WorldWideScience

Sample records for network field sampling

  1. 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

  2. Network and adaptive sampling

    CERN Document Server

    Chaudhuri, Arijit

    2014-01-01

    Combining the two statistical techniques of network sampling and adaptive sampling, this book illustrates the advantages of using them in tandem to effectively capture sparsely located elements in unknown pockets. It shows how network sampling is a reliable guide in capturing inaccessible entities through linked auxiliaries. The text also explores how adaptive sampling is strengthened in information content through subsidiary sampling with devices to mitigate unmanageable expanding sample sizes. Empirical data illustrates the applicability of both methods.

  3. On sampling social networking services

    OpenAIRE

    Wang, Baiyang

    2012-01-01

    This article aims at summarizing the existing methods for sampling social networking services and proposing a faster confidence interval for related sampling methods. It also includes comparisons of common network sampling techniques.

  4. Sampling of temporal networks: Methods and biases

    Science.gov (United States)

    Rocha, Luis E. C.; Masuda, Naoki; Holme, Petter

    2017-11-01

    Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.

  5. Quality-control design for surface-water sampling in the National Water-Quality Network

    Science.gov (United States)

    Riskin, Melissa L.; Reutter, David C.; Martin, Jeffrey D.; Mueller, David K.

    2018-04-10

    The data-quality objectives for samples collected at surface-water sites in the National Water-Quality Network include estimating the extent to which contamination, matrix effects, and measurement variability affect interpretation of environmental conditions. Quality-control samples provide insight into how well the samples collected at surface-water sites represent the true environmental conditions. Quality-control samples used in this program include field blanks, replicates, and field matrix spikes. This report describes the design for collection of these quality-control samples and the data management needed to properly identify these samples in the U.S. Geological Survey’s national database.

  6. High speed network sampling

    OpenAIRE

    Rindalsholt, Ole Arild

    2005-01-01

    Master i nettverks- og systemadministrasjon Classical Sampling methods play an important role in the current practice of Internet measurement. With today’s high speed networks, routers cannot manage to generate complete Netflow data for every packet. They have to perform restricted sampling. This thesis summarizes some of the most important sampling schemes and their applications before diving into an analysis on the effect of sampling Netflow records.

  7. An improved sampling method of complex network

    Science.gov (United States)

    Gao, Qi; Ding, Xintong; Pan, Feng; Li, Weixing

    2014-12-01

    Sampling subnet is an important topic of complex network research. Sampling methods influence the structure and characteristics of subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines the advantages of random sampling and snowball sampling is proposed in this paper. It has the ability to explore global information and discover the local structure at the same time. The experiments indicate that this novel sampling method could keep the similarity between sampling subnet and original network on degree distribution, connectivity rate and average shortest path. This method is applicable to the situation where the prior knowledge about degree distribution of original network is not sufficient.

  8. Note: Design and development of wireless controlled aerosol sampling network for large scale aerosol dispersion experiments

    International Nuclear Information System (INIS)

    Gopalakrishnan, V.; Subramanian, V.; Baskaran, R.; Venkatraman, B.

    2015-01-01

    Wireless based custom built aerosol sampling network is designed, developed, and implemented for environmental aerosol sampling. These aerosol sampling systems are used in field measurement campaign, in which sodium aerosol dispersion experiments have been conducted as a part of environmental impact studies related to sodium cooled fast reactor. The sampling network contains 40 aerosol sampling units and each contains custom built sampling head and the wireless control networking designed with Programmable System on Chip (PSoC™) and Xbee Pro RF modules. The base station control is designed using graphical programming language LabView. The sampling network is programmed to operate in a preset time and the running status of the samplers in the network is visualized from the base station. The system is developed in such a way that it can be used for any other environment sampling system deployed in wide area and uneven terrain where manual operation is difficult due to the requirement of simultaneous operation and status logging

  9. Note: Design and development of wireless controlled aerosol sampling network for large scale aerosol dispersion experiments

    Energy Technology Data Exchange (ETDEWEB)

    Gopalakrishnan, V.; Subramanian, V.; Baskaran, R.; Venkatraman, B. [Radiation Impact Assessment Section, Radiological Safety Division, Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102 (India)

    2015-07-15

    Wireless based custom built aerosol sampling network is designed, developed, and implemented for environmental aerosol sampling. These aerosol sampling systems are used in field measurement campaign, in which sodium aerosol dispersion experiments have been conducted as a part of environmental impact studies related to sodium cooled fast reactor. The sampling network contains 40 aerosol sampling units and each contains custom built sampling head and the wireless control networking designed with Programmable System on Chip (PSoC™) and Xbee Pro RF modules. The base station control is designed using graphical programming language LabView. The sampling network is programmed to operate in a preset time and the running status of the samplers in the network is visualized from the base station. The system is developed in such a way that it can be used for any other environment sampling system deployed in wide area and uneven terrain where manual operation is difficult due to the requirement of simultaneous operation and status logging.

  10. The African Field Epidemiology Network-Networking for effective field epidemiology capacity building and service delivery

    Science.gov (United States)

    Gitta, Sheba Nakacubo; Mukanga, David; Babirye, Rebecca; Dahlke, Melissa; Tshimanga, Mufuta; Nsubuga, Peter

    2011-01-01

    Networks are a catalyst for promoting common goals and objectives of their membership. Public Health networks in Africa are crucial, because of the severe resource limitations that nations face in dealing with priority public health problems. For a long time, networks have existed on the continent and globally, but many of these are disease-specific with a narrow scope. The African Field Epidemiology Network (AFENET) is a public health network established in 2005 as a non-profit networking alliance of Field Epidemiology and Laboratory Training Programs (FELTPs) and Field Epidemiology Training Programs (FETPs) in Africa. AFENET is dedicated to helping ministries of health in Africa build strong, effective and sustainable programs and capacity to improve public health systems by partnering with global public health experts. The Network's goal is to strengthen field epidemiology and public health laboratory capacity to contribute effectively to addressing epidemics and other major public health problems in Africa. AFENET currently networks 12 FELTPs and FETPs in sub-Saharan Africa with operations in 20 countries. AFENET has a unique tripartite working relationship with government technocrats from human health and animal sectors, academicians from partner universities, and development partners, presenting the Network with a distinct vantage point. Through the Network, African nations are making strides in strengthening their health systems. Members are able to: leverage resources to support field epidemiology and public health laboratory training and service delivery notably in the area of outbreak investigation and response as well as disease surveillance; by-pass government bureaucracies that often hinder and frustrate development partners; and consolidate efforts of different partners channelled through the FELTPs by networking graduates through alumni associations and calling on them to offer technical support in various public health capacities as the need arises

  11. Influences of sampling effort on detected patterns and structuring processes of a Neotropical plant-hummingbird network.

    Science.gov (United States)

    Vizentin-Bugoni, Jeferson; Maruyama, Pietro K; Debastiani, Vanderlei J; Duarte, L da S; Dalsgaard, Bo; Sazima, Marlies

    2016-01-01

    Virtually all empirical ecological interaction networks to some extent suffer from undersampling. However, how limitations imposed by sampling incompleteness affect our understanding of ecological networks is still poorly explored, which may hinder further advances in the field. Here, we use a plant-hummingbird network with unprecedented sampling effort (2716 h of focal observations) from the Atlantic Rainforest in Brazil, to investigate how sampling effort affects the description of network structure (i.e. widely used network metrics) and the relative importance of distinct processes (i.e. species abundances vs. traits) in determining the frequency of pairwise interactions. By dividing the network into time slices representing a gradient of sampling effort, we show that quantitative metrics, such as interaction evenness, specialization (H2 '), weighted nestedness (wNODF) and modularity (Q; QuanBiMo algorithm) were less biased by sampling incompleteness than binary metrics. Furthermore, the significance of some network metrics changed along the sampling effort gradient. Nevertheless, the higher importance of traits in structuring the network was apparent even with small sampling effort. Our results (i) warn against using very poorly sampled networks as this may bias our understanding of networks, both their patterns and structuring processes, (ii) encourage the use of quantitative metrics little influenced by sampling when performing spatio-temporal comparisons and (iii) indicate that in networks strongly constrained by species traits, such as plant-hummingbird networks, even small sampling is sufficient to detect their relative importance for the frequencies of interactions. Finally, we argue that similar effects of sampling are expected for other highly specialized subnetworks. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

  12. 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

  13. Sampling from complex networks with high community structures.

    Science.gov (United States)

    Salehi, Mostafa; Rabiee, Hamid R; Rajabi, Arezo

    2012-06-01

    In this paper, we propose a novel link-tracing sampling algorithm, based on the concepts from PageRank vectors, to sample from networks with high community structures. Our method has two phases; (1) Sampling the closest nodes to the initial nodes by approximating personalized PageRank vectors and (2) Jumping to a new community by using PageRank vectors and unknown neighbors. Empirical studies on several synthetic and real-world networks show that the proposed method improves the performance of network sampling compared to the popular link-based sampling methods in terms of accuracy and visited communities.

  14. Artificial Neural Network L* from different magnetospheric field models

    Science.gov (United States)

    Yu, Y.; Koller, J.; Zaharia, S. G.; Jordanova, V. K.

    2011-12-01

    The third adiabatic invariant L* plays an important role in modeling and understanding the radiation belt dynamics. The popular way to numerically obtain the L* value follows the recipe described by Roederer [1970], which is, however, slow and computational expensive. This work focuses on a new technique, which can compute the L* value in microseconds without losing much accuracy: artificial neural networks. Since L* is related to the magnetic flux enclosed by a particle drift shell, global magnetic field information needed to trace the drift shell is required. A series of currently popular empirical magnetic field models are applied to create the L* data pool using 1 million data samples which are randomly selected within a solar cycle and within the global magnetosphere. The networks, trained from the above L* data pool, can thereby be used for fairly efficient L* calculation given input parameters valid within the trained temporal and spatial range. Besides the empirical magnetospheric models, a physics-based self-consistent inner magnetosphere model (RAM-SCB) developed at LANL is also utilized to calculate L* values and then to train the L* neural network. This model better predicts the magnetospheric configuration and therefore can significantly improve the L*. The above neural network L* technique will enable, for the first time, comprehensive solar-cycle long studies of radiation belt processes. However, neural networks trained from different magnetic field models can result in different L* values, which could cause mis-interpretation of radiation belt dynamics, such as where the source of the radiation belt charged particle is and which mechanism is dominant in accelerating the particles. Such a fact calls for attention to cautiously choose a magnetospheric field model for the L* calculation.

  15. Critical field measurements in a superconducting networks

    International Nuclear Information System (INIS)

    Pannetier, B.; Chaussy, J.; Rammal, R.

    1984-01-01

    We have measured the critical field of a periodic two-dimensional network of superconducting indium. At low fields, the critical line Hsub(c)(T) reflects the network topology and exhibits well-defined cusps due to flux quantization corresponding to both integer and rational number of flux quanta phi 0 = h/2e per unit loop of the network [fr

  16. Visual Sample Plan (VSP) - FIELDS Integration

    Energy Technology Data Exchange (ETDEWEB)

    Pulsipher, Brent A.; Wilson, John E.; Gilbert, Richard O.; Hassig, Nancy L.; Carlson, Deborah K.; Bing-Canar, John; Cooper, Brian; Roth, Chuck

    2003-04-19

    Two software packages, VSP 2.1 and FIELDS 3.5, are being used by environmental scientists to plan the number and type of samples required to meet project objectives, display those samples on maps, query a database of past sample results, produce spatial models of the data, and analyze the data in order to arrive at defensible decisions. VSP 2.0 is an interactive tool to calculate optimal sample size and optimal sample location based on user goals, risk tolerance, and variability in the environment and in lab methods. FIELDS 3.0 is a set of tools to explore the sample results in a variety of ways to make defensible decisions with quantified levels of risk and uncertainty. However, FIELDS 3.0 has a small sample design module. VSP 2.0, on the other hand, has over 20 sampling goals, allowing the user to input site-specific assumptions such as non-normality of sample results, separate variability between field and laboratory measurements, make two-sample comparisons, perform confidence interval estimation, use sequential search sampling methods, and much more. Over 1,000 copies of VSP are in use today. FIELDS is used in nine of the ten U.S. EPA regions, by state regulatory agencies, and most recently by several international countries. Both software packages have been peer-reviewed, enjoy broad usage, and have been accepted by regulatory agencies as well as site project managers as key tools to help collect data and make environmental cleanup decisions. Recently, the two software packages were integrated, allowing the user to take advantage of the many design options of VSP, and the analysis and modeling options of FIELDS. The transition between the two is simple for the user – VSP can be called from within FIELDS, automatically passing a map to VSP and automatically retrieving sample locations and design information when the user returns to FIELDS. This paper will describe the integration, give a demonstration of the integrated package, and give users download

  17. Design for mosquito abundance, diversity, and phenology sampling within the National Ecological Observatory Network

    Science.gov (United States)

    Hoekman, D.; Springer, Yuri P.; Barker, C.M.; Barrera, R.; Blackmore, M.S.; Bradshaw, W.E.; Foley, D. H.; Ginsberg, Howard; Hayden, M. H.; Holzapfel, C. M.; Juliano, S. A.; Kramer, L. D.; LaDeau, S. L.; Livdahl, T. P.; Moore, C. G.; Nasci, R.S.; Reisen, W.K.; Savage, H. M.

    2016-01-01

    The National Ecological Observatory Network (NEON) intends to monitor mosquito populations across its broad geographical range of sites because of their prevalence in food webs, sensitivity to abiotic factors and relevance for human health. We describe the design of mosquito population sampling in the context of NEON’s long term continental scale monitoring program, emphasizing the sampling design schedule, priorities and collection methods. Freely available NEON data and associated field and laboratory samples, will increase our understanding of how mosquito abundance, demography, diversity and phenology are responding to land use and climate change.

  18. Sampling networks with prescribed degree correlations

    Science.gov (United States)

    Del Genio, Charo; Bassler, Kevin; Erdos, Péter; Miklos, István; Toroczkai, Zoltán

    2014-03-01

    A feature of a network known to affect its structural and dynamical properties is the presence of correlations amongst the node degrees. Degree correlations are a measure of how much the connectivity of a node influences the connectivity of its neighbours, and they are fundamental in the study of processes such as the spreading of information or epidemics, the cascading failures of damaged systems and the evolution of social relations. We introduce a method, based on novel mathematical results, that allows the exact sampling of networks where the number of connections between nodes of any given connectivity is specified. Our algorithm provides a weight associated to each sample, thereby allowing network observables to be measured according to any desired distribution, and it is guaranteed to always terminate successfully in polynomial time. Thus, our new approach provides a preferred tool for scientists to model complex systems of current relevance, and enables researchers to precisely study correlated networks with broad societal importance. CIDG acknowledges support by the European Commission's FP7 through grant No. 288021. KEB acknowledges support from the NSF through grant DMR?1206839. KEB, PE, IM and ZT acknowledge support from AFSOR and DARPA through grant FA?9550-12-1-0405.

  19. A soil sampling intercomparison exercise for the ALMERA network

    Energy Technology Data Exchange (ETDEWEB)

    Belli, Maria [Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), Via di Castel Romano 100, I-00128 Roma (Italy)], E-mail: maria.belli@apat.it; Zorzi, Paolo de [Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), Via di Castel Romano 100, I-00128 Roma (Italy)], E-mail: paolo.dezorzi@isprambiente.it; Sansone, Umberto [International Atomic Energy Agency (IAEA), Agency' s Laboratories Seibersdorf, A-2444 Seibersdorf (Austria)], E-mail: u.sansone@iaea.org; Shakhashiro, Abduhlghani [International Atomic Energy Agency (IAEA), Agency' s Laboratories Seibersdorf, A-2444 Seibersdorf (Austria)], E-mail: a.shakhashiro@iaea.org; Gondin da Fonseca, Adelaide [International Atomic Energy Agency (IAEA), Agency' s Laboratories Seibersdorf, A-2444 Seibersdorf (Austria)], E-mail: a.gondin-da-fonseca-azeredo@iaea.org; Trinkl, Alexander [International Atomic Energy Agency (IAEA), Agency' s Laboratories Seibersdorf, A-2444 Seibersdorf (Austria)], E-mail: a.trinkl@iaea.org; Benesch, Thomas [International Atomic Energy Agency (IAEA), Agency' s Laboratories Seibersdorf, A-2444 Seibersdorf (Austria)], E-mail: t.benesch@iaea.org

    2009-11-15

    Soil sampling and analysis for radionuclides after an accidental or routine release is a key factor for the dose calculation to members of the public, and for the establishment of possible countermeasures. The IAEA organized for selected laboratories of the ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network a Soil Sampling Intercomparison Exercise (IAEA/SIE/01) with the objective of comparing soil sampling procedures used by different laboratories. The ALMERA network is a world-wide network of analytical laboratories located in IAEA member states capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. Ten ALMERA laboratories were selected to participate in the sampling exercise. The soil sampling intercomparison exercise took place in November 2005 in an agricultural area qualified as a 'reference site', aimed at assessing the uncertainties associated with soil sampling in agricultural, semi-natural, urban and contaminated environments and suitable for performing sampling intercomparison. In this paper, the laboratories sampling performance were evaluated.

  20. A soil sampling intercomparison exercise for the ALMERA network

    International Nuclear Information System (INIS)

    Belli, Maria; Zorzi, Paolo de; Sansone, Umberto; Shakhashiro, Abduhlghani; Gondin da Fonseca, Adelaide; Trinkl, Alexander; Benesch, Thomas

    2009-01-01

    Soil sampling and analysis for radionuclides after an accidental or routine release is a key factor for the dose calculation to members of the public, and for the establishment of possible countermeasures. The IAEA organized for selected laboratories of the ALMERA (Analytical Laboratories for the Measurement of Environmental Radioactivity) network a Soil Sampling Intercomparison Exercise (IAEA/SIE/01) with the objective of comparing soil sampling procedures used by different laboratories. The ALMERA network is a world-wide network of analytical laboratories located in IAEA member states capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. Ten ALMERA laboratories were selected to participate in the sampling exercise. The soil sampling intercomparison exercise took place in November 2005 in an agricultural area qualified as a 'reference site', aimed at assessing the uncertainties associated with soil sampling in agricultural, semi-natural, urban and contaminated environments and suitable for performing sampling intercomparison. In this paper, the laboratories sampling performance were evaluated.

  1. Structural stability of interaction networks against negative external fields

    Science.gov (United States)

    Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.

    2018-04-01

    We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.

  2. Mean field interaction in biochemical reaction networks

    KAUST Repository

    Tembine, Hamidou; Tempone, Raul; Vilanova, Pedro

    2011-01-01

    In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits

  3. Random Walks on Directed Networks: Inference and Respondent-Driven Sampling

    Directory of Open Access Journals (Sweden)

    Malmros Jens

    2016-06-01

    Full Text Available Respondent-driven sampling (RDS is often used to estimate population properties (e.g., sexual risk behavior in hard-to-reach populations. In RDS, already sampled individuals recruit population members to the sample from their social contacts in an efficient snowball-like sampling procedure. By assuming a Markov model for the recruitment of individuals, asymptotically unbiased estimates of population characteristics can be obtained. Current RDS estimation methodology assumes that the social network is undirected, that is, all edges are reciprocal. However, empirical social networks in general also include a substantial number of nonreciprocal edges. In this article, we develop an estimation method for RDS in populations connected by social networks that include reciprocal and nonreciprocal edges. We derive estimators of the selection probabilities of individuals as a function of the number of outgoing edges of sampled individuals. The proposed estimators are evaluated on artificial and empirical networks and are shown to generally perform better than existing estimators. This is the case in particular when the fraction of directed edges in the network is large.

  4. Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

    Science.gov (United States)

    Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

    2015-01-01

    This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

  5. Mean field interaction in biochemical reaction networks

    KAUST Repository

    Tembine, Hamidou

    2011-09-01

    In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits and illustrate them with numerical examples. © 2011 IEEE.

  6. Sampling soils for 137Cs using various field-sampling volumes

    International Nuclear Information System (INIS)

    Nyhan, J.W.; Schofield, T.G.; White, G.C.; Trujillo, G.

    1981-10-01

    The sediments from a liquid effluent receiving area at the Los Alamos National Laboratory and soils from intensive study area in the fallout pathway of Trinity were sampled for 137 Cs using 25-, 500-, 2500-, and 12 500-cm 3 field sampling volumes. A highly replicated sampling program was used to determine mean concentrations and inventories of 137 Cs at each site, as well as estimates of spatial, aliquoting, and counting variance components of the radionuclide data. The sampling methods were also analyzed as a function of soil size fractions collected in each field sampling volume and of the total cost of the program for a given variation in the radionuclide survey results. Coefficients of variation (CV) of 137 Cs inventory estimates ranged from 0.063 to 0.14 for Mortandad Canyon sediments, where CV values for Trinity soils were observed from 0.38 to 0.57. Spatial variance components of 137 Cs concentration data were usually found to be larger than either the aliquoting or counting variance estimates and were inversely related to field sampling volume at the Trinity intensive site. Subsequent optimization studies of the sampling schemes demonstrated that each aliquot should be counted once, and that only 2 to 4 aliquots out of an many as 30 collected need be assayed for 137 Cs. The optimization studies showed that as sample costs increased to 45 man-hours of labor per sample, the variance of the mean 137 Cs concentration decreased dramatically, but decreased very little with additional labor

  7. Vector network analyzer ferromagnetic resonance spectrometer with field differential detection

    Science.gov (United States)

    Tamaru, S.; Tsunegi, S.; Kubota, H.; Yuasa, S.

    2018-05-01

    This work presents a vector network analyzer ferromagnetic resonance (VNA-FMR) spectrometer with field differential detection. This technique differentiates the S-parameter by applying a small binary modulation field in addition to the DC bias field to the sample. By setting the modulation frequency sufficiently high, slow sensitivity fluctuations of the VNA, i.e., low-frequency components of the trace noise, which limit the signal-to-noise ratio of the conventional VNA-FMR spectrometer, can be effectively removed, resulting in a very clean FMR signal. This paper presents the details of the hardware implementation and measurement sequence as well as the data processing and analysis algorithms tailored for the FMR spectrum obtained with this technique. Because the VNA measures a complex S-parameter, it is possible to estimate the Gilbert damping parameter from the slope of the phase variation of the S-parameter with respect to the bias field. We show that this algorithm is more robust against noise than the conventional algorithm based on the linewidth.

  8. Sampling Criterion for EMC Near Field Measurements

    DEFF Research Database (Denmark)

    Franek, Ondrej; Sørensen, Morten; Ebert, Hans

    2012-01-01

    An alternative, quasi-empirical sampling criterion for EMC near field measurements intended for close coupling investigations is proposed. The criterion is based on maximum error caused by sub-optimal sampling of near fields in the vicinity of an elementary dipole, which is suggested as a worst......-case representative of a signal trace on a typical printed circuit board. It has been found that the sampling density derived in this way is in fact very similar to that given by the antenna near field sampling theorem, if an error less than 1 dB is required. The principal advantage of the proposed formulation is its...

  9. Application of Artificial Neural Networks to the Analysis of NORM Samples

    International Nuclear Information System (INIS)

    Moser, H.; Peyrés, V.; Mejuto, M.; García-Toraño, E.

    2015-01-01

    This work describes the application of artificial neural networks (ANNs) to analyze the raw data of gamma-ray spectra of NORM samples and decide if the activity content of a certain nuclide is above or below the exemption limit of 1 Bq/g. The main advantage of using an ANN for this purpose is that for the user no specialized knowledge in the field of gamma-ray spectrometry is necessary. In total a number of 635 spectra consisting of varying activity concentrations, seven different materials and three densities each have been generated by Monte Carlo simulation to provide training material to the ANN. These spectra have been created using the simulation code PENELOPE. Validation was carried out with a number of NORM samples previously characterized by conventional gamma-ray spectrometry with peak fitting

  10. Efficient sampling of complex network with modified random walk strategies

    Science.gov (United States)

    Xie, Yunya; Chang, Shuhua; Zhang, Zhipeng; Zhang, Mi; Yang, Lei

    2018-02-01

    We present two novel random walk strategies, choosing seed node (CSN) random walk and no-retracing (NR) random walk. Different from the classical random walk sampling, the CSN and NR strategies focus on the influences of the seed node choice and path overlap, respectively. Three random walk samplings are applied in the Erdös-Rényi (ER), Barabási-Albert (BA), Watts-Strogatz (WS), and the weighted USAir networks, respectively. Then, the major properties of sampled subnets, such as sampling efficiency, degree distributions, average degree and average clustering coefficient, are studied. The similar conclusions can be reached with these three random walk strategies. Firstly, the networks with small scales and simple structures are conducive to the sampling. Secondly, the average degree and the average clustering coefficient of the sampled subnet tend to the corresponding values of original networks with limited steps. And thirdly, all the degree distributions of the subnets are slightly biased to the high degree side. However, the NR strategy performs better for the average clustering coefficient of the subnet. In the real weighted USAir networks, some obvious characters like the larger clustering coefficient and the fluctuation of degree distribution are reproduced well by these random walk strategies.

  11. Endogenous fields enhanced stochastic resonance in a randomly coupled neuronal network

    International Nuclear Information System (INIS)

    Deng, Bin; Wang, Lin; Wang, Jiang; Wei, Xi-le; Yu, Hai-tao

    2014-01-01

    Highlights: • We study effects of endogenous fields on stochastic resonance in a neural network. • Stochastic resonance can be notably enhanced by endogenous field feedback. • Endogenous field feedback delay plays a vital role in stochastic resonance. • The parameters of low-passed filter play a subtle role in SR. - Abstract: Endogenous field, evoked by structured neuronal network activity in vivo, is correlated with many vital neuronal processes. In this paper, the effects of endogenous fields on stochastic resonance (SR) in a randomly connected neuronal network are investigated. The network consists of excitatory and inhibitory neurons and the axonal conduction delays between neurons are also considered. Numerical results elucidate that endogenous field feedback results in more rhythmic macroscope activation of the network for proper time delay and feedback coefficient. The response of the network to the weak periodic stimulation can be notably enhanced by endogenous field feedback. Moreover, the endogenous field feedback delay plays a vital role in SR. We reveal that appropriately tuned delays of the feedback can either induce the enhancement of SR, appearing at every integer multiple of the weak input signal’s oscillation period, or the depression of SR, appearing at every integer multiple of half the weak input signal’s oscillation period for the same feedback coefficient. Interestingly, the parameters of low-passed filter which is used in obtaining the endogenous field feedback signal play a subtle role in SR

  12. Rapid Sampling of Hydrogen Bond Networks for Computational Protein Design.

    Science.gov (United States)

    Maguire, Jack B; Boyken, Scott E; Baker, David; Kuhlman, Brian

    2018-05-08

    Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

  13. The wireshark field guide analyzing and troubleshooting network traffic

    CERN Document Server

    Shimonski, Robert

    2013-01-01

    The Wireshark Field Guide provides hackers, pen testers, and network administrators with practical guidance on capturing and interactively browsing computer network traffic. Wireshark is the world's foremost network protocol analyzer, with a rich feature set that includes deep inspection of hundreds of protocols, live capture, offline analysis and many other features. The Wireshark Field Guide covers the installation, configuration and use of this powerful multi-platform tool. The book give readers the hands-on skills to be more productive with Wireshark as they drill

  14. Research collaboration in groups and networks: differences across academic fields.

    Science.gov (United States)

    Kyvik, Svein; Reymert, Ingvild

    2017-01-01

    The purpose of this paper is to give a macro-picture of collaboration in research groups and networks across all academic fields in Norwegian research universities, and to examine the relative importance of membership in groups and networks for individual publication output. To our knowledge, this is a new approach, which may provide valuable information on collaborative patterns in a particular national system, but of clear relevance to other national university systems. At the system level, conducting research in groups and networks are equally important, but there are large differences between academic fields. The research group is clearly most important in the field of medicine and health, while undertaking research in an international network is most important in the natural sciences. Membership in a research group and active participation in international networks are likely to enhance publication productivity and the quality of research.

  15. Network Model-Assisted Inference from Respondent-Driven Sampling Data.

    Science.gov (United States)

    Gile, Krista J; Handcock, Mark S

    2015-06-01

    Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population.

  16. Network Model-Assisted Inference from Respondent-Driven Sampling Data

    Science.gov (United States)

    Gile, Krista J.; Handcock, Mark S.

    2015-01-01

    Summary Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights for traditional design-based inference, and likelihood inference requires modeling the complex sampling process. As an alternative, we introduce a model-assisted approach, resulting in a design-based estimator leveraging a working network model. We derive a new class of estimators for population means and a corresponding bootstrap standard error estimator. We demonstrate improved performance compared to existing estimators, including adjustment for an initial convenience sample. We also apply the method and an extension to the estimation of HIV prevalence in a high-risk population. PMID:26640328

  17. Respondent-driven sampling and the recruitment of people with small injecting networks.

    Science.gov (United States)

    Paquette, Dana; Bryant, Joanne; de Wit, John

    2012-05-01

    Respondent-driven sampling (RDS) is a form of chain-referral sampling, similar to snowball sampling, which was developed to reach hidden populations such as people who inject drugs (PWID). RDS is said to reach members of a hidden population that may not be accessible through other sampling methods. However, less attention has been paid as to whether there are segments of the population that are more likely to be missed by RDS. This study examined the ability of RDS to capture people with small injecting networks. A study of PWID, using RDS, was conducted in 2009 in Sydney, Australia. The size of participants' injecting networks was examined by recruitment chain and wave. Participants' injecting network characteristics were compared to those of participants from a separate pharmacy-based study. A logistic regression analysis was conducted to examine the characteristics independently associated with having small injecting networks, using the combined RDS and pharmacy-based samples. In comparison with the pharmacy-recruited participants, RDS participants were almost 80% less likely to have small injecting networks, after adjusting for other variables. RDS participants were also more likely to have their injecting networks form a larger proportion of those in their social networks, and to have acquaintances as part of their injecting networks. Compared to those with larger injecting networks, individuals with small injecting networks were equally likely to engage in receptive sharing of injecting equipment, but less likely to have had contact with prevention services. These findings suggest that those with small injecting networks are an important group to recruit, and that RDS is less likely to capture these individuals.

  18. Toward cost-efficient sampling methods

    Science.gov (United States)

    Luo, Peng; Li, Yongli; Wu, Chong; Zhang, Guijie

    2015-09-01

    The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper proposes two new sampling methods based on the idea that a small part of vertices with high node degree could possess the most structure information of a complex network. The two proposed sampling methods are efficient in sampling high degree nodes so that they would be useful even if the sampling rate is low, which means cost-efficient. The first new sampling method is developed on the basis of the widely used stratified random sampling (SRS) method and the second one improves the famous snowball sampling (SBS) method. In order to demonstrate the validity and accuracy of two new sampling methods, we compare them with the existing sampling methods in three commonly used simulation networks that are scale-free network, random network, small-world network, and also in two real networks. The experimental results illustrate that the two proposed sampling methods perform much better than the existing sampling methods in terms of achieving the true network structure characteristics reflected by clustering coefficient, Bonacich centrality and average path length, especially when the sampling rate is low.

  19. The collection and field chemical analysis of water samples

    International Nuclear Information System (INIS)

    Korte, N.E.; Ealey, D.T.; Hollenbach, M.H.

    1984-01-01

    A successful water sampling program requires a clear understanding of appropriate measurement and sampling procedures in order to obtain reliable field data and representative samples. It is imperative that the personnel involved have a thorough knowledge of the limitations of the techniques being used. Though this seems self-evident, many sampling and field-chemical-analysis programs are still not properly conducted. Recognizing these problems, the Department of Energy contracted with Bendix Field Engineering Corporation through the Technical Measurements Center to develop and select procedures for water sampling and field chemical analysis at waste sites. The fundamental causese of poor field programs are addressed in this paper, largely through discussion of specific field-measurement techniques and their limitations. Recommendations for improvement, including quality-assurance measures, are also presented

  20. Field Sampling from a Segmented Image

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-06-01

    Full Text Available This paper presents a statistical method for deriving the optimal prospective field sampling scheme on a remote sensing image to represent different categories in the field. The iterated conditional modes algorithm (ICM) is used for segmentation...

  1. Waferscale assembly of Field-Aligned nanotube Networks (FANs)

    DEFF Research Database (Denmark)

    Dimaki, Maria; Bøggild, Peter

    2006-01-01

    We demonstrate the integration of nanotube networks on 512 individual devices on a full 4-inch wafer in less than 60 seconds with a roughly 80% yield using dielectrophoresis. We present here investigations of the morphology and electrical resistance of such field aligned networks for different fr...

  2. Predicting local field potentials with recurrent neural networks.

    Science.gov (United States)

    Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

    2016-08-01

    We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

  3. Sampling the equilibrium kinetic network of Trp-cage in explicit solvent

    NARCIS (Netherlands)

    Du, W.; Bolhuis, P.G.

    2014-01-01

    We employed the single replica multiple state transition interface sampling (MSTIS) approach to sample the kinetic (un) folding network of Trp-cage mini-protein in explicit water. Cluster analysis yielded 14 important metastable states in the network. The MSTIS simulation thus resulted in a full 14

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

    Directory of Open Access Journals (Sweden)

    Young Soo Suh

    2009-04-01

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

  5. Low and High-Frequency Field Potentials of Cortical Networks ...

    Science.gov (United States)

    Neural networks grown on microelectrode arrays (MEAs) have become an important, high content in vitro assay for assessing neuronal function. MEA experiments typically examine high- frequency (HF) (>200 Hz) spikes, and bursts which can be used to discriminate between different pharmacological agents/chemicals. However, normal brain activity is additionally composed of integrated low-frequency (0.5-100 Hz) field potentials (LFPs) which are filtered out of MEA recordings. The objective of this study was to characterize the relationship between HF and LFP neural network signals, and to assess the relative sensitivity of LFPs to selected neurotoxicants. Rat primary cortical cultures were grown on glass, single-well MEA chips. Spontaneous activity was sampled at 25 kHz and recorded (5 min) (Multi-Channel Systems) from mature networks (14 days in vitro). HF (spike, mean firing rate, MFR) and LF (power spectrum, amplitude) components were extracted from each network and served as its baseline (BL). Next, each chip was treated with either 1) a positive control, bicuculline (BIC, 25μM) or domoic acid (DA, 0.3μM), 2) or a negative control, acetaminophen (ACE, 100μM) or glyphosate (GLY, 100μM), 3) a solvent control (H2O or DMSO:EtOH), or 4) a neurotoxicant, (carbaryl, CAR 5, 30μM ; lindane, LIN 1, 10μM; permethrin, PERM 25, 50μM; triadimefon, TRI 5, 65μM). Post treatment, 5 mins of spontaneous activity was recorded and analyzed. As expected posit

  6. Application of CMAC Neural Network to Solar Energy Heliostat Field Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Neng-Sheng Pai

    2013-01-01

    Full Text Available Solar energy heliostat fields comprise numerous sun tracking platforms. As a result, fault detection is a highly challenging problem. Accordingly, the present study proposes a cerebellar model arithmetic computer (CMAC neutral network for automatically diagnosing faults within the heliostat field in accordance with the rotational speed, vibration, and temperature characteristics of the individual heliostat transmission systems. As compared with radial basis function (RBF neural network and back propagation (BP neural network in the heliostat field fault diagnosis, the experimental results show that the proposed neural network has a low training time, good robustness, and a reliable diagnostic performance. As a result, it provides an ideal solution for fault diagnosis in modern, large-scale heliostat fields.

  7. Towards Cost-efficient Sampling Methods

    OpenAIRE

    Peng, Luo; Yongli, Li; Chong, Wu

    2014-01-01

    The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper presents two new sampling methods based on the perspective that a small part of vertices with high node degree can possess the most structure information of a network. The two proposed sampling methods are efficient in sampling the nodes with high degree. The first new sampling method is improved on the basis of the stratified random sampling method and...

  8. Remedial investigation sampling and analysis plan for J-Field, Aberdeen Proving Ground, Maryland. Volume 1: Field Sampling Plan

    Energy Technology Data Exchange (ETDEWEB)

    Benioff, P.; Biang, R.; Dolak, D.; Dunn, C.; Martino, L.; Patton, T.; Wang, Y.; Yuen, C.

    1995-03-01

    The Environmental Management Division (EMD) of Aberdeen Proving Ground (APG), Maryland, is conducting a remedial investigation and feasibility study (RI/FS) of the J-Field area at APG pursuant to the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA), as amended. J-Field is within the Edgewood Area of APG in Harford County, Maryland (Figure 1. 1). Since World War II activities in the Edgewood Area have included the development, manufacture, testing, and destruction of chemical agents and munitions. These materials were destroyed at J-Field by open burning and open detonation (OB/OD). Considerable archival information about J-Field exists as a result of efforts by APG staff to characterize the hazards associated with the site. Contamination of J-Field was first detected during an environmental survey of the Edgewood Area conducted in 1977 and 1978 by the US Army Toxic and Hazardous Materials Agency (USATHAMA) (predecessor to the US Army Environmental Center [AEC]). As part of a subsequent USATHAMA -environmental survey, 11 wells were installed and sampled at J-Field. Contamination at J-Field was also detected during a munitions disposal survey conducted by Princeton Aqua Science in 1983. The Princeton Aqua Science investigation involved the installation and sampling of nine wells and the collection and analysis of surficial and deep composite soil samples. In 1986, a Resource Conservation and Recovery Act (RCRA) permit (MD3-21-002-1355) requiring a basewide RCRA Facility Assessment (RFA) and a hydrogeologic assessment of J-Field was issued by the US Environmental Protection Agency (EPA). In 1987, the US Geological Survey (USGS) began a two-phased hydrogeologic assessment in data were collected to model, groundwater flow at J-Field. Soil gas investigations were conducted, several well clusters were installed, a groundwater flow model was developed, and groundwater and surface water monitoring programs were established that continue today.

  9. AC Electric Field Communication for Human-Area Networking

    Science.gov (United States)

    Kado, Yuichi; Shinagawa, Mitsuru

    We have proposed a human-area networking technology that uses the surface of the human body as a data transmission path and uses an AC electric field signal below the resonant frequency of the human body. This technology aims to achieve a “touch and connect” intuitive form of communication by using the electric field signal that propagates along the surface of the human body, while suppressing both the electric field radiating from the human body and mutual interference. To suppress the radiation field, the frequency of the AC signal that excites the transmitter electrode must be lowered, and the sensitivity of the receiver must be raised while reducing transmission power to its minimally required level. We describe how we are developing AC electric field communication technologies to promote the further evolution of a human-area network in support of ubiquitous services, focusing on three main characteristics, enabling-transceiver technique, application-scenario modeling, and communications quality evaluation. Special attention is paid to the relationship between electro-magnetic compatibility evaluation and regulations for extremely low-power radio stations based on Japan's Radio Law.

  10. Random sampling of elementary flux modes in large-scale metabolic networks.

    Science.gov (United States)

    Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

    2012-09-15

    The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

  11. Adaptive Importance Sampling Simulation of Queueing Networks

    NARCIS (Netherlands)

    de Boer, Pieter-Tjerk; Nicola, V.F.; Rubinstein, N.; Rubinstein, Reuven Y.

    2000-01-01

    In this paper, a method is presented for the efficient estimation of rare-event (overflow) probabilities in Jackson queueing networks using importance sampling. The method differs in two ways from methods discussed in most earlier literature: the change of measure is state-dependent, i.e., it is a

  12. Non-equilibrium mean-field theories on scale-free networks

    International Nuclear Information System (INIS)

    Caccioli, Fabio; Dall'Asta, Luca

    2009-01-01

    Many non-equilibrium processes on scale-free networks present anomalous critical behavior that is not explained by standard mean-field theories. We propose a systematic method to derive stochastic equations for mean-field order parameters that implicitly account for the degree heterogeneity. The method is used to correctly predict the dynamical critical behavior of some binary spin models and reaction–diffusion processes. The validity of our non-equilibrium theory is further supported by showing its relation with the generalized Landau theory of equilibrium critical phenomena on networks

  13. Kaolin Quality Prediction from Samples: A Bayesian Network Approach

    International Nuclear Information System (INIS)

    Rivas, T.; Taboada, J.; Ordonez, C.; Matias, J. M.

    2009-01-01

    We describe the results of an expert system applied to the evaluation of samples of kaolin for industrial use in paper or ceramic manufacture. Different machine learning techniques - classification trees, support vector machines and Bayesian networks - were applied with the aim of evaluating and comparing their interpretability and prediction capacities. The predictive capacity of these models for the samples analyzed was highly satisfactory, both for ceramic quality and paper quality. However, Bayesian networks generally proved to be the most useful technique for our study, as this approach combines good predictive capacity with excellent interpretability of the kaolin quality structure, as it graphically represents relationships between variables and facilitates what-if analyses.

  14. Performance evaluation of an importance sampling technique in a Jackson network

    Science.gov (United States)

    brahim Mahdipour, E.; Masoud Rahmani, Amir; Setayeshi, Saeed

    2014-03-01

    Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.

  15. Mean field games for cognitive radio networks

    KAUST Repository

    Tembine, Hamidou; Tempone, Raul; Vilanova, Pedro

    2012-01-01

    In this paper we study mobility effect and power saving in cognitive radio networks using mean field games. We consider two types of users: primary and secondary users. When active, each secondary transmitter-receiver uses carrier sensing

  16. An energy-efficient adaptive sampling scheme for wireless sensor networks

    NARCIS (Netherlands)

    Masoum, Alireza; Meratnia, Nirvana; Havinga, Paul J.M.

    2013-01-01

    Wireless sensor networks are new monitoring platforms. To cope with their resource constraints, in terms of energy and bandwidth, spatial and temporal correlation in sensor data can be exploited to find an optimal sampling strategy to reduce number of sampling nodes and/or sampling frequencies while

  17. Trapped field measurements on MgB{sub 2} bulk samples

    Energy Technology Data Exchange (ETDEWEB)

    Koblischka, Michael; Karwoth, Thomas; Zeng, XianLin; Hartmann, Uwe [Institute of Experimental Physics, Saarland University, P. O. Box 151150, D-66041 Saarbruecken (Germany); Berger, Kevin; Douine, Bruno [University of Lorraine, GREEN, 54506 Vandoeuvre-les-Nancy (France)

    2016-07-01

    Trapped field measurements were performed on bulk, polycrystalline MgB{sub 2} samples stemming from different sources with the emphasis to develop applications like superconducting permanent magnets ('supermagnets') and electric motors. We describe the setup for the trapped field measurements and the experimental procedure (field cooling, zero-field cooling, field sweep rates). The trapped field measurements were conducted using a cryocooling system to cool the bulk samples to the desired temperatures, and a low-loss cryostat equipped with a room-temperature bore and a maximum field of ±5 T was employed to provide the external magnetic field. The superconducting coil of this cryostat is operated using a bidirectional power supply. Various sweep rates of the external magnetic field ranging between 1 mT/s and 40 mT/s were used to generate the applied field. The measurements were performed with one sample and two samples stacked together. A maximum trapped field of 7 T was recorded. We discuss the results obtained and the problems arising due to flux jumping, which is often seen for the MgB{sub 2} samples cooled to temperatures below 10 K.

  18. Experiment of Wireless Sensor Network to Monitor Field Data

    Directory of Open Access Journals (Sweden)

    Kwang Sik Kim

    2009-08-01

    Full Text Available Recently the mobile wireless network has been drastically enhanced and one of the most efficient ways to realize the ubiquitous network will be to develop the converged network by integrating the mobile wireless network with other IP fixed network like NGN (Next Generation Network. So in this paper the term of the wireless ubiquitous network is used to describe this approach. In this paper, first, the wireless ubiquitous network architecture is described based on IMS which has been standardized by 3GPP (3rd Generation Partnership Program. Next, the field data collection system to match the satellite data using location information is proposed based on the concept of the wireless ubiquitous network architecture. The purpose of the proposed system is to provide more accurate analyzing method with the researchers in the remote sensing area.

  19. Bayesian prediction and adaptive sampling algorithms for mobile sensor networks online environmental field reconstruction in space and time

    CERN Document Server

    Xu, Yunfei; Dass, Sarat; Maiti, Tapabrata

    2016-01-01

    This brief introduces a class of problems and models for the prediction of the scalar field of interest from noisy observations collected by mobile sensor networks. It also introduces the problem of optimal coordination of robotic sensors to maximize the prediction quality subject to communication and mobility constraints either in a centralized or distributed manner. To solve such problems, fully Bayesian approaches are adopted, allowing various sources of uncertainties to be integrated into an inferential framework effectively capturing all aspects of variability involved. The fully Bayesian approach also allows the most appropriate values for additional model parameters to be selected automatically by data, and the optimal inference and prediction for the underlying scalar field to be achieved. In particular, spatio-temporal Gaussian process regression is formulated for robotic sensors to fuse multifactorial effects of observations, measurement noise, and prior distributions for obtaining the predictive di...

  20. Mean field methods for cortical network dynamics

    DEFF Research Database (Denmark)

    Hertz, J.; Lerchner, Alexander; Ahmadi, M.

    2004-01-01

    We review the use of mean field theory for describing the dynamics of dense, randomly connected cortical circuits. For a simple network of excitatory and inhibitory leaky integrate- and-fire neurons, we can show how the firing irregularity, as measured by the Fano factor, increases...... with the strength of the synapses in the network and with the value to which the membrane potential is reset after a spike. Generalizing the model to include conductance-based synapses gives insight into the connection between the firing statistics and the high- conductance state observed experimentally in visual...

  1. An evaluation of soil sampling for 137Cs using various field-sampling volumes.

    Science.gov (United States)

    Nyhan, J W; White, G C; Schofield, T G; Trujillo, G

    1983-05-01

    The sediments from a liquid effluent receiving area at the Los Alamos National Laboratory and soils from an intensive study area in the fallout pathway of Trinity were sampled for 137Cs using 25-, 500-, 2500- and 12,500-cm3 field sampling volumes. A highly replicated sampling program was used to determine mean concentrations and inventories of 137Cs at each site, as well as estimates of spatial, aliquoting, and counting variance components of the radionuclide data. The sampling methods were also analyzed as a function of soil size fractions collected in each field sampling volume and of the total cost of the program for a given variation in the radionuclide survey results. Coefficients of variation (CV) of 137Cs inventory estimates ranged from 0.063 to 0.14 for Mortandad Canyon sediments, whereas CV values for Trinity soils were observed from 0.38 to 0.57. Spatial variance components of 137Cs concentration data were usually found to be larger than either the aliquoting or counting variance estimates and were inversely related to field sampling volume at the Trinity intensive site. Subsequent optimization studies of the sampling schemes demonstrated that each aliquot should be counted once, and that only 2-4 aliquots out of as many as 30 collected need be assayed for 137Cs. The optimization studies showed that as sample costs increased to 45 man-hours of labor per sample, the variance of the mean 137Cs concentration decreased dramatically, but decreased very little with additional labor.

  2. A wireless sensor network design and evaluation for large structural strain field monitoring

    International Nuclear Information System (INIS)

    Qiu, Zixue; Wu, Jian; Yuan, Shenfang

    2011-01-01

    Structural strain changes under external environmental or mechanical loads are the main monitoring parameters in structural health monitoring or mechanical property tests. This paper presents a wireless sensor network designed for monitoring large structural strain field variation. First of all, a precision strain sensor node is designed for multi-channel strain gauge signal conditioning and wireless monitoring. In order to establish a synchronous strain data acquisition network, the cluster-star network synchronization method is designed in detail. To verify the functionality of the designed wireless network for strain field monitoring capability, a multi-point network evaluation system is developed for an experimental aluminum plate structure for load variation monitoring. Based on the precision wireless strain nodes, the wireless data acquisition network is deployed to synchronously gather, process and transmit strain gauge signals and monitor results under concentrated loads. This paper shows the efficiency of the wireless sensor network for large structural strain field monitoring

  3. Spin imaging in solids using synchronously rotating field gradients and samples

    International Nuclear Information System (INIS)

    Wind, R.A.; Yannoni, C.S.

    1983-01-01

    A method for spin-imaging in solids using nuclear magnetic resonance (NMR) spectroscopy is described. With this method, the spin density distribution of a two- or three-dimensional object such as a solid can be constructed resulting in an image of the sample. This method lends itself to computer control to map out an image of the object. This spin-imaging method involves the steps of placing a solid sample in the rf coil field and the external magnetic field of an NMR spectrometer. A magnetic field gradient is superimposed across the sample to provide a field gradient which results in a varying DC field that has different values over different parts of the sample. As a result, nuclei in different parts of the sample have different resonant NMR frequencies. The sample is rotated about an axis which makes a particular angle of 54.7 degrees with the static external magnetic field. The magnetic field gradient which has a spatial distribution related to the sample spinning axis is then rotated synchronously with the sample. Data is then collected while performing a solid state NMR line narrowing procedure. The next step is to change the phase relation between the sample rotation and the field gradient rotation. The data is again collected as before while the sample and field gradient are synchronously rotated. The phase relation is changed a number of times and data collected each time. The spin image of the solid sample is then reconstructed from the collected data

  4. Site-specific waste management instruction for the field sampling organization

    International Nuclear Information System (INIS)

    Bryant, D.L.

    1997-01-01

    The Site-Specific Waste Management Instruction (SSWMI) provides guidance for the management of waste generated from field-sampling activities performed by the Environment Restoration Contractor (ERC) Sampling Organization that are not managed as part of a project SSWMI. Generally, the waste is unused preserved groundwater trip blanks, used and expired calibration solutions, and other similar waste that cannot be returned to an ERC project for disposal. The specific waste streams addressed by this SSWMI are identified in Section 2.0. This SSWMI was prepared in accordance with BHI-EE-02, Environmental Requirements. Waste generated from field sample collection activities should be returned to the project and managed in accordance with the applicable project-specific SSWMI whenever possible. However, returning all field sample collection and associated waste to a project for disposal may not always be practical or cost effective. Therefore, the ERC field sampling organization must manage and arrange to dispose of the waste using the (Bechtel Hanford, Inc. [BHI]) Field Support Waste Management (FSWM) services. This SSWMI addresses those waste streams that are the responsibility of the field sampling organization to manage and make arrangements for disposal

  5. A network approach to the geometric structure of shallow cloud fields

    Science.gov (United States)

    Glassmeier, F.; Feingold, G.

    2017-12-01

    The representation of shallow clouds and their radiative impact is one of the largest challenges for global climate models. While the bulk properties of cloud fields, including effects of organization, are a very active area of research, the potential of the geometric arrangement of cloud fields for the development of new parameterizations has hardly been explored. Self-organized patterns are particularly evident in the cellular structure of Stratocumulus (Sc) clouds so readily visible in satellite imagery. Inspired by similar patterns in biology and physics, we approach pattern formation in Sc fields from the perspective of natural cellular networks. Our network analysis is based on large-eddy simulations of open- and closed-cell Sc cases. We find the network structure to be neither random nor characteristic to natural convection. It is independent of macroscopic cloud fields properties like the Sc regime (open vs closed) and its typical length scale (boundary layer height). The latter is a consequence of entropy maximization (Lewis's Law with parameter 0.16). The cellular pattern is on average hexagonal, where non-6 sided cells occur according to a neighbor-number distribution variance of about 2. Reflecting the continuously renewing dynamics of Sc fields, large (many-sided) cells tend to neighbor small (few-sided) cells (Aboav-Weaire Law with parameter 0.9). These macroscopic network properties emerge independent of the Sc regime because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. This model offers for the first time a fundamental and universal explanation for the geometric pattern of Sc clouds. It may contribute to the development of advanced Sc parameterizations

  6. 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.

  7. Sparse Power-Law Network Model for Reliable Statistical Predictions Based on Sampled Data

    Directory of Open Access Journals (Sweden)

    Alexander P. Kartun-Giles

    2018-04-01

    Full Text Available A projective network model is a model that enables predictions to be made based on a subsample of the network data, with the predictions remaining unchanged if a larger sample is taken into consideration. An exchangeable model is a model that does not depend on the order in which nodes are sampled. Despite a large variety of non-equilibrium (growing and equilibrium (static sparse complex network models that are widely used in network science, how to reconcile sparseness (constant average degree with the desired statistical properties of projectivity and exchangeability is currently an outstanding scientific problem. Here we propose a network process with hidden variables which is projective and can generate sparse power-law networks. Despite the model not being exchangeable, it can be closely related to exchangeable uncorrelated networks as indicated by its information theory characterization and its network entropy. The use of the proposed network process as a null model is here tested on real data, indicating that the model offers a promising avenue for statistical network modelling.

  8. Epidemic spreading in weighted networks: an edge-based mean-field solution.

    Science.gov (United States)

    Yang, Zimo; Zhou, Tao

    2012-05-01

    Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

  9. Mean field dynamics of networks of delay-coupled noisy excitable units

    Energy Technology Data Exchange (ETDEWEB)

    Franović, Igor, E-mail: franovic@ipb.ac.rs [Scientific Computing Laboratory, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade (Serbia); Todorović, Kristina; Burić, Nikola [Department of Physics and Mathematics, Faculty of Pharmacy, University of Belgrade, Vojvode Stepe 450, Belgrade (Serbia); Vasović, Nebojša [Department of Applied Mathematics, Faculty of Mining and Geology, University of Belgrade, PO Box 162, Belgrade (Serbia)

    2016-06-08

    We use the mean-field approach to analyze the collective dynamics in macroscopic networks of stochastic Fitzhugh-Nagumo units with delayed couplings. The conditions for validity of the two main approximations behind the model, called the Gaussian approximation and the Quasi-independence approximation, are examined. It is shown that the dynamics of the mean-field model may indicate in a self-consistent fashion the parameter domains where the Quasi-independence approximation fails. Apart from a network of globally coupled units, we also consider the paradigmatic setup of two interacting assemblies to demonstrate how our framework may be extended to hierarchical and modular networks. In both cases, the mean-field model can be used to qualitatively analyze the stability of the system, as well as the scenarios for the onset and the suppression of the collective mode. In quantitative terms, the mean-field model is capable of predicting the average oscillation frequency corresponding to the global variables of the exact system.

  10. On Field Size and Success Probability in Network Coding

    DEFF Research Database (Denmark)

    Geil, Hans Olav; Matsumoto, Ryutaroh; Thomsen, Casper

    2008-01-01

    Using tools from algebraic geometry and Gröbner basis theory we solve two problems in network coding. First we present a method to determine the smallest field size for which linear network coding is feasible. Second we derive improved estimates on the success probability of random linear network...... coding. These estimates take into account which monomials occur in the support of the determinant of the product of Edmonds matrices. Therefore we finally investigate which monomials can occur in the determinant of the Edmonds matrix....

  11. Importance Sampling Simulation of Population Overflow in Two-node Tandem Networks

    NARCIS (Netherlands)

    Nicola, V.F.; Zaburnenko, T.S.; Baier, C; Chiola, G.; Smirni, E.

    2005-01-01

    In this paper we consider the application of importance sampling in simulations of Markovian tandem networks in order to estimate the probability of rare events, such as network population overflow. We propose a heuristic methodology to obtain a good approximation to the 'optimal' state-dependent

  12. Upper critical field of complex superconducting networks in the continuum limit

    International Nuclear Information System (INIS)

    Santhanam, P.; Chi, C.C.

    1988-01-01

    We propose a simple method for calculating the superconducting upper critical field of complex periodic two-dimensional networks in the continuum limit. Two specific lattices with space groups P4gm and C2mm are used to demonstrate this approach. We obtain the result that the ratio of the critical field of these networks to that of a uniform film is close to but larger than 2

  13. Feynman diagrams sampling for quantum field theories on the QPACE 2 supercomputer

    Energy Technology Data Exchange (ETDEWEB)

    Rappl, Florian

    2016-08-01

    This work discusses the application of Feynman diagram sampling in quantum field theories. The method uses a computer simulation to sample the diagrammatic space obtained in a series expansion. For running large physical simulations powerful computers are obligatory, effectively splitting the thesis in two parts. The first part deals with the method of Feynman diagram sampling. Here the theoretical background of the method itself is discussed. Additionally, important statistical concepts and the theory of the strong force, quantum chromodynamics, are introduced. This sets the context of the simulations. We create and evaluate a variety of models to estimate the applicability of diagrammatic methods. The method is then applied to sample the perturbative expansion of the vertex correction. In the end we obtain the value for the anomalous magnetic moment of the electron. The second part looks at the QPACE 2 supercomputer. This includes a short introduction to supercomputers in general, as well as a closer look at the architecture and the cooling system of QPACE 2. Guiding benchmarks of the InfiniBand network are presented. At the core of this part, a collection of best practices and useful programming concepts are outlined, which enables the development of efficient, yet easily portable, applications for the QPACE 2 system.

  14. Delay-tolerant mobile network protocol for rice field monitoring using wireless sensor networks

    Science.gov (United States)

    Guitton, Alexandre; Andres, Frédéric; Cardoso, Jarbas Lopes; Kawtrakul, Asanee; Barbin, Silvio E.

    2015-10-01

    The monitoring of rice fields can improve productivity by helping farmers throughout the rice cultivation cycle, on various issues: when to harvest, when to treat the crops against disease, when to increase the water level, how to share observations and decisions made in a collaborative way, etc. In this paper, we propose an architecture to monitor a rice field by a wireless sensor network. Our architecture is based on static sensor nodes forming a disconnected network, and mobile nodes communicating with the sensor nodes in a delay-tolerant manner. The data collected by the static sensor nodes are transmitted to mobile nodes, which in turn transmit them to a gateway, connected to a database, for further analysis. We focus on the related architecture, as well as on the energy-efficient protocols intended to perform the data collection.

  15. Protocol of Magnetic Field Area Network and its Applications

    International Nuclear Information System (INIS)

    Won, Yunjae; Kang, Shinjae; Lim, Seungok; Kahng, Hyunkook

    2012-01-01

    The social needs are increasing in the wireless communication technology based on sensors for the monitoring of natural disasters such as avalanche and storm, the management of underground conditions from ground sinking and landslide, the monitoring of pipes, wires buried under the ground, the management of building and bridge, and the monitoring of the pollutions such as soils and water. However, the conventional wireless communication systems based on EM (Electro Magnetic) waves have not supported reliable communication because of large signal strength attenuation around soil, water, and metals. In order to handle this problem, various efforts in the wireless communication area have been conducted. Magnetic Field Area Network (MFAN) supports the reliable communication service without large signal attenuation around water, soil, and metal. Therefore, Magnetic Field Area Network (MFAN) is expected to be one of promising solutions to the limit of the conventional technologies such as Radio Frequency Indentification (RFID) and Wireless Sensor Network (WSN)

  16. Protocol of Magnetic Field Area Network and its Applications

    Energy Technology Data Exchange (ETDEWEB)

    Won, Yunjae; Kang, Shinjae; Lim, Seungok [Korea Electronics Technology Institute, Seoul (Korea, Republic of); Kahng, Hyunkook [Korea Univ., Seoul (Korea, Republic of)

    2012-03-15

    The social needs are increasing in the wireless communication technology based on sensors for the monitoring of natural disasters such as avalanche and storm, the management of underground conditions from ground sinking and landslide, the monitoring of pipes, wires buried under the ground, the management of building and bridge, and the monitoring of the pollutions such as soils and water. However, the conventional wireless communication systems based on EM (Electro Magnetic) waves have not supported reliable communication because of large signal strength attenuation around soil, water, and metals. In order to handle this problem, various efforts in the wireless communication area have been conducted. Magnetic Field Area Network (MFAN) supports the reliable communication service without large signal attenuation around water, soil, and metal. Therefore, Magnetic Field Area Network (MFAN) is expected to be one of promising solutions to the limit of the conventional technologies such as Radio Frequency Indentification (RFID) and Wireless Sensor Network (WSN)

  17. Magnetostatic modes in ferromagnetic samples with inhomogeneous internal fields

    Science.gov (United States)

    Arias, Rodrigo

    2015-03-01

    Magnetostatic modes in ferromagnetic samples are very well characterized and understood in samples with uniform internal magnetic fields. More recently interest has shifted to the study of magnetization modes in ferromagnetic samples with inhomogeneous internal fields. The present work shows that under the magnetostatic approximation and for samples of arbitrary shape and/or arbitrary inhomogeneous internal magnetic fields the modes can be classified as elliptic or hyperbolic, and their associated frequency spectrum can be delimited. This results from the analysis of the character of the second order partial differential equation for the magnetostatic potential under these general conditions. In general, a sample with an inhomogeneous internal field and at a given frequency, may have regions of elliptic and hyperbolic character separated by a boundary. In the elliptic regions the magnetostatic modes have a smooth monotonic character (generally decaying form the surfaces (a ``tunneling'' behavior)) and in hyperbolic regions an oscillatory wave-like character. A simple local criterion distinguishes hyperbolic from elliptic regions: the sign of a susceptibility parameter. This study shows that one may control to some extent magnetostatic modes via external fields or geometry. R.E.A. acknowledges Financiamiento Basal para Centros Cientificos y Tecnologicos de Excelencia under Project No. FB 0807 (Chile), Grant No. ICM P10-061-F by Fondo de Innovacion para la Competitividad-MINECON, and Proyecto Fondecyt 1130192.

  18. Adaptive enhanced sampling by force-biasing using neural networks

    Science.gov (United States)

    Guo, Ashley Z.; Sevgen, Emre; Sidky, Hythem; Whitmer, Jonathan K.; Hubbell, Jeffrey A.; de Pablo, Juan J.

    2018-04-01

    A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here, it is illustrated in the context of an adaptive biasing force approach where, rather than relying on discrete force estimates, one can resort to a self-regularizing artificial neural network to generate continuous, estimated generalized forces. By doing so, the proposed approach addresses several shortcomings common to adaptive biasing force and other algorithms. Specifically, the neural network enables (1) smooth estimates of generalized forces in sparsely sampled regions, (2) force estimates in previously unexplored regions, and (3) continuous force estimates with which to bias the simulation, as opposed to biases generated at specific points of a discrete grid. The usefulness of the method is illustrated with three different examples, chosen to highlight the wide range of applicability of the underlying concepts. In all three cases, the new method is found to enhance considerably the underlying traditional adaptive biasing force approach. The method is also found to provide improvements over previous implementations of neural network assisted algorithms.

  19. Neural attractor network for application in visual field data classification

    International Nuclear Information System (INIS)

    Fink, Wolfgang

    2004-01-01

    The purpose was to introduce a novel method for computer-based classification of visual field data derived from perimetric examination, that may act as a ' counsellor', providing an independent 'second opinion' to the diagnosing physician. The classification system consists of a Hopfield-type neural attractor network that obtains its input data from perimetric examination results. An iterative relaxation process determines the states of the neurons dynamically. Therefore, even 'noisy' perimetric output, e.g., early stages of a disease, may eventually be classified correctly according to the predefined idealized visual field defect (scotoma) patterns, stored as attractors of the network, that are found with diseases of the eye, optic nerve and the central nervous system. Preliminary tests of the classification system on real visual field data derived from perimetric examinations have shown a classification success of over 80%. Some of the main advantages of the Hopfield-attractor-network-based approach over feed-forward type neural networks are: (1) network architecture is defined by the classification problem; (2) no training is required to determine the neural coupling strengths; (3) assignment of an auto-diagnosis confidence level is possible by means of an overlap parameter and the Hamming distance. In conclusion, the novel method for computer-based classification of visual field data, presented here, furnishes a valuable first overview and an independent 'second opinion' in judging perimetric examination results, pointing towards a final diagnosis by a physician. It should not be considered a substitute for the diagnosing physician. Thanks to the worldwide accessibility of the Internet, the classification system offers a promising perspective towards modern computer-assisted diagnosis in both medicine and tele-medicine, for example and in particular, with respect to non-ophthalmic clinics or in communities where perimetric expertise is not readily available

  20. Field-effect Flow Control in Polymer Microchannel Networks

    Science.gov (United States)

    Sniadecki, Nathan; Lee, Cheng S.; Beamesderfer, Mike; DeVoe, Don L.

    2003-01-01

    A new Bio-MEMS electroosmotic flow (EOF) modulator for plastic microchannel networks has been developed. The EOF modulator uses field-effect flow control (FEFC) to adjust the zeta potential at the Parylene C microchannel wall. By setting a differential EOF pumping rate in two of the three microchannels at a T-intersection with EOF modulators, the induced pressure at the intersection generated pumping in the third, field-free microchannel. The EOF modulators are able to change the magnitude and direction of the pressure pumping by inducing either a negative or positive pressure at the intersection. The flow velocity is tracked by neutralized fluorescent microbeads in the microchannels. The proof-of-concept of the EOF modulator described here may be applied to complex plastic ,microchannel networks where individual microchannel flow rates are addressable by localized induced-pressure pumping.

  1. Classification of networks of automata by dynamical mean field theory

    International Nuclear Information System (INIS)

    Burda, Z.; Jurkiewicz, J.; Flyvbjerg, H.

    1990-01-01

    Dynamical mean field theory is used to classify the 2 24 =65,536 different networks of binary automata on a square lattice with nearest neighbour interactions. Application of mean field theory gives 700 different mean field classes, which fall in seven classes of different asymptotic dynamics characterized by fixed points and two-cycles. (orig.)

  2. Magnetorheological measurements with consideration for the internal magnetic field in samples

    Energy Technology Data Exchange (ETDEWEB)

    Kordonski, W; Gorodkin, S [QED Technologies International, 1040 University Ave., Rochester, NY 14607 (United States)], E-mail: kordonski@qedmrf.com

    2009-02-01

    The magnetically induced yield stress in a sample of suspension of magnetic particles is associated with formation of a field-oriented structure, the strength of which depends on the degree of particles magnetization. This factor is largely defined by the actual magnetic field strength in the sample. At the same time it is common practice to present and analyze magnetorheological characteristics as a function of the applied magnetic field. Uncertainty of an influence function in magnetorheology hampers interpretation of data obtained with different measurement configurations. It was shown in this paper that rheological response of magnetorheological fluid to the applied magnetic field is defined by the sample's actual (internal) magnetic field intensity, which, in turn, depends on sample geometry and field orientation all other factors being equal. Utilization of the sample's actual field as an influence function in magnetorheology allows proper interpretation of data obtained with different measuring system configurations. Optimization of the actual internal field is a promising approach in designing of energy efficient magnetorheological devices.

  3. Focus on the emerging new fields of network physiology and network medicine

    Science.gov (United States)

    Ivanov, Plamen Ch; Liu, Kang K. L.; Bartsch, Ronny P.

    2016-10-01

    Despite the vast progress and achievements in systems biology and integrative physiology in the last decades, there is still a significant gap in understanding the mechanisms through which (i) genomic, proteomic and metabolic factors and signaling pathways impact vertical processes across cells, tissues and organs leading to the expression of different disease phenotypes and influence the functional and clinical associations between diseases, and (ii) how diverse physiological systems and organs coordinate their functions over a broad range of space and time scales and horizontally integrate to generate distinct physiologic states at the organism level. Two emerging fields, network medicine and network physiology, aim to address these fundamental questions. Novel concepts and approaches derived from recent advances in network theory, coupled dynamical systems, statistical and computational physics show promise to provide new insights into the complexity of physiological structure and function in health and disease, bridging the genetic and sub-cellular level with inter-cellular interactions and communications among integrated organ systems and sub-systems. These advances form first building blocks in the methodological formalism and theoretical framework necessary to address fundamental problems and challenges in physiology and medicine. This ‘focus on’ issue contains 26 articles representing state-of-the-art contributions covering diverse systems from the sub-cellular to the organism level where physicists have key role in laying the foundations of these new fields.

  4. Cortical information flow in Parkinson's disease: a composite network/field model

    Directory of Open Access Journals (Sweden)

    Cliff C. Kerr

    2013-04-01

    Full Text Available The basal ganglia play a crucial role in the execution of movements, as demonstrated by the severe motor deficits that accompany Parkinson's disease (PD. Since motor commands originate in the cortex, an important question is how the basal ganglia influence cortical information flow, and how this influence becomes pathological in PD. To explore this, we developed a composite neuronal network/neural field model. The network model consisted of 4950 spiking neurons, divided into 15 excitatory and inhibitory cell populations in the thalamus and cortex. The field model consisted of the cortex, thalamus, striatum, subthalamic nucleus, and globus pallidus. Both models have been separately validated in previous work. Three field models were used: one with basal ganglia parameters based on data from healthy individuals, one based on data from individuals with PD, and one purely thalamocortical model. Spikes generated by these field models were then used to drive the network model. Compared to the network driven by the healthy model, the PD-driven network had lower firing rates, a shift in spectral power towards lower frequencies, and higher probability of bursting; each of these findings is consistent with empirical data on PD. In the healthy model, we found strong Granger causality in the beta and low gamma bands between cortical layers, but this was largely absent in the PD model. In particular, the reduction in Granger causality from the main "input" layer of the cortex (layer 4 to the main "output" layer (layer 5 was pronounced. This may account for symptoms of PD that seem to reflect deficits in information flow, such as bradykinesia. In general, these results demonstrate that the brain's large-scale oscillatory environment, represented here by the field model, strongly influences the information processing that occurs within its subnetworks. Hence, it may be preferable to drive spiking network models with physiologically realistic inputs rather than

  5. Comparison of leach results from field and laboratory prepared samples

    International Nuclear Information System (INIS)

    Oblath, S.B.; Langton, C.A.

    1985-01-01

    The leach behavior of saltstone prepared in the laboratory agrees well with that from samples mixed in the field using the Littleford mixer. Leach rates of nitrates and cesium from the current reference formulation saltstone were compared. The laboratory samples were prepared using simulated salt solution; those in the field used Tank 50 decontaminated supernate. For both nitrate and cesium, the field and laboratory samples showed nearly identical leach rates for the first 30 to 50 days. For the remaining period of the test, the field samples showed higher leach rates with the maximum difference being less than a factor of three. Ruthenium and antimony were present in the Tank 50 supernate in known amounts. Antimony-125 was observed in the leachate and a fractional leach rate was calculated to be at least a factor of ten less than that of 137 Cs. No 106 Ru was observed in the leachate, and the release rate was not calculated. However, based on the detection limits for the analysis, the ruthenium leach rate must also be at least a factor of ten less than cesium. These data are the first measurements of the leach rates of Ru and Sb from saltstone. The nitrate leach rates for these samples were 5 x 10 -5 grams of nitrate per square cm per day after 100 days for the laboratory samples and after 200 days for the field samples. These values are consistent with the previously measured leach rates for reference formulation saltstone. The relative standard deviation in the leach rate is about 15% for the field samples, which all were produced from one batch of saltstone, and about 35% for the laboratory samples, which came from different batches. These are the first recorded estimates of the error in leach rates for saltstone

  6. Soil sampling intercomparison exercise by selected laboratories of the ALMERA Network

    International Nuclear Information System (INIS)

    2009-01-01

    The IAEA's Seibersdorf Laboratories in Austria have the programmatic responsibility to provide assistance to Member State laboratories in maintaining and improving the reliability of analytical measurement results, both in radionuclide and trace element determinations. This is accomplished through the provision of reference materials of terrestrial origin, validated analytical procedures, training in the implementation of internal quality control, and through the evaluation of measurement performance by the organization of worldwide and regional interlaboratory comparison exercises. The IAEA is mandated to support global radionuclide measurement systems related to accidental or intentional releases of radioactivity in the environment. To fulfil this obligation and ensure a reliable, worldwide, rapid and consistent response, the IAEA coordinates an international network of analytical laboratories for the measurement of environmental radioactivity (ALMERA). The network was established by the IAEA in 1995 and makes available to Member States a world-wide network of analytical laboratories capable of providing reliable and timely analysis of environmental samples in the event of an accidental or intentional release of radioactivity. A primary requirement for the ALMERA members is participation in the IAEA interlaboratory comparison exercises, which are specifically organized for ALMERA on a regular basis. These exercises are designed to monitor and demonstrate the performance and analytical capabilities of the network members, and to identify gaps and problem areas where further development is needed. In this framework, the IAEA organized a soil sampling intercomparison exercise (IAEA/SIE/01) for selected laboratories of the ALMERA network. The main objective of this exercise was to compare soil sampling procedures used by different participating laboratories. The performance evaluation results of the interlaboratory comparison exercises performed in the framework of

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

    Directory of Open Access Journals (Sweden)

    Tim D Williams

    2011-08-01

    Full Text Available 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.

  8. Using remotely-sensed data for optimal field sampling

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-09-01

    Full Text Available M B E R 2 0 0 8 15 USING REMOTELY- SENSED DATA FOR OPTIMAL FIELD SAMPLING BY DR PRAVESH DEBBA STATISTICS IS THE SCIENCE pertaining to the collection, summary, analysis, interpretation and presentation of data. It is often impractical... studies are: where to sample, what to sample and how many samples to obtain. Conventional sampling techniques are not always suitable in environmental studies and scientists have explored the use of remotely-sensed data as ancillary information to aid...

  9. Sample cell for in-field X-ray diffraction experiments

    Directory of Open Access Journals (Sweden)

    Viktor Höglin

    2015-01-01

    Full Text Available A sample cell making it possible to perform synchrotron radiation X-ray powder diffraction experiments in a magnetic field of 0.35 T has been constructed. The device is an add-on to an existing sample cell and contains a strong permanent magnet of NdFeB-type. Experiments have shown that the setup is working satisfactory making it possible to perform in-field measurements.

  10. Communication: Multiple atomistic force fields in a single enhanced sampling simulation

    Energy Technology Data Exchange (ETDEWEB)

    Hoang Viet, Man [Department of Physics, North Carolina State University, Raleigh, North Carolina 27695-8202 (United States); Derreumaux, Philippe, E-mail: philippe.derreumaux@ibpc.fr [Laboratoire de Biochimie Théorique, UPR 9080, CNRS, Université Denis Diderot, Sorbonne Paris Cité IBPC, 13 rue Pierre et Marie Curie, 75005 Paris (France); Institut Universitaire de France, 103 Bvd Saint-Germain, 75005 Paris (France); Nguyen, Phuong H., E-mail: phuong.nguyen@ibpc.fr [Laboratoire de Biochimie Théorique, UPR 9080, CNRS, Université Denis Diderot, Sorbonne Paris Cité IBPC, 13 rue Pierre et Marie Curie, 75005 Paris (France)

    2015-07-14

    The main concerns of biomolecular dynamics simulations are the convergence of the conformational sampling and the dependence of the results on the force fields. While the first issue can be addressed by employing enhanced sampling techniques such as simulated tempering or replica exchange molecular dynamics, repeating these simulations with different force fields is very time consuming. Here, we propose an automatic method that includes different force fields into a single advanced sampling simulation. Conformational sampling using three all-atom force fields is enhanced by simulated tempering and by formulating the weight parameters of the simulated tempering method in terms of the energy fluctuations, the system is able to perform random walk in both temperature and force field spaces. The method is first demonstrated on a 1D system and then validated by the folding of the 10-residue chignolin peptide in explicit water.

  11. Sample selection via angular distance in the space of the arguments of an artificial neural network

    Science.gov (United States)

    Fernández Jaramillo, J. M.; Mayerle, R.

    2018-05-01

    In the construction of an artificial neural network (ANN) a proper data splitting of the available samples plays a major role in the training process. This selection of subsets for training, testing and validation affects the generalization ability of the neural network. Also the number of samples has an impact in the time required for the design of the ANN and the training. This paper introduces an efficient and simple method for reducing the set of samples used for training a neural network. The method reduces the required time to calculate the network coefficients, while keeping the diversity and avoiding overtraining the ANN due the presence of similar samples. The proposed method is based on the calculation of the angle between two vectors, each one representing one input of the neural network. When the angle formed among samples is smaller than a defined threshold only one input is accepted for the training. The accepted inputs are scattered throughout the sample space. Tidal records are used to demonstrate the proposed method. The results of a cross-validation show that with few inputs the quality of the outputs is not accurate and depends on the selection of the first sample, but as the number of inputs increases the accuracy is improved and differences among the scenarios with a different starting sample have and important reduction. A comparison with the K-means clustering algorithm shows that for this application the proposed method with a smaller number of samples is producing a more accurate network.

  12. 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.

  13. 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.

  14. The challenge of social networking in the field of environment and health.

    Science.gov (United States)

    van den Hazel, Peter; Keune, Hans; Randall, Scott; Yang, Aileen; Ludlow, David; Bartonova, Alena

    2012-06-28

    The fields of environment and health are both interdisciplinary and trans-disciplinary, and until recently had little engagement in social networking designed to cross disciplinary boundaries. The EU FP6 project HENVINET aimed to establish integrated social network and networking facilities for multiple stakeholders in environment and health. The underlying assumption is that increased social networking across disciplines and sectors will enhance the quality of both problem knowledge and problem solving, by facilitating interactions. Inter- and trans-disciplinary networks are considered useful for this purpose. This does not mean that such networks are easily organized, as openness to such cooperation and exchange is often difficult to ascertain. Different methods may enhance network building. Using a mixed method approach, a diversity of actions were used in order to investigate the main research question: which kind of social networking activities and structures can best support the objective of enhanced inter- and trans-disciplinary cooperation and exchange in the fields of environment and health. HENVINET applied interviews, a role playing session, a personal response system, a stakeholder workshop and a social networking portal as part of the process of building an interdisciplinary and trans-disciplinary network. The interviews provided support for the specification of requirements for an interdisciplinary and trans-disciplinary network. The role playing session, the personal response system and the stakeholder workshop were assessed as useful tools in forming such network, by increasing the awareness by different disciplines of other's positions. The social networking portal was particularly useful in delivering knowledge, but the role of the scientist in social networking is not yet clear. The main challenge in the field of environment and health is not so much a lack of scientific problem knowledge, but rather the ability to effectively communicate, share

  15. Portable field water sample filtration unit

    International Nuclear Information System (INIS)

    Hebert, A.J.; Young, G.G.

    1977-01-01

    A lightweight back-packable field-tested filtration unit is described. The unit is easily cleaned without cross contamination at the part-per-billion level and allows rapid filtration of boiling hot and sometimes muddy water. The filtration results in samples that are free of bacteria and particulates and which resist algae growth even after storage for months. 3 figures

  16. Optimizing Soil Moisture Sampling Locations for Validation Networks for SMAP

    Science.gov (United States)

    Roshani, E.; Berg, A. A.; Lindsay, J.

    2013-12-01

    Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories

  17. AN/VRC 118 Mid-Tier Networking Vehicular Radio (MNVR) and Joint Enterprise Network Manager (JENM) Early Fielding Report

    Science.gov (United States)

    2017-01-18

    requirements. The Army intends to conduct the MNVR Initial Operational Test and Evaluation ( IOT &E) with the new radio in FY21 to support a fielding decision...improve the commander’s ability to conduct mission command over the MNVR WNW mid-tier network. Network Usage During the 2016 MNVR Operational...its reliability requirement in a loaded network simulating full brigade usage . Based on the results of developmental test, the Army made

  18. Teknik Sampling Snowball dalam Penelitian Lapangan

    Directory of Open Access Journals (Sweden)

    Nina Nurdiani

    2014-12-01

    Full Text Available Field research can be associated with both qualitative and quantitative research methods, depending on the problems faced and the goals to be achieved. The success of data collection in the field research depends on the determination of the appropriate sampling technique, to obtain accurate data, and reliably. In studies that have problems related to specific issues, requiring a non-probability sampling techniques one of which is the snowball sampling technique. This technique is useful for finding, identifying, selecting and taking samples in a network or chain of relationships. Phased implementation procedures performed through interviews and questionnaires. Snowball sampling technique has strengths and weaknesses in its application. Field research housing sector become the case study to explain this sampling technique.

  19. A brief review of advances in complex networks of nuclear science and technology field

    International Nuclear Information System (INIS)

    Fang Jinqing

    2010-01-01

    A brief review of advances in complex networks of nuclear science and technology field at home and is given and summarized. These complex networks include: nuclear energy weapon network, network centric warfare, beam transport networks, continuum percolation evolving network associated with nuclear reactions, global nuclear power station network, (nuclear) chemistry reaction networks, radiological monitoring and anti-nuclear terror networks, and so on. Some challenge issues and development prospects of network science are pointed out finally. (authors)

  20. Mean field games for cognitive radio networks

    KAUST Repository

    Tembine, Hamidou

    2012-06-01

    In this paper we study mobility effect and power saving in cognitive radio networks using mean field games. We consider two types of users: primary and secondary users. When active, each secondary transmitter-receiver uses carrier sensing and is subject to long-term energy constraint. We formulate the interaction between primary user and large number of secondary users as an hierarchical mean field game. In contrast to the classical large-scale approaches based on stochastic geometry, percolation theory and large random matrices, the proposed mean field framework allows one to describe the evolution of the density distribution and the associated performance metrics using coupled partial differential equations. We provide explicit formulas and algorithmic power management for both primary and secondary users. A complete characterization of the optimal distribution of energy and probability of success is given.

  1. Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

    Science.gov (United States)

    Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

    In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

  2. Learning spectrum's selection in OLAM network for analysis cement samples

    International Nuclear Information System (INIS)

    Huang Ning; Wang Peng; Tang Daiquan; Hu Renlan

    2010-01-01

    It uses OLAM artificial neural network to analyze the samples of cement raw material. Two kinds of spectrums are used for network learning: pure-element spectrum and mix-element spectrum. The output of pure-element method can be used to construct a simulate spectrum, which can be compared with the original spectrum and judge the shift of spectrum; the mix-element method can store more message and correct the matrix effect, but the multicollinearity among spectrums can cause some side effect to the results. (authors)

  3. LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

    Science.gov (United States)

    Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

    2018-09-01

    The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

  4. Noisy mean field game model for malware propagation in opportunistic networks

    KAUST Repository

    Tembine, Hamidou

    2012-01-01

    In this paper we present analytical mean field techniques that can be used to better understand the behavior of malware propagation in opportunistic large networks. We develop a modeling methodology based on stochastic mean field optimal control that is able to capture many aspects of the problem, especially the impact of the control and heterogeneity of the system on the spreading characteristics of malware. The stochastic large process characterizing the evolution of the total number of infected nodes is examined with a noisy mean field limit and compared to a deterministic one. The stochastic nature of the wireless environment make stochastic approaches more realistic for such types of networks. By introducing control strategies, we show that the fraction of infected nodes can be maintained below some threshold. In contrast to most of the existing results on mean field propagation models which focus on deterministic equations, we show that the mean field limit is stochastic if the second moment of the number of object transitions per time slot is unbounded with the size of the system. This allows us to compare one path of the fraction of infected nodes with the stochastic trajectory of its mean field limit. In order to take into account the heterogeneity of opportunistic networks, the analysis is extended to multiple types of nodes. Our numerical results show that the heterogeneity can help to stabilize the system. We verify the results through simulation showing how to obtain useful approximations in the case of very large systems. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

  5. NEON terrestrial field observations: designing continental scale, standardized sampling

    Science.gov (United States)

    R. H. Kao; C.M. Gibson; R. E. Gallery; C. L. Meier; D. T. Barnett; K. M. Docherty; K. K. Blevins; P. D. Travers; E. Azuaje; Y. P. Springer; K. M. Thibault; V. J. McKenzie; M. Keller; L. F. Alves; E. L. S. Hinckley; J. Parnell; D. Schimel

    2012-01-01

    Rapid changes in climate and land use and the resulting shifts in species distributions and ecosystem functions have motivated the development of the National Ecological Observatory Network (NEON). Integrating across spatial scales from ground sampling to remote sensing, NEON will provide data for users to address ecological responses to changes in climate, land use,...

  6. Validation of Networks Derived from Snowball Sampling of Municipal Science Education Actors

    Science.gov (United States)

    von der Fehr, Ane; Sølberg, Jan; Bruun, Jesper

    2018-01-01

    Social network analysis (SNA) has been used in many educational studies in the past decade, but what these studies have in common is that the populations in question in most cases are defined and known to the researchers studying the networks. Snowball sampling is an SNA methodology most often used to study hidden populations, for example, groups…

  7. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

    DEFF Research Database (Denmark)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L

    2016-01-01

    on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network......With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical...... and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...

  8. Optimal sampling schemes for vegetation and geological field visits

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2012-07-01

    Full Text Available The presentation made to Wits Statistics Department was on common classification methods used in the field of remote sensing, and the use of remote sensing to design optimal sampling schemes for field visits with applications in vegetation...

  9. Event-triggered synchronization for reaction-diffusion complex networks via random sampling

    Science.gov (United States)

    Dong, Tao; Wang, Aijuan; Zhu, Huiyun; Liao, Xiaofeng

    2018-04-01

    In this paper, the synchronization problem of the reaction-diffusion complex networks (RDCNs) with Dirichlet boundary conditions is considered, where the data is sampled randomly. An event-triggered controller based on the sampled data is proposed, which can reduce the number of controller and the communication load. Under this strategy, the synchronization problem of the diffusion complex network is equivalently converted to the stability of a of reaction-diffusion complex dynamical systems with time delay. By using the matrix inequality technique and Lyapunov method, the synchronization conditions of the RDCNs are derived, which are dependent on the diffusion term. Moreover, it is found the proposed control strategy can get rid of the Zeno behavior naturally. Finally, a numerical example is given to verify the obtained results.

  10. Artificial Neural Network for Total Laboratory Automation to Improve the Management of Sample Dilution.

    Science.gov (United States)

    Ialongo, Cristiano; Pieri, Massimo; Bernardini, Sergio

    2017-02-01

    Diluting a sample to obtain a measure within the analytical range is a common task in clinical laboratories. However, for urgent samples, it can cause delays in test reporting, which can put patients' safety at risk. The aim of this work is to show a simple artificial neural network that can be used to make it unnecessary to predilute a sample using the information available through the laboratory information system. Particularly, the Multilayer Perceptron neural network built on a data set of 16,106 cardiac troponin I test records produced a correct inference rate of 100% for samples not requiring predilution and 86.2% for those requiring predilution. With respect to the inference reliability, the most relevant inputs were the presence of a cardiac event or surgery and the result of the previous assay. Therefore, such an artificial neural network can be easily implemented into a total automation framework to sensibly reduce the turnaround time of critical orders delayed by the operation required to retrieve, dilute, and retest the sample.

  11. Revisiting random walk based sampling in networks: evasion of burn-in period and frequent regenerations.

    Science.gov (United States)

    Avrachenkov, Konstantin; Borkar, Vivek S; Kadavankandy, Arun; Sreedharan, Jithin K

    2018-01-01

    In the framework of network sampling, random walk (RW) based estimation techniques provide many pragmatic solutions while uncovering the unknown network as little as possible. Despite several theoretical advances in this area, RW based sampling techniques usually make a strong assumption that the samples are in stationary regime, and hence are impelled to leave out the samples collected during the burn-in period. This work proposes two sampling schemes without burn-in time constraint to estimate the average of an arbitrary function defined on the network nodes, for example, the average age of users in a social network. The central idea of the algorithms lies in exploiting regeneration of RWs at revisits to an aggregated super-node or to a set of nodes, and in strategies to enhance the frequency of such regenerations either by contracting the graph or by making the hitting set larger. Our first algorithm, which is based on reinforcement learning (RL), uses stochastic approximation to derive an estimator. This method can be seen as intermediate between purely stochastic Markov chain Monte Carlo iterations and deterministic relative value iterations. The second algorithm, which we call the Ratio with Tours (RT)-estimator, is a modified form of respondent-driven sampling (RDS) that accommodates the idea of regeneration. We study the methods via simulations on real networks. We observe that the trajectories of RL-estimator are much more stable than those of standard random walk based estimation procedures, and its error performance is comparable to that of respondent-driven sampling (RDS) which has a smaller asymptotic variance than many other estimators. Simulation studies also show that the mean squared error of RT-estimator decays much faster than that of RDS with time. The newly developed RW based estimators (RL- and RT-estimators) allow to avoid burn-in period, provide better control of stability along the sample path, and overall reduce the estimation time. Our

  12. Long-Term Ecological Monitoring Field Sampling Plan for 2007

    International Nuclear Information System (INIS)

    T. Haney R. VanHorn

    2007-01-01

    This field sampling plan describes the field investigations planned for the Long-Term Ecological Monitoring Project at the Idaho National Laboratory Site in 2007. This plan and the Quality Assurance Project Plan for Waste Area Groups 1, 2, 3, 4, 5, 6, 7, 10, and Removal Actions constitute the sampling and analysis plan supporting long-term ecological monitoring sampling in 2007. The data collected under this plan will become part of the long-term ecological monitoring data set that is being collected annually. The data will be used to determine the requirements for the subsequent long-term ecological monitoring. This plan guides the 2007 investigations, including sampling, quality assurance, quality control, analytical procedures, and data management. As such, this plan will help to ensure that the resulting monitoring data will be scientifically valid, defensible, and of known and acceptable quality

  13. Long-Term Ecological Monitoring Field Sampling Plan for 2007

    Energy Technology Data Exchange (ETDEWEB)

    T. Haney

    2007-07-31

    This field sampling plan describes the field investigations planned for the Long-Term Ecological Monitoring Project at the Idaho National Laboratory Site in 2007. This plan and the Quality Assurance Project Plan for Waste Area Groups 1, 2, 3, 4, 5, 6, 7, 10, and Removal Actions constitute the sampling and analysis plan supporting long-term ecological monitoring sampling in 2007. The data collected under this plan will become part of the long-term ecological monitoring data set that is being collected annually. The data will be used t determine the requirements for the subsequent long-term ecological monitoring. This plan guides the 2007 investigations, including sampling, quality assurance, quality control, analytical procedures, and data management. As such, this plan will help to ensure that the resulting monitoring data will be scientifically valid, defensible, and of known and acceptable quality.

  14. The genesis and evolution of the African Field Epidemiology Network

    African Journals Online (AJOL)

    The genesis and evolution of the African Field Epidemiology Network. David Mukanga, Mufuta Tshimanga, Frederick Wurapa, David Serwada, George Pariyo, Fred Wabwire-Mangen, Sheba Gitta, Stella Chungong, Murray Trostle, Peter Nsubuga ...

  15. Advanced path sampling of the kinetic network of small proteins

    NARCIS (Netherlands)

    Du, W.

    2014-01-01

    This thesis is focused on developing advanced path sampling simulation methods to study protein folding and unfolding, and to build kinetic equilibrium networks describing these processes. In Chapter 1 the basic knowledge of protein structure and folding theories were introduced and a brief overview

  16. Mean field theory of epidemic spreading with effective contacts on networks

    International Nuclear Information System (INIS)

    Wu, Qingchu; Chen, Shufang

    2015-01-01

    We present a general approach to the analysis of the susceptible-infected-susceptible model with effective contacts on networks, where each susceptible node will be infected with a certain probability only for effective contacts. In the network, each node has a given effective contact number. By using the one-vertex heterogenous mean-field (HMF) approximation and the pair HMF approximation, we obtain conditions for epidemic outbreak on degree-uncorrelated networks. Our results suggest that the epidemic threshold is closely related to the effective contact and its distribution. However, when the effective contact is only dependent of node degree, the epidemic threshold can be established by the degree distribution of networks.

  17. Hofstadter's Butterfly and Phase Transition of Checkerboard Superconducting Network in a Magnetic Field

    International Nuclear Information System (INIS)

    Hou Jingmin; Tian, Li-Jim

    2010-01-01

    We study the magnetic effect of the checkerboard superconducting wire network. Based on the de Gennes-Alexader theory, we obtain difference equations for superconducting order parameter in the wire network. Through solving these difference equations, we obtain the eigenvalues, linked to the coherence length, as a function of magnetic field. The diagram of eigenvalues shows a fractal structure, being so-called Hofstadter's butterfly. We also calculate and discuss the dependence of the transition temperature of the checkerboard superconducting wire network on the applied magnetic field, which is related to up-edge of the Hofstadter's butterfly spectrum. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

  18. Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure

    International Nuclear Information System (INIS)

    Yang Xuhua; Sun Bao; Wang Bo; Sun Youxian

    2010-01-01

    Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper. (general)

  19. Second harmonic sound field after insertion of a biological tissue sample

    Science.gov (United States)

    Zhang, Dong; Gong, Xiu-Fen; Zhang, Bo

    2002-01-01

    Second harmonic sound field after inserting a biological tissue sample is investigated by theory and experiment. The sample is inserted perpendicular to the sound axis, whose acoustical properties are different from those of surrounding medium (distilled water). By using the superposition of Gaussian beams and the KZK equation in quasilinear and parabolic approximations, the second harmonic field after insertion of the sample can be derived analytically and expressed as a linear combination of self- and cross-interaction of the Gaussian beams. Egg white, egg yolk, porcine liver, and porcine fat are used as the samples and inserted in the sound field radiated from a 2 MHz uniformly excited focusing source. Axial normalized sound pressure curves of the second harmonic wave before and after inserting the sample are measured and compared with the theoretical results calculated with 10 items of Gaussian beam functions.

  20. Mean field approximation for biased diffusion on Japanese inter-firm trading network.

    Science.gov (United States)

    Watanabe, Hayafumi

    2014-01-01

    By analysing the financial data of firms across Japan, a nonlinear power law with an exponent of 1.3 was observed between the number of business partners (i.e. the degree of the inter-firm trading network) and sales. In a previous study using numerical simulations, we found that this scaling can be explained by both the money-transport model, where a firm (i.e. customer) distributes money to its out-edges (suppliers) in proportion to the in-degree of destinations, and by the correlations among the Japanese inter-firm trading network. However, in this previous study, we could not specifically identify what types of structure properties (or correlations) of the network determine the 1.3 exponent. In the present study, we more clearly elucidate the relationship between this nonlinear scaling and the network structure by applying mean-field approximation of the diffusion in a complex network to this money-transport model. Using theoretical analysis, we obtained the mean-field solution of the model and found that, in the case of the Japanese firms, the scaling exponent of 1.3 can be determined from the power law of the average degree of the nearest neighbours of the network with an exponent of -0.7.

  1. Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.

    Science.gov (United States)

    Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang

    2011-11-01

    The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by sampling, which can explain a large number of macroscopic experimental data in neuroscience and cognitive science. But it has turned out to be surprisingly difficult to create a link between these abstract models for stochastic computations and more detailed models of the dynamics of networks of spiking neurons. Here we create such a link and show that under some conditions the stochastic firing activity of networks of spiking neurons can be interpreted as probabilistic inference via Markov chain Monte Carlo (MCMC) sampling. Since common methods for MCMC sampling in distributed systems, such as Gibbs sampling, are inconsistent with the dynamics of spiking neurons, we introduce a different approach based on non-reversible Markov chains that is able to reflect inherent temporal processes of spiking neuronal activity through a suitable choice of random variables. We propose a neural network model and show by a rigorous theoretical analysis that its neural activity implements MCMC sampling of a given distribution, both for the case of discrete and continuous time. This provides a step towards closing the gap between abstract functional models of cortical computation and more detailed models of networks of spiking neurons.

  2. A stochastic-field description of finite-size spiking neural networks.

    Science.gov (United States)

    Dumont, Grégory; Payeur, Alexandre; Longtin, André

    2017-08-01

    Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity-the density of active neurons per unit time-is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks; this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics.

  3. Optimal information transfer in enzymatic networks: A field theoretic formulation

    Science.gov (United States)

    Samanta, Himadri S.; Hinczewski, Michael; Thirumalai, D.

    2017-07-01

    Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus [Hinczewski and Thirumalai, Phys. Rev. X 4, 041017 (2014), 10.1103/PhysRevX.4.041017]. We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudointermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudointermediate. Surprisingly, in these examples the minimum error computed using simulations that take nonlinearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second-order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in

  4. Field applications of the channel network model, CHAN3D

    International Nuclear Information System (INIS)

    Khademi, B.; Gylling, B.; Moreno, L.; Neretnieks, I.

    1998-01-01

    The Channel Network model and its computer implementation, CHAN3D, was developed to simulate fluid flow and transport of solutes in fractured media. The model has been used to interpret field experiments of flow and transport in small and in large scale. It may also be used for safety assessments of repositories for nuclear and other hazardous wastes. In this case, CHAN3D has been coupled to a compartment model, NUCTRAN, to describe the near field of the repository. The model is based on field observations, which indicate that the flow and solute transport take place in a three-dimensional network of connected channels. The channels have very different properties and they are generated in the model from observed stochastic distributions. This allows us to represent the large heterogeneity of the flow distribution commonly observed in fractured media. Solute transport is modelled considering advection and rock interactions such as matrix diffusion and sorption within the interior of the rock. Objects such as fracture zones, tunnels and release sources can be incorporated in the model

  5. Using a Control System Ethernet Network as a Field Bus

    CERN Document Server

    De Van, William R; Lawson, Gregory S; Wagner, William H; Wantland, David M; Williams, Ernest

    2005-01-01

    A major component of a typical accelerator distributed control system (DCS) is a dedicated, large-scale local area communications network (LAN). The SNS EPICS-based control system uses a LAN based on the popular IEEE-802.3 set of standards (Ethernet). Since the control system network infrastructure is available throughout the facility, and since Ethernet-based controllers are readily available, it is tempting to use the control system LAN for "fieldbus" communications to low-level control devices (e.g. vacuum controllers; remote I/O). These devices may or may not be compatible with the high-level DCS protocols. This paper presents some of the benefits and risks of combining high-level DCS communications with low-level "field bus" communications on the same network, and describes measures taken at SNS to promote compatibility between devices connected to the control system network.

  6. A recurrent neural network for classification of unevenly sampled variable stars

    Science.gov (United States)

    Naul, Brett; Bloom, Joshua S.; Pérez, Fernando; van der Walt, Stéfan

    2018-02-01

    Astronomical surveys of celestial sources produce streams of noisy time series measuring flux versus time (`light curves'). Unlike in many other physical domains, however, large (and source-specific) temporal gaps in data arise naturally due to intranight cadence choices as well as diurnal and seasonal constraints1-5. With nightly observations of millions of variable stars and transients from upcoming surveys4,6, efficient and accurate discovery and classification techniques on noisy, irregularly sampled data must be employed with minimal human-in-the-loop involvement. Machine learning for inference tasks on such data traditionally requires the laborious hand-coding of domain-specific numerical summaries of raw data (`features')7. Here, we present a novel unsupervised autoencoding recurrent neural network8 that makes explicit use of sampling times and known heteroskedastic noise properties. When trained on optical variable star catalogues, this network produces supervised classification models that rival other best-in-class approaches. We find that autoencoded features learned in one time-domain survey perform nearly as well when applied to another survey. These networks can continue to learn from new unlabelled observations and may be used in other unsupervised tasks, such as forecasting and anomaly detection.

  7. Self-sustained firing activities of the cortical network with plastic rules in weak AC electrical fields

    International Nuclear Information System (INIS)

    Qin Ying-Mei; Wang Jiang; Men Cong; Zhao Jia; Wei Xi-Le; Deng Bin

    2012-01-01

    Both external and endogenous electrical fields widely exist in the environment of cortical neurons. The effects of a weak alternating current (AC) field on a neural network model with synaptic plasticity are studied. It is found that self-sustained rhythmic firing patterns, which are closely correlated with the cognitive functions, are significantly modified due to the self-organizing of the network in the weak AC field. The activities of the neural networks are affected by the synaptic connection strength, the external stimuli, and so on. In the presence of learning rules, the synaptic connections can be modulated by the external stimuli, which will further enhance the sensitivity of the network to the external signal. The properties of the external AC stimuli can serve as control parameters in modulating the evolution of the neural network. (interdisciplinary physics and related areas of science and technology)

  8. Field Sample Preparation Method Development for Isotope Ratio Mass Spectrometry

    International Nuclear Information System (INIS)

    Leibman, C.; Weisbrod, K.; Yoshida, T.

    2015-01-01

    Non-proliferation and International Security (NA-241) established a working group of researchers from Los Alamos National Laboratory (LANL), Pacific Northwest National Laboratory (PNNL) and Savannah River National Laboratory (SRNL) to evaluate the utilization of in-field mass spectrometry for safeguards applications. The survey of commercial off-the-shelf (COTS) mass spectrometers (MS) revealed no instrumentation existed capable of meeting all the potential safeguards requirements for performance, portability, and ease of use. Additionally, fieldable instruments are unlikely to meet the International Target Values (ITVs) for accuracy and precision for isotope ratio measurements achieved with laboratory methods. The major gaps identified for in-field actinide isotope ratio analysis were in the areas of: 1. sample preparation and/or sample introduction, 2. size reduction of mass analyzers and ionization sources, 3. system automation, and 4. decreased system cost. Development work in 2 through 4, numerated above continues, in the private and public sector. LANL is focusing on developing sample preparation/sample introduction methods for use with the different sample types anticipated for safeguard applications. Addressing sample handling and sample preparation methods for MS analysis will enable use of new MS instrumentation as it becomes commercially available. As one example, we have developed a rapid, sample preparation method for dissolution of uranium and plutonium oxides using ammonium bifluoride (ABF). ABF is a significantly safer and faster alternative to digestion with boiling combinations of highly concentrated mineral acids. Actinides digested with ABF yield fluorides, which can then be analyzed directly or chemically converted and separated using established column chromatography techniques as needed prior to isotope analysis. The reagent volumes and the sample processing steps associated with ABF sample digestion lend themselves to automation and field

  9. A method for under-sampled ecological network data analysis: plant-pollination as case study

    Directory of Open Access Journals (Sweden)

    Peter B. Sorensen

    2012-01-01

    Full Text Available In this paper, we develop a method, termed the Interaction Distribution (ID method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1, pi,j: the probability for a visit made by the i’th pollinator species to take place on the j’th plant species; (2, qi,j: the probability for a visit received by the j’th plant species to be made by the i’th pollinator. The method applies the Dirichlet distribution to estimate these two probabilities, based on a given empirical data set. The estimated mean values for pi,j and qi,j reflect the relative differences between recorded numbers of visits for different pollinator and plant species, and the estimated uncertainty of pi,j and qi,j decreases with higher numbers of recorded visits.

  10. Quantum dynamics in transverse-field Ising models from classical networks

    Directory of Open Access Journals (Sweden)

    Markus Schmitt, Markus Heyl

    2018-02-01

    Full Text Available The efficient representation of quantum many-body states with classical resources is a key challenge in quantum many-body theory. In this work we analytically construct classical networks for the description of the quantum dynamics in transverse-field Ising models that can be solved efficiently using Monte Carlo techniques. Our perturbative construction encodes time-evolved quantum states of spin-1/2 systems in a network of classical spins with local couplings and can be directly generalized to other spin systems and higher spins. Using this construction we compute the transient dynamics in one, two, and three dimensions including local observables, entanglement production, and Loschmidt amplitudes using Monte Carlo algorithms and demonstrate the accuracy of this approach by comparisons to exact results. We include a mapping to equivalent artificial neural networks, which were recently introduced to provide a universal structure for classical network wave functions.

  11. Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

    Science.gov (United States)

    Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

    2018-01-01

    This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

  12. Feasible sampling plan for Bemisia tabaci control decision-making in watermelon fields.

    Science.gov (United States)

    Lima, Carlos Ho; Sarmento, Renato A; Pereira, Poliana S; Galdino, Tarcísio Vs; Santos, Fábio A; Silva, Joedna; Picanço, Marcelo C

    2017-11-01

    The silverleaf whitefly Bemisia tabaci is one of the most important pests of watermelon fields worldwide. Conventional sampling plans are the starting point for the generation of decision-making systems of integrated pest management programs. The aim of this study was to determine a conventional sampling plan for B. tabaci in watermelon fields. The optimal leaf for B. tabaci adult sampling was the 6 th most apical leaf. Direct counting was the best pest sampling technique. Crop pest densities fitted the negative binomial distribution and had a common aggregation parameter (K common ). The sampling plan consisted of evaluating 103 samples per plot. This sampling plan was conducted for 56 min, costing US$ 2.22 per sampling and with a 10% maximum evaluation error. The sampling plan determined in this study can be adopted by farmers because it enables the adequate evaluation of B. tabaci populations in watermelon fields (10% maximum evaluation error) and is a low-cost (US$ 2.22 per sampling), fast (56 min per sampling) and feasible (because it may be used in a standardized way throughout the crop cycle) technique. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  13. Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks

    Science.gov (United States)

    Pukrittayakamee, A.; Malshe, M.; Hagan, M.; Raff, L. M.; Narulkar, R.; Bukkapatnum, S.; Komanduri, R.

    2009-04-01

    An improved neural network (NN) approach is presented for the simultaneous development of accurate potential-energy hypersurfaces and corresponding force fields that can be utilized to conduct ab initio molecular dynamics and Monte Carlo studies on gas-phase chemical reactions. The method is termed as combined function derivative approximation (CFDA). The novelty of the CFDA method lies in the fact that although the NN has only a single output neuron that represents potential energy, the network is trained in such a way that the derivatives of the NN output match the gradient of the potential-energy hypersurface. Accurate force fields can therefore be computed simply by differentiating the network. Both the computed energies and the gradients are then accurately interpolated using the NN. This approach is superior to having the gradients appear in the output layer of the NN because it greatly simplifies the required architecture of the network. The CFDA permits weighting of function fitting relative to gradient fitting. In every test that we have run on six different systems, CFDA training (without a validation set) has produced smaller out-of-sample testing error than early stopping (with a validation set) or Bayesian regularization (without a validation set). This indicates that CFDA training does a better job of preventing overfitting than the standard methods currently in use. The training data can be obtained using an empirical potential surface or any ab initio method. The accuracy and interpolation power of the method have been tested for the reaction dynamics of H+HBr using an analytical potential. The results show that the present NN training technique produces more accurate fits to both the potential-energy surface as well as the corresponding force fields than the previous methods. The fitting and interpolation accuracy is so high (rms error=1.2 cm-1) that trajectories computed on the NN potential exhibit point-by-point agreement with corresponding

  14. Rock property estimates using multiple seismic attributes and neural networks; Pegasus Field, West Texas

    Energy Technology Data Exchange (ETDEWEB)

    Schuelke, J.S.; Quirein, J.A.; Sarg, J.F.

    1998-12-31

    This case study shows the benefit of using multiple seismic trace attributes and the pattern recognition capabilities of neural networks to predict reservoir architecture and porosity distribution in the Pegasus Field, West Texas. The study used the power of neural networks to integrate geologic, borehole and seismic data. Illustrated are the improvements between the new neural network approach and the more traditional method of seismic trace inversion for porosity estimation. Comprehensive statistical methods and interpretational/subjective measures are used in the prediction of porosity from seismic attributes. A 3-D volume of seismic derived porosity estimates for the Devonian reservoir provide a very detailed estimate of porosity, both spatially and vertically, for the field. The additional reservoir porosity detail provided, between the well control, allows for optimal placement of horizontal wells and improved field development. 6 refs., 2 figs.

  15. Sampling atmospheric pesticides with SPME: Laboratory developments and field study

    International Nuclear Information System (INIS)

    Wang Junxia; Tuduri, Ludovic; Mercury, Maud; Millet, Maurice; Briand, Olivier; Montury, Michel

    2009-01-01

    To estimate the atmospheric exposure of the greenhouse workers to pesticides, solid phase microextraction (SPME) was used under non-equilibrium conditions. Using Fick's law of diffusion, the concentrations of pesticides in the greenhouse can be calculated using pre-determined sampling rates (SRs). Thus the sampling rates (SRs) of two modes of SPME in the lab and in the field were determined and compared. The SRs for six pesticides in the lab were 20.4-48.3 mL min -1 for the exposed fiber and 0.166-0.929 mL min -1 for the retracted fiber. In field sampling, two pesticides, dichlorvos and cyprodinil were detected with exposed SPME. SR with exposed SPME for dichlorvos in the field (32.4 mL min -1 ) was consistent with that in the lab (34.5 mL min -1 ). SR for dichlorvos in the field (32.4 mL min -1 ) was consistent with that in the lab (34.5 mL min -1 ). The trends of temporal concentration and the inhalation exposure were also obtained. - SPME was proved to be a powerful and simple tool for determining pesticides' atmospheric concentration

  16. Social network analysis of Iranian researchers in the field of violence.

    Science.gov (United States)

    Salamati, Payman; Soheili, Faramarz

    2016-10-01

    The social network analysis (SNA) is a paradigm for analyzing structural patterns in social re- lations, testing knowledge sharing process and identifying bottlenecks of information flow. The purpose of this study was to determine the status of research in the fleld of violence in Iran using SNA. Research population included all the papers with at least one Iranian affiliation published in violence fleld indexed in SCIE, PubMed and Scopus databases. The co-word maps, co-authorship network and structural holes were drawn using related software. In the next step, the active authors and some measures of our network including degree centrality (DC), closeness, eigenvector, betweeness, density, diameter, compactness and size of the main component were assessed. Likewise, the trend of the published articles was evaluated based on the number of documents and their citations from 1972 to 2014. Five hundred and seventy one records were obtained. The five main clusters and hot spots were mental health, violence, war, psychiatric disorders and suicide. The co-authorship network was complex, tangled and scale free. The top nine authors with cut point role and top ten active authors were identified. The mean (standard deviation) of normalized DC, closeness, eigenvector and betweeness were 0.449 (0.805), 0.609 (0.214), 2.373 (7.353) and 0.338 (1.122), respectively. The density, diameter and mean compactness of our co-authorship network were 0.0494, 3.955 and 0.125, respectively. The main component consisted of 216 nodes that formed 17% of total size of the network. Both the number of the documents and their citations has increased in the field of violence in the recent years. Although the number of the documents has recently increased in the field of violence, the information flow is slow and there are not many relations among the authors in the network. However, the active authors have ability to influence the flow of knowledge within the network.

  17. An introduction to neural networks surgery, a field of neuromodulation which is based on advances in neural networks science and digitised brain imaging.

    Science.gov (United States)

    Sakas, D E; Panourias, I G; Simpson, B A

    2007-01-01

    Operative Neuromodulation is the field of altering electrically or chemically the signal transmission in the nervous system by implanted devices in order to excite, inhibit or tune the activities of neurons or neural networks and produce therapeutic effects. The present article reviews relevant literature on procedures or devices applied either in contact with the cerebral cortex or cranial nerves or in deep sites inside the brain in order to treat various refractory neurological conditions such as: a) chronic pain (facial, somatic, deafferentation, phantom limb), b) movement disorders (Parkinson's disease, dystonia, Tourette syndrome), c) epilepsy, d) psychiatric disease, e) hearing deficits, and f) visual loss. These data indicate that in operative neuromodulation, a new field emerges that is based on neural networks research and on advances in digitised stereometric brain imaging which allow precise localisation of cerebral neural networks and their relay stations; this field can be described as Neural networks surgery because it aims to act extrinsically or intrinsically on neural networks and to alter therapeutically the neural signal transmission with the use of implantable electrical or electronic devices. The authors also review neurotechnology literature relevant to neuroengineering, nanotechnologies, brain computer interfaces, hybrid cultured probes, neuromimetics, neuroinformatics, neurocomputation, and computational neuromodulation; the latter field is dedicated to the study of the biophysical and mathematical characteristics of electrochemical neuromodulation. The article also brings forward particularly interesting lines of research such as the carbon nanofibers electrode arrays for simultaneous electrochemical recording and stimulation, closed-loop systems for responsive neuromodulation, and the intracortical electrodes for restoring hearing or vision. The present review of cerebral neuromodulatory procedures highlights the transition from the

  18. Field effect control of electro-osmotic flow in microfluidic networks

    NARCIS (Netherlands)

    van der Wouden, E.J.

    2006-01-01

    This thesis describes the development of a Field Effect Flow Control (FEFC) system for the control of Electro Osmotic Flow (EOF) in microfluidic networks. For this several aspects of FEFC have been reviewed and a process to fabricate microfluidic channels with integrated electrodes has been

  19. Field-theoretic approach to fluctuation effects in neural networks

    International Nuclear Information System (INIS)

    Buice, Michael A.; Cowan, Jack D.

    2007-01-01

    A well-defined stochastic theory for neural activity, which permits the calculation of arbitrary statistical moments and equations governing them, is a potentially valuable tool for theoretical neuroscience. We produce such a theory by analyzing the dynamics of neural activity using field theoretic methods for nonequilibrium statistical processes. Assuming that neural network activity is Markovian, we construct the effective spike model, which describes both neural fluctuations and response. This analysis leads to a systematic expansion of corrections to mean field theory, which for the effective spike model is a simple version of the Wilson-Cowan equation. We argue that neural activity governed by this model exhibits a dynamical phase transition which is in the universality class of directed percolation. More general models (which may incorporate refractoriness) can exhibit other universality classes, such as dynamic isotropic percolation. Because of the extremely high connectivity in typical networks, it is expected that higher-order terms in the systematic expansion are small for experimentally accessible measurements, and thus, consistent with measurements in neocortical slice preparations, we expect mean field exponents for the transition. We provide a quantitative criterion for the relative magnitude of each term in the systematic expansion, analogous to the Ginsburg criterion. Experimental identification of dynamic universality classes in vivo is an outstanding and important question for neuroscience

  20. Workshop on Thermal Field Theory to Neural Networks

    CERN Document Server

    Veneziano, Gabriele; Aurenche, Patrick

    1996-01-01

    Tanguy Altherr was a Fellow in the Theory Division at CERN, on leave from LAPP (CNRS) Annecy. At the time of his accidental death in July 1994, he was only 31.A meeting was organized at CERN, covering the various aspects of his scientific interests: thermal field theory and its applications to hot or dense media, neural networks and its applications to high energy data analysis. Speakers were among his closest collaborators and friends.

  1. Robust segmentation of medical images using competitive hop field neural network as a clustering tool

    International Nuclear Information System (INIS)

    Golparvar Roozbahani, R.; Ghassemian, M. H.; Sharafat, A. R.

    2001-01-01

    This paper presents the application of competitive Hop field neural network for medical images segmentation. Our proposed approach consists of Two steps: 1) translating segmentation of the given medical image into an optimization problem, and 2) solving this problem by a version of Hop field network known as competitive Hop field neural network. Segmentation is considered as a clustering problem and its validity criterion is based on both intra set distance and inter set distance. The algorithm proposed in this paper is based on gray level features only. This leads to near optimal solutions if both intra set distance and inter set distance are considered at the same time. If only one of these distances is considered, the result of segmentation process by competitive Hop field neural network will be far from optimal solution and incorrect even for very simple cases. Furthermore, sometimes the algorithm receives at unacceptable states. Both these problems may be solved by contributing both in tera distance and inter distances in the segmentation (optimization) process. The performance of the proposed algorithm is tested on both phantom and real medical images. The promising results and the robustness of algorithm to system noises show near optimal solutions

  2. Mean-field approach to evolving spatial networks, with an application to osteocyte network formation

    Science.gov (United States)

    Taylor-King, Jake P.; Basanta, David; Chapman, S. Jonathan; Porter, Mason A.

    2017-07-01

    We consider evolving networks in which each node can have various associated properties (a state) in addition to those that arise from network structure. For example, each node can have a spatial location and a velocity, or it can have some more abstract internal property that describes something like a social trait. Edges between nodes are created and destroyed, and new nodes enter the system. We introduce a "local state degree distribution" (LSDD) as the degree distribution at a particular point in state space. We then make a mean-field assumption and thereby derive an integro-partial differential equation that is satisfied by the LSDD. We perform numerical experiments and find good agreement between solutions of the integro-differential equation and the LSDD from stochastic simulations of the full model. To illustrate our theory, we apply it to a simple model for osteocyte network formation within bones, with a view to understanding changes that may take place during cancer. Our results suggest that increased rates of differentiation lead to higher densities of osteocytes, but with a smaller number of dendrites. To help provide biological context, we also include an introduction to osteocytes, the formation of osteocyte networks, and the role of osteocytes in bone metastasis.

  3. Mean-field modeling approach for understanding epidemic dynamics in interconnected networks

    International Nuclear Information System (INIS)

    Zhu, Guanghu; Fu, Xinchu; Tang, Qinggan; Li, Kezan

    2015-01-01

    Modern systems (e.g., social, communicant, biological networks) are increasingly interconnected each other formed as ‘networks of networks’. Such complex systems usually possess inconsistent topologies and permit agents distributed in different subnetworks to interact directly/indirectly. Corresponding dynamics phenomena, such as the transmission of information, power, computer virus and disease, would exhibit complicated and heterogeneous tempo-spatial patterns. In this paper, we focus on the scenario of epidemic spreading in interconnected networks. We intend to provide a typical mean-field modeling framework to describe the time-evolution dynamics, and offer some mathematical skills to study the spreading threshold and the global stability of the model. Integrating the research with numerical analysis, we are able to quantify the effects of networks structure and epidemiology parameters on the transmission dynamics. Interestingly, we find that the diffusion transition in the whole network is governed by a unique threshold, which mainly depends on the most heterogenous connection patterns of network substructures. Further, the dynamics is highly sensitive to the critical values of cross infectivity with switchable phases.

  4. Radiofrequency Field Distribution Assessment in Indoor Areas Covered by Wireless Local Area Network

    Directory of Open Access Journals (Sweden)

    HELBET, R.

    2009-02-01

    Full Text Available Electromagnetic environment becomes day by day more congested. Radio communication systems in the short range are now part of everyday life, and there is a need to also assess the pollution level due to their emission if we take into account human health and protection. There is consistent scientific evidence that environmental electromagnetic field may cause undesirable biological effects or even health hazards. Present paper aims at giving a view on exposure level due to wireless local area networks (WLAN emission solely, as part of environmental radiofrequency pollution. Highly accurate measurements were made indoor by using a frequency-selective measurement system and identifying the correct settings for an error-minimum assessment. We focused on analysis of the electric flux density distribution inside a room, in the far field of the emitting antennas, in case of a single network communication channel. We analyze the influence the network configuration parameters have on the field level. Distance from the source and traffic rate are also important parameters that affect the exposure level. Our measurements indicate that in the immediate vicinity of the WLAN stations the average field may reach as much as 13% from the present accepted reference levels given in the human exposure standards.

  5. Quantum communication network utilizing quadripartite entangled states of optical field

    International Nuclear Information System (INIS)

    Shen Heng; Su Xiaolong; Jia Xiaojun; Xie Changde

    2009-01-01

    We propose two types of quantum dense coding communication networks with optical continuous variables, in which a quadripartite entangled state of the optical field with totally three-party correlations of quadrature amplitudes is utilized. In the networks, the exchange of information between any two participants can be manipulated by one or two of the remaining participants. The channel capacities for a variety of communication protocols are numerically calculated. Due to the fact that the quadripartite entangled states applied in the communication systems have been successfully prepared already in the laboratory, the proposed schemes are experimentally accessible at present.

  6. Chimeralike states in networks of bistable time-delayed feedback oscillators coupled via the mean field.

    Science.gov (United States)

    Ponomarenko, V I; Kulminskiy, D D; Prokhorov, M D

    2017-08-01

    We study the collective dynamics of oscillators in a network of identical bistable time-delayed feedback systems globally coupled via the mean field. The influence of delay and inertial properties of the mean field on the collective behavior of globally coupled oscillators is investigated. A variety of oscillation regimes in the network results from the presence of bistable states with substantially different frequencies in coupled oscillators. In the physical experiment and numerical simulation we demonstrate the existence of chimeralike states, in which some of the oscillators in the network exhibit synchronous oscillations, while all other oscillators remain asynchronous.

  7. Norm in soil and sludge samples in Dukhan oil Field, Qatar state

    Energy Technology Data Exchange (ETDEWEB)

    Al-Kinani, A.T.; Hushari, M.; Al-Sulaiti, Huda; Alsadig, I.A., E-mail: mmhushari@moe.gov.qa [Radiation and Chemical Protection Department, Ministry of Environment, Doha (Qatar)

    2015-07-01

    The main objective of this work is to measure the activity concentrations of Naturally Occurring radioactive Materials (NORM) produced as a buy products in oil production. The analyses of NORM give available information for guidelines concerning radiation protection. Recently NORM subjected to restricted regulation issued by high legal authority at Qatar state. Twenty five samples of soil from Dukhan onshore oil field and 10 sludge samples collected from 2 offshore fields at Qatar state. High resolution low-level gamma-ray spectrometry used to measure gamma emitters of NORM. The activity concentrations of natural radionuclide in 22 samples from Dukhan oil field, were with average worldwide values . Only three soil samples have high activity concentration of Ra-226 which is more than 185 Bq/kg the exempted level for NORM in the Quatrain regulation. The natural radionuclide activity concentrations of 10 sludge samples from offshore oil fields was greater than 1100Bq/kg the exempted values of NORM set by Quatrain regulation so the sludge need special treatments. The average hazards indices (H{sub ex} , D , and Ra{sub eq}), for the 22 samples were below the word permissible values .This means that the human exposure to such material not impose any radiation risk. The average hazards indices (H{sub ex} , D , and Ra{sub eq}), for 3 soil samples and sludge samples are higher than the published maximal permissible. Thus human exposure to such material impose radiation risk. (author)

  8. Norm in soil and sludge samples in Dukhan oil Field, Qatar state

    International Nuclear Information System (INIS)

    Al-Kinani, A.T.; Hushari, M.; Al-Sulaiti, Huda; Alsadig, I.A.

    2015-01-01

    The main objective of this work is to measure the activity concentrations of Naturally Occurring radioactive Materials (NORM) produced as a buy products in oil production. The analyses of NORM give available information for guidelines concerning radiation protection. Recently NORM subjected to restricted regulation issued by high legal authority at Qatar state. Twenty five samples of soil from Dukhan onshore oil field and 10 sludge samples collected from 2 offshore fields at Qatar state. High resolution low-level gamma-ray spectrometry used to measure gamma emitters of NORM. The activity concentrations of natural radionuclide in 22 samples from Dukhan oil field, were with average worldwide values . Only three soil samples have high activity concentration of Ra-226 which is more than 185 Bq/kg the exempted level for NORM in the Quatrain regulation. The natural radionuclide activity concentrations of 10 sludge samples from offshore oil fields was greater than 1100Bq/kg the exempted values of NORM set by Quatrain regulation so the sludge need special treatments. The average hazards indices (H ex , D , and Ra eq ), for the 22 samples were below the word permissible values .This means that the human exposure to such material not impose any radiation risk. The average hazards indices (H ex , D , and Ra eq ), for 3 soil samples and sludge samples are higher than the published maximal permissible. Thus human exposure to such material impose radiation risk. (author)

  9. Flight Vehicle Control and Aerobiological Sampling Applications

    OpenAIRE

    Techy, Laszlo

    2009-01-01

    Aerobiological sampling using unmanned aerial vehicles (UAVs) is an exciting research field blending various scientific and engineering disciplines. The biological data collected using UAVs helps to better understand the atmospheric transport of microorganisms. Autopilot-equipped UAVs can accurately sample along pre-defined flight plans and precisely regulated altitudes. They can provide even greater utility when they are networked together in coordinated sampling missions: such measurements ...

  10. 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.

  11. Experimental study on the luminous radiation associated to the field emission of samples submitted to high RF fields

    International Nuclear Information System (INIS)

    Maissa, S.; Junquera, T.; Fouaidy, M.; Le Goff, A.; Luong, M.; Tan, J.; Bonin, B.; Safa, H.

    1996-01-01

    The accelerating gradient of the RF cavities is limited by the strong field emission (FE) of electrons stemming from the metallic walls. Previous experiments evidenced luminous radiations associated with electron emission of cathodes subjected to intense DC electric field. These observations invoked the proposal of new theoretical models of the field emission phenomenon. This experimental study extends the previous DC works to the RF case. A special copper RF cavity has been developed equipped with an optical window and a removable sample. It has been designed for measuring both electron current and luminous radiation emitted by the sample, subjected to maximum RF electric field. The optical apparatus attached to the cavity permits to characterize the radiation in terms of intensity, glowing duration and spectral distribution. The results concerning different niobium or copper samples, whom top was either scratched or intentionally contaminated with metallic or dielectric particles are summarized. (author)

  12. How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

    Science.gov (United States)

    Grabska-Barwińska, Agnieszka; Latham, Peter E

    2014-06-01

    We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.

  13. Noisy mean field game model for malware propagation in opportunistic networks

    KAUST Repository

    Tembine, Hamidou; Vilanova, Pedro; Debbah, Mé roú ane

    2012-01-01

    nodes is examined with a noisy mean field limit and compared to a deterministic one. The stochastic nature of the wireless environment make stochastic approaches more realistic for such types of networks. By introducing control strategies, we show

  14. Field and long-term demonstration of a wide area quantum key distribution network.

    Science.gov (United States)

    Wang, Shuang; Chen, Wei; Yin, Zhen-Qiang; Li, Hong-Wei; He, De-Yong; Li, Yu-Hu; Zhou, Zheng; Song, Xiao-Tian; Li, Fang-Yi; Wang, Dong; Chen, Hua; Han, Yun-Guang; Huang, Jing-Zheng; Guo, Jun-Fu; Hao, Peng-Lei; Li, Mo; Zhang, Chun-Mei; Liu, Dong; Liang, Wen-Ye; Miao, Chun-Hua; Wu, Ping; Guo, Guang-Can; Han, Zheng-Fu

    2014-09-08

    A wide area quantum key distribution (QKD) network deployed on communication infrastructures provided by China Mobile Ltd. is demonstrated. Three cities and two metropolitan area QKD networks were linked up to form the Hefei-Chaohu-Wuhu wide area QKD network with over 150 kilometers coverage area, in which Hefei metropolitan area QKD network was a typical full-mesh core network to offer all-to-all interconnections, and Wuhu metropolitan area QKD network was a representative quantum access network with point-to-multipoint configuration. The whole wide area QKD network ran for more than 5000 hours, from 21 December 2011 to 19 July 2012, and part of the network stopped until last December. To adapt to the complex and volatile field environment, the Faraday-Michelson QKD system with several stability measures was adopted when we designed QKD devices. Through standardized design of QKD devices, resolution of symmetry problem of QKD devices, and seamless switching in dynamic QKD network, we realized the effective integration between point-to-point QKD techniques and networking schemes.

  15. Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

    Science.gov (United States)

    La, Hung Manh; Sheng, Weihua

    2013-04-01

    In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

  16. Magnetic fields in a residential neighbourhood by network analysis and field calculation

    International Nuclear Information System (INIS)

    Mader, D.L.

    1992-01-01

    A magnetic field research facility has been used for validation of a method to compute 60-Hz magnetic fields in a residential neighbourhood. Network analysis is used to solve for currents in a mathematical model of the electric power distribution system including grounding conductors and metallic water supply pipes. Then, magnetic fields are calculated using the currents and the locations of all conductors. The critical role of joint resistance was highlighted by this study as follows. With initial estimates of resistances in the model, a fitting algorithm was able to obtain excellent agreement between the model and measurements, and provide confidence in its predictive capability. Simulations are then done to illustrate the effects of a poor joint, multiple unbalanced loads, heavy balanced loads, a heavy feeder line going through the neighbourhood, injection of current into the local neutral from an adjacent neighbourhood, use of plastic water pipes instead of metal, wet soil, increasing the distance from the power line, changing from twisted wires to an open secondary bus, and primary current loops caused by poor joints in the interconnected system neutral. 8 refs., 24 figs., 8 tabs

  17. Experimental study on the luminous radiation associated to the field emission of samples submitted to high RF fields

    International Nuclear Information System (INIS)

    Maissa, S.; Junquera, T.; Fouaidy, M.; Le Goff, A.; Luong, M.; Tan, J.; Bonin, B.; Safa, H.

    1996-01-01

    Nowadays the accelerating gradient of the RF cavities is limited by the strong field emission (FE) of electrons stemming from the metallic walls. Previous experiments evidenced luminous radiations associated with electron emission on cathodes subjected to intense DC electric field. These observations led these authors to propose new theoretical models of the field emission phenomenon. The presented experimental study extends these previous DC works to the RF case. A special copper RF cavity has been developed equipped with an optical window and a removable sample. It has been designed for measuring both electron current and luminous radiation emitted by the sample, subjected to maximum RF electric field. The optical apparatus attached to the cavity permits to characterize the radiation in terms of intensity, glowing duration and spectral distribution. The results concerning different niobium or copper samples, whom top was either scratched or intentionally contaminated with metallic or dielectric particles are summarized. (author)

  18. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

    Science.gov (United States)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

    2016-12-01

    With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

  19. Adaptive sampling rate control for networked systems based on statistical characteristics of packet disordering.

    Science.gov (United States)

    Li, Jin-Na; Er, Meng-Joo; Tan, Yen-Kheng; Yu, Hai-Bin; Zeng, Peng

    2015-09-01

    This paper investigates an adaptive sampling rate control scheme for networked control systems (NCSs) subject to packet disordering. The main objectives of the proposed scheme are (a) to avoid heavy packet disordering existing in communication networks and (b) to stabilize NCSs with packet disordering, transmission delay and packet loss. First, a novel sampling rate control algorithm based on statistical characteristics of disordering entropy is proposed; secondly, an augmented closed-loop NCS that consists of a plant, a sampler and a state-feedback controller is transformed into an uncertain and stochastic system, which facilitates the controller design. Then, a sufficient condition for stochastic stability in terms of Linear Matrix Inequalities (LMIs) is given. Moreover, an adaptive tracking controller is designed such that the sampling period tracks a desired sampling period, which represents a significant contribution. Finally, experimental results are given to illustrate the effectiveness and advantages of the proposed scheme. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Field desorption and field ion surface studies of samples exposed to the plasmas of PLT and ISX

    International Nuclear Information System (INIS)

    Kellogg, G.L.; Panitz, J.A.

    1978-01-01

    Modifications to the surface of field-ion specimens exposed to plasma discharges in PLT and ISX determined by Imaging Probe, Field Ion Microscope, and Transmission Electron Microscope analysis have in the past shown several consistent features. Surface films consisting primarily of limiter material with trapped plasma and impurity species have been found to reside on samples with direct line of sight exposure to the plasma during the discharges. Control specimens placed in the tokamak, but shielded from the plasma, on the other hand, remained free of deposits. When exposed to only high power plasma discharges, samples placed at the wall position in PLT and ISX have survived the exposures with no evidence of damage or implantation. In this paper we describe the results of a recent exposure in PLT in which for the first time samples of stainless steel were included for High-Field Surface Analysis. Tokamak operating conditions, including stainless-steel limiters, titanium gettering between discharges, and the occurrence of a disruption, also distinguished this exposure from those carried out previously. Surprisingly, even with stainless-steel limiters, carbon films were found to be deposited on the samples at a rate

  1. Moving your laboratories to the field – Advantages and limitations of the use of field portable instruments in environmental sample analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gałuszka, Agnieszka, E-mail: Agnieszka.Galuszka@ujk.edu.pl [Geochemistry and the Environment Division, Institute of Chemistry, Jan Kochanowski University, 15G Świętokrzyska St., 25-406 Kielce (Poland); Migaszewski, Zdzisław M. [Geochemistry and the Environment Division, Institute of Chemistry, Jan Kochanowski University, 15G Świętokrzyska St., 25-406 Kielce (Poland); Namieśnik, Jacek [Department of Analytical Chemistry, Chemical Faculty, Gdańsk University of Technology (GUT), 11/12 G. Narutowicz St., 80-233 Gdańsk (Poland)

    2015-07-15

    The recent rapid progress in technology of field portable instruments has increased their applications in environmental sample analysis. These instruments offer a possibility of cost-effective, non-destructive, real-time, direct, on-site measurements of a wide range of both inorganic and organic analytes in gaseous, liquid and solid samples. Some of them do not require the use of reagents and do not produce any analytical waste. All these features contribute to the greenness of field portable techniques. Several stationary analytical instruments have their portable versions. The most popular ones include: gas chromatographs with different detectors (mass spectrometer (MS), flame ionization detector, photoionization detector), ultraviolet–visible and near-infrared spectrophotometers, X-ray fluorescence spectrometers, ion mobility spectrometers, electronic noses and electronic tongues. The use of portable instruments in environmental sample analysis gives a possibility of on-site screening and a subsequent selection of samples for routine laboratory analyses. They are also very useful in situations that require an emergency response and for process monitoring applications. However, quantification of results is still problematic in many cases. The other disadvantages include: higher detection limits and lower sensitivity than these obtained in laboratory conditions, a strong influence of environmental factors on the instrument performance and a high possibility of sample contamination in the field. This paper reviews recent applications of field portable instruments in environmental sample analysis and discusses their analytical capabilities. - Highlights: • Field portable instruments are widely used in environmental sample analysis. • Field portable instruments are indispensable for analysis in emergency response. • Miniaturization of field portable instruments reduces resource consumption. • In situ analysis is in agreement with green analytical chemistry

  2. Moving your laboratories to the field – Advantages and limitations of the use of field portable instruments in environmental sample analysis

    International Nuclear Information System (INIS)

    Gałuszka, Agnieszka; Migaszewski, Zdzisław M.; Namieśnik, Jacek

    2015-01-01

    The recent rapid progress in technology of field portable instruments has increased their applications in environmental sample analysis. These instruments offer a possibility of cost-effective, non-destructive, real-time, direct, on-site measurements of a wide range of both inorganic and organic analytes in gaseous, liquid and solid samples. Some of them do not require the use of reagents and do not produce any analytical waste. All these features contribute to the greenness of field portable techniques. Several stationary analytical instruments have their portable versions. The most popular ones include: gas chromatographs with different detectors (mass spectrometer (MS), flame ionization detector, photoionization detector), ultraviolet–visible and near-infrared spectrophotometers, X-ray fluorescence spectrometers, ion mobility spectrometers, electronic noses and electronic tongues. The use of portable instruments in environmental sample analysis gives a possibility of on-site screening and a subsequent selection of samples for routine laboratory analyses. They are also very useful in situations that require an emergency response and for process monitoring applications. However, quantification of results is still problematic in many cases. The other disadvantages include: higher detection limits and lower sensitivity than these obtained in laboratory conditions, a strong influence of environmental factors on the instrument performance and a high possibility of sample contamination in the field. This paper reviews recent applications of field portable instruments in environmental sample analysis and discusses their analytical capabilities. - Highlights: • Field portable instruments are widely used in environmental sample analysis. • Field portable instruments are indispensable for analysis in emergency response. • Miniaturization of field portable instruments reduces resource consumption. • In situ analysis is in agreement with green analytical chemistry

  3. Field sampling of residual aviation gasoline in sandy soil

    International Nuclear Information System (INIS)

    Ostendorf, D.W.; Hinlein, E.S.; Yuefeng, Xie; Leach, L.E.

    1991-01-01

    Two complementary field sampling methods for the determination of residual aviation gasoline content in the contaminated capillary fringe of a fine, uniform, sandy soil were investigated. The first method featured field extrusion of core barrels into pint-size Mason jars, while the second consisted of laboratory partitioning of intact stainless steel core sleeves. Soil samples removed from the Mason jars (in the field) and sleeve segments (in the laboratory) were subjected to methylene chloride extraction and gas chromatographic analysis to compare their aviation gasoline content. The barrel extrusion sampling method yielded a vertical profile with 0.10m resolution over an essentially continuous 5.0m interval from the ground surface to the water table. The sleeve segment alternative yielded a more resolved 0.03m vertical profile over a shorter 0.8m interval through the capillary fringe. The two methods delivered precise estimates of the vertically integrated mass of aviation gasoline at a given horizontal location, and a consistent view of the vertical profile as well. In the latter regard, a 0.2m thick lens of maximum contamination was found in the center of the capillary fringe, where moisture filled all voids smaller than the mean pore size. The maximum peak was resolved by the core sleeve data, but was partially obscured by the barrel extrusion observations, so that replicate barrels or a half-pint Mason jar size should be considered for data supporting vertical transport analyses in the absence of sleeve partitions

  4. Identification of driving network of cellular differentiation from single sample time course gene expression data

    Science.gov (United States)

    Chen, Ye; Wolanyk, Nathaniel; Ilker, Tunc; Gao, Shouguo; Wang, Xujing

    Methods developed based on bifurcation theory have demonstrated their potential in driving network identification for complex human diseases, including the work by Chen, et al. Recently bifurcation theory has been successfully applied to model cellular differentiation. However, there one often faces a technical challenge in driving network prediction: time course cellular differentiation study often only contains one sample at each time point, while driving network prediction typically require multiple samples at each time point to infer the variation and interaction structures of candidate genes for the driving network. In this study, we investigate several methods to identify both the critical time point and the driving network through examination of how each time point affects the autocorrelation and phase locking. We apply these methods to a high-throughput sequencing (RNA-Seq) dataset of 42 subsets of thymocytes and mature peripheral T cells at multiple time points during their differentiation (GSE48138 from GEO). We compare the predicted driving genes with known transcription regulators of cellular differentiation. We will discuss the advantages and limitations of our proposed methods, as well as potential further improvements of our methods.

  5. Sampling of high amounts of bioaerosols using a high-volume electrostatic field sampler

    DEFF Research Database (Denmark)

    Madsen, A. M.; Sharma, Anoop Kumar

    2008-01-01

    For studies of the biological effects of bioaerosols, large samples are necessary. To be able to sample enough material and to cover the variations in aerosol content during and between working days, a long sampling time is necessary. Recently, a high-volume transportable electrostatic field...... and 315 mg dust (net recovery of the lyophilized dust) was sampled during a period of 7 days, respectively. The sampling rates of the electrostatic field samplers were between 1.34 and 1.96 mg dust per hour, the value for the Gravikon was between 0.083 and 0.108 mg dust per hour and the values for the GSP...... samplers were between 0.0031 and 0.032 mg dust per hour. The standard deviations of replica samplings and the following microbial analysis using the electrostatic field sampler and GSP samplers were at the same levels. The exposure to dust in the straw storage was 7.7 mg m(-3) when measured...

  6. A simplified field protocol for genetic sampling of birds using buccal swabs

    Science.gov (United States)

    Vilstrup, Julia T.; Mullins, Thomas D.; Miller, Mark P.; McDearman, Will; Walters, Jeffrey R.; Haig, Susan M.

    2018-01-01

    DNA sampling is an essential prerequisite for conducting population genetic studies. For many years, blood sampling has been the preferred method for obtaining DNA in birds because of their nucleated red blood cells. Nonetheless, use of buccal swabs has been gaining favor because they are less invasive yet still yield adequate amounts of DNA for amplifying mitochondrial and nuclear markers; however, buccal swab protocols often include steps (e.g., extended air-drying and storage under frozen conditions) not easily adapted to field settings. Furthermore, commercial extraction kits and swabs for buccal sampling can be expensive for large population studies. We therefore developed an efficient, cost-effective, and field-friendly protocol for sampling wild birds after comparing DNA yield among 3 inexpensive buccal swab types (2 with foam tips and 1 with a cotton tip). Extraction and amplification success was high (100% and 97.2% respectively) using inexpensive generic swabs. We found foam-tipped swabs provided higher DNA yields than cotton-tipped swabs. We further determined that omitting a drying step and storing swabs in Longmire buffer increased efficiency in the field while still yielding sufficient amounts of DNA for detailed population genetic studies using mitochondrial and nuclear markers. This new field protocol allows time- and cost-effective DNA sampling of juveniles or small-bodied birds for which drawing blood may cause excessive stress to birds and technicians alike.

  7. The Channel Network model and field applications

    International Nuclear Information System (INIS)

    Khademi, B.; Moreno, L.; Neretnieks, I.

    1999-01-01

    The Channel Network model describes the fluid flow and solute transport in fractured media. The model is based on field observations, which indicate that flow and transport take place in a three-dimensional network of connected channels. The channels are generated in the model from observed stochastic distributions and solute transport is modeled taking into account advection and rock interactions, such as matrix diffusion and sorption within the rock. The most important site-specific data for the Channel Network model are the conductance distribution of the channels and the flow-wetted surface. The latter is the surface area of the rock in contact with the flowing water. These parameters may be estimated from hydraulic measurements. For the Aespoe site, several borehole data sets are available, where a packer distance of 3 meters was used. Numerical experiments were performed in order to study the uncertainties in the determination of the flow-wetted surface and conductance distribution. Synthetic data were generated along a borehole and hydraulic tests with different packer distances were simulated. The model has previously been used to study the Long-term Pumping and Tracer Test (LPT2) carried out in the Aespoe Hard Rock Laboratory (HRL) in Sweden, where the distance travelled by the tracers was of the order hundreds of meters. Recently, the model has been used to simulate the tracer tests performed in the TRUE experiment at HRL, with travel distance of the order of tens of meters. Several tracer tests with non-sorbing and sorbing species have been performed

  8. Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

    Science.gov (United States)

    Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

    2011-01-01

    An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717

  9. Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neurons.

    Directory of Open Access Journals (Sweden)

    Dejan Pecevski

    2011-12-01

    Full Text Available An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows ("explaining away" and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons.

  10. Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neurons.

    Science.gov (United States)

    Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

    2011-12-01

    An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows ("explaining away") and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons.

  11. Reconstruction of coupling architecture of neural field networks from vector time series

    Science.gov (United States)

    Sysoev, Ilya V.; Ponomarenko, Vladimir I.; Pikovsky, Arkady

    2018-04-01

    We propose a method of reconstruction of the network coupling matrix for a basic voltage-model of the neural field dynamics. Assuming that the multivariate time series of observations from all nodes are available, we describe a technique to find coupling constants which is unbiased in the limit of long observations. Furthermore, the method is generalized for reconstruction of networks with time-delayed coupling, including the reconstruction of unknown time delays. The approach is compared with other recently proposed techniques.

  12. [Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

    Science.gov (United States)

    Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

    2015-03-01

    Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

  13. Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

    Science.gov (United States)

    Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

    2018-05-01

    Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

  14. Sampling Design of Soil Physical Properties in a Conilon Coffee Field

    Directory of Open Access Journals (Sweden)

    Eduardo Oliveira de Jesus Santos

    Full Text Available ABSTRACT Establishing the number of samples required to determine values of soil physical properties ultimately results in optimization of labor and allows better representation of such attributes. The objective of this study was to analyze the spatial variability of soil physical properties in a Conilon coffee field and propose a soil sampling method better attuned to conditions of the management system. The experiment was performed in a Conilon coffee field in Espírito Santo state, Brazil, under a 3.0 × 2.0 × 1.0 m (4,000 plants ha-1 double spacing design. An irregular grid, with dimensions of 107 × 95.7 m and 65 sampling points, was set up. Soil samples were collected from the 0.00-0.20 m depth from each sampling point. Data were analyzed under descriptive statistical and geostatistical methods. Using statistical parameters, the adequate number of samples for analyzing the attributes under study was established, which ranged from 1 to 11 sampling points. With the exception of particle density, all soil physical properties showed a spatial dependence structure best fitted to the spherical model. Establishment of the number of samples and spatial variability for the physical properties of soils may be useful in developing sampling strategies that minimize costs for farmers within a tolerable and predictable level of error.

  15. A network of spiking neurons that can represent interval timing: mean field analysis.

    Science.gov (United States)

    Gavornik, Jeffrey P; Shouval, Harel Z

    2011-04-01

    Despite the vital importance of our ability to accurately process and encode temporal information, the underlying neural mechanisms are largely unknown. We have previously described a theoretical framework that explains how temporal representations, similar to those reported in the visual cortex, can form in locally recurrent cortical networks as a function of reward modulated synaptic plasticity. This framework allows networks of both linear and spiking neurons to learn the temporal interval between a stimulus and paired reward signal presented during training. Here we use a mean field approach to analyze the dynamics of non-linear stochastic spiking neurons in a network trained to encode specific time intervals. This analysis explains how recurrent excitatory feedback allows a network structure to encode temporal representations.

  16. Effects of Sample Size and Dimensionality on the Performance of Four Algorithms for Inference of Association Networks in Metabonomics

    NARCIS (Netherlands)

    Suarez Diez, M.; Saccenti, E.

    2015-01-01

    We investigated the effect of sample size and dimensionality on the performance of four algorithms (ARACNE, CLR, CORR, and PCLRC) when they are used for the inference of metabolite association networks. We report that as many as 100-400 samples may be necessary to obtain stable network estimations,

  17. Networked control systems with communication constraints :tradeoffs between sampling intervals, delays and performance

    NARCIS (Netherlands)

    Heemels, W.P.M.H.; Teel, A.R.; Wouw, van de N.; Nesic, D.

    2010-01-01

    There are many communication imperfections in networked control systems (NCS) such as varying transmission delays, varying sampling/transmission intervals, packet loss, communication constraints and quantization effects. Most of the available literature on NCS focuses on only some of these aspects,

  18. Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Hossein Bashashati

    2017-07-01

    Full Text Available Classification of EEG signals in self-paced Brain Computer Interfaces (BCI is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF. NNCRF is a combination of a neural network and conditional random field (CRF. As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF, and to two classical classifiers (Logistic Regression and Support Vector Machines. The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC of the BCI system.

  19. Activities of the senspol and NICOLE network concerning field investigation at contaminated sites

    Energy Technology Data Exchange (ETDEWEB)

    Ree, C.C.D.F. von [GeoDelft, AB Delft (Netherlands); Alcock, S. [Cranfield Univ. of Silsoe, Bedfordshire (United Kingdom)

    2003-07-01

    At a European level several networks can be identified aimed at developments and exchange of knowledge relevant to sustainable management of the subsurface. Based on the common interests in the field of site characterisation and monitoring the SENSPOL and NICOLE networks have established links resulting in cooperation in several project-activities. In this presentation two projects will be addressed: - Seville technicalmeeting (Aznacollar mining site). - Bridging gaps between sensor developers and (end) users in a pragmatic approach (GAPS-project). The goal of the Seville technical meeting was to apply the latest sensing technologies at a site contaminated by metal mining activities, to properly evaluate the advances and limitations in the monitoring of contaminated sites for sustainable land management and to determine further steps to commercial exploitation. Some 17 different instruments have been brought including: - Electrochemical sensors using different forms of anodic stripping voltammetry and constant current chronopotentiometry combined with several types of screen printed electrodes. - An amperometric biosensor using screen printed electrodes, which measures toxicity by inhibition effects on urease and its sensitive to Hg(II), Ag(I), Cu(I) and to a lesser extent to Pb(II), Zn(II) and Cd(II) and a selectrochemical DNA biosensor measuring overall toxicity. - A luminescent bacterial sensors for measuring the bioavailable fraction of Cd, Pb, Zn, Cu, As, and Hg, and a bioluminescent fiber optic sensor for Hg and As. - Toxicity testing instruments (Checklight 'ToxScreen Multi-Shot Test, ToxAlert {sup registered} 100 and ToxAlert {sup registered} 10) - A fieldprobe for pH, EC, TDS measurement - A lead automatic analyser AQUAMET using a ion-selective electrode. - Pulse-neutron borehole device in which interaction of neutrons with the surrounding medium can be used to monitor changes. In a two-day field session on the mining site participants were provided

  20. A comparative study of multilayer perceptron neural networks for the identification of rhubarb samples.

    Science.gov (United States)

    Zhang, Zhuoyong; Wang, Yamin; Fan, Guoqiang; Harrington, Peter de B

    2007-01-01

    Artificial neural networks have gained much attention in recent years as fast and flexible methods for quality control in traditional medicine. Near-infrared (NIR) spectroscopy has become an accepted method for the qualitative and quantitative analyses of traditional Chinese medicine since it is simple, rapid, and non-destructive. The present paper describes a method by which to discriminate official and unofficial rhubarb samples using three layer perceptron neural networks applied to NIR data. Multilayer perceptron neural networks were trained with back propagation, delta-bar-delta and quick propagation algorithms. Results obtained using these methods were all satisfactory, but the best outcomes were obtained with the delta-bar-delta algorithm.

  1. Astronaut Neil Armstrong studies rock samples during geological field trip

    Science.gov (United States)

    1969-01-01

    Astronaut Neil Armstrong, commander of the Apollo 11 lunar landing mission, studies rock samples during a geological field trip to the Quitman Mountains area near the Fort Quitman ruins in far west Texas.

  2. Uniform field loop-gap resonator and rectangular TEU02 for aqueous sample EPR at 94 GHz

    Science.gov (United States)

    Sidabras, Jason W.; Sarna, Tadeusz; Mett, Richard R.; Hyde, James S.

    2017-09-01

    In this work we present the design and implementation of two uniform-field resonators: a seven-loop-six-gap loop-gap resonator (LGR) and a rectangular TEU02 cavity resonator. Each resonator has uniform-field-producing end-sections. These resonators have been designed for electron paramagnetic resonance (EPR) of aqueous samples at 94 GHz. The LGR geometry employs low-loss Rexolite end-sections to improve the field homogeneity over a 3 mm sample region-of-interest from near-cosine distribution to 90% uniform. The LGR was designed to accommodate large degassable Polytetrafluorethylen (PTFE) tubes (0.81 mm O.D.; 0.25 mm I.D.) for aqueous samples. Additionally, field modulation slots are designed for uniform 100 kHz field modulation incident at the sample. Experiments using a point sample of lithium phthalocyanine (LiPC) were performed to measure both the uniformity of the microwave magnetic field and 100 kHz field modulation, and confirm simulations. The rectangular TEU02 cavity resonator employs over-sized end-sections with sample shielding to provide an 87% uniform field for a 0.1 × 2 × 6 mm3 sample geometry. An evanescent slotted window was designed for light access to irradiate 90% of the sample volume. A novel dual-slot iris was used to minimize microwave magnetic field perturbations and maintain cross-sectional uniformity. Practical EPR experiments using the application of light irradiated rose bengal (4,5,6,7-tetrachloro-2‧,4‧,5‧,7‧-tetraiodofluorescein) were performed in the TEU02 cavity. The implementation of these geometries providing a practical designs for uniform field resonators that continue resonator advancements towards quantitative EPR spectroscopy.

  3. Operable Unit 3-13, Group 3, Other Surface Soils (Phase II) Field Sampling Plan

    Energy Technology Data Exchange (ETDEWEB)

    G. L. Schwendiman

    2006-07-27

    This Field Sampling Plan describes the Operable Unit 3-13, Group 3, Other Surface Soils, Phase II remediation field sampling activities to be performed at the Idaho Nuclear Technology and Engineering Center located within the Idaho National Laboratory Site. Sampling activities described in this plan support characterization sampling of new sites, real-time soil spectroscopy during excavation, and confirmation sampling that verifies that the remedial action objectives and remediation goals presented in the Final Record of Decision for Idaho Nuclear Technology and Engineering Center, Operable Unit 3-13 have been met.

  4. Exploring the field of public construction clients by a graphical network analysis

    OpenAIRE

    Eisma, P.R.; Volker, L.

    2014-01-01

    Because public construction clients form the majority of construction clients and procure over 40% of the construction output in most countries, they are important actors in the construction industry. Yet, the field of research on clients is still underdeveloped. In order to identify the research gaps in this field, a graphical network analysis of existing literature is performed. The analysis is based on a query executed in the scientific database Scopus resulting in around 3,300 publication...

  5. Strain on field effect transistors with single–walled–carbon nanotube network on flexible substrate

    Energy Technology Data Exchange (ETDEWEB)

    Kim, T. G. [Samsung Advanced Institute of Technology, Research center for Time-domain Nano-functional Device, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Department of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713 (Korea, Republic of); Kim, U. J.; Lee, E. H. [Samsung Advanced Institute of Technology, Frontier Research Laboratory, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Hwang, J. S. [School of Advanced Materials Science and Engineering, SKKU Advanced Institute of Nanotechnology, Sungkyunkwan University, Suwon, Gyeonggi 440-746 (Korea, Republic of); Hwang, S. W., E-mail: swnano.hwang@samsung.com, E-mail: sangsig@korea.ac.kr [Samsung Advanced Institute of Technology, Research center for Time-domain Nano-functional Device, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Samsung Advanced Institute of Technology, Frontier Research Laboratory, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Kim, S., E-mail: swnano.hwang@samsung.com, E-mail: sangsig@korea.ac.kr [Department of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713 (Korea, Republic of)

    2013-12-07

    We have systematically analyzed the effect of strain on the electrical properties of flexible field effect transistors with a single-walled carbon nanotube (SWCNT) network on a polyethersulfone substrate. The strain was applied and estimated at the microscopic scale (<1 μm) by using scanning electron microscope (SEM) equipped with indigenously designed special bending jig. Interestingly, the strain estimated at the microscopic scale was found to be significantly different from the strain calculated at the macroscopic scale (centimeter-scale), by a factor of up to 4. Further in-depth analysis using SEM indicated that the significant difference in strain, obtained from two different measurement scales (microscale and macroscale), could be attributed to the formation of cracks and tears in the SWCNT network, or at the junction of SWCNT network and electrode during the strain process. Due to this irreversible morphological change, the electrical properties, such as on current level and field effect mobility, lowered by 14.3% and 4.6%, respectively.

  6. Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks.

    Science.gov (United States)

    Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

    2014-12-08

    Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the "small sample size" (SSS) problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1) how to define diverse base classifiers from the small data; (2) how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0-1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system.

  7. Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks

    Directory of Open Access Journals (Sweden)

    Cuicui Zhang

    2014-12-01

    Full Text Available Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the “small sample size” (SSS problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1 how to define diverse base classifiers from the small data; (2 how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0–1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system.

  8. Multiobjecitve Sampling Design for Calibration of Water Distribution Network Model Using Genetic Algorithm and Neural Network

    Directory of Open Access Journals (Sweden)

    Kourosh Behzadian

    2008-03-01

    Full Text Available In this paper, a novel multiobjective optimization model is presented for selecting optimal locations in the water distribution network (WDN with the aim of installing pressure loggers. The pressure data collected at optimal locations will be used later on in the calibration of the proposed WDN model. Objective functions consist of maximization of calibrated model prediction accuracy and minimization of the total cost for sampling design. In order to decrease the model run time, an optimization model has been developed using multiobjective genetic algorithm and adaptive neural network (MOGA-ANN. Neural networks (NNs are initially trained after a number of initial GA generations and periodically retrained and updated after generation of a specified number of full model-analyzed solutions. Trained NNs are replaced with the fitness evaluation of some chromosomes within the GA progress. Using cache prevents objective function evaluation of repetitive chromosomes within GA. Optimal solutions are obtained through pareto-optimal front with respect to the two objective functions. Results show that jointing NNs in MOGA for approximating portions of chromosomes’ fitness in each generation leads to considerable savings in model run time and can be promising for reducing run-time in optimization models with significant computational effort.

  9. Evaluating the stability of DSM-5 PTSD symptom network structure in a national sample of U.S. military veterans.

    Science.gov (United States)

    von Stockert, Sophia H H; Fried, Eiko I; Armour, Cherie; Pietrzak, Robert H

    2018-03-15

    Previous studies have used network models to investigate how PTSD symptoms associate with each other. However, analyses examining the degree to which these networks are stable over time, which are critical to identifying symptoms that may contribute to the chronicity of this disorder, are scarce. In the current study, we evaluated the temporal stability of DSM-5 PTSD symptom networks over a three-year period in a nationally representative sample of trauma-exposed U.S. military veterans. Data were analyzed from 611 trauma-exposed U.S. military veterans who participated in the National Health and Resilience in Veterans Study (NHRVS). We estimated regularized partial correlation networks of DSM-5 PTSD symptoms at baseline (Time 1) and at three-year follow-up (Time 2), and examined their temporal stability. Evaluation of the network structure of PTSD symptoms at Time 1 and Time 2 using a formal network comparison indicated that the Time 1 network did not differ significantly from the Time 2 network with regard to network structure (p = 0.12) or global strength (sum of all absolute associations, i.e. connectivity; p = 0.25). Centrality estimates of both networks (r = 0.86) and adjacency matrices (r = 0.69) were highly correlated. In both networks, avoidance, intrusive, and negative cognition and mood symptoms were among the more central nodes. This study is limited by the use of a self-report instrument to assess PTSD symptoms and recruitment of a relatively homogeneous sample of predominantly older, Caucasian veterans. Results of this study demonstrate the three-year stability of DSM-5 PTSD symptom network structure in a nationally representative sample of trauma-exposed U.S. military veterans. They further suggest that trauma-related avoidance, intrusive, and dysphoric symptoms may contribute to the chronicity of PTSD symptoms in this population. Published by Elsevier B.V.

  10. Field Exploration and Life Detection Sampling for Planetary Analogue Research (FELDSPAR)

    Science.gov (United States)

    Gentry, D.; Stockton, A. M.; Amador, E. S.; Cable, M. L.; Cantrell, T.; Chaudry, N.; Cullen, T.; Duca, Z. A.; Jacobsen, M. B.; Kirby, J.; McCaig, H. C.; Murukesan, G.; Rennie, V.; Rader, E.; Schwieterman, E. W.; Stevens, A. H.; Sutton, S. A.; Tan, G.; Yin, C.; Cullen, D.; Geppert, W.

    2017-12-01

    Extraterrestrial studies are typically conducted on mg samples from cm-scale features, while landing sites are selected based on m to km-scale features. It is therefore critical to understand spatial distribution of organic molecules over scales from cm to the km, particularly in geological features that appear homogenous at m to km scales. This is addressed by FELDSPAR, a NASA-funded project that conducts field operations analogous to Mars sample return in its science, operations, and technology [1]. Here, we present recent findings from a 2016 and a 2017 campaign to multiple Martian analogue sites in Iceland. Icelandic volcanic regions are Mars analogues due to desiccation, low nutrient availability, temperature extremes [2], and are relatively young and isolated from anthropogenic contamination [3]. Operationally, many Icelandic analogue sites are remote enough to require that field expeditions address several sampling constraints that are also faced by robotic exploration [1, 2]. Four field sites were evaluated in this study. The Fimmvörðuháls lava field was formed by a basaltic effusive eruption associated with the 2010 Eyjafjallajökull eruption. Mælifellssandur is a recently deglaciated plain to the north of the Myrdalsjökull glacier. Holuhraun is a basaltic spatter and cinder cone formed by 2014 fissure eruptions just north of the Vatnajökull glacier. Dyngjusandur is a plain kept barren by repeated aeolian mechanical weathering. Samples were collected in nested triangular grids from 10 cm to the 1 km scale. We obtained overhead imagery at 1 m to 200 m elevation to create digital elevation models. In-field reflectance spectroscopy was obtained with an ASD spectrometer and chemical composition was measured by a Bruker handheld XRF. All sites chosen were homogeneous in apparent color, morphology, moisture, grain size, and reflectance spectra at all scales greater than 10 cm. Field lab ATP assays were conducted to monitor microbial habitation, and home

  11. Optimal experiment design in a filtering context with application to sampled network data

    OpenAIRE

    Singhal, Harsh; Michailidis, George

    2010-01-01

    We examine the problem of optimal design in the context of filtering multiple random walks. Specifically, we define the steady state E-optimal design criterion and show that the underlying optimization problem leads to a second order cone program. The developed methodology is applied to tracking network flow volumes using sampled data, where the design variable corresponds to controlling the sampling rate. The optimal design is numerically compared to a myopic and a naive strategy. Finally, w...

  12. Network as transconcept: elements for a conceptual demarcation in the field of public health.

    Science.gov (United States)

    Amaral, Carlos Eduardo Menezes; Bosi, Maria Lúcia Magalhães

    2016-08-22

    The main proposal to set up an articulated mode of operation of health services has been the concept of network, which has been appropriated in different ways in the field of public health, as it is used in other disciplinary fields or even taking it from common sense. Amid the diversity of uses and concepts, we recognize the need for rigorous conceptual demarcation about networks in the field of health. Such concern aims to preserve the strategic potential of this concept in the research and planning in the field, overcoming uncertainties and distortions still observed in its discourse-analytic circulation in public health. To this end, we will introduce the current uses of network in different disciplinary fields, emphasizing dialogues with the field of public health. With this, we intend to stimulate discussions about the development of empirical dimensions and analytical models that may allow us to understand the processes produced within and around health networks. RESUMO A principal proposta para configurar um modo articulado de funcionamento dos serviços de saúde tem sido o conceito de rede, que vem sendo apropriado de diferentes formas no campo da saúde coletiva, conforme seu emprego em outros campos disciplinares ou mesmo tomando-o do senso comum. Em meio à pluralidade de usos e concepções, reconhecemos a necessidade de rigorosa demarcação conceitual acerca de redes no campo da saúde. Tal preocupação visa a preservar o potencial estratégico desse conceito na investigação e planificação no campo, superando precariedades e distorções ainda observadas em sua circulação discursivo-analítica na saúde coletiva. Para tanto, apresentaremos os usos correntes de rede em diferentes campos disciplinares, destacando interlocuções com o campo da saúde coletiva. Com isso, pretendemos estimular o debate acerca do desenvolvimento de dimensões empíricas e modelos de análise que permitam compreender os processos produzidos no interior e ao redor

  13. INTERACTION OF IMPULSE ELECTROMAGNETIC FIELDS WITH SURFACES OF METAL SAMPLES

    Directory of Open Access Journals (Sweden)

    V. V. Pavliouchenko

    2006-01-01

    Full Text Available Measurements of maximum tangential component of magnetic intensity Hτm have been carried out in the paper. The measurements have been taken on the surface of metal samples according to time of single current pulse rise in the form of semi-sinusoid of a linear current wire. Measurements have been made with the purpose to determine a value of the component according to thickness of samples made of aluminium.Temporary resolution ranges of electric and magnetic properties and defects of sample continuity along the depth have been found.Empirical formulae of dependence Hτm on sample thickness have been derived and their relation with efficient depth penetration of magnetic field into metal has been found.

  14. A spatially distributed isotope sampling network in a snow-dominated catchment for the quantification of snow meltwater

    Science.gov (United States)

    Rücker, Andrea; Boss, Stefan; Von Freyberg, Jana; Zappa, Massimiliano; Kirchner, James

    2017-04-01

    In mountainous catchments with seasonal snowpacks, river discharge in downstream valleys is largely sustained by snowmelt in spring and summer. Future climate warming will likely reduce snow volumes and lead to earlier and faster snowmelt in such catchments. This, in turn, may increase the risk of summer low flows and hydrological droughts. Improved runoff predictions are thus required in order to adapt water management to future climatic conditions and to assure the availability of fresh water throughout the year. However, a detailed understanding of the hydrological processes is crucial to obtain robust predictions of river streamflow. This in turn requires fingerprinting source areas of streamflow, tracing water flow pathways, and measuring timescales of catchment storage, using tracers such as stable water isotopes (18O, 2H). For this reason, we have established an isotope sampling network in the Alptal, a snowmelt-dominated catchment (46.4 km2) in Central-Switzerland, as part of the SREP-Drought project (Snow Resources and the Early Prediction of hydrological DROUGHT in mountainous streams). Precipitation and snow cores are analyzed for their isotopic signature at daily or weekly intervals. Three-week bulk samples of precipitation are also collected on a transect along the Alptal valley bottom, and along an elevational transect perpendicular to the Alptal valley axis. Streamwater samples are taken at the catchment outlet as well as in two small nested sub-catchments (automatic snow lysimeter system was developed, which also facilitates real-time monitoring of snowmelt events, system status and environmental conditions (air and soil temperature). Three lysimeter systems were installed within the catchment, in one forested site and two open field sites at different elevations, and have been operational since November 2016. We will present the isotope time series from our regular sampling network, as well as initial results from our snowmelt lysimeter sites. Our

  15. Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons.

    Science.gov (United States)

    Sadeh, Sadra; Cardanobile, Stefano; Rotter, Stefan

    2014-01-01

    Mechanisms underlying the emergence of orientation selectivity in the primary visual cortex are highly debated. Here we study the contribution of inhibition-dominated random recurrent networks to orientation selectivity, and more generally to sensory processing. By simulating and analyzing large-scale networks of spiking neurons, we investigate tuning amplification and contrast invariance of orientation selectivity in these networks. In particular, we show how selective attenuation of the common mode and amplification of the modulation component take place in these networks. Selective attenuation of the baseline, which is governed by the exceptional eigenvalue of the connectivity matrix, removes the unspecific, redundant signal component and ensures the invariance of selectivity across different contrasts. Selective amplification of modulation, which is governed by the operating regime of the network and depends on the strength of coupling, amplifies the informative signal component and thus increases the signal-to-noise ratio. Here, we perform a mean-field analysis which accounts for this process.

  16. Group field theory and tensor networks: towards a Ryu–Takayanagi formula in full quantum gravity

    Science.gov (United States)

    Chirco, Goffredo; Oriti, Daniele; Zhang, Mingyi

    2018-06-01

    We establish a dictionary between group field theory (thus, spin networks and random tensors) states and generalized random tensor networks. Then, we use this dictionary to compute the Rényi entropy of such states and recover the Ryu–Takayanagi formula, in two different cases corresponding to two different truncations/approximations, suggested by the established correspondence.

  17. Modeling Geoelectric Fields and Geomagnetically Induced Currents Around New Zealand to Explore GIC in the South Island's Electrical Transmission Network

    Science.gov (United States)

    Divett, T.; Ingham, M.; Beggan, C. D.; Richardson, G. S.; Rodger, C. J.; Thomson, A. W. P.; Dalzell, M.

    2017-10-01

    Transformers in New Zealand's South Island electrical transmission network have been impacted by geomagnetically induced currents (GIC) during geomagnetic storms. We explore the impact of GIC on this network by developing a thin-sheet conductance (TSC) model for the region, a geoelectric field model, and a GIC network model. (The TSC is composed of a thin-sheet conductance map with underlying layered resistivity structure.) Using modeling approaches that have been successfully used in the United Kingdom and Ireland, we applied a thin-sheet model to calculate the electric field as a function of magnetic field and ground conductance. We developed a TSC model based on magnetotelluric surveys, geology, and bathymetry, modified to account for offshore sediments. Using this representation, the thin sheet model gave good agreement with measured impedance vectors. Driven by a spatially uniform magnetic field variation, the thin-sheet model results in electric fields dominated by the ocean-land boundary with effects due to the deep ocean and steep terrain. There is a strong tendency for the electric field to align northwest-southeast, irrespective of the direction of the magnetic field. Applying this electric field to a GIC network model, we show that modeled GIC are dominated by northwest-southeast transmission lines rather than east-west lines usually assumed to dominate.

  18. Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

    Science.gov (United States)

    Cuntz, Hermann; Lansner, Anders; Panzeri, Stefano; Einevoll, Gaute T.

    2015-01-01

    Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best “LFP proxy”, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with “ground-truth” LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo. PMID:26657024

  19. Computing the Local Field Potential (LFP from Integrate-and-Fire Network Models.

    Directory of Open Access Journals (Sweden)

    Alberto Mazzoni

    2015-12-01

    Full Text Available Leaky integrate-and-fire (LIF network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP. Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

  20. PlumpyFieldNetwork of local producers of RUF (contributed paper)

    International Nuclear Information System (INIS)

    Belete, Hilina

    2014-01-01

    Full text: Expanding coverage for the 35 million children in the world suffering from Moderate Acute Malnutrition (MAM) will require sustainably scaling up regional procurement of lipid-based RUSF products. Momentum is now building to achieve this aim through ten local ready-to-use food (RUF) producers in the PlumpyField Network, which was established by the French company Nutriset in 2005. These independently-owned factories, located in Sub-Saharan Africa, Asia, and the Caribbean, currently produce one-third of the world’s RUF supply. Overcoming substantial obstacles, they have achieved the same high quality standards of producers in Europe and the U.S., with increasingly competitive pricing. Being part of a mutually supportive and interactive network of RUF producers from around the world provides unique learning and partnership opportunities, from sharing insights on peanut supply chain development, increasingly complex quality challenges, to pooled procurement. This network system has been instrumental to the success of local production for the members of the PlumpyField Network. Historically, local producers achieving economies of scale and reliable local and international supply chains (i.e. for peanuts, oil, sugar, milk etc.) takes several years, making the cost of locally-procured products more expensive in the short term. However, there are numerous positive outcomes and externalities that cannot be ignored, such as decreased lead times (especially crucial to reach children with acute malnutrition), lower shipping costs, economic development, and maturation of the food processing and microbiological laboratory sectors. UNICEF and WFP have become leaders in local and regional procurement as they continually optimize their strategies to best meet global needs. Local production is often an important stimulant of public-private partnerships, including procurement of RUF by local governments for government-run acute malnutrition programs, furthering

  1. Sampling Strategies for Evaluating the Rate of Adventitious Transgene Presence in Non-Genetically Modified Crop Fields.

    Science.gov (United States)

    Makowski, David; Bancal, Rémi; Bensadoun, Arnaud; Monod, Hervé; Messéan, Antoine

    2017-09-01

    According to E.U. regulations, the maximum allowable rate of adventitious transgene presence in non-genetically modified (GM) crops is 0.9%. We compared four sampling methods for the detection of transgenic material in agricultural non-GM maize fields: random sampling, stratified sampling, random sampling + ratio reweighting, random sampling + regression reweighting. Random sampling involves simply sampling maize grains from different locations selected at random from the field concerned. The stratified and reweighting sampling methods make use of an auxiliary variable corresponding to the output of a gene-flow model (a zero-inflated Poisson model) simulating cross-pollination as a function of wind speed, wind direction, and distance to the closest GM maize field. With the stratified sampling method, an auxiliary variable is used to define several strata with contrasting transgene presence rates, and grains are then sampled at random from each stratum. With the two methods involving reweighting, grains are first sampled at random from various locations within the field, and the observations are then reweighted according to the auxiliary variable. Data collected from three maize fields were used to compare the four sampling methods, and the results were used to determine the extent to which transgene presence rate estimation was improved by the use of stratified and reweighting sampling methods. We found that transgene rate estimates were more accurate and that substantially smaller samples could be used with sampling strategies based on an auxiliary variable derived from a gene-flow model. © 2017 Society for Risk Analysis.

  2. A contribution from dielectric analysis to the study of the formation of multi-wall carbon nanotubes percolated networks in epoxy resin under an electric field

    International Nuclear Information System (INIS)

    Risi, Celso L.S.; Hattenhauer, Irineu; Ramos, Airton; Coelho, Luiz A.F.; Pezzin, Sérgio H.

    2015-01-01

    The formation of percolation networks in epoxy matrix nanocomposites reinforced with multi-wall carbon nanotubes (MWNT) during the curing process, at different MWNT contents, was studied by using a parallel plate cell subjected to a 300 V/cm AC electric field at 1 kHz. The percolation was verified by the electrical current output measured during and after the resin curing. The behavior of electric dipoles was characterized by impedance spectroscopy and followed the Debye first order dispersion model, by which an average relaxation time of 6.0 × 10 −4 s and a cut-off frequency of 1.7 kHz were experimentally found. By applying the theory of percolation, a critical probability, p c , equal to 0.038 vol% and an exponent of conductivity of 2.0 were found. Both aligned and random samples showed dipole relaxation times typical of interfacial and/or charge-hopping polarization, while the permittivity exhibited an exponential decrease with frequency. This behavior can be related to the increased ability to trap electrical charges due to the formation of the carbon nanotubes network. Optical and electron microscopies confirm the theoretical prediction that the application of an electric field during cure helps the process of MWNT debundling in epoxy resin. - Highlights: • We report the formation of percolating networks of MWNTs under AC electric field. • MWNT/epoxy dielectric properties were measured by impedance spectroscopy. • Lower percolation thresholds were obtained for composites with aligned CNTs. • Application of AC electric field helps the debundling of CNTs. • CNT/Epoxy with percolated networks presents interfacial and hopping polarizations

  3. Field sampling for monitoring migration and defining the areal extent of chemical contamination

    International Nuclear Information System (INIS)

    Thomas, J.M.; Skalski, J.R.; Eberhardt, L.L.; Simmons, M.A.

    1984-11-01

    Initial research on compositing, field designs, and site mapping oriented toward detecting spills and migration at commercial low-level radioactive or chemical waste sites is summarized. Results indicate that the significance test developed to detect samples containing high levels of contamination when they are mixed with several other samples below detectable limits (composites), will be highly effective with large sample sizes when contaminant levels frequently or greatly exceed a maximum acceptable level. These conditions of frequent and high contaminant levels are most likely to occur in regions of a commercial waste site where the priors (previous knowledge) about a spill or migration are highest. Conversely, initial investigations of Bayes sampling strategies suggest that field sampling efforts should be inversely proportional to the priors (expressed as probabilities) for the occurrence of contamination

  4. On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions.

    Science.gov (United States)

    Schmitt, Michael

    2004-09-01

    We study networks of spiking neurons that use the timing of pulses to encode information. Nonlinear interactions model the spatial groupings of synapses on the neural dendrites and describe the computations performed at local branches. Within a theoretical framework of learning we analyze the question of how many training examples these networks must receive to be able to generalize well. Bounds for this sample complexity of learning can be obtained in terms of a combinatorial parameter known as the pseudodimension. This dimension characterizes the computational richness of a neural network and is given in terms of the number of network parameters. Two types of feedforward architectures are considered: constant-depth networks and networks of unconstrained depth. We derive asymptotically tight bounds for each of these network types. Constant depth networks are shown to have an almost linear pseudodimension, whereas the pseudodimension of general networks is quadratic. Networks of spiking neurons that use temporal coding are becoming increasingly more important in practical tasks such as computer vision, speech recognition, and motor control. The question of how well these networks generalize from a given set of training examples is a central issue for their successful application as adaptive systems. The results show that, although coding and computation in these networks is quite different and in many cases more powerful, their generalization capabilities are at least as good as those of traditional neural network models.

  5. Sampled-data consensus in switching networks of integrators based on edge events

    Science.gov (United States)

    Xiao, Feng; Meng, Xiangyu; Chen, Tongwen

    2015-02-01

    This paper investigates the event-driven sampled-data consensus in switching networks of multiple integrators and studies both the bidirectional interaction and leader-following passive reaction topologies in a unified framework. In these topologies, each information link is modelled by an edge of the information graph and assigned a sequence of edge events, which activate the mutual data sampling and controller updates of the two linked agents. Two kinds of edge-event-detecting rules are proposed for the general asynchronous data-sampling case and the synchronous periodic event-detecting case. They are implemented in a distributed fashion, and their effectiveness in reducing communication costs and solving consensus problems under a jointly connected topology condition is shown by both theoretical analysis and simulation examples.

  6. Convolutional neural networks based on augmented training samples for synthetic aperture radar target recognition

    Science.gov (United States)

    Yan, Yue

    2018-03-01

    A synthetic aperture radar (SAR) automatic target recognition (ATR) method based on the convolutional neural networks (CNN) trained by augmented training samples is proposed. To enhance the robustness of CNN to various extended operating conditions (EOCs), the original training images are used to generate the noisy samples at different signal-to-noise ratios (SNRs), multiresolution representations, and partially occluded images. Then, the generated images together with the original ones are used to train a designed CNN for target recognition. The augmented training samples can contrapuntally improve the robustness of the trained CNN to the covered EOCs, i.e., the noise corruption, resolution variance, and partial occlusion. Moreover, the significantly larger training set effectively enhances the representation capability for other conditions, e.g., the standard operating condition (SOC), as well as the stability of the network. Therefore, better performance can be achieved by the proposed method for SAR ATR. For experimental evaluation, extensive experiments are conducted on the Moving and Stationary Target Acquisition and Recognition dataset under SOC and several typical EOCs.

  7. Pre-Mission Input Requirements to Enable Successful Sample Collection by a Remote Field/EVA Team

    Science.gov (United States)

    Cohen, B. A.; Young, K. E.; Lim, D. S.

    2015-01-01

    This paper is intended to evaluate the sample collection process with respect to sample characterization and decision making. In some cases, it may be sufficient to know whether a given outcrop or hand sample is the same as or different from previous sampling localities or samples. In other cases, it may be important to have more in-depth characterization of the sample, such as basic composition, mineralogy, and petrology, in order to effectively identify the best sample. Contextual field observations, in situ/handheld analysis, and backroom evaluation may all play a role in understanding field lithologies and their importance for return. For example, whether a rock is a breccia or a clast-laden impact melt may be difficult based on a single sample, but becomes clear as exploration of a field site puts it into context. The FINESSE (Field Investigations to Enable Solar System Science and Exploration) team is a new activity focused on a science and exploration field based research program aimed at generating strategic knowledge in preparation for the human and robotic exploration of the Moon, near-Earth asteroids (NEAs) and Phobos and Deimos. We used the FINESSE field excursion to the West Clearwater Lake Impact structure (WCIS) as an opportunity to test factors related to sampling decisions. In contract to other technology-driven NASA analog studies, The FINESSE WCIS activity is science-focused, and moreover, is sampling-focused, with the explicit intent to return the best samples for geochronology studies in the laboratory. This specific objective effectively reduces the number of variables in the goals of the field test and enables a more controlled investigation of the role of the crewmember in selecting samples. We formulated one hypothesis to test: that providing details regarding the analytical fate of the samples (e.g. geochronology, XRF/XRD, etc.) to the crew prior to their traverse will result in samples that are more likely to meet specific analytical

  8. Field sampling for monitoring, migration and defining the areal extent of chemical contamination

    International Nuclear Information System (INIS)

    Thomas, J.M.; Skalski, J.R.; Eberhardt, L.L.; Simmons, M.A.

    1984-01-01

    As part of two studies funded by the U.S. Nuclear Regulatory Commission and the USEPA, the authors have investigated field sampling strategies and compositing as a means of detecting spills or migration at commercial low-level radioactive and chemical waste disposal sites and bioassays for detecting contamination at chemical waste sites. Compositing (pooling samples) for detection is discussed first, followed by the development of a statistical test to determine whether any component of a composite exceeds a prescribed maximum acceptable level. Subsequently, the authors explore the question of optimal field sampling designs and present the features of a microcomputer program designed to show the difficulties in constructing efficient field designs and using compositing schemes. Finally, they propose the use of bioassays as an adjunct or replacement for chemical analysis as a means of detecting and defining the areal extent of chemical migration

  9. How to construct the statistic network? An association network of herbaceous

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2012-06-01

    Full Text Available In present study I defined a new type of network, the statistic network. The statistic network is a weighted and non-deterministic network. In the statistic network, a connection value, i.e., connection weight, represents connection strength and connection likelihood between two nodes and its absolute value falls in the interval (0,1]. The connection value is expressed as a statistical measure such as correlation coefficient, association coefficient, or Jaccard coefficient, etc. In addition, all connections of the statistic network can be statistically tested for their validity. A connection is true if the connection value is statistically significant. If all connection values of a node are not statistically significant, it is an isolated node. An isolated node has not any connection to other nodes in the statistic network. Positive and negative connection values denote distinct connectiontypes (positive or negative association or interaction. In the statistic network, two nodes with the greater connection value will show more similar trend in the change of their states. At any time we can obtain a sample network of the statistic network. A sample network is a non-weighted and deterministic network. Thestatistic network, in particular the plant association network that constructed from field sampling, is mostly an information network. Most of the interspecific relationships in plant community are competition and cooperation. Therefore in comparison to animal networks, the methodology of statistic network is moresuitable to construct plant association networks. Some conclusions were drawn from this study: (1 in the plant association network, most connections are weak and positive interactions. The association network constructed from Spearman rank correlation has most connections and isolated taxa are fewer. From net linear correlation,linear correlation, to Spearman rank correlation, the practical number of connections and connectance in the

  10. Fulcrum Network Codes

    DEFF Research Database (Denmark)

    2015-01-01

    Fulcrum network codes, which are a network coding framework, achieve three objectives: (i) to reduce the overhead per coded packet to almost 1 bit per source packet; (ii) to operate the network using only low field size operations at intermediate nodes, dramatically reducing complexity...... in the network; and (iii) to deliver an end-to-end performance that is close to that of a high field size network coding system for high-end receivers while simultaneously catering to low-end ones that can only decode in a lower field size. Sources may encode using a high field size expansion to increase...... the number of dimensions seen by the network using a linear mapping. Receivers can tradeoff computational effort with network delay, decoding in the high field size, the low field size, or a combination thereof....

  11. Field Trial of 40 Gb/s Optical Transport Network using Open WDM Interfaces

    DEFF Research Database (Denmark)

    Fagertun, Anna Manolova; Ruepp, Sarah Renée; Petersen, Martin Nordal

    2013-01-01

    An experimental field-trail deployment of a 40Gb/s open WDM interface in an operational network is presented, in cross-carrier interconnection scenario. Practical challenges of integration and performance measures for both native and alien channels are outlined....

  12. Astronauts Armstrong and Aldrin study rock samples during field trip

    Science.gov (United States)

    1969-01-01

    Astronaut Neil Armstrong, commander of the Apollo 11 lunar landing mission, and Astronaut Edwin Aldrin, Lunar module pilot for Apollo 11, study rock samples during a geological field trip to the Quitman Mountains area near the Fort Quitman ruins in far west Texas.

  13. Quantum dot-based local field imaging reveals plasmon-based interferometric logic in silver nanowire networks.

    Science.gov (United States)

    Wei, Hong; Li, Zhipeng; Tian, Xiaorui; Wang, Zhuoxian; Cong, Fengzi; Liu, Ning; Zhang, Shunping; Nordlander, Peter; Halas, Naomi J; Xu, Hongxing

    2011-02-09

    We show that the local electric field distribution of propagating plasmons along silver nanowires can be imaged by coating the nanowires with a layer of quantum dots, held off the surface of the nanowire by a nanoscale dielectric spacer layer. In simple networks of silver nanowires with two optical inputs, control of the optical polarization and phase of the input fields directs the guided waves to a specific nanowire output. The QD-luminescent images of these structures reveal that a complete family of phase-dependent, interferometric logic functions can be performed on these simple networks. These results show the potential for plasmonic waveguides to support compact interferometric logic operations.

  14. Using remote sensing images to design optimal field sampling schemes

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2008-08-01

    Full Text Available sampling schemes case studies Optimized field sampling representing the overall distribution of a particular mineral Deriving optimal exploration target zones CONTINUUM REMOVAL for vegetation [13, 27, 46]. The convex hull transform is a method... of normalizing spectra [16, 41]. The convex hull technique is anal- ogous to fitting a rubber band over a spectrum to form a continuum. Figure 5 shows the concept of the convex hull transform. The differ- ence between the hull and the orig- inal spectrum...

  15. Random field Ising chain and neutral networks with synchronous dynamics

    International Nuclear Information System (INIS)

    Skantzos, N.S.; Coolen, A.C.C.

    2001-01-01

    We first present an exact solution of the one-dimensional random-field Ising model in which spin-updates are made fully synchronously, i.e. in parallel (in contrast to the more conventional Glauber-type sequential rules). We find transitions where the support of local observables turns from a continuous interval into a Cantor set and we show that synchronous and sequential random-field models lead asymptotically to the same physical states. We then proceed to an application of these techniques to recurrent neural networks where 1D short-range interactions are combined with infinite-range ones. Due to the competing interactions these models exhibit phase diagrams with first-order transitions and regions with multiple locally stable solutions for the macroscopic order parameters

  16. Centralized and decentralized global outer-synchronization of asymmetric recurrent time-varying neural network by data-sampling.

    Science.gov (United States)

    Lu, Wenlian; Zheng, Ren; Chen, Tianping

    2016-03-01

    In this paper, we discuss outer-synchronization of the asymmetrically connected recurrent time-varying neural networks. By using both centralized and decentralized discretization data sampling principles, we derive several sufficient conditions based on three vector norms to guarantee that the difference of any two trajectories starting from different initial values of the neural network converges to zero. The lower bounds of the common time intervals between data samples in centralized and decentralized principles are proved to be positive, which guarantees exclusion of Zeno behavior. A numerical example is provided to illustrate the efficiency of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Design, analysis, and interpretation of field quality-control data for water-sampling projects

    Science.gov (United States)

    Mueller, David K.; Schertz, Terry L.; Martin, Jeffrey D.; Sandstrom, Mark W.

    2015-01-01

    The process of obtaining and analyzing water samples from the environment includes a number of steps that can affect the reported result. The equipment used to collect and filter samples, the bottles used for specific subsamples, any added preservatives, sample storage in the field, and shipment to the laboratory have the potential to affect how accurately samples represent the environment from which they were collected. During the early 1990s, the U.S. Geological Survey implemented policies to include the routine collection of quality-control samples in order to evaluate these effects and to ensure that water-quality data were adequately representing environmental conditions. Since that time, the U.S. Geological Survey Office of Water Quality has provided training in how to design effective field quality-control sampling programs and how to evaluate the resultant quality-control data. This report documents that training material and provides a reference for methods used to analyze quality-control data.

  18. Synchronized High-Speed Vision Sensor Network for Expansion of Field of View

    Directory of Open Access Journals (Sweden)

    Akihito Noda

    2018-04-01

    Full Text Available We propose a 500-frames-per-second high-speed vision (HSV sensor network that acquires frames at a timing that is precisely synchronized across the network. Multiple vision sensor nodes, individually comprising a camera and a PC, are connected via Ethernet for data transmission and for clock synchronization. A network of synchronized HSV sensors provides a significantly expanded field-of-view compared with that of each individual HSV sensor. In the proposed system, the shutter of each camera is controlled based on the clock of the PC locally provided inside the node, and the shutters are globally synchronized using the Precision Time Protocol (PTP over the network. A theoretical analysis and experiment results indicate that the shutter trigger skew among the nodes is a few tens of microseconds at most, which is significantly smaller than the frame interval of 1000-fps-class high-speed cameras. Experimental results obtained with the proposed system comprising four nodes demonstrated the ability to capture the propagation of a small displacement along a large-scale structure.

  19. Insights into a spatially embedded social network from a large-scale snowball sample

    Science.gov (United States)

    Illenberger, J.; Kowald, M.; Axhausen, K. W.; Nagel, K.

    2011-12-01

    Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals' characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

  20. Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

    Science.gov (United States)

    Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

    2009-01-01

    Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

  1. Networked Thermodynamic Boundary Layer Profiling with AERIs during the PECAN Field Campaign

    Science.gov (United States)

    Gero, P. J.; Turner, D. D.; Hackel, D.; Phillips, C.; Smith, N.; Wagner, T.

    2015-12-01

    The Plains Elevated Convection at Night (PECAN) campaign was a large-scale field experiment in the Great Plains region of the U.S. that was conducted in June-July 2015. Nocturnal storms provide the majority of the precipitation in the Great Plains, yet the initiation and evolution of nocturnal convection is not understood to the same level as daytime surface-based convection, and thus provides significant challenges for operational weather forecasters. PECAN's objectives were to study elevated nocturnal convection initiation and the lifecycle of nocturnal convection. Specific research areas that were studied were the evolution of mesoscale convective systems, the structure and evolution of nocturnal low-level jets, atmospheric bores, and elevated convection initiation. A broad range of fixed and mobile observing systems were deployed by several agencies and organizations in a domain centered around Kansas. The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based instrument that measures downwelling infrared radiance from the atmosphere. AERI observations can be used to obtain vertical profiles of tropospheric temperature and water vapor in the lowest 3 km of the troposphere, as well as measurements of the concentration of various trace gases and microphysical and optical properties of clouds and aerosols. A network of eight AERIs was deployed in the domain during PECAN, with six at fixed sites and two in mobile facilities. One of the goals of the campaign was a demonstration of the use of real-time high-temporal-resolution boundary layer profiles from the network of AERIs for characterizing the mesoscale environment and its evolution during the weather events sampled during PECAN. If successful, a future network could be implemented across CONUS and thermodynamic profiles in the boundary layer data assimilated to help improve numerical weather prediction. We present an overview of the AERI deployments, a summary of the technique used to retrieve

  2. Porosity, permeability and 3D fracture network characterisation of dolomite reservoir rock samples.

    Science.gov (United States)

    Voorn, Maarten; Exner, Ulrike; Barnhoorn, Auke; Baud, Patrick; Reuschlé, Thierry

    2015-03-01

    With fractured rocks making up an important part of hydrocarbon reservoirs worldwide, detailed analysis of fractures and fracture networks is essential. However, common analyses on drill core and plug samples taken from such reservoirs (including hand specimen analysis, thin section analysis and laboratory porosity and permeability determination) however suffer from various problems, such as having a limited resolution, providing only 2D and no internal structure information, being destructive on the samples and/or not being representative for full fracture networks. In this paper, we therefore explore the use of an additional method - non-destructive 3D X-ray micro-Computed Tomography (μCT) - to obtain more information on such fractured samples. Seven plug-sized samples were selected from narrowly fractured rocks of the Hauptdolomit formation, taken from wellbores in the Vienna basin, Austria. These samples span a range of different fault rocks in a fault zone interpretation, from damage zone to fault core. We process the 3D μCT data in this study by a Hessian-based fracture filtering routine and can successfully extract porosity, fracture aperture, fracture density and fracture orientations - in bulk as well as locally. Additionally, thin sections made from selected plug samples provide 2D information with a much higher detail than the μCT data. Finally, gas- and water permeability measurements under confining pressure provide an important link (at least in order of magnitude) towards more realistic reservoir conditions. This study shows that 3D μCT can be applied efficiently on plug-sized samples of naturally fractured rocks, and that although there are limitations, several important parameters can be extracted. μCT can therefore be a useful addition to studies on such reservoir rocks, and provide valuable input for modelling and simulations. Also permeability experiments under confining pressure provide important additional insights. Combining these and

  3. Cascading a systolic array and a feedforward neural network for navigation and obstacle avoidance using potential fields

    Science.gov (United States)

    Plumer, Edward S.

    1991-01-01

    A technique is developed for vehicle navigation and control in the presence of obstacles. A potential function was devised that peaks at the surface of obstacles and has its minimum at the proper vehicle destination. This function is computed using a systolic array and is guaranteed not to have local minima. A feedfoward neural network is then used to control the steering of the vehicle using local potential field information. In this case, the vehicle is a trailer truck backing up. Previous work has demonstrated the capability of a neural network to control steering of such a trailer truck backing to a loading platform, but without obstacles. Now, the neural network was able to learn to navigate a trailer truck around obstacles while backing toward its destination. The network is trained in an obstacle free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.

  4. Preservation of RNA and DNA from mammal samples under field conditions.

    Science.gov (United States)

    Camacho-Sanchez, Miguel; Burraco, Pablo; Gomez-Mestre, Ivan; Leonard, Jennifer A

    2013-07-01

    Ecological and conservation genetics require sampling of organisms in the wild. Appropriate preservation of the collected samples, usually by cryostorage, is key to the quality of the genetic data obtained. Nevertheless, cryopreservation in the field to ensure RNA and DNA stability is not always possible. We compared several nucleic acid preservation solutions appropriate for field sampling and tested them on rat (Rattus rattus) blood, ear and tail tip, liver, brain and muscle. We compared the efficacy of a nucleic acid preservation (NAP) buffer for DNA preservation against 95% ethanol and Longmire buffer, and for RNA preservation against RNAlater (Qiagen) and Longmire buffer, under simulated field conditions. For DNA, the NAP buffer was slightly better than cryopreservation or 95% ethanol, but high molecular weight DNA was preserved in all conditions. The NAP buffer preserved RNA as well as RNAlater. Liver yielded the best RNA and DNA quantity and quality; thus, liver should be the tissue preferentially collected from euthanized animals. We also show that DNA persists in nonpreserved muscle tissue for at least 1 week at ambient temperature, although degradation is noticeable in a matter of hours. When cryopreservation is not possible, the NAP buffer is an economical alternative for RNA preservation at ambient temperature for at least 2 months and DNA preservation for at least 10 months. © 2013 John Wiley & Sons Ltd.

  5. Data splitting for artificial neural networks using SOM-based stratified sampling.

    Science.gov (United States)

    May, R J; Maier, H R; Dandy, G C

    2010-03-01

    Data splitting is an important consideration during artificial neural network (ANN) development where hold-out cross-validation is commonly employed to ensure generalization. Even for a moderate sample size, the sampling methodology used for data splitting can have a significant effect on the quality of the subsets used for training, testing and validating an ANN. Poor data splitting can result in inaccurate and highly variable model performance; however, the choice of sampling methodology is rarely given due consideration by ANN modellers. Increased confidence in the sampling is of paramount importance, since the hold-out sampling is generally performed only once during ANN development. This paper considers the variability in the quality of subsets that are obtained using different data splitting approaches. A novel approach to stratified sampling, based on Neyman sampling of the self-organizing map (SOM), is developed, with several guidelines identified for setting the SOM size and sample allocation in order to minimize the bias and variance in the datasets. Using an example ANN function approximation task, the SOM-based approach is evaluated in comparison to random sampling, DUPLEX, systematic stratified sampling, and trial-and-error sampling to minimize the statistical differences between data sets. Of these approaches, DUPLEX is found to provide benchmark performance with good model performance, with no variability. The results show that the SOM-based approach also reliably generates high-quality samples and can therefore be used with greater confidence than other approaches, especially in the case of non-uniform datasets, with the benefit of scalability to perform data splitting on large datasets. Copyright 2009 Elsevier Ltd. All rights reserved.

  6. Sampling general N-body interactions with auxiliary fields

    Science.gov (United States)

    Körber, C.; Berkowitz, E.; Luu, T.

    2017-09-01

    We present a general auxiliary field transformation which generates effective interactions containing all possible N-body contact terms. The strength of the induced terms can analytically be described in terms of general coefficients associated with the transformation and thus are controllable. This transformation provides a novel way for sampling 3- and 4-body (and higher) contact interactions non-perturbatively in lattice quantum Monte Carlo simulations. As a proof of principle, we show that our method reproduces the exact solution for a two-site quantum mechanical problem.

  7. Using maximum entropy modeling for optimal selection of sampling sites for monitoring networks

    Science.gov (United States)

    Stohlgren, Thomas J.; Kumar, Sunil; Barnett, David T.; Evangelista, Paul H.

    2011-01-01

    Environmental monitoring programs must efficiently describe state shifts. We propose using maximum entropy modeling to select dissimilar sampling sites to capture environmental variability at low cost, and demonstrate a specific application: sample site selection for the Central Plains domain (453,490 km2) of the National Ecological Observatory Network (NEON). We relied on four environmental factors: mean annual temperature and precipitation, elevation, and vegetation type. A “sample site” was defined as a 20 km × 20 km area (equal to NEON’s airborne observation platform [AOP] footprint), within which each 1 km2 cell was evaluated for each environmental factor. After each model run, the most environmentally dissimilar site was selected from all potential sample sites. The iterative selection of eight sites captured approximately 80% of the environmental envelope of the domain, an improvement over stratified random sampling and simple random designs for sample site selection. This approach can be widely used for cost-efficient selection of survey and monitoring sites.

  8. Feasibility of artificial geomagnetic field generation by a superconducting ring network

    International Nuclear Information System (INIS)

    Motojima, Osamu; Yanagi, Nagato

    2008-05-01

    The geomagnetic field shields the Earth from a large proportion of incoming radiation, and has thus played a key role in sustaining life on Earth. Paleomagnetic measurements have shown that the geomagnetic field undergoes many reversals of polarity. Continuous observations of the field intensity have revealed a weakening of approximately 10% over the last 150 years. If we assume that this trend indicates the onset of polarity reversal, the geomagnetic field, particularly the dipole component, may weaken sufficiently over the next thousand years to expose the atmosphere and nearby space to significantly increased levels of cosmic and solar radiation. This may have a serious impact on vital infrastructure such as satellites, air traffic, and electricity networks, as well as on global climate changes, indicating that measures should better be taken in an attempt to support the limited protection provided by the remaining higher-order multipole fields and atmosphere. Here we show that a series of planet-encircling superconducting rings can provide an artificial geomagnetic field equivalent to 10% of the present-day field necessary to prevent adverse effects. A feasible system consists of 12 latitudinal high-temperature superconducting rings, each carrying 6.4 MA current with a modest 1 GW of power requirement. (author)

  9. Guidance for establishment and implementation of field sample management programs in support of EM environmental sampling and analysis activities

    International Nuclear Information System (INIS)

    1994-01-01

    The role of the National Sample Management Program (NSMP) proposed by the Department of Energy's Office of Environmental Management (EM) is to be a resource for EM programs and for local Field Sample Management Programs (FSMPs). It will be a source of information on sample analysis and data collection within the DOE complex. The purpose of this document is to establish the suggested scope of the FSMP activities to be performed under each Operations Office, list the drivers under which the program will operate, define terms and list references. This guidance will apply only to EM sampling and analysis activities associated with project planning, contracting, laboratory selection, sample collection, sample transportation, laboratory analysis and data management

  10. Intact preservation of environmental samples by freezing under an alternating magnetic field.

    Science.gov (United States)

    Morono, Yuki; Terada, Takeshi; Yamamoto, Yuhji; Xiao, Nan; Hirose, Takehiro; Sugeno, Masaya; Ohwada, Norio; Inagaki, Fumio

    2015-04-01

    The study of environmental samples requires a preservation system that stabilizes the sample structure, including cells and biomolecules. To address this fundamental issue, we tested the cell alive system (CAS)-freezing technique for subseafloor sediment core samples. In the CAS-freezing technique, an alternating magnetic field is applied during the freezing process to produce vibration of water molecules and achieve a stable, super-cooled liquid phase. Upon further cooling, the temperature decreases further, achieving a uniform freezing of sample with minimal ice crystal formation. In this study, samples were preserved using the CAS and conventional freezing techniques at 4, -20, -80 and -196 (liquid nitrogen) °C. After 6 months of storage, microbial cell counts by conventional freezing significantly decreased (down to 10.7% of initial), whereas that by CAS-freezing resulted in minimal. When Escherichia coli cells were tested under the same freezing conditions and storage for 2.5 months, CAS-frozen E. coli cells showed higher viability than the other conditions. In addition, an alternating magnetic field does not impact on the direction of remanent magnetization in sediment core samples, although slight partial demagnetization in intensity due to freezing was observed. Consequently, our data indicate that the CAS technique is highly useful for the preservation of environmental samples. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

  11. Effect of sample shape on nonlinear magnetization dynamics under an external magnetic field

    International Nuclear Information System (INIS)

    Vagin, Dmitry V.; Polyakov, Oleg P.

    2008-01-01

    Effect of sample shape on the nonlinear collective dynamics of magnetic moments in the presence of oscillating and constant external magnetic fields is studied using the Landau-Lifshitz-Gilbert (LLG) approach. The uniformly magnetized sample is considered to be an ellipsoidal axially symmetric particle described by demagnetization factors and uniaxial crystallographic anisotropy formed some angle with an applied field direction. It is investigated as to how the change in particle shape affects its nonlinear magnetization dynamics. To produce a regular study, all results are presented in the form of bifurcation diagrams for all sufficient dynamics regimes of the considered system. In this paper, we show that the sample's (particle's) shape and its orientation with respect to the external field (system configuration) determine the character of magnetization dynamics: deterministic behavior and appearance of chaotic states. A simple change in the system's configuration or in the shapes of its parts can transfer it from chaotic to periodic or even static regime and back. Moreover, the effect of magnetization precession stall and magnetic moments alignment parallel or antiparallel to the external oscillating field is revealed and the way of control of such 'polarized' states is found. Our results suggest that varying the particle's shape and fields' geometry may provide a useful way of magnetization dynamics control in complex magnetic systems

  12. Minimal BRDF Sampling for Two-Shot Near-Field Reflectance Acquisition

    DEFF Research Database (Denmark)

    Xu, Zexiang; Nielsen, Jannik Boll; Yu, Jiyang

    2016-01-01

    We develop a method to acquire the BRDF of a homogeneous flat sample from only two images, taken by a near-field perspective camera, and lit by a directional light source. Our method uses the MERL BRDF database to determine the optimal set of lightview pairs for data-driven reflectance acquisition...

  13. Polymer-Sorted Semiconducting Carbon Nanotube Networks for High-Performance Ambipolar Field-Effect Transistors

    Science.gov (United States)

    2014-01-01

    Efficient selection of semiconducting single-walled carbon nanotubes (SWNTs) from as-grown nanotube samples is crucial for their application as printable and flexible semiconductors in field-effect transistors (FETs). In this study, we use atactic poly(9-dodecyl-9-methyl-fluorene) (a-PF-1-12), a polyfluorene derivative with asymmetric side-chains, for the selective dispersion of semiconducting SWNTs with large diameters (>1 nm) from plasma torch-grown SWNTs. Lowering the molecular weight of the dispersing polymer leads to a significant improvement of selectivity. Combining dense semiconducting SWNT networks deposited from an enriched SWNT dispersion with a polymer/metal-oxide hybrid dielectric enables transistors with balanced ambipolar, contact resistance-corrected mobilities of up to 50 cm2·V–1·s–1, low ohmic contact resistance, steep subthreshold swings (0.12–0.14 V/dec) and high on/off ratios (106) even for short channel lengths (<10 μm). These FETs operate at low voltages (<3 V) and show almost no current hysteresis. The resulting ambipolar complementary-like inverters exhibit gains up to 61. PMID:25493421

  14. Serum Dried Samples to Detect Dengue Antibodies: A Field Study

    Directory of Open Access Journals (Sweden)

    Angelica Maldonado-Rodríguez

    2017-01-01

    Full Text Available Background. Dried blood and serum samples are useful resources for detecting antiviral antibodies. The conditions for elution of the sample need to be optimized for each disease. Dengue is a widespread disease in Mexico which requires continuous surveillance. In this study, we standardized and validated a protocol for the specific detection of dengue antibodies from dried serum spots (DSSs. Methods. Paired serum and DSS samples from 66 suspected cases of dengue were collected in a clinic in Veracruz, Mexico. Samples were sent to our laboratory, where the conditions for optimal elution of DSSs were established. The presence of anti-dengue antibodies was determined in the paired samples. Results. DSS elution conditions were standardized as follows: 1 h at 4°C in 200 µl of DNase-, RNase-, and protease-free PBS (1x. The optimal volume of DSS eluate to be used in the IgG assay was 40 µl. Sensitivity of 94%, specificity of 93.3%, and kappa concordance of 0.87 were obtained when comparing the antidengue reactivity between DSSs and serum samples. Conclusion. DSS samples are useful for detecting anti-dengue IgG antibodies in the field.

  15. Improving the Network Scale-Up Estimator: Incorporating Means of Sums, Recursive Back Estimation, and Sampling Weights.

    Directory of Open Access Journals (Sweden)

    Patrick Habecker

    Full Text Available Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations via traditional survey tools such as telephone or mail surveys--by asking a representative sample to estimate the number of people they know who are members of such a "hidden" subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation "trimming" to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights.

  16. EARLY DETECTION OF NEAR-FIELD TSUNAMIS USING UNDERWATER SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    L. E. Freitag

    2012-01-01

    Full Text Available We propose a novel approach for near-field tsunami detection, specifically for the area near the city of Padang, Indonesia. Padang is located on the western shore of Sumatra, directly across from the Mentawai segment of the Sunda Trench, where accumulated strain has not been released since the great earthquake of 1797. Consequently, the risk of a major tsunamigenic earthquake on this segment is high. Currently, no ocean-bottom pressure sensors are deployed in the Mentawai basin to provide a definitive tsunami warning for Padang. Timely warnings are essential to initiate evacuation procedures and minimize loss of human life. Our approach augments existing technology with a network of underwater sensors to detect tsunamis generated by an earthquake or landslide fast enough to provide at least 15 minutes of warning. Data from the underwater sensor network would feed into existing decision support systems that accept input from land and sea-based sensors and provide warning information to city and regional authorities.

  17. Impacts of Sample Design for Validation Data on the Accuracy of Feedforward Neural Network Classification

    Directory of Open Access Journals (Sweden)

    Giles M. Foody

    2017-08-01

    Full Text Available Validation data are often used to evaluate the performance of a trained neural network and used in the selection of a network deemed optimal for the task at-hand. Optimality is commonly assessed with a measure, such as overall classification accuracy. The latter is often calculated directly from a confusion matrix showing the counts of cases in the validation set with particular labelling properties. The sample design used to form the validation set can, however, influence the estimated magnitude of the accuracy. Commonly, the validation set is formed with a stratified sample to give balanced classes, but also via random sampling, which reflects class abundance. It is suggested that if the ultimate aim is to accurately classify a dataset in which the classes do vary in abundance, a validation set formed via random, rather than stratified, sampling is preferred. This is illustrated with the classification of simulated and remotely-sensed datasets. With both datasets, statistically significant differences in the accuracy with which the data could be classified arose from the use of validation sets formed via random and stratified sampling (z = 2.7 and 1.9 for the simulated and real datasets respectively, for both p < 0.05%. The accuracy of the classifications that used a stratified sample in validation were smaller, a result of cases of an abundant class being commissioned into a rarer class. Simple means to address the issue are suggested.

  18. Network Neurodegeneration in Alzheimer’s Disease via MRI based Shape Diffeomorphometry and High Field Atlasing

    Directory of Open Access Journals (Sweden)

    Michael I Miller

    2015-05-01

    Full Text Available This paper examines MRI analysis of neurodegeneration in Alzheimer’s Disease (AD in a network of structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing in which the entorhinal cortex is partitioned into nine subareas. The morphometry markers for three groups of subjects (controls, preclinical AD and symptomatic AD are indexed to template coordinates measured with respect to these nine subareas. The location and timing of changes are examined within the subareas as it pertains to the classic Braak and Braak staging by comparing the three groups. We demonstrate that the earliest preclinical changes in the population occur in the lateral most sulcal extent in the entorhinal cortex (alluded to as trans entorhinal cortex by Braak and Braak, and then proceeds medially which is consistent with the Braak and Braak staging. We use high field 11T atlasing to demonstrate that the network changes are occurring at the junctures of the substructures in this medial temporal lobe network. Temporal progression of the disease through the network is also examined via changepoint analysis demonstrating earliest changes in entorhinal cortex. The differential expression of rate of atrophy with progression signaling the changepoint time across the network is demonstrated to be signaling in the intermediate caudal subarea of the entorhinal cortex, which has been noted to be proximal to the hippocampus. This coupled to the findings of the nearby basolateral involvement in amygdala demonstrates the selectivity of neurodegeneration in early AD.

  19. Graphene-based field effect transistor in two-dimensional paper networks

    Energy Technology Data Exchange (ETDEWEB)

    Cagang, Aldrine Abenoja; Abidi, Irfan Haider; Tyagi, Abhishek [Department of Chemical and Biomolecular Engineering, Hong Kong University of Science and Technology, Clear Water Bay (Hong Kong); Hu, Jie; Xu, Feng [Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an 710049 (China); The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an 710049 (China); Lu, Tian Jian [Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an 710049 (China); Luo, Zhengtang, E-mail: keztluo@ust.hk [Department of Chemical and Biomolecular Engineering, Hong Kong University of Science and Technology, Clear Water Bay (Hong Kong)

    2016-04-21

    We demonstrate the fabrication of a graphene-based field effect transistor (GFET) incorporated in a two-dimensional paper network format (2DPNs). Paper serves as both a gate dielectric and an easy-to-fabricate vessel for holding the solution with the target molecules in question. The choice of paper enables a simpler alternative approach to the construction of a GFET device. The fabricated device is shown to behave similarly to a solution-gated GFET device with electron and hole mobilities of ∼1256 cm{sup 2} V{sup −1} s{sup −1} and ∼2298 cm{sup 2} V{sup −1} s{sup −1} respectively and a Dirac point around ∼1 V. When using solutions of ssDNA and glucose it was found that the added molecules induce negative electrolytic gating effects shifting the conductance minimum to the right, concurrent with increasing carrier concentrations which results to an observed increase in current response correlated to the concentration of the solution used. - Highlights: • A graphene-based field effect transistor sensor was fabricated for two-dimensional paper network formats. • The constructed GFET on 2DPN was shown to behave similarly to solution-gated GFETs. • Electrolyte gating effects have more prominent effect over adsorption effects on the behavior of the device. • The GFET incorporated on 2DPN was shown to yield linear response to presence of glucose and ssDNA soaked inside the paper.

  20. Graphene-based field effect transistor in two-dimensional paper networks

    International Nuclear Information System (INIS)

    Cagang, Aldrine Abenoja; Abidi, Irfan Haider; Tyagi, Abhishek; Hu, Jie; Xu, Feng; Lu, Tian Jian; Luo, Zhengtang

    2016-01-01

    We demonstrate the fabrication of a graphene-based field effect transistor (GFET) incorporated in a two-dimensional paper network format (2DPNs). Paper serves as both a gate dielectric and an easy-to-fabricate vessel for holding the solution with the target molecules in question. The choice of paper enables a simpler alternative approach to the construction of a GFET device. The fabricated device is shown to behave similarly to a solution-gated GFET device with electron and hole mobilities of ∼1256 cm 2  V −1  s −1 and ∼2298 cm 2  V −1  s −1 respectively and a Dirac point around ∼1 V. When using solutions of ssDNA and glucose it was found that the added molecules induce negative electrolytic gating effects shifting the conductance minimum to the right, concurrent with increasing carrier concentrations which results to an observed increase in current response correlated to the concentration of the solution used. - Highlights: • A graphene-based field effect transistor sensor was fabricated for two-dimensional paper network formats. • The constructed GFET on 2DPN was shown to behave similarly to solution-gated GFETs. • Electrolyte gating effects have more prominent effect over adsorption effects on the behavior of the device. • The GFET incorporated on 2DPN was shown to yield linear response to presence of glucose and ssDNA soaked inside the paper.

  1. Neuro-genetic system for optimization of GMI samples sensitivity.

    Science.gov (United States)

    Pitta Botelho, A C O; Vellasco, M M B R; Hall Barbosa, C R; Costa Silva, E

    2016-03-01

    Magnetic sensors are largely used in several engineering areas. Among them, magnetic sensors based on the Giant Magnetoimpedance (GMI) effect are a new family of magnetic sensing devices that have a huge potential for applications involving measurements of ultra-weak magnetic fields. The sensitivity of magnetometers is directly associated with the sensitivity of their sensing elements. The GMI effect is characterized by a large variation of the impedance (magnitude and phase) of a ferromagnetic sample, when subjected to a magnetic field. Recent studies have shown that phase-based GMI magnetometers have the potential to increase the sensitivity by about 100 times. The sensitivity of GMI samples depends on several parameters, such as sample length, external magnetic field, DC level and frequency of the excitation current. However, this dependency is yet to be sufficiently well-modeled in quantitative terms. So, the search for the set of parameters that optimizes the samples sensitivity is usually empirical and very time consuming. This paper deals with this problem by proposing a new neuro-genetic system aimed at maximizing the impedance phase sensitivity of GMI samples. A Multi-Layer Perceptron (MLP) Neural Network is used to model the impedance phase and a Genetic Algorithm uses the information provided by the neural network to determine which set of parameters maximizes the impedance phase sensitivity. The results obtained with a data set composed of four different GMI sample lengths demonstrate that the neuro-genetic system is able to correctly and automatically determine the set of conditioning parameters responsible for maximizing their phase sensitivities. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Scanning SQUID microscope with an in-situ magnetization/demagnetization field for geological samples

    Science.gov (United States)

    Du, Junwei; Liu, Xiaohong; Qin, Huafeng; Wei, Zhao; Kong, Xiangyang; Liu, Qingsong; Song, Tao

    2018-04-01

    Magnetic properties of rocks are crucial for paleo-, rock-, environmental-magnetism, and magnetic material sciences. Conventional rock magnetometers deal with bulk properties of samples, whereas scanning microscope can map the distribution of remanent magnetization. In this study, a new scanning microscope based on a low-temperature DC superconducting quantum interference device (SQUID) equipped with an in-situ magnetization/demagnetization device was developed. To realize the combination of sensitive instrument as SQUID with high magnetizing/demagnetizing fields, the pick-up coil, the magnetization/demagnetization coils and the measurement mode of the system were optimized. The new microscope has a field sensitivity of 250 pT/√Hz at a coil-to-sample spacing of ∼350 μm, and high magnetization (0-1 T)/ demagnetization (0-300 mT, 400 Hz) functions. With this microscope, isothermal remanent magnetization (IRM) acquisition and the according alternating field (AF) demagnetization curves can be obtained for each point without transferring samples between different procedures, which could result in position deviation, waste of time, and other interferences. The newly-designed SQUID microscope, thus, can be used to investigate the rock magnetic properties of samples at a micro-area scale, and has a great potential to be an efficient tool in paleomagnetism, rock magnetism, and magnetic material studies.

  3. Self-Organizing Maps Neural Networks Applied to the Classification of Ethanol Samples According to the Region of Commercialization

    Directory of Open Access Journals (Sweden)

    Aline Regina Walkoff

    2017-10-01

    Full Text Available Physical-chemical analysis data were collected, from 998 ethanol samples of automotive ethanol commercialized in the northern, midwestern and eastern regions of the state of Paraná. The data presented self-organizing maps (SOM neural networks, which classified them according to those regions. The self-organizing maps best configuration had a 45 x 45 topology and 5000 training epochs, with a final learning rate of 6.7x10-4, a final neighborhood relationship of 3x10-2 and a mean quantization error of 2x10-2. This neural network provided a topological map depicting three separated groups, each one corresponding to samples of a same region of commercialization. Four maps of weights, one for each parameter, were presented. The network established the pH was the most important variable for classification and electrical conductivity the least one. The self-organizing maps application allowed the segmentation of alcohol samples, therefore identifying them according to the region of commercialization. DOI: http://dx.doi.org/10.17807/orbital.v9i4.982

  4. Quantum perceptron over a field and neural network architecture selection in a quantum computer.

    Science.gov (United States)

    da Silva, Adenilton José; Ludermir, Teresa Bernarda; de Oliveira, Wilson Rosa

    2016-04-01

    In this work, we propose a quantum neural network named quantum perceptron over a field (QPF). Quantum computers are not yet a reality and the models and algorithms proposed in this work cannot be simulated in actual (or classical) computers. QPF is a direct generalization of a classical perceptron and solves some drawbacks found in previous models of quantum perceptrons. We also present a learning algorithm named Superposition based Architecture Learning algorithm (SAL) that optimizes the neural network weights and architectures. SAL searches for the best architecture in a finite set of neural network architectures with linear time over the number of patterns in the training set. SAL is the first learning algorithm to determine neural network architectures in polynomial time. This speedup is obtained by the use of quantum parallelism and a non-linear quantum operator. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Quantum phase transition of the transverse-field quantum Ising model on scale-free networks.

    Science.gov (United States)

    Yi, Hangmo

    2015-01-01

    I investigate the quantum phase transition of the transverse-field quantum Ising model in which nearest neighbors are defined according to the connectivity of scale-free networks. Using a continuous-time quantum Monte Carlo simulation method and the finite-size scaling analysis, I identify the quantum critical point and study its scaling characteristics. For the degree exponent λ=6, I obtain results that are consistent with the mean-field theory. For λ=4.5 and 4, however, the results suggest that the quantum critical point belongs to a non-mean-field universality class. Further simulations indicate that the quantum critical point remains mean-field-like if λ>5, but it continuously deviates from the mean-field theory as λ becomes smaller.

  6. Radial Peripapillary Capillary Network Visualized Using Wide-Field Montage Optical Coherence Tomography Angiography.

    Science.gov (United States)

    Mase, Tomoko; Ishibazawa, Akihiro; Nagaoka, Taiji; Yokota, Harumasa; Yoshida, Akitoshi

    2016-07-01

    We quantitatively analyzed the features of a radial peripapillary capillary (RPC) network visualized using wide-field montage optical coherence tomography (OCT) angiography in healthy human eyes. Twenty eyes of 20 healthy subjects were recruited. En face 3 × 3-mm OCT angiograms of multiple locations in the posterior pole were acquired using the RTVue XR Avanti, and wide-field montage images of the RPC were created. To evaluate the RPC density, the montage images were binarized and skeletonized. The correlation between the RPC density and the retinal nerve fiber layer (RNFL) thickness measured by an OCT circle scan was investigated. The RPC at the temporal retina was detected as far as 7.6 ± 0.7 mm from the edge of the optic disc but not around the perifoveal area within 0.9 ± 0.1 mm of the fovea. Capillary-free zones beside the first branches of the arterioles were significantly (P optic disc edge were 13.6 ± 0.8, 11.9 ± 0.9, and 10.4 ± 0.9 mm-1. The RPC density also was correlated significantly (r = 0.64, P network. The RPC is present in the superficial peripapillary retina in proportion to the RNFL thickness, supporting the idea that the RPC may be the vascular network primarily responsible for RNFL nourishment.

  7. Comparison of dechlorination rates for field DNAPL vs synthetic samples: effect of sample matrix

    Science.gov (United States)

    O'Carroll, D. M.; Sakulchaicharoen, N.; Herrera, J. E.

    2015-12-01

    Nanometals have received significant attention in recent years due to their ability to rapidly destroy numerous priority source zone contaminants in controlled laboratory studies. This has led to great optimism surrounding nanometal particle injection for insitu remediation. Reported dechlorination rates vary widely among different investigators. These differences have been ascribed to differences in the iron types (granular, micro, or nano-sized iron), matrix solution chemistry and the morphology of the nZVI surface. Among these, the effects of solution chemistry on rates of reductive dechlorination of various chlorinated compounds have been investigated in several short-term laboratory studies. Variables investigated include the effect of anions or groundwater solutes such as SO4-2, Cl-, NO3-, pH, natural organic matters (NOM), surfactant, and humic acid on dechlorination reaction of various chlorinated compounds such as TCE, carbon tetrachloride (CT), and chloroform (CF). These studies have normally centered on the assessment of nZVI reactivity toward dechlorination of an isolated individual contaminant spiked into a ground water sample under ideal conditions, with limited work conducted using real field samples. In this work, the DNAPL used for the dechlorination study was obtained from a contaminatied site. This approach was selected to adequately simulate a condition where the nZVI suspension was in direct contact with DNAPL and to isolate the dechlorination activity shown by the nZVI from the groundwater matrix effects. An ideal system "synthetic DNAPL" composed of a mixture of chlorinated compounds mimicking the composition of the actual DNAPL was also dechlorinated to evaluate the DNAPL "matrix effect" on NZVI dechlorination activity. This approach allowed us to evaluate the effect of the presence of different types of organic compounds (volatile fatty acids and humic acids) found in the actual DNAPL on nZVI dechlorination activity. This presentation will

  8. Reconstructing the Hopfield network as an inverse Ising problem

    International Nuclear Information System (INIS)

    Huang Haiping

    2010-01-01

    We test four fast mean-field-type algorithms on Hopfield networks as an inverse Ising problem. The equilibrium behavior of Hopfield networks is simulated through Glauber dynamics. In the low-temperature regime, the simulated annealing technique is adopted. Although performances of these network reconstruction algorithms on the simulated network of spiking neurons are extensively studied recently, the analysis of Hopfield networks is lacking so far. For the Hopfield network, we found that, in the retrieval phase favored when the network wants to memory one of stored patterns, all the reconstruction algorithms fail to extract interactions within a desired accuracy, and the same failure occurs in the spin-glass phase where spurious minima show up, while in the paramagnetic phase, albeit unfavored during the retrieval dynamics, the algorithms work well to reconstruct the network itself. This implies that, as an inverse problem, the paramagnetic phase is conversely useful for reconstructing the network while the retrieval phase loses all the information about interactions in the network except for the case where only one pattern is stored. The performances of algorithms are studied with respect to the system size, memory load, and temperature; sample-to-sample fluctuations are also considered.

  9. Wireless networks of opportunity in support of secure field operations

    Science.gov (United States)

    Stehle, Roy H.; Lewis, Mark

    1997-02-01

    Under funding from the Defense Advanced Research Projects Agency (DARPA) for joint military and law enforcement technologies, demonstrations of secure information transfer in support of law enforcement and military operations other than war, using wireless and wired technology, were held in September 1996 at several locations in the United States. In this paper, the network architecture, protocols, and equipment supporting the demonstration's scenarios are presented, together with initial results, including lessons learned and desired system enhancements. Wireless networks of opportunity encompassed in-building (wireless-LAN), campus-wide (Metricom Inc.), metropolitan (AMPS cellular, CDPD), and national (one- and two-way satellite) systems. Evolving DARPA-sponsored packet radio technology was incorporated. All data was encrypted, using multilevel information system security initiative (MISSI)FORTEZZA technology, for carriage over unsecured and unclassified commercial networks. The identification and authentication process inherent in the security system permitted logging for database accesses and provided an audit trail useful in evidence gathering. Wireless and wireline communications support, to and between modeled crisis management centers, was demonstrated. Mechanisms for the guarded transport of data through the secret-high military tactical Internet were included, to support joint law enforcement and crisis management missions. A secure World Wide Web (WWW) browser forms the primary, user-friendly interface for information retrieval and submission. The WWW pages were structured to be sensitive to the bandwidth, error rate, and cost of the communications medium in use (e.g., the use of and resolution for graphical data). Both still and motion compressed video were demonstrated, along with secure voice transmission from laptop computers in the field. Issues of network bandwidth, airtime costs, and deployment status are discussed.

  10. Importance Sampling for a Markov Modulated Queuing Network with Customer Impatience until the End of Service

    Directory of Open Access Journals (Sweden)

    Ebrahim MAHDIPOUR

    2009-01-01

    Full Text Available For more than two decades, there has been a growing of interest in fast simulation techniques for estimating probabilities of rare events in queuing networks. Importance sampling is a variance reduction method for simulating rare events. The present paper carries out strict deadlines to the paper by Dupuis et al for a two node tandem network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We derive a closed form solution for the probability of missing deadlines. Then we have employed the results to an importance sampling technique to estimate the probability of total population overflow which is a rare event. We have also shown that the probability of this rare event may be affected by various deadline values.

  11. Representative Delay Measurements (RDM: Facing the Challenge of Modern Networks

    Directory of Open Access Journals (Sweden)

    Joachim Fabini

    2015-02-01

    Full Text Available Network access technologies have evolved significantly in the last years. They deploy novel mechanisms like reactive capacity allocation and time-slotted operation to optimize overall network capacity. From a single node's perspective, such optimizations decrease network determinism and measurement repeatability. Evolving application fields like machine to machine (M2M communications or real-time gaming often have strict real-time requirements to operate correctly. Highly accurate delay measurements are necessary to monitor network compliance with application demands or to detect deviations of normal network behavior, which may be caused by network failures, misconfigurations or attacks. This paper analyzes factors that challenge active delay measurements in modern networks. It introduces the Representative Delay Measurement tool (RDM that addresses these factors and proposes solutions that conform to requirements of the recently published RFC7312. Delay measurement results acquired using RDM in live networks confirm that advanced measurement methods can significantly improve the quality of measurement samples by isolating systematic network behavior. The resulting high-quality samples are one prerequisite for accurate statistics that support proper operation of subsequent algorithms and applications.

  12. 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.

  13. Does respondent driven sampling alter the social network composition and health-seeking behaviors of illicit drug users followed prospectively?

    Directory of Open Access Journals (Sweden)

    Abby E Rudolph

    2011-05-01

    Full Text Available Respondent driven sampling (RDS was originally developed to sample and provide peer education to injection drug users at risk for HIV. Based on the premise that drug users' social networks were maintained through sharing rituals, this peer-driven approach to disseminate educational information and reduce risk behaviors capitalizes and expands upon the norms that sustain these relationships. Compared with traditional outreach interventions, peer-driven interventions produce greater reductions in HIV risk behaviors and adoption of safer behaviors over time, however, control and intervention groups are not similarly recruited. As peer-recruitment may alter risk networks and individual risk behaviors over time, such comparison studies are unable to isolate the effect of a peer-delivered intervention. This analysis examines whether RDS recruitment (without an intervention is associated with changes in health-seeking behaviors and network composition over 6 months. New York City drug users (N = 618 were recruited using targeted street outreach (TSO and RDS (2006-2009. 329 non-injectors (RDS = 237; TSO = 92 completed baseline and 6-month surveys ascertaining demographic, drug use, and network characteristics. Chi-square and t-tests compared RDS- and TSO-recruited participants on changes in HIV testing and drug treatment utilization and in the proportion of drug using, sex, incarcerated and social support networks over the follow-up period. The sample was 66% male, 24% Hispanic, 69% black, 62% homeless, and the median age was 35. At baseline, the median network size was 3, 86% used crack, 70% used cocaine, 40% used heroin, and in the past 6 months 72% were tested for HIV and 46% were enrolled in drug treatment. There were no significant differences by recruitment strategy with respect to changes in health-seeking behaviors or network composition over 6 months. These findings suggest no association between RDS recruitment and changes in

  14. Calculating ensemble averaged descriptions of protein rigidity without sampling.

    Science.gov (United States)

    González, Luis C; Wang, Hui; Livesay, Dennis R; Jacobs, Donald J

    2012-01-01

    Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG) algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG) that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars) that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged [Formula: see text] properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.

  15. Phase transitions in scale-free neural networks: Departure from the standard mean-field universality class

    International Nuclear Information System (INIS)

    Aldana, Maximino; Larralde, Hernan

    2004-01-01

    We investigate the nature of the phase transition from an ordered to a disordered state that occurs in a family of neural network models with noise. These models are closely related to the majority voter model, where a ferromagneticlike interaction between the elements prevails. Each member of the family is distinguished by the network topology, which is determined by the probability distribution of the number of incoming links. We show that for homogeneous random topologies, the phase transition belongs to the standard mean-field universality class, characterized by the order parameter exponent β=1/2. However, for scale-free networks we obtain phase transition exponents ranging from 1/2 to infinity. Furthermore, we show the existence of a phase transition even for values of the scale-free exponent in the interval (1.5,2], where the average network connectivity diverges

  16. The Study of Indoor and Field Trials on 2×8 MIMO Architecture in TD-LTE Network

    Directory of Open Access Journals (Sweden)

    Xiang Zhang

    2013-01-01

    the networks are based on frequency division duplexing (FDD. In this paper, measurement methods of four MIMO transmission modes (TMs in time division-LTE (TD-LTE are studied and analyzed. Link level simulation is carried out to evaluate the downlink throughput for different signal-to-noise ratios and parameter settings. Furthermore, indoor and field tests are also presented in the paper to investigate how real-world propagation affects the capacity and the error performance of MIMO transmission scheme. For the indoor test, radio channel emulators are applied to generate realistic wireless fading channel, while in the field trials, a live TD-LTE experiment cellular network is built, which contains several evolved nodeBs (eNBs and a precommercial user equipment (UE. It is shown from both simulation and tests results that MIMO deployment gives a substantial performance improvement compared with the third generation wireless networks.

  17. Genus-Specific Primers for Study of Fusarium Communities in Field Samples

    Science.gov (United States)

    Edel-Hermann, Véronique; Gautheron, Nadine; Durling, Mikael Brandström; Kolseth, Anna-Karin; Steinberg, Christian; Persson, Paula; Friberg, Hanna

    2015-01-01

    Fusarium is a large and diverse genus of fungi of great agricultural and economic importance, containing many plant pathogens and mycotoxin producers. To date, high-throughput sequencing of Fusarium communities has been limited by the lack of genus-specific primers targeting regions with high discriminatory power at the species level. In the present study, we evaluated two Fusarium-specific primer pairs targeting translation elongation factor 1 (TEF1). We also present the new primer pair Fa+7/Ra+6. Mock Fusarium communities reflecting phylogenetic diversity were used to evaluate the accuracy of the primers in reflecting the relative abundance of the species. TEF1 amplicons were subjected to 454 high-throughput sequencing to characterize Fusarium communities. Field samples from soil and wheat kernels were included to test the method on more-complex material. For kernel samples, a single PCR was sufficient, while for soil samples, nested PCR was necessary. The newly developed primer pairs Fa+7/Ra+6 and Fa/Ra accurately reflected Fusarium species composition in mock DNA communities. In field samples, 47 Fusarium operational taxonomic units were identified, with the highest Fusarium diversity in soil. The Fusarium community in soil was dominated by members of the Fusarium incarnatum-Fusarium equiseti species complex, contradicting findings in previous studies. The method was successfully applied to analyze Fusarium communities in soil and plant material and can facilitate further studies of Fusarium ecology. PMID:26519387

  18. Temperature and flow fields in samples heated in monoellipsoidal mirror furnaces

    Science.gov (United States)

    Rivas, D.; Haya, R.

    The temperature field in samples heated in monoellipsoidal mirror furnaces will be analyzed. The radiation heat exchange between the sample and the mirror is formulated analytically, taking into account multiple reflections at the mirror. It will be shown that the effect of these multiple reflections in the heating process is quite important, and, as a consequence, the effect of the mirror reflectance in the temperature field is quite strong. The conduction-radiation model will be used to simulate the heating process in the floating-zone technique in microgravity conditions; important parameters like the Marangoni number (that drives the thermocapillary flow in the melt), and the temperature gradient at the melt-crystal interface will be estimated. The model will be validated comparing with experimental data. The case of samples mounted in a wall-free configuration (as in the MAXUS-4 programme) will be also considered. Application to the case of compound samples (graphite-silicon-graphite) will be made; the melting of the silicon part and the surface temperature distribution in the melt will be analyzed. Of special interest is the temperature difference between the two graphite rods that hold the silicon part, since it drives the thermocapillary flow in the melt. This thermocapillary flow will be studied, after coupling the previous model with the convective effects. The possibility of counterbalancing this flow by the controlled vibration of the graphite rods will be studied as well. Numerical results show that suppressing the thermocapillary flow can be accomplished quite effectively.

  19. Global analysis of the temperature and flow fields in samples heated in multizone resistance furnaces

    Science.gov (United States)

    Pérez-Grande, I.; Rivas, D.; de Pablo, V.

    The temperature field in samples heated in multizone resistance furnaces will be analyzed, using a global model where the temperature fields in the sample, the furnace and the insulation are coupled; the input thermal data is the electric power supplied to the heaters. The radiation heat exchange between the sample and the furnace is formulated analytically, taking into account specular reflections at the sample; for the solid sample the reflectance is both diffuse and specular, and for the melt it is mostly specular. This behavior is modeled through the exchange view factors, which depend on whether the sample is solid or liquid, and, therefore, they are not known a priori. The effect of this specular behavior in the temperature field will be analyzed, by comparing with the case of diffuse samples. A parameter of great importance is the thermal conductivity of the insulation material; it will be shown that the temperature field depends strongly on it. A careful characterization of the insulation is therefore necessary, here it will be done with the aid of experimental results, which will also serve to validate the model. The heating process in the floating-zone technique in microgravity conditions will be simulated; parameters like the Marangoni number or the temperature gradient at the melt-crystal interface will be estimated. Application to the case of compound samples (graphite-silicon-graphite) will be made; the temperature distribution in the silicon part will be studied, especially the temperature difference between the two graphite rods that hold the silicon, since it drives the thermocapillary flow in the melt. This flow will be studied, after coupling the previous model with the convective effects. The possibility of suppresing this flow by the controlled vibration of the graphite rods will be also analyzed. Numerical results show that the thermocapillary flow can indeed be counterbalanced quite effectively.

  20. Deep recurrent conditional random field network for protein secondary prediction

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

    2017-01-01

    Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

  1. Convolutional neural network using generated data for SAR ATR with limited samples

    Science.gov (United States)

    Cong, Longjian; Gao, Lei; Zhang, Hui; Sun, Peng

    2018-03-01

    Being able to adapt all weather at all times, it has been a hot research topic that using Synthetic Aperture Radar(SAR) for remote sensing. Despite all the well-known advantages of SAR, it is hard to extract features because of its unique imaging methodology, and this challenge attracts the research interest of traditional Automatic Target Recognition(ATR) methods. With the development of deep learning technologies, convolutional neural networks(CNNs) give us another way out to detect and recognize targets, when a huge number of samples are available, but this premise is often not hold, when it comes to monitoring a specific type of ships. In this paper, we propose a method to enhance the performance of Faster R-CNN with limited samples to detect and recognize ships in SAR images.

  2. Application of Artificial Neural Networks to the Analysis of NORM Samples; Aplicación de las Redes Neuronales al Análisis de Muestras NORM

    Energy Technology Data Exchange (ETDEWEB)

    Moser, H.; Peyrés, V.; Mejuto, M.; García-Toraño, E.

    2015-07-01

    This work describes the application of artificial neural networks (ANNs) to analyze the raw data of gamma-ray spectra of NORM samples and decide if the activity content of a certain nuclide is above or below the exemption limit of 1 Bq/g. The main advantage of using an ANN for this purpose is that for the user no specialized knowledge in the field of gamma-ray spectrometry is necessary. In total a number of 635 spectra consisting of varying activity concentrations, seven different materials and three densities each have been generated by Monte Carlo simulation to provide training material to the ANN. These spectra have been created using the simulation code PENELOPE. Validation was carried out with a number of NORM samples previously characterized by conventional gamma-ray spectrometry with peak fitting.

  3. A longitudinal field multiple sampling ionization chamber for RIBLL2

    International Nuclear Information System (INIS)

    Tang Shuwen; Ma Peng; Lu Chengui; Duan Limin; Sun Zhiyu; Yang Herun; Zhang Jinxia; Hu Zhengguo; Xu Shanhu

    2012-01-01

    A longitudinal field MUltiple Sampling Ionization Chamber (MUSIC), which makes multiple measurements of energy loss for very high energy heavy ions at RIBLL2, has been constructed and tested with 3 constituent α source ( 239 Pu : 3.435 MeV, 241 Am : 3.913 MeV, 244 Cm : 4.356 MeV). The voltage plateau curve has been plotted and-500 V is determined as a proper work voltage. The energy resolution is 271.4 keV FWHM for the sampling unit when 3.435 MeV energy deposited. A Geant4 Monte Carlo simulation is made and it indicates the detector can provide unique particle identification for ions Z≥4. (authors)

  4. Analysis of The Game Mechanism in The Field of Network Security between China and the US and The Prospect of The Future

    Directory of Open Access Journals (Sweden)

    Wang Xiang

    2016-12-01

    Full Text Available In the field of Sino-US relations, the network space plays a very important role during a very short period of time. In recent years, the intensity and frequency of Chinese and American network security game has increased significantly, which has increased the instability of Sino-US relations. This paper reviews the network security game events between China and the US in recent years, and points out that network security has become a high risk problem in the relationship between China and the US and it has become the factors affecting the whole area. Network security issues need cooperation between China and the US to develop guidelines for the conduct of Cyberspace. As regards the prospect of Sino-US cyber security relations in the future, this paper argues that the strength and strategy in the Internet field of China and the US lead to the likelihood that China and the US fall into the “prisoner’s dilemma”. China and the US have to control the network security game to prevent damage to the overall situation of Sino-US relations; this is very urgent. Strengthening the network security fields of cooperation between China and the US is an inevitable choice both in terms of necessity and possibility.

  5. DeepCotton: in-field cotton segmentation using deep fully convolutional network

    Science.gov (United States)

    Li, Yanan; Cao, Zhiguo; Xiao, Yang; Cremers, Armin B.

    2017-09-01

    Automatic ground-based in-field cotton (IFC) segmentation is a challenging task in precision agriculture, which has not been well addressed. Nearly all the existing methods rely on hand-crafted features. Their limited discriminative power results in unsatisfactory performance. To address this, a coarse-to-fine cotton segmentation method termed "DeepCotton" is proposed. It contains two modules, fully convolutional network (FCN) stream and interference region removal stream. First, FCN is employed to predict initially coarse map in an end-to-end manner. The convolutional networks involved in FCN guarantee powerful feature description capability, simultaneously, the regression analysis ability of neural network assures segmentation accuracy. To our knowledge, we are the first to introduce deep learning to IFC segmentation. Second, our proposed "UP" algorithm composed of unary brightness transformation and pairwise region comparison is used for obtaining interference map, which is executed to refine the coarse map. The experiments on constructed IFC dataset demonstrate that our method outperforms other state-of-the-art approaches, either in different common scenarios or single/multiple plants. More remarkable, the "UP" algorithm greatly improves the property of the coarse result, with the average amplifications of 2.6%, 2.4% on accuracy and 8.1%, 5.5% on intersection over union for common scenarios and multiple plants, separately.

  6. KMTNET: A Network of 1.6 m Wide-Field Optical Telescopes Installed at Three Southern Observatories

    Science.gov (United States)

    Kim, Seung-Lee; Lee, Chung-Uk; Park, Byeong-Gon; Kim, Dong-Jin; Cha, Sang-Mok; Lee, Yongseok; Han, Cheongho; Chun, Moo-Young; Yuk, Insoo

    2016-02-01

    The Korea Microlensing Telescope Network (KMTNet) is a wide-field photometric system installed by the Korea Astronomy and Space Science Institute (KASI). Here, we present the overall technical specifications of the KMTNet observation system, test observation results, data transfer and image processing procedure, and finally, the KMTNet science programs. The system consists of three 1.6 m wide-field optical telescopes equipped with mosaic CCD cameras of 18k by 18k pixels. Each telescope provides a 2.0 by 2.0 square degree field of view. We have finished installing all three telescopes and cameras sequentially at the Cerro-Tololo Inter-American Observatory (CTIO) in Chile, the South African Astronomical Observatory (SAAO) in South Africa, and the Siding Spring Observatory (SSO) in Australia. This network of telescopes, which is spread over three different continents at a similar latitude of about -30 degrees, enables 24-hour continuous monitoring of targets observable in the Southern Hemisphere. The test observations showed good image quality that meets the seeing requirement of less than 1.0 arcsec in I-band. All of the observation data are transferred to the KMTNet data center at KASI via the international network communication and are processed with the KMTNet data pipeline. The primary scientific goal of the KMTNet is to discover numerous extrasolar planets toward the Galactic bulge by using the gravitational microlensing technique, especially earth-mass planets in the habitable zone. During the non-bulge season, the system is used for wide-field photometric survey science on supernovae, asteroids, and external galaxies.

  7. The SCPRI (Central Service of Protection against Ionizing Radiation) in France: its sampling and surveying network

    International Nuclear Information System (INIS)

    1994-06-01

    The SCPRI, organism placed under tutelage of Ministers in charge of Health and Work, has the mission to practice every measurement, analysis or dosage of radioactivity or ionizing radiation in media where their presence is a risk for health. This mission involves radioactivity measurement on sampling like waters, air, vegetables, food chain. There is an important network of sampling on the whole national territory with a distribution in different climatic areas and also near the nuclear sites. It makes about 50 000 sampling by year with, for each one, different analysis and measurement

  8. Social network recruitment for Yo Puedo: an innovative sexual health intervention in an underserved urban neighborhood—sample and design implications.

    Science.gov (United States)

    Minnis, Alexandra M; vanDommelen-Gonzalez, Evan; Luecke, Ellen; Cheng, Helen; Dow, William; Bautista-Arredondo, Sergio; Padian, Nancy S

    2015-02-01

    Most existing evidence-based sexual health interventions focus on individual-level behavior, even though there is substantial evidence that highlights the influential role of social environments in shaping adolescents' behaviors and reproductive health outcomes. We developed Yo Puedo, a combined conditional cash transfer and life skills intervention for youth to promote educational attainment, job training, and reproductive health wellness that we then evaluated for feasibility among 162 youth aged 16-21 years in a predominantly Latino community in San Francisco, CA. The intervention targeted youth's social networks and involved recruitment and randomization of small social network clusters. In this paper we describe the design of the feasibility study and report participants' baseline characteristics. Furthermore, we examined the sample and design implications of recruiting social network clusters as the unit of randomization. Baseline data provide evidence that we successfully enrolled high risk youth using a social network recruitment approach in community and school-based settings. Nearly all participants (95%) were high risk for adverse educational and reproductive health outcomes based on multiple measures of low socioeconomic status (81%) and/or reported high risk behaviors (e.g., gang affiliation, past pregnancy, recent unprotected sex, frequent substance use; 62%). We achieved variability in the study sample through heterogeneity in recruitment of the index participants, whereas the individuals within the small social networks of close friends demonstrated substantial homogeneity across sociodemographic and risk profile characteristics. Social networks recruitment was feasible and yielded a sample of high risk youth willing to enroll in a randomized study to evaluate a novel sexual health intervention.

  9. Accuracy and Effort of Interpolation and Sampling: Can GIS Help Lower Field Costs?

    Directory of Open Access Journals (Sweden)

    Greg Simpson

    2014-12-01

    Full Text Available Sedimentation is a problem for all reservoirs in the Black Hills of South Dakota. Before working on sediment removal, a survey on the extent and distribution of the sediment is needed. Two sample lakes were used to determine which of three interpolation methods gave the most accurate volume results. A secondary goal was to see if fewer samples could be taken while still providing similar results. The smaller samples would mean less field time and thus lower costs. Subsamples of 50%, 33% and 25% were taken from the total samples and evaluated for the lowest Root Mean Squared Error values. Throughout the trials, the larger sample sizes generally showed better accuracy than smaller samples. Graphing the sediment volume estimates of the full sample, 50%, 33% and 25% showed little improvement after a sample of approximately 40%–50% when comparing the asymptote of the separate samples. When we used smaller subsamples the predicted sediment volumes were normally greater than the full sample volumes. It is suggested that when planning future sediment surveys, workers plan on gathering data at approximately every 5.21 meters. These sample sizes can be cut in half and still retain relative accuracy if time savings are needed. Volume estimates may slightly suffer with these reduced samples sizes, but the field work savings can be of benefit. Results from these surveys are used in prioritization of available funds for reclamation efforts.

  10. Path integral methods for primordial density perturbations - sampling of constrained Gaussian random fields

    International Nuclear Information System (INIS)

    Bertschinger, E.

    1987-01-01

    Path integrals may be used to describe the statistical properties of a random field such as the primordial density perturbation field. In this framework the probability distribution is given for a Gaussian random field subjected to constraints such as the presence of a protovoid or supercluster at a specific location in the initial conditions. An algorithm has been constructed for generating samples of a constrained Gaussian random field on a lattice using Monte Carlo techniques. The method makes possible a systematic study of the density field around peaks or other constrained regions in the biased galaxy formation scenario, and it is effective for generating initial conditions for N-body simulations with rare objects in the computational volume. 21 references

  11. Electric field computation and measurements in the electroporation of inhomogeneous samples

    Science.gov (United States)

    Bernardis, Alessia; Bullo, Marco; Campana, Luca Giovanni; Di Barba, Paolo; Dughiero, Fabrizio; Forzan, Michele; Mognaschi, Maria Evelina; Sgarbossa, Paolo; Sieni, Elisabetta

    2017-12-01

    In clinical treatments of a class of tumors, e.g. skin tumors, the drug uptake of tumor tissue is helped by means of a pulsed electric field, which permeabilizes the cell membranes. This technique, which is called electroporation, exploits the conductivity of the tissues: however, the tumor tissue could be characterized by inhomogeneous areas, eventually causing a non-uniform distribution of current. In this paper, the authors propose a field model to predict the effect of tissue inhomogeneity, which can affect the current density distribution. In particular, finite-element simulations, considering non-linear conductivity against field relationship, are developed. Measurements on a set of samples subject to controlled inhomogeneity make it possible to assess the numerical model in view of identifying the equivalent resistance between pairs of electrodes.

  12. Social Network Status and Depression among Adolescents: An Examination of Social Network Influences and Depressive Symptoms in a Chinese Sample

    OpenAIRE

    Okamoto, Janet; Johnson, C. Anderson; Leventhal, Adam; Milam, Joel; Pentz, Mary Ann; Schwartz, David; Valente, Thomas W.

    2011-01-01

    Despite the well established influence of peer experiences on adolescent attitudes, thoughts, and behaviors, surprisingly little research has examined the importance of peer context and the increased prevalence of depressive symptoms accompanying the transition into adolescence. Examination of social networks may provide some insight into the role of peers in the vulnerability of some adolescents to depression. To address this issue, we leveraged an existing sample of 5,563 Chinese 10th grade...

  13. Multistatic Array Sampling Scheme for Fast Near-Field Image Reconstruction

    Science.gov (United States)

    2016-01-01

    human-sized scene in 0.048sec− 0.101sec. Index Terms—Microwave imaging, multistatic radar, Fast Fourier Transform (FFT). I. INTRODUCTION Near-field...configuration, but its computational demands are extreme. Fast Fourier Transform (FFT) imaging has long been used to efficiently construct images sampled...with the block diagram depicted in Fig. 4. It is noted that the multistatic to monostatic correction is valid over a finite imaging domain. However, as

  14. Social networks of men who have sex with men: a study of recruitment chains using Respondent Driven Sampling in Salvador, Bahia State, Brazil.

    Science.gov (United States)

    Brignol, Sandra Mara Silva; Dourado, Inês; Amorim, Leila Denise; Miranda, José Garcia Vivas; Kerr, Lígia R F S

    2015-11-01

    Social and sexual contact networks between men who have sex with men (MSM) play an important role in understanding the transmission of HIV and other sexually transmitted infections (STIs). In Salvador (Bahia State, Brazil), one of the cities in the survey Behavior, Attitudes, Practices, and Prevalence of HIV and Syphilis among Men Who Have Sex with Men in 10 Brazilian Cities, data were collected in 2008/2009 from a sample of 383 MSM using Respondent Driven Sampling (RDS). Network analysis was used to study friendship networks and sexual partner networks. The study also focused on the association between the number of links (degree) and the number of sexual partners, in addition to socio-demographic characteristics. The networks' structure potentially facilitates HIV transmission. However, the same networks can also be used to spread messages on STI/HIV prevention, since the proximity and similarity of MSM in these networks can encourage behavior change and positive attitudes towards prevention.

  15. Application of a series of artificial neural networks to on-site quantitative analysis of lead into real soil samples by laser induced breakdown spectroscopy

    International Nuclear Information System (INIS)

    El Haddad, J.; Bruyère, D.; Ismaël, A.; Gallou, G.; Laperche, V.; Michel, K.; Canioni, L.; Bousquet, B.

    2014-01-01

    Artificial neural networks were applied to process data from on-site LIBS analysis of soil samples. A first artificial neural network allowed retrieving the relative amounts of silicate, calcareous and ores matrices into soils. As a consequence, each soil sample was correctly located inside the ternary diagram characterized by these three matrices, as verified by ICP-AES. Then a series of artificial neural networks were applied to quantify lead into soil samples. More precisely, two models were designed for classification purpose according to both the type of matrix and the range of lead concentrations. Then, three quantitative models were locally applied to three data subsets. This complete approach allowed reaching a relative error of prediction close to 20%, considered as satisfying in the case of on-site analysis. - Highlights: • Application of a series of artificial neural networks (ANN) to quantitative LIBS • Matrix-based classification of the soil samples by ANN • Concentration-based classification of the soil samples by ANN • Series of quantitative ANN models dedicated to the analysis of data subsets • Relative error of prediction lower than 20% for LIBS analysis of soil samples

  16. Circulating persistent current and induced magnetic field in a fractal network

    Energy Technology Data Exchange (ETDEWEB)

    Saha, Srilekha [Condensed Matter Physics Division, Saha Institute of Nuclear Physics, Sector-I, Block-AF, Bidhannagar, Kolkata 700 064 (India); Maiti, Santanu K., E-mail: santanu.maiti@isical.ac.in [Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 Barrackpore Trunk Road, Kolkata 700 108 (India); Karmakar, S.N. [Condensed Matter Physics Division, Saha Institute of Nuclear Physics, Sector-I, Block-AF, Bidhannagar, Kolkata 700 064 (India)

    2016-04-29

    We present the overall conductance as well as the circulating currents in individual loops of a Sierpinski gasket (SPG) as we apply bias voltage via the side attached electrodes. SPG being a self-similar structure, its manifestation on loop currents and magnetic fields is examined in various generations of this fractal and it has been observed that for a given configuration of the electrodes, the physical quantities exhibit certain regularity as we go from one generation to another. Also a notable feature is the introduction of anisotropy in hopping causes an increase in magnitude of overall transport current. These features are a subject of interest in this article. - Highlights: • Voltage driven circular current is analyzed in a fractal network. • Current induced magnetic field is strong enough to flip a spin. • Anisotropy in hopping enhances overall transport current.

  17. The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory.

    Science.gov (United States)

    Li, Man; Wang, Yanhui; Jia, Limin

    2017-01-01

    Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.

  18. The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory.

    Directory of Open Access Journals (Sweden)

    Man Li

    Full Text Available Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.

  19. New method for the exact determination of the effective conductivity and the local field in RLC networks

    International Nuclear Information System (INIS)

    Zekri, L.; Zekri, N.; Bouamrane, R.

    1999-10-01

    We present a new numerical method for determining exactly the effective conductivity and the local field for random RLC networks. This method is compared to a real space renormalization group method and the Frank and Lobb method. Although our method is slower than the Frank and Lobb method, it also computes exactly the local field for large size systems. We also show that the renormalization group method fails in determining the local field. (author)

  20. Types of non-probabilistic sampling used in marketing research. „Snowball” sampling

    OpenAIRE

    Manuela Rozalia Gabor

    2007-01-01

    A significant way of investigating a firm’s market is the statistical sampling. The sampling typology provides a non / probabilistic models of gathering information and this paper describes thorough information related to network sampling, named “snowball” sampling. This type of sampling enables the survey of occurrence forms concerning the decision power within an organisation and of the interpersonal relation network governing a certain collectivity, a certain consumer panel. The snowball s...

  1. High-conductance states in a mean-field cortical network model

    CERN Document Server

    Lerchner, A; Hertz, J

    2004-01-01

    Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1 due to the tendency of spikes being clustered into bursts. We show that this behavior emerges naturally in a balanced cortical network model with random connectivity and conductance-based synapses. We employ mean field theory with correctly colored noise to describe temporal correlations in the neuronal activity. Our results illuminate the connection between two independent experimental findings: high conductance states of cortical neurons in their natural environment, and variable non-Poissonian spike statistics with Fano factors greater than 1.

  2. Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

    Science.gov (United States)

    Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

    2015-02-04

    In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

  3. Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

    Directory of Open Access Journals (Sweden)

    Yong Cui

    2015-02-01

    Full Text Available In the wireless sensor networks (WSNs for electric field measurement system under the High-Voltage Direct Current (HVDC transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes’ neighbor lists based on the Received Signal Strength Indicator (RSSI values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

  4. Delays and networked control systems

    CERN Document Server

    Hetel, Laurentiu; Daafouz, Jamal; Johansson, Karl

    2016-01-01

    This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students. .

  5. Convolutional Neural Networks with Batch Normalization for Classifying Hi-hat, Snare, and Bass Percussion Sound Samples

    DEFF Research Database (Denmark)

    Gajhede, Nicolai; Beck, Oliver; Purwins, Hendrik

    2016-01-01

    After having revolutionized image and speech processing, convolu- tional neural networks (CNN) are now starting to become more and more successful in music information retrieval as well. We compare four CNN types for classifying a dataset of more than 3000 acoustic and synthesized samples...

  6. Statistical mechanics of a multiconnected Hopfield neural-network model in a transverse field

    International Nuclear Information System (INIS)

    Ma, Y.; Gong, C.

    1995-01-01

    The Hopfield neural-network model with p-spin interactions in the presence of a transverse field is introduced and solved exactly in the limit p→∞. In the phase diagrams drawn as a function of the temperature, the important results such as reentrance are found, and the effects of the quantum fluctuations on the phase transitions, the retrieval phase, and the storage ratio α are examined

  7. Calculating ensemble averaged descriptions of protein rigidity without sampling.

    Directory of Open Access Journals (Sweden)

    Luis C González

    Full Text Available Previous works have demonstrated that protein rigidity is related to thermodynamic stability, especially under conditions that favor formation of native structure. Mechanical network rigidity properties of a single conformation are efficiently calculated using the integer body-bar Pebble Game (PG algorithm. However, thermodynamic properties require averaging over many samples from the ensemble of accessible conformations to accurately account for fluctuations in network topology. We have developed a mean field Virtual Pebble Game (VPG that represents the ensemble of networks by a single effective network. That is, all possible number of distance constraints (or bars that can form between a pair of rigid bodies is replaced by the average number. The resulting effective network is viewed as having weighted edges, where the weight of an edge quantifies its capacity to absorb degrees of freedom. The VPG is interpreted as a flow problem on this effective network, which eliminates the need to sample. Across a nonredundant dataset of 272 protein structures, we apply the VPG to proteins for the first time. Our results show numerically and visually that the rigidity characterizations of the VPG accurately reflect the ensemble averaged [Formula: see text] properties. This result positions the VPG as an efficient alternative to understand the mechanical role that chemical interactions play in maintaining protein stability.

  8. Using Social Network Analysis to Better Understand Compulsive Exercise Behavior Among a Sample of Sorority Members.

    Science.gov (United States)

    Patterson, Megan S; Goodson, Patricia

    2017-05-01

    Compulsive exercise, a form of unhealthy exercise often associated with prioritizing exercise and feeling guilty when exercise is missed, is a common precursor to and symptom of eating disorders. College-aged women are at high risk of exercising compulsively compared with other groups. Social network analysis (SNA) is a theoretical perspective and methodology allowing researchers to observe the effects of relational dynamics on the behaviors of people. SNA was used to assess the relationship between compulsive exercise and body dissatisfaction, physical activity, and network variables. Descriptive statistics were conducted using SPSS, and quadratic assignment procedure (QAP) analyses were conducted using UCINET. QAP regression analysis revealed a statistically significant model (R 2 = .375, P exercise behavior. Physical activity, body dissatisfaction, and network variables were statistically significant predictor variables in the QAP regression model. In our sample, women who are connected to "important" or "powerful" people in their network are likely to have higher compulsive exercise scores. This result provides healthcare practitioners key target points for intervention within similar groups of women. For scholars researching eating disorders and associated behaviors, this study supports looking into group dynamics and network structure in conjunction with body dissatisfaction and exercise frequency.

  9. Field emission from vertically aligned few-layer graphene

    International Nuclear Information System (INIS)

    Malesevic, Alexander; Kemps, Raymond; Vanhulsel, Annick; Chowdhury, Manish Pal; Volodin, Alexander; Van Haesendonck, Chris

    2008-01-01

    The electric field emission behavior of vertically aligned few-layer graphene was studied in a parallel plate-type setup. Few-layer graphene was synthesized in the absence of any metallic catalyst by microwave plasma enhanced chemical vapor deposition with gas mixtures of methane and hydrogen. The deposit consists of nanostructures that are several micrometers wide, highly crystalline stacks of four to six atomic layers of graphene, aligned vertically to the substrate surface in a high density network. The few-layer graphene is found to be a good field emitter, characterized by turn-on fields as low as 1 V/μm and field amplification factors up to several thousands. We observe a clear dependence of the few-layer graphene field emission behavior on the synthesis parameters: Hydrogen is identified as an efficient etchant to improve field emission, and samples grown on titanium show lower turn-on field values and higher amplification factors when compared to samples grown on silicon

  10. Intelligent networked teleoperation control

    CERN Document Server

    Li, Zhijun; Su, Chun-Yi

    2015-01-01

    This book describes a unified framework for networked teleoperation systems involving multiple research fields: networked control systems for linear and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral teleoperation and cooperative teleoperation. It closely examines networked control as a field at the intersection of systems & control and robotics and presents a number of experimental case studies on testbeds for robotic systems, including networked haptic devices, robotic network systems and sensor network systems. The concepts and results outlined are easy to understand, even for readers fairly new to the subject. As such, the book offers a valuable reference work for researchers and engineers in the fields of systems & control and robotics.

  11. Sampling history and 2009--2010 results for pesticides and inorganic constituents monitored by the Lake Wales Ridge Groundwater Network, central Florida

    Science.gov (United States)

    Choquette, Anne F.; Freiwald, R. Scott; Kraft, Carol L.

    2012-01-01

    The Lake Wales Ridge Monitoring (LWRM) Network was established to provide a long-term record of water quality of the surficial aquifer in one of the principal citrus-production areas of Florida. This region is underlain by sandy soils that contain minimal organic matter and are highly vulnerable to leaching of chemicals into the subsurface. This report documents the 1989 through May 2010 sampling history of the LWRM Network and summarizes monitoring results for 38 Network wells that were sampled during the period January 2009 through May 2010. During 1989 through May 2010, the Network’s citrus land-use wells were sampled intermittently to 1999, quarterly from April 1999 to October 2009, and thereafter quarterly to semiannually. The water-quality summaries in this report focus on the period January 2009 through May 2010, during which the Network’s citrus land-use wells were sampled six times and the non-citrus land-use wells were sampled two times. Within the citrus land-use wells sampled, a total of 13 pesticide compounds (8 parent pesticides and 5 degradates) were detected of the 37 pesticide compounds analyzed during this period. The most frequently detected compounds included demethyl norflurazon (83 percent of wells), norflurazon (79 percent), aldicarb sulfoxide (41 percent), aldicarb sulfone (38 percent), imidacloprid (38 percent), and diuron (28 percent). Agrichemical concentrations in samples from the citrus land-use wells during the 2009 through May 2010 period exceeded Federal drinking-water standards (maximum contaminant levels, MCLs) in 1.5 to 24 percent of samples for aldicarb and its degradates (sulfone and sulfoxide), and in 68 percent of the samples for nitrate. Florida statutes restrict the distance of aldicarb applications to drinking-water wells; however, these statutes do not apply to monitoring wells. Health-screening benchmark levels that identify unregulated chemicals of potential concern were exceeded for norflurazon and diuron in 29 and

  12. Ratio methods for cost-effective field sampling of commercial radioactive low-level wastes

    International Nuclear Information System (INIS)

    Eberhardt, L.L.; Simmons, M.A.; Thomas, J.M.

    1985-07-01

    In many field studies to determine the quantities of radioactivity at commercial low-level radioactive waste sites, preliminary appraisals are made with field radiation detectors, or other relatively inaccurate devices. More accurate determinations are subsequently made with procedures requiring chemical separations or other expensive analyses. Costs of these laboratory determinations are often large, so that adequate sampling may not be achieved due to budget limitations. In this report, we propose double sampling as a way to combine the expensive and inexpensive aproaches to substantially reduce overall costs. The underlying theory was developed for human and agricultural surveys, and is partially based on assumptions that are not appropriate for commercial low-level waste sites. Consequently, extensive computer simulations were conducted to determine whether the results can be applied in circumstances of importance to the Nuclear Regulatory Commission. This report gives the simulation details, and concludes that the principal equations are appropriate for most studies at commercial low-level waste sites. A few points require further research, using actual commercial low-level radioactive waste site data. The final section of the report provides some guidance (via an example) for the field use of double sampling. Details of the simulation programs are available from the authors. Major findings are listed in the Executive Summary. 9 refs., 9 figs., 30 tabs

  13. Consuming Social Networks: A Study on BeeTalk Network

    Directory of Open Access Journals (Sweden)

    Jamal Mohammadi

    Full Text Available BeeTalk is one of the most common social networks that have attracted many users during these years. As a whole, social networks are parts of everyday life nowadays and, especially among the new generation, have caused some basic alterations in the field of identity-formation, sense-making and the form and content of communication. This article is a research about BeeTalk users, their virtual interactions and experiences, and the feelings, pleasures, meanings and attitudes that they obtain through participating in the virtual world. This is a qualitative research. The sample is selected by way of theoretical sampling among the students of University of Kurdistan. Direct observation and semistructured interviews are used to gathering data, which are interpreted through grounded theory. The findings show that some contexts like “searching real interests in a non-real world” and “the representation of users’ voices in virtual space” have provided the space for participating in BeeTalk, and an intervening factor called “instant availability” has intensified this participation. Users’ participation in this social network has changed their social interaction in the real world and formed some new types of communication among them such as “representation of faked identities”, “experiencing ceremonial space” and “artificial literacy”. Moreover, this participation has some consequences like “virtual addiction” and “virtual collectivism” in users’ everyday life that effects their ways of providing meaning and identity in their social lives. It can be said that the result of user’s activity in this network is to begin a kind of simulated relation that has basic differences with relations in the real world. The experience of relation in this network lacks nobility, enrichment and animation, rather it is instant, artificial and without any potential to vitalization.

  14. Social networks of men who have sex with men: a study of recruitment chains using Respondent Driven Sampling in Salvador, Bahia State, Brazil

    Directory of Open Access Journals (Sweden)

    Sandra Mara Silva Brignol

    2015-11-01

    Full Text Available Abstract Social and sexual contact networks between men who have sex with men (MSM play an important role in understanding the transmission of HIV and other sexually transmitted infections (STIs. In Salvador (Bahia State, Brazil, one of the cities in the survey Behavior, Attitudes, Practices, and Prevalence of HIV and Syphilis among Men Who Have Sex with Men in 10 Brazilian Cities, data were collected in 2008/2009 from a sample of 383 MSM using Respondent Driven Sampling (RDS. Network analysis was used to study friendship networks and sexual partner networks. The study also focused on the association between the number of links (degree and the number of sexual partners, in addition to socio-demographic characteristics. The networks’ structure potentially facilitates HIV transmission. However, the same networks can also be used to spread messages on STI/HIV prevention, since the proximity and similarity of MSM in these networks can encourage behavior change and positive attitudes towards prevention.

  15. Field manual for geohydrological sampling as applied to the radioactive waste disposal program

    International Nuclear Information System (INIS)

    Levin, M.

    1983-08-01

    This report serves as a manual for geohydrological sampling as practised by NUCOR's Geology Department. It discusses systematically all aspects concerned with sampling and stresses those where negligence has caused complications in the past. Accurate, neat and systematic procedures are emphasised. The report is intended as a reference work for the field technician. Analytical data on water samples provide an indication of the geohydrological processes taking place during the interaction between groundwater and the enclosing aquifers. It is possible to identify water bodies, using some of a multitude of parameters such as major ions, trace elements and isotopes which may give clues as to the origin, directions of flow and age of groundwater bodies. The South African Radioactive Waste Project also requires this information for determining the direction of migration of the radionuclides in the environment in the event of a spillage. The sampling procedures required for water, and in particular groundwater, must be applied in such a manner that the natural variation of dissolved species is not disturbed to any significant degree. With this in mind, the operator has to exercise meticulous care during initial preparation, collection, storing, preserving and handling of the water samples. This report is a field manual and describes the procedures adopted for the Radwaste Project geohydrological investigations in the Northwest Cape

  16. Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots.

    Science.gov (United States)

    Župunski, Vesna; Jevtić, Radivoje; Jokić, Vesna Spasić; Župunski, Ljubica; Lalošević, Mirjana; Ćirić, Mihajlo; Ćurčić, Živko

    2017-06-01

    Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m 2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of soil. Goodness of fit of data to probability distribution tested with χ 2 test confirmed a negative binomial distribution of cyst counts for 21 out of 23 plots. The recommended measure of sampling precision of 17% expressed through coefficient of variation ( cv ) was achieved if the plots of 1 m 2 contaminated with more than 90 cysts per 100 g of soil were sampled with 10-core bulk samples taken in five repetitions. If plots were contaminated with less than 75 cysts per 100 g of soil, 10-core bulk samples taken in seven repetitions gave cv higher than 23%. This study indicates that more attention should be paid on estimation of sampling error in experimental field plots to ensure more reliable estimation of population density of cyst nematodes.

  17. Electro-Optic Sampling of Transient Electric Fields from Charged Particle Beams

    Energy Technology Data Exchange (ETDEWEB)

    Fitch, Michael James [Rochester U.

    2000-01-01

    The passage of a relativistic charged particle beam bunch through a structure is accompanied by transient electromagnetic fields. By causality, these fields must be behind the bunch, and are called "wakefields." The wakefields act back on the beam, and cause instabilities such as the beam break-up instability, and the headtail instability, which limit the luminosity of linear colliders. The wakefields are particularly important for short bunches with high charge. A great deal of effort is devoted to analytical and numerical calculations of wakefields, and wakefield effects. Experimental numbers are needed. In this thesis, we present measurements of the transient electric fields induced by a short high-charge electron bunch passing through a 6-way vacuum cross. These measurements are performed in the time domain using electro-optic sampling with a time resolution of approximately 5 picoseconds. With different orientations of the electro-optic crystal, we have measured different vector components of the electric field. The Fourier transform of the time-domain data yields the product of the beam impedance with the excitation spectrum of the bunch. Since the bunch length is known from streak camera measurements, the k loss factor is directly obtained. There is reasonably good agreement between the experimental k loss factor with calculations from the code MAFIA. To our knowledge, this is the first direct measurement of the k loss factor for bunch lengths shorter than one millimeter ( nns). We also present results of magnetic bunch compression (using a dipole chicane) of a high-charge photoinjector beam for two different UV laser pulse lengths on the pholocalhode. Al best compression, a 13.87 nC bunch was compressed to 0.66 mm (2.19 ps) rms, or a peak current of 3 kA. Other results from the photoinjeclor are given, and the laser system for pholocalhode excitation and electro-optic sampling is described.

  18. Modulation of cortical-subcortical networks in Parkinson’s disease by applied field effects

    OpenAIRE

    Hess, Christopher W.

    2013-01-01

    Studies suggest that endogenous field effects may play a role in neuronal oscillations and communication. Non-invasive transcranial electrical stimulation with low-intensity currents can also have direct effects on the underlying cortex as well as distant network effects. While Parkinson’s disease (PD) is amenable to invasive neuromodulation in the basal ganglia by deep brain stimulation (DBS), techniques of non-invasive neuromodulation like transcranial direct current stimulation (tDCS) and ...

  19. High-conductance states in a mean-field cortical network model

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Ahmadi, Mandana; Hertz, John

    2004-01-01

    cortical network model with random connectivity and conductance-based synapses. We employ mean-field theory with correctly colored noise to describe temporal correlations in the neuronal activity. Our results illuminate the connection between two independent experimental findings: high-conductance states......Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1, indicating a tendency toward spikes being clustered. We show that this behavior emerges naturally in a balanced...... of cortical neurons in their natural environment, and variable non-Poissonian spike statistics with Fano factors greater than 1. (C) 2004 Elsevier B.V. All rights reserved....

  20. The concentration of Cs, Sr and other elements in water samples collected in a paddy field

    International Nuclear Information System (INIS)

    Ban-nai, Tadaaki; Hisamatsu, Shun'ichi; Yanai-Kudo, Masumi; Hasegawa, Hidenao; Torikai, Yuji

    2000-01-01

    To research elemental concentrations in soil water in a paddy field, samples of the soil water were collected with porous Teflon resin tubes which were buried in the field. The soil water collections were made at various depth, 2.5, 12.5, 25 and 35 cm from the surface in the paddy field, located in Rokkasho, Aomori, once every two weeks during the rice cultivation period, from May to October in 1998. The paddy field was irrigated from May 7th to July 20th, dried from July 20th to August 5th, then again irrigated until September 16th. Drastic changes of the alkaline earth metal elements, Fe and Mn in soil water samples were seen at the beginning and end of the midsummer drainage. The concentrations of Cs, Fe, Mn and NH 4 in soil water samples showed a similar variation pattern to that of alkaline earth metal elements in the waterlogged period. The change of redox potential was considered a possible cause for the concentration variation for these substances. (author)

  1. Neural network scatter correction technique for digital radiography

    International Nuclear Information System (INIS)

    Boone, J.M.

    1990-01-01

    This paper presents a scatter correction technique based on artificial neural networks. The technique utilizes the acquisition of a conventional digital radiographic image, coupled with the acquisition of a multiple pencil beam (micro-aperture) digital image. Image subtraction results in a sparsely sampled estimate of the scatter component in the image. The neural network is trained to develop a causal relationship between image data on the low-pass filtered open field image and the sparsely sampled scatter image, and then the trained network is used to correct the entire image (pixel by pixel) in a manner which is operationally similar to but potentially more powerful than convolution. The technique is described and is illustrated using clinical primary component images combined with scatter component images that are realistically simulated using the results from previously reported Monte Carlo investigations. The results indicate that an accurate scatter correction can be realized using this technique

  2. Secure transfer of surveillance data over Internet using Virtual Private Network technology. Field trial between STUK and IAEA

    International Nuclear Information System (INIS)

    Smartt, H.; Martinez, R.; Caskey, S.; Honkamaa, T.; Ilander, T.; Poellaenen, R.; Jeremica, N.; Ford, G.

    2000-01-01

    One of the primary concerns of employing remote monitoring technologies for IAEA safeguards applications is the high cost of data transmission. Transmitting data over the Internet has been shown often to be less expensive than other data transmission methods. However, data security of the Internet is often considered to be at a low level. Virtual Private Networks has emerged as a solution to this problem. A field demonstration was implemented to evaluate the use of Virtual Private Networks (via the Internet) as a means for data transmission. Evaluation points included security, reliability and cost. The existing Finnish Remote Environmental Monitoring System, located at the STUK facility in Helsinki, Finland, served as the field demonstration system. Sandia National Laboratories (SNL) established a Virtual Private Network between STUK (Radiation and Nuclear Safety Authority) Headquarters in Helsinki, Finland, and IAEA Headquarters in Vienna, Austria. Data from the existing STUK Remote Monitoring System was viewed at the IAEA via this network. The Virtual Private Network link was established in a proper manner, which guarantees the data security. Encryption was verified using a network sniffer. No problems were? encountered during the test. In the test system, fixed costs were higher than in the previous system, which utilized telephone lines. On the other hand transmission and operating costs are very low. Therefore, with low data amounts, the test system is not cost-effective, but if the data amount is tens of Megabytes per day the use of Virtual Private Networks and Internet will be economically justifiable. A cost-benefit analysis should be performed for each site due to significant variables. (orig.)

  3. An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest.

    Directory of Open Access Journals (Sweden)

    Renske Hijbeek

    Full Text Available In vegetation science and forest management, tree density is often used as a variable. To determine the value of this variable, reliable field methods are necessary. When vegetation is sparse or not easily accessible, the use of sample plots is not feasible in the field. Therefore, plotless methods, like the Point Centred Quarter Method, are often used as an alternative. In this study we investigate the accuracy of different plotless sampling methods. To this end, tree densities of a mangrove forest were determined and compared with estimates provided by several plotless methods. None of these methods proved accurate across all field sites with mean underestimations up to 97% and mean overestimations up to 53% in the field. Applying the methods to different vegetation patterns shows that when random spatial distributions were used the true density was included within the 95% confidence limits of all the plotless methods tested. It was also found that, besides aggregation and regularity, density trends often found in mangroves contribute to the unreliability. This outcome raises questions about the use of plotless sampling in forest monitoring and management, as well as for estimates of density-based carbon sequestration. We give recommendations to minimize errors in vegetation surveys and recommendations for further in-depth research.

  4. Real-time object tracking system based on field-programmable gate array and convolution neural network

    Directory of Open Access Journals (Sweden)

    Congyi Lyu

    2016-12-01

    Full Text Available Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit- or graphics processing unit-based computers are not good choices due to the high weight and power consumption. To address the problem, this article proposed a real-time object tracking system based on field-programmable gate array, convolution neural network, and visual servo technology. The time-consuming image processing algorithms, such as distortion correction, color space convertor, and Sobel edge, Harris corner features detector, and convolution neural network were redesigned using the programmable gates in field-programmable gate array. Based on the field-programmable gate array-based image processing, an image-based visual servo controller was designed to drive a two degree of freedom manipulator to track the target in real time. Finally, experiments on the proposed system were performed to illustrate the effectiveness of the real-time object tracking system.

  5. From Field to the Web: Management and Publication of Geoscience Samples in CSIRO Mineral Resources

    Science.gov (United States)

    Devaraju, A.; Klump, J. F.; Tey, V.; Fraser, R.; Reid, N.; Brown, A.; Golodoniuc, P.

    2016-12-01

    Inaccessible samples are an obstacle to the reproducibility of research and may cause waste of time and resources through duplication of sample collection and management. Within the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mineral Resources there are various research communities who collect or generate physical samples as part of their field studies and analytical processes. Materials can be varied and could be rock, soil, plant materials, water, and even synthetic materials. Given the wide range of applications in CSIRO, each researcher or project may follow their own method of collecting, curating and documenting samples. In many cases samples and their documentation are often only available to the sample collector. For example, the Australian Resources Research Centre stores rock samples and research collections dating as far back as the 1970s. Collecting these samples again would be prohibitively expensive and in some cases impossible because the site has been mined out. These samples would not be easily discoverable by others without an online sample catalog. We identify some of the organizational and technical challenges to provide unambiguous and systematic access to geoscience samples, and present their solutions (e.g., workflow, persistent identifier and tools). We present the workflow starting from field sampling to sample publication on the Web, and describe how the International Geo Sample Number (IGSN) can be applied to identify samples along the process. In our test case geoscientific samples are collected as part of the Capricorn Distal Footprints project, a collaboration project between the CSIRO, the Geological Survey of Western Australia, academic institutions and industry partners. We conclude by summarizing the values of our solutions in terms of sample management and publication.

  6. A Comparative Field Monitoring of Column Shortenings in Tall Buildings Using Wireless and Wired Sensor Network Systems

    Directory of Open Access Journals (Sweden)

    Sungho Lee

    2016-01-01

    Full Text Available A comparative field measurement for column shortening of tall buildings is presented in this study, with a focus on the reliability and stability of a wireless sensor network. A wireless sensor network was used for monitoring the column shortenings of a 58-story building under construction. The wireless sensor network, which was composed of sensor and master nodes, employed the ultra-high-frequency band and CDMA communication methods. To evaluate the reliability and stability of the wireless sensor network system, the column shortenings were also measured using a conventional wired monitoring system. Two vibration wire gauges were installed in each of the selected 7 columns and 3 walls. Measurements for selected columns and walls were collected for 270 days after casting of the concrete. The results measured by the wireless sensor network were compared with the results of the conventional method. The strains and column shortenings measured using both methods showed good agreement for all members. It was verified that the column shortenings of tall buildings could be monitored using the wireless sensor network system with its reliability and stability.

  7. Adaptive Sampling in Autonomous Marine Sensor Networks

    National Research Council Canada - National Science Library

    Eickstedt, Donald P

    2006-01-01

    ... oceanographic network scenario. This architecture has three major components, an intelligent, logical sensor that provides high-level environmental state information to a behavior-based autonomous vehicle control system, a new...

  8. Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

    Directory of Open Access Journals (Sweden)

    Lieven P C Verbeke

    Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

  9. [Social networks in drinking behaviors among Japanese: support network, drinking network, and intervening network].

    Science.gov (United States)

    Yoshihara, Chika; Shimizu, Shinji

    2005-10-01

    The national representative sample was analyzed to examine the relationship between respondents' drinking practice and the social network which was constructed of three different types of network: support network, drinking network, and intervening network. Non-parametric statistical analysis was conducted with chi square method and ANOVA analysis, due to the risk of small samples in some basic tabulation cells. The main results are as follows: (1) In the support network of workplace associates, moderate drinkers enjoyed much more sociable support care than both nondrinkers and hard drinkers, which might suggest a similar effect as the French paradox. Meanwhile in the familial and kinship network, the more intervening care support was provided, the harder respondents' drinking practice. (2) The drinking network among Japanese people for both sexes is likely to be convergent upon certain types of network categories and not decentralized in various categories. This might reflect of the drinking culture of Japan, which permits people to drink everyday as a practice, especially male drinkers. Subsequently, solitary drinking is not optional for female drinkers. (3) Intervening network analysis showed that the harder the respondents' drinking practices, the more frequently their drinking behaviors were checked in almost all the categories of network. A rather complicated gender double-standard was found in the network of hard drinkers with their friends, particularly for female drinkers. Medical professionals played a similar intervening role for men as family and kinship networks but to a less degree than friends for females. The social network is considerably associated with respondents' drinking, providing both sociability for moderate drinkers and intervention for hard drinkers, depending on network categories. To minimize the risk of hard drinking and advance self-healthy drinking there should be more research development on drinking practice and the social network.

  10. An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks

    International Nuclear Information System (INIS)

    Wu, Ji; Zhang, Chenbin; Chen, Zonghai

    2016-01-01

    Highlights: • An online RUL estimation method for lithium-ion battery is proposed. • RUL is described by the difference among battery terminal voltage curves. • A feed forward neural network is employed for RUL estimation. • Importance sampling is utilized to select feed forward neural network inputs. - Abstract: An accurate battery remaining useful life (RUL) estimation can facilitate the design of a reliable battery system as well as the safety and reliability of actual operation. A reasonable definition and an effective prediction algorithm are indispensable for the achievement of an accurate RUL estimation result. In this paper, the analysis of battery terminal voltage curves under different cycle numbers during charge process is utilized for RUL definition. Moreover, the relationship between RUL and charge curve is simulated by feed forward neural network (FFNN) for its simplicity and effectiveness. Considering the nonlinearity of lithium-ion charge curve, importance sampling (IS) is employed for FFNN input selection. Based on these results, an online approach using FFNN and IS is presented to estimate lithium-ion battery RUL in this paper. Experiments and numerical comparisons are conducted to validate the proposed method. The results show that the FFNN with IS is an accurate estimation method for actual operation.

  11. Modification and Application of a Leaf Blower-vac for Field Sampling of Arthropods.

    Science.gov (United States)

    Zou, Yi; van Telgen, Mario D; Chen, Junhui; Xiao, Haijun; de Kraker, Joop; Bianchi, Felix J J A; van der Werf, Wopke

    2016-08-10

    Rice fields host a large diversity of arthropods, but investigating their population dynamics and interactions is challenging. Here we describe the modification and application of a leaf blower-vac for suction sampling of arthropod populations in rice. When used in combination with an enclosure, application of this sampling device provides absolute estimates of the populations of arthropods as numbers per standardized sampling area. The sampling efficiency depends critically on the sampling duration. In a mature rice crop, a two-minute sampling in an enclosure of 0.13 m(2) yields more than 90% of the arthropod population. The device also allows sampling of arthropods dwelling on the water surface or the soil in rice paddies, but it is not suitable for sampling fast flying insects, such as predatory Odonata or larger hymenopterous parasitoids. The modified blower-vac is simple to construct, and cheaper and easier to handle than traditional suction sampling devices, such as D-vac. The low cost makes the modified blower-vac also accessible to researchers in developing countries.

  12. Development of near-field laser ablation inductively coupled plasma mass spectrometry for sub-micrometric analysis of solid samples

    International Nuclear Information System (INIS)

    Jabbour, Chirelle

    2016-01-01

    A near field laser ablation method was developed for chemical analysis of solid samples at sub-micrometric scale. This analytical technique combines a nanosecond laser Nd:YAG, an atomic Force Microscope (AFM), and an inductively coupled plasma mass spectrometer (ICPMS). In order to improve the spatial resolution of the laser ablation process, the near-field enhancement effect was applied by illuminating, by the laser beam, the apex of the AFM conductive sharp tip maintained at a few nanometers (5 to 30 nm) above the sample surface. The interaction between the illuminated tip and the sample surface enhances locally the incident laser energy and leads to the ablation process. By applying this technique to conducting gold and tantalum samples, and semiconducting silicon sample, a lateral resolution of 100 nm and depths of a few nanometers were demonstrated. Two home-made numerical codes have enabled the study of two phenomena occurring around the tip: the enhancement of the laser electrical field by tip effect, and the induced laser heating at the sample surface. The influence of the main operating parameters on these two phenomena, amplification and heating, was studied. an experimental multi-parametric study was carried out in order to understand the effect of different experimental parameters (laser fluence, laser wavelength, number of laser pulses, tip-to-sample distance, sample and tip nature) on the near-field laser ablation efficiency, crater dimensions and amount of ablated material. (author) [fr

  13. Toxicity evaluation of natural samples from the vicinity of rice fields using two trophic levels.

    Science.gov (United States)

    Marques, Catarina R; Pereira, Ruth; Gonçalves, Fernando

    2011-09-01

    An ecotoxicological screening of environmental samples collected in the vicinity of rice fields followed a combination of physical and chemical measurements and chronic bioassays with two freshwater trophic levels (microalgae: Pseudokirchneriella subcapitata and Chlorella vulgaris; daphnids: Daphnia longispina and Daphnia magna). As so, water and sediment/soil elutriate samples were obtained from three sites: (1) in a canal reach crossing a protected wetland upstream, (2) in a canal reach surrounded by rice fields and (3) in a rice paddy. The sampling was performed before and during the rice culture. During the rice cropping, the whole system quality decreased comparatively to the situation before that period (e.g. nutrient overload, the presence of pesticides in elutriates from sites L2 and L3). This was reinforced by a significant inhibition of both microalgae growth, especially under elutriates. Contrary, the life-history traits of daphnids were significantly stimulated with increasing concentrations of water and elutriates, for both sampling periods.

  14. Recent developments on field gas extraction and sample preparation methods for radiokrypton dating of groundwater

    Science.gov (United States)

    Yokochi, Reika

    2016-09-01

    Current and foreseen population growths will lead to an increased demand in freshwater, large quantities of which is stored as groundwater. The ventilation age is crucial to the assessment of groundwater resources, complementing the hydrological model approach based on hydrogeological parameters. Ultra-trace radioactive isotopes of Kr (81 Kr and 85 Kr) possess the ideal physical and chemical properties for groundwater dating. The recent advent of atom trap trace analyses (ATTA) has enabled determination of ultra-trace noble gas radioisotope abundances using 5-10 μ L of pure Kr. Anticipated developments will enable ATTA to analyze radiokrypton isotope abundances at high sample throughput, which necessitates simple and efficient sample preparation techniques that are adaptable to various sample chemistries. Recent developments of field gas extraction devices and simple and rapid Kr separation method at the University of Chicago are presented herein. Two field gas extraction devices optimized for different sampling conditions were recently designed and constructed, aiming at operational simplicity and portability. A newly developed Kr purification system enriches Kr by flowing a sample gas through a moderately cooled (138 K) activated charcoal column, followed by a gentle fractionating desorption. This simple process uses a single adsorbent and separates 99% of the bulk atmospheric gases from Kr without significant loss. The subsequent two stages of gas chromatographic separation and a hot Ti sponge getter further purify the Kr-enriched gas. Abundant CH4 necessitates multiple passages through one of the gas chromatographic separation columns. The presented Kr separation system has a demonstrated capability of extracting Kr with > 90% yield and 99% purity within 75 min from 1.2 to 26.8 L STP of atmospheric air with various concentrations of CH4. The apparatuses have successfully been deployed for sampling in the field and purification of groundwater samples.

  15. Application of Chitosan-Zinc Oxide Nanoparticles for Lead Extraction From Water Samples by Combining Ant Colony Optimization with Artificial Neural Network

    Science.gov (United States)

    Khajeh, M.; Pourkarami, A.; Arefnejad, E.; Bohlooli, M.; Khatibi, A.; Ghaffari-Moghaddam, M.; Zareian-Jahromi, S.

    2017-09-01

    Chitosan-zinc oxide nanoparticles (CZPs) were developed for solid-phase extraction. Combined artificial neural network-ant colony optimization (ANN-ACO) was used for the simultaneous preconcentration and determination of lead (Pb2+) ions in water samples prior to graphite furnace atomic absorption spectrometry (GF AAS). The solution pH, mass of adsorbent CZPs, amount of 1-(2-pyridylazo)-2-naphthol (PAN), which was used as a complexing agent, eluent volume, eluent concentration, and flow rates of sample and eluent were used as input parameters of the ANN model, and the percentage of extracted Pb2+ ions was used as the output variable of the model. A multilayer perception network with a back-propagation learning algorithm was used to fit the experimental data. The optimum conditions were obtained based on the ACO. Under the optimized conditions, the limit of detection for Pb2+ ions was found to be 0.078 μg/L. This procedure was also successfully used to determine the amounts of Pb2+ ions in various natural water samples.

  16. Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

    Directory of Open Access Journals (Sweden)

    Wilten eNicola

    2016-02-01

    Full Text Available A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF. The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks

  17. Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

    Science.gov (United States)

    Nicola, Wilten; Tripp, Bryan; Scott, Matthew

    2016-01-01

    A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.

  18. A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks.

    Science.gov (United States)

    González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

    2017-01-09

    Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

  19. Temporal network epidemiology

    CERN Document Server

    Holme, Petter

    2017-01-01

    This book covers recent developments in epidemic process models and related data on temporally varying networks. It is widely recognized that contact networks are indispensable for describing, understanding, and intervening to stop the spread of infectious diseases in human and animal populations; “network epidemiology” is an umbrella term to describe this research field. More recently, contact networks have been recognized as being highly dynamic. This observation, also supported by an increasing amount of new data, has led to research on temporal networks, a rapidly growing area. Changes in network structure are often informed by epidemic (or other) dynamics, in which case they are referred to as adaptive networks. This volume gathers contributions by prominent authors working in temporal and adaptive network epidemiology, a field essential to understanding infectious diseases in real society.

  20. Performance of Overlaid MIMO Cellular Networks with TAS/MRC under Hybrid-Access Small Cells and Poisson Field Interference

    KAUST Repository

    AbdelNabi, Amr A.

    2018-02-12

    This paper presents new approaches to characterize the achieved performance of hybrid control-access small cells in the context of two-tier multi-input multi-output (MIMO) cellular networks with random interference distributions. The hybrid scheme at small cells (such as femtocells) allows for sharing radio resources between the two network tiers according to the densities of small cells and their associated users, as well as the observed interference power levels in the two network tiers. The analysis considers MIMO transceivers at all nodes, for which antenna arrays can be utilized to implement transmit antenna selection (TAS) and receive maximal ratio combining (MRC) under MIMO point-to-point channels. Moreover, it tar-gets network-level models of interference sources inside each tier and between the two tiers, which are assumed to follow Poisson field processes. To fully capture the occasions for Poisson field distribution on MIMO spatial domain. Two practical scenarios of interference sources are addressed including highly-correlated or uncorrelated transmit antenna arrays of the serving macrocell base station. The analysis presents new analytical approaches that can characterize the downlink outage probability performance in any tier. Furthermore, the outage performance in high signal-to-noise (SNR) regime is also obtained, which can be useful to deduce diversity and/or coding gains.

  1. Performance of Overlaid MIMO Cellular Networks with TAS/MRC under Hybrid-Access Small Cells and Poisson Field Interference

    KAUST Repository

    AbdelNabi, Amr A.; Al-Qahtani, Fawaz S.; Radaydeh, Redha Mahmoud Mesleh; Shaqfeh, Mohammad; Manna, Raed F.

    2018-01-01

    This paper presents new approaches to characterize the achieved performance of hybrid control-access small cells in the context of two-tier multi-input multi-output (MIMO) cellular networks with random interference distributions. The hybrid scheme at small cells (such as femtocells) allows for sharing radio resources between the two network tiers according to the densities of small cells and their associated users, as well as the observed interference power levels in the two network tiers. The analysis considers MIMO transceivers at all nodes, for which antenna arrays can be utilized to implement transmit antenna selection (TAS) and receive maximal ratio combining (MRC) under MIMO point-to-point channels. Moreover, it tar-gets network-level models of interference sources inside each tier and between the two tiers, which are assumed to follow Poisson field processes. To fully capture the occasions for Poisson field distribution on MIMO spatial domain. Two practical scenarios of interference sources are addressed including highly-correlated or uncorrelated transmit antenna arrays of the serving macrocell base station. The analysis presents new analytical approaches that can characterize the downlink outage probability performance in any tier. Furthermore, the outage performance in high signal-to-noise (SNR) regime is also obtained, which can be useful to deduce diversity and/or coding gains.

  2. Social network data analytics

    CERN Document Server

    Aggarwal, Charu C

    2011-01-01

    Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Pr

  3. Near-field acoustic holography using sparse regularization and compressive sampling principles.

    Science.gov (United States)

    Chardon, Gilles; Daudet, Laurent; Peillot, Antoine; Ollivier, François; Bertin, Nancy; Gribonval, Rémi

    2012-09-01

    Regularization of the inverse problem is a complex issue when using near-field acoustic holography (NAH) techniques to identify the vibrating sources. This paper shows that, for convex homogeneous plates with arbitrary boundary conditions, alternative regularization schemes can be developed based on the sparsity of the normal velocity of the plate in a well-designed basis, i.e., the possibility to approximate it as a weighted sum of few elementary basis functions. In particular, these techniques can handle discontinuities of the velocity field at the boundaries, which can be problematic with standard techniques. This comes at the cost of a higher computational complexity to solve the associated optimization problem, though it remains easily tractable with out-of-the-box software. Furthermore, this sparsity framework allows us to take advantage of the concept of compressive sampling; under some conditions on the sampling process (here, the design of a random array, which can be numerically and experimentally validated), it is possible to reconstruct the sparse signals with significantly less measurements (i.e., microphones) than classically required. After introducing the different concepts, this paper presents numerical and experimental results of NAH with two plate geometries, and compares the advantages and limitations of these sparsity-based techniques over standard Tikhonov regularization.

  4. Deterministic and stochastic algorithms for resolving the flow fields in ducts and networks using energy minimization

    Science.gov (United States)

    Sochi, Taha

    2016-09-01

    Several deterministic and stochastic multi-variable global optimization algorithms (Conjugate Gradient, Nelder-Mead, Quasi-Newton and global) are investigated in conjunction with energy minimization principle to resolve the pressure and volumetric flow rate fields in single ducts and networks of interconnected ducts. The algorithms are tested with seven types of fluid: Newtonian, power law, Bingham, Herschel-Bulkley, Ellis, Ree-Eyring and Casson. The results obtained from all those algorithms for all these types of fluid agree very well with the analytically derived solutions as obtained from the traditional methods which are based on the conservation principles and fluid constitutive relations. The results confirm and generalize the findings of our previous investigations that the energy minimization principle is at the heart of the flow dynamics systems. The investigation also enriches the methods of computational fluid dynamics for solving the flow fields in tubes and networks for various types of Newtonian and non-Newtonian fluids.

  5. Report on the second ALMERA network coordination meeting and the ALMERA soil sampling intercomparison exercise IAEA/SIE/01

    International Nuclear Information System (INIS)

    2006-05-01

    The overall aim of the meeting was to evaluate the current status of the ALMERA network laboratories and to help to improve their technical competence through harmonization of sampling, monitoring and measurement protocols and staff training. The meeting was also addressed to defining the structure of the ALMERA network and future proficiency tests and intercomparison trials to be organized by the IAEA to help the laboratories to maintain and improve the quality of their analytical measurements. 45 participants from 29 different institutions attended the meeting

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

    Science.gov (United States)

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

    2014-07-01

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

  7. Graph sampling

    OpenAIRE

    Zhang, L.-C.; Patone, M.

    2017-01-01

    We synthesise the existing theory of graph sampling. We propose a formal definition of sampling in finite graphs, and provide a classification of potential graph parameters. We develop a general approach of Horvitz–Thompson estimation to T-stage snowball sampling, and present various reformulations of some common network sampling methods in the literature in terms of the outlined graph sampling theory.

  8. Reverse engineering biological networks :applications in immune responses to bio-toxins.

    Energy Technology Data Exchange (ETDEWEB)

    Martino, Anthony A.; Sinclair, Michael B.; Davidson, George S.; Haaland, David Michael; Timlin, Jerilyn Ann; Thomas, Edward Victor; Slepoy, Alexander; Zhang, Zhaoduo; May, Elebeoba Eni; Martin, Shawn Bryan; Faulon, Jean-Loup Michel

    2005-12-01

    Our aim is to determine the network of events, or the regulatory network, that defines an immune response to a bio-toxin. As a model system, we are studying T cell regulatory network triggered through tyrosine kinase receptor activation using a combination of pathway stimulation and time-series microarray experiments. Our approach is composed of five steps (1) microarray experiments and data error analysis, (2) data clustering, (3) data smoothing and discretization, (4) network reverse engineering, and (5) network dynamics analysis and fingerprint identification. The technological outcome of this study is a suite of experimental protocols and computational tools that reverse engineer regulatory networks provided gene expression data. The practical biological outcome of this work is an immune response fingerprint in terms of gene expression levels. Inferring regulatory networks from microarray data is a new field of investigation that is no more than five years old. To the best of our knowledge, this work is the first attempt that integrates experiments, error analyses, data clustering, inference, and network analysis to solve a practical problem. Our systematic approach of counting, enumeration, and sampling networks matching experimental data is new to the field of network reverse engineering. The resulting mathematical analyses and computational tools lead to new results on their own and should be useful to others who analyze and infer networks.

  9. Sample problem calculations related to two-phase flow transients in a PWR relief-piping network

    International Nuclear Information System (INIS)

    Shin, Y.W.; Wiedermann, A.H.

    1981-03-01

    Two sample problems related with the fast transients of water/steam flow in the relief line of a PWR pressurizer were calculated with a network-flow analysis computer code STAC (System Transient-Flow Analysis Code). The sample problems were supplied by EPRI and are designed to test computer codes or computational methods to determine whether they have the basic capability to handle the important flow features present in a typical relief line of a PWR pressurizer. It was found necessary to implement into the STAC code a number of additional boundary conditions in order to calculate the sample problems. This includes the dynamics of the fluid interface that is treated as a moving boundary. This report describes the methodologies adopted for handling the newly implemented boundary conditions and the computational results of the two sample problems. In order to demonstrate the accuracies achieved in the STAC code results, analytical solutions are also obtained and used as a basis for comparison

  10. Institutional and scientific co-operation, networking and capacity building in the field of food safety and quality

    NARCIS (Netherlands)

    Boekel, van M.A.J.S.; Meerdink, G.; Banati, D.; Marvin, H.J.P.; Kuiper, H.A.; Houtman, C.B.

    2002-01-01

    This paper explains the situation in Hungary and The Netherlands regarding scientific co-operation, networking and capacity building in the field of food quality and safety. Specific details are given about institutional co-operation including exchanges between staff and students, collaborative

  11. Modification and application of a leaf blower-vac for field sampling of arthropods

    NARCIS (Netherlands)

    Zou, Yi; Telgen, van Mario D.; Chen, Junhui; Xiao, Haijun; Kraker, de Joop; Bianchi, Felix J.J.A.; Werf, van der Wopke

    2016-01-01

    Rice fields host a large diversity of arthropods, but investigating their population dynamics and interactions is challenging. Here we describe the modification and application of a leaf blower-vac for suction sampling of arthropod populations in rice. When used in combination with an enclosure,

  12. Response of Cultured Neuronal Network Activity After High-Intensity Power Frequency Magnetic Field Exposure

    Directory of Open Access Journals (Sweden)

    Atsushi Saito

    2018-03-01

    Full Text Available High-intensity and low frequency (1–100 kHz time-varying electromagnetic fields stimulate the human body through excitation of the nervous system. In power frequency range (50/60 Hz, a frequency-dependent threshold of the external electric field-induced neuronal modulation in cultured neuronal networks was used as one of the biological indicator in international guidelines; however, the threshold of the magnetic field-induced neuronal modulation has not been elucidated. In this study, we exposed rat brain-derived neuronal networks to a high-intensity power frequency magnetic field (hPF-MF, and evaluated the modulation of synchronized bursting activity using a multi-electrode array (MEA-based extracellular recording technique. As a result of short-term hPF-MF exposure (50–400 mT root-mean-square (rms, 50 Hz, sinusoidal wave, 6 s, the synchronized bursting activity was increased in the 400 mT-exposed group. On the other hand, no change was observed in the 50–200 mT-exposed groups. In order to clarify the mechanisms of the 400 mT hPF-MF exposure-induced neuronal response, we evaluated it after blocking inhibitory synapses using bicuculline methiodide (BMI; subsequently, increase in bursting activity was observed with BMI application, and the response of 400 mT hPF-MF exposure disappeared. Therefore, it was suggested that the response of hPF-MF exposure was involved in the inhibitory input. Next, we screened the inhibitory pacemaker-like neuronal activity which showed autonomous 4–10 Hz firing with CNQX and D-AP5 application, and it was confirmed that the activity was reduced after 400 mT hPF-MF exposure. Comparison of these experimental results with estimated values of the induced electric field (E-field in the culture medium revealed that the change in synchronized bursting activity occurred over 0.3 V/m, which was equivalent to the findings of a previous study that used the external electric fields. In addition, the results suggested that

  13. Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

    Science.gov (United States)

    Piastra, Marco

    2013-05-01

    Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. The effect of an exogenous magnetic field on neural coding in deep spiking neural networks.

    Science.gov (United States)

    Guo, Lei; Zhang, Wei; Zhang, Jialei

    2018-01-01

    A ten-layer feed forward network is constructed in the presence of an exogenous alternating magnetic field. Specifically, our results indicate that for rate coding, the firing rate is significantly increased in the presence of an exogenous alternating magnetic field and particularly with increasing enhancement of the alternating magnetic field amplitude. For temporal coding, the interspike intervals of the spiking sequence are decreased and the distribution of the interspike intervals of the spiking sequence tends to be uniform in the presence of alternating magnetic field.

  15. The Governmentality of Meta-governance : Identifying Theoretical and Empirical Challenges of Network Governance in the Political Field of Security and Beyond

    OpenAIRE

    Larsson, Oscar

    2015-01-01

    Meta-governance recently emerged in the field of governance as a new approach which claims that its use enables modern states to overcome problems associated with network governance. This thesis shares the view that networks are an important feature of contemporary politics which must be taken seriously, but it also maintains that networks pose substantial analytical and political challenges. It proceeds to investigate the potential possibilities and problems associated with meta-governance o...

  16. A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Eva González-Parada

    2017-01-01

    Full Text Available Autonomous mobile nodes in mobile wireless sensor networks (MWSN allow self-deployment and self-healing. In both cases, the goals are: (i to achieve adequate coverage; and (ii to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

  17. Field data analysis of active chlorine-containing stormwater samples.

    Science.gov (United States)

    Zhang, Qianyi; Gaafar, Mohamed; Yang, Rong-Cai; Ding, Chen; Davies, Evan G R; Bolton, James R; Liu, Yang

    2018-01-15

    Many municipalities in Canada and all over the world use chloramination for drinking water secondary disinfection to avoid DBPs formation from conventional chlorination. However, the long-lasting monochloramine (NH 2 Cl) disinfectant can pose a significant risk to aquatic life through its introduction into municipal storm sewer systems and thus fresh water sources by residential, commercial, and industrial water uses. To establish general total active chlorine (TAC) concentrations in discharges from storm sewers, the TAC concentration was measured in stormwater samples in Edmonton, Alberta, Canada, during the summers of 2015 and 2016 under both dry and wet weather conditions. The field-sampling results showed TAC concentration variations from 0.02 to 0.77 mg/L in summer 2015, which exceeds the discharge effluent limit of 0.02 mg/L. As compared to 2015, the TAC concentrations were significantly lower during the summer 2016 (0-0.24 mg/L), for which it is believed that the higher precipitation during summer 2016 reduced outdoor tap water uses. Since many other cities also use chloramines as disinfectants for drinking water disinfection, the TAC analysis from Edmonton may prove useful for other regions as well. Other physicochemical and biological characteristics of stormwater and storm sewer biofilm samples were also analyzed, and no significant difference was found during these two years. Higher density of AOB and NOB detected in the storm sewer biofilm of residential areas - as compared with other areas - generally correlated to high concentrations of ammonium and nitrite in this region in both of the two years, and they may have contributed to the TAC decay in the storm sewers. The NH 2 Cl decay laboratory experiments illustrate that dissolved organic carbon (DOC) concentration is the dominant factor in determining the NH 2 Cl decay rate in stormwater samples. The high DOC concentrations detected from a downstream industrial sampling location may contribute to a

  18. Fluctuations of Attentional Networks and Default Mode Network during the Resting State Reflect Variations in Cognitive States: Evidence from a Novel Resting-state Experience Sampling Method.

    Science.gov (United States)

    Van Calster, Laurens; D'Argembeau, Arnaud; Salmon, Eric; Peters, Frédéric; Majerus, Steve

    2017-01-01

    Neuroimaging studies have revealed the recruitment of a range of neural networks during the resting state, which might reflect a variety of cognitive experiences and processes occurring in an individual's mind. In this study, we focused on the default mode network (DMN) and attentional networks and investigated their association with distinct mental states when participants are not performing an explicit task. To investigate the range of possible cognitive experiences more directly, this study proposes a novel method of resting-state fMRI experience sampling, informed by a phenomenological investigation of the fluctuation of mental states during the resting state. We hypothesized that DMN activity would increase as a function of internal mentation and that the activity of dorsal and ventral networks would indicate states of top-down versus bottom-up attention at rest. Results showed that dorsal attention network activity fluctuated as a function of subjective reports of attentional control, providing evidence that activity of this network reflects the perceived recruitment of controlled attentional processes during spontaneous cognition. Activity of the DMN increased when participants reported to be in a subjective state of internal mentation, but not when they reported to be in a state of perception. This study provides direct evidence for a link between fluctuations of resting-state neural activity and fluctuations in specific cognitive processes.

  19. A Data Scheduling and Management Infrastructure for the TEAM Network

    Science.gov (United States)

    Andelman, S.; Baru, C.; Chandra, S.; Fegraus, E.; Lin, K.; Unwin, R.

    2009-04-01

    currently partnering with the San Diego Super Computer Center to build the data management infrastructure. Data collected from the three core protocols as well as others are currently made available through the TEAM Network portal, which provides the content management framework, the data scheduling and management framework, an administrative framework to implement and manage TEAM sites, collaborative tools and a number of tools and applications utilizing Google Map and Google Earth products. A critical element of the TEAM Network data management infrastructure is to make the data publicly available in as close to real-time as possible (the TEAM Network Data Use Policy: http://www.teamnetwork.org/en/data/policy). This requires two essential tasks to be accomplished, 1) A data collection schedule has to be planned, proposed and approved for a given TEAM site. This is a challenging process since TEAM sites are geographically distributed across the tropics and hence have different seasons where they schedule field sampling for the different TEAM protocols. Capturing this information and ensuring that TEAM sites follow the outlined legal contract is key to the data collection process and 2) A stream-lined and efficient information management system to ensure data collected from the field meet the minimum data standards (i.e. are of the highest scientific quality) and are securely transferred, archived, processed and be rapidly made publicaly available, as a finished consumable product via the TEAM Network portal. The TEAM Network is achieving these goals by implementing an end-to-end framework consisting of the Sampling Scheduler application and the Data Management Framework. Sampling Scheduler The Sampling Scheduler is a project management, calendar based portal application that will allow scientists at a TEAM site to schedule field sampling for each of the TEAM protocols implemented at that site. The sampling scheduler addresses the specific requirements established in the

  20. The EU network on trace element speciation in full swing

    DEFF Research Database (Denmark)

    Cornelis, R.; Camara, C.; Ebdon, L.

    2000-01-01

    health and hygiene. The network covers a number of important issues including organotin compounds, chromium and nickel species, chemical characterisation of environmental and industrial particulate samples, risk assessment, selenium and a series of other essential and toxic elements in food, as well......The EC-funded thematic network 'Speciation 21' links scientists in analytical chemistry working in method development for the chemical speciation of trace elements, and potential users from industry and representatives of legislative agencies, in the field of environment, food and occupational...

  1. A contemporary decennial global Landsat sample of changing agricultural field sizes

    Science.gov (United States)

    White, Emma; Roy, David

    2014-05-01

    Agriculture has caused significant human induced Land Cover Land Use (LCLU) change, with dramatic cropland expansion in the last century and significant increases in productivity over the past few decades. Satellite data have been used for agricultural applications including cropland distribution mapping, crop condition monitoring, crop production assessment and yield prediction. Satellite based agricultural applications are less reliable when the sensor spatial resolution is small relative to the field size. However, to date, studies of agricultural field size distributions and their change have been limited, even though this information is needed to inform the design of agricultural satellite monitoring systems. Moreover, the size of agricultural fields is a fundamental description of rural landscapes and provides an insight into the drivers of rural LCLU change. In many parts of the world field sizes may have increased. Increasing field sizes cause a subsequent decrease in the number of fields and therefore decreased landscape spatial complexity with impacts on biodiversity, habitat, soil erosion, plant-pollinator interactions, and impacts on the diffusion of herbicides, pesticides, disease pathogens, and pests. The Landsat series of satellites provide the longest record of global land observations, with 30m observations available since 1982. Landsat data are used to examine contemporary field size changes in a period (1980 to 2010) when significant global agricultural changes have occurred. A multi-scale sampling approach is used to locate global hotspots of field size change by examination of a recent global agricultural yield map and literature review. Nine hotspots are selected where significant field size change is apparent and where change has been driven by technological advancements (Argentina and U.S.), abrupt societal changes (Albania and Zimbabwe), government land use and agricultural policy changes (China, Malaysia, Brazil), and/or constrained by

  2. Solid state magnetic field sensors for micro unattended ground networks using spin dependent tunneling

    Science.gov (United States)

    Tondra, Mark; Nordman, Catherine A.; Lange, Erik H.; Reed, Daniel; Jander, Albrect; Akou, Seraphin; Daughton, James

    2001-09-01

    Micro Unattended Ground Sensor Networks will likely employ magnetic sensors, primarily for discrimination of objects as opposed to initial detection. These magnetic sensors, then, must fit within very small cost, size, and power budgets to be compatible with the envisioned sensor suites. Also, a high degree of sensitivity is required to minimize the number of sensor cells required to survey a given area in the field. Solid state magnetoresistive sensors, with their low cost, small size, and ease of integration, are excellent candidates for these applications assuming that their power and sensitivity performance are acceptable. SDT devices have been fabricated into prototype magnetic field sensors suitable for use in micro unattended ground sensor networks. They are housed in tiny SOIC 8-pin packages and mounted on a circuit board with required voltage regulation, signal amplification and conditioning, and sensor control and communications functions. The best sensitivity results to date are 289 pT/rt. Hz at 1 Hz, and and 7 pT/rt. Hz at f > 10 kHz. Expected near term improvements in performance would bring these levels to approximately 10 pT/rt Hz at 1 Hz and approximately 1 pT/rt. Hz at > 1 kHz.

  3. Study on pattern recognition of Raman spectrum based on fuzzy neural network

    Science.gov (United States)

    Zheng, Xiangxiang; Lv, Xiaoyi; Mo, Jiaqing

    2017-10-01

    Hydatid disease is a serious parasitic disease in many regions worldwide, especially in Xinjiang, China. Raman spectrum of the serum of patients with echinococcosis was selected as the research object in this paper. The Raman spectrum of blood samples from healthy people and patients with echinococcosis are measured, of which the spectrum characteristics are analyzed. The fuzzy neural network not only has the ability of fuzzy logic to deal with uncertain information, but also has the ability to store knowledge of neural network, so it is combined with the Raman spectrum on the disease diagnosis problem based on Raman spectrum. Firstly, principal component analysis (PCA) is used to extract the principal components of the Raman spectrum, reducing the network input and accelerating the prediction speed and accuracy of Network based on remaining the original data. Then, the information of the extracted principal component is used as the input of the neural network, the hidden layer of the network is the generation of rules and the inference process, and the output layer of the network is fuzzy classification output. Finally, a part of samples are randomly selected for the use of training network, then the trained network is used for predicting the rest of the samples, and the predicted results are compared with general BP neural network to illustrate the feasibility and advantages of fuzzy neural network. Success in this endeavor would be helpful for the research work of spectroscopic diagnosis of disease and it can be applied in practice in many other spectral analysis technique fields.

  4. A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2011-01-01

    Full Text Available Abstract Background Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. Methods In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Results Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs. In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. Conclusions A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.

  5. Composite Extension Finite Fields for Low Overhead Network Coding

    DEFF Research Database (Denmark)

    Heide, Janus; Roetter, Daniel Enrique Lucani

    2015-01-01

    Although Network Coding (NC) has been proven to increase throughput and reliability in communication networks, its adoption is typically hindered by the additional complexity it introduces at various nodes in the network and the overhead to signal the coding coefficients associated with each code...

  6. Ambient krypton-85 air sampling at Hanford

    International Nuclear Information System (INIS)

    Trevathan, M.S.; Price, K.R.

    1985-01-01

    In the fall of 1982, the Environmental Evaluations Section of Pacific Northwest Laboratory (PNL) initiated a network of continuous 85 Kr air samplers located on and around the Hanford Site. This effort was in response to the resumption of operations at a nuclear fuel reprocessing plant located onsite where 85 Kr was to be released during fuel dissolution. Preoperational data were collected using noble gas samplers designed by the Environmental Protection Agency-Las Vegas (EPA-LV). The samplers functioned erratically resulting in excessive maintenance costs and prompted a search for a new sampling system. State-of-the-art 85 Dr sampling methods were reviewed and found to be too costly, too complex and inappropriate for field application, so a simple bag collection system was designed and field tested. The system is composed of a reinforced, heavy plastic bag, connected to a variable flow pump and housed in a weatherproof enclosure. At the end of the four week sampling period the air in the bag is transferred by a compressor into a pressure tank for easy transport to the laboratory for analysis. After several months of operation, the air sampling system has proven its reliability and sensitivity to ambient levels of 85 Kr

  7. Ambient krypton-85 air sampling at Hanford

    International Nuclear Information System (INIS)

    Trevathan, M.S.; Price, K.R.

    1984-10-01

    In the fall of 1982, the Environmental Evaluations Section of Pacific Northwest Laboratory (PNL) initiated a network of continuous krypton-85 air samplers located on and around the Hanford Site. This effort was in response to the resumption of operations at a nuclear fuel reprocessing plant located onsite where krypton-85 was to be released during fuel dissolution. Preoperational data were collected using noble gas samplers designed by the Environmental Protection Agency-Las Vegas (EPA-LV). The samplers functioned erratically resulting in excessive maintenance costs and prompted a search for a new sampling system. State of the art krypton-85 sampling methods were reviewed and found to be too costly, too complex and inappropriate for field application, so a simple bag collection system was designed and field tested. The system is composed of a reinforced, heavy plastic bag, connected to a variable flow pump and housed in a weatherproof enclosure. At the end of the four week sampling period the air in the bag is transferred by a compressor into a pressure tank for easy transport to the laboratory for analysis. After several months of operation, the air sampling system has proven its reliability and sensitivity to ambient levels of krypton-85. 3 references, 3 figures, 1 table

  8. Evaluation of the Radiochemistry of Near-Field Water Samples at the Nevada Test Site Applied to the Definition of a Hydrologic Source Term

    International Nuclear Information System (INIS)

    Smith, D K

    2002-01-01

    National Laboratory and Los Alamos National Laboratory have annually returned water samples from wells in near-field locations at the NTS for radiochemical analyses. This report makes the distinction between samples taken in the near-field and the far field. The near-field includes the area extending radially ∼300 meters from surface ground zero (the firing point of an underground nuclear test projected upwards on ground surface). Over the years this sampling program has also been refereed to as the ''hot-well monitoring program'' because these water samples contained concentrations of tritium above natural background (tritium concentrations in southern Nevada precipitation are 0.5 to 2.0 Bq/L, Farmer et al., 1998). A majority of the hot wells contain tritium in excess of the 741 Bq/L (20,000 pCi/L) drinking water standard (Smith et al., 1996a; Smith et al., 1997). The sites which comprise our current hot well sampling network are plotted on a map of the NTS in Figure 1

  9. Assessing NIR & MIR Spectral Analysis as a Method for Soil C Estimation Across a Network of Sampling Sites

    Science.gov (United States)

    Spencer, S.; Ogle, S.; Borch, T.; Rock, B.

    2008-12-01

    Monitoring soil C stocks is critical to assess the impact of future climate and land use change on carbon sinks and sources in agricultural lands. A benchmark network for soil carbon monitoring of stock changes is being designed for US agricultural lands with 3000-5000 sites anticipated and re-sampling on a 5- to10-year basis. Approximately 1000 sites would be sampled per year producing around 15,000 soil samples to be processed for total, organic, and inorganic carbon, as well as bulk density and nitrogen. Laboratory processing of soil samples is cost and time intensive, therefore we are testing the efficacy of using near-infrared (NIR) and mid-infrared (MIR) spectral methods for estimating soil carbon. As part of an initial implementation of national soil carbon monitoring, we collected over 1800 soil samples from 45 cropland sites in the mid-continental region of the U.S. Samples were processed using standard laboratory methods to determine the variables above. Carbon and nitrogen were determined by dry combustion and inorganic carbon was estimated with an acid-pressure test. 600 samples are being scanned using a bench- top NIR reflectance spectrometer (30 g of 2 mm oven-dried soil and 30 g of 8 mm air-dried soil) and 500 samples using a MIR Fourier-Transform Infrared Spectrometer (FTIR) with a DRIFT reflectance accessory (0.2 g oven-dried ground soil). Lab-measured carbon will be compared to spectrally-estimated carbon contents using Partial Least Squares (PLS) multivariate statistical approach. PLS attempts to develop a soil C predictive model that can then be used to estimate C in soil samples not lab-processed. The spectral analysis of soil samples either whole or partially processed can potentially save both funding resources and time to process samples. This is particularly relevant for the implementation of a national monitoring network for soil carbon. This poster will discuss our methods, initial results and potential for using NIR and MIR spectral

  10. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  11. Real-Time Earthquake Monitoring with Spatio-Temporal Fields

    Science.gov (United States)

    Whittier, J. C.; Nittel, S.; Subasinghe, I.

    2017-10-01

    With live streaming sensors and sensor networks, increasingly large numbers of individual sensors are deployed in physical space. Sensor data streams are a fundamentally novel mechanism to deliver observations to information systems. They enable us to represent spatio-temporal continuous phenomena such as radiation accidents, toxic plumes, or earthquakes almost as instantaneously as they happen in the real world. Sensor data streams discretely sample an earthquake, while the earthquake is continuous over space and time. Programmers attempting to integrate many streams to analyze earthquake activity and scope need to write code to integrate potentially very large sets of asynchronously sampled, concurrent streams in tedious application code. In previous work, we proposed the field stream data model (Liang et al., 2016) for data stream engines. Abstracting the stream of an individual sensor as a temporal field, the field represents the Earth's movement at the sensor position as continuous. This simplifies analysis across many sensors significantly. In this paper, we undertake a feasibility study of using the field stream model and the open source Data Stream Engine (DSE) Apache Spark(Apache Spark, 2017) to implement a real-time earthquake event detection with a subset of the 250 GPS sensor data streams of the Southern California Integrated GPS Network (SCIGN). The field-based real-time stream queries compute maximum displacement values over the latest query window of each stream, and related spatially neighboring streams to identify earthquake events and their extent. Further, we correlated the detected events with an USGS earthquake event feed. The query results are visualized in real-time.

  12. Development and Progress of Ireland's Biobank Network: Ethical, Legal, and Social Implications (ELSI), Standardized Documentation, Sample and Data Release, and International Perspective

    LENUS (Irish Health Repository)

    Mee, Blanaid

    2013-02-19

    Biobank Ireland Trust (BIT) was established in 2004 to promote and develop an Irish biobank network to benefit patients, researchers, industry, and the economy. The network commenced in 2008 with two hospital biobanks and currently consists of biobanks in the four main cancer hospitals in Ireland. The St. James\\'s Hospital (SJH) Biobank coordinates the network. Procedures, based on ISBER and NCI guidelines, are standardized across the network. Policies and documents—Patient Consent Policy, Patient Information Sheet, Biobank Consent Form, Sample and Data Access Policy (SAP), and Sample Application Form have been agreed upon (after robust discussion) for use in each hospital. An optimum sequence for document preparation and submission for review is outlined. Once consensus is reached among the participating biobanks, the SJH biobank liaises with the Research and Ethics Committees, the Office of the Data Protection Commissioner, The National Cancer Registry (NCR), patient advocate groups, researchers, and other stakeholders. The NCR provides de-identified data from its database for researchers via unique biobank codes. ELSI issues discussed include the introduction of prospective consent across the network and the return of significant research results to patients. Only 4 of 363 patients opted to be re-contacted and re-consented on each occasion that their samples are included in a new project. It was decided, after multidisciplinary discussion, that results will not be returned to patients. The SAP is modeled on those of several international networks. Biobank Ireland is affiliated with international biobanking groups—Marble Arch International Working Group, ISBER, and ESBB. The Irish government continues to deliberate on how to fund and implement biobanking nationally. Meanwhile BIT uses every opportunity to promote awareness of the benefits of biobanking in events and in the media.

  13. The complex interplay of social networks, geography and HIV risk among Malaysian Drug Injectors: Results from respondent-driven sampling.

    Science.gov (United States)

    Zelenev, Alexei; Long, Elisa; Bazazi, Alexander R; Kamarulzaman, Adeeba; Altice, Frederick L

    2016-11-01

    HIV is primarily concentrated among people who inject drugs (PWID) in Malaysia, where currently HIV prevention and treatment coverage is inadequate. To improve the targeting of interventions, we examined HIV clustering and the role that social networks and geographical distance play in influencing HIV transmission among PWID. Data were derived from a respondent-driven survey sample (RDS) collected during 2010 of 460 PWID in greater Kuala Lumpur. Analysis focused on socio-demographic, clinical, behavioural, and network information. Spatial probit models were developed based on a distinction between the influence of peers (individuals nominated through a recruitment network) and neighbours (residing a close distance to the individual). The models were expanded to account for the potential influence of the network formation. Recruitment patterns of HIV-infected PWID clustered both spatially and across the recruitment networks. In addition, HIV-infected PWID were more likely to have peers and neighbours who inject with clean needles were HIV-infected and lived nearby (applied to identify injection network structures, and this provides an important mechanism for improving public health surveillance, accessing high-risk populations, and implementing risk-reduction interventions to slow HIV transmission. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Social networks

    CERN Document Server

    Etaner-Uyar, A Sima

    2014-01-01

    The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many

  15. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model

    Directory of Open Access Journals (Sweden)

    Dan Liu

    2018-04-01

    Full Text Available This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN and a continuous pairwise Conditional Random Field (CRF model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  16. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model.

    Science.gov (United States)

    Liu, Dan; Liu, Xuejun; Wu, Yiguang

    2018-04-24

    This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  17. Imaging samples larger than the field of view: the SLS experience

    Science.gov (United States)

    Vogiatzis Oikonomidis, Ioannis; Lovric, Goran; Cremona, Tiziana P.; Arcadu, Filippo; Patera, Alessandra; Schittny, Johannes C.; Stampanoni, Marco

    2017-06-01

    Volumetric datasets with micrometer spatial and sub-second temporal resolutions are nowadays routinely acquired using synchrotron X-ray tomographic microscopy (SRXTM). Although SRXTM technology allows the examination of multiple samples with short scan times, many specimens are larger than the field-of-view (FOV) provided by the detector. The extension of the FOV in the direction perpendicular to the rotation axis remains non-trivial. We present a method that can efficiently increase the FOV merging volumetric datasets obtained by region-of-interest tomographies in different 3D positions of the sample with a minimal amount of artefacts and with the ability to handle large amounts of data. The method has been successfully applied for the three-dimensional imaging of a small number of mouse lung acini of intact animals, where pixel sizes down to the micrometer range and short exposure times are required.

  18. Networks of networks the last frontier of complexity

    CERN Document Server

    Scala, Antonio

    2014-01-01

    The present work is meant as a reference to provide an organic and comprehensive view of the most relevant results in the exciting new field of Networks of Networks (NetoNets). Seminal papers have recently been published posing the basis to study what happens when different networks interact, thus providing evidence for the emergence of new, unexpected behaviors and vulnerabilities. From those seminal works, the awareness on the importance understanding Networks of Networks (NetoNets) has spread to the entire community of Complexity Science. The reader will benefit from the experience of some of the most well-recognized leaders in this field. The contents have been aggregated under four headings; General Theory, Phenomenology, Applications and Risk Assessment. The reader will be impressed by the different applications of the general paradigm that span from physiology, to financial risk, to transports. We are currently making the first steps to reduce the distance between the language and the way of thinking o...

  19. Three neural network based sensor systems for environmental monitoring

    International Nuclear Information System (INIS)

    Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

    1994-05-01

    Compact, portable systems capable of quickly identifying contaminants in the field are of great importance when monitoring the environment. One of the missions of the Pacific Northwest Laboratory is to examine and develop new technologies for environmental restoration and waste management at the Hanford Site. In this paper, three prototype sensing systems are discussed. These prototypes are composed of sensing elements, data acquisition system, computer, and neural network implemented in software, and are capable of automatically identifying contaminants. The first system employs an array of tin-oxide gas sensors and is used to identify chemical vapors. The second system employs an array of optical sensors and is used to identify the composition of chemical dyes in liquids. The third system contains a portable gamma-ray spectrometer and is used to identify radioactive isotopes. In these systems, the neural network is used to identify the composition of the sensed contaminant. With a neural network, the intense computation takes place during the training process. Once the network is trained, operation consists of propagating the data through the network. Since the computation involved during operation consists of vector-matrix multiplication and application of look-up tables unknown samples can be rapidly identified in the field

  20. Patent citation network in nanotechnology (1976-2004)

    International Nuclear Information System (INIS)

    Li Xin; Chen Hsinchun; Huang Zan; Roco, Mihail C.

    2007-01-01

    The patent citation networks are described using critical node, core network, and network topological analysis. The main objective is understanding of the knowledge transfer processes between technical fields, institutions and countries. This includes identifying key influential players and subfields, the knowledge transfer patterns among them, and the overall knowledge transfer efficiency. The proposed framework is applied to the field of nanoscale science and engineering (NSE), including the citation networks of patent documents, submitting institutions, technology fields, and countries. The NSE patents were identified by keywords 'full-text' searching of patents at the United States Patent and Trademark Office (USPTO). The analysis shows that the United States is the most important citation center in NSE research. The institution citation network illustrates a more efficient knowledge transfer between institutions than a random network. The country citation network displays a knowledge transfer capability as efficient as a random network. The technology field citation network and the patent document citation network exhibit a less efficient knowledge diffusion capability than a random network. All four citation networks show a tendency to form local citation clusters

  1. Ensemble Sampling

    OpenAIRE

    Lu, Xiuyuan; Van Roy, Benjamin

    2017-01-01

    Thompson sampling has emerged as an effective heuristic for a broad range of online decision problems. In its basic form, the algorithm requires computing and sampling from a posterior distribution over models, which is tractable only for simple special cases. This paper develops ensemble sampling, which aims to approximate Thompson sampling while maintaining tractability even in the face of complex models such as neural networks. Ensemble sampling dramatically expands on the range of applica...

  2. A Network Analysis of the Teachers and Graduate Students’ Research Topics in the Field of Mass Communication

    Directory of Open Access Journals (Sweden)

    Ming-Shu Yuan

    2013-06-01

    Full Text Available The completion of a master’s thesis requires the advisor’s guidance on topic selection, data collection, analysis, interpretation and writing. The advisory committee’s input also contributes to the work. This study conducted content analysis and network analysis on a sample of 547 master’s theses from eight departments of the College of Journalism and Communications of Shih Hsin University to examine the relationships between the advisors and committee members as well as the connections of research topics. The results showed that the topic “lifestyle” have attracted cross-department research interests in the college. The academic network of the college is rather loose, and serving university administration duties may have broadened a faculty member’s centrality in the network. The Department of Communications Management and the Graduate Institute of Communications served as the bridges for the inter-departmental communication in the network. One can understand the interrelations among professors and departments through study on network analysis of thesis as to identify the characteristics of each department, as well as to reveal invisible relations of academic network and scholarly communication. [Article content in Chinese

  3. Using a fully convolutional neural network for detecting locations of weeds in images from cereal fields

    DEFF Research Database (Denmark)

    Dyrmann, Mads; Skovsen, Søren; Sørensen, René A.

    2018-01-01

    been evaluated on an Nvidia Titan X, on which it is able to process a 5MPx image in 0.02s, making the method suitable for real-time field operation. For mechanical weed control, this network is sufficient. However, for chemical weed control, we also need to know the weed species in order to choose...

  4. Statistical properties of the surface velocity field in the northern Gulf of Mexico sampled by GLAD drifters

    OpenAIRE

    Mariano, A.J.; Ryan, E.H.; Huntley, H.S.; Laurindo, L.C.; Coelho, E.; Ozgokmen, TM; Berta, M.; Bogucki, D; Chen, S.S.; Curcic, M.; Drouin, K.L.; Gough, M; Haus, BK; Haza, A.C.; Hogan, P

    2016-01-01

    The Grand LAgrangian Deployment (GLAD) used multiscale sampling and GPS technology to observe time series of drifter positions with initial drifter separation of O(100 m) to O(10 km), and nominal 5 min sampling, during the summer and fall of 2012 in the northern Gulf of Mexico. Histograms of the velocity field and its statistical parameters are non-Gaussian; most are multimodal. The dominant periods for the surface velocity field are 1–2 days due to inertial oscillations, tides, and the sea b...

  5. 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

  6. Use of spatially distributed time-integrated sediment sampling networks and distributed fine sediment modelling to inform catchment management.

    Science.gov (United States)

    Perks, M T; Warburton, J; Bracken, L J; Reaney, S M; Emery, S B; Hirst, S

    2017-11-01

    Under the EU Water Framework Directive, suspended sediment is omitted from environmental quality standards and compliance targets. This omission is partly explained by difficulties in assessing the complex dose-response of ecological communities. But equally, it is hindered by a lack of spatially distributed estimates of suspended sediment variability across catchments. In this paper, we demonstrate the inability of traditional, discrete sampling campaigns for assessing exposure to fine sediment. Sampling frequencies based on Environmental Quality Standard protocols, whilst reflecting typical manual sampling constraints, are unable to determine the magnitude of sediment exposure with an acceptable level of precision. Deviations from actual concentrations range between -35 and +20% based on the interquartile range of simulations. As an alternative, we assess the value of low-cost, suspended sediment sampling networks for quantifying suspended sediment transfer (SST). In this study of the 362 km 2 upland Esk catchment we observe that spatial patterns of sediment flux are consistent over the two year monitoring period across a network of 17 monitoring sites. This enables the key contributing sub-catchments of Butter Beck (SST: 1141 t km 2 yr -1 ) and Glaisdale Beck (SST: 841 t km 2 yr -1 ) to be identified. The time-integrated samplers offer a feasible alternative to traditional infrequent and discrete sampling approaches for assessing spatio-temporal changes in contamination. In conjunction with a spatially distributed diffuse pollution model (SCIMAP), time-integrated sediment sampling is an effective means of identifying critical sediment source areas in the catchment, which can better inform sediment management strategies for pollution prevention and control. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Forecasting Urban Air Quality via a Back-Propagation Neural Network and a Selection Sample Rule

    Directory of Open Access Journals (Sweden)

    Yonghong Liu

    2015-07-01

    Full Text Available In this paper, based on a sample selection rule and a Back Propagation (BP neural network, a new model of forecasting daily SO2, NO2, and PM10 concentration in seven sites of Guangzhou was developed using data from January 2006 to April 2012. A meteorological similarity principle was applied in the development of the sample selection rule. The key meteorological factors influencing SO2, NO2, and PM10 daily concentrations as well as weight matrices and threshold matrices were determined. A basic model was then developed based on the improved BP neural network. Improving the basic model, identification of the factor variation consistency was added in the rule, and seven sets of sensitivity experiments in one of the seven sites were conducted to obtain the selected model. A comparison of the basic model from May 2011 to April 2012 in one site showed that the selected model for PM10 displayed better forecasting performance, with Mean Absolute Percentage Error (MAPE values decreasing by 4% and R2 values increasing from 0.53 to 0.68. Evaluations conducted at the six other sites revealed a similar performance. On the whole, the analysis showed that the models presented here could provide local authorities with reliable and precise predictions and alarms about air quality if used at an operational scale.

  8. Irradiation test of HAFM and tag gas samples at the standard neutron field of 'YAYOI'

    International Nuclear Information System (INIS)

    Iguchi, Tetsuo

    1997-03-01

    To check the accuracy of helium accumulation neutron fluence monitors (HAFM) as new technique for fast reactor neutron dosimetry and the applicability of tag gas activation analysis to fast reactor failed fuel detection, their samples were irradiated at the standard neutron field of the fast neutron source reactor 'YAYOI' (Nuclear Engineering Research Laboratory, University of Tokyo). Since October in 1996, the HAFM samples such as 93% enriched boron (B) powders of 1 mg and natural B powders of 10 mg contained in vanadium (V) capsule were intermittently irradiated at the reactor core center (Glory hole: Gy) and/or under the leakage neutron field from the reactor core (Fast column: FC). In addition, new V capsules filled with enriched B of 40 mg and Be of 100 mg, respectively, were put into an experimental hole through the blanket surrounding the core. These neutron fields were monitored by the activation foils consisting of Fe, Co, Ni, Au, 235 U, 237 Np etc., mainly to confirm the results obtained from 1995's preliminary works. In particular, neutron flux distributions in the vicinity of irradiated samples were measured in more detail. At the end of March in 1997, the irradiated neutron fluence have reached the goal necessary to produce the detectable number of He atoms more than ∼10 13 in each HAFM sample. Six kinds of tag gas samples, which are the mixed gases of isotopically adjusted Xe and Kr contained in SUS capsules, were separately irradiated three times at Gy under the neutron fluence of ∼10 16 n/cm 2 in average. After irradiation, γ-ray spectra were measured for each sample. Depending on the composition of tag gas mixtures, the different patterns of γ-ray peak spectra from 79 Kr, 125 Xe, etc. produced through tag gas activation were able to be clearly identified. These experimental data will be very useful for the benchmark test of tag gas activation calculation applied to the fast reactor failed fuel detection. (author)

  9. TRAN-STAT, Issue No. 3, January 1978. Topics discussed: some statistical aspects of compositing field samples

    International Nuclear Information System (INIS)

    Gilbert, R.O.

    1978-01-01

    Some statistical aspects of compositing field samples of soils for determining the content of Pu are discussed. Some of the potential problems involved in pooling samples are reviewed. This is followed by more detailed discussions and examples of compositing designs, adequacy of mixing, statistical models and their role in compositing, and related topics

  10. [Strategies for biobank networks. Classification of different approaches for locating samples and an outlook on the future within the BBMRI-ERIC].

    Science.gov (United States)

    Lablans, Martin; Kadioglu, Dennis; Mate, Sebastian; Leb, Ines; Prokosch, Hans-Ulrich; Ückert, Frank

    2016-03-01

    Medical research projects often require more biological material than can be supplied by a single biobank. For this reason, a multitude of strategies support locating potential research partners with matching material without requiring centralization of sample storage. Classification of different strategies for biobank networks, in particular for locating suitable samples. Description of an IT infrastructure combining these strategies. Existing strategies can be classified according to three criteria: (a) granularity of sample data: coarse bank-level data (catalogue) vs. fine-granular sample-level data, (b) location of sample data: central (central search service) vs. decentral storage (federated search services), and (c) level of automation: automatic (query-based, federated search service) vs. semi-automatic (inquiry-based, decentral search). All mentioned search services require data integration. Metadata help to overcome semantic heterogeneity. The "Common Service IT" in BBMRI-ERIC (Biobanking and BioMolecular Resources Research Infrastructure) unites a catalogue, the decentral search and metadata in an integrated platform. As a result, researchers receive versatile tools to search suitable biomaterial, while biobanks retain a high degree of data sovereignty. Despite their differences, the presented strategies for biobank networks do not rule each other out but can complement and even benefit from each other.

  11. Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

    Science.gov (United States)

    Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

    2015-01-01

    Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

  12. No Man is an Island: Social Distance, Network Flow, and Other-Regarding Behaviors in a Natural Field Experiment

    Directory of Open Access Journals (Sweden)

    XIAOYE LI

    2012-01-01

    Full Text Available A natural field experiment is designed to explore the impacts of social distanceand network flow on other-regarding behaviors. A greater degree ofcommunication between the voluntary organization and volunteers was found toreduce their social distance and thereby improve volunteering commitment. Theimprovement was even more notable if the party initiating communication was thevoluntary organization. Two other practical means of lessening social distancewere for volunteers to learn more about other volunteers, and for informationtobe dispersed throughout the organization more rapidly. Additionally, this studyshows a reversed “U-shaped” relationship between network flow and volunteeringcommitment.

  13. Complex Networks

    CERN Document Server

    Evsukoff, Alexandre; González, Marta

    2013-01-01

    In the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know th...

  14. Social networks and alcohol use disorders: findings from a nationally representative sample

    Science.gov (United States)

    Mowbray, Orion; Quinn, Adam; Cranford, James A.

    2014-01-01

    Background While some argue that social network ties of individuals with alcohol use disorders (AUD) are robust, there is evidence to suggest that individuals with AUDs have few social network ties, which are a known risk factor for health and wellness. Objectives Social network ties to friends, family, co-workers and communities of individuals are compared among individuals with a past-year diagnosis of alcohol dependence or alcohol abuse to individuals with no lifetime diagnosis of AUD. Method Respondents from Wave 2 of the National Epidemiologic Survey on Alcohol Related Conditions (NESARC) were assessed for the presence of past-year alcohol dependence or past-year alcohol abuse, social network ties, sociodemographics and clinical characteristics. Results Bivariate analyses showed that both social network size and social network diversity was significantly smaller among individuals with alcohol dependence, compared to individuals with alcohol abuse or no AUD. When social and clinical factors related to AUD status were controlled, multinomial logistic models showed that social network diversity remained a significant predictor of AUD status, while social network size did not differ among AUD groups. Conclusion Social networks of individuals with AUD may be different than individuals with no AUD, but this claim is dependent on specific AUD diagnosis and how social networks are measured. PMID:24405256

  15. Extreme robustness of scaling in sample space reducing processes explains Zipf’s law in diffusion on directed networks

    International Nuclear Information System (INIS)

    Corominas-Murtra, Bernat; Hanel, Rudolf; Thurner, Stefan

    2016-01-01

    It has been shown recently that a specific class of path-dependent stochastic processes, which reduce their sample space as they unfold, lead to exact scaling laws in frequency and rank distributions. Such sample space reducing processes offer an alternative new mechanism to understand the emergence of scaling in countless processes. The corresponding power law exponents were shown to be related to noise levels in the process. Here we show that the emergence of scaling is not limited to the simplest SSRPs, but holds for a huge domain of stochastic processes that are characterised by non-uniform prior distributions. We demonstrate mathematically that in the absence of noise the scaling exponents converge to −1 (Zipf’s law) for almost all prior distributions. As a consequence it becomes possible to fully understand targeted diffusion on weighted directed networks and its associated scaling laws in node visit distributions. The presence of cycles can be properly interpreted as playing the same role as noise in SSRPs and, accordingly, determine the scaling exponents. The result that Zipf’s law emerges as a generic feature of diffusion on networks, regardless of its details, and that the exponent of visiting times is related to the amount of cycles in a network could be relevant for a series of applications in traffic-, transport- and supply chain management. (paper)

  16. A Systematic Review of Research on Social Networks of Older Adults.

    Science.gov (United States)

    Ayalon, Liat; Levkovich, Inbar

    2018-01-29

    There has been a substantial interest in life course/life span changes in older adults' social networks and in the relationship between social networks and health and wellbeing. The study embarked on a systematic review to examine the existing knowledgebase on social network in the field of gerontology. Our focus was on studies in which both ego (respondents) and his or her alters (network members) are queried about their social ties. We searched for studies published in English before September, 2017, relied on quantitative methods to obtain data from both ego (60 years of age and older) and alters and provided a quantitative account of the social network properties. We searched the following data sets: APA Psychnet, Pubmed, Sociological abstracts, and Ageline. This was followed by a snowball search of relevant articles using Google Scholar. Titles and abstracts were reviewed and selected articles were extracted independently by two reviewers. A total of 5,519 records were retrieved. Of these, 3,994 records remained after the removal of duplicates. Ten records reporting on five original samples were kept for the systematic review. One study described a social network of community dwelling older adults and the remaining studies described social networks of institutional older adults. The present study points to a lacuna in current understanding of social networks in the field of gerontology. It provides a useful review and possible tools for the design of future studies to address current shortcomings in the field. © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. Choice of sample size for high transport critical current density in a granular superconductor: percolation versus self-field effects

    International Nuclear Information System (INIS)

    Mulet, R.; Diaz, O.; Altshuler, E.

    1997-01-01

    The percolative character of the current paths and the self-field effects were considered to estimate optimal sample dimensions for the transport current of a granular superconductor by means of a Monte Carlo algorithm and critical-state model calculations. We showed that, under certain conditions, self-field effects are negligible and the J c dependence on sample dimensions is determined by the percolative character of the current. Optimal dimensions are demonstrated to be a function of the fraction of superconducting phase in the sample. (author)

  18. Method Evaluation And Field Sample Measurements For The Rate Of Movement Of The Oxidation Front In Saltstone

    Energy Technology Data Exchange (ETDEWEB)

    Almond, P. M. [Savannah River Site (SRS), Aiken, SC (United States); Kaplan, D. I. [Savannah River Site (SRS), Aiken, SC (United States); Langton, C. A. [Savannah River Site (SRS), Aiken, SC (United States); Stefanko, D. B. [Savannah River Site (SRS), Aiken, SC (United States); Spencer, W. A. [Savannah River Site (SRS), Aiken, SC (United States); Hatfield, A. [Clemson University, Clemson, SC (United States); Arai, Y. [Clemson University, Clemson, SC (United States)

    2012-08-23

    The objective of this work was to develop and evaluate a series of methods and validate their capability to measure differences in oxidized versus reduced saltstone. Validated methods were then applied to samples cured under field conditions to simulate Performance Assessment (PA) needs for the Saltstone Disposal Facility (SDF). Four analytical approaches were evaluated using laboratory-cured saltstone samples. These methods were X-ray absorption spectroscopy (XAS), diffuse reflectance spectroscopy (DRS), chemical redox indicators, and thin-section leaching methods. XAS and thin-section leaching methods were validated as viable methods for studying oxidation movement in saltstone. Each method used samples that were spiked with chromium (Cr) as a tracer for oxidation of the saltstone. The two methods were subsequently applied to field-cured samples containing chromium to characterize the oxidation state of chromium as a function of distance from the exposed air/cementitious material surface.

  19. Strong geomagnetic activity forecast by neural networks under dominant southern orientation of the interplanetary magnetic field

    Czech Academy of Sciences Publication Activity Database

    Valach, F.; Bochníček, Josef; Hejda, Pavel; Revallo, M.

    2014-01-01

    Roč. 53, č. 4 (2014), s. 589-598 ISSN 0273-1177 R&D Projects: GA AV ČR(CZ) IAA300120608; GA MŠk OC09070 Institutional support: RVO:67985530 Keywords : geomagnetic activity * interplanetary magnetic field * artificial neural network * ejection of coronal mass * X-ray flares Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 1.358, year: 2014

  20. Internal fracture heterogeneity in discrete fracture network modelling: Effect of correlation length and textures with connected and disconnected permeability field

    Science.gov (United States)

    Frampton, A.; Hyman, J.; Zou, L.

    2017-12-01

    Analysing flow and transport in sparsely fractured media is important for understanding how crystalline bedrock environments function as barriers to transport of contaminants, with important applications towards subsurface repositories for storage of spent nuclear fuel. Crystalline bedrocks are particularly favourable due to their geological stability, low advective flow and strong hydrogeochemical retention properties, which can delay transport of radionuclides, allowing decay to limit release to the biosphere. There are however many challenges involved in quantifying and modelling subsurface flow and transport in fractured media, largely due to geological complexity and heterogeneity, where the interplay between advective and dispersive flow strongly impacts both inert and reactive transport. A key to modelling transport in a Lagrangian framework involves quantifying pathway travel times and the hydrodynamic control of retention, and both these quantities strongly depend on heterogeneity of the fracture network at different scales. In this contribution, we present recent analysis of flow and transport considering fracture networks with single-fracture heterogeneity described by different multivariate normal distributions. A coherent triad of fields with identical correlation length and variance are created but which greatly differ in structure, corresponding to textures with well-connected low, medium and high permeability structures. Through numerical modelling of multiple scales in a stochastic setting we quantify the relative impact of texture type and correlation length against network topological measures, and identify key thresholds for cases where flow dispersion is controlled by single-fracture heterogeneity versus network-scale heterogeneity. This is achieved by using a recently developed novel numerical discrete fracture network model. Furthermore, we highlight enhanced flow channelling for cases where correlation structure continues across

  1. Design of Field Experiments for Adaptive Sampling of the Ocean with Autonomous Vehicles

    Science.gov (United States)

    Zheng, H.; Ooi, B. H.; Cho, W.; Dao, M. H.; Tkalich, P.; Patrikalakis, N. M.

    2010-05-01

    Due to the highly non-linear and dynamical nature of oceanic phenomena, the predictive capability of various ocean models depends on the availability of operational data. A practical method to improve the accuracy of the ocean forecast is to use a data assimilation methodology to combine in-situ measured and remotely acquired data with numerical forecast models of the physical environment. Autonomous surface and underwater vehicles with various sensors are economic and efficient tools for exploring and sampling the ocean for data assimilation; however there is an energy limitation to such vehicles, and thus effective resource allocation for adaptive sampling is required to optimize the efficiency of exploration. In this paper, we use physical oceanography forecasts of the coastal zone of Singapore for the design of a set of field experiments to acquire useful data for model calibration and data assimilation. The design process of our experiments relied on the oceanography forecast including the current speed, its gradient, and vorticity in a given region of interest for which permits for field experiments could be obtained and for time intervals that correspond to strong tidal currents. Based on these maps, resources available to our experimental team, including Autonomous Surface Craft (ASC) are allocated so as to capture the oceanic features that result from jets and vortices behind bluff bodies (e.g., islands) in the tidal current. Results are summarized from this resource allocation process and field experiments conducted in January 2009.

  2. First field trial of Virtual Network Operator oriented network on demand (NoD) service provisioning over software defined multi-vendor OTN networks

    Science.gov (United States)

    Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Chen, Haoran; Zhu, Ruijie; Zhou, Quanwei; Yu, Chenbei; Cui, Rui

    2017-01-01

    A Virtual Network Operator (VNO) is a provider and reseller of network services from other telecommunications suppliers. These network providers are categorized as virtual because they do not own the underlying telecommunication infrastructure. In terms of business operation, VNO can provide customers with personalized services by leasing network infrastructure from traditional network providers. The unique business modes of VNO lead to the emergence of network on demand (NoD) services. The conventional network provisioning involves a series of manual operation and configuration, which leads to high cost in time. Considering the advantages of Software Defined Networking (SDN), this paper proposes a novel NoD service provisioning solution to satisfy the private network need of VNOs. The solution is first verified in the real software defined multi-domain optical networks with multi-vendor OTN equipment. With the proposed solution, NoD service can be deployed via online web portals in near-real time. It reinvents the customer experience and redefines how network services are delivered to customers via an online self-service portal. Ultimately, this means a customer will be able to simply go online, click a few buttons and have new services almost instantaneously.

  3. A convolutional neural network neutrino event classifier

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  4. Search for life on Mars in surface samples: Lessons from the 1999 Marsokhod rover field experiment

    Science.gov (United States)

    Newsom, Horton E.; Bishop, J.L.; Cockell, C.; Roush, T.L.; Johnson, J. R.

    2001-01-01

    The Marsokhod 1999 field experiment in the Mojave Desert included a simulation of a rover-based sample selection mission. As part of this mission, a test was made of strategies and analytical techniques for identifying past or present life in environments expected to be present on Mars. A combination of visual clues from high-resolution images and the detection of an important biomolecule (chlorophyll) with visible/near-infrared (NIR) spectroscopy led to the successful identification of a rock with evidence of cryptoendolithic organisms. The sample was identified in high-resolution images (3 times the resolution of the Imager for Mars Pathfinder camera) on the basis of a green tinge and textural information suggesting the presence of a thin, partially missing exfoliating layer revealing the organisms. The presence of chlorophyll bands in similar samples was observed in visible/NIR spectra of samples in the field and later confirmed in the laboratory using the same spectrometer. Raman spectroscopy in the laboratory, simulating a remote measurement technique, also detected evidence of carotenoids in samples from the same area. Laboratory analysis confirmed that the subsurface layer of the rock is inhabited by a community of coccoid Chroococcidioposis cyanobacteria. The identification of minerals in the field, including carbonates and serpentine, that are associated with aqueous processes was also demonstrated using the visible/NIR spectrometer. Other lessons learned that are applicable to future rover missions include the benefits of web-based programs for target selection and for daily mission planning and the need for involvement of the science team in optimizing image compression schemes based on the retention of visual signature characteristics. Copyright 2000 by the American Geophysical Union.

  5. 8th Conference on Complex Networks

    CERN Document Server

    Menezes, Ronaldo; Sinatra, Roberta; Zlatic, Vinko

    2017-01-01

    This book collects the works presented at the 8th International Conference on Complex Networks (CompleNet) 2017 in Dubrovnik, Croatia, on March 21-24, 2017. CompleNet aims at bringing together researchers and practitioners working in areas related to complex networks. The past two decades has witnessed an exponential increase in the number of publications within this field. From biological systems to computer science, from economic to social systems, complex networks are becoming pervasive in many fields of science. It is this interdisciplinary nature of complex networks that CompleNet aims at addressing. The last decades have seen the emergence of complex networks as the language with which a wide range of complex phenomena in fields as diverse as physics, computer science, and medicine (to name a few) can be properly described and understood. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as network controllability, social structure, online behavior, recommend...

  6. Technologies for Home Networking

    DEFF Research Database (Denmark)

    A broad overview of the home networking field, ranging from wireless technologies to practical applications. In the future, it is expected that private networks (e.g. home networks) will become part of the global network ecosystem, participating in sharing their own content, running IP...

  7. Field portable low temperature porous layer open tubular cryoadsorption headspace sampling and analysis part I: Instrumentation.

    Science.gov (United States)

    Bruno, Thomas J

    2016-01-15

    Building on the successful application in the laboratory of PLOT-cryoadsorption as a means of collecting vapor (or headspace) samples for chromatographic analysis, in this paper a field portable apparatus is introduced. This device fits inside of a briefcase (aluminum tool carrier), and can be easily transported by vehicle or by air. The portable apparatus functions entirely on compressed air, making it suitable for use in locations lacking electrical power, and for use in flammable and explosive environments. The apparatus consists of four aspects: a field capable PLOT-capillary platform, the supporting equipment platform, the service interface between the PLOT-capillary and the supporting equipment, and the necessary peripherals. Vapor sampling can be done with either a hand piece (containing the PLOT capillary) or with a custom fabricated standoff module. Both the hand piece and the standoff module can be heated and cooled to facilitate vapor collection and subsequent vapor sample removal. The service interface between the support platform and the sampling units makes use of a unique counter current approach that minimizes loss of cooling and heating due to heat transfer with the surroundings (recuperative thermostatting). Several types of PLOT-capillary elements and sampling probes are described in this report. Applications to a variety of samples relevant to forensic and environmental analysis are discussed in a companion paper. Published by Elsevier B.V.

  8. Mobile field data acquisition in geosciences

    Science.gov (United States)

    Golodoniuc, Pavel; Klump, Jens; Reid, Nathan; Gray, David

    2016-04-01

    The Discovering Australia's Mineral Resources Program of CSIRO is conducting a study to develop novel methods and techniques to reliably define distal footprints of mineral systems under regolith cover in the Capricorn Orogen - the area that lies between two well-known metallogenic provinces of Pilbara and Yilgarn Cratons in Western Australia. The multidisciplinary study goes beyond the boundaries of a specific discipline and aims at developing new methods to integrate heterogeneous datasets to gain insight into the key indicators of mineralisation. The study relies on large regional datasets obtained from previous hydrogeochemical, regolith, and resistate mineral studies around known deposits, as well as new data obtained from the recent field sampling campaigns around areas of interest. With thousands of water, vegetation, rock and soil samples collected over the past years, it has prompted us to look at ways to standardise field sampling procedures and review the data acquisition process. This process has evolved over the years (Golodoniuc et al., 2015; Klump et al., 2015) and has now reached the phase where fast and reliable collection of scientific data in remote areas is possible. The approach is backed by a unified discipline-agnostic platform - the Federated Archaeological Information Management System (FAIMS). FAIMS is an open source framework for mobile field data acquisition, developed at the University of New South Wales for archaeological field data collection. The FAIMS framework can easily be adapted to a diverse range of scenarios, different kinds of samples, each with its own peculiarities, integration with GPS, and the ability to associate photographs taken with the device embedded camera with captured data. Three different modules have been developed so far, dedicated to geochemical water, plant and rock sampling. All modules feature automatic date and position recording, and reproduce the established data recording workflows. The rock sampling

  9. Continuous assessment of land mapping accuracy at High Resolution from global networks of atmospheric and field observatories -concept and demonstration

    Science.gov (United States)

    Sicard, Pierre; Martin-lauzer, François-regis

    2017-04-01

    In the context of global climate change and adjustment/resilience policies' design and implementation, there is a need not only i. for environmental monitoring, e.g. through a range of Earth Observations (EO) land "products" but ii. for a precise assessment of uncertainties of the aforesaid information that feed environmental decision-making (to be introduced in the EO metadata) and also iii. for a perfect handing of the thresholds which help translate "environment tolerance limits" to match detected EO changes through ecosystem modelling. Uncertainties' insight means precision and accuracy's knowledge and subsequent ability of setting thresholds for change detection systems. Traditionally, the validation of satellite-derived products has taken the form of intensive field campaigns to sanction the introduction of data processors in Payload Data Ground Segments chains. It is marred by logistical challenges and cost issues, reason why it is complemented by specific surveys at ground-based monitoring sites which can provide near-continuous observations at a high temporal resolution (e.g. RadCalNet). Unfortunately, most of the ground-level monitoring sites, in the number of 100th or 1000th, which are part of wider observation networks (e.g. FLUXNET, NEON, IMAGINES) mainly monitor the state of the atmosphere and the radiation exchange at the surface, which are different to the products derived from EO data. In addition they are "point-based" compared to the EO cover to be obtained from Sentinel-2 or Sentinel-3. Yet, data from these networks, processed by spatial extrapolation models, are well-suited to the bottom-up approach and relevant to the validation of vegetation parameters' consistency (e.g. leaf area index, fraction of absorbed photosynthetically active radiation). Consistency means minimal errors on spatial and temporal gradients of EO products. Test of the procedure for land-cover products' consistency assessment with field measurements delivered by worldwide

  10. Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

    Science.gov (United States)

    Zhang, WenJun

    2007-07-01

    Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

  11. Field sampling and travel report

    Science.gov (United States)

    Dr. Sigua was involved with two field visits of watersheds with different livestock production systems (poultry, swine, and beef/dairy cattle); one in the sub-basins of Pinhal River Watershed (October 23, 2008) and at the micro-basins of the Rio Pine Forest (October 29, 2008) where studies of assess...

  12. Network coding at different layers in wireless networks

    CERN Document Server

    2016-01-01

    This book focuses on how to apply network coding at different layers in wireless networks – including MAC, routing, and TCP – with special focus on cognitive radio networks. It discusses how to select parameters in network coding (e.g., coding field, number of packets involved, and redundant information ration) in order to be suitable for the varying wireless environments. The book explores how to deploy network coding in MAC to improve network performance and examines joint network coding with opportunistic routing to improve the successful rate of routing. In regards to TCP and network coding, the text considers transport layer protocol working with network coding to overcome the transmission error rate, particularly with how to use the ACK feedback of TCP to enhance the efficiency of network coding. The book pertains to researchers and postgraduate students, especially whose interests are in opportunistic routing and TCP in cognitive radio networks.

  13. Optical transmission testing based on asynchronous sampling techniques: images analysis containing chromatic dispersion using convolutional neural network

    Science.gov (United States)

    Mrozek, T.; Perlicki, K.; Tajmajer, T.; Wasilewski, P.

    2017-08-01

    The article presents an image analysis method, obtained from an asynchronous delay tap sampling (ADTS) technique, which is used for simultaneous monitoring of various impairments occurring in the physical layer of the optical network. The ADTS method enables the visualization of the optical signal in the form of characteristics (so called phase portraits) that change their shape under the influence of impairments such as chromatic dispersion, polarization mode dispersion and ASE noise. Using this method, a simulation model was built with OptSim 4.0. After the simulation study, data were obtained in the form of images that were further analyzed using the convolutional neural network algorithm. The main goal of the study was to train a convolutional neural network to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses only on the analysis of images containing chromatic dispersion.

  14. Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

    Science.gov (United States)

    Meng, Su; Chen, Jie; Sun, Jian

    2017-10-01

    This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

  15. Network compensation for missing sensors

    Science.gov (United States)

    Ahumada, Albert J., Jr.; Mulligan, Jeffrey B.

    1991-01-01

    A network learning translation invariance algorithm to compute interpolation functions is presented. This algorithm with one fixed receptive field can construct a linear transformation compensating for gain changes, sensor position jitter, and sensor loss when there are enough remaining sensors to adequately sample the input images. However, when the images are undersampled and complete compensation is not possible, the algorithm need to be modified. For moderate sensor losses, the algorithm works if the transformation weight adjustment is restricted to the weights to output units affected by the loss.

  16. An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

    Science.gov (United States)

    Srbinovski, Bruno; Magno, Michele; Edwards-Murphy, Fiona; Pakrashi, Vikram; Popovici, Emanuel

    2016-01-01

    Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN) are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind). Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA) in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources) and power hungry sensors (ultrasonic wind sensor and gas sensors). The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA. PMID:27043559

  17. An Energy Aware Adaptive Sampling Algorithm for Energy Harvesting WSN with Energy Hungry Sensors

    Directory of Open Access Journals (Sweden)

    Bruno Srbinovski

    2016-03-01

    Full Text Available Wireless sensor nodes have a limited power budget, though they are often expected to be functional in the field once deployed for extended periods of time. Therefore, minimization of energy consumption and energy harvesting technology in Wireless Sensor Networks (WSN are key tools for maximizing network lifetime, and achieving self-sustainability. This paper proposes an energy aware Adaptive Sampling Algorithm (ASA for WSN with power hungry sensors and harvesting capabilities, an energy management technique that can be implemented on any WSN platform with enough processing power to execute the proposed algorithm. An existing state-of-the-art ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using two in-field testbeds that are supplied by two different energy harvesting sources (solar and wind. Simulation and comparison between the state-of-the-art ASA and the proposed energy aware ASA (EASA in terms of energy durability are carried out using in-field measured harvested energy (using both wind and solar sources and power hungry sensors (ultrasonic wind sensor and gas sensors. The simulation results demonstrate that using ASA in combination with an energy aware function on the nodes can drastically increase the lifetime of a WSN node and enable self-sustainability. In fact, the proposed EASA in conjunction with energy harvesting capability can lead towards perpetual WSN operation and significantly outperform the state-of-the-art ASA.

  18. Hybrid Access Femtocells in Overlaid MIMO Cellular Networks with Transmit Selection under Poisson Field Interference

    KAUST Repository

    Abdel Nabi, Amr A

    2017-09-21

    This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.

  19. Hybrid Access Femtocells in Overlaid MIMO Cellular Networks with Transmit Selection under Poisson Field Interference

    KAUST Repository

    Abdel Nabi, Amr A; Al-Qahtani, Fawaz S.; Radaydeh, Redha Mahmoud Mesleh; Shaqfeh, Mohammed

    2017-01-01

    This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.

  20. Visualization maps for the evolution of research hotspots in the field of regional health information networks.

    Science.gov (United States)

    Wang, Yanjun; Zheng, Jianzhong; Zhang, Ailian; Zhou, Wei; Dong, Haiyuan

    2018-03-01

    The aim of this study was to reveal research hotspots in the field of regional health information networks (RHINs) and use visualization techniques to explore their evolution over time and differences between countries. We conducted a literature review for a 50-year period and compared the prevalence of certain index terms during the periods 1963-1993 and 1994-2014 and in six countries. We applied keyword frequency analysis, keyword co-occurrence analysis, multidimensional scaling analysis, and network visualization technology. The total number of keywords was found to increase with time. From 1994 to 2014, the research priorities shifted from hospital planning to community health planning. The number of keywords reflecting information-based research increased. The density of the knowledge network increased significantly, and partial keywords condensed into knowledge groups. All six countries focus on keywords including Information Systems; Telemedicine; Information Service; Medical Records Systems, Computerized; Internet; etc.; however, the level of development and some research priorities are different. RHIN research has generally increased in popularity over the past 50 years. The research hotspots are evolving and are at different levels of development in different countries. Knowledge network mapping and perceptual maps provide useful information for scholars, managers, and policy-makers.

  1. When Is Network Lasso Accurate?

    Directory of Open Access Journals (Sweden)

    Alexander Jung

    2018-01-01

    Full Text Available The “least absolute shrinkage and selection operator” (Lasso method has been adapted recently for network-structured datasets. In particular, this network Lasso method allows to learn graph signals from a small number of noisy signal samples by using the total variation of a graph signal for regularization. While efficient and scalable implementations of the network Lasso are available, only little is known about the conditions on the underlying network structure which ensure network Lasso to be accurate. By leveraging concepts of compressed sensing, we address this gap and derive precise conditions on the underlying network topology and sampling set which guarantee the network Lasso for a particular loss function to deliver an accurate estimate of the entire underlying graph signal. We also quantify the error incurred by network Lasso in terms of two constants which reflect the connectivity of the sampled nodes.

  2. Flower development as an interplay between dynamical physical fields and genetic networks.

    Science.gov (United States)

    Barrio, Rafael Ángel; Hernández-Machado, Aurora; Varea, C; Romero-Arias, José Roberto; Alvarez-Buylla, Elena

    2010-10-27

    In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN) underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels.

  3. Cryogen free high magnetic field and low temperature sample environments for neutron scattering - latest developments

    International Nuclear Information System (INIS)

    Burgoyne, John

    2016-01-01

    Continuous progress has been made over many years now in the provision of low- and ultra-low temperature sample environments, together with new high-field superconducting magnets and increased convenience for both the user and the neutron research facility via new cooling technologies. Within Oxford Instrument's experience, this has been achieved in many cases through close collaboration with neutron scientists, and with the neutron facilities' sample environment leaders in particular. Superconducting magnet designs ranging from compact Small Angle (SANS) systems up to custom-engineered wide-angle scattering systems have been continuously developed. Recondensing, or 'zero boil-off' (ZBO), systems are well established for situations in which a high field magnet is not conducive to totally cryogen free cooling solutions, and offer a reliable route with the best trade-offs of maximum system capability versus running costs and user convenience. Fully cryogen free solutions for cryostats, dilution refrigerators, and medium-field magnets are readily available. Here we will present the latest technology developments in these options, describing the state-of-the art, the relative advantages of each, and the opportunities they offer to the neutron science community. (author)

  4. Dense graph limits under respondent-driven sampling

    Indian Academy of Sciences (India)

    Siva Athreya

    Types of network. Food. Political. Social. Linkedin. Protien. Professional. Source: IUPUI Network Sampling course. Page 3. Techniques to Analyse Networks. Network Characteristics: • Distribution: degree, clustering coefficient, hop-plot. ... Hypothesis Testing: H0: Graph is a linkedin network. H1: Graph is a facebook network ...

  5. ARCTOX: a pan-Arctic sampling network to track mercury contamination across Arctic marine food webs

    DEFF Research Database (Denmark)

    Fort, Jerome; Helgason, Halfdan; Amelineau, Francoise

    and is still a source of major environmental concerns. In that context, providing a large-scale and comprehensive understanding of the Arctic marine food-web contamination is essential to better apprehend impacts of anthropogenic activities and climate change on the exposure of Arctic species and humans to Hg....... In 2015, an international sampling network (ARCTOX) has been established, allowing the collection seabird samples all around the Arctic. Seabirds are indeed good indicators of Hg contamination of marine food webs at large spatial scale. Gathering researchers from 10 countries, ARCTOX allowed......Arctic marine ecosystems are threatened by new risks of Hg contamination under the combined effects of climate change and human activities. Rapid change of the cryosphere might for instance release large amounts of Hg trapped in sea-ice, permafrost and terrestrial glaciers over the last decades...

  6. A comparative study between nonlinear regression and artificial neural network approaches for modelling wild oat (Avena fatua) field emergence

    Science.gov (United States)

    Non-linear regression techniques are used widely to fit weed field emergence patterns to soil microclimatic indices using S-type functions. Artificial neural networks present interesting and alternative features for such modeling purposes. In this work, a univariate hydrothermal-time based Weibull m...

  7. Detection of pesticides residues in water samples from organic and conventional paddy fields of Ledang, Johor, Malaysia

    Science.gov (United States)

    Abdullah, Md Pauzi; Othman, Mohamed Rozali; Ishak, Anizan; Nabhan, Khitam Jaber

    2016-11-01

    Pesticides have been used extensively by the farmers in Malaysia during the last few decades. Sixteen water samples, collected from paddy fields both organic and conventional, from Ledang, Johor, were analyzed to determine the occurrence and distribution of organochlorine (OCPs) and organophosphorus (OPPs) pesticide residues. GC-ECD instrument was used to identify and determine the concentrations of these pesticide residues. Pesticide residues were detected in conventional fields in the range about 0.036-0.508 µg/L higher than detected in organic fields about 0.015-0.428 µg/L. However the level of concentration of pesticide residues in water sample from both paddy fields are in the exceed limit for human consumption, according to European Economic Commission (EEC) (Directive 98/83/EC) at 0.1 µg/L for any pesticide or 0.5 µg/L for total pesticides. The results that the organic plot is still contaminated with pesticides although pesticides were not use at all in plot possibly from historical used as well as from airborne contamination.

  8. A new centrality measure for identifying influential nodes in social networks

    Science.gov (United States)

    Rhouma, Delel; Ben Romdhane, Lotfi

    2018-04-01

    The identification of central nodes has been a key problem in the field of social network analysis. In fact, it is a measure that accounts the popularity or the visibility of an actor within a network. In order to capture this concept, various measures, either sample or more elaborate, has been developed. Nevertheless, many of "traditional" measures are not designed to be applicable to huge data. This paper sets out a new node centrality index suitable for large social network. It uses the amount of the neighbors of a node and connections between them to characterize a "pivot" node in the graph. We presented experimental results on real data sets which show the efficiency of our proposal.

  9. Mass transfer of H2O between petroleum and water: implications for oil field water sample quality

    International Nuclear Information System (INIS)

    McCartney, R.A.; Ostvold, T.

    2005-01-01

    Water mass transfer can occur between water and petroleum during changes in pressure and temperature. This process can result in the dilution or concentration of dissolved ions in the water phase of oil field petroleum-water samples. In this study, PVT simulations were undertaken for 4 petroleum-water systems covering a range of reservoir conditions (80-185 o C; 300-1000 bar) and a range of water-petroleum mixtures (volume ratios of 1:1000-300:1000) to quantify the extent of H 2 O mass transfer as a result of pressure and temperature changes. Conditions were selected to be relevant to different types of oil field water sample (i.e. surface, downhole and core samples). The main variables determining the extent of dilution and concentration were found to be: (a) reservoir pressure and temperature, (b) pressure and temperature of separation of water and petroleum, (c) petroleum composition, and (d) petroleum:water ratio (PWR). The results showed that significant dilution and concentration of water samples could occur, particularly at high PWR. It was not possible to establish simple guidelines for identifying good and poor quality samples due to the interplay of the above variables. Sample quality is best investigated using PVT software of the type used in this study. (author)

  10. Competing edge networks

    International Nuclear Information System (INIS)

    Parsons, Mark; Grindrod, Peter

    2012-01-01

    We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, subject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other's growth and encourage the other's demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails. -- Highlights: ► A model for edgewise-competing evolving network pairs is introduced. ► Defined competition equations yield to a mean field analysis. ► Multiple equilibrium states and different bifurcation types can occur. ► The system is sensitive to sparse initial conditions and near unstable equilibriums.

  11. Study of Low Temperature Baking Effect on Field Emission on Nb Samples Treated by BEP, EP, and BCP

    International Nuclear Information System (INIS)

    Wu, Andy; Jin, Song; Rimmer, Robert; Lu, Xiang Yang; Zhao, K.; MacIntyre, Laura; Ike, Robert

    2010-01-01

    Field emission is still one of the major obstacles facing Nb superconducting radio frequency (SRF) community for allowing Nb SRF cavities to reach routinely accelerating gradient of 35 MV/m that is required for the international linear collider. Nowadays, the well know low temperature baking at 120 C for 48 hours is a common procedure used in the SRF community to improve the high field Q slope. However, some cavity production data have showed that the low temperature baking may induce field emission for cavities treated by EP. On the other hand, an earlier study of field emission on Nb flat samples treated by BCP showed an opposite conclusion. In this presentation, the preliminary measurements of Nb flat samples treated by BEP, EP, and BCP via our unique home-made scanning field emission microscope before and after the low temperature baking are reported. Some correlations between surface smoothness and the number of the observed field emitters were found. The observed experimental results can be understood, at least partially, by a simple model that involves the change of the thickness of the pent-oxide layer on Nb surfaces.

  12. Critical Fluctuations in Spatial Complex Networks

    Science.gov (United States)

    Bradde, Serena; Caccioli, Fabio; Dall'Asta, Luca; Bianconi, Ginestra

    2010-05-01

    An anomalous mean-field solution is known to capture the nontrivial phase diagram of the Ising model in annealed complex networks. Nevertheless, the critical fluctuations in random complex networks remain mean field. Here we show that a breakdown of this scenario can be obtained when complex networks are embedded in geometrical spaces. Through the analysis of the Ising model on annealed spatial networks, we reveal, in particular, the spectral properties of networks responsible for critical fluctuations and we generalize the Ginsburg criterion to complex topologies.

  13. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimise the management of the Technical Network (TN), to facilitate understanding of the purpose of devices connected to the TN and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive e-mails from IT/CS asking them to add the corresponding information in the network database at "network-cern-ch". Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  14. Inferring general relations between network characteristics from specific network ensembles.

    Science.gov (United States)

    Cardanobile, Stefano; Pernice, Volker; Deger, Moritz; Rotter, Stefan

    2012-01-01

    Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their ability to generate networks with large structural variability. In particular, we consider the statistical constraints which the respective construction scheme imposes on the generated networks. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This makes it possible to infer global features from local ones using regression models trained on networks with high generalization power. Our results confirm and extend previous findings regarding the synchronization properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks in good approximation. Finally, we demonstrate on three different data sets (C. elegans neuronal network, R. prowazekii metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models.

  15. Parallel importance sampling in conditional linear Gaussian networks

    DEFF Research Database (Denmark)

    Salmerón, Antonio; Ramos-López, Darío; Borchani, Hanen

    2015-01-01

    In this paper we analyse the problem of probabilistic inference in CLG networks when evidence comes in streams. In such situations, fast and scalable algorithms, able to provide accurate responses in a short time are required. We consider the instantiation of variational inference and importance ...

  16. Interaction of Aquifer and River-Canal Network near Well Field.

    Science.gov (United States)

    Ghosh, Narayan C; Mishra, Govinda C; Sandhu, Cornelius S S; Grischek, Thomas; Singh, Vikrant V

    2015-01-01

    The article presents semi-analytical mathematical models to asses (1) enhancements of seepage from a canal and (2) induced flow from a partially penetrating river in an unconfined aquifer consequent to groundwater withdrawal in a well field in the vicinity of the river and canal. The nonlinear exponential relation between seepage from a canal reach and hydraulic head in the aquifer beneath the canal reach is used for quantifying seepage from the canal reach. Hantush's (1967) basic solution for water table rise due to recharge from a rectangular spreading basin in absence of pumping well is used for generating unit pulse response function coefficients for water table rise in the aquifer. Duhamel's convolution theory and method of superposition are applied to obtain water table position due to pumping and recharge from different canal reaches. Hunt's (1999) basic solution for river depletion due to constant pumping from a well in the vicinity of a partially penetrating river is used to generate unit pulse response function coefficients. Applying convolution technique and superposition, treating the recharge from canal reaches as recharge through conceptual injection wells, river depletion consequent to variable pumping and recharge is quantified. The integrated model is applied to a case study in Haridwar (India). The well field consists of 22 pumping wells located in the vicinity of a perennial river and a canal network. The river bank filtrate portion consequent to pumping is quantified. © 2014, National GroundWater Association.

  17. Imaging the Flow Networks from a Harmonic Pumping in a Karstic Field with an Inversion Algorithm

    Science.gov (United States)

    Fischer, P.; Lecoq, N.; Jardani, A.; Jourde, H.; Wang, X.; Chedeville, S.; Cardiff, M. A.

    2017-12-01

    Identifying flow paths within karstic fields remains a complex task because of the high dependency of the hydraulic responses to the relative locations between the observation boreholes and the karstic conduits and interconnected fractures that control the main flows of the hydrosystem. In this context, harmonic pumping is a new investigation tool that permits to inform on the flow paths connectivity between the boreholes. We have shown that the amplitude and phase offset values in the periodic responses of a hydrosystem to a harmonic pumping test characterize three different type of flow behavior between the measurement boreholes and the pumping borehole: a direct connectivity response (conduit flow), an indirect connectivity (conduit and short matrix flows), and an absence of connectivity (matrix). When the hydraulic responses to study are numerous and complex, the interpretation of the flow paths requires an inverse modeling. Therefore, we have recently developed a Cellular Automata-based Deterministic Inversion (CADI) approach that permits to infer the spatial distribution of field hydraulic conductivities in a structurally constrained model. This method distributes hydraulic conductivities along linear structures (i.e. karst conduits) and iteratively modifies the structural geometry of this conduits network to progressively match the observed responses to the modeled ones. As a result, this method produces a conductivity model that is composed of a discrete conduit network embedded in the background matrix, capable of producing the same flow behavior as the investigated hydrologic system. We applied the CADI approach in order to reproduce, in a model, the amplitude and phase offset values of a set of periodic responses generated from harmonic pumping tests conducted in different boreholes at the Terrieu karstic field site (Southern France). This association of oscillatory responses with the CADI method provides an interpretation of the flow paths within the

  18. On-the-field performance of quintuple-play long-reach OFDM-based WDM-PON optical access networks.

    Science.gov (United States)

    Llorente, Roberto; Morant, Maria; Pellicer, Eloy; Herman, Milan; Nagy, Zsolt; Alves, Tiago; Cartaxo, Adolfo; Herrera, Javier; Correcher, Jose; Quinlan, Terence; Walker, Stuart; Rodrigues, Cláudio; Cluzeaud, Pierre; Schmidt, Axel; Piesiewicz, Radoslaw; Sambaraju, Rakesh

    2014-03-24

    In this paper the on-the-field performance of a WDM-PON optical access providing quintuple-play services using orthogonal frequency division multiplexing (OFDM) modulation is evaluated in a real fiber-to-the-home (FTTH) network deployed by Towercom operator in Bratislava (Slovakia). A bundle of quintuple-play services comprising full-standard OFDM-based signals (LTE, WiMAX, UWB and DVB-T) and an ad-hoc OFDM-GbE signal is transmitted in coexistence per single user. Both downstream and upstream transmission performances are evaluated in different on-the-field long-reach optical link distance configurations. Four wavelength multi-user transmission of quintuple-play OFDM services is demonstrated exceeding 60.8 km reach in standard single mode fiber.

  19. Study of aerosol sample interaction with dc plasma in the presence of oscillating magnetic field

    International Nuclear Information System (INIS)

    Stoiljkovic, M.M.; Pavlovic, M.S.; Savovic, J.; Kuzmanovic, M.; Marinkovic, M.

    2005-01-01

    Oscillating magnetic field was used to study the efficiency of the aerosol sample introduction into the dc plasma. At atmospheric plasmas, the effect of magnetic field is reduced to Lorentz forces on the current carrying plasma, which produces motion of the plasma. The motion velocity of dc plasma caused by oscillating magnetic field was correlated to spectral emission enhancement of analytes introduced as aerosols. Emission enhancement is the consequence of the reduced barrier to introduction of analyte species and aerosol particles into the hot plasma region. Two hypotheses described in the literature for the origin of the barrier are considered: (i) barrier induced by temperature field is based upon the thermophoretic forces on the aerosol particles when their radius is comparable to the molecular free path in the surrounding gas and (ii) barrier induced by radial electric field, recently described, that originates from gradients of charged particles in radial direction. Correlation between ionization energy of the analyte atoms with experimental emission enhancement obtained by the use of oscillating magnetic field indicates that mechanism (ii) based upon the radial electric field is predominant. The ultimate emission enhancement and possible analytical advantage is discussed

  20. Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—applied to GPR crosshole traveltime inversion

    Science.gov (United States)

    Hansen, T. M.; Cordua, K. S.

    2017-12-01

    Probabilistically formulated inverse problems can be solved using Monte Carlo-based sampling methods. In principle, both advanced prior information, based on for example, complex geostatistical models and non-linear forward models can be considered using such methods. However, Monte Carlo methods may be associated with huge computational costs that, in practice, limit their application. This is not least due to the computational requirements related to solving the forward problem, where the physical forward response of some earth model has to be evaluated. Here, it is suggested to replace a numerical complex evaluation of the forward problem, with a trained neural network that can be evaluated very fast. This will introduce a modeling error that is quantified probabilistically such that it can be accounted for during inversion. This allows a very fast and efficient Monte Carlo sampling of the solution to an inverse problem. We demonstrate the methodology for first arrival traveltime inversion of crosshole ground penetrating radar data. An accurate forward model, based on 2-D full-waveform modeling followed by automatic traveltime picking, is replaced by a fast neural network. This provides a sampling algorithm three orders of magnitude faster than using the accurate and computationally expensive forward model, and also considerably faster and more accurate (i.e. with better resolution), than commonly used approximate forward models. The methodology has the potential to dramatically change the complexity of non-linear and non-Gaussian inverse problems that have to be solved using Monte Carlo sampling techniques.

  1. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  2. Transport properties of field effect transistors with randomly networked single walled carbon nanotubes grown by plasma enhanced chemical vapour deposition

    International Nuclear Information System (INIS)

    Kim, Un Jeong; Park, Wanjun

    2009-01-01

    The transport properties of randomly networked single walled carbon nanotube (SWNT) transistors with different channel lengths of L c = 2-10 μm were investigated. Randomly networked SWNTs were directly grown for the two different densities of ρ ∼ 25 μm -2 and ρ ∼ 50 μm -2 by water plasma enhanced chemical vapour deposition. The field effect transport is governed mainly by formation of the current paths that is related to the nanotube density. On the other hand, the off-state conductivity deviates from linear dependence for both nanotube density and channel length. The field effect mobility of holes is estimated as 4-13 cm 2 V -1 s -1 for the nanotube transistors based on the simple MOS theory. The mobility is increased for the higher density without meaningful dependence on the channel lengths.

  3. Modulation of Cortical-subcortical Networks in Parkinson’s Disease by Applied Field Effects

    Directory of Open Access Journals (Sweden)

    Christopher William Hess

    2013-09-01

    Full Text Available Studies suggest that endogenous field effects may play a role in neuronal oscillations and communication. Non-invasive transcranial electrical stimulation with low-intensity currents can also have direct effects on the underlying cortex as well as distant network effects. While Parkinson's disease (PD is amenable to invasive neuromodulation in the basal ganglia by deep brain stimulation, techniques of non-invasive neuromodulation like transcranial direct current stimulation (tDCS and transcranial alternating current stimulation (tACS are being investigated as possible therapies. tDCS and tACS have the potential to influence the abnormal cortical-subcortical network activity that occurs in PD through sub-threshold changes in cortical excitability or through entrainment or disruption of ongoing rhythmic cortical activity. This may allow for the targeting of specific features of the disease involving abnormal oscillatory activity, as well as the enhancement of potential cortical compensation for basal ganglia dysfunction and modulation of cortical plasticity in neurorehabilitation. However, little is currently known about how cortical stimulation will affect subcortical structures, the size of any effect, and the factors of stimulation that will influence these effects.

  4. Field assessment of bacterial communities and total trihalomethanes: Implications for drinking water networks.

    Science.gov (United States)

    Montoya-Pachongo, Carolina; Douterelo, Isabel; Noakes, Catherine; Camargo-Valero, Miller Alonso; Sleigh, Andrew; Escobar-Rivera, Juan-Carlos; Torres-Lozada, Patricia

    2018-03-01

    Operation and maintenance (O&M) of drinking water distribution networks (DWDNs) in tropical countries simultaneously face the control of acute and chronic risks due to the presence of microorganisms and disinfection by-products, respectively. In this study, results from a detailed field characterization of microbiological, chemical and infrastructural parameters of a tropical-climate DWDN are presented. Water physicochemical parameters and the characteristics of the network were assessed to evaluate the relationship between abiotic and microbiological factors and their association with the presence of total trihalomethanes (TTHMs). Illumina sequencing of the bacterial 16s rRNA gene revealed significant differences in the composition of biofilm and planktonic communities. The highly diverse biofilm communities showed the presence of methylotrophic bacteria, which suggest the presence of methyl radicals such as THMs within this habitat. Microbiological parameters correlated with water age, pH, temperature and free residual chlorine. The results from this study are necessary to increase the awareness of O&M practices in DWDNs required to reduce biofilm formation and maintain appropriate microbiological and chemical water quality, in relation to biofilm detachment and DBP formation. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Finnish remote environmental monitoring field demonstration

    International Nuclear Information System (INIS)

    Toivonen, H.; Leppaenen, A.; Ylaetalo, S.; Lehtinen, J.; Hokkinen, J.; Tarvainen, M.; Crawford, T.; Glidewell, D.; Smartt, H.; Torres, J.

    1997-10-01

    Radiation and Nuclear Safety Authority (STUK), Helsinki, Finland and Sandia National Laboratories (SNL), working under the Finnish Support Program to IAEA Safeguards and the United States Department of Energy (DOE) funded International Remote Monitoring Program (Task FIN E 935), have undertaken a joint effort to demonstrate the use of remote monitoring for environmental air sampling and safeguards applications. The results of the task will be used by the IAEA to identify the feasibility, cost-effectiveness, reliability, advantages, and problems associated with remote environmental monitoring. An essential prerequisite for a reliable remote air sampling system is the protection of samples against tampering. Means must be developed to guarantee that the sampling itself has been performed as designed and the original samples are not substituted with samples produced with other equipment at another site. One such method is to label the samples with an unequivocal tag. In addition, the inspection personnel must have the capability to remotely monitor and access the automated environmental air sampling system through the use of various sensors and video imagery equipment. A unique aspect to this project is the network integration of remote monitoring equipment with a STUK radiation monitoring system. This integration will allow inspectors to remotely view air sampler radiation data and sensor/image data through separate software applications on the same review station. A sensor network and video system will be integrated with the SNL developed Modular Integrated Monitoring System (MIMS) to provide a comprehensive remote monitoring approach for safeguards purposes. This field trial system is being implemented through a multiphase approach for use by STUK, SNL, and for possible future use by the IAEA

  6. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimize the management of the Technical Network (TN), to ease the understanding and purpose of devices connected to the TN, and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive email notifications from IT/CS asking them to add the corresponding information in the network database. Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  7. Replicability and generalizability of PTSD networks

    DEFF Research Database (Denmark)

    Eiko I., Fried; Eidhof, Marloes B.; Palic, Sabina

    2018-01-01

    The growing literature conceptualizing mental disorders like Posttraumatic Stress Disorder (PTSD) as networks of interacting symptoms faces three key challenges. Prior studies predominantly used (a) small samples with low power for precise estimation, (b) non-clinical samples, and (c) single...... samples. This renders network structures in clinical data, and the extent to which networks replicate across datasets, unknown. To overcome these limitations, the present cross-cultural multisite study estimated regularized partial correlation networks of 16 PTSD symptoms across four datasets...... of traumatized patients receiving treatment for PTSD (total N=2,782). Despite differences in culture, trauma-type and severity of the samples, considerable similarities emerged, with moderate to high correlations between symptom profiles (0.43-0.82), network structures (0.62-0.74), and centrality estimates (0...

  8. Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

    Science.gov (United States)

    Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

    2012-10-01

    We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

  9. Using Web2.0 social network technology for sampling framework identification and respondent recruitment: experiences with a small-scale experiment

    NARCIS (Netherlands)

    Grigolon, A.B.; Kemperman, A.D.A.M.; Timmermans, H.J.P.

    2011-01-01

    In this paper, we report the results of a small–scale experiment to explore the potential of using social network technology for respondent recruitment. Of particular interest are the following questions (i) can social media be used for the identification of sampling frames, (ii) what response rates

  10. Water sampling at the Berge Helene FPSO at Chinguetti field in Mauritania using passive samplers

    NARCIS (Netherlands)

    Korytar, P.; Galien, van der W.

    2007-01-01

    Three rounds of water sampling were performed at the Berge Helene FPSO at the Chinguetti field in Mauritania using passive samplers attached to the FPSO to determine the levels of contamination that could potentially accumulate in organisms. Two rounds were carried out prior to the commencement of

  11. Advanced network programming principles and techniques : network application programming with Java

    CERN Document Server

    Ciubotaru, Bogdan

    2013-01-01

    Answering the need for an accessible overview of the field, this text/reference presents a manageable introduction to both the theoretical and practical aspects of computer networks and network programming. Clearly structured and easy to follow, the book describes cutting-edge developments in network architectures, communication protocols, and programming techniques and models, supported by code examples for hands-on practice with creating network-based applications. Features: presents detailed coverage of network architectures; gently introduces the reader to the basic ideas underpinning comp

  12. Reverse sample genome probing, a new technique for identification of bacteria in environmental samples by DNA hybridization, and its application to the identification of sulfate-reducing bacteria in oil field samples

    International Nuclear Information System (INIS)

    Voordouw, G.; Voordouw, J.K.; Karkhoff-Schweizer, R.R.; Fedorak, P.M.; Westlake, D.W.S.

    1991-01-01

    A novel method for identification of bacteria in environmental samples by DNA hybridization is presented. It is based on the fact that, even within a genus, the genomes of different bacteria may have little overall sequence homology. This allows the use of the labeled genomic DNA of a given bacterium (referred to as a standard) to probe for its presence and that of bacteria with highly homologous genomes in total DNA obtained from an environmental sample. Alternatively, total DNA extracted from the sample can be labeled and used to probe filters on which denatured chromosomal DNA from relevant bacterial standards has been spotted. The latter technique is referred to as reverse sample genome probing, since it is the reverse of the usual practice of deriving probes from reference bacteria for analyzing a DNA sample. Reverse sample genome probing allows identification of bacteria in a sample in a single step once a master filter with suitable standards has been developed. Application of reverse sample genome probing to the identification of sulfate-reducing bacteria in 31 samples obtained primarily from oil fields in the province of Alberta has indicated that there are at least 20 genotypically different sulfate-reducing bacteria in these samples

  13. EXTERNALITIES IN EXCHANGE NETWORKS AN ADAPTATION OF EXISTING THEORIES OF EXCHANGE NETWORKS

    NARCIS (Netherlands)

    Dijkstra, Jacob

    2009-01-01

    The present paper extends the focus of network exchange research to externalities in exchange networks. Externalities of exchange are defined as direct effects on an actor's utility, of an exchange in which this actor is not involved. Existing theories in the field of network exchange do not inform

  14. On/off ratio enhancement in single-walled carbon nanotube field-effect transistor by controlling network density via sonication

    Science.gov (United States)

    Jang, Ho-Kyun; Choi, Jun Hee; Kim, Do-Hyun; Kim, Gyu Tae

    2018-06-01

    Single-walled carbon nanotube (SWCNT) is generally used as a networked structure in the fabrication of a field-effect transistor (FET) since it is known that one-third of SWCNT is electrically metallic and the remains are semiconducting. In this case, the presence of metallic paths by metallic SWCNT (m-SWCNT) becomes a significant technical barrier which hinders the networks from achieving a semiconducting behavior, resulting in a low on/off ratio. Here, we report on an easy method of controlling the on/off ratio of a FET where semiconducting SWCNT (s-SWCNT) and m-SWCNT constitute networks between source and drain electrodes. A FET with SWCNT networks was simply sonicated under water to control the on/off ratio and network density. As a result, the FET having an almost metallic behavior due to the metallic paths by m-SWCNT exhibited a p-type semiconducting behavior. The on/off ratio ranged from 1 to 9.0 × 104 along sonication time. In addition, theoretical calculations based on Monte-Carlo method and circuit simulation were performed to understand and explain the phenomenon of a change in the on/off ratio and network density by sonication. On the basis of experimental and theoretical results, we found that metallic paths contributed to a high off-state current which leads to a low on/off ratio and that sonication formed sparse SWCNT networks where metallic paths of m-SWCNT were removed, resulting in a high on/off ratio. This method can open a chance to save the device which has been considered as a failed one due to a metallic behavior by a high network density leading to a low on/off ratio.

  15. Urban exposure to ELF magnetic field due to high-, medium- and low-voltage electricity supply networks

    International Nuclear Information System (INIS)

    Bottura, V.; Cappio Borlino, M.; Carta, N.; Cerise, L.; Imperial, E.

    2009-01-01

    The regional environment protection agency (ARPA) of the Aosta Valley region in north Italy performed a survey of magnetic field triggered by the power supply network in high, medium and low voltages on the entire area of Aosta town. The electrical distribution system for houses was not however taken into account. The aim of the survey was to evaluate the global population exposure and not simply the assessment of the legal exposure limit compliance. (authors)

  16. Field and sample history dependence of the compensation temperature in Sm0.97Gd0.03Al2

    International Nuclear Information System (INIS)

    Vaidya, U.V.; Rakhecha, V.C.; Sumithra, S.; Ramakrishnan, S.; Grover, A.K.

    2007-01-01

    We present magnetization data on three polycrystalline specimens of Sm 0.97 Gd 0.03 Al 2 : (1) as-cast (grainy texture), (2) powder, and (3) re-melted fast-quenched (plate). The data are presented for nominally zero- (ZFC) and high-field-cooling (HFC) histories. A zero cross-over in magnetization curve at some temperature T=T 0 was seen in ZFC data on grainy and powder samples, but not in the plate sample. At fields surpassing magnetocrystalline anisotropy, a 4f magnetic moment flip was still evidenced by HFC data in all samples at a compensation temperature T comp , which must necessarily be treated as distinct from T 0 (T 0 may not even exist). Proper understanding of T comp should take account of thermomagnetic history effects

  17. Flower development as an interplay between dynamical physical fields and genetic networks.

    Directory of Open Access Journals (Sweden)

    Rafael Ángel Barrio

    Full Text Available In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels.

  18. Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

    Directory of Open Access Journals (Sweden)

    Mohammad S. Islam

    2017-01-01

    Full Text Available Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs for robust movement decoding of Parkinson’s disease (PD and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.

  19. Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

    Science.gov (United States)

    Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

    2017-04-01

    attributes. When working within the same spatial resolution for covariates, however only modifying the desired number of sampling points produced, the change of point location portrayed a strong geospatial relationship when using continuous data. Access to agricultural fields and adjacent land uses is often "pinned" as the greatest deterrent to performing soil sampling for both soil survey and soil attribute validation work. The lack of access can be a result of poor road access and/or difficult geographical conditions to navigate for field work individuals. This seems a simple yet continuous issue to overcome for the scientific community and in particular, soils professionals. The ability to assist with the ease of access to sampling points will be in the future a contribution to the Latin Hypercube Sampling (LHS) approach. By removing all locations in the initial instance from the DEM, the LHS model can be restricted to locations only with access from the adjacent road or trail. To further the approach, a road network geospatial dataset can be included within spatial Geographic Information Systems (GIS) applications to access already produced points using a shortest-distance network method.

  20. [Weighted gene co-expression network analysis in biomedicine research].

    Science.gov (United States)

    Liu, Wei; Li, Li; Ye, Hua; Tu, Wei

    2017-11-25

    High-throughput biological technologies are now widely applied in biology and medicine, allowing scientists to monitor thousands of parameters simultaneously in a specific sample. However, it is still an enormous challenge to mine useful information from high-throughput data. The emergence of network biology provides deeper insights into complex bio-system and reveals the modularity in tissue/cellular networks. Correlation networks are increasingly used in bioinformatics applications. Weighted gene co-expression network analysis (WGCNA) tool can detect clusters of highly correlated genes. Therefore, we systematically reviewed the application of WGCNA in the study of disease diagnosis, pathogenesis and other related fields. First, we introduced principle, workflow, advantages and disadvantages of WGCNA. Second, we presented the application of WGCNA in disease, physiology, drug, evolution and genome annotation. Then, we indicated the application of WGCNA in newly developed high-throughput methods. We hope this review will help to promote the application of WGCNA in biomedicine research.

  1. Temporal networks

    Science.gov (United States)

    Holme, Petter; Saramäki, Jari

    2012-10-01

    A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via e-mail, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names-temporal graphs, evolving graphs, time-varying graphs, time-aggregated graphs, time-stamped graphs, dynamic networks, dynamic graphs, dynamical graphs, and so on. This review covers different fields where temporal graphs are considered

  2. Reliable Communication in Wireless Meshed Networks using Network Coding

    DEFF Research Database (Denmark)

    Pahlevani, Peyman; Paramanathan, Achuthan; Hundebøll, Martin

    2012-01-01

    The advantages of network coding have been extensively studied in the field of wireless networks. Integrating network coding with existing IEEE 802.11 MAC layer is a challenging problem. The IEEE 802.11 MAC does not provide any reliability mechanisms for overheard packets. This paper addresses...... this problem and suggests different mechanisms to support reliability as part of the MAC protocol. Analytical expressions to this problem are given to qualify the performance of the modified network coding. These expressions are confirmed by numerical result. While the suggested reliability mechanisms...

  3. Solution-Processed Donor-Acceptor Polymer Nanowire Network Semiconductors For High-Performance Field-Effect Transistors

    Science.gov (United States)

    Lei, Yanlian; Deng, Ping; Li, Jun; Lin, Ming; Zhu, Furong; Ng, Tsz-Wai; Lee, Chun-Sing; Ong, Beng S.

    2016-01-01

    Organic field-effect transistors (OFETs) represent a low-cost transistor technology for creating next-generation large-area, flexible and ultra-low-cost electronics. Conjugated electron donor-acceptor (D-A) polymers have surfaced as ideal channel semiconductor candidates for OFETs. However, high-molecular weight (MW) D-A polymer semiconductors, which offer high field-effect mobility, generally suffer from processing complications due to limited solubility. Conversely, the readily soluble, low-MW D-A polymers give low mobility. We report herein a facile solution process which transformed a lower-MW, low-mobility diketopyrrolopyrrole-dithienylthieno[3,2-b]thiophene (I) into a high crystalline order and high-mobility semiconductor for OFETs applications. The process involved solution fabrication of a channel semiconductor film from a lower-MW (I) and polystyrene blends. With the help of cooperative shifting motion of polystyrene chain segments, (I) readily self-assembled and crystallized out in the polystyrene matrix as an interpenetrating, nanowire semiconductor network, providing significantly enhanced mobility (over 8 cm2V−1s−1), on/off ratio (107), and other desirable field-effect properties that meet impactful OFET application requirements. PMID:27091315

  4. Characterizing dust aerosols in the atmospheric boundary layer over the deserts in Northwest China: monitoring network and field observation

    Science.gov (United States)

    He, Q.; Matimin, A.; Yang, X.

    2016-12-01

    TheTaklimakan, Gurbantunggut and BadainJaran Deserts with the total area of 43.8×104 km2 in Northwest China are the major dust emission sources in Central Asia. Understanding Central Asian dust emissions and the interaction with the atmospheric boundary layer has an important implication for regional and global climate and environment changes. In order to explore these scientific issues, a monitoring network of 63 sites was established over the vast deserts (Taklimakan Desert, Gurbantunggut Desert and Badain Jaran Desert) in Northwest China for the comprehensive measurements of dust aerosol emission, transport and deposition as well as the atmospheric boundary layer including the meteorological parameters of boundary layer, surface radiation, surface heat fluxes, soil parameters, dust aerosol properties, water vapor profiles, and dust emission. Based on the monitoring network, the field experiments have been conducted to characterize dust aerosols and the atmospheric boundary layer over the deserts. The experiment observation indicated that depth of the convective boundary layer can reach 5000m on summer afternoons. In desert regions, the diurnal mean net radiation was effected significantly by dust weather, and sensible heat was much greater than latent heat accounting about 40-50% in the heat balance of desert. The surface soil and dust size distributions of Northwest China Deserts were obtained through widely collecting samples, results showed that the dominant dust particle size was PM100within 80m height, on average accounting for 60-80% of the samples, with 0.9-2.5% for PM0-2.5, 3.5-7.0% for PM0-10 and 5.0-14.0% for PM0-20. The time dust emission of Taklimakan Desert, Gurbantunggut Desert and Badain Jaran Desert accounted for 0.48%, 7.3%×10-5and 1.9% of the total time within a year, and the threshold friction velocity for dust emission were 0.22-1.06m/s, 0.29-1.5m/s and 0.21-0.59m/s, respectively.

  5. Artificial neural networks in NDT

    International Nuclear Information System (INIS)

    Abdul Aziz Mohamed

    2001-01-01

    Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

  6. Interconnected networks

    CERN Document Server

    2016-01-01

    This volume provides an introduction to and overview of the emerging field of interconnected networks which include multi layer or multiplex networks, as well as networks of networks. Such networks present structural and dynamical features quite different from those observed in isolated networks. The presence of links between different networks or layers of a network typically alters the way such interconnected networks behave – understanding the role of interconnecting links is therefore a crucial step towards a more accurate description of real-world systems. While examples of such dissimilar properties are becoming more abundant – for example regarding diffusion, robustness and competition – the root of such differences remains to be elucidated. Each chapter in this topical collection is self-contained and can be read on its own, thus making it also suitable as reference for experienced researchers wishing to focus on a particular topic.

  7. Networks as systems.

    Science.gov (United States)

    Best, Allan; Berland, Alex; Greenhalgh, Trisha; Bourgeault, Ivy L; Saul, Jessie E; Barker, Brittany

    2018-03-19

    Purpose The purpose of this paper is to present a case study of the World Health Organization's Global Healthcare Workforce Alliance (GHWA). Based on a commissioned evaluation of GHWA, it applies network theory and key concepts from systems thinking to explore network emergence, effectiveness, and evolution to over a ten-year period. The research was designed to provide high-level strategic guidance for further evolution of global governance in human resources for health (HRH). Design/methodology/approach Methods included a review of published literature on HRH governance and current practice in the field and an in-depth case study whose main data sources were relevant GHWA background documents and key informant interviews with GHWA leaders, staff, and stakeholders. Sampling was purposive and at a senior level, focusing on board members, executive directors, funders, and academics. Data were analyzed thematically with reference to systems theory and Shiffman's theory of network development. Findings Five key lessons emerged: effective management and leadership are critical; networks need to balance "tight" and "loose" approaches to their structure and processes; an active communication strategy is key to create and maintain support; the goals, priorities, and membership must be carefully focused; and the network needs to support shared measurement of progress on agreed-upon goals. Shiffman's middle-range network theory is a useful tool when guided by the principles of complex systems that illuminate dynamic situations and shifting interests as global alliances evolve. Research limitations/implications This study was implemented at the end of the ten-year funding cycle. A more continuous evaluation throughout the term would have provided richer understanding of issues. Experience and perspectives at the country level were not assessed. Practical implications Design and management of large, complex networks requires ongoing attention to key issues like leadership

  8. Domain wall networks on solitons

    International Nuclear Information System (INIS)

    Sutcliffe, Paul

    2003-01-01

    Domain wall networks on the surface of a soliton are studied in a simple theory. It consists of two complex scalar fields, in 3+1 dimensions, with a global U(1)xZ n symmetry, where n>2. Solutions are computed numerically in which one of the fields forms a Q ball and the other field forms a network of domain walls localized on the surface of the Q ball. Examples are presented in which the domain walls lie along the edges of a spherical polyhedron, forming junctions at its vertices. It is explained why only a small restricted class of polyhedra can arise as domain wall networks

  9. Optimization of potential field method parameters through networks for swarm cooperative manipulation tasks

    Directory of Open Access Journals (Sweden)

    Rocco Furferi

    2016-10-01

    Full Text Available An interesting current research field related to autonomous robots is mobile manipulation performed by cooperating robots (in terrestrial, aerial and underwater environments. Focusing on the underwater scenario, cooperative manipulation of Intervention-Autonomous Underwater Vehicles (I-AUVs is a complex and difficult application compared with the terrestrial or aerial ones because of many technical issues, such as underwater localization and limited communication. A decentralized approach for cooperative mobile manipulation of I-AUVs based on Artificial Neural Networks (ANNs is proposed in this article. This strategy exploits the potential field method; a multi-layer control structure is developed to manage the coordination of the swarm, the guidance and navigation of I-AUVs and the manipulation task. In the article, this new strategy has been implemented in the simulation environment, simulating the transportation of an object. This object is moved along a desired trajectory in an unknown environment and it is transported by four underwater mobile robots, each one provided with a seven-degrees-of-freedom robotic arm. The simulation results are optimized thanks to the ANNs used for the potentials tuning.

  10. Interactive Editing of GigaSample Terrain Fields

    KAUST Repository

    Treib, Marc

    2012-05-01

    Previous terrain rendering approaches have addressed the aspect of data compression and fast decoding for rendering, but applications where the terrain is repeatedly modified and needs to be buffered on disk have not been considered so far. Such applications require both decoding and encoding to be faster than disk transfer. We present a novel approach for editing gigasample terrain fields at interactive rates and high quality. To achieve high decoding and encoding throughput, we employ a compression scheme for height and pixel maps based on a sparse wavelet representation. On recent GPUs it can encode and decode up to 270 and 730 MPix/s of color data, respectively, at compression rates and quality superior to JPEG, and it achieves more than twice these rates for lossless height field compression. The construction and rendering of a height field triangulation is avoided by using GPU ray-casting directly on the regular grid underlying the compression scheme. We show the efficiency of our method for interactive editing and continuous level-of-detail rendering of terrain fields comprised of several hundreds of gigasamples. © 2012 The Author(s).

  11. Using Respondent Driven Sampling to Identify Malaria Risks and Occupational Networks among Migrant Workers in Ranong, Thailand.

    Directory of Open Access Journals (Sweden)

    Piyaporn Wangroongsarb

    Full Text Available Ranong Province in southern Thailand is one of the primary entry points for migrants entering Thailand from Myanmar, and borders Kawthaung Township in Myanmar where artemisinin resistance in malaria parasites has been detected. Areas of high population movement could increase the risk of spread of artemisinin resistance in this region and beyond.A respondent-driven sampling (RDS methodology was used to compare migrant populations coming from Myanmar in urban (Site 1 vs. rural (Site 2 settings in Ranong, Thailand. The RDS methodology collected information on knowledge, attitudes, and practices for malaria, travel and occupational histories, as well as social network size and structure. Individuals enrolled were screened for malaria by microscopy, Real Time-PCR, and serology.A total of 619 participants were recruited in Ranong City and 623 participants in Kraburi, a rural sub-district. By PCR, a total of 14 (1.1% samples were positive (2 P. falciparum in Site 1; 10 P. vivax, 1 Pf, and 1 P. malariae in Site 2. PCR analysis demonstrated an overall weighted prevalence of 0.5% (95% CI, 0-1.3% in the urban site and 1.0% (95% CI, 0.5-1.7% in the rural site for all parasite species. PCR positivity did not correlate with serological positivity; however, as expected there was a strong association between antibody prevalence and both age and exposure. Access to long-lasting insecticidal treated nets remains low despite relatively high reported traditional net use among these populations.The low malaria prevalence, relatively smaller networks among migrants in rural settings, and limited frequency of travel to and from other areas of malaria transmission in Myanmar, suggest that the risk for the spread of artemisinin resistance from this area may be limited in these networks currently but may have implications for regional malaria elimination efforts.

  12. Support vector regression to predict porosity and permeability: Effect of sample size

    Science.gov (United States)

    Al-Anazi, A. F.; Gates, I. D.

    2012-02-01

    Porosity and permeability are key petrophysical parameters obtained from laboratory core analysis. Cores, obtained from drilled wells, are often few in number for most oil and gas fields. Porosity and permeability correlations based on conventional techniques such as linear regression or neural networks trained with core and geophysical logs suffer poor generalization to wells with only geophysical logs. The generalization problem of correlation models often becomes pronounced when the training sample size is small. This is attributed to the underlying assumption that conventional techniques employing the empirical risk minimization (ERM) inductive principle converge asymptotically to the true risk values as the number of samples increases. In small sample size estimation problems, the available training samples must span the complexity of the parameter space so that the model is able both to match the available training samples reasonably well and to generalize to new data. This is achieved using the structural risk minimization (SRM) inductive principle by matching the capability of the model to the available training data. One method that uses SRM is support vector regression (SVR) network. In this research, the capability of SVR to predict porosity and permeability in a heterogeneous sandstone reservoir under the effect of small sample size is evaluated. Particularly, the impact of Vapnik's ɛ-insensitivity loss function and least-modulus loss function on generalization performance was empirically investigated. The results are compared to the multilayer perception (MLP) neural network, a widely used regression method, which operates under the ERM principle. The mean square error and correlation coefficients were used to measure the quality of predictions. The results demonstrate that SVR yields consistently better predictions of the porosity and permeability with small sample size than the MLP method. Also, the performance of SVR depends on both kernel function

  13. Field Sampling Plan for Closure of the Central Facilities Area Sewage Treatment Plant Lagoon 3 and Land Application Area

    International Nuclear Information System (INIS)

    Lewis, Michael George

    2016-01-01

    This field sampling plan describes sampling of the soil/liner of Lagoon 3 at the Central Facilities Area Sewage Treatment Plant. The lagoon is to be closed, and samples obtained from the soil/liner will provide information to determine if Lagoon 3 and the land application area can be closed in a manner that renders it safe to human health and the environment. Samples collected under this field sampling plan will be compared to Idaho National Laboratory background soil concentrations. If the concentrations of constituents of concern exceed the background level, they will be compared to Comprehensive Environmental Response, Compensation, and Liability Act preliminary remediation goals and Resource Conservation and Recovery Act levels. If the concentrations of constituents of concern are lower than the background levels, Resource Conservation and Recovery Act levels, or the preliminary remediation goals, then Lagoon 3 and the land application area will be closed. If the Resource Conservation and Recovery Act levels and/or the Comprehensive Environmental Response, Compensation, and Liability Act preliminary remediation goals are exceeded, additional sampling and action may be required.

  14. Field Sampling Plan for Closure of the Central Facilities Area Sewage Treatment Plant Lagoon 3 and Land Application Area

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, Michael George [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-10-01

    This field sampling plan describes sampling of the soil/liner of Lagoon 3 at the Central Facilities Area Sewage Treatment Plant. The lagoon is to be closed, and samples obtained from the soil/liner will provide information to determine if Lagoon 3 and the land application area can be closed in a manner that renders it safe to human health and the environment. Samples collected under this field sampling plan will be compared to Idaho National Laboratory background soil concentrations. If the concentrations of constituents of concern exceed the background level, they will be compared to Comprehensive Environmental Response, Compensation, and Liability Act preliminary remediation goals and Resource Conservation and Recovery Act levels. If the concentrations of constituents of concern are lower than the background levels, Resource Conservation and Recovery Act levels, or the preliminary remediation goals, then Lagoon 3 and the land application area will be closed. If the Resource Conservation and Recovery Act levels and/or the Comprehensive Environmental Response, Compensation, and Liability Act preliminary remediation goals are exceeded, additional sampling and action may be required.

  15. Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data

    Science.gov (United States)

    Kennedy, Jeffrey R.; Ferre, Ty P.A.

    2015-01-01

    The relative gravimeter is the primary terrestrial instrument for measuring spatially and temporally varying gravitational fields. The background noise of the instrument—that is, non-linear drift and random tares—typically requires some form of least-squares network adjustment to integrate data collected during a campaign that may take several days to weeks. Here, we present an approach to remove the change in the observed relative-gravity differences caused by hydrologic or other transient processes during a single campaign, so that the adjusted gravity values can be referenced to a single epoch. The conceptual approach is an example of coupled hydrogeophysical inversion, by which a hydrologic model is used to inform and constrain the geophysical forward model. The hydrologic model simulates the spatial variation of the rate of change of gravity as either a linear function of distance from an infiltration source, or using a 3-D numerical groundwater model. The linear function can be included in and solved for as part of the network adjustment. Alternatively, the groundwater model is used to predict the change of gravity at each station through time, from which the accumulated gravity change is calculated and removed from the data prior to the network adjustment. Data from a field experiment conducted at an artificial-recharge facility are used to verify our approach. Maximum gravity change due to hydrology (observed using a superconducting gravimeter) during the relative-gravity field campaigns was up to 2.6 μGal d−1, each campaign was between 4 and 6 d and one month elapsed between campaigns. The maximum absolute difference in the estimated gravity change between two campaigns, two months apart, using the standard network adjustment method and the new approach, was 5.5 μGal. The maximum gravity change between the same two campaigns was 148 μGal, and spatial variation in gravity change revealed zones of preferential infiltration and areas of relatively

  16. Bridging scale gaps between regional maps of forest aboveground biomass and field sampling plots using TanDEM-X data

    Science.gov (United States)

    Ni, W.; Zhang, Z.; Sun, G.

    2017-12-01

    Several large-scale maps of forest AGB have been released [1] [2] [3]. However, these existing global or regional datasets were only approximations based on combining land cover type and representative values instead of measurements of actual forest aboveground biomass or forest heights [4]. Rodríguez-Veiga et al[5] reported obvious discrepancies of existing forest biomass stock maps with in-situ observations in Mexico. One of the biggest challenges to the credibility of these maps comes from the scale gaps between the size of field sampling plots used to develop(or validate) estimation models and the pixel size of these maps and the availability of field sampling plots with sufficient size for the verification of these products [6]. It is time-consuming and labor-intensive to collect sufficient number of field sampling data over the plot size of the same as resolutions of regional maps. The smaller field sampling plots cannot fully represent the spatial heterogeneity of forest stands as shown in Figure 1. Forest AGB is directly determined by forest heights, diameter at breast height (DBH) of each tree, forest density and tree species. What measured in the field sampling are the geometrical characteristics of forest stands including the DBH, tree heights and forest densities. The LiDAR data is considered as the best dataset for the estimation of forest AGB. The main reason is that LiDAR can directly capture geometrical features of forest stands by its range detection capabilities.The remotely sensed dataset, which is capable of direct measurements of forest spatial structures, may serve as a ladder to bridge the scale gaps between the pixel size of regional maps of forest AGB and field sampling plots. Several researches report that TanDEM-X data can be used to characterize the forest spatial structures [7, 8]. In this study, the forest AGB map of northeast China were produced using ALOS/PALSAR data taking TanDEM-X data as a bridges. The TanDEM-X InSAR data used in

  17. Computer-communication networks

    CERN Document Server

    Meditch, James S

    1983-01-01

    Computer- Communication Networks presents a collection of articles the focus of which is on the field of modeling, analysis, design, and performance optimization. It discusses the problem of modeling the performance of local area networks under file transfer. It addresses the design of multi-hop, mobile-user radio networks. Some of the topics covered in the book are the distributed packet switching queuing network design, some investigations on communication switching techniques in computer networks and the minimum hop flow assignment and routing subject to an average message delay constraint

  18. Neural network control of focal position during time-lapse microscopy of cells.

    Science.gov (United States)

    Wei, Ling; Roberts, Elijah

    2018-05-09

    Live-cell microscopy is quickly becoming an indispensable technique for studying the dynamics of cellular processes. Maintaining the specimen in focus during image acquisition is crucial for high-throughput applications, especially for long experiments or when a large sample is being continuously scanned. Automated focus control methods are often expensive, imperfect, or ill-adapted to a specific application and are a bottleneck for widespread adoption of high-throughput, live-cell imaging. Here, we demonstrate a neural network approach for automatically maintaining focus during bright-field microscopy. Z-stacks of yeast cells growing in a microfluidic device were collected and used to train a convolutional neural network to classify images according to their z-position. We studied the effect on prediction accuracy of the various hyperparameters of the neural network, including downsampling, batch size, and z-bin resolution. The network was able to predict the z-position of an image with ±1 μm accuracy, outperforming human annotators. Finally, we used our neural network to control microscope focus in real-time during a 24 hour growth experiment. The method robustly maintained the correct focal position compensating for 40 μm of focal drift and was insensitive to changes in the field of view. About ~100 annotated z-stacks were required to train the network making our method quite practical for custom autofocus applications.

  19. Bidirectional Long Short-Term Memory Network with a Conditional Random Field Layer for Uyghur Part-Of-Speech Tagging

    Directory of Open Access Journals (Sweden)

    Maihemuti Maimaiti

    2017-11-01

    Full Text Available Uyghur is an agglutinative and a morphologically rich language; natural language processing tasks in Uyghur can be a challenge. Word morphology is important in Uyghur part-of-speech (POS tagging. However, POS tagging performance suffers from error propagation of morphological analyzers. To address this problem, we propose a few models for POS tagging: conditional random fields (CRF, long short-term memory (LSTM, bidirectional LSTM networks (BI-LSTM, LSTM networks with a CRF layer, and BI-LSTM networks with a CRF layer. These models do not depend on stemming and word disambiguation for Uyghur and combine hand-crafted features with neural network models. State-of-the-art performance on Uyghur POS tagging is achieved on test data sets using the proposed approach: 98.41% accuracy on 15 labels and 95.74% accuracy on 64 labels, which are 2.71% and 4% improvements, respectively, over the CRF model results. Using engineered features, our model achieves further improvements of 0.2% (15 labels and 0.48% (64 labels. The results indicate that the proposed method could be an effective approach for POS tagging in other morphologically rich languages.

  20. Proceedings of the African Field Epidemiology Network (AFENET) Scientific Conference 17-22 November 2013 Addis Ababa, Ethiopia: plenaries and oral presentations

    OpenAIRE

    Gitta, Sheba Nakacubo; Mwesiga, Allan; Kamadjeu, Raoul; Stanley, Claire; Borchert, Jeff; Mensah, George; Bejtullahu, Armand; Kamadjeu, Raoul; Kebede, Amha; Berhane, Yemane; Jocker, Mathew Lado; Ebontane, Ndode Corlins; Feyissa, Daba; Yeshitila, Kidanie; Mehari, Goitom

    2015-01-01

    Biennially, trainees and graduates of Field Epidemiology and Laboratory Training Programs (FELTPs) are presented with a platform to share investigations and projects undertaken during their two-year training in Applied Epidemiology. The African Field Epidemiology Network (AFENET) Scientific Conference, is a perfect opportunity for public health professionals from various sectors and organizations to come together to discuss issues that impact on public health in Africa. This year's conference...

  1. Logistical networking: a global storage network

    International Nuclear Information System (INIS)

    Beck, Micah; Moore, Terry

    2005-01-01

    The absence of an adequate distributed storage infrastructure for data buffering has become a significant impediment to the flow of work in the wide area, data intensive collaborations that are increasingly characteristic of leading edge research in several fields. One solution to this problem, pioneered under DOE's SciDAC program, is Logistical Networking, which provides a framework for a globally scalable, maximally interoperable storage network based on the Internet Backplane Protocol (IBP). This paper provides a brief overview of the Logistical Networking (LN) architecture, the middleware developed to exploit its value, and a few of the applications that some of research communities have made of it

  2. Reconstructing consensus Bayesian network structures with application to learning molecular interaction networks

    NARCIS (Netherlands)

    Fröhlich, H.; Klau, G.W.

    2013-01-01

    Bayesian Networks are an established computational approach for data driven network inference. However, experimental data is limited in its availability and corrupted by noise. This leads to an unavoidable uncertainty about the correct network structure. Thus sampling or bootstrap based strategies

  3. Network analysis: A new way of understanding psychopathology?

    Science.gov (United States)

    Fonseca-Pedrero, Eduardo

    Current taxonomic systems are based on a descriptive and categorical approach where psychopathological symptoms and signs are caused by a hypothetical underlying mental disorder. In order to circumvent the limitations of classification systems, it is necessary to incorporate new conceptual and psychometric models that allow to understand, analyze and intervene in psychopathological phenomena from another perspective. The main goal was to present a new approach called network analysis for its application in the field of psychopathology. First of all, a brief introduction where psychopathological disorders are conceived as complex dynamic systems was carried out. Key concepts, as well as the different types of networks and the procedures for their estimation, are discussed. Following this, centrality measures, important for the understanding of the network as well as to examine the relevance of the variables within the network were addressed. These factors were then exemplified by estimating a network of self-reported psychopathological symptoms in a representative sample of adolescents. Finally, a brief recapitulation is made and future lines of research are discussed. Copyright © 2017 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

  4. Classification of underwater targets from autonomous underwater vehicle sampled bistatic acoustic scattered fields.

    Science.gov (United States)

    Fischell, Erin M; Schmidt, Henrik

    2015-12-01

    One of the long term goals of autonomous underwater vehicle (AUV) minehunting is to have multiple inexpensive AUVs in a harbor autonomously classify hazards. Existing acoustic methods for target classification using AUV-based sensing, such as sidescan and synthetic aperture sonar, require an expensive payload on each outfitted vehicle and post-processing and/or image interpretation. A vehicle payload and machine learning classification methodology using bistatic angle dependence of target scattering amplitudes between a fixed acoustic source and target has been developed for onboard, fully autonomous classification with lower cost-per-vehicle. To achieve the high-quality, densely sampled three-dimensional (3D) bistatic scattering data required by this research, vehicle sampling behaviors and an acoustic payload for precision timed data acquisition with a 16 element nose array were demonstrated. 3D bistatic scattered field data were collected by an AUV around spherical and cylindrical targets insonified by a 7-9 kHz fixed source. The collected data were compared to simulated scattering models. Classification and confidence estimation were shown for the sphere versus cylinder case on the resulting real and simulated bistatic amplitude data. The final models were used for classification of simulated targets in real time in the LAMSS MOOS-IvP simulation package [M. Benjamin, H. Schmidt, P. Newman, and J. Leonard, J. Field Rob. 27, 834-875 (2010)].

  5. Network analysis: An innovative framework for understanding eating disorder psychopathology.

    Science.gov (United States)

    Smith, Kathryn E; Crosby, Ross D; Wonderlich, Stephen A; Forbush, Kelsie T; Mason, Tyler B; Moessner, Markus

    2018-03-01

    Network theory and analysis is an emerging approach in psychopathology research that has received increasing attention across fields of study. In contrast to medical models or latent variable approaches, network theory suggests that psychiatric syndromes result from systems of causal and reciprocal symptom relationships. Despite the promise of this approach to elucidate key mechanisms contributing to the development and maintenance of eating disorders (EDs), thus far, few applications of network analysis have been tested in ED samples. We first present an overview of network theory, review the existing findings in the ED literature, and discuss the limitations of this literature to date. In particular, the reliance on cross-sectional designs, use of single-item self-reports of symptoms, and instability of results have raised concern about the inferences that can be made from network analyses. We outline several areas to address in future ED network analytic research, which include the use of prospective designs and adoption of multimodal assessment methods. Doing so will provide a clearer understanding of whether network analysis can enhance our current understanding of ED psychopathology and inform clinical interventions. © 2018 Wiley Periodicals, Inc.

  6. Sediment and radionuclide transport in rivers. Phase 3. Field sampling program for Cattaraugus and Buttermilk Creeks, New York

    International Nuclear Information System (INIS)

    Ecker, R.M.; Walters, W.H.; Onishi, Y.

    1982-08-01

    A field sampling program was conducted on Cattaraugus and Buttermilk Creeks, New York during April 1979 to investigate the transport of radionuclides in surface waters as part of a continuing program to provide data for application and verification of Pacific Northwest Laboratory's (PNL) sediment and radionuclide transport model, SERATRA. Bed sediment, suspended sediment and water samples were collected during unsteady flow conditions over a 45 mile reach of stream channel. Radiological analysis of these samples included gamma ray spectrometry analysis, and radiochemical separation and analysis of Sr-90, Pu-238, Pu-239, 240, Am-241 and Cm-244. Tritium analysis was also performed on water samples. Based on the evaluation of radionuclide levels in Cattaraugus and Buttermilk Creeks, the Nuclear Fuel Services facility at West Valley, New York, may be the source of Cs-137, Sr-90, Cs-134, Co-60, Pu-238, Pu-239, 240, Am-241, Cm-244 and tritium found in the bed sediment, suspended sediment and water of Buttermilk and Cattaraugus Creeks. This field sampling effort was the last of a three phase program to collect hydrologic and radiologic data at different flow conditions

  7. Collaboration networks and intersectoriality in public daycares of São Paulo state

    Directory of Open Access Journals (Sweden)

    Claudia Maria Simões Martinez

    2016-10-01

    Full Text Available Introduction: The literature indicates positive impacts on child development for those children attending day care centers, when this context includes good practices. It is believed that a set of actions, networking, coordinated by managers can positively to impact the children development. Objective: Although the literature indicate the fields of knowledge “health, education and social” as the daycare collaborative networks, this study evaluated are the points that allow connections in these networks today, and the possible existence of other networks describing their characteristics. Method: The methodology included ethical procedures and definition of the sampling plan, which resulted in 32 daycare schools in the municipalities of São Paulo. Data were collected through interviews with the daycares directors seeking to identify the network points, from situations present in their daily practice. Results: The results showed the presence of 75 points of the cooperation network in 32 municipalities with different service partnerships, sometimes with more extensive networks, or shorter. We highlight the strong presence of intersectorality arising from the fields of education, health and social. Municipal equipment for infrastructure actions were identified, as well as the presence of various government programs from the federal level. Conclusion: The scale of child development is present in an intense way in the sphere of education and health. The data are discussed from the perspective of supporting leaders for solving the problems considering the potential of preventive action in early childhood.

  8. PTSD symptomics: network analyses in the field of psychotraumatology.

    Science.gov (United States)

    Armour, Cherie; Fried, Eiko I; Olff, Miranda

    2017-01-01

    Recent years have seen increasing attention on posttraumatic stress disorder (PTSD) research. While research has largely focused on the dichotomy between patients diagnosed with mental disorders and healthy controls - in other words, investigations at the level of diagnoses - recent work has focused on psychopathology symptoms. Symptomics research in the area of PTSD has been scarce so far, although several studies have focused on investigating the network structures of PTSD symptoms. The present special issue of EJPT adds to the literature by curating additional PTSD network studies, each looking at a different aspect of PTSD. We hope that this special issue encourages researchers to conceptualize and model PTSD data from a network perspective, which arguably has the potential to inform and improve the efficacy of therapeutic interventions.

  9. Spatial networks

    Science.gov (United States)

    Barthélemy, Marc

    2011-02-01

    Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

  10. Approaches to Sampling Gay, Bisexual, and Other Men Who Have Sex with Men from Geosocial-Networking Smartphone Applications: A Methodological Note

    Directory of Open Access Journals (Sweden)

    William C. Goedel

    2016-09-01

    Full Text Available Geosocial-networking smartphone applications utilize global positioning system (GPS technologies to connect users based on their physical proximity. Many gay, bisexual, and other men who have sex with men (MSM have smartphones, and these new mobile technologies have generated quicker and easier modes for MSM to meet potential partners. In doing so, these technologies may facilitate a user’s ability to have multiple concurrent partners, thereby increasing their risk for acquiring HIV or other sexually transmitted infections. Researchers have sought to recruit users of these applications (e.g., Grindr, Jack’d, Scruff into HIV prevention studies, primarily through advertising on the application. Given that these advertisements often broadly targeted large urban areas, these approaches have generated samples that are not representative of the population of users of the given application in a given area. As such, we propose a method to generate a spatially representative sample of MSM via direct messaging on a given application using New York City and its geography as an example of this sampling and recruitment method. These methods can increase geographic representativeness and wider access to MSM who use geosocial-networking smartphone applications.

  11. 7th Workshop on Complex Networks

    CERN Document Server

    Gonçalves, Bruno; Menezes, Ronaldo; Sinatra, Roberta

    2016-01-01

    The last decades have seen the emergence of Complex Networks as the language with which a wide range of complex phenomena in fields as diverse as Physics, Computer Science, and Medicine (to name just a few) can be properly described and understood. This book provides a view of the state of the art in this dynamic field and covers topics ranging from network controllability, social structure, online behavior, recommendation systems, and network structure. This book includes the peer-reviewed list of works presented at the 7th Workshop on Complex Networks CompleNet 2016 which was hosted by the Université de Bourgogne, France, from March 23-25, 2016. The 28 carefully reviewed and selected contributions in this book address many topics related to complex networks and have been organized in seven major groups: (1) Theory of Complex Networks, (2) Multilayer networks, (3) Controllability of networks, (4) Algorithms for networks, (5) Community detection, (6) Dynamics and spreading phenomena on networks, (7) Applicat...

  12. A Discrete Fracture Network Model with Stress-Driven Nucleation and Growth

    Science.gov (United States)

    Lavoine, E.; Darcel, C.; Munier, R.; Davy, P.

    2017-12-01

    The realism of Discrete Fracture Network (DFN) models, beyond the bulk statistical properties, relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. The realism can be improved by injecting prior information in DFN from a better knowledge of the geological fracturing processes. We first develop a model using simple kinematic rules for mimicking the growth of fractures from nucleation to arrest, in order to evaluate the consequences of the DFN structure on the network connectivity and flow properties. The model generates fracture networks with power-law scaling distributions and a percentage of T-intersections that are consistent with field observations. Nevertheless, a larger complexity relying on the spatial variability of natural fractures positions cannot be explained by the random nucleation process. We propose to introduce a stress-driven nucleation in the timewise process of this kinematic model to study the correlations between nucleation, growth and existing fracture patterns. The method uses the stress field generated by existing fractures and remote stress as an input for a Monte-Carlo sampling of nuclei centers at each time step. Networks so generated are found to have correlations over a large range of scales, with a correlation dimension that varies with time and with the function that relates the nucleation probability to stress. A sensibility analysis of input parameters has been performed in 3D to quantify the influence of fractures and remote stress field orientations.

  13. Use of remote sensing and ground control in monitoring oil fields in Alabama

    Energy Technology Data Exchange (ETDEWEB)

    La Moreaux, P E; Muzikar, R [ed.

    1978-01-01

    Present and future water pollution problems resulting from oil field operations in Alabama are analyzed. An outline of a program of data collection and interpretation necessary to determine and evaluate solutions to these problems is presented. A method of adequate monitoring of the oil and gas fields in Alabama to protect against pollution of its valuable surface and groundwater supplies is described. Samples of brine are continuously collected and analyzed from sources representing all water producing horizons in the oil fields. A network of observation wells has been established in oil fields to periodically determine changes in the chemical quality of groundwaters. Water samples from wells adjacent to all major saltwater evaporation pits have been collected and analyzed for possible changes in chemical quality. Discharge measurements are made on streams adjacent to all oil fields. Periodic aerial photographs are being made of each field. Preliminary administrative reports are regularly prepared on each problem in the oil fields and remedial or disciplinary actions are taken by the Oil and Gas Board.

  14. Network analysis of PTSD symptoms following mass violence.

    Science.gov (United States)

    Sullivan, Connor P; Smith, Andrew J; Lewis, Michael; Jones, Russell T

    2018-01-01

    Network analysis is a useful tool for understanding how symptoms interact with one another to influence psychopathology. However, this analytic strategy has not been fully utilized in the PTSD field. The current study utilized network analysis to examine connectedness and strength among PTSD symptoms (employing both partial correlation and regression network analyses) among a community sample of students exposed to the 2007 Virginia Tech shootings. Respondents (N = 4,639) completed online surveys 3-4 months postshootings, with PTSD symptom severity measured via the Trauma Symptom Questionnaire. Data were analyzed via adaptive least absolute shrinkage and selection operator (LASSO) and relative importance networks, as well as Dijkstra's algorithm to identify the shortest path from each symptom to all other symptoms. Relative importance network analysis revealed that intrusive thoughts had the strongest influence on other symptoms (i.e., had many strong connections [highest outdegree]) while computing Dijkstra's algorithm indicated that anger produced the shortest path to all other symptoms (i.e., the strongest connections to all other symptoms). Findings suggest that anger or intrusion likely play a crucial role in the development and maintenance of PTSD (i.e., are more influential within the network than are other symptoms). (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  15. Neural Networks: Implementations and Applications

    OpenAIRE

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  16. Network Approach to Understanding Emotion Dynamics in Relation to Childhood Trauma and Genetic Liability to Psychopathology: Replication of a Prospective Experience Sampling Analysis

    Directory of Open Access Journals (Sweden)

    Laila Hasmi

    2017-11-01

    Full Text Available Background: The network analysis of intensive time series data collected using the Experience Sampling Method (ESM may provide vital information in gaining insight into the link between emotion regulation and vulnerability to psychopathology. The aim of this study was to apply the network approach to investigate whether genetic liability (GL to psychopathology and childhood trauma (CT are associated with the network structure of the emotions “cheerful,” “insecure,” “relaxed,” “anxious,” “irritated,” and “down”—collected using the ESM method.Methods: Using data from a population-based sample of twin pairs and siblings (704 individuals, we examined whether momentary emotion network structures differed across strata of CT and GL. GL was determined empirically using the level of psychopathology in monozygotic and dizygotic co-twins. Network models were generated using multilevel time-lagged regression analysis and were compared across three strata (low, medium, and high of CT and GL, respectively. Permutations were utilized to calculate p values and compare regressions coefficients, density, and centrality indices. Regression coefficients were presented as connections, while variables represented the nodes in the network.Results: In comparison to the low GL stratum, the high GL stratum had significantly denser overall (p = 0.018 and negative affect network density (p < 0.001. The medium GL stratum also showed a directionally similar (in-between high and low GL strata but statistically inconclusive association with network density. In contrast to GL, the results of the CT analysis were less conclusive, with increased positive affect density (p = 0.021 and overall density (p = 0.042 in the high CT stratum compared to the medium CT stratum but not to the low CT stratum. The individual node comparisons across strata of GL and CT yielded only very few significant results, after adjusting for multiple testing.Conclusions: The

  17. Creative Network Communities in the Translocal Space of Digital Networks

    Directory of Open Access Journals (Sweden)

    Rasa Smite

    2013-01-01

    Full Text Available What should sociological research be in the age of Web 2.0? Considering that the task of “network sociology” is not only empirical research but also the interpretation of tendencies of the network culture, this research explores the rise of network communities within Eastern and Western Europe in the early Internet era. I coined the term creative networks to distinguish these early creative and social activities from today’s popular social networking. Thus I aimed to interpret the meaning of social action; the motivation of creative community actors, their main fields of activities and social organization forms; and the potential that these early developments contain for the future sustainability of networks. Data comprise interviews with networking experts and founders and members of various networks. Investigating respondents’ motivations for creating online networks and communities, and interpreting those terms, allows for comparing the creative networks of the 1990s with today’s social networks and for drawing conclusions.

  18. Persistent Identifiers for Field Deployments: A Missing Link in the Provenance Chain

    Science.gov (United States)

    Arko, R. A.; Ji, P.; Fils, D.; Shepherd, A.; Chandler, C. L.; Lehnert, K.

    2016-12-01

    Research in the geosciences is characterized by a wide range of complex and costly field deployments including oceanographic cruises, submersible dives, drilling expeditions, seismic networks, geodetic campaigns, moored arrays, aircraft flights, and satellite missions. Each deployment typically produces a mix of sensor and sample data, spanning a period from hours to decades, that ultimately yields a long tail of post-field products and publications. Publishing persistent, citable identifiers for field deployments will facilitate 1) preservation and reuse of the original field data, 2) reproducibility of the resulting publications, and 3) recognition for both the facilities that operate the platforms and the investigators who secure funding for the experiments. In the ocean domain, sharing unique identifiers for field deployments is a familiar practice. For example, the Biological and Chemical Oceanography Data Management Office (BCO-DMO) routinely links datasets to cruise identifiers published by the Rolling Deck to Repository (R2R) program. In recent years, facilities have started to publish formal/persistent identifiers, typically Digital Object Identifiers (DOIs), for field deployments including seismic networks, oceanographic cruises, and moored arrays. For example, the EarthChem Library (ECL) publishes a DOI for each dataset which, if it derived from an oceanographic research cruise on a US vessel, is linked to a DOI for the cruise published by R2R. Work is underway to create similar links for the IODP JOIDES Resolution Science Operator (JRSO) and the Continental Scientific Drilling Coordination Office (CSDCO). We present results and lessons learned including a draft schema for publishing field deployments as DataCite DOI records; current practice for linking these DOIs with related identifiers such as Open Researcher and Contributor IDs (ORCIDs), Open Funder Registry (OFR) codes, and International Geo Sample Numbers (IGSNs); and consideration of other

  19. Application of neural networks to waste site screening

    Energy Technology Data Exchange (ETDEWEB)

    Dabiri, A.E.; Kraft, T.; Hilton, J.M. [Science Applications International Corp., San Diego, CA (United States)

    1993-03-01

    Waste site screening requires knowledge of the actual concentrations of hazardous materials and rates of flow around and below the site with time. The present approach to site screening consists primarily of drilling, boreholes near contaminated site and chemically analyzing the extracted physical samples and processing the data. In addition, hydraulic and geochemical soil properties are obtained so that numerical simulation models can be used to interpret and extrapolate the field data. The objective of this work is to investigate the feasibility of using neural network techniques to reduce the cost of waste site screening. A successful technique may lead to an ability to reduce the number of boreholes and the number of samples analyzed from each borehole to properly screen the waste site. The analytic tool development described here is inexpensive because it makes use of neural network techniques that can interpolate rapidly and which can learn how to analyze data rather than having to be explicitly programmed. In the following sections, data collection and data analyses will be described, followed by a section on different neural network techniques used. The results will be presented and compared with mathematical model. Finally, the last section will summarize the research work performed and make several recommendations for future work.

  20. Predicting bioavailability of PAHs in field-contaminated soils by passive sampling with triolein embedded cellulose acetate membranes

    Energy Technology Data Exchange (ETDEWEB)

    Tao Yuqiang [State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085 (China); Zhang Shuzhen [State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085 (China)], E-mail: szzhang@rcees.ac.cn; Wang Zijian [State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085 (China); Christie, Peter [Queen' s University Belfast, Agricultural and Environmental Science Department, Newforge Lane, Belfast BT9 5PX (United Kingdom)

    2009-02-15

    Triolein embedded cellulose acetate membrane (TECAM) was used for passive sampling of the fraction of naphthalene, phenanthrene, pyrene and benzo[a]pyrene in 18 field-contaminated soils. The sampling process of PAHs by TECAM fitted well with a first-order kinetics model and PAHs reached 95% of equilibrium in TECAM within 20 h. Concentrations of PAHs in TECAM (C{sub TECAM}) correlated well with the concentrations in soils (r{sup 2} = 0.693-0.962, p < 0.001). Furthermore, concentrations of PAHs determined in the soil solution were very close to the values estimated by C{sub TECAM} and the partition coefficient between TECAM and water (K{sub TECAM-w}). After lipid normalization nearly 1:1 relationships were observed between PAH concentrations in TECAMs and earthworms exposed to the soils (r{sup 2} = 0.591-0.824, n = 18, p < 0.01). These results suggest that TECAM can be a useful tool to predict bioavailability of PAHs in field-contaminated soils. - Triolein embedded cellulose acetate membranes can be a useful tool to predict bioavailability of PAHs in field-contaminated soils.

  1. PTSD symptomics: network analyses in the field of psychotraumatology

    Science.gov (United States)

    Armour, Cherie; Fried, Eiko I.; Olff, Miranda

    2017-01-01

    ABSTRACT Recent years have seen increasing attention on posttraumatic stress disorder (PTSD) research. While research has largely focused on the dichotomy between patients diagnosed with mental disorders and healthy controls — in other words, investigations at the level of diagnoses — recent work has focused on psychopathology symptoms. Symptomics research in the area of PTSD has been scarce so far, although several studies have focused on investigating the network structures of PTSD symptoms. The present special issue of EJPT adds to the literature by curating additional PTSD network studies, each looking at a different aspect of PTSD. We hope that this special issue encourages researchers to conceptualize and model PTSD data from a network perspective, which arguably has the potential to inform and improve the efficacy of therapeutic interventions. PMID:29250305

  2. Recurrent Spatial Transformer Networks

    DEFF Research Database (Denmark)

    Sønderby, Søren Kaae; Sønderby, Casper Kaae; Maaløe, Lars

    2015-01-01

    We integrate the recently proposed spatial transformer network (SPN) [Jaderberg et. al 2015] into a recurrent neural network (RNN) to form an RNN-SPN model. We use the RNN-SPN to classify digits in cluttered MNIST sequences. The proposed model achieves a single digit error of 1.5% compared to 2.......9% for a convolutional networks and 2.0% for convolutional networks with SPN layers. The SPN outputs a zoomed, rotated and skewed version of the input image. We investigate different down-sampling factors (ratio of pixel in input and output) for the SPN and show that the RNN-SPN model is able to down-sample the input...

  3. Field sampling, preparation procedure and plutonium analyses of large freshwater samples

    International Nuclear Information System (INIS)

    Straelberg, E.; Bjerk, T.O.; Oestmo, K.; Brittain, J.E.

    2002-01-01

    This work is part of an investigation of the mobility of plutonium in freshwater systems containing humic substances. A well-defined bog-stream system located in the catchment area of a subalpine lake, Oevre Heimdalsvatn, Norway, is being studied. During the summer of 1999, six water samples were collected from the tributary stream Lektorbekken and the lake itself. However, the analyses showed that the plutonium concentration was below the detection limit in all the samples. Therefore renewed sampling at the same sites was carried out in August 2000. The results so far are in agreement with previous analyses from the Heimdalen area. However, 100 times higher concentrations are found in the lowlands in the eastern part of Norway. The reason for this is not understood, but may be caused by differences in the concentrations of humic substances and/or the fact that the mountain areas are covered with snow for a longer period of time every year. (LN)

  4. Investigation of applicability of extrapolation method for sample field determination in single-yoke measuring setup

    Czech Academy of Sciences Publication Activity Database

    Stupakov, Oleksandr

    2006-01-01

    Roč. 307, - (2006), s. 279-287 ISSN 0304-8853 R&D Projects: GA AV ČR(CZ) 1QS100100508 Institutional research plan: CEZ:AV0Z10100520 Keywords : magnetic measurement * open magnetic sample * surface field determination * single-yoke setup * magnetic non-destructive testing Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.212, year: 2006

  5. Technologies for pre-screening IAEA swipe samples

    International Nuclear Information System (INIS)

    Smith, Nicholas A.; Steeb, Jennifer L.; Lee, Denise L.; Huckabay, Heath A.; Ticknor, Brian W.

    2015-01-01

    During the course of International Atomic Energy Agency (IAEA) inspections, many samples are taken for the purpose of verifying the declared facility activities and identifying any possible undeclared activities. One of these sampling techniques is the environmental swipe sample. Due to the large number of samples collected, and the amount of time that is required to analyze them, prioritizing these swipes in the field or upon receipt at the Network of Analytical Laboratories (NWAL) will allow sensitive or mission-critical analyses to be performed sooner. As a result of this study, technologies were placed into one of three categories: recommended, promising, or not recommended. Both neutron activation analysis (NAA) and X-ray fluorescence (XRF) are recommended for further study and possible field deployment. These techniques performed the best in initial trials for pre-screening and prioritizing IAEA swipes. We learned that for NAA more characterization of cold elements (such as calcium and magnesium) would need to be emphasized, and for XRF it may be appropriate to move towards a benchtop XRF versus a handheld XRF due to the increased range of elements available on benchtop equipment. Promising techniques that will require additional research and development include confocal Raman microscopy, fluorescence microscopy, and infrared (IR) microscopy. These techniques showed substantive responses to uranium compounds, but expensive instrumentation upgrades (confocal Raman) or university engagement (fluorescence microscopy) may be necessary to investigate the utility of the techniques completely. Point-and-shoot (handheld) Raman and attenuated total reflectance–infrared (ATR-IR) measurements are not recommended, as they have not shown enough promise to continue investigations.

  6. Technologies for pre-screening IAEA swipe samples

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Nicholas A. [Argonne National Lab. (ANL), Argonne, IL (United States); Steeb, Jennifer L. [Argonne National Lab. (ANL), Argonne, IL (United States); Lee, Denise L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Huckabay, Heath A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ticknor, Brian W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-11-09

    During the course of International Atomic Energy Agency (IAEA) inspections, many samples are taken for the purpose of verifying the declared facility activities and identifying any possible undeclared activities. One of these sampling techniques is the environmental swipe sample. Due to the large number of samples collected, and the amount of time that is required to analyze them, prioritizing these swipes in the field or upon receipt at the Network of Analytical Laboratories (NWAL) will allow sensitive or mission-critical analyses to be performed sooner. As a result of this study, technologies were placed into one of three categories: recommended, promising, or not recommended. Both neutron activation analysis (NAA) and X-ray fluorescence (XRF) are recommended for further study and possible field deployment. These techniques performed the best in initial trials for pre-screening and prioritizing IAEA swipes. We learned that for NAA more characterization of cold elements (such as calcium and magnesium) would need to be emphasized, and for XRF it may be appropriate to move towards a benchtop XRF versus a handheld XRF due to the increased range of elements available on benchtop equipment. Promising techniques that will require additional research and development include confocal Raman microscopy, fluorescence microscopy, and infrared (IR) microscopy. These techniques showed substantive responses to uranium compounds, but expensive instrumentation upgrades (confocal Raman) or university engagement (fluorescence microscopy) may be necessary to investigate the utility of the techniques completely. Point-and-shoot (handheld) Raman and attenuated total reflectance–infrared (ATR-IR) measurements are not recommended, as they have not shown enough promise to continue investigations.

  7. Social Networks and Externalities from Gift Exchange: Evidence from A Field Experiment.

    Science.gov (United States)

    Currie, Janet; Lin, Wanchuan; Meng, Juanjuan

    2013-11-01

    This paper asks whether gift exchange generates externalities for people outside of the bilateral relationship between the gift giver and recipient, and whether the nature of this relationship is affected by social networks. We examine this question in the context of a field experiment in urban Chinese hospital outpatient clinics. We first show that when patients give a small gift, doctors reciprocate with better service and a fewer unnecessary prescriptions of antibiotics. We then show that gift giving creates externalities for third parties. If two patients, A and B are perceived as unrelated, B receives worse care when A gives a gift. However, if A identifies B as a friend, then both A and B benefit from A's gift giving. Hence, we show that gift giving can create positive or negative externalities, depending on the giver's social distance to the third party.

  8. Exponential Synchronization for Stochastic Neural Networks with Mixed Time Delays and Markovian Jump Parameters via Sampled Data

    Directory of Open Access Journals (Sweden)

    Yingwei Li

    2014-01-01

    Full Text Available The exponential synchronization issue for stochastic neural networks (SNNs with mixed time delays and Markovian jump parameters using sampled-data controller is investigated. Based on a novel Lyapunov-Krasovskii functional, stochastic analysis theory, and linear matrix inequality (LMI approach, we derived some novel sufficient conditions that guarantee that the master systems exponentially synchronize with the slave systems. The design method of the desired sampled-data controller is also proposed. To reflect the most dynamical behaviors of the system, both Markovian jump parameters and stochastic disturbance are considered, where stochastic disturbances are given in the form of a Brownian motion. The results obtained in this paper are a little conservative comparing the previous results in the literature. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

  9. Superconducting nanowire networks formed on nanoporous membrane substrates

    Science.gov (United States)

    Luo, Qiong

    attributed to thermal phase slips and Little-Parks effect, revealing new phenomena at extreme conditions. This research significantly advanced our understanding on confinement effects in superconductors. Since AAO membranes of large area can be fabricated easily and filtration membranes are commercially available, the developed fabrication approach provides an alternative but more accessible templating method to achieve samples for exploring phenomena in superconductors with transverse dimensions down to few nanometers. This research also sets limitations on efforts to pursue high commensurate vortex pinning fields by increasing the density of holes in a perforated film: a reduction in the width of superconducting section between neighboring holes can turn a 2D film into a network of 1D nanowires which dissipate energy when conducting electricity due to thermal and possibly also quantum phase slippages, eliminating the desired pinning effect of the introduced hole.

  10. Development of analytical techniques for safeguards environmental samples at JAEA

    International Nuclear Information System (INIS)

    Sakurai, Satoshi; Magara, Masaaki; Usuda, Shigekazu; Watanabe, Kazuo; Esaka, Fumitaka; Hirayama, Fumio; Lee, Chi-Gyu; Yasuda, Kenichiro; Inagawa, Jun; Suzuki, Daisuke; Iguchi, Kazunari; Kokubu, Yoko S.; Miyamoto, Yutaka; Ohzu, Akira

    2007-01-01

    JAEA has been developing, under the auspices of the Ministry of Education, Culture, Sports, Science and Technology of Japan, analytical techniques for ultra-trace amounts of nuclear materials in environmental samples in order to contribute to the strengthened safeguards system. Development of essential techniques for bulk and particle analysis, as well as screening, of the environmental swipe samples has been established as ultra-trace analytical methods of uranium and plutonium. In January 2003, JAEA was qualified, including its quality control system, as a member of the JAEA network analytical laboratories for environmental samples. Since 2004, JAEA has conducted the analysis of domestic and the IAEA samples, through which JAEA's analytical capability has been verified and improved. In parallel, advanced techniques have been developed in order to expand the applicability to the samples of various elemental composition and impurities and to improve analytical accuracy and efficiency. This paper summarizes the trace of the technical development in environmental sample analysis at JAEA, and refers to recent trends of research and development in this field. (author)

  11. How iSamples (Internet of Samples in the Earth Sciences) Improves Sample and Data Stewardship in the Next Generation of Geoscientists

    Science.gov (United States)

    Hallett, B. W.; Dere, A. L. D.; Lehnert, K.; Carter, M.

    2016-12-01

    Vast numbers of physical samples are routinely collected by geoscientists to probe key scientific questions related to global climate change, biogeochemical cycles, magmatic processes, mantle dynamics, etc. Despite their value as irreplaceable records of nature the majority of these samples remain undiscoverable by the broader scientific community because they lack a digital presence or are not well-documented enough to facilitate their discovery and reuse for future scientific and educational use. The NSF EarthCube iSamples Research Coordination Network seeks to develop a unified approach across all Earth Science disciplines for the registration, description, identification, and citation of physical specimens in order to take advantage of the new opportunities that cyberinfrastructure offers. Even as consensus around best practices begins to emerge, such as the use of the International Geo Sample Number (IGSN), more work is needed to communicate these practices to investigators to encourage widespread adoption. Recognizing the importance of students and early career scientists in particular to transforming data and sample management practices, the iSamples Education and Training Working Group is developing training modules for sample collection, documentation, and management workflows. These training materials are made available to educators/research supervisors online at http://earthcube.org/group/isamples and can be modularized for supervisors to create a customized research workflow. This study details the design and development of several sample management tutorials, created by early career scientists and documented in collaboration with undergraduate research students in field and lab settings. Modules under development focus on rock outcrops, rock cores, soil cores, and coral samples, with an emphasis on sample management throughout the collection, analysis and archiving process. We invite others to share their sample management/registration workflows and to

  12. Health research networks on the web: an analysis of the Brazilian presence

    Directory of Open Access Journals (Sweden)

    Pamela Barreto Lang

    2014-02-01

    Full Text Available In order to map Brazilian institutions’ web presence in an international network of health research institutions, a study was conducted in 2009, including 190 institutions from 42 countries. The sample was based on WHO (World Health Organization collaborating centers, and the methodology used webometric analyses and techniques, especially interlinks, and social network analysis. The results showed the presence of five Brazilian institutions, featuring the Oswaldo Cruz Foundation (Fiocruz, showing links to 20 countries and 42 institutions. Through the interface between the health field and the web, the study aims to contribute to future analyses and a plan for strategic repositioning of these institutions in the virtual world, as well as to the elaboration of public policies and recognition of webometrics as an area to be explored and applied to various other fields of knowledge.

  13. Recruiting an Internet Panel Using Respondent-Driven Sampling

    Directory of Open Access Journals (Sweden)

    Schonlau Matthias

    2014-06-01

    Full Text Available Respondent-driven sampling (RDS is a network sampling technique typically employed for hard-to-reach populations when traditional sampling approaches are not feasible (e.g., homeless or do not work well (e.g., people with HIV. In RDS, seed respondents recruit additional respondents from their network of friends. The recruiting process repeats iteratively, thereby forming long referral chains.

  14. A balanced memory network.

    Directory of Open Access Journals (Sweden)

    Yasser Roudi

    2007-09-01

    Full Text Available A fundamental problem in neuroscience is understanding how working memory--the ability to store information at intermediate timescales, like tens of seconds--is implemented in realistic neuronal networks. The most likely candidate mechanism is the attractor network, and a great deal of effort has gone toward investigating it theoretically. Yet, despite almost a quarter century of intense work, attractor networks are not fully understood. In particular, there are still two unanswered questions. First, how is it that attractor networks exhibit irregular firing, as is observed experimentally during working memory tasks? And second, how many memories can be stored under biologically realistic conditions? Here we answer both questions by studying an attractor neural network in which inhibition and excitation balance each other. Using mean-field analysis, we derive a three-variable description of attractor networks. From this description it follows that irregular firing can exist only if the number of neurons involved in a memory is large. The same mean-field analysis also shows that the number of memories that can be stored in a network scales with the number of excitatory connections, a result that has been suggested for simple models but never shown for realistic ones. Both of these predictions are verified using simulations with large networks of spiking neurons.

  15. Effects of the soil pore network architecture on the soil's physical functionalities

    Science.gov (United States)

    Smet, Sarah; Beckers, Eléonore; Léonard, Angélique; Degré, Aurore

    2017-04-01

    The soil fluid movement's prediction is of major interest within an agricultural or environmental scope because many processes depend ultimately on the soil fluids dynamic. It is common knowledge that the soil microscopic pore network structure governs the inner-soil convective fluids flow. There isn't, however, a general methodthat consider the pore network structure as a variable in the prediction of thecore scale soil's physical functionalities. There are various possible representations of the microscopic pore network: sample scale averaged structural parameters, extrapolation of theoretic pore network, or use of all the information available by modeling within the observed pore network. Different representations implydifferent analyzing methodologies. To our knowledge, few studies have compared the micro-and macroscopic soil's characteristics for the same soil core sample. The objective of our study is to explore the relationship between macroscopic physical properties and microscopic pore network structure. The saturated hydraulic conductivity, the air permeability, the retention curve, and others classical physical parameters were measured for ten soil samples from an agricultural field. The pore network characteristics were quantified through the analyses of X-ray micro-computed tomographic images(micro-CT system Skyscan-1172) with a voxel size of 22 µm3. Some of the first results confirmed what others studies had reported. Then, the comparison between macroscopic properties and microscopic parameters suggested that the air movements depended mostly on the pore connectivity and tortuosity than on the total porosity volume. We have also found that the fractal dimension calculated from the X-ray images and the fractal dimension calculated from the retention curve were significantly different. Our communication will detailthose results and discuss the methodology: would the results be similar with a different voxel size? What are the calculated and measured

  16. Electromagnetic Fields and Public Health: Mobile Phones

    Science.gov (United States)

    ... waves through a network of fixed antennas called base stations. Radiofrequency waves are electromagnetic fields, and unlike ionizing radiation ... waves through a network of fixed antennas called base stations. Radiofrequency waves are electromagnetic fields, and unlike ionizing radiation ...

  17. Ice nucleating particles from a large-scale sampling network: insight into geographic and temporal variability

    Science.gov (United States)

    Schrod, Jann; Weber, Daniel; Thomson, Erik S.; Pöhlker, Christopher; Saturno, Jorge; Artaxo, Paulo; Curtius, Joachim; Bingemer, Heinz

    2017-04-01

    The number concentration of ice nucleating particles (INP) is an important, yet under quantified atmospheric parameter. The temporal and geographic extent of observations worldwide remains relatively small, with many regions of the world (even whole continents and oceans), almost completely unrepresented by observational data. Measurements at pristine sites are particularly rare, but all the more valuable because such observations are necessary to estimate the pre-industrial baseline of aerosol and cloud related parameters that are needed to better understand the climate system and forecast future scenarios. As a partner of BACCHUS we began in September 2014 to operate an INP measurement network of four sampling stations, with a global geographic distribution. The stations are located at unique sites reaching from the Arctic to the equator: the Amazonian Tall Tower Observatory ATTO in Brazil, the Observatoire Volcanologique et Sismologique on the island of Martinique in the Caribbean Sea, the Zeppelin Observatory at Svalbard in the Norwegian Arctic and the Taunus Observatory near Frankfurt, Germany. Since 2014 samples were collected regularly by electrostatic precipitation of aerosol particles onto silicon substrates. The INP on the substrate are activated and analyzed in the isothermal static diffusion chamber FRIDGE at temperatures between -20°C and -30°C and relative humidity with respect to ice from 115 to 135%. Here we present data from the years 2015 and 2016 from this novel INP network and from selected campaign-based measurements from remote sites, including the Mt. Kenya GAW station. Acknowledgements The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) project BACCHUS under grant agreement No 603445 and the Deutsche Forschungsgemeinschaft (DFG) under the Research Unit FOR 1525 (INUIT).

  18. Using Network Sampling and Recruitment Data to Understand Social Structures Related to Community Health in a Population of People Who Inject Drugs in Rural Puerto Rico.

    Science.gov (United States)

    Coronado-García, Mayra; Thrash, Courtney R; Welch-Lazoritz, Melissa; Gauthier, Robin; Reyes, Juan Carlos; Khan, Bilal; Dombrowski, Kirk

    2017-06-01

    This research examined the social network and recruitment patterns of a sample of people who inject drugs (PWIDs) in rural Puerto Rico, in an attempt to uncover systematic clustering and between-group social boundaries that potentially influence disease spread. Respondent driven sampling was utilized to obtain a sample of PWID in rural Puerto Rico. Through eight initial "seeds", 317 injection drug users were recruited. Using recruitment patterns of this sample, estimates of homophily and affiliation were calculated using RDSAT. Analyses showed clustering within the social network of PWID in rural Puerto Rico. In particular, females showed a very high tendency to recruit male PWID, which suggests low social cohesion among female PWID. Results for (believed) HCV status at the time of interview indicate that HCV+ individuals were less likely to interact with HCV- individuals or those who were unaware of their status, and may be acting as "gatekeepers" to prevent disease spread. Individuals who participated in a substance use program were more likely to affiliate with one another. The use of speedballs was related to clustering within the network, in which individuals who injected this mixture were more likely to affiliate with other speedball users. Social clustering based on several characteristics and behaviors were found within the IDU population in rural Puerto Rico. RDS was effective in not only garnering a sample of PWID in rural Puerto Rico, but also in uncovering social clustering that can potentially influence disease spread among this population.

  19. Semantic labeling of high-resolution aerial images using an ensemble of fully convolutional networks

    Science.gov (United States)

    Sun, Xiaofeng; Shen, Shuhan; Lin, Xiangguo; Hu, Zhanyi

    2017-10-01

    High-resolution remote sensing data classification has been a challenging and promising research topic in the community of remote sensing. In recent years, with the rapid advances of deep learning, remarkable progress has been made in this field, which facilitates a transition from hand-crafted features designing to an automatic end-to-end learning. A deep fully convolutional networks (FCNs) based ensemble learning method is proposed to label the high-resolution aerial images. To fully tap the potentials of FCNs, both the Visual Geometry Group network and a deeper residual network, ResNet, are employed. Furthermore, to enlarge training samples with diversity and gain better generalization, in addition to the commonly used data augmentation methods (e.g., rotation, multiscale, and aspect ratio) in the literature, aerial images from other datasets are also collected for cross-scene learning. Finally, we combine these learned models to form an effective FCN ensemble and refine the results using a fully connected conditional random field graph model. Experiments on the ISPRS 2-D Semantic Labeling Contest dataset show that our proposed end-to-end classification method achieves an overall accuracy of 90.7%, a state-of-the-art in the field.

  20. Field Investigation Plan for 1301-N and 1325-N Facilities Sampling to Support Remedial Design

    International Nuclear Information System (INIS)

    Weiss, S. G.

    1998-01-01

    This field investigation plan (FIP) provides for the sampling and analysis activities supporting the remedial design planning for the planned removal action for the 1301-N and 1325-N Liquid Waste Disposal Facilities (LWDFs), which are treatment, storage,and disposal (TSD) units (cribs/trenches). The planned removal action involves excavation, transportation, and disposal of contaminated material at the Environmental Restoration Disposal Facility (ERDF).An engineering study (BHI 1997) was performed to develop and evaluate various options that are predominantly influenced by the volume of high- and low-activity contaminated soil requiring removal. The study recommended that additional sampling be performed to supplement historical data for use in the remedial design