive effect on synchronization in E/I networks than that in excitatory networks. This may explain the strong robustness of synchronization in E/I neuronal networks. (paper)

Network Resilience Analysis: Review Of Concepts And A Country-Level. Case Study

Directory of Open Access Journals (Sweden)

Mariusz Kamola

2014-01-01

Full Text Available This paper presents the rationale behind performing an analysis of Internet resilience in the sense of maintaining a connection of autonomous systems in the presence of failures or attacks — on a level of a single country. Next, the graph of a network is constructed that represents interconnections between autonomous systems. The connectivity of the graph is examined for cases of link or node failure. Resilience metrics are proposed, focusing on a single autonomous system or on overall network reliability. The process of geographic location of networking infrastructure is presented, leading to an analysis of network resilience in the case of a joint failure of neighboring autonomous systems.

Between "design" and "bricolage": genetic networks, levels of selection, and adaptive evolution.

Science.gov (United States)

Wilkins, Adam S

2007-05-15

The extent to which "developmental constraints" in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a "network perspective" may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed.

Psychology and social networks: a dynamic network theory perspective.

Science.gov (United States)

Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

2014-04-01

Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

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

Science.gov (United States)

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

2018-04-01

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

Estimating surface soil moisture from SMAP observations using a Neural Network technique.

Science.gov (United States)

Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

2018-01-01

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Distributed Observer Network (DON), Version 3.0, User's Guide

Science.gov (United States)

Mazzone, Rebecca A.; Conroy, Michael P.

2015-01-01

The Distributed Observer Network (DON) is a data presentation tool developed by the National Aeronautics and Space Administration (NASA) to distribute and publish simulation results. Leveraging the display capabilities inherent in modern gaming technology, DON places users in a fully navigable 3-D environment containing graphical models and allows the users to observe how those models evolve and interact over time in a given scenario. Each scenario is driven with data that has been generated by authoritative NASA simulation tools and exported in accordance with a published data interface specification. This decoupling of the data from the source tool enables DON to faithfully display a simulator's results and ensure that every simulation stakeholder will view the exact same information every time.

A possible edge effect in enhanced network. [solar K-line observations by multichannel spectrometer

Science.gov (United States)

Jones, H. P.; Brown, D. R.

1977-01-01

K-line observations of enhanced network taken with the NASA/SPO Multichannel Spectrometer on September 28, 1975, in support of OSO-8 are discussed. The data show a correlation between core brightness and asymmetry for spatial scans which cross enhanced network boundaries. The implications of this result concerning mass flow in and near supergranule boundaries are discussed.

Sea level differences between Topex/Poseidon altimetry and tide gauges: observed trends and vertical land motions

Science.gov (United States)

Lombard, A.; Dominh, K.; Cazenave, A.; Calmant, S.; Cretaux, J.

2002-12-01

Nine year-long (1993-2001) sea level difference time series have been constructed by comparing sea level recorded by tide gauges and Topex/Poseidon altimetry. Although the primary goal of such an analysis is to define a sub network of good quality tide gauges for calibration of satellite altimetry systems, in particular Jason-1. The difference time series displaying large positive or negative trends may give evidence of vertical land motion at the tide gauge site. We have analyzed 98 tide gauge records from the UHSLC. Among them, 42 sites mainly located on open ocean islands, give very good agreement (better than 2 mm/year) with Topex/Poseidon-derived sea level trends. 22 other sites, mainly located along the continental coastlines of the Pacific Ocean, present sea level trends differing by more than 5 mm/year with Topex/Poseidon. Many of these sites are located in active tectonic areas (either in the vicinity of subduction zones or in active volcanic areas), where vertical land motions (either transient or long-term) are expected. For example, this is the case at Kushimoto, Ofunato, Kushiro (Japan), Kodiak Island and Yakutat (Alaska), La Libertad, Callao, Caldera (western south America), and Rabaul (western Pacific). When possible, we compare these observed trends in sea level differences with GPS and/or DORIS observations.

Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train

Directory of Open Access Journals (Sweden)

Yun Li

2013-01-01

Full Text Available A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropriate parameter. When sensor faults happen, the residual between the real states and the observer outputs indicates which kind of sensor failures occurs. Finally, simulation results using the actual parameters of CMS-04 maglev train indicate that the proposed method is effective for maglev train.

An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

Directory of Open Access Journals (Sweden)

Liu Lili

2013-06-01

Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

A BHR Composite Network-Based Visualization Method for Deformation Risk Level of Underground Space.

Directory of Open Access Journals (Sweden)

Wei Zheng

Full Text Available This study proposes a visualization processing method for the deformation risk level of underground space. The proposed method is based on a BP-Hopfield-RGB (BHR composite network. Complex environmental factors are integrated in the BP neural network. Dynamic monitoring data are then automatically classified in the Hopfield network. The deformation risk level is combined with the RGB color space model and is displayed visually in real time, after which experiments are conducted with the use of an ultrasonic omnidirectional sensor device for structural deformation monitoring. The proposed method is also compared with some typical methods using a benchmark dataset. Results show that the BHR composite network visualizes the deformation monitoring process in real time and can dynamically indicate dangerous zones.

Toward a Theory of Industrial Supply Networks: A Multi-Level Perspective via Network Analysis

Directory of Open Access Journals (Sweden)

Yi Zuo

2017-07-01

Full Text Available In most supply chains (SCs, transaction relationships between suppliers and customers are commonly considered to be an extrapolation from a linear perspective. However, this traditional linear concept of an SC is egotistic and oversimplified and does not sufficiently reflect the complex and cyclical structure of supplier-customer relationships in current economic and industrial situations. The interactional relationships and topological characteristics between suppliers and customers should be analyzed using supply networks (SNs rather than traditional linear SCs. Therefore, this paper reconceptualizes SCs as SNs in complex adaptive systems (CAS, and presents three main contributions. First, we propose an integrated framework of CAS network by synthesizing multi-level network analysis from the network-, community- and vertex-perspective. The CAS perspective enables us to understand the advances of SN properties. Second, in order to emphasize the CAS properties of SNs, we conducted a real-world SN based on the Japanese industry and describe an advanced investigation of SN theory. The CAS properties help in enriching the SN theory, which can benefit SN management, community economics and industrial resilience. Third, we propose a quantitative metric of entropy to measure the complexity and robustness of SNs. The results not only support a specific understanding of the structural outcomes relevant to SNs, but also deliver efficient and effective support to the management and design of SNs.

Character-level neural network for biomedical named entity recognition.

Science.gov (United States)

Gridach, Mourad

2017-06-01

Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance. In this paper, we introduce a novel neural network architecture that benefits from both word- and character-level representations automatically, by using a combination of bidirectional long short-term memory (LSTM) and conditional random field (CRF) eliminating the need for most feature engineering tasks. We evaluate our system on two datasets: JNLPBA corpus and the BioCreAtIvE II Gene Mention (GM) corpus. We obtained state-of-the-art performance by outperforming the previous systems. To the best of our knowledge, we are the first to investigate the combination of deep neural networks, CRF, word embeddings and character-level representation in recognizing biomedical named entities. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of a Regional Neural Network for Coastal Water Level Predictions

National Research Council Canada - National Science Library

Huang, Wenrui; Murray, Catherine; Kraus, Nicholas; Rosati, Julie

2003-01-01

.... Fortunately, the US National Oceanographic and Atmospheric Administration (NOAA) has a national network of water level monitoring stations distributed in regional scale that has been operating for several decades...

The 1% rule in four digital health social networks: an observational study.

Science.gov (United States)

van Mierlo, Trevor

2014-02-04

In recent years, cyberculture has informally reported a phenomenon named the 1% rule, or 90-9-1 principle, which seeks to explain participatory patterns and network effects within Internet communities. The rule states that 90% of actors observe and do not participate, 9% contribute sparingly, and 1% of actors create the vast majority of new content. This 90%, 9%, and 1% are also known as Lurkers, Contributors, and Superusers, respectively. To date, very little empirical research has been conducted to verify the 1% rule. The 1% rule is widely accepted in digital marketing. Our goal was to determine if the 1% rule applies to moderated Digital Health Social Networks (DHSNs) designed to facilitate behavior change. To help gain insight into participatory patterns, descriptive data were extracted from four long-standing DHSNs: the AlcoholHelpCenter, DepressionCenter, PanicCenter, and StopSmokingCenter sites. During the study period, 63,990 actors created 578,349 posts. Less than 25% of actors made one or more posts. The applicability of the 1% rule was confirmed as Lurkers, Contributors, and Superusers accounted for a weighted average of 1.3% (n=4668), 24.0% (n=88,732), and 74.7% (n=276,034) of content. The 1% rule was consistent across the four DHSNs. As social network sustainability requires fresh content and timely interactions, these results are important for organizations actively promoting and managing Internet communities. Superusers generate the vast majority of traffic and create value, so their recruitment and retention is imperative for long-term success. Although Lurkers may benefit from observing interactions between Superusers and Contributors, they generate limited or no network value. The results of this study indicate that DHSNs may be optimized to produce network effects, positive externalities, and bandwagon effects. Further research in the development and expansion of DHSNs is required.

The 1% Rule in Four Digital Health Social Networks: An Observational Study

Science.gov (United States)

2014-01-01

Background In recent years, cyberculture has informally reported a phenomenon named the 1% rule, or 90-9-1 principle, which seeks to explain participatory patterns and network effects within Internet communities. The rule states that 90% of actors observe and do not participate, 9% contribute sparingly, and 1% of actors create the vast majority of new content. This 90%, 9%, and 1% are also known as Lurkers, Contributors, and Superusers, respectively. To date, very little empirical research has been conducted to verify the 1% rule. Objective The 1% rule is widely accepted in digital marketing. Our goal was to determine if the 1% rule applies to moderated Digital Health Social Networks (DHSNs) designed to facilitate behavior change. Methods To help gain insight into participatory patterns, descriptive data were extracted from four long-standing DHSNs: the AlcoholHelpCenter, DepressionCenter, PanicCenter, and StopSmokingCenter sites. Results During the study period, 63,990 actors created 578,349 posts. Less than 25% of actors made one or more posts. The applicability of the 1% rule was confirmed as Lurkers, Contributors, and Superusers accounted for a weighted average of 1.3% (n=4668), 24.0% (n=88,732), and 74.7% (n=276,034) of content. Conclusions The 1% rule was consistent across the four DHSNs. As social network sustainability requires fresh content and timely interactions, these results are important for organizations actively promoting and managing Internet communities. Superusers generate the vast majority of traffic and create value, so their recruitment and retention is imperative for long-term success. Although Lurkers may benefit from observing interactions between Superusers and Contributors, they generate limited or no network value. The results of this study indicate that DHSNs may be optimized to produce network effects, positive externalities, and bandwagon effects. Further research in the development and expansion of DHSNs is required. PMID:24496109

Migrant networks and pathways to child obesity in Mexico.

Science.gov (United States)

Creighton, Mathew J; Goldman, Noreen; Teruel, Graciela; Rubalcava, Luis

2011-03-01

The purpose of this paper is twofold: 1) to assess the link between migrant networks and becoming overweight or obese and 2) to explore the pathways by which migrant networks may contribute to the increasing overweight and obese population of children in Mexico. Using two waves of the Mexican Family Life Survey (MxFLS), we find that children and adolescents (ages 3 to 15) living in households with migrant networks are at an increased risk of becoming overweight or obese over the period of observation, relative to their peers with no migrant networks. Sedentary behavior and household-level measures of economic wellbeing explain some of the association between networks and changes in weight status, but the role of extended networks remains significant. Community-level characteristics related to migration do not account for any of the observed relationship between household-level networks and becoming overweight or obese. Copyright © 2010 Elsevier Ltd. All rights reserved.

Network Compression as a Quality Measure for Protein Interaction Networks

Science.gov (United States)

Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

2012-01-01

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

Communication Networks - Analysis of jitter due to call-level fluctuations

NARCIS (Netherlands)

Mandjes, M.R.H.

2007-01-01

Abstract In communication networks used by constant bit rate applications, call-level dynamics (i.e. entering and leaving calls) lead to fluctuations in the load, and therefore also fluctuations in the delay (jitter). By intentionally delaying the packets at the destination, one can transform the

The Micro-Pulse Lidar Network (MPLNET): A Federated Network of Micro-pulse Lidars and AERONET Sunphotometers

Science.gov (United States)

Welton, Ellsworth J.; Campbell, James R.; Spinhirne, James D.; Berkoff, Timothy A.; Holben, Brent; Tsay, Si-Chee

2004-01-01

We present the formation of a new global-ground based eye-safe lidar network, the NASA Micro-Pulse Lidar Network (MPLNET). The aim of MPLNET is to acquire long- term observations of aerosol and cloud vertical profiles at unique geographic sites within the NASA Aerosol Robotic Network (AERONET). MPLNET utilizes standard instrumentation and data processing algorithms for efficient network operations and direct comparison of data between each site. The micro-pulse lidar is eye-safe, compact, and commercially available, and most easily allows growth of the network without sacrificing standardized instrumentation goals. Network growth follows a federated approach, pioneered by AERONET, wherein independent research groups may join MPLNET with their own instrument and site. MPLNET sites produce not only vertical profile data, but also column-averaged products already available from AERONET (aerosol optical depth, sky radiance, size distributions). Algorithms are presented for each MPLNET data product. Real-time Level 1 data products (next-day) include daily lidar signal images from the surface to -2Okm, and Level 1.5 aerosol extinction profiles at times co-incident with AERONET observations. Quality assured Level 2 aerosol extinction profiles are generated after screening the Level 1.5 results and removing bad data. Level 3 products include continuous day/night aerosol extinction profiles, and are produced using Level 2 calibration data. Rigorous uncertainty calculations are presented for all data products. Analysis of MPLNET data show the MPL and our analysis routines are capable of successfully retrieving aerosol profiles, with the strenuous accounting of uncertainty necessary for accurate interpretation of the results.

Multi-level deep supervised networks for retinal vessel segmentation.

Science.gov (United States)

Mo, Juan; Zhang, Lei

2017-12-01

Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation from retinal images is very challenging because of low blood vessel contrast, intricate vessel topology, and the presence of pathologies such as microaneurysms and hemorrhages. To overcome these challenges, we propose a neural network-based method for vessel segmentation. A deep supervised fully convolutional network is developed by leveraging multi-level hierarchical features of the deep networks. To improve the discriminative capability of features in lower layers of the deep network and guide the gradient back propagation to overcome gradient vanishing, deep supervision with auxiliary classifiers is incorporated in some intermediate layers of the network. Moreover, the transferred knowledge learned from other domains is used to alleviate the issue of insufficient medical training data. The proposed approach does not rely on hand-crafted features and needs no problem-specific preprocessing or postprocessing, which reduces the impact of subjective factors. We evaluate the proposed method on three publicly available databases, the DRIVE, STARE, and CHASE_DB1 databases. Extensive experiments demonstrate that our approach achieves better or comparable performance to state-of-the-art methods with a much faster processing speed, making it suitable for real-world clinical applications. The results of cross-training experiments demonstrate its robustness with respect to the training set. The proposed approach segments retinal vessels accurately with a much faster processing speed and can be easily applied to other biomedical segmentation tasks.

Digital Levelling in Subterranean Spaces

Directory of Open Access Journals (Sweden)

Tomáš Jiřikovský

2007-06-01

Full Text Available For precision levelling works are now more often used digital levels and code-scale staffs. Advantages in (and problems with their application to the regular line-levelling are well known and described. However, when using the digital levelling for measurements in specific local geodetic networks, monitoring networks and inside of buildings and underground spaces, new problems appear with the signalisation of the observed points, readability of the code (non-uniform illumination, temperature changes etc. The article informs about the application of two types of digital levels (Sokkia SDL-2, Trimble Zeiss DiNi 12T in the experimental subterranean levelling network for the basement settlement monitoring of a ten-floor building; the solution of marking of the points, field calibration and the system calibration of digital levels.

Associating at the European Level: Civil Society Networks in Brussels

NARCIS (Netherlands)

Brandsen, T.; Sittermann, B.; Freise, M.; Hallmann, T.

2014-01-01

This chapter examines the position of the third sector at the European level, where it has slowly been building a presence. Although great advances have been made, especially from the 1990s onwards, and the sector’s European networks are much stronger than before, it remains institutionally weak and

Two-level Robust Measurement Fusion Kalman Filter for Clustering Sensor Networks

Institute of Scientific and Technical Information of China (English)

ZHANG Peng; QI Wen-Juan; DENG Zi-Li

2014-01-01

This paper investigates the distributed fusion Kalman filtering over clustering sensor networks. The sensor network is partitioned as clusters by the nearest neighbor rule and each cluster consists of sensing nodes and cluster-head. Using the minimax robust estimation principle, based on the worst-case conservative system with the conservative upper bounds of noise variances, two-level robust measurement fusion Kalman filter is presented for the clustering sensor network systems with uncertain noise variances. It can significantly reduce the communication load and save energy when the number of sensors is very large. A Lyapunov equation approach for the robustness analysis is presented, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented, and the robust accuracy relations among the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the two-level weighted measurement fuser is equal to that of the global centralized robust fuser and is higher than those of each local robust filter and each local weighted measurement fuser. A simulation example shows the correctness and effectiveness of the proposed results.

Onsets of Solar Proton Events in Satellite and Ground Level Observations: A Comparison

Science.gov (United States)

He, Jing; Rodriguez, Juan V.

2018-03-01

The early detection of solar proton event onsets is essential for protecting humans and electronics in space, as well as passengers and crew at aviation altitudes. Two commonly compared methods for observing solar proton events that are sufficiently large and energetic to be detected on the ground through the creation of secondary radiation—known as ground level enhancements (GLEs)—are (1) a network of ground-based neutron monitors (NMs) and (2) satellite-based particle detectors. Until recently, owing to the different time resolution of the two data sets, it has not been feasible to compare these two types of observations using the same detection algorithm. This paper presents a comparison between the two observational platforms using newly processed >100 MeV 1 min count rates and fluxes from National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellite (GOES) 8-12 satellites, and 1 min count rates from the Neutron Monitor Database. We applied the same detection algorithm to each data set (tuned to the different background noise levels of the instrument types). Seventeen SPEs with GLEs were studied: GLEs 55-70 from Solar Cycle 23 and GLE 71 from Solar Cycle 24. The median difference in the event detection times by GOES and NM data is 0 min, indicating no innate benefit in time of either system. The 10th, 25th, 75th, and 90th percentiles of the onset time differences (GOES minus NMs) are -7.2 min, -1.5 min, 2.5 min, and 4.2 min, respectively. This is in contrast to previous studies in which NM detections led GOES by 8 to 52 min without accounting for different alert protocols.

Surrogate-assisted identification of influences of network construction on evolving weighted functional networks

Science.gov (United States)

Stahn, Kirsten; Lehnertz, Klaus

2017-12-01

We aim at identifying factors that may affect the characteristics of evolving weighted networks derived from empirical observations. To this end, we employ various chains of analysis that are often used in field studies for a data-driven derivation and characterization of such networks. As an example, we consider fully connected, weighted functional brain networks before, during, and after epileptic seizures that we derive from multichannel electroencephalographic data recorded from epilepsy patients. For these evolving networks, we estimate clustering coefficient and average shortest path length in a time-resolved manner. Lastly, we make use of surrogate concepts that we apply at various levels of the chain of analysis to assess to what extent network characteristics are dominated by properties of the electroencephalographic recordings and/or the evolving weighted networks, which may be accessible more easily. We observe that characteristics are differently affected by the unavoidable referencing of the electroencephalographic recording, by the time-series-analysis technique used to derive the properties of network links, and whether or not networks were normalized. Importantly, for the majority of analysis settings, we observe temporal evolutions of network characteristics to merely reflect the temporal evolutions of mean interaction strengths. Such a property of the data may be accessible more easily, which would render the weighted network approach—as used here—as an overly complicated description of simple aspects of the data.

A network-level explanation for the differences in HIV prevalence in ...

African Journals Online (AJOL)

A network-level explanation for the differences in HIV prevalence in South Africa's ... or ethnic groups may help explain the differential spread of HIV in South Africa. ... Keywords: concurrency, epidemiology, ethnicity, HIV/AIDS, race, social ...

Network marketing on a small-world network

Science.gov (United States)

Kim, Beom Jun; Jun, Tackseung; Kim, Jeong-Yoo; Choi, M. Y.

2006-02-01

We investigate a dynamic model of network marketing in a small-world network structure artificially constructed similarly to the Watts-Strogatz network model. Different from the traditional marketing, consumers can also play the role of the manufacturer's selling agents in network marketing, which is stimulated by the referral fee the manufacturer offers. As the wiring probability α is increased from zero to unity, the network changes from the one-dimensional regular directed network to the star network where all but one player are connected to one consumer. The price p of the product and the referral fee r are used as free parameters to maximize the profit of the manufacturer. It is observed that at α=0 the maximized profit is constant independent of the network size N while at α≠0, it increases linearly with N. This is in parallel to the small-world transition. It is also revealed that while the optimal value of p stays at an almost constant level in a broad range of α, that of r is sensitive to a change in the network structure. The consumer surplus is also studied and discussed.

Neural Networks Mediating High-Level Mentalizing in Patients With Right Cerebral Hemispheric Gliomas

Directory of Open Access Journals (Sweden)

Riho Nakajima

2018-03-01

Full Text Available Mentalizing is the ability to understand others’ mental state through external cues. It consists of two networks, namely low-level and high-level metalizing. Although it is an essential function in our daily social life, surgical resection of right cerebral hemisphere disturbs mentalizing processing with high possibility. In the past, little was known about the white matter related to high-level mentalizing, and the conservation of high-level mentalizing during surgery has not been a focus of attention. Therefore, the main purpose of this study was to examine the neural networks underlying high-level mentalizing and then, secondarily, investigate the usefulness of awake surgery in preserving the mentalizing network. A total of 20 patients with glioma localized in the right hemisphere who underwent awake surgery participated in this study. All patients were assigned to two groups: with or without intraoperative assessment of high-level mentalizing. Their high-level mentalizing abilities were assessed before surgery and 1 week and 3 months after surgery. At 3 months after surgery, only patients who received the intraoperative high-level mentalizing test showed the same score as normal healthy volunteers. The tract-based lesion symptom analysis was performed to confirm the severity of damage of associated fibers and high-level mentalizing accuracy. This analysis revealed the superior longitudinal fascicles (SLF III and fronto-striatal tract (FST to be associated with high-level mentalizing processing. Moreover, the voxel-based lesion symptom analysis demonstrated that resection of orbito-frontal cortex (OFC causes persistent mentalizing dysfunction. Our study indicates that damage of the OFC and structural connectivity of the SLF and FST causes the disorder of mentalizing after surgery, and assessing high-level mentalizing during surgery may be useful to preserve these pathways.

A Bi-Level Programming Model for the Railway Express Cargo Service Network Design Problem

Directory of Open Access Journals (Sweden)

Boliang Lin

2018-06-01

Full Text Available Service network design is fundamentally crucial for railway express cargo transportation. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and high expected operational incomes. Different configurations of these objectives will have different impacts on the quality of freight transportation services. In this paper, a bi-level programming model for the railway express cargo service network design problem is proposed. The upper-level model forms the optimal decisions in terms of the service characteristics, and the low-level model selects the service arcs for each commodity. The rail express cargo is strictly subject to the service commitment, the capacity restriction, flow balance constraints, and logical relationship constraints among the decisions variables. Moreover, linearization techniques are used to convert the lower-level model to a linear one so that it can be directly solved by a standard optimization solver. Finally, a real-world case study based on the Beijing–Guangzhou Railway Line is carried out to demonstrate the effectiveness and efficiency of the proposed solution approach.

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

Science.gov (United States)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks

KAUST Repository

Douik, Ahmed; Dahrouj, Hayssam; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2016-01-01

results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

Learning characteristics of a space-time neural network as a tether skiprope observer

Science.gov (United States)

Lea, Robert N.; Villarreal, James A.; Jani, Yashvant; Copeland, Charles

1993-01-01

The Software Technology Laboratory at the Johnson Space Center is testing a Space Time Neural Network (STNN) for observing tether oscillations present during retrieval of a tethered satellite. Proper identification of tether oscillations, known as 'skiprope' motion, is vital to safe retrieval of the tethered satellite. Our studies indicate that STNN has certain learning characteristics that must be understood properly to utilize this type of neural network for the tethered satellite problem. We present our findings on the learning characteristics including a learning rate versus momentum performance table.

Social Capital, Network Effects and Savings in Rural Vietnam

DEFF Research Database (Denmark)

Newman, Carol; Tarp, Finn; Van Den Broeck, Katleen

social networks in rural Vietnam can play a role in increasing formal savings where knowledge gaps exist. Networks are defined as active membership of women’s unions and the quality of networks is measured by the level of formal savings observed among group members. We find that membership of high...... quality networks leads to higher levels of saving in formal financial institutions and to higher levels of saving for productive investments as compared with other precautionary or lifecycle motives. Our results suggest that transmitting financial information through formal networks could be effective...... in increasing formal savings at grassroots level. We also conclude that ensuring information disseminated by networks is both accurate and desirable as well as important given that behavioural effects are also found in low-quality networks....

TWO-LEVEL HIERARCHICAL COORDINATION QUEUING METHOD FOR TELECOMMUNICATION NETWORK NODES

Directory of Open Access Journals (Sweden)

M. V. Semenyaka

2014-07-01

Full Text Available The paper presents hierarchical coordination queuing method. Within the proposed method a queuing problem has been reduced to optimization problem solving that was presented as two-level hierarchical structure. The required distribution of flows and bandwidth allocation was calculated at the first level independently for each macro-queue; at the second level solutions obtained on lower level for each queue were coordinated in order to prevent probable network link overload. The method of goal coordination has been determined for multilevel structure managing, which makes it possible to define the order for consideration of queue cooperation restrictions and calculation tasks distribution between levels of hierarchy. Decisions coordination was performed by the method of Lagrange multipliers. The study of method convergence has been carried out by analytical modeling.

INTERCONNECTING NETWORKS WITH DIFFERENT LEVELS OF SECURITY – A PRESENT NATO PROBLEM

Directory of Open Access Journals (Sweden)

LIVIU TATOMIR

2016-07-01

Full Text Available A situation often met in the Romanian Armed Forces in recent years is the need for interconnecting two networks (domains with different levels of classification. Considering that the Romanian armed troops are involved in numerous missions with NATO partners, solutions, already implemented across the organization, are considered to be applied in domestic systems, also. This paper presents the solutions adopted by NATO in order to solve the problem of cross -domains interconnections. We present the maturity level reached by these solutions and the possibility of implementing these solutions in the Romanian Armed Forces, with or without specific adaptation to our own rules and regulations. The goal is to use a NATO already proved solution to our national classified networks.

The Quake-Catcher Network: Improving Earthquake Strong Motion Observations Through Community Engagement

Science.gov (United States)

Cochran, E. S.; Lawrence, J. F.; Christensen, C. M.; Chung, A. I.; Neighbors, C.; Saltzman, J.

2010-12-01

The Quake-Catcher Network (QCN) involves the community in strong motion data collection by utilizing volunteer computing techniques and low-cost MEMS accelerometers. Volunteer computing provides a mechanism to expand strong-motion seismology with minimal infrastructure costs, while promoting community participation in science. Micro-Electro-Mechanical Systems (MEMS) triaxial accelerometers can be attached to a desktop computer via USB and are internal to many laptops. Preliminary shake table tests show the MEMS accelerometers can record high-quality seismic data with instrument response similar to research-grade strong-motion sensors. QCN began distributing sensors and software to K-12 schools and the general public in April 2008 and has grown to roughly 1500 stations worldwide. We also recently tested whether sensors could be quickly deployed as part of a Rapid Aftershock Mobilization Program (RAMP) following the 2010 M8.8 Maule, Chile earthquake. Volunteers are recruited through media reports, web-based sensor request forms, as well as social networking sites. Using data collected to date, we examine whether a distributed sensing network can provide valuable seismic data for earthquake detection and characterization while promoting community participation in earthquake science. We utilize client-side triggering algorithms to determine when significant ground shaking occurs and this metadata is sent to the main QCN server. On average, trigger metadata are received within 1-10 seconds from the observation of a trigger; the larger data latencies are correlated with greater server-station distances. When triggers are detected, we determine if the triggers correlate to others in the network using spatial and temporal clustering of incoming trigger information. If a minimum number of triggers are detected then a QCN-event is declared and an initial earthquake location and magnitude is estimated. Initial analysis suggests that the estimated locations and magnitudes are

Analysis on the University’s Network Security Level System in the Big Data Era

Science.gov (United States)

Li, Tianli

2017-12-01

The rapid development of science and technology, the continuous expansion of the scope of computer network applications, has gradually improved the social productive forces, has had a positive impact on the increase production efficiency and industrial scale of China's different industries. Combined with the actual application of computer network in the era of large data, we can see the existence of influencing factors such as network virus, hacker and other attack modes, threatening network security and posing a potential threat to the safe use of computer network in colleges and universities. In view of this unfavorable development situation, universities need to pay attention to the analysis of the situation of large data age, combined with the requirements of network security use, to build a reliable network space security system from the equipment, systems, data and other different levels. To avoid the security risks exist in the network. Based on this, this paper will analyze the hierarchical security system of cyberspace security in the era of large data.

Two-level modulation scheme to reduce latency for optical mobile fronthaul networks.

Science.gov (United States)

Sung, Jiun-Yu; Chow, Chi-Wai; Yeh, Chien-Hung; Chang, Gee-Kung

2016-10-31

A system using optical two-level orthogonal-frequency-division-multiplexing (OFDM) - amplitude-shift-keying (ASK) modulation is proposed and demonstrated to reduce the processing latency for the optical mobile fronthaul networks. At the proposed remote-radio-head (RRH), the high data rate OFDM signal does not need to be processed, but is directly launched into a high speed photodiode (HSPD) and subsequently emitted by an antenna. Only a low bandwidth PD is needed to recover the low data rate ASK control signal. Hence, it is simple and provides low-latency. Furthermore, transporting the proposed system over the already deployed optical-distribution-networks (ODNs) of passive-optical-networks (PONs) is also demonstrated with 256 ODN split-ratios.

Neural Network Control for the Probe Landing Based on Proportional Integral Observer

Directory of Open Access Journals (Sweden)

Yuanchun Li

2015-01-01

Full Text Available For the probe descending and landing safely, a neural network control method based on proportional integral observer (PIO is proposed. First, the dynamics equation of the probe under the landing site coordinate system is deduced and the nominal trajectory meeting the constraints in advance on three axes is preplanned. Then the PIO designed by using LMI technique is employed in the control law to compensate the effect of the disturbance. At last, the neural network control algorithm is used to guarantee the double zero control of the probe and ensure the probe can land safely. An illustrative design example is employed to demonstrate the effectiveness of the proposed control approach.

Working Group 1: Observations

International Nuclear Information System (INIS)

Trenberth, K.; Angell, J.; Barry, R.; Bradley, R.; Diaz, H.; Elliott, W.; Etkins, R.; Folland, C.; Jenne, R.; Jones, P.; Karl, T.; Levitus, S.; Oort, A.; Parker, D.; Ropelewski, C.; Vinnikov, K.; Wigley, T.

1991-01-01

Topics of discussion include the following: the need for observations; issues in establishing global climate trends; climate variables such as surface air temperature over land, marine temperature, precipitation, circulation, upper air measurements, historical observations, subsurface ocean data, sea level, cryosphere, clouds, solar radiation, and aerosols; future considerations and recommendations which focuses on the establishment of a global benchmark climate monitoring network and data management

Working Group 1: Observations

International Nuclear Information System (INIS)

Trenberth, K.; Angell, J.; Barry, R.; Bradley, R.; Diaz, H.; Elliott, W.; Etkins, R.; Folland, C.; Jenne, R.; Jones, P.; Karl, T.; Levitus, S.; Oort, A.; Parker, D.; Ropelewski, C.; Vinnikov, K.; Wigley, T.

1990-01-01

Topics of discussion include the following: the need for observations; issues in establishing global climate trends; climate variables such as surface air temperature over land, marine temperature, precipitation, circulation, upper air measurements, historical observations, subsurface ocean data, sea level, cryosphere, clouds, solar radiation, and aerosols; future considerations and recommendations which focuses on the establishment of a global benchmark climate monitoring network and data management

Study on application of adaptive fuzzy control and neural network in the automatic leveling system

Science.gov (United States)

Xu, Xiping; Zhao, Zizhao; Lan, Weiyong; Sha, Lei; Qian, Cheng

2015-04-01

This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.

Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models

Directory of Open Access Journals (Sweden)

Chih-Chieh Young

2015-01-01

Full Text Available Accurate prediction of water level fluctuation is important in lake management due to its significant impacts in various aspects. This study utilizes four model approaches to predict water levels in the Yuan-Yang Lake (YYL in Taiwan: a three-dimensional hydrodynamic model, an artificial neural network (ANN model (back propagation neural network, BPNN, a time series forecasting (autoregressive moving average with exogenous inputs, ARMAX model, and a combined hydrodynamic and ANN model. Particularly, the black-box ANN model and physically based hydrodynamic model are coupled to more accurately predict water level fluctuation. Hourly water level data (a total of 7296 observations was collected for model calibration (training and validation. Three statistical indicators (mean absolute error, root mean square error, and coefficient of correlation were adopted to evaluate model performances. Overall, the results demonstrate that the hydrodynamic model can satisfactorily predict hourly water level changes during the calibration stage but not for the validation stage. The ANN and ARMAX models better predict the water level than the hydrodynamic model does. Meanwhile, the results from an ANN model are superior to those by the ARMAX model in both training and validation phases. The novel proposed concept using a three-dimensional hydrodynamic model in conjunction with an ANN model has clearly shown the improved prediction accuracy for the water level fluctuation.

An Optimal Medium Access Control with Partial Observations for Sensor Networks

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Servetto Sergio D

2005-01-01

Full Text Available We consider medium access control (MAC in multihop sensor networks, where only partial information about the shared medium is available to the transmitter. We model our setting as a queuing problem in which the service rate of a queue is a function of a partially observed Markov chain representing the available bandwidth, and in which the arrivals are controlled based on the partial observations so as to keep the system in a desirable mildly unstable regime. The optimal controller for this problem satisfies a separation property: we first compute a probability measure on the state space of the chain, namely the information state, then use this measure as the new state on which the control decisions are based. We give a formal description of the system considered and of its dynamics, we formalize and solve an optimal control problem, and we show numerical simulations to illustrate with concrete examples properties of the optimal control law. We show how the ergodic behavior of our queuing model is characterized by an invariant measure over all possible information states, and we construct that measure. Our results can be specifically applied for designing efficient and stable algorithms for medium access control in multiple-accessed systems, in particular for sensor networks.

Power-Hop: A Pervasive Observation for Real Complex Networks

Science.gov (United States)

2016-03-14

e.g., power grid, the Internet and the web-graph), social (e.g., friendship networks — Facebook , Gowalla—and co- authorship networks ), urban (e.g...Mislove A., Cha M. and Gummadi K.P. On the evolution of user interaction in Facebook . In Proc. Workshop on Online Social Networks 2009. doi...scale-free distribution is pervasive and describes a large variety of networks , ranging from social and urban to technological and biological networks

The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

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Michele Romolini

2013-09-01

Full Text Available By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.

The Inverse Contagion Problem (ICP) vs.. Predicting site contagion in real time, when network links are not observable

Science.gov (United States)

Mushkin, I.; Solomon, S.

2017-10-01

We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires "only" the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types. The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the "false link difficulty". By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the "false link difficulty" of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure. We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it

Damage Level Prediction of Reinforced Concrete Building Based on Earthquake Time History Using Artificial Neural Network

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Suryanita Reni

2017-01-01

Full Text Available The strong motion earthquake could cause the building damage in case of the building not considered in the earthquake design of the building. The study aims to predict the damage-level of building due to earthquake using Artificial Neural Networks method. The building model is a reinforced concrete building with ten floors and height between floors is 3.6 m. The model building received a load of the earthquake based on nine earthquake time history records. Each time history scaled to 0,5g, 0,75g, and 1,0g. The Artificial Neural Networks are designed in 4 architectural models using the MATLAB program. Model 1 used the displacement, velocity, and acceleration as input and Model 2 used the displacement only as the input. Model 3 used the velocity as input, and Model 4 used the acceleration just as input. The output of the Neural Networks is the damage level of the building with the category of Safe (1, Immediate Occupancy (2, Life Safety (3 or in a condition of Collapse Prevention (4. According to the results, Neural Network models have the prediction rate of the damage level between 85%-95%. Therefore, one of the solutions for analyzing the structural responses and the damage level promptly and efficiently when the earthquake occurred is by using Artificial Neural Network

Global Production Networks and International Inequality: Making a Case for a Meso-Level Turn in Macro-Comparative Sociology

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Mathew Mahutga

2015-08-01

Full Text Available In this article, I extend recent macro-comparative empirical research on the developmental implications of global production networks. I draw from theories of commodity/value chains, global production networks and economic sociology to identify three contending theoretical perspectives for exactly how the developmental returns to network participants should be distributed-cooperation, exploitation and differential gains-and derive testable hypotheses for each. Adding to recent empirical advances for measuring the average network position of firms at the country level, I evaluate these hypotheses by way of dynamic panel regression models of hourly wage rates in the garment and transportation equipment industries. The results suggest that macro-sociological theories linking underdevelopment to the structure of the world-economy, as well as theories of the distribution of the gains from network participation, miss important variation at the industry level. Cooperation provides a poor account of the distribution of the gains from network participation. Instead, both industries appear to distribute the gains from network participation differentially across network participants. However, the extent of this inequality increases, and the garment industry transitions to exploitation, when global production networks become entrenched organizational logics. Variation in the distribution of the returns to network participation is explicable only by accounting for production-network governance as it varies across industries and over time. I conclude by highlighting the analytical utility to macro-comparative sociology of a turn toward the mesa-level of global industries.

Operation of a Data Acquisition, Transfer, and Storage System for the Global Space-Weather Observation Network

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T Nagatsuma

2014-10-01

Full Text Available A system to optimize the management of global space-weather observation networks has been developed by the National Institute of Information and Communications Technology (NICT. Named the WONM (Wide-area Observation Network Monitoring system, it enables data acquisition, transfer, and storage through connection to the NICT Science Cloud, and has been supplied to observatories for supporting space-weather forecast and research. This system provides us with easier management of data collection than our previously employed systems by means of autonomous system recovery, periodical state monitoring, and dynamic warning procedures. Operation of the WONM system is introduced in this report.

Observations of thunderstorm-related 630 nm airglow depletions

Science.gov (United States)

Kendall, E. A.; Bhatt, A.

2015-12-01

The Midlatitude All-sky imaging Network for Geophysical Observations (MANGO) is an NSF-funded network of 630 nm all-sky imagers in the continental United States. MANGO will be used to observe the generation, propagation, and dissipation of medium and large-scale wave activity in the subauroral, mid and low-latitude thermosphere. This network is actively being deployed and will ultimately consist of nine all-sky imagers. These imagers form a network providing continuous coverage over the western United States, including California, Oregon, Washington, Utah, Arizona and Texas extending south into Mexico. This network sees high levels of both medium and large scale wave activity. Apart from the widely reported northeast to southwest propagating wave fronts resulting from the so called Perkins mechanism, this network observes wave fronts propagating to the west, north and northeast. At least three of these anomalous events have been associated with thunderstorm activity. Imager data has been correlated with both GPS data and data from the AIRS (Atmospheric Infrared Sounder) instrument on board NASA's Earth Observing System Aqua satellite. We will present a comprehensive analysis of these events and discuss the potential thunderstorm source mechanism.

Conceptual plan for closer integration of network- and project-level pavement management

Science.gov (United States)

1998-01-01

This report presents an evaluation of current performance modeling concepts and a feasibility study of the possibility of integrating network- and project-level performance prediction. The widely differing modeling methods in use today are reviewed a...

Present day sea level changes: observation and causes; Les variations actuelles du niveau de la mer: observations et causes

Energy Technology Data Exchange (ETDEWEB)

Lombard, A

2005-11-15

Whereas sea level has changed little over the last 2000 years, it has risen at a rate of about 2 mm/year during the 20. century. This unexpected sea level rise has been attributed to the anthropogenic global warming, recorded over several decades. Sea level variations have been measured globally and precisely for about 12 years due to satellite altimeter missions Topex/Poseidon and Jason-1. These observations indicate a global mean sea level rise of about 3 mm/year since 1993, a value significantly larger than observed during previous decades. Recent observations have allowed us to quantify the various climatic factors contributing to observed sea level change: thermal expansion of sea water due to ocean warming, melting of mountain glaciers and ice sheets, and changes in the land water reservoirs. A water budget based on these new observations allows us to partly explain the observed sea level rise. In particular, we show that the thermal expansion explains only 25% of the secular sea level rise as recorded by tide-gauges over the last 50 years, while it contributes about 50% of sea level rise observed over the last decade. Meanwhile, recent studies show that glacier and ice sheet melting could contribute the equivalent of 1 mm/year in sea level rise over the last decade. In addition, the high regional variability of sea level trends revealed by satellite altimetry is mainly due to thermal expansion. There is also an important decadal spatio-temporal variability in the ocean thermal expansion over the last 50 years, which seems to be controlled by natural climate fluctuations. We question for the first time the link between the decadal fluctuations in the ocean thermal expansion and in the land reservoirs, and indeed their climatic contribution to sea level change. Finally a preliminary analysis of GRACE spatial gravimetric observations over the oceans allows us to estimate the seasonal variations in mean sea level due to ocean water mass balance variations

New Results from the NOAA CREST Lidar Network (CLN Observations in the US Eastcoast

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Moshary Fred

2016-01-01

Full Text Available This paper presents coordinated ground-based observations by the NOAA-CREST Lidar Network (CLN for profiling of aerosols, cloud, water vapor, and wind along the US east coast including Caribbean region at Puerto Rico. The instrumentation, methodology and observation capability are reviewed. The applications to continental and intercontinental-scale transport of smoke and dust plumes, and their large scale regional impact are discussed.

Observed Sea-Level Changes along the Norwegian Coast

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Kristian Breili

2017-07-01

Full Text Available Norway’s national sea level observing system consists of an extensive array of tide gauges, permanent GNSS stations, and lines of repeated levelling. Here, we make use of this observation system to calculate relative sea-level rates and rates corrected for glacial isostatic adjustment (GIA along the Norwegian coast for three different periods, i.e., 1960 to 2010, 1984 to 2014, and 1993 to 2016. For all periods, the relative sea-level rates show considerable spatial variations that are largely due to differences in vertical land motion due to GIA. The variation is reduced by applying corrections for vertical land motion and associated gravitational effects on sea level. For 1960 to 2010 and 1984 to 2014, the coastal average GIA-corrected rates for Norway are 2.0 ± 0.6 mm/year and 2.2 ± 0.6 mm/year, respectively. This is close to the rate of global sea-level rise for the same periods. For the most recent period, 1993 to 2016, the GIA-corrected coastal average is 3.5 ± 0.6 mm/year and 3.2 ± 0.6 mm/year with and without inverse barometer (IB corrections, respectively, which is significantly higher than for the two earlier periods. For 1993 to 2016, the coastal average IB-corrected rates show broad agreement with two independent sets of altimetry. This suggests that there is no systematic error in the vertical land motion corrections applied to the tide-gauge data. At the same time, altimetry does not capture the spatial variation identified in the tide-gauge records. This could be an effect of using altimetry observations off the coast instead of directly at each tide gauge. Finally, we note that, owing to natural variability in the climate system, our estimates are highly sensitive to the selected study period. For example, using a 30-year moving window, we find that the estimated rates may change by up to 1 mm/year when shifting the start epoch by only one year.

Risk Evaluation of Railway Coal Transportation Network Based on Multi Level Grey Evaluation Model

Science.gov (United States)

Niu, Wei; Wang, Xifu

2018-01-01

The railway transport mode is currently the most important way of coal transportation, and now China’s railway coal transportation network has become increasingly perfect, but there is still insufficient capacity, some lines close to saturation and other issues. In this paper, the theory and method of risk assessment, analytic hierarchy process and multi-level gray evaluation model are applied to the risk evaluation of coal railway transportation network in China. Based on the example analysis of Shanxi railway coal transportation network, to improve the internal structure and the competitiveness of the market.

Randomization and resilience of brain functional networks as systems-level endophenotypes of schizophrenia.

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Lo, Chun-Yi Zac; Su, Tsung-Wei; Huang, Chu-Chung; Hung, Chia-Chun; Chen, Wei-Ling; Lan, Tsuo-Hung; Lin, Ching-Po; Bullmore, Edward T

2015-07-21

Schizophrenia is increasingly conceived as a disorder of brain network organization or dysconnectivity syndrome. Functional MRI (fMRI) networks in schizophrenia have been characterized by abnormally random topology. We tested the hypothesis that network randomization is an endophenotype of schizophrenia and therefore evident also in nonpsychotic relatives of patients. Head movement-corrected, resting-state fMRI data were acquired from 25 patients with schizophrenia, 25 first-degree relatives of patients, and 29 healthy volunteers. Graphs were used to model functional connectivity as a set of edges between regional nodes. We estimated the topological efficiency, clustering, degree distribution, resilience, and connection distance (in millimeters) of each functional network. The schizophrenic group demonstrated significant randomization of global network metrics (reduced clustering, greater efficiency), a shift in the degree distribution to a more homogeneous form (fewer hubs), a shift in the distance distribution (proportionally more long-distance edges), and greater resilience to targeted attack on network hubs. The networks of the relatives also demonstrated abnormal randomization and resilience compared with healthy volunteers, but they were typically less topologically abnormal than the patients' networks and did not have abnormal connection distances. We conclude that schizophrenia is associated with replicable and convergent evidence for functional network randomization, and a similar topological profile was evident also in nonpsychotic relatives, suggesting that this is a systems-level endophenotype or marker of familial risk. We speculate that the greater resilience of brain networks may confer some fitness advantages on nonpsychotic relatives that could explain persistence of this endophenotype in the population.

Reconfigurable network systems and software-defined networking

OpenAIRE

Zilberman, N.; Watts, P. M.; Rotsos, C.; Moore, A. W.

2015-01-01

Modern high-speed networks have evolved from relatively static networks to highly adaptive networks facilitating dynamic reconfiguration. This evolution has influenced all levels of network design and management, introducing increased programmability and configuration flexibility. This influence has extended from the lowest level of physical hardware interfaces to the highest level of network management by software. A key representative of this evolution is the emergence of software-defined n...

Optimisation of groundwater level monitoring networks using geostatistical modelling based on the Spartan family variogram and a genetic algorithm method

Science.gov (United States)

Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.

2016-04-01

Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the

Measuring progress of the global sea level observing system

Science.gov (United States)

Woodworth, Philip L.; Aarup, Thorkild; Merrifield, Mark; Mitchum, Gary T.; Le Provost, Christian

Sea level is such a fundamental parameter in the sciences of oceanography geophysics, and climate change, that in the mid-1980s, the Intergovernmental Oceanographic Commission (IOC) established the Global Sea Level Observing System (GLOSS). GLOSS was to improve the quantity and quality of data provided to the Permanent Service for Mean Sea Level (PSMSL), and thereby, data for input to studies of long-term sea level change by the Intergovernmental Panel on Climate Change (IPCC). It would also provide the key data needed for international programs, such as the World Ocean Circulation Experiment (WOCE) and later, the Climate Variability and Predictability Programme (CLIVAR).GLOSS is now one of the main observation components of the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM) of IOC and the World Meteorological Organization (WMO). Progress and deficiencies in GLOSS were presented in July to the 22nd IOC Assembly at UNESCO in Paris and are contained in the GLOSS Assessment Report (GAR) [IOC, 2003a].

Realtime Delivery of Alarms and Key Observables in a Deployed Hydrological Sensor Network

Science.gov (United States)

Marshall, I. W.; Price, M. C.; Li, H.; Boyd, N.; Boult, S.

2007-12-01

It has widely [1-3] been proposed that sensor networks are a good solution for environmental monitoring. However, this application presents a number of major challenges for current technology. In particular environmental science involves the study of coupled non-equilibrium dynamic processes that generate time series with non-stationary means and strongly dependent variables and which operate in the presence of large amounts of noise/interference (thermal, chemical and biological) and multiple quasi-periodic forcing factors (diurnal cycles, tides, etc). This typically means that any analysis must be based on large data samples obtained at multiple scales of space and time. In addition the areas of interest are large, relatively inaccessible and typically extremely hostile to electronic instrumentation. Our analysis of these factors has encouraged us to focus on this list of generic requirements; a) Node lifetime (between visits) should be 1 yr or greater b) Communication range should be ~250m c) Nodes should be portable, unobtrusive, low cost, etc. d) Networks are expected to be sparse since areas of interest are large and budgets are small However, the characteristics of each environment, the dominant processes operating in it and the measurements that are of interest are sufficiently different that the design of an appropriate sensor network solution is normally most determined by site specific constraints. Most importantly the opportunities for exploiting contextual correlation to disambiguate observations and improve the maintenance and robustness of a deployed sensor network are always site specific. We will describe the design and initial deployment of a hydrological sensor network we are developing to assess the hydro-dynamics of surface water drainage into Great Crowden Brook in the Peak District (UK). The complete network will observe soil moisture, temperature and rainfall on a number of transects across the valley, and will also investigate water quality

Between “design” and “bricolage”: Genetic networks, levels of selection, and adaptive evolution

Science.gov (United States)

Wilkins, Adam S.

2007-01-01

The extent to which “developmental constraints” in complex organisms restrict evolutionary directions remains contentious. Yet, other forms of internal constraint, which have received less attention, may also exist. It will be argued here that a set of partial constraints below the level of phenotypes, those involving genes and molecules, influences and channels the set of possible evolutionary trajectories. At the top-most organizational level there are the genetic network modules, whose operations directly underlie complex morphological traits. The properties of these network modules, however, have themselves been set by the evolutionary history of the component genes and their interactions. Characterization of the components, structures, and operational dynamics of specific genetic networks should lead to a better understanding not only of the morphological traits they underlie but of the biases that influence the directions of evolutionary change. Furthermore, such knowledge may permit assessment of the relative degrees of probability of short evolutionary trajectories, those on the microevolutionary scale. In effect, a “network perspective” may help transform evolutionary biology into a scientific enterprise with greater predictive capability than it has hitherto possessed. PMID:17494754

Neural Network Observer-Based Finite-Time Formation Control of Mobile Robots

Directory of Open Access Journals (Sweden)

Caihong Zhang

2014-01-01

Full Text Available This paper addresses the leader-following formation problem of nonholonomic mobile robots. In the formation, only the pose (i.e., the position and direction angle of the leader robot can be obtained by the follower. First, the leader-following formation is transformed into special trajectory tracking. And then, a neural network (NN finite-time observer of the follower robot is designed to estimate the dynamics of the leader robot. Finally, finite-time formation control laws are developed for the follower robot to track the leader robot in the desired separation and bearing in finite time. The effectiveness of the proposed NN finite-time observer and the formation control laws are illustrated by both qualitative analysis and simulation results.

Seismic network at the Olkiluoto site and microearthquake observations in 2002-2013

International Nuclear Information System (INIS)

Saari, J.; Malm, M.

2014-05-01

This report describes the structure and operation of Posiva's seismic network after the comprehensive upgrade performed in 2013 and presents a summary of its micro-earthquake observations in 2002 - 2013. Excavation of the underground rock characterisation facility called ONKALO started in 2004. Before that, in February 2002, Posiva Oy established a local seismic network of six stations on the island of Olkiluoto. The number of seismic stations has increased gradually and communication, hardware and software have developed in over ten years. The upgrade in 2013 included data transmission, the equipment in several seismic stations, the server responsible for the data processing in Olkiluoto and software applied in operation and analysis of observations. After the upgrade Posiva's permanent seismic network consists of 17 seismic stations and 21 triaxial sensors. The purpose of the microearthquake measurements at Olkiluoto is to improve understanding of the structure, behaviour and long term stability of the bedrock. The investigation area includes two target areas, of which the larger one, the seismic semi-regional area, includes the Olkiluoto island and its surroundings. The aim is to monitor explosions and tectonic earthquakes in regional scale inside that area. All the expected excavation induced events are assumed to occur inside the smaller target area, the seismic ONKALO block, which is a 2 km x 2 km x 2 km cube surrounding the ONKALO. An additional task of monitoring is related to safeguarding of the construction of the ONKALO.In the beginning the network monitored tectonic earthquakes in order to characterise the undisturbed baseline of seismicity in Olkiluoto. After August 2004, the network also monitored excavation induced seismicity. The first three excavation induced earthquakes were recorded in September 2005. At the moment the total number of excavation induced earthquakes is 17. During the same time about 10 000 excavation blasts were located. The

Building oceanographic and atmospheric observation networks by composition: unmanned vehicles, communication networks, and planning and execution control frameworks

Science.gov (United States)

Sousa, J. T.; Pinto, J.; Martins, R.; Costa, M.; Ferreira, F.; Gomes, R.

2014-12-01

The problem of developing mobile oceanographic and atmospheric observation networks (MOAO) with coordinated air and ocean vehicles is discussed in the framework of the communications and control software tool chain developed at Underwater Systems and Technologies Laboratory (LSTS) from Porto University. This is done with reference to field experiments to illustrate key capabilities and to assess future MOAO operations. First, the motivation for building MOAO by "composition" of air and ocean vehicles, communication networks, and planning and execution control frameworks is discussed - in networked vehicle systems information and commands are exchanged among multiple vehicles and operators, and the roles, relative positions, and dependencies of these vehicles and operators change during operations. Second, the planning and execution control framework developed at LSTS for multi-vehicle systems is discussed with reference to key concepts such as autonomy, mixed-initiative interactions, and layered organization. Third, the LSTS tool software tool chain is presented to show how to develop MOAO by composition. The tool chain comprises the Neptus command and control framework for mixed initiative interactions, the underlying IMC messaging protocol, and the DUNE on-board software. Fourth, selected LSTS operational deployments illustrate MOAO capability building. In 2012 we demonstrated the use of UAS to "ferry" data from UUVs located beyond line of sight (BLOS). In 2013 we demonstrated coordinated observations of coastal fronts with small UAS and UUVs, "bent" BLOS through the use of UAS as communication relays, and UAS tracking of juvenile hammer-head sharks. In 2014 we demonstrated UUV adaptive sampling with the closed loop controller of the UUV residing on a UAS; this was done with the help of a Wave Glider ASV with a communications gateway. The results from these experiments provide a background for assessing potential future UAS operations in a compositional MOAO.

Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems

International Nuclear Information System (INIS)

Santos, Sérgio F.; Fitiwi, Desta Z.; Cruz, Marco R.M.; Cabrita, Carlos M.P.; Catalão, João P.S.

2017-01-01

Highlights: • A dynamic and multi-objective stochastic mixed integer linear programming model is developed. • A new mechanism to quantify the impacts of network flexibility and ESS deployments on RES integration is presented. • Optimal integration of ESSs dramatically increases the level and the optimal exploitation of renewable DGs. • As high as 90% of RES integration level may be possible in distribution network systems. • Joint DG and ESS installations along with optimal network reconfiguration greatly contribute to voltage stability. - Abstract: Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network’s switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not

Manifestations of personality in Online Social Networks: self-reported Facebook-related behaviors and observable profile information.

Science.gov (United States)

Gosling, Samuel D; Augustine, Adam A; Vazire, Simine; Holtzman, Nicholas; Gaddis, Sam

2011-09-01

Despite the enormous popularity of Online Social Networking sites (OSNs; e.g., Facebook and Myspace), little research in psychology has been done on them. Two studies examining how personality is reflected in OSNs revealed several connections between the Big Five personality traits and self-reported Facebook-related behaviors and observable profile information. For example, extraversion predicted not only frequency of Facebook usage (Study 1), but also engagement in the site, with extraverts (vs. introverts) showing traces of higher levels of Facebook activity (Study 2). As in offline contexts, extraverts seek out virtual social engagement, which leaves behind a behavioral residue in the form of friends lists and picture postings. Results suggest that, rather than escaping from or compensating for their offline personality, OSN users appear to extend their offline personalities into the domains of OSNs.

OBSERVATIONS ON LEVELS OF INTERNAL PARASITES IN FREE ...

African Journals Online (AJOL)

The purpose of this investigation was to record information on levels of parasitism and to observe any obvious pathogenic effects. METHOD. The majority of the 120 kudu examined were shot during Tsetse Game Control ..... DINNIK et aI. 1963.

Developing an Arctic Observing Network: Looking Beyond Scientific Research as a Driver to Broader Societal Benefits as Drivers

Science.gov (United States)

Jeffries, M. O.

2017-12-01

This presentation will address the first ever application of the Societal Benefit Areas approach to continuing efforts to develop an integrated pan-Arctic Observing Network. The scientific research community has been calling for an Arctic Observing Network since the early years of this century, at least. There is no question of the importance of research-driven observations at a time when rapid changes occurring throughout the Arctic environmental system are affecting people and communities in the Arctic and in regions far from the Arctic. Observations are need for continued environmental monitoring and change detection; improving understanding of how the system and its components function, and how they are connected to lower latitude regions; advancing numerical modeling capabilities for forecasting and projection; and developing value-added products and services for people and communities, and for decision- and policymaking. Scientific research is, without question, a benefit to society, but the benefits of Earth observations extend beyond scientific research. Societal Benefit Areas (SBAs) were first described by the international Group on Earth Observations (GEO) and have since been used by USGEO as the basis for its National Earth Observation Assessments. The most recent application of SBAs to Earth observing realized a framework of SBAs, SBA Sub-areas, and Key Objectives required for the completion of a full Earth observing assessment for the Arctic. This framework, described in a report released in June 2017, and a brief history of international efforts to develop an integrated pan-Arctic Observing Network, are the subjects of this presentation.

Automatic adjustment of display window (gray-level condition) for MR images using neural networks

International Nuclear Information System (INIS)

Ohhashi, Akinami; Nambu, Kyojiro.

1992-01-01

We have developed a system to automatically adjust the display window width and level (WWL) for MR images using neural networks. There were three main points in the development of our system as follows: 1) We defined an index for the clarity of a displayed image, and called 'EW'. EW is a quantitative measure of the clarity of an image displayed in a certain WWL, and can be derived from the difference between gray-level with the WWL adjusted by a human expert and with a certain WWL. 2) We extracted a group of six features from a gray-level histogram of a displayed image. We designed two neural networks which are able to learn the relationship between these features and the desired output (teaching signal), 'EQ', which is normalized to 0 to 1.0 from EW. Two neural networks were used to share the patterns to be learned; one learns a variety of patterns with less accuracy, and the other learns similar patterns with accuracy. Learning was performed using a back-propagation method. As a result, the neural networks after learning are able to provide a quantitative measure, 'Q', of the clarity of images displayed in the designated WWL. 3) Using the 'Hill climbing' method, we have been able to determine the best possible WWL for a displaying image. We have tested this technique for MR brain images. The results show that this system can adjust WWL comparable to that adjusted by a human expert for the majority of test images. The neural network is effective for the automatic adjustment of the display window for MR images. We are now studying the application of this method to MR images of another regions. (author)

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

Science.gov (United States)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks

International Nuclear Information System (INIS)

Han, Seong Ik; Jeong, Chan Se; Yang, Soon Yong

2012-01-01

A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme

Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks

Energy Technology Data Exchange (ETDEWEB)

Han, Seong Ik [Pusan National University, Busan (Korea, Republic of); Jeong, Chan Se; Yang, Soon Yong [University of Ulsan, Ulsan (Korea, Republic of)

2012-04-15

A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme.

Prediction of SO{sub 2} levels using neural networks

Energy Technology Data Exchange (ETDEWEB)

Belen M. Fernandez de Castro; Jose Manuel Prada Sanchez; Wenceslao Gonzalez Manteiga [and others] [University of Santiago de Compostela, Santiago (Spain). Department of Statistics and Operations Research, Faculty of Mathematics

2003-05-01

The paper presents an adaptation of the air pollution control help system in the neighbourhood of a coal-fired power plant in As Pontes (A Coruna, Spain), property of Endesa Generacion S.A., to the European Council Directive 1999/30/CE. This system contains a statistical prediction made half an hour before the measurement, and it helps the staff in the power plant prevent air quality level episodes. The prediction is made using neural network models. This prediction is compared with one made by a semiparametric model. 11 refs., 6 figs., 4 tabs.

LEA: An Algorithm to Estimate the Level of Location Exposure in Infrastructure-Based Wireless Networks

Directory of Open Access Journals (Sweden)

Francisco Garcia

2017-01-01

Full Text Available Location privacy in wireless networks is nowadays a major concern. This is due to the fact that the mere fact of transmitting may allow a network to pinpoint a mobile node. We consider that a first step to protect a mobile node in this situation is to provide it with the means to quantify how accurately a network establishes its position. To achieve this end, we introduce the location-exposure algorithm (LEA, which runs on the mobile terminal only and whose operation consists of two steps. In the first step, LEA discovers the positions of nearby network nodes and uses this information to emulate how they estimate the position of the mobile node. In the second step, it quantifies the level of exposure by computing the distance between the position estimated in the first step and its true position. We refer to these steps as a location-exposure problem. We tested our proposal with simulations and testbed experiments. These results show the ability of LEA to reproduce the location of the mobile node, as seen by the network, and to quantify the level of exposure. This knowledge can help the mobile user decide which actions should be performed before transmitting.

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

Science.gov (United States)

Li, Tongwen; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Xuechen; Zhang, Liangpei

2017-12-01

Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

High level cognitive information processing in neural networks

Science.gov (United States)

Barnden, John A.; Fields, Christopher A.

1992-01-01

Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

A Quality-Control-Oriented Database for a Mesoscale Meteorological Observation Network

Science.gov (United States)

Lussana, C.; Ranci, M.; Uboldi, F.

2012-04-01

In the operational context of a local weather service, data accessibility and quality related issues must be managed by taking into account a wide set of user needs. This work describes the structure and the operational choices made for the operational implementation of a database system storing data from highly automated observing stations, metadata and information on data quality. Lombardy's environmental protection agency, ARPA Lombardia, manages a highly automated mesoscale meteorological network. A Quality Assurance System (QAS) ensures that reliable observational information is collected and disseminated to the users. The weather unit in ARPA Lombardia, at the same time an important QAS component and an intensive data user, has developed a database specifically aimed to: 1) providing quick access to data for operational activities and 2) ensuring data quality for real-time applications, by means of an Automatic Data Quality Control (ADQC) procedure. Quantities stored in the archive include hourly aggregated observations of: precipitation amount, temperature, wind, relative humidity, pressure, global and net solar radiation. The ADQC performs several independent tests on raw data and compares their results in a decision-making procedure. An important ADQC component is the Spatial Consistency Test based on Optimal Interpolation. Interpolated and Cross-Validation analysis values are also stored in the database, providing further information to human operators and useful estimates in case of missing data. The technical solution adopted is based on a LAMP (Linux, Apache, MySQL and Php) system, constituting an open source environment suitable for both development and operational practice. The ADQC procedure itself is performed by R scripts directly interacting with the MySQL database. Users and network managers can access the database by using a set of web-based Php applications.

Exploring the relationship between a ground-based network and airborne CCN spectra observed at the cloud level

Science.gov (United States)

Corrigan, C.; Roberts, G. C.; Ritchie, J.; Creamean, J.; White, A. B.

2011-12-01

Cloud condensation nuclei (CCN) are aerosol particles that participate in the formation of clouds, and consequently, play a significant role in the influence of anthropogenic aerosols on atmospheric processes and climate change. Ultimately, the CCN of the most interest occupy the part of the atmosphere where cloud processes are occurring. A question arises as to whether in-cloud CCN are properly represented by the measurements of CCN at the ground level. While different locations may result in different answers depending upon local meteorology, the data set collected during CalWater 2011 may allow us to answer to what degree the ground-based observations of CCN are sufficient for evaluating cloud micro-physics over California's Central Valley and the lower slopes of the Sierra Nevada Mountains. During CalWater 2011, ground observations were performed at three different altitudes to assess the evolution of cloud-active aerosols as they were transported from sources in California's Central Valley to the lower slopes of the Sierra Nevada Mountains. CCN spectra were collected over a supersaturation range of 0.08 to 0.80%. Results from these data sets show a diurnal cycle with aerosol concentrations increasing during the afternoon and retreating during the night. In addition, a CCN instrument was placed aboard aircraft for several flights and was able to collect vertical profiles that encompassed the altitudes of the ground sites. The flight data shows a large drop in CCN concentration above the boundary layer and suggests the highest altitude ground site at China Wall ( 1540 masl)was sometimes above the Central Valley boundary layer. By using estimates of boundary layer heights over the mid-altitude site at Sugar Pine Dam (1060 masl), the events when the China Wall site is near or above the boundary layer are identified. During these events, the CCN measurements at China Wall best represent in-cloud CCN behavior. The results of this analysis may be applied towards a

Social networks usage implications at the level of medical services consumption in Romania

Directory of Open Access Journals (Sweden)

Daniel Adrian Gardan

2017-03-01

The research results reveal key issues from the perspective of emotional involvement within consumption for the patients and the influence of key variables such as level of education, personality and lifestyle within social networks usage context.

A Demonstration Marine Biodiversity Observation Network (MBON): Understanding Marine Life and its Role in Maintaining Ecosystem Services

Science.gov (United States)

Muller-Karger, F. E.; Iken, K.; Miller, R. J.; Duffy, J. E.; Chavez, F.; Montes, E.

2016-02-01

The U.S. Federal government (NOAA, NASA, BOEM, and the Smithsonian Institution), academic researchers, and private partners are laying the foundation for a Marine Biodiversity Observation Network (MBON). The goals of the network are to: 1) Observe and understand life, from microbes to whales, in different coastal and continental shelf habitats; 2) Define an efficient set of observations required for implementing a useful MBON; 3) Develop technology for biodiversity assessments including emerging environmental DNA (eDNA), remote sensing, and image analysis methods to coordinate with classical sampling; 4) Integrate and synthesize information in coordination with the Integrated Ocean Observing System (IOOS), the international Group on Earth Observations Biodiversity Observation Network(GEO BON), and the Ocean Biogeographic Information System (OBIS) sponsored by UNESCO's Intergovernmental Oceanographic Commission (IOC); and 5) Understand the linkages between marine biodiversity, ecosystem processes, and the social-economic context of a region. Pilot projects have been implemented within three NOAA National Marine Sanctuaries (Florida Keys, Monterey Bay, and Channel Islands), the wider Santa Barbara Channel, in the Chukchi Sea, and through the Smithsonian's Tennenbaum Marine Observatories Network (TMON) at several sites in the U.S. and collaborating countries. Together, these MBON sites encompass a wide range of marine environments, including deep sea, continental shelves, and coastal habitats including estuaries, wetlands, and coral reefs. The present MBON partners are open to growth of the MBON through additional collaborations. Given these initiatives, GEO BON is proposing an MBON effort that spans from pole to pole, with a pathfinder effort among countries in the Americas. By specializing in coastal ecosystems—where marine biodiversity and people are concentrated and interact most—the MBON and TMON initiatives aim to provide policymakers with the science to

Precise levelling campaigns at Olkiluoto in 2006 - 2007

International Nuclear Information System (INIS)

Lehmuskoski, P.

2008-04-01

The GPS observation network of Olkiluoto was constructed in 1994 for monitoring crustal deformations in the investigation area. To fulfil a better vertical control of the GPS network, precise levellings were started in the area in autumn 2003. The GPS network was first connected at Lapijoki to the precise levelling network of Finland to control the vertical movements of the whole island of Olkiluoto. Then the GPS network was levelled. It consisted of the reserve marks of eight GPS pillars and five levelling bench marks, two of which constituted the nodal bench mark pair. The second precise levelling campaign on the area was carried out in autumn 2005. Now only the GPS network added with the antenna platforms of nine GPS pillars were levelled. Compared to the other points, the elevation difference of two reserve mark pairs had changed significantly during two years, about one millimetre. The reason may be the blasting of the rock in the neighbourhood of these points and deformation of the rock after the blasting. Inspired by the observed elevation changes in 2005, micro loops were established and levelled onto the ONKALO and the VLJ Repository in autumn 2006. The micro loops consisted of seven and five bench marks the mean interval being about 300 metres. The campaign in autumn 2007 consisted of the levellings of all measured and undestroyed points of the earlier campaigns. The most interesting results were: (1) Compared to the mean theoretical land uplift the nodal bench mark 03216 near the crossing of Olkiluodontie and Satamatie had risen in four years 2.6 mm more than the nodal bench mark of Lapijoki and 1.9 mm of this occurred within the 0.8 mm long interval which separates the island and the continent. (2) During four years the northern part of the island had risen about one millimetre more than the middle part, where the before mentioned 03216 is located. (3) The elevation differences between the bench marks of the ONKALO micro loop were changed even one

A Computational Framework for Quantifying and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation

Science.gov (United States)

Cioaca, Alexandru

A deep scientific understanding of complex physical systems, such as the atmosphere, can be achieved neither by direct measurements nor by numerical simulations alone. Data assimila- tion is a rigorous procedure to fuse information from a priori knowledge of the system state, the physical laws governing the evolution of the system, and real measurements, all with associated error statistics. Data assimilation produces best (a posteriori) estimates of model states and parameter values, and results in considerably improved computer simulations. The acquisition and use of observations in data assimilation raises several important scientific questions related to optimal sensor network design, quantification of data impact, pruning redundant data, and identifying the most beneficial additional observations. These questions originate in operational data assimilation practice, and have started to attract considerable interest in the recent past. This dissertation advances the state of knowledge in four dimensional variational (4D-Var) data assimilation by developing, implementing, and validating a novel computational framework for estimating observation impact and for optimizing sensor networks. The framework builds on the powerful methodologies of second-order adjoint modeling and the 4D-Var sensitivity equations. Efficient computational approaches for quantifying the observation impact include matrix free linear algebra algorithms and low-rank approximations of the sensitivities to observations. The sensor network configuration problem is formulated as a meta-optimization problem. Best values for parameters such as sensor location are obtained by optimizing a performance criterion, subject to the constraint posed by the 4D-Var optimization. Tractable computational solutions to this "optimization-constrained" optimization problem are provided. The results of this work can be directly applied to the deployment of intelligent sensors and adaptive observations, as well as

Future sea level rise constrained by observations and long-term commitment

Science.gov (United States)

Mengel, Matthias; Levermann, Anders; Frieler, Katja; Robinson, Alexander; Marzeion, Ben; Winkelmann, Ricarda

2016-01-01

Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28–56 cm, 37–77 cm, and 57–131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The “constrained extrapolation” approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with process-based projections. PMID:26903648

Future sea level rise constrained by observations and long-term commitment.

Science.gov (United States)

Mengel, Matthias; Levermann, Anders; Frieler, Katja; Robinson, Alexander; Marzeion, Ben; Winkelmann, Ricarda

2016-03-08

Sea level has been steadily rising over the past century, predominantly due to anthropogenic climate change. The rate of sea level rise will keep increasing with continued global warming, and, even if temperatures are stabilized through the phasing out of greenhouse gas emissions, sea level is still expected to rise for centuries. This will affect coastal areas worldwide, and robust projections are needed to assess mitigation options and guide adaptation measures. Here we combine the equilibrium response of the main sea level rise contributions with their last century's observed contribution to constrain projections of future sea level rise. Our model is calibrated to a set of observations for each contribution, and the observational and climate uncertainties are combined to produce uncertainty ranges for 21st century sea level rise. We project anthropogenic sea level rise of 28-56 cm, 37-77 cm, and 57-131 cm in 2100 for the greenhouse gas concentration scenarios RCP26, RCP45, and RCP85, respectively. Our uncertainty ranges for total sea level rise overlap with the process-based estimates of the Intergovernmental Panel on Climate Change. The "constrained extrapolation" approach generalizes earlier global semiempirical models and may therefore lead to a better understanding of the discrepancies with process-based projections.

Reviews and syntheses: guiding the evolution of the observing system for the carbon cycle through quantitative network design

Science.gov (United States)

Kaminski, Thomas; Rayner, Peter Julian

2017-10-01

Various observational data streams have been shown to provide valuable constraints on the state and evolution of the global carbon cycle. These observations have the potential to reduce uncertainties in past, current, and predicted natural and anthropogenic surface fluxes. In particular such observations provide independent information for verification of actions as requested by the Paris Agreement. It is, however, difficult to decide which variables to sample, and how, where, and when to sample them, in order to achieve an optimal use of the observational capabilities. Quantitative network design (QND) assesses the impact of a given set of existing or hypothetical observations in a modelling framework. QND has been used to optimise in situ networks and assess the benefit to be expected from planned space missions. This paper describes recent progress and highlights aspects that are not yet sufficiently addressed. It demonstrates the advantage of an integrated QND system that can simultaneously evaluate a multitude of observational data streams and assess their complementarity and redundancy.

Multi-level policies and adaptive social networks – a conceptual modeling study for maintaining a polycentric governance system

Directory of Open Access Journals (Sweden)

Jean-Denis Mathias

2017-03-01

Full Text Available Information and collaboration patterns embedded in social networks play key roles in multilevel and polycentric modes of governance. However, modeling the dynamics of such social networks in multilevel settings has been seldom addressed in the literature. Here we use an adaptive social network model to elaborate the interplay between a central and a local government in order to maintain a polycentric governance. More specifically, our analysis explores in what ways specific policy choices made by a central agent affect the features of an emerging social network composed of local organizations and local users. Using two types of stylized policies, adaptive co-management and adaptive one-level management, we focus on the benefits of multi-level adaptive cooperation for network management. Our analysis uses viability theory to explore and to quantify the ability of these policies to achieve specific network properties. Viability theory gives the family of policies that enables maintaining the polycentric governance unlike optimal control that gives a unique blueprint. We found that the viability of the policies can change dramatically depending on the goals and features of the social network. For some social networks, we also found a very large difference between the viability of the adaptive one-level management and adaptive co-management policies. However, results also show that adaptive co-management doesn’t always provide benefits. Hence, we argue that applying viability theory to governance networks can help policy design by analyzing the trade-off between the costs of adaptive co-management and the benefits associated with its ability to maintain desirable social network properties in a polycentric governance framework.

Recharge signal identification based on groundwater level observations.

Science.gov (United States)

Yu, Hwa-Lung; Chu, Hone-Jay

2012-10-01

This study applied a method of the rotated empirical orthogonal functions to directly decompose the space-time groundwater level variations and determine the potential recharge zones by investigating the correlation between the identified groundwater signals and the observed local rainfall records. The approach is used to analyze the spatiotemporal process of piezometric heads estimated by Bayesian maximum entropy method from monthly observations of 45 wells in 1999-2007 located in the Pingtung Plain of Taiwan. From the results, the primary potential recharge area is located at the proximal fan areas where the recharge process accounts for 88% of the spatiotemporal variations of piezometric heads in the study area. The decomposition of groundwater levels associated with rainfall can provide information on the recharge process since rainfall is an important contributor to groundwater recharge in semi-arid regions. Correlation analysis shows that the identified recharge closely associates with the temporal variation of the local precipitation with a delay of 1-2 months in the study area.

Teacher Candidates' Opinions Regarding Instructional and Safe Use of Social Networks and Internet Addiction Risk Levels

Directory of Open Access Journals (Sweden)

Enis Fasli

2018-05-01

Full Text Available In conjunction with the development and advancement of internet technologies, social networking sites have created a socialization environment. Instructors point out that these tools must be used as an active and different form of communication with students. Also, participation of the students through social networking sites should be encouraged. However, the risk of internet addiction has also become widespread on the increase use of social networks. The aim of this research is to “determine the opinions of teacher candidates on the use of social networking sites in education and Internet addiction risk levels”. General survey model was used in this research in order to determine the opinions regarding social networks of teacher candidates from the education faculties in the Turkish Republic of Northern Cyprus and figure out their internet addiction risk levels. “Use of Social Networks in Education Scale” developed by Ozturk and Akgun and “Internet Addiction Test” developed by Young were used in this research. According to the results of the study, it has been figured out that almost all of the teacher candidates think that sharing information through social networking sites is either partially safe or not safe. Besides, most of the teacher candidates feel anxious about keeping information as confidential. Another important result is that teacher candidates are internet users at an average level. It also shows that they might spend too much time on the internet however they use internet in a controlled manner.

Manifestations of Personality in Online Social Networks: Self-Reported Facebook-Related Behaviors and Observable Profile Information

Science.gov (United States)

Augustine, Adam A; Vazire, Simine; Holtzman, Nicholas; Gaddis, Sam

2011-01-01

Abstract Despite the enormous popularity of Online Social Networking sites (OSNs; e.g., Facebook and Myspace), little research in psychology has been done on them. Two studies examining how personality is reflected in OSNs revealed several connections between the Big Five personality traits and self-reported Facebook-related behaviors and observable profile information. For example, extraversion predicted not only frequency of Facebook usage (Study 1), but also engagement in the site, with extraverts (vs. introverts) showing traces of higher levels of Facebook activity (Study 2). As in offline contexts, extraverts seek out virtual social engagement, which leaves behind a behavioral residue in the form of friends lists and picture postings. Results suggest that, rather than escaping from or compensating for their offline personality, OSN users appear to extend their offline personalities into the domains of OSNs. PMID:21254929

State-dependent, bidirectional modulation of neural network activity by endocannabinoids.

Science.gov (United States)

Piet, Richard; Garenne, André; Farrugia, Fanny; Le Masson, Gwendal; Marsicano, Giovanni; Chavis, Pascale; Manzoni, Olivier J

2011-11-16

The endocannabinoid (eCB) system and the cannabinoid CB1 receptor (CB1R) play key roles in the modulation of brain functions. Although actions of eCBs and CB1Rs are well described at the synaptic level, little is known of their modulation of neural activity at the network level. Using microelectrode arrays, we have examined the role of CB1R activation in the modulation of the electrical activity of rat and mice cortical neural networks in vitro. We find that exogenous activation of CB1Rs expressed on glutamatergic neurons decreases the spontaneous activity of cortical neural networks. Moreover, we observe that the net effect of the CB1R antagonist AM251 inversely correlates with the initial level of activity in the network: blocking CB1Rs increases network activity when basal network activity is low, whereas it depresses spontaneous activity when its initial level is high. Our results reveal a complex role of CB1Rs in shaping spontaneous network activity, and suggest that the outcome of endogenous neuromodulation on network function might be state dependent.

Object-oriented Approach to High-level Network Monitoring and Management

Science.gov (United States)

Mukkamala, Ravi

2000-01-01

An absolute prerequisite for the management of large investigating methods to build high-level monitoring computer networks is the ability to measure their systems that are built on top of existing monitoring performance. Unless we monitor a system, we cannot tools. Due to the heterogeneous nature of the hope to manage and control its performance. In this underlying systems at NASA Langley Research Center, paper, we describe a network monitoring system that we use an object-oriented approach for the design, we are currently designing and implementing. Keeping, first, we use UML (Unified Modeling Language) to in mind the complexity of the task and the required model users' requirements. Second, we identify the flexibility for future changes, we use an object-oriented existing capabilities of the underlying monitoring design methodology. The system is built using the system. Third, we try to map the former with the latter. APIs offered by the HP OpenView system.

Diffusion Imaging of Cerebral White Matter in Persons Who Stutter: Evidence for Network-Level Anomalies

Directory of Open Access Journals (Sweden)

Shanqing eCai

2014-02-01

Full Text Available Deficits in brain white matter have been a main focus of recent neuroimaging studies on stuttering. However, no prior study has examined brain connectivity on the global level of the cerebral cortex in persons who stutter (PWS. In the current study, we analyzed the results from probabilistic tractography between regions comprising the cortical speech network. An anatomical parcellation scheme was used to define 28 speech production-related ROIs in each hemisphere. We used network-based statistic (NBS and graph theory to analyze the connectivity patterns obtained from tractography. At the network level, the probabilistic corticocortical connectivity from the PWS group were significantly weaker that from persons with fluent speech (PFS. NBS analysis revealed significant components in the bilateral speech networks with negative correlations with stuttering severity. To facilitate comparison with previous studies, we also performed tract-based spatial statistics (TBSS and regional fractional anisotropy (FA averaging. Results from tractography, TBSS and regional FA averaging jointly highlight the importance of several regions in the left peri-Rolandic sensorimotor and premotor areas, most notably the left ventral premotor cortex and middle primary motor cortex, in the neuroanatomical basis of stuttering.

The future for the Global Sea Level Observing System (GLOSS) Sea Level Data Rescue

Science.gov (United States)

Bradshaw, Elizabeth; Matthews, Andrew; Rickards, Lesley; Aarup, Thorkild

2016-04-01

Historical sea level data are rare and unrepeatable measurements with a number of applications in climate studies (sea level rise), oceanography (ocean currents, tides, surges), geodesy (national datum), geophysics and geology (coastal land movements) and other disciplines. However, long-term time series are concentrated in the northern hemisphere and there are no records at the Permanent Service for Mean Sea Level (PSMSL) global data bank longer than 100 years in the Arctic, Africa, South America or Antarctica. Data archaeology activities will help fill in the gaps in the global dataset and improve global sea level reconstruction. The Global Sea Level Observing System (GLOSS) is an international programme conducted under the auspices of the WMO-IOC Joint Technical Commission for Oceanography and Marine Meteorology. It was set up in 1985 to collect long-term tide gauge observations and to develop systems and standards "for ocean monitoring and flood warning purposes". At the GLOSS-GE-XIV Meeting in 2015, GLOSS agreed on a number of action items to be developed in the next two years. These were: 1. To explore mareogram digitisation applications, including NUNIEAU (more information available at: http://www.mediterranee.cerema.fr/logiciel-de-numerisation-des-enregistrements-r57.html) and other recent developments in scanning/digitisation software, such as IEDRO's Weather Wizards program, to see if they could be used via a browser. 2. To publicise sea level data archaeology and rescue by: • maintaining and regularly updating the Sea Level Data Archaeology page on the GLOSS website • strengthening links to the GLOSS data centres and data rescue organisations e.g. linking to IEDRO, ACRE, RDA • restarting the sea level data rescue blog with monthly posts. 3. Investigate sources of funding for data archaeology and rescue projects. 4. Propose "Guidelines" for rescuing sea level data. These action items will aid the discovery, scanning, digitising and quality control

Gaia science alerts and the observing facilities of the Serbian-Bulgarian mini-network telescopes

Directory of Open Access Journals (Sweden)

Damljanović G.

2014-01-01

Full Text Available The astrometric European Space Agency (ESA Gaia mission was launched in December 19, 2013. One of the tasks of the Gaia mission is production of an astrometric catalog of over one billion stars and more than 500000 extragalactic sources. The quasars (QSOs, as extragalactic sources and radio emitters, are active galactic nuclei objects (AGNs whose coordinates are well determined via Very Long Baseline Interferometry (VLBI technique and may reach sub-milliarcsecond accuracy. The QSOs are the defining sources of the quasi-inertial International Celestial Reference Frame (ICRF because of their core radio morphology, negligible proper motions (until sub-milliarcsecond per year, and apparent point-like nature. Compact AGNs, visible in optical domain, are useful for a direct link of the future Gaia optical reference frame with the most accurate radio one. Apart from the above mentioned activities, Gaia has other goals such as follow-up of transient objects. One of the most important Gaia's requirements for photometric alerts is a fast observation and reduction response, that is, submition of observations within 24 hours. For this reason we have developed a pipeline. In line with possibilities of our new telescope (D(cm/F(cm=60/600 at the Astronomical Station Vidojevica (ASV, of the Astronomical Observatory in Belgrade, we joined the Gaia-Follow-Up Network for Transients Objects (Gaia-FUN-TO for the photometric alerts. Moreover, in view of the cooperation with Bulgarian colleagues (in the frst place, SV, one of us (GD initiated a local mini-network of Serbian { Bulgarian telescopes useful for the Gaia-FUN-TO and other astronomical purposes. During the next year we expect a new 1.4 m telescope at ASV site. The speed of data processing (from observation to calibration server could be one day. Here, we present an overview of our activities in the Gaia-FUN-TO which includes establishing Serbian { Bulgarian mini-network (of five telescopes at three sites

Development of Human-level Decision Making Algorithm for NPPs through Deep Neural Networks : Conceptual Approach

International Nuclear Information System (INIS)

Kim, Seung Geun; Seong, Poong Hyun

2017-01-01

Development of operation support systems and automation systems are closely related to machine learning field. However, since it is hard to achieve human-level delicacy and flexibility for complex tasks with conventional machine learning technologies, only operation support systems with simple purposes were developed and high-level automation related studies were not actively conducted. As one of the efforts for reducing human error in NPPs and technical advance toward automation, the ultimate goal of this research is to develop human-level decision making algorithm for NPPs during emergency situations. The concepts of SL, RL, policy network, value network, and MCTS, which were applied to decision making algorithm for other fields are introduced and combined with nuclear field specifications. Since the research is currently at the conceptual stage, more research is warranted.

Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

Science.gov (United States)

Foremski, Paweł; Gorawski, Michał; Grochla, Krzysztof; Polys, Konrad

2015-01-01

The paper presents a practical application of the crowdsensing idea to measure human mobility and signal coverage in cellular networks. Currently, virtually everyone is carrying a mobile phone, which may be used as a sensor to gather research data by measuring, e.g., human mobility and radio signal levels. However, many users are unwilling to participate in crowdsensing experiments. This work begins with the analysis of the barriers for engaging people in crowdsensing. A survey showed that people who agree to participate in crowdsensing expect a minimum impact on their battery lifetime and phone usage habits. To address these requirements, this paper proposes an application for measuring the location and signal strength data based on energy-efficient GPS tracking, which allows one to perform the measurements of human mobility and radio signal levels with minimum energy utilization and without any engagement of the user. The method described combines measurements from the accelerometer with effective management of the GPS to monitor the user mobility with the decrease in battery lifetime by approximately 20%. To show the applicability of the proposed platform, the sample results of signal level distribution and coverage maps gathered for an LTE network and representing human mobility are shown. PMID:26340633

Forest Focus Monitoring Database System - Technical Report 2003 Level II Data

OpenAIRE

HIEDERER ROLAND; DURRANT TRACY; GRANKE O.; LAMBOTTE Michel; LORENZ M.; MIGNON B.; OEHMICHEN K.

2007-01-01

Forest Focus (Regulation (EC) No 2152/2003) is a Community scheme for harmonized, broad-based, comprehensive and long-term monitoring of European forest ecosystems. Under this scheme the monitoring of air pollution effects on forests is carried out by participating countries on the basis of the systematic network of observation points (Level I) and of the network of observation plots for intensive and continuous monitoring (Level II). According to Article 15(1) of the Forest Focus Regulat...

Forest Focus Monitoring Database System - Technical Report 2006 Level II Data

OpenAIRE

HIEDERER Roland; DURRANT Tracy; GRANKE Oliver; LAMBOTTE Michel; LORENZ Martin; MIGNON Bertrand

2008-01-01

Forest Focus (Regulation (EC) No 2152/2003) is a Community scheme for harmonized, broadbased, comprehensive and long-term monitoring of European forest ecosystems. Under this scheme the monitoring of air pollution effects on forests is carried out by participating countries on the basis of the systematic network of observation points (Level I) and of the network of observation plots for intensive and continuous monitoring (Level II). According to Article 15(1) of the Forest Focus Regulatio...

Integration of numerical modeling and observations for the Gulf of Naples monitoring network

Science.gov (United States)

Iermano, I.; Uttieri, M.; Zambianchi, E.; Buonocore, B.; Cianelli, D.; Falco, P.; Zambardino, G.

2012-04-01

Lethal effects of mineral oils on fragile marine and coastal ecosystems are now well known. Risks and damages caused by a maritime accident can be reduced with the help of better forecasts and efficient monitoring systems. The MED project TOSCA (Tracking Oil Spills and Coastal Awareness Network), which gathers 13 partners from 4 Mediterranean countries, has been designed to help create a better response system to maritime accidents. Through the construction of an observational network, based on state of the art technology (HF radars and drifters), TOSCA provides real-time observations and forecasts of the Mediterranean coastal marine environmental conditions. The system is installed and assessed in five test sites on the coastal areas of oil spill outlets (Eastern Mediterranean) and on high traffic areas (Western Mediterranean). The Gulf of Naples, a small semi-closed basin opening to the Tyrrhenian Sea is one of the five test-sites. It is of particular interest from both the environmental point of view, due to peculiar ecosystem properties in the area, and because it sustains important touristic and commercial activities. Currently the Gulf of Naples monitoring network is represented by five automatic weather stations distributed along the coasts of the Gulf, one weather radar, two tide gauges, one waverider buoy, and moored physical, chemical and bio-optical instrumentation. In addition, a CODAR-SeaSonde HF coastal radar system composed of three antennas is located in Portici, Massa Lubrense and Castellammare. The system provides hourly data of surface currents over the entire Gulf with a 1km spatial resolution. A numerical modeling implementation based on Regional Ocean Modeling System (ROMS) is actually integrated in the Gulf of Naples monitoring network. ROMS is a 3-D, free-surface, hydrostatic, primitive equation, finite difference ocean model. In our configuration, the model has high horizontal resolution (250m), and 30 sigma levels in the vertical. Thanks

MetNet - In situ observational Network and Orbital platform to investigate the Martian environment

Science.gov (United States)

Harri, Ari-Matti; Leinonen, Jussi; Merikallio, Sini; Paton, Mark; Haukka, Harri; Polkko, Jouni

2007-09-01

MetNet Mars Mission is an in situ observational network and orbital platform mission to investigate the Martian environment and it has been proposed to European Space Agency in response to Call for proposals for the first planning cycle of Cosmic Vision 2015-2025 D/SCI/DJS/SV/val/21851. The MetNet Mars Mission is to be implemented in collaboration with ESA, FMI, LA, IKI and the payload providing science teams. The scope of the MetNet Mission is to deploy 16 MetNet Landers (MNLs) on the Martian surface by using inflatable descent system structures accompanied by an atmospheric sounder and data relay onboard the MetNet Orbiter (MNO), which is based on ESA Mars Express satellite platform. The MNLs are attached on the three sides of the satellite and most of the MNLs are deployed to Mars separately a few weeks prior to the arrival to Mars. The MetNet Orbiter will perform continuous atmospheric soundings thus complementing the accurate in situ observations at the Martian ground produced by the MetNet observation network, as well as the orbiter will serve as the primary data relay between the MetNet Landers and the Earth. The MNLs are equipped with a versatile science payload focused on the atmospheric science of Mars. Detailed characterisation of the Martian atmospheric circulation patterns, boundary layer phenomena, and climatological cycles, as well as interior investigations, require simultaneous in situ meteorological, seismic and magnetic measurements from networks of stations on the Martian surface. MetNet Mars Mission will also provide a crucial support for the safety of large landing missions in general and manned Mars missions in particular. Accurate knowledge of atmospheric conditions and weather data is essential to guarantee safe landings of the forthcoming Mars mission elements.

How Should the Fires Network for the Future Force BDE Level UA be Structured?

National Research Council Canada - National Science Library

Ulloa, Juan

2004-01-01

... to all available fires in the area of operations. This monograph constitutes an exploratory study of and preliminary analysis of the effects of networking all available fires at the brigade level UA...

Atmospheric mercury concentrations observed at ground-based monitoring sites globally distributed in the framework of the GMOS network

Directory of Open Access Journals (Sweden)

F. Sprovieri

2016-09-01

Full Text Available Long-term monitoring of data of ambient mercury (Hg on a global scale to assess its emission, transport, atmospheric chemistry, and deposition processes is vital to understanding the impact of Hg pollution on the environment. The Global Mercury Observation System (GMOS project was funded by the European Commission (http://www.gmos.eu and started in November 2010 with the overall goal to develop a coordinated global observing system to monitor Hg on a global scale, including a large network of ground-based monitoring stations, ad hoc periodic oceanographic cruises and measurement flights in the lower and upper troposphere as well as in the lower stratosphere. To date, more than 40 ground-based monitoring sites constitute the global network covering many regions where little to no observational data were available before GMOS. This work presents atmospheric Hg concentrations recorded worldwide in the framework of the GMOS project (2010–2015, analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. Major findings highlighted in this paper include a clear gradient of Hg concentrations between the Northern and Southern hemispheres, confirming that the gradient observed is mostly driven by local and regional sources, which can be anthropogenic, natural or a combination of both.

Identification of Pavement Distress Types and Pavement Condition Evaluation Based on Network Level Inspection for Jazan City Road Network

Directory of Open Access Journals (Sweden)

M Mubaraki

2014-06-01

Full Text Available The first step in establishing a pavement management system (PMS is road network identification. An important feature of a PMS is the ability to determine the current condition of a road network and predict its future condition. Pavement condition evaluation may involve structure, roughness, surface distress, and safety evaluation. In this study, a pavement distress condition rating procedure was used to achieve the objectives of this study. The main objectives of this study were to identify the common types of distress that exist on the Jazan road network (JRN, either on main roads or secondary roads, and to evaluate the pavement condition based on network level inspection. The study was conducted by collecting pavement distress types from 227 sample units on main roads and 500 sample units from secondary roads. Data were examined through analysis of common types of distress identified in both main and secondary roads. Through these data, pavement condition index (PCI for each sample unit was then calculated. Through these calculations, average PCIs for the main and secondary roads were determined. Results indicated that the most common pavement distress types on main roads were patching and utility cut patching, longitudinal and transverse cracking, polished aggregate, weathering and raveling, and alligator cracking. The most common pavement distress types on secondary roads were weathering and raveling, patching and utility cut patching, longitudinal and transverse cracking, potholes, and alligator cracking. The results also indicated that 65% of Jazan's main road network has an average pavement condition rating of very good while only 30% of Jazan's secondary roads network has an average pavement condition.

The French Contribution to the Voluntary Observing Ships Network of Sea Surface Salinity

Science.gov (United States)

Delcroix, T. C.; Alory, G.; Téchiné, P.; Diverrès, D.; Varillon, D.; Cravatte, S. E.; Gouriou, Y.; Grelet, J.; Jacquin, S.; Kestenare, E.; Maes, C.; Morrow, R.; Perrier, J.; Reverdin, G. P.; Roubaud, F.

2016-02-01

Sea Surface Salinity (SSS) is an essential climate variable that requires long term in situ observation. The French SSS Observation Service (SSS-OS) manages a network of Voluntary Observing Ships equipped with thermosalinographs (TSG). The network is global though more concentrated in the tropical Pacific and North Atlantic oceanic basins. The acquisition system is autonomous with real time transmission and is regularly serviced at harbor calls. There are distinct real time and delayed time processing chains. Real time processing includes automatic alerts to detect potential instrument problems, in case raw data are outside of climatic limits, and graphical monitoring tools. Delayed time processing relies on a dedicated software for attribution of data quality flags by visual inspection, and correction of TSG time series by comparison with daily water samples and collocated Argo data. A method for optimizing the automatic attribution of quality flags in real time, based on testing different thresholds for data deviation from climatology and retroactively comparing the resulting flags to delayed time flags, is presented. The SSS-OS real time data feed the Coriolis operational oceanography database, while the research-quality delayed time data can be extracted for selected time and geographical ranges through a graphical web interface. Delayed time data have been also combined with other SSS data sources to produce gridded files for the Pacific and Atlantic oceans. A short review of the research activities conducted with such data is given. It includes observation-based process-oriented and climate studies from regional to global scale as well as studies where in situ SSS is used for calibration/validation of models, coral proxies or satellite data.

Coordination and Integration of Global Ocean Observing through JCOMM

Science.gov (United States)

Legler, D. M.; Meldrum, D. T.; Hill, K. L.; Charpentier, E.

2016-02-01

The primary objective of the JCOMM Observations Coordination Group (OCG) is to provide technical coordination to implement fully integrated ocean observing system across the entire marine meteorology and oceanographic community. JCOMM OCG works in partnership with the Global Ocean Observing System, , which focusses on setting observing system requirements and conducting evalutions. JCOMM OCG initially focused on major global observing networks (e.g. Argo profiling floats, moored buoys, ship based observations, sea level stations, reference sites, etc), and is now expanding its horizon in recognition of new observing needs and new technologies/networks (e.g. ocean gliders). Over the next five years the JCOMM OCG is focusing its attention on integration and coordination in four major areas: observing network implementation particularly in response to integrated ocean observing requirements; observing system monitoring and metrics; standards and best practices; and improving integrated data management and access. This presentation will describe the scope and mission of JCOMM OCG; summarize the state of the global ocean observing system; highlight recent successes and resources for the research, prediction, and assessment communities; summarize our plans for the next several years; and suggest engagement opportunities.

Stability of glassy hierarchical networks

Science.gov (United States)

Zamani, M.; Camargo-Forero, L.; Vicsek, T.

2018-02-01

The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

Systems-level mechanisms of action of Panax ginseng: a network pharmacological approach.

Science.gov (United States)

Park, Sa-Yoon; Park, Ji-Hun; Kim, Hyo-Su; Lee, Choong-Yeol; Lee, Hae-Jeung; Kang, Ki Sung; Kim, Chang-Eop

2018-01-01

Panax ginseng has been used since ancient times based on the traditional Asian medicine theory and clinical experiences, and currently, is one of the most popular herbs in the world. To date, most of the studies concerning P. ginseng have focused on specific mechanisms of action of individual constituents. However, in spite of many studies on the molecular mechanisms of P. ginseng , it still remains unclear how multiple active ingredients of P. ginseng interact with multiple targets simultaneously, giving the multidimensional effects on various conditions and diseases. In order to decipher the systems-level mechanism of multiple ingredients of P. ginseng , a novel approach is needed beyond conventional reductive analysis. We aim to review the systems-level mechanism of P. ginseng by adopting novel analytical framework-network pharmacology. Here, we constructed a compound-target network of P. ginseng using experimentally validated and machine learning-based prediction results. The targets of the network were analyzed in terms of related biological process, pathways, and diseases. The majority of targets were found to be related with primary metabolic process, signal transduction, nitrogen compound metabolic process, blood circulation, immune system process, cell-cell signaling, biosynthetic process, and neurological system process. In pathway enrichment analysis of targets, mainly the terms related with neural activity showed significant enrichment and formed a cluster. Finally, relative degrees analysis for the target-disease association of P. ginseng revealed several categories of related diseases, including respiratory, psychiatric, and cardiovascular diseases.

A network model for the propagation of Hepatitis C with HIV co-infection

Science.gov (United States)

Nucit, Arnaud; Randon-Furling, Julien

2017-05-01

We define and examine a model of epidemic propagation for a virus such as Hepatitis C (with HIV co-infection) on a network of networks, namely the network of French urban areas. One network level is that of the individual interactions inside each urban area. The second level is that of the areas themselves, linked by individuals travelling between these areas and potentially helping the epidemic spread from one city to another. We choose to encode the second level of the network as extra, special nodes in the first level. We observe that such an encoding leads to sensible results in terms of the extent and speed of propagation of an epidemic, depending on its source point.

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder.

Science.gov (United States)

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-04-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.

Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder

Science.gov (United States)

Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina

2018-01-01

Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC–vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder. PMID:28944772

Predicting cryptic links in host-parasite networks.

Directory of Open Access Journals (Sweden)

Tad Dallas

2017-05-01

Full Text Available Networks are a way to represent interactions among one (e.g., social networks or more (e.g., plant-pollinator networks classes of nodes. The ability to predict likely, but unobserved, interactions has generated a great deal of interest, and is sometimes referred to as the link prediction problem. However, most studies of link prediction have focused on social networks, and have assumed a completely censused network. In biological networks, it is unlikely that all interactions are censused, and ignoring incomplete detection of interactions may lead to biased or incorrect conclusions. Previous attempts to predict network interactions have relied on known properties of network structure, making the approach sensitive to observation errors. This is an obvious shortcoming, as networks are dynamic, and sometimes not well sampled, leading to incomplete detection of links. Here, we develop an algorithm to predict missing links based on conditional probability estimation and associated, node-level features. We validate this algorithm on simulated data, and then apply it to a desert small mammal host-parasite network. Our approach achieves high accuracy on simulated and observed data, providing a simple method to accurately predict missing links in networks without relying on prior knowledge about network structure.

Emergence of cooperation in non-scale-free networks

International Nuclear Information System (INIS)

Zhang, Yichao; Aziz-Alaoui, M A; Bertelle, Cyrille; Zhou, Shi; Wang, Wenting

2014-01-01

Evolutionary game theory is one of the key paradigms behind many scientific disciplines from science to engineering. Previous studies proposed a strategy updating mechanism, which successfully demonstrated that the scale-free network can provide a framework for the emergence of cooperation. Instead, individuals in random graphs and small-world networks do not favor cooperation under this updating rule. However, a recent empirical result shows the heterogeneous networks do not promote cooperation when humans play a prisoner’s dilemma. In this paper, we propose a strategy updating rule with payoff memory. We observe that the random graphs and small-world networks can provide even better frameworks for cooperation than the scale-free networks in this scenario. Our observations suggest that the degree heterogeneity may be neither a sufficient condition nor a necessary condition for the widespread cooperation in complex networks. Also, the topological structures are not sufficed to determine the level of cooperation in complex networks. (paper)

Self-organized critical neural networks

International Nuclear Information System (INIS)

Bornholdt, Stefan; Roehl, Torsten

2003-01-01

A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

The 3D Mesonet Concept: Extending Networked Surface Meteorological Tower Observations Through Unmanned Aircraft Systems

Science.gov (United States)

Chilson, P. B.; Fiebrich, C. A.; Huck, R.; Grimsley, J.; Salazar-Cerreno, J.; Carson, K.; Jacob, J.

2017-12-01

Fixed monitoring sites, such as those in the US National Weather Service Automated Surface Observing System (ASOS) and the Oklahoma Mesonet provide valuable, high temporal resolution information about the atmosphere to forecasters and the general public. The Oklahoma Mesonet is comprised of a network of 120 surface sites providing a wide array of atmospheric measurements up to a height of 10 m with an update time of five minutes. The deployment of small unmanned aircraft to collect in-situ vertical measurements of the atmospheric state in conjunction with surface conditions has potential to significantly expand weather observation capabilities. This concept can enhance the safety of individuals and support commerce through improved observations and short-term forecasts of the weather and other environmental variables in the lower atmosphere. We report on a concept of adding the capability of collecting vertical atmospheric measurements (profiles) through the use of unmanned aerial systems (UAS) at remote Oklahoma sites deemed suitable for this application. While there are a number of other technologies currently available that can provide measurements of one or a few variables, the proposed UAS concept will be expandable and modular to accommodate several different sensor packages and provide accurate in-situ measurements in virtually all weather conditions. Such a system would facilitate off-site maintenance and calibration and would provide the ability to add new sensors as they are developed or as new requirements are identified. The small UAS must be capable of accommodating the weight of all sensor packages and have lighting, communication, and aircraft avoidance systems necessary to meet existing or future FAA regulations. The system must be able to operate unattended, which necessitates the inclusion of risk mitigation measures such as a detect and avoid radar and the ability to transmit and receive transponder signals. Moreover, the system should be able to

Using satellite observations in performance evaluation for regulatory air quality modeling: Comparison with ground-level measurements

Science.gov (United States)

Odman, M. T.; Hu, Y.; Russell, A.; Chai, T.; Lee, P.; Shankar, U.; Boylan, J.

2012-12-01

Regulatory air quality modeling, such as State Implementation Plan (SIP) modeling, requires that model performance meets recommended criteria in the base-year simulations using period-specific, estimated emissions. The goal of the performance evaluation is to assure that the base-year modeling accurately captures the observed chemical reality of the lower troposphere. Any significant deficiencies found in the performance evaluation must be corrected before any base-case (with typical emissions) and future-year modeling is conducted. Corrections are usually made to model inputs such as emission-rate estimates or meteorology and/or to the air quality model itself, in modules that describe specific processes. Use of ground-level measurements that follow approved protocols is recommended for evaluating model performance. However, ground-level monitoring networks are spatially sparse, especially for particulate matter. Satellite retrievals of atmospheric chemical properties such as aerosol optical depth (AOD) provide spatial coverage that can compensate for the sparseness of ground-level measurements. Satellite retrievals can also help diagnose potential model or data problems in the upper troposphere. It is possible to achieve good model performance near the ground, but have, for example, erroneous sources or sinks in the upper troposphere that may result in misleading and unrealistic responses to emission reductions. Despite these advantages, satellite retrievals are rarely used in model performance evaluation, especially for regulatory modeling purposes, due to the high uncertainty in retrievals associated with various contaminations, for example by clouds. In this study, 2007 was selected as the base year for SIP modeling in the southeastern U.S. Performance of the Community Multiscale Air Quality (CMAQ) model, at a 12-km horizontal resolution, for this annual simulation is evaluated using both recommended ground-level measurements and non-traditional satellite

Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia

Science.gov (United States)

Karimi, Sepideh; Kisi, Ozgur; Shiri, Jalal; Makarynskyy, Oleg

2013-03-01

Accurate predictions of sea level with different forecast horizons are important for coastal and ocean engineering applications, as well as in land drainage and reclamation studies. The methodology of tidal harmonic analysis, which is generally used for obtaining a mathematical description of the tides, is data demanding requiring processing of tidal observation collected over several years. In the present study, hourly sea levels for Darwin Harbor, Australia were predicted using two different, data driven techniques, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN). Multi linear regression (MLR) technique was used for selecting the optimal input combinations (lag times) of hourly sea level. The input combination comprises current sea level as well as five previous level values found to be optimal. For the ANFIS models, five different membership functions namely triangular, trapezoidal, generalized bell, Gaussian and two Gaussian membership function were tested and employed for predicting sea level for the next 1 h, 24 h, 48 h and 72 h. The used ANN models were trained using three different algorithms, namely, Levenberg-Marquardt, conjugate gradient and gradient descent. Predictions of optimal ANFIS and ANN models were compared with those of the optimal auto-regressive moving average (ARMA) models. The coefficient of determination, root mean square error and variance account statistics were used as comparison criteria. The obtained results indicated that triangular membership function was optimal for predictions with the ANFIS models while adaptive learning rate and Levenberg-Marquardt were most suitable for training the ANN models. Consequently, ANFIS and ANN models gave similar forecasts and performed better than the developed for the same purpose ARMA models for all the prediction intervals.

Evaluating C-RAN Fronthaul Functional Splits in Terms of Network Level Energy and Cost Savings

DEFF Research Database (Denmark)

Checko, Aleksandra; Popovska Avramova, Andrijana; Berger, Michael Stübert

2016-01-01

The placement of the complete baseband processing in a centralized pool results in high data rate requirement and inflexibility of the fronthaul network, which challenges the energy and cost effectiveness of the cloud radio access network (C-RAN). Recently, redesign of the C-RAN through functional...... split in the baseband processing chain has been proposed to overcome these challenges. This paper evaluates, by mathematical and simulation methods, different splits with respect to network level energy and cost efficiency having in the mind the expected quality of service.The proposed mathematical...... model quantifies the multiplexing gains and the trade-offs between centralization and decentralization concerning the cost of the pool, fronthaul network capacity and resource utilization. The event-based simulation captures the influence of the traffic load dynamics and traffic type variation...

The effect of increasing levels of embedded generation on the distribution network. Final report

Energy Technology Data Exchange (ETDEWEB)

Collinson, A; Earp, G K; Howson, D; Owen, R D; Wright, A J

1999-10-01

This report was commissioned as part of the EA Technology Strategic Technology Programme under guidance of the Module 5 (Embedded Generation) Steering Group. This report aims to provide information related to the distribution and supply of electricity in the context of increasing levels of embedded generation. There is a brief description of the operating environment within which electricity companies in the UK must operate. Technical issues related to the connection of generation to the existing distribution infrastructure are highlighted and the design philosophy adopted by network designers in accommodating applications for the connection of embedded generation to the network is discussed. The effects embedded generation has on the network and the issues raised are presented as many of them present barriers to the connection of embedded generators. The final chapters cover the forecast of required connection to 2010 and solutions to restrictions preventing the connection of more embedded generation to the network. (author)

The dynamics of social networks among female Asian elephants

Directory of Open Access Journals (Sweden)

de Silva Shermin

2011-07-01

Full Text Available Abstract Background Patterns in the association of individuals can shed light on the underlying conditions and processes that shape societies. Here we characterize patterns of association in a population of wild Asian Elephants at Uda Walawe National Park in Sri Lanka. We observed 286 individually-identified adult female elephants over 20 months and examined their social dynamics at three levels of organization: pairs of individuals (dyads, small sets of direct companions (ego-networks, and the population level (complete networks. Results Corroborating previous studies of this and other Asian elephant populations, we find that the sizes of elephant groups observed in the field on any particular day are typically small and that rates of association are low. In contrast to earlier studies, our longitudinal observations reveal that individuals form larger social units that can be remarkably stable across years while associations among such units change across seasons. Association rates tend to peak in dry seasons as opposed to wet seasons, with some cyclicity at the level of dyads. In addition, we find that individuals vary substantially in their fidelity to companions. At the ego-network level, we find that despite these fluctuations, individuals associate with a pool of long-term companions. At the population level, social networks do not exhibit any clear seasonal structure or hierarchical stratification. Conclusions This detailed longitudinal study reveals different social dynamics at different levels of organization. Taken together, these results demonstrate that low association rates, seemingly small group sizes, and fission-fusion grouping behavior mask hidden stability in the extensive and fluid social affiliations in this population of Asian elephants.

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

Science.gov (United States)

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2017-11-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.

Science.gov (United States)

Adhikari, Badri; Hou, Jie; Cheng, Jianlin

2018-05-01

Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key contributors to the recent progress in ab initio protein structure prediction, as demonstrated in the recent CASP experiments. Continuing the development of new methods to reliably predict contact maps is essential to further improve ab initio structure prediction. In this paper we discuss DNCON2, an improved protein contact map predictor based on two-level deep convolutional neural networks. It consists of six convolutional neural networks-the first five predict contacts at 6, 7.5, 8, 8.5 and 10 Å distance thresholds, and the last one uses these five predictions as additional features to predict final contact maps. On the free-modeling datasets in CASP10, 11 and 12 experiments, DNCON2 achieves mean precisions of 35, 50 and 53.4%, respectively, higher than 30.6% by MetaPSICOV on CASP10 dataset, 34% by MetaPSICOV on CASP11 dataset and 46.3% by Raptor-X on CASP12 dataset, when top L/5 long-range contacts are evaluated. We attribute the improved performance of DNCON2 to the inclusion of short- and medium-range contacts into training, two-level approach to prediction, use of the state-of-the-art optimization and activation functions, and a novel deep learning architecture that allows each filter in a convolutional layer to access all the input features of a protein of arbitrary length. The web server of DNCON2 is at http://sysbio.rnet.missouri.edu/dncon2/ where training and testing datasets as well as the predictions for CASP10, 11 and 12 free-modeling datasets can also be downloaded. Its source code is available at https://github.com/multicom-toolbox/DNCON2/. chengji@missouri.edu. Supplementary data are available at Bioinformatics online.

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

Science.gov (United States)

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

Network-level reproduction number and extinction threshold for vector-borne diseases.

Science.gov (United States)

Xue, Ling; Scoglio, Caterina

2015-06-01

The basic reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or not. Thresholds for disease extinction contribute crucial knowledge of disease control, elimination, and mitigation of infectious diseases. Relationships between basic reproduction numbers of two deterministic network-based ordinary differential equation vector-host models, and extinction thresholds of corresponding stochastic continuous-time Markov chain models are derived under some assumptions. Numerical simulation results for malaria and Rift Valley fever transmission on heterogeneous networks are in agreement with analytical results without any assumptions, reinforcing that the relationships may always exist and proposing a mathematical problem for proving existence of the relationships in general. Moreover, numerical simulations show that the basic reproduction number does not monotonically increase or decrease with the extinction threshold. Consistent trends of extinction probability observed through numerical simulations provide novel insights into mitigation strategies to increase the disease extinction probability. Research findings may improve understandings of thresholds for disease persistence in order to control vector-borne diseases.

A Lane-Level LBS System for Vehicle Network with High-Precision BDS/GPS Positioning

Science.gov (United States)

Guo, Chi; Guo, Wenfei; Cao, Guangyi; Dong, Hongbo

2015-01-01

In recent years, research on vehicle network location service has begun to focus on its intelligence and precision. The accuracy of space-time information has become a core factor for vehicle network systems in a mobile environment. However, difficulties persist in vehicle satellite positioning since deficiencies in the provision of high-quality space-time references greatly limit the development and application of vehicle networks. In this paper, we propose a high-precision-based vehicle network location service to solve this problem. The major components of this study include the following: (1) application of wide-area precise positioning technology to the vehicle network system. An adaptive correction message broadcast protocol is designed to satisfy the requirements for large-scale target precise positioning in the mobile Internet environment; (2) development of a concurrence service system with a flexible virtual expansion architecture to guarantee reliable data interaction between vehicles and the background; (3) verification of the positioning precision and service quality in the urban environment. Based on this high-precision positioning service platform, a lane-level location service is designed to solve a typical traffic safety problem. PMID:25755665

Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

Science.gov (United States)

Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

2013-09-01

In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Altered Brain Network in Amyotrophic Lateral Sclerosis: A Resting Graph Theory-Based Network Study at Voxel-Wise Level.

Science.gov (United States)

Zhou, Chaoyang; Hu, Xiaofei; Hu, Jun; Liang, Minglong; Yin, Xuntao; Chen, Lin; Zhang, Jiuquan; Wang, Jian

2016-01-01

Amyotrophic lateral sclerosis (ALS) is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex-matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC), a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe, and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC's z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

Altered brain network in Amyotrophic Lateral Sclerosis: a resting graph theory-based network study at voxel-wise level

Directory of Open Access Journals (Sweden)

Chaoyang eZhou

2016-05-01

Full Text Available Amyotrophic lateral sclerosis (ALS is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex- matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC, a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC’s z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

Emergent explosive synchronization in adaptive complex networks

Science.gov (United States)

Avalos-Gaytán, Vanesa; Almendral, Juan A.; Leyva, I.; Battiston, F.; Nicosia, V.; Latora, V.; Boccaletti, S.

2018-04-01

Adaptation plays a fundamental role in shaping the structure of a complex network and improving its functional fitting. Even when increasing the level of synchronization in a biological system is considered as the main driving force for adaptation, there is evidence of negative effects induced by excessive synchronization. This indicates that coherence alone cannot be enough to explain all the structural features observed in many real-world networks. In this work, we propose an adaptive network model where the dynamical evolution of the node states toward synchronization is coupled with an evolution of the link weights based on an anti-Hebbian adaptive rule, which accounts for the presence of inhibitory effects in the system. We found that the emergent networks spontaneously develop the structural conditions to sustain explosive synchronization. Our results can enlighten the shaping mechanisms at the heart of the structural and dynamical organization of some relevant biological systems, namely, brain networks, for which the emergence of explosive synchronization has been observed.

A Terrestrial Reference Frame realised on the observation level using a GPS-LEO satellite constellation

Science.gov (United States)

Koenig, Daniel

2018-02-01

Applying a one-step integrated process, i.e. by simultaneously processing all data and determining all satellite orbits involved, a Terrestrial Reference Frame (TRF) consisting of a geometric as well as a dynamic part has been determined at the observation level using the EPOS-OC software of Deutsches GeoForschungsZentrum. The satellite systems involved comprise the Global Positioning System (GPS) as well as the twin GRACE spacecrafts. Applying a novel approach, the inherent datum defect has been overcome empirically. In order not to rely on theoretical assumptions this is done by carrying out the TRF estimation based on simulated observations and using the associated satellite orbits as background truth. The datum defect is identified here as the total of all three translations as well as the rotation about the z-axis of the ground station network leading to a rank-deficient estimation problem. To rectify this singularity, datum constraints comprising no-net translation (NNT) conditions in x, y, and z as well as a no-net rotation (NNR) condition about the z-axis are imposed. Thus minimally constrained, the TRF solution covers a time span of roughly a year with daily resolution. For the geometric part the focus is put on Helmert transformations between the a priori and the estimated sets of ground station positions, and the dynamic part is represented by gravity field coefficients of degree one and two. The results of a reference solution reveal the TRF parameters to be estimated reliably with high precision. Moreover, carrying out a comparable two-step approach using the same data and models leads to parameters and observational residuals of worse quality. A validation w.r.t. external sources shows the dynamic origin to coincide at a level of 5 mm or better in x and y, and mostly better than 15 mm in z. Comparing the derived GPS orbits to IGS final orbits as well as analysing the SLR residuals for the GRACE satellites reveals an orbit quality on the few cm level

Identification of Hadronically-Decaying W Boson Top Quarks Using High-Level Features as Input to Boosted Decision Trees and Deep Neural Networks in ATLAS at #sqrt{s} = 13 TeV

CERN Document Server

Nitta, Tatsumi; The ATLAS collaboration

2017-01-01

The application of boosted decision trees and deep neural networks to the identification of hadronically-decaying W bosons and top quarks using high-level jet observables as inputs is investigated using Monte Carlo simulations. In the case of both boosted decision trees and deep neural networks, the use of machine learning techniques is found to improve the background rejection with respect to simple reference single jet substructure and mass taggers. Linear correlations between the resulting classifiers and the substructure variables are also presented.

Sliding Mode Control for NSVs with Input Constraint Using Neural Network and Disturbance Observer

Directory of Open Access Journals (Sweden)

Yan-long Zhou

2013-01-01

Full Text Available The sliding mode control (SMC scheme is proposed for near space vehicles (NSVs with strong nonlinearity, high coupling, parameter uncertainty, and unknown time-varying disturbance based on radial basis function neural networks (RBFNNs and the nonlinear disturbance observer (NDO. Considering saturation characteristic of rudders, RBFNNs are constructed as a compensator to overcome the saturation nonlinearity. The stability of the closed-loop system is proved, and the tracking error as well as the disturbance observer error can converge to the origin through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed flight control scheme.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

Science.gov (United States)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

Screen-level data assimilation of observations and pseudo-observations in COSMO-I2

Science.gov (United States)

Milelli, Dr.; Turco, Dr.; Cane, Dr.; Oberto, Dr.; Pelosini, Dr.

2009-09-01

general a positive impact during the assimilation cycle and below 1000-1500 m respectively and a neutral impact elsewhere, because the effect of the nudging vanishes a few hours after the end of the assimilation. As a second step, we introduced the assimilation of the 2 m temperature forecasts given by the Multimodel SuperEnsemble technique for all the available stations of the ARPA Piemonte network into the model, as if they were observations (we call them pseudo-observations), from +12h to +24h. The Multimodel SuperEnsemble technique is a powerful post-processing method for the estimation of weather forecast parameters. Several model outputs are combined, using weights calculated during a so-called training period. This technique has already been tested and implemented in many works on limited-area models in order to obtain reliable forecasts in complex orography regions. Also in this case we observe a positive impact mainly on the surface variables, but the effect lasts up to +24h.

Network analysis and synthesis a modern systems theory approach

CERN Document Server

Anderson, Brian D O

2006-01-01

Geared toward upper-level undergraduates and graduate students, this book offers a comprehensive look at linear network analysis and synthesis. It explores state-space synthesis as well as analysis, employing modern systems theory to unite the classical concepts of network theory. The authors stress passive networks but include material on active networks. They avoid topology in dealing with analysis problems and discuss computational techniques. The concepts of controllability, observability, and degree are emphasized in reviewing the state-variable description of linear systems. Explorations

Empirical evaluation of neutral interactions in host-parasite networks.

Science.gov (United States)

Canard, E F; Mouquet, N; Mouillot, D; Stanko, M; Miklisova, D; Gravel, D

2014-04-01

While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.

Application of GPS in a high precision engineering survey network

International Nuclear Information System (INIS)

Ruland, R.; Leick, A.

1985-04-01

A GPS satellite survey was carried out with the Macrometer to support construction at the Stanford Linear Accelerator Center (SLAC). The network consists of 16 stations of which 9 stations were part of the Macrometer network. The horizontal and vertical accuracy of the GPS survey is estimated to be 1 to 2 mm and 2 to 3 mm respectively. The horizontal accuracy of the terrestrial survey, consisting of angles and distances, equals that of the GPS survey only in the ''loop'' portion of the network. All stations are part of a precise level network. The ellipsoidal heights obtained from the GPS survey and the orthometric heights of the level network are used to compute geoid undulations. A geoid profile along the linac was computed by the National Geodetic Survey in 1963. This profile agreed with the observed geoid within the standard deviation of the GPS survey. Angles and distances were adjusted together (TERRA), and all terrestrial observations were combined with the GPS vector observations in a combination adjustment (COMB). A comparison of COMB and TERRA revealed systematic errors in the terrestrial solution. A scale factor of 1.5 ppM +- .8 ppM was estimated. This value is of the same magnitude as the over-all horizontal accuracy of both networks. 10 refs., 3 figs., 5 tabs

Sea Level Data Archaeology for the Global Sea Level Observing System (GLOSS)

Science.gov (United States)

Bradshaw, Elizabeth; Matthews, Andy; Rickards, Lesley; Jevrejeva, Svetlana

2015-04-01

The Global Sea Level Observing System (GLOSS) was set up in 1985 to collect long term tide gauge observations and has carried out a number of data archaeology activities over the past decade, including sending member organisations questionnaires to report on their repositories. The GLOSS Group of Experts (GLOSS GE) is looking to future developments in sea level data archaeology and will provide its user community with guidance on finding, digitising, quality controlling and distributing historic records. Many records may not be held in organisational archives and may instead by in national libraries, archives and other collections. GLOSS will promote a Citizen Science approach to discovering long term records by providing tools for volunteers to report data. Tide gauge data come in two different formats, charts and hand-written ledgers. Charts are paper analogue records generated by the mechanical instrument driving a pen trace. Several GLOSS members have developed software to automatically digitise these charts and the various methods were reported in a paper on automated techniques for the digitization of archived mareograms, delivered to the GLOSS GE 13th meeting. GLOSS is creating a repository of software for scanning analogue charts. NUNIEAU is the only publically available software for digitising tide gauge charts but other organisations have developed their own tide gauge digitising software that is available internally. There are several other freely available software packages that convert image data to numerical values. GLOSS could coordinate a comparison study of the various different digitising software programs by: Sending the same charts to each organisation and asking everyone to digitise them using their own procedures Comparing the digitised data Providing recommendations to the GLOSS community The other major form of analogue sea level data is handwritten ledgers, which are usually observations of high and low waters, but sometimes contain higher

Global Space Weather Observational Network: Challenges and China's Contribution

Science.gov (United States)

Wang, C.

2017-12-01

To understand space weather physical processes and predict space weather accurately, global space-borne and ground-based space weather observational network, making simultaneous observations from the Sun to geo-space (magnetosphere, ionosphere and atmosphere), plays an essential role. In this talk, we will present the advances of the Chinese space weather science missions, including the ASO-S (Advanced Space-borne Solar Observatory), MIT (Magnetosphere - Ionosphere- Thermosphere Coupling Exploration), and the ESA-China joint space weather science mission SMILE (Solar wind - Magnetosphere - Ionosphere Link Explore), a new mission to image the magnetosphere. Compared to satellites, ground-based monitors are cheap, convenient, and provide continuous real-time data. We will also introduce the Chinese Meridian Project (CMP), a ground-based program fully utilizing the geographic location of the Chinese landmass to monitor the geo-space environment. CMP is just one arm of a larger program that Chinese scientists are proposing to the international community. The International Meridian Circle Program (IMCP) for space weather hopes to connect chains of ground-based monitors at the longitudinal meridians 120 deg E and 60 deg W. IMCP takes advantage of the fact that these meridians already have the most monitors of any on Earth, with monitors in Russia, Australia, Brazil, the United States, Canada, and other countries. This data will greatly enhance the ability of scientists to monitor and predict the space weather worldwide.

The "Quasar" Network Observations in e-VLBI Mode Within the Russian Domestic VLBI Programs

Science.gov (United States)

Finkelstein, Andrey; Ipatov, Alexander; Kaidanovsky, Michael; Bezrukov, Ilia; Mikhailov, Andrey; Salnikov, Alexander; Surkis, Igor; Skurikhina, Elena

2010-01-01

The purpose of the Russian VLBI "Quasar" Network is to carry out astrometrical and geodynamical investigations. Since 2006 purely domestic observational programs with data processing at the IAA correlator have been carried out. To maintain these geodynamical programs e-VLBI technology is being developed and tested. This paper describes the IAA activity of developing a real-time VLBI system using high-speed digital communication links.

When BOLD is thicker than water: processing social information about kin and friends at different levels of the social network.

Science.gov (United States)

Wlodarski, Rafael; Dunbar, Robin I M

2016-12-01

The aim of this study was to examine differences in the neural processing of social information about kin and friends at different levels of closeness and social network level. Twenty-five female participants engaged in a cognitive social task involving different individuals in their social network while undergoing functional magnetic resonance imaging scanning to detect BOLD (Blood Oxygen Level Dependent) signals changes. Greater levels of activation occurred in several regions of the brain previously associated with social cognition when thinking about friends than when thinking about kin, including the posterior cingulate cortex (PCC) and the ventral medial prefrontal cortex (vMPFC). Linear parametric analyses across network layers further showed that, when it came to thinking about friends, activation increased in the vMPFC, lingual gyrus, and sensorimotor cortex as individuals thought about friends at closer layers of the network. These findings suggest that maintaining friendships may be more cognitively exacting than maintaining kin relationships. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Wideband noise observed at ground level in the auroral region

International Nuclear Information System (INIS)

Benson, R.F.; Desch, M.D.

1991-01-01

A sideband noise event was detected at ground level from the Andoya Rocket Range in Norway in January 1989. The signals were observed on four commercial communication receivers (tuned to 159, 515, 905, and 1200 kHz), an ionosonde (200-kHz to 3.5-MHz interference-free observations) and a riometer (32.5 MHz). The event, which occurred during a period of magnetic disturbance near magnetic midnight, was the only one observed during nearly 3 weeks of operations. This low frequency-of-occurrence is attributed partly to high local noise levels. The ease with which this event was identified on the ionograms produced by the local ionosonde suggests that routine ionosonde recordings should be inspected in search for such events. Such an effort would enhance existing research directed toward developing techniques for identifying quiet communication channels and help to identify the origin and frequency-of-occurrence of high-latitude wideband noise events. 20 refs

Present day sea level changes: observations and climatic causes

International Nuclear Information System (INIS)

Lombard, A.

2007-01-01

After a few thousand years of relative stability, sea level has risen of about 20 cm since the beginning of the 20. century. It currently rises at an average rate of about 3 mm/yr in response to global warming. About half of this rate is directly attributed to thermal expansion of sea water due to ocean warming, while the other half is mainly due to the melting of mountain glaciers and ice sheets. Satellite observations show that sea level rise is highly non-uniform. (author)

NANOOS, the Northwest Association of Networked Ocean Observing Systems: a regional Integrated Ocean Observing System (IOOS) for the Pacific Northwest US

Science.gov (United States)

Newton, J.; Martin, D.; Kosro, M.

2012-12-01

NANOOS is the Northwest Association of Networked Ocean Observing Systems, the Pacific Northwest Regional Association of the United States Integrated Ocean Observing System (US IOOS). User driven since its inception in 2003, this regional observing system is responding to a variety of scientific and societal needs across its coastal ocean, estuaries, and shorelines. Regional priorities have been solicited and re-affirmed through active engagement with users and stakeholders. NANOOS membership is composed of an even mix of academic, governmental, industry, and non-profit organizations, who appoint representatives to the NANOOS Governing Council who confirm the priority applications of the observing system. NANOOS regional priorities are: Maritime Operations, Regional Fisheries, Ecosystem Assessment, Coastal Hazards, and Climate. NANOOS' regional coastal ocean observing system is implemented by seven partners (three universities, three state agencies, and one industry). Together, these partners conduct the observations, modeling, data management and communication, analysis products, education and outreach activities of NANOOS. Observations, designed to span coastal ocean, shorelines, and estuaries, include physical, chemical, biological and geological measurements. To date, modeling has been more limited in scope, but has provided the system with increased coverage for some parameters. The data management and communication system for NANOOS, led by the NANOOS Visualization System (NVS) is the cornerstone of the user interaction with NANOOS. NVS gives users access to observational data, both real time and archived, as well as modeling output. Given the diversity of user needs, measurements, and the complexity of the coastal environment, the challenge for the system is large. NANOOS' successes take advantage of technological advances, including real-time data transmission, profiling buoys, gliders, HF radars, and modeling. The most profound challenges NANOOS faces stem

The contribution to distribution network fault levels from the connection of distributed generation

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-07-01

This report summarises the findings of a study investigating the potential impact of distributed generation (DG) on the UK distribution network fault levels up to the year 2010, and examining ways of managing the fault levels so that they do not become a barrier to increased penetration of DG. The project focuses on the circumstances and scenarios that give rise to the fault levels. The background to the study is traced, and a technical review is presented covering the relationship between DG and fault levels, and the likely impact in the period to 2010. Options for managing increased fault levels, and fault level management and costs are outlined, and a case study is given. The measurement and calculation of fault level values are described along with constraints to DG penetration due to fault level limitations, characteristics of DG machines, and long term perspectives to 2020-2030.

Comparación de los datos de áreas de manchas solares de los telescopios de la red SOON (``Solar Optical Observing Network'')

Science.gov (United States)

Leuzzi, L.; Balmaceda, L.; Francile, C.

2017-10-01

At present different studies reveal that the observations of the size of sunspots made by the network of telescopes SOON (Solar Optical Observing Network), differ from those obtained by other observatories although there is still no consensus as to the magnitude of that difference . In order to have a better understanding of the causes that give rise to these discrepancies, we present a detailed study of the sunspot series from each of the observatories that belong to the SOON network, covering the period 1982 - present and whose importance lies in the fact that they serve as a link between the historical record of the Greenwich Royal Observatory (1874-1976) and the most recent observations (as of 1976).

Compensatory plasticity in the action observation network: virtual lesions of STS enhance anticipatory simulation of seen actions.

Science.gov (United States)

Avenanti, Alessio; Annella, Laura; Candidi, Matteo; Urgesi, Cosimo; Aglioti, Salvatore M

2013-03-01

Observation of snapshots depicting ongoing motor acts increases corticospinal motor excitability. Such motor facilitation indexes the anticipatory simulation of observed (implied) actions and likely reflects computations occurring in the parietofrontal nodes of a cortical network subserving action perception (action observation network, AON). However, direct evidence for the active role of AON in simulating the future of seen actions is lacking. Using a perturb-and-measure transcranial magnetic stimulation (TMS) approach, we show that off-line TMS disruption of regions within (inferior frontal cortex, IFC) and upstream (superior temporal sulcus, STS) the parietofrontal AON transiently abolishes and enhances the motor facilitation to observed implied actions, respectively. Our findings highlight the critical role of IFC in anticipatory motor simulation. More importantly, they show that disruption of STS calls into play compensatory motor simulation activity, fundamental for counteracting the noisy visual processing induced by TMS. Thus, short-term plastic changes in the AON allow motor simulation to deal with any gap or ambiguity of ever-changing perceptual worlds. These findings support the active, compensatory, and predictive role of frontoparietal nodes of the AON in the perception and anticipatory simulation of implied actions.

Measuring dynamic process of working memory training with functional brain networks

Directory of Open Access Journals (Sweden)

Hong Wang

2015-12-01

Full Text Available In this paper, we proposed the functional brain networks and graphic theory method to measure the effect of working memory training on the neural activities. 12 subjects were recruited in this study, and they did the same working memory task before they had been trained and after training. We architected functional brain networks based on EEG coherence and calculated properties of brain networks to measure the neural co-activities and the working memory level of subjects. As the result, the internal connections in frontal region decreased after working memory training, but the connection between frontal region and top region increased. And the more small-world feature was observed after training. The features observed above were in alpha (8-13 Hz and beta (13-30 Hz bands. The functional brain networks based on EEG coherence proposed in this paper can be used as the indicator of working memory level.

Identification of Hadronically-Decaying W Bosons and Top Quarks Using High-Level Features as Input to Boosted Decision Trees and Deep Neural Networks in ATLAS at $\\sqrt{s}$ = 13 TeV

CERN Document Server

The ATLAS collaboration

2017-01-01

The application of boosted decision trees and deep neural networks to the identification of hadronically-decaying W bosons and top quarks using high-level jet observables as inputs is investigated using Monte Carlo simulations. In the case of both boosted decision trees and deep neural networks, the use of machine learning techniques is found to improve the background rejection with respect to simple reference single jet substructure and mass taggers. Linear correlations between the resulting classifiers and the substructure variables are also presented.

Enhanced activation of motor execution networks using action observation combined with imagination of lower limb movements.

Directory of Open Access Journals (Sweden)

Michael Villiger

Full Text Available The combination of first-person observation and motor imagery, i.e. first-person observation of limbs with online motor imagination, is commonly used in interactive 3D computer gaming and in some movie scenes. These scenarios are designed to induce a cognitive process in which a subject imagines himself/herself acting as the agent in the displayed movement situation. Despite the ubiquity of this type of interaction and its therapeutic potential, its relationship to passive observation and imitation during observation has not been directly studied using an interactive paradigm. In the present study we show activation resulting from observation, coupled with online imagination and with online imitation of a goal-directed lower limb movement using functional MRI (fMRI in a mixed block/event-related design. Healthy volunteers viewed a video (first-person perspective of a foot kicking a ball. They were instructed to observe-only the action (O, observe and simultaneously imagine performing the action (O-MI, or imitate the action (O-IMIT. We found that when O-MI was compared to O, activation was enhanced in the ventralpremotor cortex bilaterally, left inferior parietal lobule and left insula. The O-MI and O-IMIT conditions shared many activation foci in motor relevant areas as confirmed by conjunction analysis. These results show that (i combining observation with motor imagery (O-MI enhances activation compared to observation-only (O in the relevant foot motor network and in regions responsible for attention, for control of goal-directed movements and for the awareness of causing an action, and (ii it is possible to extensively activate the motor execution network using O-MI, even in the absence of overt movement. Our results may have implications for the development of novel virtual reality interactions for neurorehabilitation interventions and other applications involving training of motor tasks.

Collective stochastic coherence in recurrent neuronal networks

Science.gov (United States)

Sancristóbal, Belén; Rebollo, Beatriz; Boada, Pol; Sanchez-Vives, Maria V.; Garcia-Ojalvo, Jordi

2016-09-01

Recurrent networks of dynamic elements frequently exhibit emergent collective oscillations, which can show substantial regularity even when the individual elements are considerably noisy. How noise-induced dynamics at the local level coexists with regular oscillations at the global level is still unclear. Here we show that a combination of stochastic recurrence-based initiation with deterministic refractoriness in an excitable network can reconcile these two features, leading to maximum collective coherence for an intermediate noise level. We report this behaviour in the slow oscillation regime exhibited by a cerebral cortex network under dynamical conditions resembling slow-wave sleep and anaesthesia. Computational analysis of a biologically realistic network model reveals that an intermediate level of background noise leads to quasi-regular dynamics. We verify this prediction experimentally in cortical slices subject to varying amounts of extracellular potassium, which modulates neuronal excitability and thus synaptic noise. The model also predicts that this effectively regular state should exhibit noise-induced memory of the spatial propagation profile of the collective oscillations, which is also verified experimentally. Taken together, these results allow us to construe the high regularity observed experimentally in the brain as an instance of collective stochastic coherence.

Comparison of hybrid spectral-decomposition artificial neural network models for understanding climatic forcing of groundwater levels

Science.gov (United States)

Abrokwah, K.; O'Reilly, A. M.

2017-12-01

Groundwater is an important resource that is extracted every day because of its invaluable use for domestic, industrial and agricultural purposes. The need for sustaining groundwater resources is clearly indicated by declining water levels and has led to modeling and forecasting accurate groundwater levels. In this study, spectral decomposition of climatic forcing time series was used to develop hybrid wavelet analysis (WA) and moving window average (MWA) artificial neural network (ANN) models. These techniques are explored by modeling historical groundwater levels in order to provide understanding of potential causes of the observed groundwater-level fluctuations. Selection of the appropriate decomposition level for WA and window size for MWA helps in understanding the important time scales of climatic forcing, such as rainfall, that influence water levels. Discrete wavelet transform (DWT) is used to decompose the input time-series data into various levels of approximate and details wavelet coefficients, whilst MWA acts as a low-pass signal-filtering technique for removing high-frequency signals from the input data. The variables used to develop and validate the models were daily average rainfall measurements from five National Atmospheric and Oceanic Administration (NOAA) weather stations and daily water-level measurements from two wells recorded from 1978 to 2008 in central Florida, USA. Using different decomposition levels and different window sizes, several WA-ANN and MWA-ANN models for simulating the water levels were created and their relative performances compared against each other. The WA-ANN models performed better than the corresponding MWA-ANN models; also higher decomposition levels of the input signal by the DWT gave the best results. The results obtained show the applicability and feasibility of hybrid WA-ANN and MWA-ANN models for simulating daily water levels using only climatic forcing time series as model inputs.

The network construction of CSELF for earthquake monitoring and its preliminary observation

Science.gov (United States)

Tang, J.; Zhao, G.; Chen, X.; Bing, H.; Wang, L.; Zhan, Y.; Xiao, Q.; Dong, Z.

2017-12-01

The Electromagnetic (EM) anomaly in short-term earthquake precursory is most sensitive physical phenomena. Scientists believe that EM monitoring for earthquake is one of the most promising means of forecasting. However, existing ground-base EM observation confronted with increasing impact cultural noises, and the lack of a frequency range of higher than 1Hz observations. Control source of extremely low frequency (CSELF) EM is a kind of good prospective new approach. It not only has many advantages with high S/N ratio, large coverage area, probing depth ect., thereby facilitating the identification and capture anomaly signal, and it also can be used to study the electromagnetic field variation and to study the crustal medium changes of the electric structure.The first CSELF EM network for earthquake precursory monitoring with 30 observatories in China has been constructed. The observatories distribute in Beijing surrounding area and in the southern part of North-South Seismic Zone. GMS-07 system made by Metronix is equipped at each station. The observation mixed CSELF and nature source, that is, if during the control source is off transmitted, the nature source EM signal will be recorded. In genernal, there are 3 5 frequencies signals in the 0.1-300Hz frequency band will be transmit in every morning and evening in a fixed time (length 2 hours). Besides time, natural field to extend the frequency band (0.001 1000 Hz) will be observed by using 3 sample frequencies, 4096Hz sampling rate for HF, 256Hz for MF and 16Hz for LF. The low frequency band records continuously all-day and the high and medium frequency band use a slices record, the data records by cycling acquisition in every 10 minutes with length of about 4 to 8 seconds and 64 to 128 seconds , respectively. All the data is automatically processed by server installed in the observatory. The EDI file including EM field spectrums and MT responses and time series files will be sent the data center by internet

Current status of the Essential Variables as an instrument to assess the Earth Observation Networks in Europe

Science.gov (United States)

Blonda, Palma; Maso, Joan; Bombelli, Antonio; Plag, Hans Peter; McCallum, Ian; Serral, Ivette; Nativi, Stefano Stefano

2016-04-01

ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is an H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. The project will end in February 2017. Essential Variables (EVs) are defined by ConnectinGEO as "a minimal set of variables that determine the system's state and developments, are crucial for predicting system developments, and allow us to define metrics that measure the trajectory of the system". . Specific application-dependent characteristics, such as spatial and temporal resolution of observations and data quality thresholds, are not generally included in the EV definition. This definition and the present status of EV developments in different societal benefit areas was elaborated at the ConnectinGEO workshop "Towards a sustainability process for GEOSS Essential Variables (EVs)," which was held in Bari on June 11-12, 2015 (http://www.gstss.org/2015_Bari/). Presentations and reports contributed by a wide range of communities provided important inputs from different sectors for assessing the status of the EV development. In most thematic areas, the development of sets of EVs is a community process leading to an agreement on what is essential for the goals of the community. While there are many differences across the communities in the details of the criteria, methodologies and processes used to develop sets of EVs, there is also a considerable common core across the communities, particularly those with a more advanced discussion. In particular, there is some level of overlap in different topics (e.g., Climate and Water), and there is a potential to develop an integrated set of EVs common to several thematic areas as well as specific ones that satisfy only one community. The thematic areas with

Use of modeling to assess the scalability of Ethernet networks for the ATLAS second level trigger

CERN Document Server

Korcyl, K; Dobinson, Robert W; Saka, F

1999-01-01

The second level trigger of LHC's ATLAS experiment has to perform real-time analyses on detector data at 10 GBytes/s. A switching network is required to connect more than thousand read-out buffers to about thousand processors that execute the trigger algorithm. We are investigating the use of Ethernet technology to build this large switching network. Ethernet is attractive because of the huge installed base, competitive prices, and recent introduction of the high-performance Gigabit version. Due to the network's size it has to be constructed as a layered structure of smaller units. To assess the scalability of such a structure we evaluated a single switch unit. (0 refs).

System level mechanisms of adaptation, learning, memory formation and evolvability: the role of chaperone and other networks.

Science.gov (United States)

Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter

2014-05-01

During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.

Networks and Transaction Costs

DEFF Research Database (Denmark)

Henning, Christian; Henningsen, Geraldine; Henningsen, Arne

2011-01-01

Based on the well-known fact that social networks can provide effective mechanisms that help to increase the trust level between two trade partners, we apply a simple game-theoretical framework to derive transaction costs as a high risk of opportunistic behavior in a repeated trade relation...... determined by the density and size of trading networks. In the empirical part of the paper we apply a two stage procedure to estimate the impact of social network structures on farm’s transaction costs observed for different input and output markets. At a first stage we estimate a multiple input...... transaction cost functions for all traded farm inputs and outputs. Estimation results based on a sample of 315 Polish farms imply a significant influence of social network structures on farm’s transaction costs. Moreover, estimated transaction costs correspond to a reasonable amount of farm specific shadow...

Networks and Transaction Costs

DEFF Research Database (Denmark)

Henning, Christian; Henningsen, Geraldine; Henningsen, Arne

2011-01-01

determined by the density and size of trading networks. In the empirical part of the paper we apply a two stage procedure to estimate the impact of social network structures on farm’s transaction costs observed for different input and output markets. At a first stage we estimate a multiple input......Based on the well-known fact that social networks can provide effective mechanisms that help to increase the trust level between two trade partners, we apply a simple game-theoretical framework to derive transaction costs as a high risk of opportunistic behavior in a repeated trade relation...... transaction cost functions for all traded farm inputs and outputs. Estimation results based on a sample of 315 Polish farms imply a significant influence of social network structures on farm’s transaction costs. Moreover, estimated transaction costs correspond to a reasonable amount of farm specific shadow...

LTAR information management: Six examples of data intensive work at site and network levels

Science.gov (United States)

Information systems for managing research data from the Long-term Agroecosystem Research (LTAR) program are implemented at site and network levels. Different information management tools are necessary to manage a variety of data types. There is no one-size fits all solution for managing all LTAR dat...

Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China

Directory of Open Access Journals (Sweden)

J. J. Lian

2013-02-01

Full Text Available Coastal cities are particularly vulnerable to flood under multivariable conditions, such as heavy precipitation, high sea levels, and storms. The combined effect of multiple sources and the joint probability of extremes should be considered to assess and manage flood risk better. This paper aims to study the combined effect of rainfall and the tidal level of the receiving water body on flood probability and severity in Fuzhou City, which has a complex river network. Flood severity under a range of precipitation intensities, with return periods (RPs of 5 yr to 100 yr, and tidal levels was assessed through a hydrodynamic model verified by data observed during Typhoon Longwang in 2005. According to the percentages of the river network where flooding occurred, the threshold conditions for flood severity were estimated in two scenarios: with and without working pumps. In Fuzhou City, working pumps efficiently reduce flood risk from precipitation within a 20-yr RP. However, the pumps may not work efficiently when rainfall exceeds a 100-yr RP because of the limited conveyance capacity of the river network. Joint risk probability was estimated through the optimal copula. The joint probability of rainfall and tidal level both exceeding their threshold values is very low, and the greatest threat in Fuzhou comes from heavy rainfall. However, the tidal level poses an extra risk of flood. Given that this extra risk is ignored in the design of flood defense in Fuzhou, flood frequency and severity may be higher than understood during design.

Both novelty and expertise increase action observation network activity

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Sook-Lei eLiew

2013-09-01

Full Text Available Our experiences with others affect how we perceive their actions. In particular, activity in bilateral premotor and parietal cortices during action observation, collectively known as the action observation network (AON, is modulated by one’s expertise with the observed actions or individuals. However, conflicting reports suggest that AON activity is greatest both for familiar and unfamiliar actions. The current study examines the effects of different types and amounts of experience (e.g., visual, interpersonal, personal on AON activation. fMRI was used to scan 16 healthy participants without prior experience with individuals with amputations (novices, 11 experienced occupational therapists (OTs who had varying amounts of experience with individuals with amputations, and one individual born with below-elbow residual limbs (participant CJ, as they viewed video clips of goal-matched actions performed by an individual with residual limbs and by an individual with hands. Participants were given increased visual exposure to actions performed by both effectors midway through the scanning procedure. Novices demonstrated a large AON response to the initial viewing of an individual with residual limbs compared to one with hands, but this signal was attenuated after they received visual exposure to both effectors. In contrast, OTs, who had moderate familiarity with residual limbs, demonstrated a lower AON response upon initial viewing—similar to novices after they received visual exposure. At the other extreme, CJ, who has extreme familiarity with residual limbs both visually and motorically, shows a largely increased left-lateralized AON response, exceeding that of novices and experienced OTs, when viewing the residual limb compared to hand actions. These results suggest that a nuanced model of AON engagement is needed to explain how cases of both extreme experience (CJ and extreme novelty (novices can result in the greatest AON activity.

Defining Essential Biodiversity Variables (EBVs) as a contribution to Essential Ocean Variables (EOVs): A Core Task of the Marine Biodiversity Observation Network (MBON) to Accelerate Integration of Biological Observations in the Global Ocean Observing System (GOOS)

Science.gov (United States)

Pearlman, J.; Muller-Karger, F. E.; Sousa Pinto, I.; Costello, M. J.; Duffy, J. E.; Appeltans, W.; Fischer, A. S.; Canonico, G.; Klein, E.; Obura, D.; Montes, E.; Miloslavich, P.; Howard, M.

2017-12-01

The Marine Biodiversity Observation Network (MBON) is a networking effort under the umbrella of the Group on Earth Observations Biodiversity Observation Network (GEO BON). The objective of the MBON is to link existing groups engaged in ocean observation and help define practical indices to deploy in an operational manner to track changes in the number of marine species, the abundance and biomass of marine organisms, the diverse interactions between organisms and the environment, and the variability and change of specific habitats of interest. MBON serves as the biodiversity arm of Blue Planet, the initiative of the Group on Earth Observations (GEO) for the benefit of society. The Global Ocean Observing System (GOOS) was established under the auspices of the Intergovernmental Oceanographic Commission (IOC) in 1991 to organize international ocean observing efforts. The mission of the GOOS is to support monitoring to improve the management of marine and coastal ecosystems and resources, and to enable scientific research. GOOS is engaged in a continuing, rigorous process of identifying Essential Ocean Variables (EOVs). MBON is working with GOOS and the Ocean Biogeographic Information System (OBIS, also under the IOC) to define Essential Biodiversity Variables (EBVs) as those Essential Ocean Variables (EOVs) that have explicit taxonomic records associated with them. For practical purposes, EBVs are a subset of the EOVs. The focus is to promote the integration of biological EOVs including EBVs into the existing and planned national and international ocean observing systems. The definition avoids a proliferation of 'essential' variables across multiple organizations. MBON will continue to advance practical and wide use of EBVs and related EOV. This is an effective way to contribute to several UN assessments (e.g., from IPBES, IPCC, and the World Ocean Assessment under the UN Regular Process), UN Sustainable Development Goals, and to address targets and goals defined under

Action observation and mirror neuron network: a tool for motor stroke rehabilitation.

Science.gov (United States)

Sale, P; Franceschini, M

2012-06-01

Mirror neurons are a specific class of neurons that are activated and discharge both during observation of the same or similar motor act performed by another individual and during the execution of a motor act. Different studies based on non invasive neuroelectrophysiological assessment or functional brain imaging techniques have demonstrated the presence of the mirror neuron and their mechanism in humans. Various authors have demonstrated that in the human these networks are activated when individuals learn motor actions via execution (as in traditional motor learning), imitation, observation (as in observational learning) and motor imagery. Activation of these brain areas (inferior parietal lobe and the ventral premotor cortex, as well as the caudal part of the inferior frontal gyrus [IFG]) following observation or motor imagery may thereby facilitate subsequent movement execution by directly matching the observed or imagined action to the internal simulation of that action. It is therefore believed that this multi-sensory action-observation system enables individuals to (re) learn impaired motor functions through the activation of these internal action-related representations. In humans, the mirror mechanism is also located in various brain segment: in Broca's area, which is involved in language processing and speech production and not only in centres that mediate voluntary movement, but also in cortical areas that mediate visceromotor emotion-related behaviours. On basis of this finding, during the last 10 years various studies were carry out regarding the clinical use of action observation for motor rehabilitation of sub-acute and chronic stroke patients.

A distributed water level network in ephemeral river reaches to identify hydrological processes within anthropogenic catchments

Science.gov (United States)

Sarrazin, B.; Braud, I.; Lagouy, M.; Bailly, J. S.; Puech, C.; Ayroles, H.

2009-04-01

In order to study the impact of land use change on the water cycle, distributed hydrological models are more and more used, because they have the ability to take into account the land surface heterogeneity and its evolution due to anthropogenic pressure. These models provide continuous distributed simulations of streamflow, runoff, soil moisture, etc, which, ideally, should be evaluated against continuous distributed measurements, taken at various scales and located in nested sub-catchments. Distributed network of streamflow gauging stations are in general scarce and very expensive to maintain. Furthermore, they can hardly be installed in the upstream parts of the catchments where river beds are not well defined. In this paper, we present an alternative to these standard streamflow gauging stations network, based on self powered high resolution water level sensors using a capacitive water height data logger. One of their advantages is that they can be installed even in ephemeral reaches and from channel head locations to high order streams. Furthermore, these innovative and easily adaptable low cost sensors offer the possibility to develop in the near future, a wireless network application. Such a network, including 15 sensors has been set up on nested watersheds in small and intermittent streams of a 7 km² catchment, located in the mountainous "Mont du Lyonnais" area, close to the city of Lyon, France. The land use of this catchment is mostly pasture, crop and forest, but the catchment is significantly affected by human activities, through the existence of a dense roads and paths network and urbanized areas. The equipment provides water levels survey during precipitation events in the hydrological network with a very accurate time step (2 min). Water levels can be related to runoff production and catchment response as a function of scale. This response will depend, amongst other, on variable soil water storage capacity, physiographic data and characteristics of

Observations of brine drainage networks and microstructure of first-year sea ice

Science.gov (United States)

Cole, D. M.; Shapiro, L. H.

1998-09-01

Brine drainage networks and the microstructure of first-year sea ice have been examined at two locations near Barrow, northern Alaska. A method for obtaining full-depth sections of ice sheets up to 1.8 m thick is presented and shown to provide information on the spatial distribution and geometry of brine drainage networks on a scale of meters. A number of such sections from the two test sites are presented which reveal a greater variety of main channel and side branch configurations than is typically observed in ice grown in the laboratory. Vertical and horizontal micrographs and thin section photographs were obtained in November 1993, and March and May 1994 at a test site in the relatively protected Elson Lagoon. The resulting time series of photographic records provide detailed information on the size, shape, and spatial distribution of the brine- and gas-filled inclusions and a means to quantify their size and shape changes with time. An example of the changes with time in inclusion sizes and aspect ratios in the vertical and horizontal directions for a depth of 0.2 m, with a given thermal history is also presented.

Observations Of General Learning Patterns In An Upper-Level Thermal Physics Course

Science.gov (United States)

Meltzer, David E.

2009-11-01

I discuss some observations from using interactive-engagement instructional methods in an upper-level thermal physics course over a two-year period. From the standpoint of the subject matter knowledge of the upper-level students, there was a striking persistence of common learning difficulties previously observed in students enrolled in the introductory course, accompanied, however, by some notable contrasts between the groups. More broadly, I comment on comparisons and contrasts regarding general pedagogical issues among different student sub-populations, for example: differences in the receptivity of lower- and upper-level students to diagrammatic representations; varying receptivity to tutorial-style instructional approach within the upper-level population; and contrasting approaches to learning among physics and engineering sub-populations in the upper-level course with regard to use of symbolic notation, mathematical equations, and readiness to employ verbal explanations.

Structural architecture supports functional organization in the human aging brain at a regionwise and network level.

Science.gov (United States)

Zimmermann, Joelle; Ritter, Petra; Shen, Kelly; Rothmeier, Simon; Schirner, Michael; McIntosh, Anthony R

2016-07-01

Functional interactions in the brain are constrained by the underlying anatomical architecture, and structural and functional networks share network features such as modularity. Accordingly, age-related changes of structural connectivity (SC) may be paralleled by changes in functional connectivity (FC). We provide a detailed qualitative and quantitative characterization of the SC-FC coupling in human aging as inferred from resting-state blood oxygen-level dependent functional magnetic resonance imaging and diffusion-weighted imaging in a sample of 47 adults with an age range of 18-82. We revealed that SC and FC decrease with age across most parts of the brain and there is a distinct age-dependency of regionwise SC-FC coupling and network-level SC-FC relations. A specific pattern of SC-FC coupling predicts age more reliably than does regionwise SC or FC alone (r = 0.73, 95% CI = [0.7093, 0.8522]). Hence, our data propose that regionwise SC-FC coupling can be used to characterize brain changes in aging. Hum Brain Mapp 37:2645-2661, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Why and how selection patterns in classroom networks differ between students.The potential influence of networks size preferences, level of information, and group membership.

Directory of Open Access Journals (Sweden)

Baerveldt, Chris

2010-12-01

Full Text Available High school students can select class mates for new friendships using a repertoire of patterns. They can actively pursue new friendships, make use of the existing network structure, and/ or use the scarce and often erroneous information about candidates. In this theoretical paper, we argue that such selection patterns should not be studied as the result of general rules, as is usually done in social network studies. Specifically, we state that network size preferences, the level of information about individual attributes of fellow classmates, and group membership are likely to differ among high school students, and that as a result, also their selection patterns are likely to be different. In this paper we sketch the theoretical articulations between these.

Implementation of a network level protocol on a GIXINET type local network

International Nuclear Information System (INIS)

Loeuillet, J.L.

1987-11-01

The installation of a communication system for transferring results from several experiment laboratories to a computing center is described. The objectives of a useful bit rate of 24 kbs, low connection cost and simple infrastructure, extension of the network to 4 buildings situated within a radius of 300m, and connection in the most standardized fashion possible are attained by using the GIXINET local network and adopting the X25 packet protocol. Bit rates of 17.2 kbs for standard 128 octet packets, and 44 kbs for nonstandard packets (776 octets in this case) [fr

Fragmenting networks by targeting collective influencers at a mesoscopic level

Science.gov (United States)

Kobayashi, Teruyoshi; Masuda, Naoki

2016-11-01

A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure.

A Neural Network Approach to Fluid Level Measurement in Dynamic Environments Using a Single Capacitive Sensor

Directory of Open Access Journals (Sweden)

Edin TERZIC

2010-03-01

Full Text Available A measurement system has been developed using a single tube capacitive sensor to accurately determine the fluid level in vehicular fuel tanks. A novel approach based on artificial neural networks based signal pre-processing and classification has been described in this article. A broad investigation on the Backpropagation neural network and some selected signal pre-processing filters, namely, Moving Mean, Moving Median, and Wavelet Filter has also been presented. An on field drive trial was conducted under normal driving conditions at various fuel volumes ranging from 5 L to 50 L to acquire training samples from the capacitive sensor. A second field trial was conducted to obtain test samples to verify the performance of the neural network. The neural network was trained and verified with 50 % of the training and test samples. The results obtained using the neural network approach having different filtration methods are compared with the results obtained using simple Moving Mean and Moving Median functions. It is demonstrated that the Backpropagation neural network with Moving Median filter produced the most accurate outcome compared with the other signal filtration methods.

Optimal topologies for maximizing network transmission capacity

Science.gov (United States)

Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.

2018-04-01

It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.

Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

Science.gov (United States)

Beal, Jacob; Lu, Ting; Weiss, Ron

2011-01-01

The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

Constitutive modelling of composite biopolymer networks.

Science.gov (United States)

Fallqvist, B; Kroon, M

2016-04-21

The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Network Sampling with Memory: A proposal for more efficient sampling from social networks

Science.gov (United States)

Mouw, Ted; Verdery, Ashton M.

2013-01-01

Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)—the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a “List” mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a “Search” mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS. PMID:24159246

Sparsity in Model Gene Regulatory Networks

International Nuclear Information System (INIS)

Zagorski, M.

2011-01-01

We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)

A Closer Look at Deep Learning Neural Networks with Low-level Spectral Periodicity Features

DEFF Research Database (Denmark)

Sturm, Bob L.; Kereliuk, Corey; Pikrakis, Aggelos

2014-01-01

Systems built using deep learning neural networks trained on low-level spectral periodicity features (DeSPerF) reproduced the most “ground truth” of the systems submitted to the MIREX 2013 task, “Audio Latin Genre Classification.” To answer why this was the case, we take a closer look...

The effects of music on brain functional networks: a network analysis.

Science.gov (United States)

Wu, J; Zhang, J; Ding, X; Li, R; Zhou, C

2013-10-10

The human brain can dynamically adapt to the changing surroundings. To explore this issue, we adopted graph theoretical tools to examine changes in electroencephalography (EEG) functional networks while listening to music. Three different excerpts of Chinese Guqin music were played to 16 non-musician subjects. For the main frequency intervals, synchronizations between all pair-wise combinations of EEG electrodes were evaluated with phase lag index (PLI). Then, weighted connectivity networks were created and their organizations were characterized in terms of an average clustering coefficient and characteristic path length. We found an enhanced synchronization level in the alpha2 band during music listening. Music perception showed a decrease of both normalized clustering coefficient and path length in the alpha2 band. Moreover, differences in network measures were not observed between musical excerpts. These experimental results demonstrate an increase of functional connectivity as well as a more random network structure in the alpha2 band during music perception. The present study offers support for the effects of music on human brain functional networks with a trend toward a more efficient but less economical architecture. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Seeing Eye to Eye: Predicting Teacher-Student Agreement on Classroom Social Networks

Science.gov (United States)

Neal, Jennifer Watling; Cappella, Elise; Wagner, Caroline; Atkins, Marc S.

2010-01-01

This study examines the association between classroom characteristics and teacher-student agreement in perceptions of students’ classroom peer networks. Social network, peer nomination, and observational data were collected from a sample of second through fourth grade teachers (N=33) and students (N=669) in 33 classrooms across five high poverty urban schools. Results demonstrate that variation in teacher-student agreement on the structure of students’ peer networks can be explained, in part, by developmental factors and classroom characteristics. Developmental increases in network density partially mediated the positive relationship between grade level and teacher-student agreement. Larger class sizes and higher levels of normative aggressive behavior resulted in lower levels of teacher-student agreement. Teachers’ levels of classroom organization had mixed influences, with behavior management negatively predicting agreement, and productivity positively predicting agreement. These results underscore the importance of the classroom context in shaping teacher and student perceptions of peer networks. PMID:21666768

Correlations in star networks: from Bell inequalities to network inequalities

International Nuclear Information System (INIS)

Tavakoli, Armin; Renou, Marc Olivier; Gisin, Nicolas; Brunner, Nicolas

2017-01-01

The problem of characterizing classical and quantum correlations in networks is considered. Contrary to the usual Bell scenario, where distant observers share a physical system emitted by one common source, a network features several independent sources, each distributing a physical system to a subset of observers. In the quantum setting, the observers can perform joint measurements on initially independent systems, which may lead to strong correlations across the whole network. In this work, we introduce a technique to systematically map a Bell inequality to a family of Bell-type inequalities bounding classical correlations on networks in a star-configuration. Also, we show that whenever a given Bell inequality can be violated by some entangled state ρ , then all the corresponding network inequalities can be violated by considering many copies of ρ distributed in the star network. The relevance of these ideas is illustrated by applying our method to a specific multi-setting Bell inequality. We derive the corresponding network inequalities, and study their quantum violations. (paper)

Application of Artificial Neural Network into the Water Level Modeling and Forecast

Directory of Open Access Journals (Sweden)

Marzenna Sztobryn

2013-06-01

Full Text Available The dangerous sea and river water level increase does not only destroy the human lives, but also generate the severe flooding in coastal areas. The rapidly changes in the direction and velocity of wind and associated with them sea level changes could be the severe threat for navigation, especially on the fairways of small fishery harbors located in the river mouth. There is the area of activity of two external forcing: storm surges and flood wave. The aim of the work was the description of an application of Artificial Neural Network (ANN methodology into the water level forecast in the case study field in Swibno harbor located is located at 938.7 km of the Wisla River and at a distance of about 3 km up the mouth (Gulf of Gdansk - Baltic Sea.

Design of a Multiobjective Reverse Logistics Network Considering the Cost and Service Level

Directory of Open Access Journals (Sweden)

Shuang Li

2012-01-01

Full Text Available Reverse logistics, which is induced by various forms of used products and materials, has received growing attention throughout this decade. In a highly competitive environment, the service level is an important criterion for reverse logistics network design. However, most previous studies about product returns only focused on the total cost of the reverse logistics and neglected the service level. To help a manufacturer of electronic products provide quality postsale repair service for their consumer, this paper proposes a multiobjective reverse logistics network optimisation model that considers the objectives of the cost, the total tardiness of the cycle time, and the coverage of customer zones. The Nondominated Sorting Genetic Algorithm II (NSGA-II is employed for solving this multiobjective optimisation model. To evaluate the performance of NSGA-II, a genetic algorithm based on weighted sum approach and Multiobjective Simulated Annealing (MOSA are also applied. The performance of these three heuristic algorithms is compared using numerical examples. The computational results show that NSGA-II outperforms MOSA and the genetic algorithm based on weighted sum approach. Furthermore, the key parameters of the model are tested, and some conclusions are drawn.

Power level control of the TRIGA Mark-II research reactor using the multifeedback layer neural network and the particle swarm optimization

International Nuclear Information System (INIS)

Coban, Ramazan

2014-01-01

Highlights: • A multifeedback-layer neural network controller is presented for a research reactor. • Off-line learning of the MFLNN is accomplished by the PSO algorithm. • The results revealed that the MFLNN–PSO controller has a remarkable performance. - Abstract: In this paper, an artificial neural network controller is presented using the Multifeedback-Layer Neural Network (MFLNN), which is a recently proposed recurrent neural network, for neutronic power level control of a nuclear research reactor. Off-line learning of the MFLNN is accomplished by the Particle Swarm Optimization (PSO) algorithm. The MFLNN-PSO controller design is based on a nonlinear model of the TRIGA Mark-II research reactor. The learning and the test processes are implemented by means of a computer program at different power levels. The simulation results obtained reveal that the MFLNN-PSO controller has a remarkable performance on the neutronic power level control of the reactor for tracking the step reference power trajectories

Multi-power-level Energy Saving Management for Passive Optical Networks

OpenAIRE

Taheri, Mina; Ansari, Nirwan

2014-01-01

Environmental concerns have motivated network designers to further reduce energy consumption of access networks. This paper focuses on reducing energy consumption of Ethernet passive optical network (EPON) as one of the most efficient transmission technologies for broadband access. In EPON, the downstream traffic is sent from the optical line terminal (OLT) located at the central office to all optical network units (ONUs). Each ONU checks all arrival downstream packets and selects the downstr...

Data center networks and network architecture

Science.gov (United States)

Esaki, Hiroshi

2014-02-01

This paper discusses and proposes the architectural framework, which is for data center networks. The data center networks require new technical challenges, and it would be good opportunity to change the functions, which are not need in current and future networks. Based on the observation and consideration on data center networks, this paper proposes; (i) Broadcast-free layer 2 network (i.e., emulation of broadcast at the end-node), (ii) Full-mesh point-to-point pipes, and (iii) IRIDES (Invitation Routing aDvertisement for path Engineering System).

Nonlinear Inference in Partially Observed Physical Systems and Deep Neural Networks

Science.gov (United States)

Rozdeba, Paul J.

The problem of model state and parameter estimation is a significant challenge in nonlinear systems. Due to practical considerations of experimental design, it is often the case that physical systems are partially observed, meaning that data is only available for a subset of the degrees of freedom required to fully model the observed system's behaviors and, ultimately, predict future observations. Estimation in this context is highly complicated by the presence of chaos, stochasticity, and measurement noise in dynamical systems. One of the aims of this dissertation is to simultaneously analyze state and parameter estimation in as a regularized inverse problem, where the introduction of a model makes it possible to reverse the forward problem of partial, noisy observation; and as a statistical inference problem using data assimilation to transfer information from measurements to the model states and parameters. Ultimately these two formulations achieve the same goal. Similar aspects that appear in both are highlighted as a means for better understanding the structure of the nonlinear inference problem. An alternative approach to data assimilation that uses model reduction is then examined as a way to eliminate unresolved nonlinear gating variables from neuron models. In this formulation, only measured variables enter into the model, and the resulting errors are themselves modeled by nonlinear stochastic processes with memory. Finally, variational annealing, a data assimilation method previously applied to dynamical systems, is introduced as a potentially useful tool for understanding deep neural network training in machine learning by exploiting similarities between the two problems.

The observation on plasma endothelin levels in patients with graves' disease

International Nuclear Information System (INIS)

Hao Xiaojun; Liu Changshan; Yang Lianrong; Zhang Qiliang; Wang Honggang; Liu Xudong

2002-01-01

Observing the plasma endothelin levels in patients with Graves' disease to probe its clinical significance, plasma endothelin levels were measured in 55 cases of Graves' disease before and after treatment respectively, and these were compared with that of 23 health subjects. Results: plasma endothelin levels in patients with Graves' disease significantly increase, compared with heath subjects (150.4 +- 29.31 ng/L vs 42.80 +- 7.58 ng/L, P < 0.01); post-treatment endothelin levels apparently decrease (97.61 +- 15.99 ng/L vs 150.4 +- 29.31 ng/L, P < 0.01). Plasma endothelin levels in patients with Graves' disease significantly increase, and after treatment the endothelin levels decrease following decreasing of thyroid hormone level and high hemodynamics

The combined geodetic network adjusted on the reference ellipsoid – a comparison of three functional models for GNSS observations

Directory of Open Access Journals (Sweden)

Kadaj Roman

2016-12-01

Full Text Available The adjustment problem of the so-called combined (hybrid, integrated network created with GNSS vectors and terrestrial observations has been the subject of many theoretical and applied works. The network adjustment in various mathematical spaces was considered: in the Cartesian geocentric system on a reference ellipsoid and on a mapping plane. For practical reasons, it often takes a geodetic coordinate system associated with the reference ellipsoid. In this case, the Cartesian GNSS vectors are converted, for example, into geodesic parameters (azimuth and length on the ellipsoid, but the simple form of converted pseudo-observations are the direct differences of the geodetic coordinates. Unfortunately, such an approach may be essentially distorted by a systematic error resulting from the position error of the GNSS vector, before its projection on the ellipsoid surface. In this paper, an analysis of the impact of this error on the determined measures of geometric ellipsoid elements, including the differences of geodetic coordinates or geodesic parameters is presented. Assuming that the adjustment of a combined network on the ellipsoid shows that the optimal functional approach in relation to the satellite observation, is to create the observational equations directly for the original GNSS Cartesian vector components, writing them directly as a function of the geodetic coordinates (in numerical applications, we use the linearized forms of observational equations with explicitly specified coefficients. While retaining the original character of the Cartesian vector, one avoids any systematic errors that may occur in the conversion of the original GNSS vectors to ellipsoid elements, for example the vector of the geodesic parameters. The problem is theoretically developed and numerically tested. An example of the adjustment of a subnet loaded from the database of reference stations of the ASG-EUPOS system was considered for the preferred functional

Diagnosing Anomalous Network Performance with Confidence

Energy Technology Data Exchange (ETDEWEB)

Settlemyer, Bradley W [ORNL; Hodson, Stephen W [ORNL; Kuehn, Jeffery A [ORNL; Poole, Stephen W [ORNL

2011-04-01

Variability in network performance is a major obstacle in effectively analyzing the throughput of modern high performance computer systems. High performance interconnec- tion networks offer excellent best-case network latencies; how- ever, highly parallel applications running on parallel machines typically require consistently high levels of performance to adequately leverage the massive amounts of available computing power. Performance analysts have usually quantified network performance using traditional summary statistics that assume the observational data is sampled from a normal distribution. In our examinations of network performance, we have found this method of analysis often provides too little data to under- stand anomalous network performance. Our tool, Confidence, instead uses an empirically derived probability distribution to characterize network performance. In this paper we describe several instances where the Confidence toolkit allowed us to understand and diagnose network performance anomalies that we could not adequately explore with the simple summary statis- tics provided by traditional measurement tools. In particular, we examine a multi-modal performance scenario encountered with an Infiniband interconnection network and we explore the performance repeatability on the custom Cray SeaStar2 interconnection network after a set of software and driver updates.

Observations and a linear model of water level in an interconnected inlet-bay system

Science.gov (United States)

Aretxabaleta, Alfredo; Ganju, Neil K.; Butman, Bradford; Signell, Richard

2017-01-01

A system of barrier islands and back-barrier bays occurs along southern Long Island, New York, and in many coastal areas worldwide. Characterizing the bay physical response to water level fluctuations is needed to understand flooding during extreme events and evaluate their relation to geomorphological changes. Offshore sea level is one of the main drivers of water level fluctuations in semienclosed back-barrier bays. We analyzed observed water levels (October 2007 to November 2015) and developed analytical models to better understand bay water level along southern Long Island. An increase (∼0.02 m change in 0.17 m amplitude) in the dominant M2 tidal amplitude (containing the largest fraction of the variability) was observed in Great South Bay during mid-2014. The observed changes in both tidal amplitude and bay water level transfer from offshore were related to the dredging of nearby inlets and possibly the changing size of a breach across Fire Island caused by Hurricane Sandy (after December 2012). The bay response was independent of the magnitude of the fluctuations (e.g., storms) at a specific frequency. An analytical model that incorporates bay and inlet dimensions reproduced the observed transfer function in Great South Bay and surrounding areas. The model predicts the transfer function in Moriches and Shinnecock bays where long-term observations were not available. The model is a simplified tool to investigate changes in bay water level and enables the evaluation of future conditions and alternative geomorphological settings.

Additive Routes to Action Learning: Layering Experience Shapes Engagement of the Action Observation Network.

Science.gov (United States)

Kirsch, Louise P; Cross, Emily S

2015-12-01

The way in which we perceive others in action is biased by one's prior experience with an observed action. For example, we can have auditory, visual, or motor experience with actions we observe others perform. How action experience via 1, 2, or all 3 of these modalities shapes action perception remains unclear. Here, we combine pre- and post-training functional magnetic resonance imaging measures with a dance training manipulation to address how building experience (from auditory to audiovisual to audiovisual plus motor) with a complex action shapes subsequent action perception. Results indicate that layering experience across these 3 modalities activates a number of sensorimotor cortical regions associated with the action observation network (AON) in such a way that the more modalities through which one experiences an action, the greater the response is within these AON regions during action perception. Moreover, a correlation between left premotor activity and participants' scores for reproducing an action suggests that the better an observer can perform an observed action, the stronger the neural response is. The findings suggest that the number of modalities through which an observer experiences an action impacts AON activity additively, and that premotor cortical activity might serve as an index of embodiment during action observation. © The Author 2015. Published by Oxford University Press.

Exploring the networking behaviors of hospital organizations.

Science.gov (United States)

Di Vincenzo, Fausto

2018-05-08

Despite an extensive body of knowledge exists on network outcomes and on how hospital network structures may contribute to the creation of outcomes at different levels of analysis, less attention has been paid to understanding how and why hospital organizational networks evolve and change. The aim of this paper is to study the dynamics of networking behaviors of hospital organizations. Stochastic actor-based model for network dynamics was used to quantitatively examine data covering six-years of patient transfer relations among 35 hospital organizations. Specifically, the study investigated about determinants of patient transfer evolution modeling partner selection choice as a combination of multiple organizational attributes and endogenous network-based processes. The results indicate that having overlapping specialties and treating patients with the same case-mix decrease the likelihood of observing network ties between hospitals. Also, results revealed as geographical proximity and membership of the same LHA have a positive impact on the networking behavior of hospitals organizations, there is a propensity in the network to choose larger hospitals as partners, and to transfer patients between hospitals facing similar levels of operational uncertainty. Organizational attributes (overlapping specialties and case-mix), institutional factors (LHA), and geographical proximity matter in the formation and shaping of hospital networks over time. Managers can benefit from the use of these findings by clearly identifying the role and strategic positioning of their hospital with respect to the entire network. Social network analysis can yield novel information and also aid policy makers in the formation of interventions, encouraging alliances among providers as well as planning health system restructuring.

Ensemble Sensitivity Analysis of a Severe Downslope Windstorm in Complex Terrain: Implications for Forecast Predictability Scales and Targeted Observing Networks

Science.gov (United States)

2013-09-01

observations, linear regression finds the straight line that explains the linear relationship of the sample. This line is given by the equation y = mx + b...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING NETWORKS

Dynamic Sleep Scheduling on Air Pollution Levels Monitoring with Wireless Sensor Network

OpenAIRE

Gezaq Abror; Rusminto Tjatur Widodo; M. Udin Harun Al Rasyid

2018-01-01

Wireless Sensor Network (WSN) can be applied for Air Pollution Level Monitoring System that have been determined by the Environmental Impact Management Agency which is  PM10, SO2, O3, NO2 and CO. In WSN, node system is constrained to a limited power supply, so that the node system has a lifetime. To doing lifetime maximization, power management scheme is required and sensor nodes should use energy efficiently. This paper proposes dynamic sleep scheduling using Time Category-Fuzzy Logic (Time-...

Estimation of Missing Observations in Two-Level Split-Plot Designs

DEFF Research Database (Denmark)

Almimi, Ashraf A.; Kulahci, Murat; Montgomery, Douglas C.

2008-01-01

Inserting estimates for the missing observations from split-plot designs restores their balanced or orthogonal structure and alleviates the difficulties in the statistical analysis. In this article, we extend a method due to Draper and Stoneman to estimate the missing observations from unreplicated...... two-level factorial and fractional factorial split-plot (FSP and FFSP) designs. The missing observations, which can either be from the same whole plot, from different whole plots, or comprise entire whole plots, are estimated by equating to zero a number of specific contrast columns equal...... to the number of the missing observations. These estimates are inserted into the design table and the estimates for the remaining effects (or alias chains of effects as the case with FFSP designs) are plotted on two half-normal plots: one for the whole-plot effects and the other for the subplot effects...

Tides and lake-level variations in the great Patagonian lakes: Observations, modelling and geophysical implications.

Science.gov (United States)

Marderwald, Eric; Richter, Andreas; Horwath, Martin; Hormaechea, Jose Luis; Groh, Andreas

2016-04-01

In Patagonia, the glacial-isostatic adjustment (GIA) to past ice-mass changes (Ivins & James 2004; Klemann et al. 2007) is of particular interest in the context of the determination of the complex regional rheology related to plate subduction in a triple-junction constellation. To further complicate the situation, GIA is overlaid with load deformation not only due to present ice mass changes but also due to water-level changes in the lakes surrounding the icefields and the ocean surrounding Patagonia. These elastic deformations affect the determination of glacial-isostatic uplift rates from GPS observations (Dietrich et al. 2010; Lange et al. 2014). Observations of lake tides and their comparison with the theoretical tidal signal have been used previously to validate predictions of ocean tidal loading and have revealed regional deviations from conventional global elastic earth models (Richter et al. 2009). In this work we investigate the tides and lake-level variations in Lago Argentino, Lago Viedma, Lago San Martín/O'Higgins and Lago Buenos Aires/General Carrera. This allows us to test, among other things, the validity of tidal loading models. We present pressure tide-gauge records from two sites in Lago Argentino extending over 2.5 years (Richter et al. 2015). These observations are complemented by lake-level records provided by the Argentine National Hydrometeorological Network. Based on these lake-level time series the principal processes affecting the lake level are identified and quantified. Lake-level changes reflecting variations in lake volume are dominated by a seasonal cycle exceeding 1 m in amplitude. Lake-volume changes occur in addition with a daily period in response to melt water influx from surrounding glaciers. In Lago Argentino sporadic lake-volume jumps are caused by bursting of the ice dam of Perito Moreno glacier. Water movements in these lakes are dominated by surface seiches reaching 20 cm in amplitude. A harmonic tidal analysis of the lake-level

How Networks of Informal Trails Cause Landscape Level Damage to Vegetation.

Science.gov (United States)

Barros, Agustina; Marina Pickering, Catherine

2017-07-01

When visitors are not constrained to remain on formal trails, informal trail networks can develop and damage plant communities in protected areas. These networks can form in areas with low growing vegetation, where formal trails are limited, where there is limited regulation and where vegetation is slow to recover once disturbed. To demonstrate the extent of impacts from unregulated recreational use, we assessed damage to alpine vegetation by hikers and pack animals in the highest protected area in the southern Hemisphere: Aconcagua Park, in the Andes. Within the 237 ha area surveyed in the Horcones Valley, over 19 km of trails were found, nearly all of which (94%) were informal. This network of trails resulted in the direct loss of 11.5 ha of vegetation and extensive fragmentation of alpine meadows (21 fragments) and steppe vegetation (68 fragments). When levels of disturbance off these trails were quantified using rapid visual assessments, 81% of 102 randomly located plots showed evidence of disturbance, with the severity of disturbance greatest close to trails. As a result, vegetation in 90% of the Valley has been damaged by visitor use, nearly all of it from unregulated use. These results highlight the extent to which informal trails and trampling off-trail can cause landscape damage to areas of high conservation value, and hence the importance of better regulation of visitor use. The methodology used for off-trail impact assessment can be easily applied or adapted for other popular protected areas where trampling off-trail is also an issue.

An Aerosol Extinction-to-Backscatter Ratio Database Derived from the NASA Micro-Pulse Lidar Network: Applications for Space-based Lidar Observations

Science.gov (United States)

Welton, Ellsworth J.; Campbell, James R.; Spinhime, James D.; Berkoff, Timothy A.; Holben, Brent; Tsay, Si-Chee; Bucholtz, Anthony

2004-01-01

Backscatter lidar signals are a function of both backscatter and extinction. Hence, these lidar observations alone cannot separate the two quantities. The aerosol extinction-to-backscatter ratio, S, is the key parameter required to accurately retrieve extinction and optical depth from backscatter lidar observations of aerosol layers. S is commonly defined as 4*pi divided by the product of the single scatter albedo and the phase function at 180-degree scattering angle. Values of S for different aerosol types are not well known, and are even more difficult to determine when aerosols become mixed. Here we present a new lidar-sunphotometer S database derived from Observations of the NASA Micro-Pulse Lidar Network (MPLNET). MPLNET is a growing worldwide network of eye-safe backscatter lidars co-located with sunphotometers in the NASA Aerosol Robotic Network (AERONET). Values of S for different aerosol species and geographic regions will be presented. A framework for constructing an S look-up table will be shown. Look-up tables of S are needed to calculate aerosol extinction and optical depth from space-based lidar observations in the absence of co-located AOD data. Applications for using the new S look-up table to reprocess aerosol products from NASA's Geoscience Laser Altimeter System (GLAS) will be discussed.

Variations in the microseismic noise level observed at the Bucovina Seismic Array (BURAR)

International Nuclear Information System (INIS)

Ghica, Daniela; Radulian, Mircea; Popa, Mihaela

2005-01-01

The microseismic noise level analysis for a seismic array is an essential step to accurately process the data recorded by the system. Basically, the observed background noise is a complex combination of natural and cultural sources as local geology, specific area activity (roads traffic, agricultural and industrial activities) or weather conditions.The understanding of the BURAR site noise characteristics is important for the array specific techniques (beamforming, f-k analysis), to apply the correct bandpass filtering, in order to obtain noise suppression and conservation of the 'true' seismic signal. The array monitoring potential of very small earthquakes and explosions will be enhanced, based on the best signal-to-noise ratio.The noise study at BURAR was carried out over one-year period, considering the noise power spectra in a 0.1 to 10 Hz frequency interval, for every 24 hours: 5 minutes during day and 5 minutes during night. Only short-period vertical sensors were considered. Systematic variations in the microseismic noise level at the BURAR site were observed:- diurnal: a decreasing of about 40% in night noise level at 1 Hz frequency; at 6 Hz frequency, the decreasing could reach 80-90% for 'non-winter' months (May to October); - seasonal: during the winter time, a lower noise level is observed, due to the restraining of the local specific activity (especially agriculture and farming) and of the road traffic. To summarize the level of microseismic noise observed at BURAR for one-year observations, a model curve for array noise level has been estimated, including upper and lower bounds of noise power density together with average spectrum. The BURAR noise model will be useful in the process of local site conditions estimation, by eliminating the noise contribution from the array recording. Also, the detection processing, phase identification and events location procedures will be significantly improved. (authors)

Seismic Observations in the Taipei Metropolitan Area Using the Downhole Network

Directory of Open Access Journals (Sweden)

Win-Gee Huang

2010-01-01

Full Text Available Underlain by soft soils, the Taipei Metropolitan Area (TMA experienced major damage due to ground-motion amplification during the Hualien earthquake of 1986, the Chi-Chi earthquake of 1999, the Hualien earthquake of 2002 and the Taitung earthquake of 2003. To study how a local site can substantially change the characteristics of seismic waves as they pass through soft deposits below the free surface, two complementary downhole seismic arrays have been operated in the TMA, since 1991 and 2008. The accelerometer downhole array is composed of eight boreholes at depths in excess of 300 meters. The downhole array velocity sensor collocated with accelerometer composed of four boreholes at depths up to 90 meters. The integrated seismic network monitors potential earthquakes originating from faults in and around the TMA and provides wide-dynamic range measurement of data ranging in amplitude from seismic background noise levels to damage levels as a result of shaking. The data sets can be used to address on the response of soft-soil deposits to ground motions. One of the major considerations is the nonlinear response of soft soil deposits at different levels of excitation. The collocated acceloerometer and velocity sensors at boreholes give the necessary data for studies of non-linearity to be acquired. Such measurements in anticipation of future large, damaging earthquakes will be of special importance for the mitigation of earthquake losses.

Sensor data security level estimation scheme for wireless sensor networks.

Science.gov (United States)

Ramos, Alex; Filho, Raimir Holanda

2015-01-19

Due to their increasing dissemination, wireless sensor networks (WSNs) have become the target of more and more sophisticated attacks, even capable of circumventing both attack detection and prevention mechanisms. This may cause WSN users, who totally trust these security mechanisms, to think that a sensor reading is secure, even when an adversary has corrupted it. For that reason, a scheme capable of estimating the security level (SL) that these mechanisms provide to sensor data is needed, so that users can be aware of the actual security state of this data and can make better decisions on its use. However, existing security estimation schemes proposed for WSNs fully ignore detection mechanisms and analyze solely the security provided by prevention mechanisms. In this context, this work presents the sensor data security estimator (SDSE), a new comprehensive security estimation scheme for WSNs. SDSE is designed for estimating the sensor data security level based on security metrics that analyze both attack prevention and detection mechanisms. In order to validate our proposed scheme, we have carried out extensive simulations that show the high accuracy of SDSE estimates.

Coupling of ground biosensor networks for water monitoring with satellite observations in assessing Leptospirosis

Science.gov (United States)

Skouloudis, A. N.; Rickerby, D. G.

2012-12-01

Leptospirosis became recently a major public-health problem that is closely related with the environment (Nature review Oct 2009, Vol 7, pp 736-747). This disease originates from zoonotic pathogens associated with asymptomatic rodent carriers. Unfortunately, it effects human populations via various direct and indirect routes. This disease can claim many victims with large outbreaks during natural disasters or floods occurring during seasonal conditions. The severity of the illness ranges from subclinical infection to a fulminating fatal disease. Improved water quality monitoring techniques based on biosensor, optical, micro-fluidic and information technologies are leading to radical changes in our ability to perceive and monitor the aquatic environment. Biosensors are capable of providing specific, high spatial resolution information and allow unattended operation that will be particularly useful for water borne related diseases. Current research on biosensors is leading to solutions to problems for several contaminants that were previously irresolvable due to their high degree of complexity. Networking of the sensors enables sensitive monitoring systems allowing real-time monitoring of pollutants and facilitates data transmission between the measurement points and central control stations for continuous surveillance and to provide an early warning capability. The application of intelligent biosensor networks for water quality monitoring and detection of localized sources of pollution are discussed together with the setting up of a methodology that utilizes images from satellite coupled with in-situ sensors for anticipating the zones of potential evolution of this disease and assessing the population at risk. Environmental and climatic conditions that are associated the outbreaks are described and the rational of combining earth observations coupled with advanced in-situ biosensors is explained. The implementation of sensor networks for data collection and exposure

A distributed monitoring system for photovoltaic arrays based on a two-level wireless sensor network

Science.gov (United States)

Su, F. P.; Chen, Z. C.; Zhou, H. F.; Wu, L. J.; Lin, P. J.; Cheng, S. Y.; Li, Y. F.

2017-11-01

In this paper, a distributed on-line monitoring system based on a two-level wireless sensor network (WSN) is proposed for real time status monitoring of photovoltaic (PV) arrays to support the fine management and maintenance of PV power plants. The system includes the sensing nodes installed on PV modules (PVM), sensing and routing nodes installed on combiner boxes of PV sub-arrays (PVA), a sink node and a data management centre (DMC) running on a host computer. The first level WSN is implemented by the low-cost wireless transceiver nRF24L01, and it is used to achieve single hop communication between the PVM nodes and their corresponding PVA nodes. The second level WSN is realized by the CC2530 based ZigBee network for multi-hop communication among PVA nodes and the sink node. The PVM nodes are used to monitor the PVM working voltage and backplane temperature, and they send the acquired data to their PVA node via the nRF24L01 based first level WSN. The PVA nodes are used to monitor the array voltage, PV string current and environment irradiance, and they send the acquired and received data to the DMC via the ZigBee based second level WSN. The DMC is designed using the MATLAB GUIDE and MySQL database. Laboratory experiment results show that the system can effectively acquire, display, store and manage the operating and environment parameters of PVA in real time.

Observation of high spin levels in Cs from Ba decay

Indian Academy of Sciences (India)

physics pp. 1157–1162. Observation of high spin levels in. 131. Cs from. 131. Ba decay. M SAINATH, DWARAKA RANI RAO*, K VENKATARAMANIAH and P C SOOD. Department of Physics, Sri Sathya Sai Institute of Higher Learning, Prasanthinilayam 515 134, India. £Permanent address: Department of Physics, ...

Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras.

Science.gov (United States)

Shakya, Holly B; Stafford, Derek; Hughes, D Alex; Keegan, Thomas; Negron, Rennie; Broome, Jai; McKnight, Mark; Nicoll, Liza; Nelson, Jennifer; Iriarte, Emma; Ordonez, Maria; Airoldi, Edo; Fowler, James H; Christakis, Nicholas A

2017-03-13

Despite global progress on many measures of child health, rates of neonatal mortality remain high in the developing world. Evidence suggests that substantial improvements can be achieved with simple, low-cost interventions within family and community settings, particularly those designed to change knowledge and behaviour at the community level. Using social network analysis to identify structurally influential community members and then targeting them for intervention shows promise for the implementation of sustainable community-wide behaviour change. We will use a detailed understanding of social network structure and function to identify novel ways of targeting influential individuals to foster cascades of behavioural change at a population level. Our work will involve experimental and observational analyses. We will map face-to-face social networks of 30 000 people in 176 villages in Western Honduras, and then conduct a randomised controlled trial of a friendship-based network-targeting algorithm with a set of well-established care interventions. We will also test whether the proportion of the population targeted affects the degree to which the intervention spreads throughout the network. We will test scalable methods of network targeting that would not, in the future, require the actual mapping of social networks but would still offer the prospect of rapidly identifying influential targets for public health interventions. The Yale IRB and the Honduran Ministry of Health approved all data collection procedures (Protocol number 1506016012) and all participants will provide informed consent before enrolment. We will publish our findings in peer-reviewed journals as well as engage non-governmental organisations and other actors through venues for exchanging practical methods for behavioural health interventions, such as global health conferences. We will also develop a 'toolkit' for practitioners to use in network-based intervention efforts, including public

Sea level variability in the Arctic Ocean observed by satellite altimetry

OpenAIRE

Prandi, P.; Ablain, M.; Cazenave, A.; Picot, N.

2012-01-01

We investigate sea level variability in the Arctic Ocean from observations. Variability estimates are derived both at the basin scale and on smaller local spatial scales. The periods of the signals studied vary from high frequency (intra-annual) to long term trends. We also investigate the mechanisms responsible for the observed variability. Different data types are used, the main one being a recent reprocessing of satellite altimetry data...

Systems-level organization of non-alcoholic fatty liver disease progression network

Directory of Open Access Journals (Sweden)

K. Shubham

2017-10-01

Full Text Available Non-Alcoholic Fatty Liver Disease (NAFLD is a hepatic metabolic disorder that is commonly associated with sedentary lifestyle and high fat diets. NAFLD is prevalent in individuals with obesity, insulin resistance and Type 2 Diabetes (T2D. The clinical spectrum of NAFLD ranges from simple steatosis to Non-Alcoholic Steatohepatitis (NASH with fibrosis, which can progress to cirrhosis and hepatocellular carcinoma.The pathogenesis of NAFLD is complex, involving crosstalk between multiple organs, cell-types, and environmental and genetic factors. Dysfunction of White Adipose Tissue (WAT plays a central role in the development of NAFLD and other metabolic disorders. WAT is an active endocrine organ that regulates whole-body energy homeostasis, lipid metabolism, insulin sensitivity and food intake by secreting biologically active molecules (lipokines, adipokines and cytokines. WAT dynamically reacts to nutrient excess or deprivation by remodelling the number (called hyperplasia and/or size (called hypertrophy of adipocytes to store fat or supply nutrients to other tissues by lipolysis, respectively. Adipose tissue remodelling is also accompanied by changes in the composition or function of stromal vascular cells and ECM. The major objective of our study was to identify and characterize the metabolic and signaling modules associated with the progression of NAFLD in the VAT. We performed Weighted Gene Co-expression Network Analysis (WGCNA to organize microarray data obtained from the VAT of patients at different stages of NAFLD into functional modules. In order to obtain insights into the metabolism and its regulation at the genome scale, a co-expression network of metabolic genes in the Human Metabolic Network (HMR2 was constructed and compared with the co-expression network constructed based on all the varying genes. We also used the prior network information on adipocyte metabolism (GEM to verify and extract reporter metabolites. Our analysis revealed

Self-efficacy and social networks after treatment for alcohol or drug dependence and major depression: disentangling person and time-level effects.

Science.gov (United States)

Worley, Matthew J; Trim, Ryan S; Tate, Susan R; Roesch, Scott C; Myers, Mark G; Brown, Sandra A

2014-12-01

Proximal personal and environmental factors typically predict outcomes of treatment for alcohol or drug dependence (AODD), but longitudinal treatment studies have rarely examined these factors in adults with co-occurring psychiatric disorders. In adults with AODD and major depression, the aims of this study were to: (a) disaggregate person-and time-level components of network substance use and self-efficacy, (b) examine their prospective effects on posttreatment alcohol/drug use, and (c) examine whether residential environment moderated relations between these proximal factors and substance use outcomes. Veterans (N = 201) enrolled in a trial of group psychotherapy for AODD and independent MDD completed assessments every 3 months during 1 year of posttreatment follow-up. Outcome variables were percent days drinking (PDD) and using drugs (PDDRG). Proximal variables included abstinence self-efficacy and social network drinking and drug use. Self-efficacy and network substance use at the person-level prospectively predicted PDD (ps effects of social networks predicted future PDD (ps social network effects (ps network and posttreatment drinking and drug use. Both individual differences and time-specific fluctuations in proximal targets of psychosocial interventions are related to posttreatment substance use in adults with co-occurring AODD and MDD. More structured environmental settings appear to alleviate risk associated with social network substance use, and may be especially advised for those who have greater difficulty altering social networks during outpatient treatment.

Improve observation-based ground-level ozone spatial distribution by compositing satellite and surface observations: A simulation experiment

Science.gov (United States)

Zhang, Yuzhong; Wang, Yuhang; Crawford, James; Cheng, Ye; Li, Jianfeng

2018-05-01

Obtaining the full spatial coverage of daily surface ozone fields is challenging because of the sparsity of the surface monitoring network and the difficulty in direct satellite retrievals of surface ozone. We propose an indirect satellite retrieval framework to utilize the information from satellite-measured column densities of tropospheric NO2 and CH2O, which are sensitive to the lower troposphere, to derive surface ozone fields. The method is applicable to upcoming geostationary satellites with high-quality NO2 and CH2O measurements. To prove the concept, we conduct a simulation experiment using a 3-D chemical transport model for July 2011 over the eastern US. The results show that a second order regression using both NO2 and CH2O column densities can be an effective predictor for daily maximum 8-h average ozone. Furthermore, this indirect retrieval approach is shown to be complementary to spatial interpolation of surface observations, especially in regions where the surface sites are sparse. Combining column observations of NO2 and CH2O with surface site measurements leads to an improved representation of surface ozone over simple kriging, increasing the R2 value from 0.53 to 0.64 at a surface site distance of 252 km. The improvements are even more significant with larger surface site distances. The simulation experiment suggests that the indirect satellite retrieval technique can potentially be a useful tool to derive the full spatial coverage of daily surface ozone fields if satellite observation uncertainty is moderate.

The Worldwide Interplanetary Scintillation (IPS) Stations (WIPSS) Network October 2016 Observing Campaign: Initial WIPSS Data Analyses

Science.gov (United States)

Bisi, M. M.; Fallows, R. A.; Jackson, B. V.; Tokumaru, M.; Gonzalez-Esparza, A.; Morgan, J.; Chashei, I. V.; Mejia-Ambriz, J.; Tyul'bashev, S. A.; Manoharan, P. K.; De la Luz, V.; Aguilar-Rodriguez, E.; Yu, H. S.; Barnes, D.; Chang, O.; Odstrcil, D.; Fujiki, K.; Shishov, V.

2017-12-01

Interplanetary Scintillation (IPS) allows for the determination of velocity and a proxy for plasma density to be made throughout the corona and inner heliosphere. Where sufficient observations are undertaken, the results can be used as input to the University of California, San Diego (UCSD) three-dimensional (3-D) time-dependent tomography suite to allow for the full 3-D reconstruction of both velocity and density throughout the inner heliosphere. By combining IPS results from multiple observing locations around the planet, we can increase both the temporal and spatial coverage across the whole of the inner heliosphere and hence improve forecast capability. During October 2016, a unique opportunity arose whereby the European-based LOw Frequency ARray (LOFAR) radio telescope was used to make nearly four weeks of continuous observations of IPS as a heliospheric space-weather trial campaign. This was expanded into a global effort to include observations of IPS from the Murchison Widefield Array (MWA) in Western Australia and many more observations from various IPS-dedicated WIPSS Network systems. LOFAR is a next-generation low-frequency radio interferometer capable of observing in the radio frequency range 10-250 MHz, nominally with up to 80 MHz bandwidth at a time. MWA in Western Australia is capable of observing in the 80-300 MHz frequency range nominally using up to 32 MHz of bandwidth. IPS data from LOFAR, ISEE, the MEXican Array Radio Telescope (MEXART), and, where possible, other WIPSS Network systems (such as LPI-BSA and Ooty), will be used in this study and we will present some initial findings for these data sets. We also make a first attempt at the 3-D reconstruction of multiple pertinent WIPSS results in the UCSD tomography. We will also try to highlight some of the potential future tools that make LOFAR a very unique system to be able to test and validate a whole plethora of IPS analysis methods with the same set of IPS data.

Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant Face Verification

OpenAIRE

Li, Yi; Song, Lingxiao; Wu, Xiang; He, Ran; Tan, Tieniu

2017-01-01

Makeup is widely used to improve facial attractiveness and is well accepted by the public. However, different makeup styles will result in significant facial appearance changes. It remains a challenging problem to match makeup and non-makeup face images. This paper proposes a learning from generation approach for makeup-invariant face verification by introducing a bi-level adversarial network (BLAN). To alleviate the negative effects from makeup, we first generate non-makeup images from makeu...

Non-fragile observer design for discrete-time genetic regulatory networks with randomly occurring uncertainties

International Nuclear Information System (INIS)

Banu, L Jarina; Balasubramaniam, P

2015-01-01

This paper investigates the problem of non-fragile observer design for a class of discrete-time genetic regulatory networks (DGRNs) with time-varying delays and randomly occurring uncertainties. A non-fragile observer is designed, for estimating the true concentration of mRNAs and proteins from available measurement outputs. One important feature of the results obtained that are reported here is that the parameter uncertainties are assumed to be random and their probabilities of occurrence are known a priori. On the basis of the Lyapunov–Krasovskii functional approach and using a convex combination technique, a delay-dependent estimation criterion is established for DGRNs in terms of linear matrix inequalities (LMIs) that can be efficiently solved using any available LMI solver. Finally numerical examples are provided to substantiate the theoretical results. (paper)

Using Aoristic Analysis to Link Remote and Ground-Level Phenological Observations

Science.gov (United States)

Henebry, G. M.

2013-12-01

Phenology is about observing events in time and space. With the advent of publically accessible geospatial datastreams and easy to use mapping software, specifying where an event occurs is much less of a challenge than it was just two decades ago. In contrast, specifying when an event occurs remains a nontrivial function of a population of organismal responses, sampling interval, compositing period, and reporting precision. I explore how aoristic analysis can be used to analyzing spatiotemporal events for which the location is known to acceptable levels of precision but for which temporal coordinates are poorly specified or only partially bounded. Aoristic analysis was developed in the late 1990s in the field of quantitative criminology to leverage temporally imprecise geospatial data of crime reports. Here I demonstrate how aoristic analysis can be used to link remotely sensed observations of land surface phenology to ground-level observations of organismal phenophase transitions. Explicit representation of the windows of temporal uncertainty with aoristic weights enables cross-validation exercises and forecasting efforts to avoid false precision.

Automatic classification of DMSA scans using an artificial neural network

Science.gov (United States)

Wright, J. W.; Duguid, R.; Mckiddie, F.; Staff, R. T.

2014-04-01

DMSA imaging is carried out in nuclear medicine to assess the level of functional renal tissue in patients. This study investigated the use of an artificial neural network to perform diagnostic classification of these scans. Using the radiological report as the gold standard, the network was trained to classify DMSA scans as positive or negative for defects using a representative sample of 257 previously reported images. The trained network was then independently tested using a further 193 scans and achieved a binary classification accuracy of 95.9%. The performance of the network was compared with three qualified expert observers who were asked to grade each scan in the 193 image testing set on a six point defect scale, from ‘definitely normal’ to ‘definitely abnormal’. A receiver operating characteristic analysis comparison between a consensus operator, generated from the scores of the three expert observers, and the network revealed a statistically significant increase (α quality assurance assistant in clinical practice.

Evaluating the UK's carbon budget using a dense network of tall-tower observations

Science.gov (United States)

White, E.; Rigby, M. L.; Manning, A.; Lunt, M. F.; Ganesan, A.; O'Doherty, S.; Stavert, A.; Stanley, K. M.; Williams, M. D.; Smallman, T. L.; Comyn-Platt, E.; Levy, P. E.

2017-12-01

The UK has committed to reducing greenhouse gas (GHG) emissions to 80% of 1990 levels by 2050. Evaluating the UK's GHG emissions, and in particular those of carbon dioxide, is imperative to the UK's ability to track progress towards these goals. Making top-down estimates of regional carbon dioxide emissions is challenging due to the rapid temporal variability in the biogenic flux, and the co-location of anthropogenic and biogenic sources and sinks. We present a hierarchical Bayesian inverse modelling framework, which is able to estimate a yearly total (anthropogenic and biogenic) carbon dioxide budget for the UK. Using observations from a high-density GHG monitoring network, combined with high temporal resolution prior information and a Lagrangian atmospheric transport model (NAME, developed by the UK Met Office), we derive a net positive flux for the UK of 0.39 Pg/yr in 2014. We will compare the outcome of inversions that used prior information from two different biosphere models, CARDAMOM and JULES. This comparison helps to understand more about the biogenic processes contributing to the UK's carbon dioxide budget, limitations with different modelling approaches and the sensitivity of the inversion framework to the choice of prior. A better understanding of how the biogenic flux changes throughout the year can, in turn, help to improve the UK's anthropogenic carbon dioxide inventory by identifying times in the year when the anthropogenic signal may be possible to detect.

The European network of Biosafety-Level-4 laboratories: enhancing European preparedness for new health threats.

Science.gov (United States)

Nisii, C; Castilletti, C; Di Caro, A; Capobianchi, M R; Brown, D; Lloyd, G; Gunther, S; Lundkvist, A; Pletschette, M; Ippolito, G

2009-08-01

Emerging and re-emerging infections and possible bioterrorism acts will continue to challenge both the medical community and civilian populations worldwide, urging health authorities to respond rapidly and effectively. Established in 2005, the European Community (EC)-funded European Network of Biosafety-Level-4 laboratories (Euronet-P4), which brings together the laboratories in Porton Down, London, Hamburg, Marburg, Solna, Lyon and Rome, seeks to increase international collaboration in the areas of high containment laboratory biosafety and viral diagnostic capability, to strengthen Europe's capacity to respond to an infectious disease emergency, and to offer assistance to countries not equipped with such costly facilities. Network partners have agreed on a common strategy to fill the gaps identified in the field of risk group-4 agents' laboratory diagnosis, namely the lack of standardization and of reference samples. The network has received a further 3-year funding, to offer assistance to external laboratories, and to start the planning of field activities.

Fragility in dynamic networks: application to neural networks in the epileptic cortex.

Science.gov (United States)

Sritharan, Duluxan; Sarma, Sridevi V

2014-10-01

Epilepsy is a network phenomenon characterized by atypical activity at the neuronal and population levels during seizures, including tonic spiking, increased heterogeneity in spiking rates, and synchronization. The etiology of epilepsy is unclear, but a common theme among proposed mechanisms is that structural connectivity between neurons is altered. It is hypothesized that epilepsy arises not from random changes in connectivity, but from specific structural changes to the most fragile nodes or neurons in the network. In this letter, the minimum energy perturbation on functional connectivity required to destabilize linear networks is derived. Perturbation results are then applied to a probabilistic nonlinear neural network model that operates at a stable fixed point. That is, if a small stimulus is applied to the network, the activation probabilities of each neuron respond transiently but eventually recover to their baseline values. When the perturbed network is destabilized, the activation probabilities shift to larger or smaller values or oscillate when a small stimulus is applied. Finally, the structural modifications to the neural network that achieve the functional perturbation are derived. Simulations of the unperturbed and perturbed networks qualitatively reflect neuronal activity observed in epilepsy patients, suggesting that the changes in network dynamics due to destabilizing perturbations, including the emergence of an unstable manifold or a stable limit cycle, may be indicative of neuronal or population dynamics during seizure. That is, the epileptic cortex is always on the brink of instability and minute changes in the synaptic weights associated with the most fragile node can suddenly destabilize the network to cause seizures. Finally, the theory developed here and its interpretation of epileptic networks enables the design of a straightforward feedback controller that first detects when the network has destabilized and then applies linear state

Improved control of distributed parameter systems using wireless sensor and actuator networks: An observer-based method

International Nuclear Information System (INIS)

Jiang Zheng-Xian; Cui Bao-Tong; Lou Xu-Yang; Zhuang Bo

2017-01-01

In this paper, the control problem of distributed parameter systems is investigated by using wireless sensor and actuator networks with the observer-based method. Firstly, a centralized observer which makes use of the measurement information provided by the fixed sensors is designed to estimate the distributed parameter systems. The mobile agents, each of which is affixed with a controller and an actuator, can provide the observer-based control for the target systems. By using Lyapunov stability arguments, the stability for the estimation error system and distributed parameter control system is proved, meanwhile a guidance scheme for each mobile actuator is provided to improve the control performance. A numerical example is finally used to demonstrate the effectiveness and the advantages of the proposed approaches. (paper)

Impact of Multimedia and Network Services on an Introductory Level Course

Science.gov (United States)

Russ, John C.

1996-01-01

We will demonstrate and describe the impact of our use of multimedia and network connectivity on a sophomore-level introductory course in materials science. This class services all engineering students, resulting in large (more than 150) class sections with no hands-on laboratory. In 1990 we began to develop computer graphics that might substitute for some laboratory or real-world experiences, and demonstrate relationships hard to show with static textbook images or chalkboard drawings. We created a comprehensive series of modules that cover the entire course content. Called VIMS (Visualizations in Materials Science), these are available in the form of a CD-ROM and also via the internet.

The Centralization and Decentralization of Telemedicine Networks in Korea and Japan

Directory of Open Access Journals (Sweden)

Soo-kyung Park

2013-06-01

Full Text Available This study scrutinizes telemedicine networks with regard to regionalization and the propensities and determinants of core telemedicine users (doctors and patients by employing two case areas, Choongbook in Korea and Kagawa in Japan. According to the results, telemedicine networks in Choongbook are dominated by an inter-regional level (in particular, a national level, and most of the telemedicine networks are observed between clinical sites in Choongbook and tertiary care centers in Kyunggi. In contrast, telemedicine networks in Kagawa are dispersed within the diagnostic boundary of Kagawa at a regional level. Interviews with crucial decision-makers revealed the reasons why many patients enjoy health care via telemedicine at an inter-regional level, which include psychological considerations regarding quality and level of health care services, personal stakes in telemedicine service sites, acceptability and credibility of good tertiary care centers, and easy access to and use of medical institutions. In Kagawa, both the existing health care system and the telemedicine system support the maintenance of stable regional health care within Kagawa. Importantly, human relationships based on the regional health care system contribute to creating telemedicine networks within the original purpose of the telemedicine system regarding regionalization. Also, telemedicine’s technological value, convenience, and utility are associated with the regionalization of telemedicine networks within one diagnostic area.

Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention.

Science.gov (United States)

Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J; Wilson, Tony W

2017-10-01

The dynamic allocation of neural resources to discrete features within a visual scene enables us to react quickly and accurately to salient environmental circumstances. A network of bilateral cortical regions is known to subserve such visuospatial attention functions; however the oscillatory and functional connectivity dynamics of information coding within this network are not fully understood. Particularly, the coding of information within prototypical attention-network hubs and the subsecond functional connections formed between these hubs have not been adequately characterized. Herein, we use the precise temporal resolution of magnetoencephalography (MEG) to define spectrally specific functional nodes and connections that underlie the deployment of attention in visual space. Twenty-three healthy young adults completed a visuospatial discrimination task designed to elicit multispectral activity in visual cortex during MEG, and the resulting data were preprocessed and reconstructed in the time-frequency domain. Oscillatory responses were projected to the cortical surface using a beamformer, and time series were extracted from peak voxels to examine their temporal evolution. Dynamic functional connectivity was then computed between nodes within each frequency band of interest. We find that visual attention network nodes are defined functionally by oscillatory frequency, that the allocation of attention to the visual space dynamically modulates functional connectivity between these regions on a millisecond timescale, and that these modulations significantly correlate with performance on a spatial discrimination task. We conclude that functional hubs underlying visuospatial attention are segregated not only anatomically but also by oscillatory frequency, and importantly that these oscillatory signatures promote dynamic communication between these hubs. Hum Brain Mapp 38:5128-5140, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Global TIE Observatories: Real Time Observational Astronomy Through a Robotic Telescope Network

Science.gov (United States)

Clark, G.; Mayo, L. A.

2001-12-01

Astronomy in grades K-12 is traditionally taught (if at all) using textbooks and a few simple hands-on activities. Teachers are generally not trained in observational astronomy techniques and are unfamiliar with the most basic astronomical concepts. In addition, most students, by High School graduation, will never have even looked through the eyepiece of a telescope. The problem becomes even more challenging in inner cities, remote rural areas and low socioeconomic communities where educational emphasis on topics in astronomy as well as access to observing facilities is limited or non existent. Access to most optical telescope facilities is limited to monthly observing nights that cater to a small percentage of the general public living near the observatory. Even here, the observing experience is a one-time event detached from the process of scientific enquiry and sustained educational application. Additionally, a number of large, "research grade" observatory facilities are largely unused, partially due to the slow creep of light pollution around the facilities as well as the development of newer, more capable telescopes. Though cutting edge science is often no longer possible at these sights, real research opportunities in astronomy remain numerous for these facilities as educational tools. The possibility now exists to establish a network of research grade telescopes, no longer useful to the professional astronomical community, that can be made accessible through classrooms, after school, and community based programs all across the country through existing IT technologies and applications. These telescopes could provide unparalleled research and educational opportunities for a broad spectrum of students and turns underutilized observatory facilities into valuable, state-of-the-art teaching centers. The NASA sponsored Telescopes In Education project has been wildly successful in engaging the K-12 education community in real-time, hands-on, interactive astronomy

Solution Algorithm for a New Bi-Level Discrete Network Design Problem

Directory of Open Access Journals (Sweden)

Qun Chen

2013-12-01

Full Text Available A new discrete network design problem (DNDP was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.

Network and external perturbation induce burst synchronisation in cat cerebral cortex

Science.gov (United States)

Lameu, Ewandson L.; Borges, Fernando S.; Borges, Rafael R.; Batista, Antonio M.; Baptista, Murilo S.; Viana, Ricardo L.

2016-05-01

The brain of mammals are divided into different cortical areas that are anatomically connected forming larger networks which perform cognitive tasks. The cat cerebral cortex is composed of 65 areas organised into the visual, auditory, somatosensory-motor and frontolimbic cognitive regions. We have built a network of networks, in which networks are connected among themselves according to the connections observed in the cat cortical areas aiming to study how inputs drive the synchronous behaviour in this cat brain-like network. We show that without external perturbations it is possible to observe high level of bursting synchronisation between neurons within almost all areas, except for the auditory area. Bursting synchronisation appears between neurons in the auditory region when an external perturbation is applied in another cognitive area. This is a clear evidence that burst synchronisation and collective behaviour in the brain might be a process mediated by other brain areas under stimulation.

The lateralization of intrinsic networks in the aging brain implicates the effects of cognitive training

Directory of Open Access Journals (Sweden)

Cheng eLuo

2016-03-01

Full Text Available Lateralization of function is an important organization of human brain. The distribution of intrinsic networks in the resting brain is strongly related to the cognitive function, gender and age. In this study, the longitudinal design with one year duration was used to evaluate the cognitive training effects on the lateralization of intrinsic networks among healthy older adults. The subjects were divided into two groups randomly: one with multi-domain cognitive training in three month, the other as a wait-list control group. Resting state fMRI data were acquired before training and one year after training. We analyzed the functional lateralization in ten common resting state fMRI networks. We observed statically significant training effects on the lateralization of two important RSNs related to high-level cognition: right- and left- frontoparietal networks. Especially, the lateralization of left-frontoparietal network were retained well in training group, but decreased in control group. The increased lateralization with aging was observed on the cerebellum network, in which the lateralization was significantly increased in control group although the same change tendency was observed in training group. These findings indicate that the lateralization of the high-level cognitive intrinsic networks is sensitive to the multi-domain cognitive training. This study provides a neuroimaging evidence to support that the cognitive training should have advantages to the cognitive decline in healthy older adults.

GIONET (GMES Initial Operations Network for Earth Observation Research Training)

Science.gov (United States)

Nicolas, V.; Balzter, H.

2013-12-01

GMES Initial Operations - Network for Earth Observation Research Training (GIONET) is a Marie Curie funded project that aims to establish the first of a kind European Centre of Excellence for Earth Observation Research Training. Copernicus (previously known as GMES (Global Monitoring for Environment and Security) is a joint undertaking of the European Space Agency and the European Commission. It develops fully operational Earth Observation monitoring services for a community of end users from the public and private sector. The first services that are considered fully operational are the land monitoring and emergency monitoring core services. In GIONET, 14 early stage researchers are being trained at PhD level in understanding the complex physical processes that determine how electromagnetic radiation interacts with the atmosphere and the land surface ultimately form the signal received by a satellite. In order to achieve this, the researchers are based in industry and universities across Europe, as well as receiving the best technical training and scientific education. The training programme through supervised research focuses on 14 research topics. Each topic is carried out by an Early Stage Researcher based in one of the partner organisations and is expected to lead to a PhD degree. The 14 topics are grouped in 5 research themes: Forest monitoring Land cover and change Coastal zone and freshwater monitoring Geohazards and emergency response Climate adaptation and emergency response The methods developed and used in GIONET are as diverse as its research topics. GIONET has already held two summer schools; one at Friedrich Schiller University in Jena (Germany), on 'New operational radar satellite applications: Introduction to SAR, Interferometry and Polarimetry for Land Surface Mapping'. The 2nd summer school took place last September at the University of Leicester (UK )on 'Remote sensing of land cover and forest in GMES'. The next Summer School in September 2013

Great Lakes Daily Ice Observations at NOAA Water Level Gauge Sites

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains daily visual ice observations taken yearly from 1 November to 30 April at NOAA/National Ocean Service water level gauge sites in the Great...

Open innovation in networks

DEFF Research Database (Denmark)

Hu, Yimei

and hierarchy can be analyzed from a network approach. Within a network perspective, there are different levels of network, and a firm may not always has the power to “manage” innovation networks due to different levels of power. Based on the strength of a firm’s power, its role may varies from manager...

Mobilization and Adaptation of a Rural Cradle-to-Career Network

Directory of Open Access Journals (Sweden)

Sarah J. Zuckerman

2016-10-01

Full Text Available This case study explored the development of a rural cradle-to-career network with a dual focus on the initial mobilization of network members and subsequent adaptations made to maintain mobilization, while meeting local needs. Data sources included interviews with network members, observations of meetings, and documentary evidence. Network-based social capital facilitated mobilization. Where networks were absent and where distrust and different values were evident, mobilization faltered. Three network adaptations were discovered: Special rural community organizing strategies, district-level action planning, and a theory of action focused on out-of-school factors. All three were attributable to the composition of mobilized stakeholders and this network’s rural social geography. These findings illuminate the importance of social geography in the development and advancement of rural cradle-to-career networks.

GPS network observation of traveling ionospheric disturbances following the Chelyabinsk meteorite blast

Directory of Open Access Journals (Sweden)

F. Ding

2016-11-01

Full Text Available We use the Global Positioning System (GPS network in northwest China and central Asia to monitor traveling ionospheric disturbances (TIDs, which were possibly excited by the large meteorite blast over Chelyabinsk, Russia, on 15 February 2013. Two TIDs were observed. The first TID was observed 13 min after the blast within a range of 270–600 km from the blast site. It propagated radially from the blast site with a mean velocity and period of 369 m s−1 and 12 min, respectively. The second TID was found in northwest China, 1.5 h after the time of the blast, at  ∼  2500–3100 km from the blast site. This latter TID propagated southeastward with a velocity and period of 410 m s−1 and 23 min, respectively. Severe dissipation of the perturbation total electronic content (TEC amplitude was observed. Any TIDs propagating in a global range was not found after the meteorite blast. Features of TIDs were compared with those excited by early nuclear explosion tests. It is inferred from our analysis that the energy release of the Chelyabinsk meteorite blast may not be large enough to excite such ionospheric disturbances in a global range as some nuclear explosions did.

Towards a system level understanding of non-model organisms sampled from the environment: a network biology approach.

Science.gov (United States)

Williams, Tim D; Turan, Nil; Diab, Amer M; Wu, Huifeng; Mackenzie, Carolynn; Bartie, Katie L; Hrydziuszko, Olga; Lyons, Brett P; Stentiford, Grant D; Herbert, John M; Abraham, Joseph K; Katsiadaki, Ioanna; Leaver, Michael J; Taggart, John B; George, Stephen G; Viant, Mark R; Chipman, Kevin J; Falciani, Francesco

2011-08-01

The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

Observation-Driven Estimation of the Spatial Variability of 20th Century Sea Level Rise

Science.gov (United States)

Hamlington, B. D.; Burgos, A.; Thompson, P. R.; Landerer, F. W.; Piecuch, C. G.; Adhikari, S.; Caron, L.; Reager, J. T.; Ivins, E. R.

2018-03-01

Over the past two decades, sea level measurements made by satellites have given clear indications of both global and regional sea level rise. Numerous studies have sought to leverage the modern satellite record and available historic sea level data provided by tide gauges to estimate past sea level rise, leading to several estimates for the 20th century trend in global mean sea level in the range between 1 and 2 mm/yr. On regional scales, few attempts have been made to estimate trends over the same time period. This is due largely to the inhomogeneity and quality of the tide gauge network through the 20th century, which render commonly used reconstruction techniques inadequate. Here, a new approach is adopted, integrating data from a select set of tide gauges with prior estimates of spatial structure based on historical sea level forcing information from the major contributing processes over the past century. The resulting map of 20th century regional sea level rise is optimized to agree with the tide gauge-measured trends, and provides an indication of the likely contributions of different sources to regional patterns. Of equal importance, this study demonstrates the sensitivities of this regional trend map to current knowledge and uncertainty of the contributing processes.

Development of Active External Network Topology Module for Floodlight SDN Controller

Directory of Open Access Journals (Sweden)

A. A. Noskov

2015-01-01

Full Text Available Traditional network architecture is inflexible and complicated. This observation has led to a paradigm shift towards software-defined networking (SDN, where network management level is separated from data forwarding level. This change was made possible by control plane transfer from the switching equipment to software modules that run on a dedicated server, called the controller (or network operating system, or network applications, that work with this controller. Methods of representation, storage and communication interfaces with network topology elements are the most important aspects of network operating systems available to SDN user because performance of some key controller modules is heavily dependent on internal representation of the network topology. Notably, firewall and routing modules are examples of such modules. This article describes the methods used for presentation and storage of network topologies, as well as interface to the corresponding Floodlight modules. An alternative algorithm has been suggested and developed for message exchange conveying network topology alterations between the controller and network applications. Proposed algorithm makes implementation of module alerting based on subscription to the relevant events. API for interaction between controller and network applications has been developed. This algorithm and API formed the base for Topology Tracker module capable to inform network applications about the changes that had occurred in the network topology and also stores compact representation of the network to speed up the interaction process.

Probabilistic diffusion tractography reveals improvement of structural network in musicians.

Directory of Open Access Journals (Sweden)

Jianfu Li

Full Text Available PURPOSE: Musicians experience a large amount of information transfer and integration of complex sensory, motor, and auditory processes when training and playing musical instruments. Therefore, musicians are a useful model in which to investigate neural adaptations in the brain. METHODS: Here, based on diffusion-weighted imaging, probabilistic tractography was used to determine the architecture of white matter anatomical networks in musicians and non-musicians. Furthermore, the features of the white matter networks were analyzed using graph theory. RESULTS: Small-world properties of the white matter network were observed in both groups. Compared with non-musicians, the musicians exhibited significantly increased connectivity strength in the left and right supplementary motor areas, the left calcarine fissure and surrounding cortex and the right caudate nucleus, as well as a significantly larger weighted clustering coefficient in the right olfactory cortex, the left medial superior frontal gyrus, the right gyrus rectus, the left lingual gyrus, the left supramarginal gyrus, and the right pallidum. Furthermore, there were differences in the node betweenness centrality in several regions. However, no significant differences in topological properties were observed at a global level. CONCLUSIONS: We illustrated preliminary findings to extend the network level understanding of white matter plasticity in musicians who have had long-term musical training. These structural, network-based findings may indicate that musicians have enhanced information transmission efficiencies in local white matter networks that are related to musical training.

Network science

CERN Document Server

Barabasi, Albert-Laszlo

2016-01-01

Networks are everywhere, from the Internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate and graduate level material. The mathematical formulas and derivations are included within Advanced Topics sections, enabling use at a range of levels. Extensive online resources, including films and software for network analysis, make this a multifaceted companion for anyone with an interest in network sci...

Bit Level Synchronized MAC Protocol for Multireader RFID Networks

Directory of Open Access Journals (Sweden)

Namboodiri Vinod

2010-01-01

Full Text Available The operation of multiple RFID readers in close proximity results in interference between the readers. This issue is termed the reader collision problem and cannot always be solved by assigning them to different frequency channels due to technical and regulatory limitations. The typical solution is to separate the operation of such readers across time. This sequential operation, however, results in a long delay to identify all tags. We present a bit level synchronized (BLSync MAC protocol for multi-reader RFID networks that allows multiple readers to operate simultaneously on the same frequency channel. The BLSync protocol solves the reader collision problem by allowing all readers to transmit the same query at the same time. We analyze the performance of using the BLSync protocol and demonstrate benefits of 40%–50% in terms of tag reading delay for most settings. The benefits of BLSync, first demonstrated through analysis, are then validated and quantified through simulations on realistic reader-tag layouts.

Efficiency effects of observed and unobserved heterogeneity: Evidence from Norwegian electricity distribution networks

International Nuclear Information System (INIS)

Growitsch, Christian; Jamasb, Tooraj; Wetzel, Heike

2012-01-01

Since the 1990s, efficiency and benchmarking analysis has increasingly been used in network utilities research and regulation. A recurrent concern is the effect of observable environmental factors that are beyond the influence of firms and unobserved factors that are not identifiable on measured cost and quality performance of firms. This paper analyses the effect of observed geographic and weather factors and unobserved heterogeneity on a set of 128 Norwegian electricity distribution utilities for the 2001–2004 period. We utilise data on 78 geographic and weather variables to identify real economic inefficiency while controlling for observed and unobserved heterogeneity. We use the Factor Analysis technique to reduce the number of environmental factors into few composite variables and to avoid the problem of multicollinearity. In order to identify firm-specific inefficiency, we then estimate a pooled version of the established stochastic frontier model of Aigner et al. (1977) and the recent true random effects model of Greene (2004; 2005a,b) without and with environmental variables. The results indicate that the observed environmental factors have a rather limited influence on the utilities' average efficiency and the efficiency rankings. Moreover, the difference between the average efficiency scores and the efficiency rankings among the pooled and the true random effects models imply that the type of SFA model used is highly influencing the efficiency estimates.

Sensor Data Security Level Estimation Scheme for Wireless Sensor Networks