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Sample records for network distance map

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

    Science.gov (United States)

    Deka, Lipika; Quddus, Mohammed

    2014-04-01

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

  2. Statistical Distance For Chaotic Maps

    CERN Document Server

    Johal, R S

    1998-01-01

    The purpose of this letter is to define a distance on the underlying phase space of a chaotic map, based on natural invariant density of the map. It is observed that for logistic map this distance is equivalent to Wootters' statistical distance. This distance becomes the Euclidean distance for a map with constant invariant density.

  3. Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks

    Directory of Open Access Journals (Sweden)

    Martin Alberto JM

    2009-01-01

    Full Text Available Abstract Background Prediction of protein structures from their sequences is still one of the open grand challenges of computational biology. Some approaches to protein structure prediction, especially ab initio ones, rely to some extent on the prediction of residue contact maps. Residue contact map predictions have been assessed at the CASP competition for several years now. Although it has been shown that exact contact maps generally yield correct three-dimensional structures, this is true only at a relatively low resolution (3–4 Å from the native structure. Another known weakness of contact maps is that they are generally predicted ab initio, that is not exploiting information about potential homologues of known structure. Results We introduce a new class of distance restraints for protein structures: multi-class distance maps. We show that Cα trace reconstructions based on 4-class native maps are significantly better than those from residue contact maps. We then build two predictors of 4-class maps based on recursive neural networks: one ab initio, or relying on the sequence and on evolutionary information; one template-based, or in which homology information to known structures is provided as a further input. We show that virtually any level of sequence similarity to structural templates (down to less than 10% yields more accurate 4-class maps than the ab initio predictor. We show that template-based predictions by recursive neural networks are consistently better than the best template and than a number of combinations of the best available templates. We also extract binary residue contact maps at an 8 Å threshold (as per CASP assessment from the 4-class predictors and show that the template-based version is also more accurate than the best template and consistently better than the ab initio one, down to very low levels of sequence identity to structural templates. Furthermore, we test both ab-initio and template-based 8

  4. Video surveillance using distance maps

    NARCIS (Netherlands)

    Schouten, Theo E.; Kuppens, Harco C.; van den Broek, Egon; Kehtarnavaz, Nasser; Laplante, Phillip A,

    2006-01-01

    Human vigilance is limited; hence, automatic motion and distance detection is one of the central issues in video surveillance. Hereby, many aspects are of importance, this paper specially addresses: efficiency, achieving real-time performance, accuracy, and robustness against various noise factors.

  5. Network Mapping with GIMME.

    Science.gov (United States)

    Beltz, Adriene M; Gates, Kathleen M

    2017-01-01

    Network science is booming! While the insights and images afforded by network mapping techniques are compelling, implementing the techniques is often daunting to researchers. Thus, the aim of this tutorial is to facilitate implementation in the context of GIMME, or group iterative multiple model estimation. GIMME is an automated network analysis approach for intensive longitudinal data. It creates person-specific networks that explain how variables are related in a system. The relations can signify current or future prediction that is common across people or applicable only to an individual. The tutorial begins with conceptual and mathematical descriptions of GIMME. It proceeds with a practical discussion of analysis steps, including data acquisition, preprocessing, program operation, a posteriori testing of model assumptions, and interpretation of results; throughout, a small empirical data set is analyzed to showcase the GIMME analysis pipeline. The tutorial closes with a brief overview of extensions to GIMME that may interest researchers whose questions and data sets have certain features. By the end of the tutorial, researchers will be equipped to begin analyzing the temporal dynamics of their heterogeneous time series data with GIMME.

  6. Patent Overlay Mapping: Visualizing Technological Distance

    CERN Document Server

    Kay, Luciano; Youtie, Jan; Porter, Alan L; Rafols, Ismael

    2012-01-01

    The purpose of this paper is to present a new global patent map that represents all technological categories, and a method to locate patent data of individual organizations and technological fields on the global map. This second patent overlay map technique is shown to be of potential interest to support competitive intelligence and policy decision-making. The global patent map is based on similarities in citing-to-cited relationships between categories of the International Patent Classification (IPC) of European Patent Office (EPO) patents from 2000 to 2006. This patent dataset, extracted from PatStat database, represents more than 760,000 patent records in more than 400 IPC categories. To illustrate the kind of analytical support offered by this approach, the paper shows the overlay of nanotechnology-related patenting activities of two companies and two different nanotechnology subfields on to the global patent map. The exercise shows the potential of patent overlay maps to visualize technological areas and...

  7. Interval data clustering using self-organizing maps based on adaptive Mahalanobis distances.

    Science.gov (United States)

    Hajjar, Chantal; Hamdan, Hani

    2013-10-01

    The self-organizing map is a kind of artificial neural network used to map high dimensional data into a low dimensional space. This paper presents a self-organizing map for interval-valued data based on adaptive Mahalanobis distances in order to do clustering of interval data with topology preservation. Two methods based on the batch training algorithm for the self-organizing maps are proposed. The first method uses a common Mahalanobis distance for all clusters. In the second method, the algorithm starts with a common Mahalanobis distance per cluster and then switches to use a different distance per cluster. This process allows a more adapted clustering for the given data set. The performances of the proposed methods are compared and discussed using artificial and real interval data sets. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Timed Fast Exact Euclidean Distance (tFEED) maps

    NARCIS (Netherlands)

    Kehtarnavaz, Nasser; Schouten, Theo E.; Laplante, Philip A.; Kuppens, Harco; van den Broek, Egon

    2005-01-01

    In image and video analysis, distance maps are frequently used. They provide the (Euclidean) distance (ED) of background pixels to the nearest object pixel. In a naive implementation, each object pixel feeds its (exact) ED to each background pixel; then the minimum of these values denotes the ED to

  9. Dynamic functional network connectivity using distance correlation

    Science.gov (United States)

    Rudas, Jorge; Guaje, Javier; Demertzi, Athena; Heine, Lizette; Tshibanda, Luaba; Soddu, Andrea; Laureys, Steven; Gómez, Francisco

    2015-01-01

    Investigations about the intrinsic brain organization in resting-state are critical for the understanding of healthy, pathological and pharmacological cerebral states. Recent studies on fMRI suggest that resting state activity is organized on large scale networks of coordinated activity, in the so called, Resting State Networks (RSNs). The assessment of the interactions among these functional networks plays an important role for the understanding of different brain pathologies. Current methods to quantify these interactions commonly assume that the underlying coordination mechanisms are stationary and linear through the whole recording of the resting state phenomena. Nevertheless, recent evidence suggests that rather than stationary, these mechanisms may exhibit a rich set of time-varying repertoires. In addition, these approaches do not consider possible non-linear relationships maybe linked to feed-back communication mechanisms between RSNs. In this work, we introduce a novel approach for dynamical functional network connectivity for functional magnetic resonance imaging (fMRI) resting activity, which accounts for non-linear dynamic relationships between RSNs. The proposed method is based on a windowed distance correlations computed on resting state time-courses extracted at single subject level. We showed that this strategy is complementary to the current approaches for dynamic functional connectivity and will help to enhance the discrimination capacity of patients with disorder of consciousness.

  10. Map of Life: Measuring and Visualizing Species' Relatedness with "Molecular Distance Maps"

    OpenAIRE

    Kari, Lila; Hill, Kathleen A.; Sayem, Abu Sadat; Bryans, Nathaniel; Davis, Katelyn; Dattani, Nikesh S.

    2013-01-01

    We propose a novel combination of methods that (i) portrays quantitative characteristics of a DNA sequence as an image, (ii) computes distances between these images, and (iii) uses these distances to output a map wherein each sequence is a point in a common Euclidean space. In the resulting "Molecular Distance Map" each point signifies a DNA sequence, and the geometric distance between any two points reflects the degree of relatedness between the corresponding sequences and species. Molecular...

  11. Kinetic distance and kinetic maps from molecular dynamics simulation

    CERN Document Server

    Noe, Frank

    2015-01-01

    Characterizing macromolecular kinetics from molecular dynamics (MD) simulations requires a distance metric that can distinguish slowly-interconverting states. Here we build upon diffusion map theory and define a kinetic distance for irreducible Markov processes that quantifies how slowly molecular conformations interconvert. The kinetic distance can be computed given a model that approximates the eigenvalues and eigenvectors (reaction coordinates) of the MD Markov operator. Here we employ the time-lagged independent component analysis (TICA). The TICA components can be scaled to provide a kinetic map in which the Euclidean distance corresponds to the kinetic distance. As a result, the question of how many TICA dimensions should be kept in a dimensionality reduction approach becomes obsolete, and one parameter less needs to be specified in the kinetic model construction. We demonstrate the approach using TICA and Markov state model (MSM) analyses for illustrative models, protein conformation dynamics in bovine...

  12. Very high precision survey equipment for great distances Surface surveys used to map out the surface network and the tunnelling machines then gyroscopically steered underground.

    CERN Multimedia

    1983-01-01

    At the beginning of the 1980s, CERN embarked on the enormous Large Electron-Positron Collider construction project. The excavation of the 27-kilometre LEP tunnel was a huge technical challenge. The tunnel-boring machines excavated the tunnel in 3.3 km octants and had to be operated with extraordinary precision to ensure that they reached their destination - the bottom of the next vertical shaft - precisely on target. The tunnel was excavated before high-performance instruments were developed for the construction of the Channel Tunnel. As no firms were willing to perform the surveying work, CERN's own surveyors, with experience from the SPS behind them, took up the challenge. At the surface, the surveyors established the world's most accurate geodetic network, performing measurements to an accuracy of 10-7, or 1mm per 10 km, using the Terrameter (see photo). The excavation of the tunnel was completed in 1988 and the finished tunnel's trajectory was found to diverge from the theoretical value specified by the p...

  13. Nanomechanical characterization by double-pass force-distance mapping

    Energy Technology Data Exchange (ETDEWEB)

    Dagdas, Yavuz S; Tekinay, Ayse B; Guler, Mustafa O; Dana, Aykutlu [UNAM Institute of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara (Turkey); Necip Aslan, M, E-mail: aykutlu@unam.bilkent.edu.tr [Department of Physics, Istanbul Technical University, Istanbul (Turkey)

    2011-07-22

    We demonstrate high speed force-distance mapping using a double-pass scheme. The topography is measured in tapping mode in the first pass and this information is used in the second pass to move the tip over the sample. In the second pass, the cantilever dither signal is turned off and the sample is vibrated. Rapid (few kHz frequency) force-distance curves can be recorded with small peak interaction force, and can be processed into an image. Such a double-pass measurement eliminates the need for feedback during force-distance measurements. The method is demonstrated on self-assembled peptidic nanofibers.

  14. Topographical maps as complex networks

    Science.gov (United States)

    da Fontoura Costa, Luciano; Diambra, Luis

    2005-02-01

    The neuronal networks in the mammalian cortex are characterized by the coexistence of hierarchy, modularity, short and long range interactions, spatial correlations, and topographical connections. Particularly interesting, the latter type of organization implies special demands on developing systems in order to achieve precise maps preserving spatial adjacencies, even at the expense of isometry. Although the object of intensive biological research, the elucidation of the main anatomic-functional purposes of the ubiquitous topographical connections in the mammalian brain remains an elusive issue. The present work reports on how recent results from complex network formalism can be used to quantify and model the effect of topographical connections between neuronal cells over the connectivity of the network. While the topographical mapping between two cortical modules is achieved by connecting nearest cells from each module, four kinds of network models are adopted for implementing intramodular connections, including random, preferential-attachment, short-range, and long-range networks. It is shown that, though spatially uniform and simple, topographical connections between modules can lead to major changes in the network properties in some specific cases, depending on intramodular connections schemes, fostering more effective intercommunication between the involved neuronal cells and modules. The possible implications of such effects on cortical operation are discussed.

  15. Python passive network mapping P2NMAP

    CERN Document Server

    Hosmer, Chet

    2015-01-01

    Python Passive Network Mapping: P2NMAP is the first book to reveal a revolutionary and open source method for exposing nefarious network activity. The ""Heartbleed"" vulnerability has revealed significant weaknesses within enterprise environments related to the lack of a definitive mapping of network assets. In Python Passive Network Mapping, Chet Hosmer shows you how to effectively and definitively passively map networks. Active or probing methods to network mapping have traditionally been used, but they have many drawbacks - they can disrupt operations, crash systems, and - most important

  16. Potential of Social Networking Sites for Distance Education Student Engagement

    Science.gov (United States)

    Lester, Jaime; Perini, Michael

    2010-01-01

    This chapter explores the potential of social networking sites for increasing student engagement for distance education learners. The authors present a modified student engagement model with a focus on the integration of technology, specifically social networking sites for community college distance education learners. The chapter concludes with…

  17. Network Mapping by Replaying Hyperbolic Growth

    OpenAIRE

    Papadopoulos, Fragkiskos; Psomas, Constantinos; Krioukov, Dmitri

    2012-01-01

    Recent years have shown a promising progress in understanding geometric underpinnings behind the structure, function, and dynamics of many complex networks in nature and society. However these promises cannot be readily fulfilled and lead to important practical applications, without a simple, reliable, and fast network mapping method to infer the latent geometric coordinates of nodes in a real network. Here we present HyperMap, a simple method to map a given real network to its hyperbolic spa...

  18. Pareto distance for multi-layer network analysis

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2013-01-01

    new research problems related to the extension of traditional single-layer network measures. In this paper we take a step forward over existing approaches by defining a new concept of geodesic distance that includes heterogeneous networks and connections with very limited assumptions regarding...... the strength of the connections. This is achieved by exploiting the concept of Pareto efficiency to define a simple and at the same time powerful measure that we call Pareto distance, of which geodesic distance is a particular case when a single layer (or network) is analyzed. The limited assumptions...

  19. Drawing Road Networks with Mental Maps.

    Science.gov (United States)

    Lin, Shih-Syun; Lin, Chao-Hung; Hu, Yan-Jhang; Lee, Tong-Yee

    2014-09-01

    Tourist and destination maps are thematic maps designed to represent specific themes in maps. The road network topologies in these maps are generally more important than the geometric accuracy of roads. A road network warping method is proposed to facilitate map generation and improve theme representation in maps. The basic idea is deforming a road network to meet a user-specified mental map while an optimization process is performed to propagate distortions originating from road network warping. To generate a map, the proposed method includes algorithms for estimating road significance and for deforming a road network according to various geometric and aesthetic constraints. The proposed method can produce an iconic mark of a theme from a road network and meet a user-specified mental map. Therefore, the resulting map can serve as a tourist or destination map that not only provides visual aids for route planning and navigation tasks, but also visually emphasizes the presentation of a theme in a map for the purpose of advertising. In the experiments, the demonstrations of map generations show that our method enables map generation systems to generate deformed tourist and destination maps efficiently.

  20. Going the distance for protein function prediction: a new distance metric for protein interaction networks.

    Science.gov (United States)

    Cao, Mengfei; Zhang, Hao; Park, Jisoo; Daniels, Noah M; Crovella, Mark E; Cowen, Lenore J; Hescott, Benjamin

    2013-01-01

    In protein-protein interaction (PPI) networks, functional similarity is often inferred based on the function of directly interacting proteins, or more generally, some notion of interaction network proximity among proteins in a local neighborhood. Prior methods typically measure proximity as the shortest-path distance in the network, but this has only a limited ability to capture fine-grained neighborhood distinctions, because most proteins are close to each other, and there are many ties in proximity. We introduce diffusion state distance (DSD), a new metric based on a graph diffusion property, designed to capture finer-grained distinctions in proximity for transfer of functional annotation in PPI networks. We present a tool that, when input a PPI network, will output the DSD distances between every pair of proteins. We show that replacing the shortest-path metric by DSD improves the performance of classical function prediction methods across the board.

  1. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    to map social networks and suggest how it can be used in software process improvement. We applied the mapping approach in a small software company to support the realization of new ways of improving software processes. The mapping approach was found useful in improving social networks, and thus furthers...

  2. Mapping change in large networks.

    Directory of Open Access Journals (Sweden)

    Martin Rosvall

    2010-01-01

    Full Text Available Change is a fundamental ingredient of interaction patterns in biology, technology, the economy, and science itself: Interactions within and between organisms change; transportation patterns by air, land, and sea all change; the global financial flow changes; and the frontiers of scientific research change. Networks and clustering methods have become important tools to comprehend instances of these large-scale structures, but without methods to distinguish between real trends and noisy data, these approaches are not useful for studying how networks change. Only if we can assign significance to the partitioning of single networks can we distinguish meaningful structural changes from random fluctuations. Here we show that bootstrap resampling accompanied by significance clustering provides a solution to this problem. To connect changing structures with the changing function of networks, we highlight and summarize the significant structural changes with alluvial diagrams and realize de Solla Price's vision of mapping change in science: studying the citation pattern between about 7000 scientific journals over the past decade, we find that neuroscience has transformed from an interdisciplinary specialty to a mature and stand-alone discipline.

  3. Applying weighted network measures to microarray distance matrices

    Science.gov (United States)

    Ahnert, S. E.; Garlaschelli, D.; Fink, T. M. A.; Caldarelli, G.

    2008-06-01

    In recent work we presented a new approach to the analysis of weighted networks, by providing a straightforward generalization of any network measure defined on unweighted networks. This approach is based on the translation of a weighted network into an ensemble of edges, and is particularly suited to the analysis of fully connected weighted networks. Here we apply our method to several such networks including distance matrices, and show that the clustering coefficient, constructed by using the ensemble approach, provides meaningful insights into the systems studied. In the particular case of two datasets from microarray experiments the clustering coefficient identifies a number of biologically significant genes, outperforming existing identification approaches.

  4. Applying weighted network measures to microarray distance matrices

    Energy Technology Data Exchange (ETDEWEB)

    Ahnert, S E [Theory of Condensed Matter Group, Cavendish Laboratory, JJ Thomson Avenue, Cambridge CB3 0HE (United Kingdom); Garlaschelli, D [Dipartimento di Fisica, Universita di Siena, Via Roma 56, 53100 Siena (Italy); Fink, T M A [Institut Curie, CNRS UMR 144, 26 rue d' Ulm, 75248 Paris (France); Caldarelli, G [INFM-CNR Istituto dei Sistemi Complessi and Dipartimento di Fisica Universita di Roma ' La Sapienza' Piazzale Moro 2, 00185 Roma (Italy)

    2008-06-06

    In recent work we presented a new approach to the analysis of weighted networks, by providing a straightforward generalization of any network measure defined on unweighted networks. This approach is based on the translation of a weighted network into an ensemble of edges, and is particularly suited to the analysis of fully connected weighted networks. Here we apply our method to several such networks including distance matrices, and show that the clustering coefficient, constructed by using the ensemble approach, provides meaningful insights into the systems studied. In the particular case of two datasets from microarray experiments the clustering coefficient identifies a number of biologically significant genes, outperforming existing identification approaches.

  5. Scalable Virtual Network Mapping Algorithm for Internet-Scale Networks

    Science.gov (United States)

    Yang, Qiang; Wu, Chunming; Zhang, Min

    The proper allocation of network resources from a common physical substrate to a set of virtual networks (VNs) is one of the key technical challenges of network virtualization. While a variety of state-of-the-art algorithms have been proposed in an attempt to address this issue from different facets, the challenge still remains in the context of large-scale networks as the existing solutions mainly perform in a centralized manner which requires maintaining the overall and up-to-date information of the underlying substrate network. This implies the restricted scalability and computational efficiency when the network scale becomes large. This paper tackles the virtual network mapping problem and proposes a novel hierarchical algorithm in conjunction with a substrate network decomposition approach. By appropriately transforming the underlying substrate network into a collection of sub-networks, the hierarchical virtual network mapping algorithm can be carried out through a global virtual network mapping algorithm (GVNMA) and a local virtual network mapping algorithm (LVNMA) operated in the network central server and within individual sub-networks respectively with their cooperation and coordination as necessary. The proposed algorithm is assessed against the centralized approaches through a set of numerical simulation experiments for a range of network scenarios. The results show that the proposed hierarchical approach can be about 5-20 times faster for VN mapping tasks than conventional centralized approaches with acceptable communication overhead between GVNCA and LVNCA for all examined networks, whilst performs almost as well as the centralized solutions.

  6. Project Work in Networked Distance Education

    DEFF Research Database (Denmark)

    Knudsen, Morten; Helbo, Jan; Jensen, Lars Peter

    2000-01-01

    Problem oriented project work has been the foundation for the educational system at Aalborg University since its start 25 years ago. The duration of each student project is one semester, and the students spend half of their time working on the project in groups of typically 5-6 persons...... Information Technology distance education is described. The program is offered through Open University, and the students have a BSc degree or equivalent and at least 2 years of relevant professional experience - and a full-time job. The students are assumed to study 20 hours per week, half of the time being...

  7. A Multidomain Survivable Virtual Network Mapping Algorithm

    Directory of Open Access Journals (Sweden)

    Xiancui Xiao

    2017-01-01

    Full Text Available Although the existing networks are more often deployed in the multidomain environment, most of existing researches focus on single-domain networks and there are no appropriate solutions for the multidomain virtual network mapping problem. In fact, most studies assume that the underlying network can operate without any interruption. However, physical networks cannot ensure the normal provision of network services for external reasons and traditional single-domain networks have difficulties to meet user needs, especially for the high security requirements of the network transmission. In order to solve the above problems, this paper proposes a survivable virtual network mapping algorithm (IntD-GRC-SVNE that implements multidomain mapping in network virtualization. IntD-GRC-SVNE maps the virtual communication networks onto different domain networks and provides backup resources for virtual links which improve the survivability of the special networks. Simulation results show that IntD-GRC-SVNE can not only improve the survivability of multidomain communications network but also render the network load more balanced and greatly improve the network acceptance rate due to employment of GRC (global resource capacity.

  8. Project Work in Networked Distance Education

    DEFF Research Database (Denmark)

    Knudsen, Morten; Helbo, Jan; Jensen, Lars Peter

    2000-01-01

    Problem oriented project work has been the foundation for the educational system at Aalborg University since its start 25 years ago. The duration of each student project is one semester, and the students spend half of their time working on the project in groups of typically 5-6 persons......-study, whereas the project study form is based on collaboration and dialogue. Consequently, successful implementation of project work in distance education requires extensive utilisation of new information and communication technology. In this paper the experiences of project work in a new Master of Industrial...... devoted to courses and the other half to project work. A computer conference system, LuvitÒ provides facilities for the courses, as well as structured synchronous and asynchronous communication. Eight times per year two-day seminars are held at the university for intensive lectures, project work...

  9. Rapid mapping of volumetric machine errors using distance measurements

    Energy Technology Data Exchange (ETDEWEB)

    Krulewich, D.A.

    1998-04-01

    This paper describes a relatively inexpensive, fast, and easy to execute approach to maping the volumetric errors of a machine tool, coordinate measuring machine, or robot. An error map is used to characterize a machine or to improve its accuracy by compensating for the systematic errors. The method consists of three steps: (1) models the relationship between volumetric error and the current state of the machine, (2) acquiring error data based on distance measurements throughout the work volume; and (3)fitting the error model using the nonlinear equation for the distance. The error model is formulated from the kinematic relationship among the six degrees of freedom of error an each moving axis. Expressing each parametric error as function of position each is combined to predict the error between the functional point and workpiece, also as a function of position. A series of distances between several fixed base locations and various functional points in the work volume is measured using a Laser Ball Bar (LBB). Each measured distance is a non-linear function dependent on the commanded location of the machine, the machine error, and the location of the base locations. Using the error model, the non-linear equation is solved producing a fit for the error model Also note that, given approximate distances between each pair of base locations, the exact base locations in the machine coordinate system determined during the non-linear filling procedure. Furthermore, with the use of 2048 more than three base locations, bias error in the measuring instrument can be removed The volumetric errors of three-axis commercial machining center have been mapped using this procedure. In this study, only errors associated with the nominal position of the machine were considered Other errors such as thermally induced and load induced errors were not considered although the mathematical model has the ability to account for these errors. Due to the proprietary nature of the projects we are

  10. Consensus of Multiagent Systems With Distance-Dependent Communication Networks.

    Science.gov (United States)

    Jing, Gangshan; Zheng, Yuanshi; Wang, Long

    In this paper, we study the consensus problem of discrete-time and continuous-time multiagent systems with distance-dependent communication networks, respectively. The communication weight between any two agents is assumed to be a nonincreasing function of their distance. First, we consider the networks with fixed connectivity. In this case, the interaction between adjacent agents always exists but the influence could possibly become negligible if the distance is long enough. We show that consensus can be reached under arbitrary initial states if the decay rate of the communication weight is less than a given bound. Second, we study the networks with distance-dependent connectivity. It is assumed that any two agents interact with each other if and only if their distance does not exceed a fixed range. With the validity of some conditions related to the property of the initial communication graph, we prove that consensus can be achieved asymptotically. Third, we present some applications of the main results to opinion consensus problems and formation control problems. Finally, several simulation examples are presented to illustrate the effectiveness of the theoretical findings.In this paper, we study the consensus problem of discrete-time and continuous-time multiagent systems with distance-dependent communication networks, respectively. The communication weight between any two agents is assumed to be a nonincreasing function of their distance. First, we consider the networks with fixed connectivity. In this case, the interaction between adjacent agents always exists but the influence could possibly become negligible if the distance is long enough. We show that consensus can be reached under arbitrary initial states if the decay rate of the communication weight is less than a given bound. Second, we study the networks with distance-dependent connectivity. It is assumed that any two agents interact with each other if and only if their distance does not exceed a fixed

  11. Mapping Technology Space by Normalizing Patent Networks

    OpenAIRE

    Alstott, Jeff; Triulzi, Giorgio; Yan, Bowen; Luo, Jianxi

    2015-01-01

    Technology is a complex system, with technologies relating to each other in a space that can be mapped as a network. The technology network's structure can reveal properties of technologies and of human behavior, if it can be mapped accurately. Technology networks have been made from patent data, using several measures of proximity. These measures, however, are influenced by factors of the patenting system that do not reflect technologies or their proximity. We introduce a method to precisely...

  12. Reverberation Mapping: Masses and Distance and Size, Oh My!

    Science.gov (United States)

    Denney, K.

    2013-10-01

    I review the technique of reverberation mapping and describe its use in the direct, dynamical mass measurement of actively accreting supermassive black holes located at the centers of active galactic nuclei (AGN). I discuss continued challenges to this method that current and planned observations are working to overcome. I also present some additional applications of the reverberation mapping measurements, discussing how reverberation time delays used to probe the size of the broad line-emitting region not only allow for these direct mass measurements, but also, through empirically calibrated scaling relationships, provide a method for indirect mass estimates of black holes in large samples of distant quasars. Furthermore, these broad-line region size measurements also have the potential to turn AGN into cosmic distance probes, as the measured size of this region scales with intrinsic AGN luminosity. With regard to these applications, I address some of the continuing sources of systematic uncertainties with which I am currently concerned, as well as work that is being done in an attempt to understand and mitigate these systematics.

  13. A distance constrained synaptic plasticity model of C. elegans neuronal network

    Science.gov (United States)

    Badhwar, Rahul; Bagler, Ganesh

    2017-03-01

    Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

  14. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 2: Fiber optic technology and long distance networks

    Science.gov (United States)

    1986-01-01

    The study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the Executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  15. A Bayesian Network Approach to Ontology Mapping

    National Research Council Canada - National Science Library

    Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun

    2005-01-01

    .... In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs...

  16. Comparing two distance measures in the spatial mapping of food deserts: The case of Petržalka, Slovakia

    Directory of Open Access Journals (Sweden)

    Bilková Kristína

    2017-06-01

    Full Text Available Over the last twenty years or so, researchers’ attention to the issue of food deserts has increased in the geographical literature. Accessibility to large-scale retail units is one of the essential and frequently-used indicators leading to the identification and mapping of food deserts. Numerous accessibility measures of various types are available for this purpose. Euclidean distance and street network distance rank among the most frequently-used approaches, although they may lead to slightly different results. The aim of this paper is to compare various approaches to the accessibility to food stores and to assess the differences in the results gained by these methods. Accessibility was measured for residential block centroids, with applications of various accessibility measures in a GIS environment. The results suggest a strong correspondence between Euclidean distance and a little more accurate street network distance approach, applied in the case of the urban environment of Bratislava-Petržalka, Slovakia.

  17. Network visualization: mapping Shakespeare's tragedies

    OpenAIRE

    Grandjean, Martin

    2015-01-01

    Blogpost, http://www.martingrandjean.ch/network-visualization-shakespeare/; Are Shakespeare's tragedies all structured in the same way? Are the characters rather isolated, grouped, all connected? Narration, even fictional, contains a network of interacting characters. Constituting a well defined corpus, the eleven Shakespearean tragedies can easily be compared: We propose here a network visualization in which each character is represented by a node connected with the characters that appear in...

  18. Technology Acceptance and Social Networking in Distance Learning

    Directory of Open Access Journals (Sweden)

    Barry Davidson

    2003-04-01

    Full Text Available This study examines the use of integrated communication and engineering design tools in a distributed learning environment. We examined students' attitudes toward the technology using two different approaches. First, we utilized the technology acceptance model to investigate the attitude formation process. Then, to investigate how attitudes changed over time, we applied social information processing model using social network analysis method. Using the technology acceptance model, we were able to demonstrate that students’ initial expectation affected the perceptions of, attitudes toward, and use of the system. With social network analysis, we found that one’s attitude change was significantly influenced by other students’ attitude changes. We discussed the uniqueness of distance learning environments in the context of social influence research and how studies of distance learning could contribute to the research on the social influence of technology use.

  19. Mapping standards for home networking

    NARCIS (Netherlands)

    Kaa, G. van de; Hartog, F.T.H. den; Vries, H.J. de

    2009-01-01

    In this study, we apply a step-by-step approach for the identification of standards for home networking. We develop a classification and we use this classification to categorize sixty-four (sets of) standards. By developing this categorization, we have brought order to the chaos of home networking

  20. Mapping and characterization of LCA networks

    DEFF Research Database (Denmark)

    Bjørn, Anders; Owsianiak, Mikolaj; Laurent, Alexis

    2013-01-01

    Purpose: The aims of this study were to provide an up-todate overview of global, regional and local networks supporting life cycle thinking and to characterize them according to their structure and activities. Methods: Following a tentative life cycle assessment (LCA) network definition, a mapping...... was performed based on (1) a literature search, (2) a web search and (3) an inquiry to stakeholders distributed via the two largest LCA fora. Networks were characterized based on responses from a survey. Results and discussion: We identified 100 networks, of which 29 fulfilled all six criteria composing our...... tentative network definition (the remaining fulfilled four to five criteria). The networks are mainly located in Europe and the USA, whilst Africa, the Middle East and Central Asia are less covered regions. The survey results (from 25 network responses) indicate that LCA networks appear to be primarily...

  1. An Improved Map-Matching Technique Based on the Fréchet Distance Approach for Pedestrian Navigation Services

    Directory of Open Access Journals (Sweden)

    Yoonsik Bang

    2016-10-01

    Full Text Available Wearable and smartphone technology innovations have propelled the growth of Pedestrian Navigation Services (PNS. PNS need a map-matching process to project a user’s locations onto maps. Many map-matching techniques have been developed for vehicle navigation services. These techniques are inappropriate for PNS because pedestrians move, stop, and turn in different ways compared to vehicles. In addition, the base map data for pedestrians are more complicated than for vehicles. This article proposes a new map-matching method for locating Global Positioning System (GPS trajectories of pedestrians onto road network datasets. The theory underlying this approach is based on the Fréchet distance, one of the measures of geometric similarity between two curves. The Fréchet distance approach can provide reasonable matching results because two linear trajectories are parameterized with the time variable. Then we improved the method to be adaptive to the positional error of the GPS signal. We used an adaptation coefficient to adjust the search range for every input signal, based on the assumption of auto-correlation between consecutive GPS points. To reduce errors in matching, the reliability index was evaluated in real time for each match. To test the proposed map-matching method, we applied it to GPS trajectories of pedestrians and the road network data. We then assessed the performance by comparing the results with reference datasets. Our proposed method performed better with test data when compared to a conventional map-matching technique for vehicles.

  2. An Improved Map-Matching Technique Based on the Fréchet Distance Approach for Pedestrian Navigation Services.

    Science.gov (United States)

    Bang, Yoonsik; Kim, Jiyoung; Yu, Kiyun

    2016-10-22

    Wearable and smartphone technology innovations have propelled the growth of Pedestrian Navigation Services (PNS). PNS need a map-matching process to project a user's locations onto maps. Many map-matching techniques have been developed for vehicle navigation services. These techniques are inappropriate for PNS because pedestrians move, stop, and turn in different ways compared to vehicles. In addition, the base map data for pedestrians are more complicated than for vehicles. This article proposes a new map-matching method for locating Global Positioning System (GPS) trajectories of pedestrians onto road network datasets. The theory underlying this approach is based on the Fréchet distance, one of the measures of geometric similarity between two curves. The Fréchet distance approach can provide reasonable matching results because two linear trajectories are parameterized with the time variable. Then we improved the method to be adaptive to the positional error of the GPS signal. We used an adaptation coefficient to adjust the search range for every input signal, based on the assumption of auto-correlation between consecutive GPS points. To reduce errors in matching, the reliability index was evaluated in real time for each match. To test the proposed map-matching method, we applied it to GPS trajectories of pedestrians and the road network data. We then assessed the performance by comparing the results with reference datasets. Our proposed method performed better with test data when compared to a conventional map-matching technique for vehicles.

  3. Network mapping and usage determination

    CSIR Research Space (South Africa)

    Senekal, FP

    2007-07-01

    Full Text Available detection. Based on this information, topology determination techniques can be applied to infer network structure from the information. Techniques to visualise the information are discussed. IP geolocation (the ability to associate a geographical coordinate...

  4. MetricMap: an embedding technique for processing distance-based queries in metric spaces.

    Science.gov (United States)

    Wang, Jason T L; Wang, Xiong; Shasha, Dennis; Zhang, Kaizhong

    2005-10-01

    In this paper, we present an embedding technique, called MetricMap, which is capable of estimating distances in a pseudometric space. Given a database of objects and a distance function for the objects, which is a pseudometric, we map the objects to vectors in a pseudo-Euclidean space with a reasonably low dimension while preserving the distance between two objects approximately. Such an embedding technique can be used as an approximate oracle to process a broad class of distance-based queries. It is also adaptable to data mining applications such as data clustering and classification. We present the theory underlying MetricMap and conduct experiments to compare MetricMap with other methods including MVP-tree and M-tree in processing the distance-based queries. Experimental results on both protein and RNA data show the good performance and the superiority of MetricMap over the other methods.

  5. Mapping Research Trends from 35 Years of Publications in "Distance Education"

    Science.gov (United States)

    Zawacki-Richter, Olaf; Naidu, Som

    2016-01-01

    This article maps out trends in distance education research and scholarship from 35 years of publications in the "Distance Education" journal. Titles and abstracts of 515 full papers were analyzed using the text-mining tool Leximancer™ to identify and describe themes in distance education research covered by these publications in the…

  6. Three Dimensional Fast Exact Euclidean Distance (3D-FEED) Maps

    NARCIS (Netherlands)

    Latecki, L.J.; Schouten, Theo E.; Mount, D.M.; Kuppens, Harco C.; Wu, A.Y.; van den Broek, Egon

    2006-01-01

    In image and video analysis, distance maps are frequently used. They provide the (Euclidean) distance (ED) of background pixels to the nearest object pixel. Recently, the Fast Exact Euclidean Distance (FEED) transformation was launched. In this paper, we present the three dimensional (3D) version of

  7. Epidemic spread over networks with agent awareness and social distancing

    KAUST Repository

    Paarporn, Keith

    2016-04-20

    We study an SIS epidemic model over an arbitrary connected network topology when the agents receive personalized information about the current epidemic state. The agents utilize their available information to either reduce interactions with their neighbors (social distancing) when they believe the epidemic is currently prevalent or resume normal interactions when they believe there is low risk of becoming infected. The information is a weighted combination of three sources: 1) the average states of nodes in contact neighborhoods 2) the average states of nodes in an information network 3) a global broadcast of the average epidemic state of the network. A 2n-state Markov Chain is first considered to model the disease dynamics with awareness, from which a mean-field discrete-time n-state dynamical system is derived, where each state corresponds to an agent\\'s probability of being infected. The nonlinear model is a lower bound of its linearized version about the origin. Hence, global stability of the origin (the diseasefree equilibrium) in the linear model implies global stability in the nonlinear model. When the origin is not stable, we show the existence of a nontrivial fixed point in the awareness model, which obeys a strict partial order in relation to the nontrivial fixed point of the dynamics without distancing. In simulations, we define two performance metrics to understand the effectiveness agent awareness has in reducing the spread of an epidemic. © 2015 IEEE.

  8. Mapping biological systems to network systems

    CERN Document Server

    Rathore, Heena

    2016-01-01

    The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

  9. Visualization of neural networks using saliency maps

    DEFF Research Database (Denmark)

    Mørch, Niels J.S.; Kjems, Ulrik; Hansen, Lars Kai

    1995-01-01

    The saliency map is proposed as a new method for understanding and visualizing the nonlinearities embedded in feedforward neural networks, with emphasis on the ill-posed case, where the dimensionality of the input-field by far exceeds the number of examples. Several levels of approximations...

  10. Networked curricula: fostering transnational partnership in open and distance learning

    Directory of Open Access Journals (Sweden)

    María Luz Cacheiro-González

    2013-05-01

    Full Text Available Transnational Networked Curricula (TNC provides many benefits to the institutions that offer them as well as to the different stakeholders involved, not only the students but also the academics, the institutions as a whole, and the wider society. Supporting Higher Education Institutions in enhancing and implementing international networked practices in virtual campus building is the main aim of the NetCU project, which has been developed by the EADTU, in partnership with 14 member organizations, from 2009 to 2012. The project outcomes intend to facilitate the future set-up of networked curricula in Higher Education institutions and potentially lead to more transnational partnerships in Open and Distance Education (ODE and blended learning, showing challenges, obstacles and ways to overcome them. This paper presents the main products developed in the project, assesses its completeness and usage, and discusses on the challenges of curricula networking starting from the ideas and opinions shared in different stakeholders workshops organized under the NetCU project.

  11. MIDER: network inference with mutual information distance and entropy reduction.

    Directory of Open Access Journals (Sweden)

    Alejandro F Villaverde

    Full Text Available The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species. It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html. The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good

  12. MIDER: network inference with mutual information distance and entropy reduction.

    Science.gov (United States)

    Villaverde, Alejandro F; Ross, John; Morán, Federico; Banga, Julio R

    2014-01-01

    The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide

  13. water quality assessment and mapping using inverse distance ...

    African Journals Online (AJOL)

    USER

    Several researchers have studied the water quality of the upper and lower stretches of River Kaduna with little on the middle stretch of the river. Besides, no work has ever been done on mapping the water quality of the said river. Hence, the middle stretch of River Kaduna was monitored for 12 months starting from June, ...

  14. Don't Stop Believing: Mapping Distance Learners' Research Journeys

    Science.gov (United States)

    Brahme, Maria E.; Gabriel, Lizette; Stenis, Paul V.

    2016-01-01

    Journey mapping, a method of collecting data that illustrates individuals' paths toward a specific goal, was originally developed for use in retail/customer service environments. Much of the literature describes its application in examining customer behavior when navigating merchants' Websites, allowing researchers to examine the effectiveness,…

  15. Effects of distance-dependent delay on small-world neuronal networks.

    Science.gov (United States)

    Zhu, Jinjie; Chen, Zhen; Liu, Xianbin

    2016-04-01

    We study firing behaviors and the transitions among them in small-world noisy neuronal networks with electrical synapses and information transmission delay. Each neuron is modeled by a two-dimensional Rulkov map neuron. The distance between neurons, which is a main source of the time delay, is taken into consideration. Through spatiotemporal patterns and interspike intervals as well as the interburst intervals, the collective behaviors are revealed. It is found that the networks switch from resting state into intermittent firing state under Gaussian noise excitation. Initially, noise-induced firing behaviors are disturbed by small time delays. Periodic firing behaviors with irregular zigzag patterns emerge with an increase of the delay and become progressively regular after a critical value is exceeded. More interestingly, in accordance with regular patterns, the spiking frequency doubles compared with the former stage for the spiking neuronal network. A growth of frequency persists for a larger delay and a transition to antiphase synchronization is observed. Furthermore, it is proved that these transitions are generic also for the bursting neuronal network and the FitzHugh-Nagumo neuronal network. We show these transitions due to the increase of time delay are robust to the noise strength, coupling strength, network size, and rewiring probability.

  16. An Investigation of the Reliability of Knowledge Measures Through Relational Mapping in Joint Military Environments: Knowledge, Models and Tools to Improve the Effectiveness of Naval Distance Learning

    Science.gov (United States)

    2006-06-01

    v Introduction...Tools to Improve the Effectiveness of Naval Distance Learning v AN INVESTIGATION OF THE RELIABILITY OF KNOWLEDGE MEASURES THROUGH RELATIONAL MAPPING IN...Klein (1999). SNovak and Gowin (1984). Shavelson (Ruiz-Primo, Schultz, Li, & Shavelson, 2001) Referent-based Compares the network Compares the semantic

  17. Long-distance pulse propagation on high-frequency dissipative nonlinear transmission lines/resonant tunneling diode line cascaded maps

    Energy Technology Data Exchange (ETDEWEB)

    Klofai, Yerima [Department of Physics, Higher Teacher Training College, University of Maroua, PO Box 46 Maroua (Cameroon); Essimbi, B Z [Department of Physics, Faculty of Science, University of Yaounde 1, PO Box 812 Yaounde (Cameroon); Jaeger, D, E-mail: bessimb@yahoo.fr [ZHO, Optoelectronik, Universitaet Duisburg-Essen, D-47048 Duisburg (Germany)

    2011-10-15

    Pulse propagation on high-frequency dissipative nonlinear transmission lines (NLTLs)/resonant tunneling diode line cascaded maps is investigated for long-distance propagation of short pulses. Applying perturbative analysis, we show that the dynamics of each line is reduced to an expanded Korteweg-de Vries-Burgers equation. Moreover, it is found by computer experiments that the soliton developed in NLTLs experiences an exponential amplitude decay on the one hand and an exponential amplitude growth on the other. As a result, the behavior of a pulse in special electrical networks made of concatenated pieces of lines is closely similar to the transmission of information in optical/electrical communication systems.

  18. ShakeMap at the Pacific Northwest Seismic Network

    Science.gov (United States)

    Hartog, R.; Bodin, P.; Gomberg, J.; Gustafson, B.; Malone, S.; Palmer, S.; Pratt, T.; Steele, B.; Vidale, J.; Wald, D.; Weaver, C.; Wong, I.

    2007-12-01

    We summarize efforts to tailor ShakeMap to the Pacific Northwest Seismic Network (PNSN), and to increase the resolution in the major urban areas. Our initial implementation of ShakeMap employed parameters based on data from mostly larger earthquakes outside the Pacific Northwest. The PNSN automatically generates a 45- arcsec ShakeMap for any earthquake of Md ≥ 3.0 in the Puget Sound region and for Md ≥ 4.0 earthquakes in Washington and Oregon. ShakeMap uses 3-component, real-time data from 91 strong motion, 34 broadband, and 70 Earthscope Transportable Array stations. We also automatically incorporate data from dial- up stations of the National Strong Motion Program. High-resolution (7.2 arcsec) ShakeMaps for the Seattle area have just come on-line thanks to the availability of a new, more detailed geologic map. We use data from the PNSN and other sources to derive new region-specific ground motion attenuation relations and site corrections. Preliminary results suggest that default attenuation relations included with the ShakeMap package over-predict Pacific Northwest ground motions, especially at larger distances and for deep (≥ 20km) earthquakes. We will make similar comparisons with the Next Generation Attenuation relations, to be used in future ShakeMap releases, and modify the relations if warranted. To improve site corrections we compared site amplification measurements and local magnitude residuals (available for most of the PNSN stations) to measured values of Vs30 at co-located and nearby sites. These correlate well and thus provide useful proxies for Vs30 for use in ShakeMap. We also found correlations between Vs30 estimates and the age and rock type of mapped geologic units, providing a geologically constrained means of interpolating between sites with more direct Vs30 estimates. Finally, our ShakeMaps will improve because we continue to add stations to the PNSN, providing additional direct measures of ground motion.

  19. Evaluation of Virtual Tactile Dots on Touchscreens in Map Reading: Perception of Distance and Direction

    OpenAIRE

    Watanabe, Tetsuya; Kaga, Hirotsugu; Yagi, Tsubasa

    2017-01-01

    In order to assist blind people in using a flat touchscreen, “virtual” tactile dots which feedback either of or both speech and vibration when touched have been proposed. In this paper, we investigated their effectiveness in map reading application. We conducted two experiments with eight blind participants in which participants perceived the distance and direction between two virtual tactile dots. Their results show that the perception of distance and direction by virtual tactile dots was ac...

  20. VISUAL UAV TRAJECTORY PLAN SYSTEM BASED ON NETWORK MAP

    Directory of Open Access Journals (Sweden)

    X. L. Li

    2012-07-01

    Full Text Available The base map of the current software UP-30 using in trajectory plan for Unmanned Aircraft Vehicle is vector diagram. UP-30 draws navigation points manually. But in the field of operation process, the efficiency and the quality of work is influenced because of insufficient information, screen reflection, calculate inconveniently and other factors. If we do this work in indoor, the effect of external factors on the results would be eliminated, the network earth users can browse the free world high definition satellite images through downloading a client software, and can export the high resolution image by standard file format. This brings unprecedented convenient of trajectory plan. But the images must be disposed by coordinate transformation, geometric correction. In addition, according to the requirement of mapping scale ,camera parameters and overlap degree we can calculate exposure hole interval and trajectory distance between the adjacent trajectory automatically . This will improve the degree of automation of data collection. Software will judge the position of next point according to the intersection of the trajectory and the survey area and ensure the position of point according to trajectory distance. We can undertake the points artificially. So the trajectory plan is automatic and flexible. Considering safety, the date can be used in flying after simulating flight. Finally we can export all of the date using a key

  1. The Semantic Distance Task: Quantifying Semantic Distance with Semantic Network Path Length

    Science.gov (United States)

    Kenett, Yoed N.; Levi, Effi; Anaki, David; Faust, Miriam

    2017-01-01

    Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We…

  2. Surname distribution in France: a distance analysis by a distorted geographical map.

    Science.gov (United States)

    Mourrieras, B; Darlu, P; Hochez, J; Hazout, S

    1995-01-01

    The distribution of surnames in 90 distinct regions in France during two successive periods, 1889-1915 and 1916-1940, is analysed from the civil birth registers of the 36,500 administrative units in France. A new approach, called 'Mobile Site Method' (MSM), is developed to allow representation of a surname distance matrix by a distorted geographical map. A surname distance matrix between the various regions in France is first calculated, then a distorted geographical map called the 'surname similarity map' is built up from the surname distances between regions. To interpret this map we draw (a) successive map contours obtained during the step-by-step distortion process, revealing zones of high surname dissimilarity, and (b) maps in grey levels representing the displacement magnitude, and allowing the segmentation of the geographical and surname maps into 'homogeneous surname zones'. By integrating geography and surname information in the same analysis, and by comparing results obtained for the two successive periods, the MSM approach produces convenient maps showing: (a) 'regionalism' of some peripheral populations such as Pays Basque, Alsace, Corsica and Brittany; (b) the presence of preferential axes of communications (Rhodanian corridor, Garonne valley); (c) barriers such as the Central Massif, Vosges; (d) the weak modifications of the distorted maps associated with the two periods studied suggest an extension (but limited) of the tendency of surname uniformity in France. These results are interpreted, in the nineteenth- and twentieth century context, as the consequences of a slow process of local migrations occurring over a long period of time.

  3. Attitudes and cognitive distances: On the non-unitary and flexible nature of cognitive maps.

    Science.gov (United States)

    Carbon, Claus-Christian; Hesslinger, Vera M

    2013-01-01

    Spatial relations of our environment are represented in cognitive maps. These cognitive maps are prone to various distortions (e.g., alignment and hierarchical effects) caused by basic cognitive factors (such as perceptual and conceptual reorganization) but also by affectively loaded and attitudinal influences. Here we show that even differences in attitude towards a single person representing a foreign country (here Barack Obama and the USA) can be related to drastic differences in the cognitive representation of distances concerning that country. Europeans who had a positive attitude towards Obama's first presidential program estimated distances between US and European cities as being much smaller than did people who were skeptical or negative towards Obama's ideas. On the basis of this result and existing literature, arguments on the non-unitary and flexible nature of cognitive maps are discussed.

  4. Mapping Neural Network Derived from the Parzen Window Estimator

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Hartmann, U.

    1992-01-01

    The article presents a general theoretical basis for the construction of mapping neural networks. The theory is based on the Parzen Window estimator for......The article presents a general theoretical basis for the construction of mapping neural networks. The theory is based on the Parzen Window estimator for...

  5. Pairwise-Distance-Analysis-Driven Dimensionality Reduction Model with Double Mappings for Hyperspectral Image Visualization

    Directory of Open Access Journals (Sweden)

    Yi Long

    2015-06-01

    Full Text Available This paper describes a novel strategy for the visualization of hyperspectral imagery based on the analysis of image pixel pairwise distances. The goal of this approach is to generate a final color image with excellent interpretability and high contrast at the cost of distorting a few pairwise distances. Specifically, the principle of equal variance is introduced to divide all hyperspectral bands into three subgroups and to ensure the energy is distributed uniformly between them, as in natural color images. Then, after detecting both normal and outlier pixels, these three subgroups are mapped into three color components of the output visualization using two different mapping (i.e., dimensionality reduction schemes for the two types of pixels. The widely-used multidimensional scaling (MDS is used for normal pixels and a new objective function, taking into account the weighting of pairwise distances, is presented for the outlier pixels. The pairwise distance weighting is designed such that small pairwise distances between the outliers and their respective neighbors are emphasized and large deviations are suppressed. This produces an image with high contrast and good interpretability while retaining the detailed information content. The proposed algorithm is compared with several state-of-the-art visualization techniques and evaluated on the well-known AVIRIS hyperspectral images. The effectiveness of the proposed strategy is substantiated both visually and quantitatively.

  6. Concept mapping and network analysis: an analytic approach to measure ties among constructs.

    Science.gov (United States)

    Goldman, Alyssa W; Kane, Mary

    2014-12-01

    Group concept mapping is a mixed-methods approach that helps a group visually represent its ideas on a topic of interest through a series of related maps. The maps and additional graphics are useful for planning, evaluation and theory development. Group concept maps are typically described, interpreted and utilized through points, clusters and distances, and the implications of these features in understanding how constructs relate to one another. This paper focuses on the application of network analysis to group concept mapping to quantify the strength and directionality of relationships among clusters. The authors outline the steps of this analysis, and illustrate its practical use through an organizational strategic planning example. Additional benefits of this analysis to evaluation projects are also discussed, supporting the overall utility of this supplemental technique to the standard concept mapping methodology. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Estimating Traffic and Anomaly Maps via Network Tomography

    OpenAIRE

    Mardani, Morteza; Giannakis, Georgios B.

    2014-01-01

    Mapping origin-destination (OD) network traffic is pivotal for network management and proactive security tasks. However, lack of sufficient flow-level measurements as well as potential anomalies pose major challenges towards this goal. Leveraging the spatiotemporal correlation of nominal traffic, and the sparse nature of anomalies, this paper brings forth a novel framework to map out nominal and anomalous traffic, which treats jointly important network monitoring tasks including traffic estim...

  8. Species turnover and geographic distance in an urban river network

    DEFF Research Database (Denmark)

    Rouquette, James R.; Dallimer, Martin; Armsworth, Paul R.

    2013-01-01

    of the habitat or topographic features of the landscape and the means of dispersal of the organism. River networks, in particular in human-modified landscapes, are a striking example of such a situation. Here, we use data for both aquatic and terrestrial organisms across an urban river network to examine...... patterns of species turnover and to determine whether these patterns differ between different taxonomic groups. LocationSheffield area, UK. MethodsAquatic (macroinvertebrates, diatoms) and terrestrial (birds, plants, butterflies) organisms were surveyed at 41 sites across an urban river network. We...

  9. Learners’ views regarding the use of social networking sites in distance learning

    National Research Council Canada - National Science Library

    Özmen, Büşra; Atıcı, Bünyamin

    2014-01-01

      In this study, it was aimed to examine the use of learning management systems supported by social networking sites in distance education and to determine the views of learners regarding these platforms...

  10. Visualizing Article Similarities via Sparsified Article Network and Map Projection for Systematic Reviews.

    Science.gov (United States)

    Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin

    2017-01-01

    Systematic Reviews (SRs) of biomedical literature summarize evidence from high-quality studies to inform clinical decisions, but are time and labor intensive due to the large number of article collections. Article similarities established from textual features have been shown to assist in the identification of relevant articles, thus facilitating the article screening process efficiently. In this study, we visualized article similarities to extend its utilization in practical settings for SR researchers, aiming to promote human comprehension of article distributions and hidden patterns. To prompt an effective visualization in an interpretable, intuitive, and scalable way, we implemented a graph-based network visualization with three network sparsification approaches and a distance-based map projection via dimensionality reduction. We evaluated and compared three network sparsification approaches and the visualization types (article network vs. article map). We demonstrated the effectiveness in revealing article distribution and exhibiting clustering patterns of relevant articles with practical meanings for SRs.

  11. Distinguishability notion based on Wootters statistical distance: Application to discrete maps

    Science.gov (United States)

    Gomez, Ignacio S.; Portesi, M.; Lamberti, P. W.

    2017-08-01

    We study the distinguishability notion given by Wootters for states represented by probability density functions. This presents the particularity that it can also be used for defining a statistical distance in chaotic unidimensional maps. Based on that definition, we provide a metric d ¯ for an arbitrary discrete map. Moreover, from d ¯ , we associate a metric space with each invariant density of a given map, which results to be the set of all distinguished points when the number of iterations of the map tends to infinity. Also, we give a characterization of the wandering set of a map in terms of the metric d ¯ , which allows us to identify the dissipative regions in the phase space. We illustrate the results in the case of the logistic and the circle maps numerically and analytically, and we obtain d ¯ and the wandering set for some characteristic values of their parameters. Finally, an extension of the metric space associated for arbitrary probability distributions (not necessarily invariant densities) is given along with some consequences. The statistical properties of distributions given by histograms are characterized in terms of the cardinal of the associated metric space. For two conjugate variables, the uncertainty principle is expressed in terms of the diameters of the associated metric space with those variables.

  12. Mapping Language Networks Using the Structural and Dynamic Brain Connectomes.

    Science.gov (United States)

    Del Gaizo, John; Fridriksson, Julius; Yourganov, Grigori; Hillis, Argye E; Hickok, Gregory; Misic, Bratislav; Rorden, Chris; Bonilha, Leonardo

    2017-01-01

    Lesion-symptom mapping is often employed to define brain structures that are crucial for human behavior. Even though poststroke deficits result from gray matter damage as well as secondary white matter loss, the impact of structural disconnection is overlooked by conventional lesion-symptom mapping because it does not measure loss of connectivity beyond the stroke lesion. This study describes how traditional lesion mapping can be combined with structural connectome lesion symptom mapping (CLSM) and connectome dynamics lesion symptom mapping (CDLSM) to relate residual white matter networks to behavior. Using data from a large cohort of stroke survivors with aphasia, we observed improved prediction of aphasia severity when traditional lesion symptom mapping was combined with CLSM and CDLSM. Moreover, only CLSM and CDLSM disclosed the importance of temporal-parietal junction connections in aphasia severity. In summary, connectome measures can uniquely reveal brain networks that are necessary for function, improving the traditional lesion symptom mapping approach.

  13. Protein distance constraints predicted by neural networks and probability density functions

    DEFF Research Database (Denmark)

    Lund, Ole; Frimand, Kenneth; Gorodkin, Jan

    1997-01-01

    We predict interatomic C-α distances by two independent data driven methods. The first method uses statistically derived probability distributions of the pairwise distance between two amino acids, whilst the latter method consists of a neural network prediction approach equipped with windows taking....... The predictions are based on a data set derived using a new threshold similarity. We show that distances in proteins are predicted more accurately by neural networks than by probability density functions. We show that the accuracy of the predictions can be further increased by using sequence profiles. A threading...

  14. Associative memory architecture for word-parallel smallest Euclidean distance search using distance mapping into clock-number domain

    Science.gov (United States)

    Akazawa, Toshinobu; Sasaki, Seiryu; Jürgen Mattausch, Hans

    2014-01-01

    A scalable word-parallel associative memory for smallest Euclidean distance (ED) search is presented. Due to the applied concept of distance to clock-number mapping, the reported architecture is digital in nature and scalable to advanced technology. Furthermore, the reference data of feature vectors can be scaled in principle to any vector dimension and number. Handling of the numerical complexity of the ED without large consumption of Silicon area is achieved by an area-efficient circuit, which uses the same adder for absolute-difference calculation of vector components and subsequent square calculation by sequential addition of partial products. Additionally, a clock-number minimization algorithm is proposed to significantly reduce the clock-number needed for the search when the smallest ED is a large value. The concept of the proposed architecture has been experimentally verified by measurement results from real chips fabricated in a 180 nm CMOS technology, in which the architecture is configured for parallel smallest ED search among 32 reference vectors with each vector having 16 8-bit elements. For the application example of codebook-based data compression, the fabricated test chip achieved 1.19 µs average search time, 5.77 µs worst-case search time and low power consumption of 8.75 mW at the maximum clock frequency of 47 MHz and nominal power supply voltage Vdd = 1.8 V. At reduced power supply voltage Vdd = 1.2 V, a smaller power consumption of 2.80 mW at an also smaller maximum clock frequency of 24 MHz is measured. In comparison to previous analog-digital architecture, a reduction of the normalized power-delay product per matching operation by about a factor 1.6 at Vdd = 1.8 V (about factor 2.5 at Vdd = 1.2 V) is obtained with best-case data for the analog-digital architecture and average-case data for the proposed fully-digital architecture.

  15. Distance learning via interactive telecommunications: ACCESS Network's experience

    Science.gov (United States)

    Kawashima, Junichi

    1989-05-01

    A variety of formal and informal telecourses, via interactive television (one-way audio, two-way video), for distant learners are presented. Three interactive formats (telephone, phone-in on radio, and audio teleconferencing) have been utilized in linking a studio instructor with students at home or in the classroom. More interactive segments have been allocated during the broadcast to improve the teaching-learning process. A field trial to test the usefulness of a computer conferencing facility for students studying at a distance and interacting with their teachers is described.

  16. Learning Networks for Lifelong Learning: An Exploratory Survey on Distance Learners’ preferences

    NARCIS (Netherlands)

    Berlanga, Adriana; Rusman, Ellen; Eshuis, Jannes; Hermans, Henry; Sloep, Peter

    2010-01-01

    Berlanga, A. J., Rusman, E., Eshuis, J., Hermans, H., & Sloep, P. B. (2010, 3 May). Learning Networks for Lifelong Learning: An Exploratory Survey on Distance Learners’ preferences. Presentation at the 7th International Conference on Networked Learning (NLC-2010), Aalborg, Denmark.

  17. PLANNING THE NETWORKING OF ODL INSTITUTIONS FOR ESTABLISHING INTEGRATED DISTANCE EDUCATION SYSTEM IN INDIA

    Directory of Open Access Journals (Sweden)

    Pankaj KHANNA

    2011-07-01

    Full Text Available It is proposed to establish an Integrated Distance Education System in India by designing modern technology based information communication network, connecting all its ODL (Open and Distance Learning institutions to the headquarters of the ODL system in India. The principle roles to be performed by such a system have been discussed; according to which it would enable, educate and empower every member of the academic community including distance learners so as to provide them quality distance education. The connectivity between the ODL institutions would be achieved through the use of VPN (Virtual Private Network involving wireless networking and optical networking. Various benefits of providing VPN connectivity to the ODL institutions in India, such as cost effectiveness, security, and shared applications/services have also been discussed. Thus, the networking of all the ODL institutions in India would provide a national framework so as to build an excellent Integrated Distance Education System necessary for providing equity and quality distance education at national level.

  18. Research on the Network Security Strategy for Digital Distance Education Platform

    Directory of Open Access Journals (Sweden)

    Zhang Minzhu

    2017-01-01

    Full Text Available Distance education has been an important development tendency and learning platform with the emphasis of lifelong learning of the society. Networked learning and teaching is a main characteristic of distance education, which inevitably needs to transmit large magnitude of private data among students, teachers and the education platform. To protect the security of data transmission and storage, a networked security strategy was proposed. The security strategy is based on the technologies of intrusion detection and digital signature. An intrusion detection model was established in accordance to the main tasks of distance education platform. The encryption process of digital signature was illustrated along with the information flow of the distance education platform. The paper offers an effective reference for solving security problems of distance education platforms.

  19. Eiders as long distance connectors in Arctic networks

    DEFF Research Database (Denmark)

    Vestbo, Stine; Hindberg, Claus; Olesen, Jens Mogens

    , and parasites. In addition, we examine the role of human activities in the network and predict how these activities will impact the ecological network that the common eider is part of. Finally, we will analyse how the fluctuating population sizes of common eiders can affect the stability of the different...... eider (S. spectabilis) have suffered major declines in Greenland and Canada. In 2001, the Greenland Home Rule Department of Hunting and Fishing issued a notice on the protection of birds in Greenland. Consequently, the annual catch numbers of common eiders in Greenland were reduced by more than two...... thirds. However, human activities are still threatening the survival of the common eider, e.g. by bycatching during spring when fishing for lumpsucker, and disturbances of feeding activities by fast moving motor boats. Common eiders migrate between their breeding and wintering area, hereby connecting...

  20. Distributed cognitive maps reflecting real distances between places and views in the human brain.

    Science.gov (United States)

    Sulpizio, Valentina; Committeri, Giorgia; Galati, Gaspare

    2014-01-01

    KEEPING ORIENTED IN THE ENVIRONMENT IS A MULTIFACETED ABILITY THAT REQUIRES KNOWLEDGE OF AT LEAST THREE PIECES OF INFORMATION: one's own location ("place") and orientation ("heading") within the environment, and which location in the environment one is looking at ("view"). We used functional magnetic resonance imaging (fMRI) in humans to examine the neural signatures of these information. Participants were scanned while viewing snapshots which varied for place, view and heading within a virtual room. We observed adaptation effects, proportional to the physical distances between consecutive places and views, in scene-responsive (retrosplenial complex and parahippocampal gyrus), fronto-parietal and lateral occipital regions. Multivoxel pattern classification of signals in scene-responsive regions and in the hippocampus allowed supra-chance decoding of place, view and heading, and revealed the existence of map-like representations, where places and views closer in physical space entailed activity patterns more similar in neural representational space. The pattern of hippocampal activity reflected both view- and place-based distances, the pattern of parahippocampal activity preferentially discriminated between views, and the pattern of retrosplenial activity combined place and view information, while the fronto-parietal cortex only showed transient effects of changes in place, view, and heading. Our findings provide evidence for the presence of map-like spatial representations which reflect metric distances in terms of both one's own and landmark locations.

  1. Distributed cognitive maps reflecting real distances between places and views in the human brain

    Directory of Open Access Journals (Sweden)

    Valentina eSulpizio

    2014-09-01

    Full Text Available Keeping oriented in the environment is a multifaceted ability that requires knowledge of at least three pieces of information: one’s own location (place and orientation (heading within the environment, and which location in the environment one is looking at (view. We used functional magnetic resonance imaging (fMRI in humans to examine the neural signatures of these information. Participants were scanned while viewing snapshots which varied for place, view and heading within a virtual room. We observed adaptation effects, proportional to the physical distances between consecutive places and views, in scene-responsive (retrosplenial complex and parahippocampal gyrus, fronto-parietal and lateral occipital regions. Multivoxel pattern classification of signals in scene-responsive regions and in the hippocampus allowed supra-chance decoding of place, view and heading, and revealed the existence of map-like representations, where places and views closer in physical space entailed activity patterns more similar in neural representational space. The pattern of hippocampal activity reflected both view- and place-based distances, the pattern of parahippocampal activity preferentially discriminated between views, and the pattern of retrosplenial activity combined place and view information, while the fronto-parietal cortex only showed transient effects of changes in place, view, and heading. Our findings provide evidence for the presence of map-like spatial representations which reflect metric distances in terms of both one’s own and landmark locations.

  2. Virtual optical network mapping and core allocation in elastic optical networks using multi-core fibers

    Science.gov (United States)

    Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

    2017-11-01

    Virtualization technology can greatly improve the efficiency of the networks by allowing the virtual optical networks to share the resources of the physical networks. However, it will face some challenges, such as finding the efficient strategies for virtual nodes mapping, virtual links mapping and spectrum assignment. It is even more complex and challenging when the physical elastic optical networks using multi-core fibers. To tackle these challenges, we establish a constrained optimization model to determine the optimal schemes of optical network mapping, core allocation and spectrum assignment. To solve the model efficiently, tailor-made encoding scheme, crossover and mutation operators are designed. Based on these, an efficient genetic algorithm is proposed to obtain the optimal schemes of the virtual nodes mapping, virtual links mapping, core allocation. The simulation experiments are conducted on three widely used networks, and the experimental results show the effectiveness of the proposed model and algorithm.

  3. Maps of random walks on complex networks reveal community structure.

    Science.gov (United States)

    Rosvall, Martin; Bergstrom, Carl T

    2008-01-29

    To comprehend the multipartite organization of large-scale biological and social systems, we introduce an information theoretic approach that reveals community structure in weighted and directed networks. We use the probability flow of random walks on a network as a proxy for information flows in the real system and decompose the network into modules by compressing a description of the probability flow. The result is a map that both simplifies and highlights the regularities in the structure and their relationships. We illustrate the method by making a map of scientific communication as captured in the citation patterns of >6,000 journals. We discover a multicentric organization with fields that vary dramatically in size and degree of integration into the network of science. Along the backbone of the network-including physics, chemistry, molecular biology, and medicine-information flows bidirectionally, but the map reveals a directional pattern of citation from the applied fields to the basic sciences.

  4. A Hybrid Reliable Heuristic Mapping Method Based on Survivable Virtual Networks for Network Virtualization

    Directory of Open Access Journals (Sweden)

    Qiang Zhu

    2015-01-01

    Full Text Available The reliable mapping of virtual networks is one of the hot issues in network virtualization researches. Unlike the traditional protection mechanisms based on redundancy and recovery mechanisms, we take the solution of the survivable virtual topology routing problem for reference to ensure that the rest of the mapped virtual networks keeps connected under a single node failure condition in the substrate network, which guarantees the completeness of the virtual network and continuity of services. In order to reduce the cost of the substrate network, a hybrid reliable heuristic mapping method based on survivable virtual networks (Hybrid-RHM-SVN is proposed. In Hybrid-RHM-SVN, we formulate the reliable mapping problem as an integer linear program. Firstly, we calculate the primary-cut set of the virtual network subgraph where the failed node has been removed. Then, we use the ant colony optimization algorithm to achieve the approximate optimal mapping. The links in primary-cut set should select a substrate path that does not pass through the substrate node corresponding to the virtual node that has been removed first. The simulation results show that the acceptance rate of virtual networks, the average revenue of mapping, and the recovery rate of virtual networks are increased compared with the existing reliable mapping algorithms, respectively.

  5. Developing Critical Thinking Skills through Interactive Radio Programs (IRPs: Building Online Knowledge Networks In Distance Education

    Directory of Open Access Journals (Sweden)

    Gulsun KURUBACAK

    2005-07-01

    Full Text Available ABSTRACT In considering how best to optimize distance education systems, economy (cost effectiveness and efficiency, technology (communication technologies and equity (gender, accessibility, minority, language, religion etc. are vital issues in any distance education systems. Moreover, how end-users, distance learners, can equally share and exchange knowledge and resources for educational purposes, how they can promote their higher-order thinking skills as well as how they can cope with the limitations they have (such as time, age, gender, language etc. are major concerns in distance education milieus. Kurubacak strongly emphasize that interactive radio programs, as a forgotten educational media, with a little cost can effectively integrate in any distance education systems. Therefore, the main purpose of this paper is to focus on interactive radio programs to build critical and creative knowledge networks among diverse learners in the distance education systems of developing countries.

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

    Directory of Open Access Journals (Sweden)

    Tjibbe Donker

    2017-08-01

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

  7. Probabilistic structure of the distance between tributaries of given size in river networks

    Science.gov (United States)

    Convertino, Matteo; Rigon, Riccardo; Maritan, Amos; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

    2007-11-01

    We analyze the distribution of the distances between tributaries of a given size (or of sizes larger than a given area) draining along either an open boundary or the mainstream of a river network. By proposing a description of the distance separating prescribed merging contributing areas, we also address related variables, like mean (or bankfull) flow rates and channel and riparian area widths, which are derived under a set of reasonable hydrologic assumptions. The importance of such distributions lies in their ecological, hydrologic, and geomorphic implications on the spreading of species along the ecological corridor defined by the river network and on the propagation of infections due to water-borne diseases, particularly in view of exact theoretical predictions explicitly using the alongstream distribution of confluences carrying a given flow. Use is made here of real river networks, suitably extracted from digital elevation models, optimal channel networks, and exactly solved tree-like constructs like the Peano and the Scheidegger networks. The results obtained redefine theoretically in a coherent and general manner and verify observationally the distribution function of the above distances and thus provide the general probabilistic structure of tributaries in river networks. Specifically, we find that the probability of exceedence of the alongstream distance d of tributaries of size larger than a has the explicit form P(≥d) = exp (-Cd/aH/(1+H)), where C is a constant that depends on the choice of boundary conditions and H ≤ 1 is the Hurst exponent.

  8. Google matrix and Ulam networks of intermittency maps.

    Science.gov (United States)

    Ermann, L; Shepelyansky, D L

    2010-03-01

    We study the properties of the Google matrix of an Ulam network generated by intermittency maps. This network is created by the Ulam method which gives a matrix approximant for the Perron-Frobenius operator of dynamical map. The spectral properties of eigenvalues and eigenvectors of this matrix are analyzed. We show that the PageRank of the system is characterized by a power law decay with the exponent beta dependent on map parameters and the Google damping factor alpha . Under certain conditions the PageRank is completely delocalized so that the Google search in such a situation becomes inefficient.

  9. Mapping Technology Space by Normalizing Technology Relatedness Networks

    CERN Document Server

    Alstott, Jeff; Yan, Bowen; Luo, Jianxi

    2015-01-01

    Technology is a complex system, with technologies relating to each other in a space that can be mapped as a network. The technology relatedness network's structure can reveal properties of technologies and of human behavior, if it can be mapped accurately. Technology networks have been made from patent data, using several measures of relatedness. These measures, however, are influenced by factors of the patenting system that do not reflect technologies or their relatedness. We created technology networks that precisely controlled for these impinging factors and normalized them out, using data from 3.9 million patents. The normalized technology relatedness networks were sparse, with only ~20% of technology domain pairs more related than would be expected by chance. Different measures of technology relatedness became more correlated with each other after normalization, approaching a single dimension of technology relatedness. The normalized network corresponded with human behavior: we analyzed the patenting his...

  10. Distance Mapping in Proteins Using Fluorescence Spectroscopy: The Tryptophan-Induced Quenching (TrIQ) Method

    Science.gov (United States)

    Mansoor, Steven E.; DeWitt, Mark A.; Farrens, David L.

    2014-01-01

    Studying the interplay between protein structure and function remains a daunting task. Especially lacking are methods for measuring structural changes in real time. Here we report our most recent improvements to a method that can be used to address such questions. This method, which we now call Tryptophan induced quenching (TrIQ), provides a straightforward, sensitive and inexpensive way to address questions of conformational dynamics and short-range protein interactions. Importantly, TrIQ only occurs over relatively short distances (~5 to 15 Å), making it complementary to traditional fluorescence resonance energy transfer (FRET) methods that occur over distances too large for precise studies of protein structure. As implied in the name, TrIQ measures the efficient quenching induced in some fluorophores by tryptophan (Trp). We present here our analysis of the TrIQ effect for five different fluorophores that span a range of sizes and spectral properties. Each probe was attached to four different cysteine residues on T4 lysozyme and the extent of TrIQ caused by a nearby Trp was measured. Our results show that for smaller probes, TrIQ is distance dependent. Moreover, we also demonstrate how TrIQ data can be analyzed to determine the fraction of fluorophores involved in a static, non-fluorescent complex with Trp. Based on this analysis, our study shows that each fluorophore has a different TrIQ profile, or "sphere of quenching", which correlates with its size, rotational flexibility, and the length of attachment linker. This TrIQ-based "sphere of quenching" is unique to every Trp-probe pair and reflects the distance within which one can expect to see the TrIQ effect. It provides a straightforward, readily accessible approach for mapping distances within proteins and monitoring conformational changes using fluorescence spectroscopy. PMID:20886836

  11. A Bayesian Network Approach to Ontology Mapping

    National Research Council Canada - National Science Library

    Pan, Rong; Ding, Zhongli; Yu, Yang; Peng, Yun

    2005-01-01

    This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web...

  12. Mapping monthly rainfall data in Galicia (NW Spain using inverse distances and geostatistical methods

    Directory of Open Access Journals (Sweden)

    P. Sande-Fouz

    2007-04-01

    Full Text Available In this paper, results from three different interpolation techniques based on Geostatistics (ordinary kriging, kriging with external drift and conditional simulation and one deterministic method (inverse distances for mapping total monthly rainfall are compared. The study data set comprised total monthly rainfall from 1998 till 2001 corresponding to a maximum of 121 meteorological stations irregularly distributed in the region of Galicia (NW Spain. Furthermore, a raster Geographic Information System (GIS was used for spatial interpolation with a 500×500 m grid digital elevation model. Inverse distance technique was appropriate for a rapid estimation of the rainfall at the studied scale. In order to apply geostatistical interpolation techniques, a spatial dependence analysis was performed; rainfall spatial dependence was observed in 33 out of 48 months analysed, the rest of the rainfall data sets presented a random behaviour. Different values of the semivariogram parameters caused the smoothing in the maps obtained by ordinary kriging. Kriging with external drift results were according to former studies which showed the influence of topography. Conditional simulation is considered to give more realistic results; however, this consideration must be confirmed with new data.

  13. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    Science.gov (United States)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Accurate measurements of rainfall are important in many hydrological applications, for instance, flash-flood early-warning systems, hydraulic structures design, agriculture, weather forecasting, and climate modelling. Rainfall intensities can be retrieved from (commercial) microwave link networks. Whenever possible, link networks measure and store the decrease in power of the electromagnetic signal at regular intervals. The decrease in power is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the physics involved in the measurements such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology, the spatial density of the network, and the availability of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of The Netherlands. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify

  14. Computing distance-based topological descriptors of complex chemical networks: New theoretical techniques

    Science.gov (United States)

    Hayat, Sakander

    2017-11-01

    Structure-based topological descriptors/indices of complex chemical networks enable prediction of physico-chemical properties and the bioactivities of these compounds through QSAR/QSPR methods. In this paper, we have developed a rigorous computational and theoretical technique to compute various distance-based topological indices of complex chemical networks. A fullerene is called the IPR (Isolated-Pentagon-Rule) fullerene, if every pentagon in it is surrounded by hexagons only. To ensure the applicability of our technique, we compute certain distance-based indices of an infinite family of IPR fullerenes. Our results show that the proposed technique is more diverse and bears less algorithmic and combinatorial complexity.

  15. INTEGRATING INTERNET PROTOCOL TELEVISION (IPTV IN DISTANCE EDUCATION: A Constructivist Framework for Social Networking

    Directory of Open Access Journals (Sweden)

    T. Volkan YUZER

    2011-07-01

    Full Text Available New communication technologies and constructivist pedagogy have the great potential to build very powerful paradigm shifts that enhance Internet Protocol Television (IPTV in distance education. Therefore, the main purpose of this chapter is to explore the new concerns, issues and potentials for the IPTV delivery of distance education to multicultural populations. In this study, the design strategies and principles of how to build social networking based on constructivist learning theory are discussed in order to generate a theoretical framework that provides everyday examples and experiences for IPTV in distance education. This framework also shows the needs, expectations and beliefs, and strengths-weaknesses of IPTV in distance. In short, this framework concentrates on discussing the main characteristics of IPTV in distance education and describes how those characteristics can help build constructivist online communities.

  16. Representing distance, consuming distance

    DEFF Research Database (Denmark)

    Larsen, Gunvor Riber

    Title: Representing Distance, Consuming Distance Abstract: Distance is a condition for corporeal and virtual mobilities, for desired and actual travel, but yet it has received relatively little attention as a theoretical entity in its own right. Understandings of and assumptions about distance...... to mobility and its social context. Such an understanding can be approached through representations, as distance is being represented in various ways, most noticeably in maps and through the notions of space and Otherness. The question this talk subsequently asks is whether these representations of distance...

  17. Mapping Libyan Jihadist Networks for UW

    Science.gov (United States)

    2015-12-01

    LIFG was born. The LIFG was not focused on global Jihad.78 They were primarily concerned with the overthrow of the Gaddafi apostate régime. In...while Daesh provides limited and unobtrusive support for local administration.101 Utilizing an inverse approach, AQ wants their franchises to carry out...jihadist network in Libya; 2) Ties are not limited to jihadist networks. For example, tribal ties or business connections are also included; and 3

  18. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 3: Advanced networks and economics

    Science.gov (United States)

    1986-01-01

    This study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  19. Moving Large Data Sets Over High-Performance Long Distance Networks

    Energy Technology Data Exchange (ETDEWEB)

    Hodson, Stephen W [ORNL; Poole, Stephen W [ORNL; Ruwart, Thomas [ORNL; Settlemyer, Bradley W [ORNL

    2011-04-01

    In this project we look at the performance characteristics of three tools used to move large data sets over dedicated long distance networking infrastructure. Although performance studies of wide area networks have been a frequent topic of interest, performance analyses have tended to focus on network latency characteristics and peak throughput using network traffic generators. In this study we instead perform an end-to-end long distance networking analysis that includes reading large data sets from a source file system and committing large data sets to a destination file system. An evaluation of end-to-end data movement is also an evaluation of the system configurations employed and the tools used to move the data. For this paper, we have built several storage platforms and connected them with a high performance long distance network configuration. We use these systems to analyze the capabilities of three data movement tools: BBcp, GridFTP, and XDD. Our studies demonstrate that existing data movement tools do not provide efficient performance levels or exercise the storage devices in their highest performance modes. We describe the device information required to achieve high levels of I/O performance and discuss how this data is applicable in use cases beyond data movement performance.

  20. Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

    Directory of Open Access Journals (Sweden)

    Richard A Notebaart

    2008-01-01

    Full Text Available To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.

  1. Distance metric learning for complex networks: Towards size-independent comparison of network structures

    Science.gov (United States)

    Aliakbary, Sadegh; Motallebi, Sadegh; Rashidian, Sina; Habibi, Jafar; Movaghar, Ali

    2015-02-01

    Real networks show nontrivial topological properties such as community structure and long-tail degree distribution. Moreover, many network analysis applications are based on topological comparison of complex networks. Classification and clustering of networks, model selection, and anomaly detection are just some applications of network comparison. In these applications, an effective similarity metric is needed which, given two complex networks of possibly different sizes, evaluates the amount of similarity between the structural features of the two networks. Traditional graph comparison approaches, such as isomorphism-based methods, are not only too time consuming but also inappropriate to compare networks with different sizes. In this paper, we propose an intelligent method based on the genetic algorithms for integrating, selecting, and weighting the network features in order to develop an effective similarity measure for complex networks. The proposed similarity metric outperforms state of the art methods with respect to different evaluation criteria.

  2. Implications of macroalgal isolation by distance for networks of marine protected areas.

    Science.gov (United States)

    Durrant, Halley M S; Burridge, Christopher P; Kelaher, Brendan P; Barrett, Neville S; Edgar, Graham J; Coleman, Melinda A

    2014-04-01

    The global extent of macroalgal forests is declining, greatly affecting marine biodiversity at broad scales through the effects macroalgae have on ecosystem processes, habitat provision, and food web support. Networks of marine protected areas comprise one potential tool that may safeguard gene flow among macroalgal populations in the face of increasing population fragmentation caused by pollution, habitat modification, climate change, algal harvesting, trophic cascades, and other anthropogenic stressors. Optimal design of protected area networks requires knowledge of effective dispersal distances for a range of macroalgae. We conducted a global meta-analysis based on data in the published literature to determine the generality of relation between genetic differentiation and geographic distance among macroalgal populations. We also examined whether spatial genetic variation differed significantly with respect to higher taxon, life history, and habitat characteristics. We found clear evidence of population isolation by distance across a multitude of macroalgal species. Genetic and geographic distance were positively correlated across 49 studies; a modal distance of 50-100 km maintained F(ST) < 0.2. This relation was consistent for all algal divisions, life cycles, habitats, and molecular marker classes investigated. Incorporating knowledge of the spatial scales of gene flow into the design of marine protected area networks will help moderate anthropogenic increases in population isolation and inbreeding and contribute to the resilience of macroalgal forests. ©2013 Society for Conservation Biology.

  3. Learners' Views Regarding the Use of Social Networking Sites in Distance Learning

    Science.gov (United States)

    Özmen, Büsra; Atici, Bünyamin

    2014-01-01

    In this study, it was aimed to examine the use of learning management systems supported by social networking sites in distance education and to determine the views of learners regarding these platforms. The study group of this study, which uses a qualitative research approach, consists of 15 undergraduate students who resumed their education in…

  4. Learning Networks for Lifelong Learning: An Exploratory Survey on Distance Learners’ preferences

    NARCIS (Netherlands)

    Berlanga, Adriana; Rusman, Ellen; Eshuis, Jannes; Hermans, Henry; Sloep, Peter

    2009-01-01

    Berlanga, A. J., Rusman, E., Eshuis, J., Hermans, H., & Sloep, P. B. (2010). Learning Networks for Lifelong Learning: An Exploratory Survey on Distance Learners’ preferences. In L. Dirckinck-Holmfeld, V. Hodgson, C. Jones, M. de Laat, D. McConnell, & T. Ryberg (Eds.), Proceedings of the 7th

  5. Impaired long distance functional connectivity and weighted network architecture in Alzheimer's disease.

    Science.gov (United States)

    Liu, Yong; Yu, Chunshui; Zhang, Xinqing; Liu, Jieqiong; Duan, Yunyun; Alexander-Bloch, Aaron F; Liu, Bing; Jiang, Tianzi; Bullmore, Ed

    2014-06-01

    Alzheimer's disease (AD) is increasingly recognized as a disconnection syndrome, which leads to cognitive impairment due to the disruption of functional activity across large networks or systems of interconnected brain regions. We explored abnormal functional magnetic resonance imaging (fMRI) resting-state dynamics, functional connectivity, and weighted functional networks, in a sample of patients with severe AD (N = 18) and age-matched healthy volunteers (N = 21). We found that patients had reduced amplitude and regional homogeneity of low-frequency fMRI oscillations, and reduced the strength of functional connectivity, in several regions previously described as components of the default mode network, for example, medial posterior parietal cortex and dorsal medial prefrontal cortex. In patients with severe AD, functional connectivity was particularly attenuated between regions that were separated by a greater physical distance; and loss of long distance connectivity was associated with less efficient global and nodal network topology. This profile of functional abnormality in severe AD was consistent with the results of a comparable analysis of data on 2 additional groups of patients with mild AD (N = 17) and amnestic mild cognitive impairment (MCI; N = 18). A greater degree of cognitive impairment, measured by the mini-mental state examination across all patient groups, was correlated with greater attenuation of functional connectivity, particularly over long connection distances, for example, between anterior and posterior components of the default mode network, and greater reduction of global and nodal network efficiency. These results indicate that neurodegenerative disruption of fMRI oscillations and connectivity in AD affects long-distance connections to hub nodes, with the consequent loss of network efficiency. This profile was evident also to a lesser degree in the patients with less severe cognitive impairment, indicating that the potential of resting

  6. Learners’ Views Regarding the Use of Social Networking Sites in Distance Learning

    Directory of Open Access Journals (Sweden)

    Büşra Özmen

    2014-09-01

    Full Text Available In this study, it was aimed to examine the use of learning management systems supported by social networking sites in distance education and to determine the views of learners regarding these platforms. The study group of this study, which uses a qualitative research approach, consists of 15 undergraduate students who resumed their education in Turkey. The data were gathered via a semi-structured interview form which consists of open-ended questions. Content analysis was used in the analysis of the data. According to the results of the study, it has been revealed within the scope of the course that the students have positive attitudes towards the use of social networking sites and distance education applications and these applications have positively affected the quality of communication between instructors and students. Furthermore, it was seen that the students made comments relating to the interesting aspects of the applications and the difference between distance education and face-to-face learning.

  7. Mapping, Awareness, And Virtualization Network Administrator Training Tool Virtualization Module

    Science.gov (United States)

    2016-03-01

    AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL VIRTUALIZATION MODULE by Erik W. Berndt March 2016 Thesis Advisor: John Gibson...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MAPPING, AWARENESS, AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL... VIRTUALIZATION MODULE 5. FUNDING NUMBERS 6. AUTHOR(S) Erik W. Berndt 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School

  8. Distance-Based and Low Energy Adaptive Clustering Protocol for Wireless Sensor Networks.

    Science.gov (United States)

    Liaqat, Misbah; Gani, Abdullah; Anisi, Mohammad Hossein; Ab Hamid, Siti Hafizah; Akhunzada, Adnan; Khan, Muhammad Khurram; Ali, Rana Liaqat

    A wireless sensor network (WSN) comprises small sensor nodes with limited energy capabilities. The power constraints of WSNs necessitate efficient energy utilization to extend the overall network lifetime of these networks. We propose a distance-based and low-energy adaptive clustering (DISCPLN) protocol to streamline the green issue of efficient energy utilization in WSNs. We also enhance our proposed protocol into the multi-hop-DISCPLN protocol to increase the lifetime of the network in terms of high throughput with minimum delay time and packet loss. We also propose the mobile-DISCPLN protocol to maintain the stability of the network. The modelling and comparison of these protocols with their corresponding benchmarks exhibit promising results.

  9. Visualising DEM-related flood-map uncertainties using a disparity-distance equation algorithm

    Directory of Open Access Journals (Sweden)

    S. A. Brandt

    2016-05-01

    Full Text Available The apparent absoluteness of information presented by crisp-delineated flood boundaries can lead to misconceptions among planners about the inherent uncertainties associated in generated flood maps. Even maps based on hydraulic modelling using the highest-resolution digital elevation models (DEMs, and calibrated with the most optimal Manning's roughness (n coefficients, are susceptible to errors when compared to actual flood boundaries, specifically in flat areas. Therefore, the inaccuracies in inundation extents, brought about by the characteristics of the slope perpendicular to the flow direction of the river, have to be accounted for. Instead of using the typical Monte Carlo simulation and probabilistic methods for uncertainty quantification, an empirical-based disparity-distance equation that considers the effects of both the DEM resolution and slope was used to create prediction-uncertainty zones around the resulting inundation extents of a one-dimensional (1-D hydraulic model. The equation was originally derived for the Eskilstuna River where flood maps, based on DEM data of different resolutions, were evaluated for the slope-disparity relationship. To assess whether the equation is applicable to another river with different characteristics, modelled inundation extents from the Testebo River were utilised and tested with the equation. By using the cross-sectional locations, water surface elevations, and DEM, uncertainty zones around the original inundation boundary line can be produced for different confidences. The results show that (1 the proposed method is useful both for estimating and directly visualising model inaccuracies caused by the combined effects of slope and DEM resolution, and (2 the DEM-related uncertainties alone do not account for the total inaccuracy of the derived flood map. Decision-makers can apply it to already existing flood maps, thereby recapitulating and re-analysing the inundation boundaries and the areas that

  10. A social network study of the growth of community among distance learners

    Directory of Open Access Journals (Sweden)

    Caroline Haythornthwaite

    1998-01-01

    Full Text Available Describes preliminary results from a social network study of the growth of community and use of Internet resources among a class of 15 distance learners enrolled in the LEEP option of the Master of Science in Library and Information Science at the University of Illinois at Urbana-Champaign. The LEEP programme offers a distance option for students with instruction delivered through communication and computer technologies, and through short, intensive on-campus meetings. Class members reported on their interactions with others in the class at three times over the 15 week term (Fall 1997. They indicated how often they had (1 worked with each other member on class work, (2 received or (3 given information or advice about class work, (4 socialized, and (5 exchanged emotional support (either given or received during the preceeding month. For each question, class members reported their frequency of communication via each of the available means of communication (Web-board, chat lines, email, telephone, face-to-face. Final interviews, and course evaluation questionnaires provide further information about their class experience. These data allow examination of the role of different types of information exchange in the distance learners' intra-class interactions. By using a social network approach, the data allow examination of issues of centrality and isolation in this network that may correlate with performance or satisfaction measures. Results from this study will provide feedback to course instructors on the experience of class participants in the distance education programme.

  11. Efficient mapping of ligand migration channel networks in dynamic proteins.

    Science.gov (United States)

    Lin, Tu-Liang; Song, Guang

    2011-08-01

    For many proteins such as myoglobin, the binding site lies in the interior, and there is no obvious route from the exterior to the binding site in the average structure. Although computer simulations for a limited number of proteins have found some transiently open channels, it is not clear if there exist more channels elsewhere or how the channels are regulated. A systematic approach that can map out the whole ligand migration channel network is lacking. Ligand migration in a dynamic protein resembles closely a well-studied problem in robotics, namely, the navigation of a mobile robot in a dynamic environment. In this work, we present a novel robotic motion planning inspired approach that can map the ligand migration channel network in a dynamic protein. The method combines an efficient spatial mapping of protein inner space with a temporal exploration of protein structural heterogeneity, which is represented by a structure ensemble. The spatial mapping of each conformation in the ensemble produces a partial map of protein inner cavities and their inter-connectivity. These maps are then merged to form a super map that contains all the channels that open dynamically. Results on the pathways in myoglobin for gaseous ligands demonstrate the efficiency of our approach in mapping the ligand migration channel networks. The results, obtained in a significantly less amount of time than trajectory-based approaches, are in agreement with previous simulation results. Additionally, the method clearly illustrates how and what conformational changes open or close a channel. Copyright © 2011 Wiley-Liss, Inc.

  12. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 1: Executive summary

    Science.gov (United States)

    1986-01-01

    Over the past two decades, fiber optics has emerged as a highly practical and cost-efficient communications technology. Its competitiveness vis-a-vis other transmission media, especially satellite, has become a critical question. This report studies the likely evolution and application of fiber optic networks in the United States to the end of the century. The outlook for the technology of fiber systems is assessed and forecast, scenarios of the evolution of fiber optic network development are constructed, and costs to provide service are determined and examined parametrically as a function of network size and traffic carried. Volume 1 consists of the Executive Summary. Volume 2 focuses on fiber optic technology and long distance fiber optic networks. Volume 3 develops a traffic and financial model of a nationwide long distance transmission network. Among the study's most important conclusions are: revenue requirements per circuit for LATA-to-LATA fiber optic links are less than one cent per call minute; multiplex equipment, which is likely to be required in any competing system, is the largest contributor to circuit costs; the potential capacity of fiber optic cable is very large and as yet undefined; and fiber optic transmission combined with other network optimization schemes can lead to even lower costs than those identified in this study.

  13. Mapping human whole-brain structural networks with diffusion MRI.

    Directory of Open Access Journals (Sweden)

    Patric Hagmann

    Full Text Available Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.

  14. Impact of distance on the network management capability of the home base firm

    DEFF Research Database (Denmark)

    Mykhaylenko, Alona; Wæhrens, Brian Vejrum; Slepniov, Dmitrij

    For many globally dispersed organizations the home base (HB) is historically the locus of integrative, coordinating and innovating efforts, important for the overall performance. The growing concerns about the offshoring strategies posing threats to the capabilities of the HB draw attention to how...... a HB can continuously sustain its centrality. The well-known challenges of distance in the distributed working arrangements may be regarded as a major threat to the network management capabilities (NMCs) of the HB. Therefore, this paper investigates what role does distance between the HB and its...

  15. Multiple fixed point theorems for contractive and Meir-Keeler type mappings defined on partially ordered spaces with a distance

    Directory of Open Access Journals (Sweden)

    Mitrofan M Choban

    2017-10-01

    Full Text Available We introduce and study a general concept of multiple fixed point for mappings defined on partially ordered distance spaces in the presence of a contraction type condition and appropriate monotonicity properties. This notion and the obtained results complement the corresponding ones from [M. Choban, V. Berinde, A general concept of multiple fixed point for mappings defined on  spaces with a distance, Carpathian J. Math. 33 (2017, no. 3, 275--286] and also simplifies some concepts of multiple fixed point considered by various authors in the last decade or so.

  16. Use of Tabu Search in a Solver to Map Complex Networks onto Emulab Testbeds

    National Research Council Canada - National Science Library

    MacDonald, Jason E

    2007-01-01

    The University of Utah's solver for the testbed mapping problem uses a simulated annealing metaheuristic algorithm to map a researcher's experimental network topology onto available testbed resources...

  17. Mapping distributed brain function and networks with diffuse optical tomography

    Science.gov (United States)

    Eggebrecht, Adam T.; Ferradal, Silvina L.; Robichaux-Viehoever, Amy; Hassanpour, Mahlega S.; Dehghani, Hamid; Snyder, Abraham Z.; Hershey, Tamara; Culver, Joseph P.

    2014-06-01

    Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson's disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging.

  18. Study of Tools for Network Discovery and Network Mapping

    Science.gov (United States)

    2003-11-01

    DISCOVERY OptiView Console supports central and distributed architectures. OptiView Console consists of the Viewer and the Service Manager that...OptiView console. Service Manager is the engine that performs network discovery, data management, data analysis, and provides notification services...The Service Manager gives you status information and configuration control of the services that are part of the OptiView Console application. These

  19. A Selfish Constraint Satisfaction Genetic Algorithms for Planning a Long-Distance Transportation Network

    Science.gov (United States)

    Onoyama, Takashi; Maekawa, Takuya; Kubota, Sen; Tsuruta, Setuso; Komoda, Norihisa

    To build a cooperative logistics network covering multiple enterprises, a planning method that can build a long-distance transportation network is required. Many strict constraints are imposed on this type of problem. To solve these strict-constraint problems, a selfish constraint satisfaction genetic algorithm (GA) is proposed. In this GA, each gene of an individual satisfies only its constraint selfishly, disregarding the constraints of other genes in the same individuals. Moreover, a constraint pre-checking method is also applied to improve the GA convergence speed. The experimental result shows the proposed method can obtain an accurate solution in a practical response time.

  20. Mapping information flow in sensorimotor networks.

    Directory of Open Access Journals (Sweden)

    Max Lungarella

    2006-10-01

    Full Text Available Biological organisms continuously select and sample information used by their neural structures for perception and action, and for creating coherent cognitive states guiding their autonomous behavior. Information processing, however, is not solely an internal function of the nervous system. Here we show, instead, how sensorimotor interaction and body morphology can induce statistical regularities and information structure in sensory inputs and within the neural control architecture, and how the flow of information between sensors, neural units, and effectors is actively shaped by the interaction with the environment. We analyze sensory and motor data collected from real and simulated robots and reveal the presence of information structure and directed information flow induced by dynamically coupled sensorimotor activity, including effects of motor outputs on sensory inputs. We find that information structure and information flow in sensorimotor networks (a is spatially and temporally specific; (b can be affected by learning, and (c can be affected by changes in body morphology. Our results suggest a fundamental link between physical embeddedness and information, highlighting the effects of embodied interactions on internal (neural information processing, and illuminating the role of various system components on the generation of behavior.

  1. Using obsidian transfer distances to explore social network maintenance in late Pleistocene hunter-gatherers.

    Science.gov (United States)

    Pearce, Eiluned; Moutsiou, Theodora

    2014-12-01

    Social behaviour is notoriously difficult to study archaeologically and it is unclear how large the networks of prehistoric humans were, or how they remained connected. Maintaining social cohesion was crucial for early humans because social networks facilitate cooperation and are imperative for survival and reproduction. Recent hunter-gatherer social organisation typically comprises a number of nested layers, ranging from the nuclear family through to the ~1500-strong ethnolinguistic tribe. Here we compare maximum obsidian transfer distances from the late Pleistocene with ethnographic data on the size of the geographic areas associated with each of these social grouping layers in recent hunter-gatherers. The closest match between the two is taken to indicate the maximum social layer within which contact could be sustained by Pleistocene hominins. Within both the (sub)tropical African and Subarctic biomes, the maximum obsidian transfer distances for Pleistocene modern humans (~200km and ~400km respectively) correspond to the geographic ranges of the outermost tribal layer in recent hunter-gatherers. This suggests that modern humans could potentially sustain the cohesion of their entire tribe at all latitudes, even though networks are more dispersed nearer the poles. Neanderthal obsidian transfer distances (300km) indicate that although Neanderthal home ranges are larger than those of low latitude hominins, Neanderthals travelled shorter distances than modern humans living at the same high latitudes. We argue that, like modern humans, Neanderthals could have maintained tribal cohesion, but that their tribes were substantially smaller than those of contemporary modern humans living in similar environments. The greater time taken to traverse the larger modern human tribal ranges may have limited the frequency of their face-to-face interactions and thus necessitated additional mechanisms to ensure network connectivity, such as the exchange of symbolic artefacts

  2. A Centralized Energy Efficient Distance Based Routing Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rohit D. Gawade

    2016-01-01

    Full Text Available Wireless sensor network (WSN typically consists of a large number of low cost wireless sensor nodes which collect and send various messages to a base station (BS. WSN nodes are small battery powered devices having limited energy resources. Replacement of such energy resources is not easy for thousands of nodes as they are inaccessible to users after their deployment. This generates a requirement of energy efficient routing protocol for increasing network lifetime while minimizing energy consumption. Low Energy Adaptive Clustering Hierarchy (LEACH is a widely used classic clustering algorithm in WSNs. In this paper, we propose a Centralized Energy Efficient Distance (CEED based routing protocol to evenly distribute energy dissipation among all sensor nodes. We calculate optimum number of cluster heads based on LEACH’s energy dissipation model. We propose a distributed cluster head selection algorithm based on dissipated energy of a node and its distance to BS. Moreover, we extend our protocol by multihop routing scheme to reduce energy dissipated by nodes located far away from base station. The performance of CEED is compared with other protocols such as LEACH and LEACH with Distance Based Thresholds (LEACH-DT. Simulation results show that CEED is more energy efficient as compared to other protocols. Also it improves the network lifetime and stability period over the other protocols.

  3. An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

    Science.gov (United States)

    Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

    2014-01-01

    Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption. PMID:25196015

  4. An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jin Wang

    2014-08-01

    Full Text Available Traffic patterns in wireless sensor networks (WSNs usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

  5. An energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks.

    Science.gov (United States)

    Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

    2014-08-18

    Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

  6. Concentration of 1-Lipschitz maps into an infinite dimensional $\\ell^p$-ball with $\\ell^q$-distance function

    OpenAIRE

    Funano, Kei

    2008-01-01

    In this paper, we study the L\\'{e}vy-Milman concentration phenomenon of 1-Lipschitz maps into infinite dimensional metric spaces. Our main theorem asserts that the concentration to an infinite dimensional $\\ell^p$-ball with the $\\ell^q$-distance function for $1\\leq p

  7. Network Partitioning Domain Knowledge Multiobjective Application Mapping for Large-Scale Network-on-Chip

    Directory of Open Access Journals (Sweden)

    Yin Zhen Tei

    2014-01-01

    Full Text Available This paper proposes a multiobjective application mapping technique targeted for large-scale network-on-chip (NoC. As the number of intellectual property (IP cores in multiprocessor system-on-chip (MPSoC increases, NoC application mapping to find optimum core-to-topology mapping becomes more challenging. Besides, the conflicting cost and performance trade-off makes multiobjective application mapping techniques even more complex. This paper proposes an application mapping technique that incorporates domain knowledge into genetic algorithm (GA. The initial population of GA is initialized with network partitioning (NP while the crossover operator is guided with knowledge on communication demands. NP reduces the large-scale application mapping complexity and provides GA with a potential mapping search space. The proposed genetic operator is compared with state-of-the-art genetic operators in terms of solution quality. In this work, multiobjective optimization of energy and thermal-balance is considered. Through simulation, knowledge-based initial mapping shows significant improvement in Pareto front compared to random initial mapping that is widely used. The proposed knowledge-based crossover also shows better Pareto front compared to state-of-the-art knowledge-based crossover.

  8. A Distance-Based Energy Aware Routing Algorithm for Wireless Sensor Networks

    Science.gov (United States)

    Wang, Jin; Kim, Jeong-Uk; Shu, Lei; Niu, Yu; Lee, Sungyoung

    2010-01-01

    Energy efficiency and balancing is one of the primary challenges for wireless sensor networks (WSNs) since the tiny sensor nodes cannot be easily recharged once they are deployed. Up to now, many energy efficient routing algorithms or protocols have been proposed with techniques like clustering, data aggregation and location tracking etc. However, many of them aim to minimize parameters like total energy consumption, latency etc., which cause hotspot nodes and partitioned network due to the overuse of certain nodes. In this paper, a Distance-based Energy Aware Routing (DEAR) algorithm is proposed to ensure energy efficiency and energy balancing based on theoretical analysis of different energy and traffic models. During the routing process, we consider individual distance as the primary parameter in order to adjust and equalize the energy consumption among involved sensors. The residual energy is also considered as a secondary factor. In this way, all the intermediate nodes will consume their energy at similar rate, which maximizes network lifetime. Simulation results show that the DEAR algorithm can reduce and balance the energy consumption for all sensor nodes so network lifetime is greatly prolonged compared to other routing algorithms. PMID:22163422

  9. FUZZY MAPPING IN DATA SONIFICATION SYSTEM OF WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    Arseny A. Markhotin

    2016-11-01

    Full Text Available Problem Statement. This paper describes the modeling of sonification system with possible types of wireless sensor network data. Fuzzy logic is used for the data-to-sound mapping. Methods. Devised sonification system includes input data model and sound synthesis core. It was created in Pure Data. For fuzzy output of mapped data the Fuzzy Logic Toolboxof MATLABwas used. Moreover, the system model has an ability to send data to the side application via UDP protocol. Results. We offer the method of timbre space organization for sonification system output and the following output of control sound characteristics depending on the type of input data. Practical Relevance. The offered approach of using fuzzy logic in sonification systems can be applied in development of new applications when the formalization of data-to-sound mapping is difficult and also complicated timbal space organization is required.

  10. Wavelet analysis of polarization maps of polycrystalline biological fluids networks

    Science.gov (United States)

    Ushenko, Y. A.

    2011-12-01

    The optical model of human joints synovial fluid is proposed. The statistic (statistic moments), correlation (autocorrelation function) and self-similar (Log-Log dependencies of power spectrum) structure of polarization two-dimensional distributions (polarization maps) of synovial fluid has been analyzed. It has been shown that differentiation of polarization maps of joint synovial fluid with different physiological state samples is expected of scale-discriminative analysis. To mark out of small-scale domain structure of synovial fluid polarization maps, the wavelet analysis has been used. The set of parameters, which characterize statistic, correlation and self-similar structure of wavelet coefficients' distributions of different scales of polarization domains for diagnostics and differentiation of polycrystalline network transformation connected with the pathological processes, has been determined.

  11. Quantitative Risk Mapping of Urban Gas Pipeline Networks Using GIS

    Science.gov (United States)

    Azari, P.; Karimi, M.

    2017-09-01

    Natural gas is considered an important source of energy in the world. By increasing growth of urbanization, urban gas pipelines which transmit natural gas from transmission pipelines to consumers, will become a dense network. The increase in the density of urban pipelines will influence probability of occurring bad accidents in urban areas. These accidents have a catastrophic effect on people and their property. Within the next few years, risk mapping will become an important component in urban planning and management of large cities in order to decrease the probability of accident and to control them. Therefore, it is important to assess risk values and determine their location on urban map using an appropriate method. In the history of risk analysis of urban natural gas pipeline networks, the pipelines has always been considered one by one and their density in urban area has not been considered. The aim of this study is to determine the effect of several pipelines on the risk value of a specific grid point. This paper outlines a quantitative risk assessment method for analysing the risk of urban natural gas pipeline networks. It consists of two main parts: failure rate calculation where the EGIG historical data are used and fatal length calculation that involves calculation of gas release and fatality rate of consequences. We consider jet fire, fireball and explosion for investigating the consequences of gas pipeline failure. The outcome of this method is an individual risk and is shown as a risk map.

  12. QUANTITATIVE RISK MAPPING OF URBAN GAS PIPELINE NETWORKS USING GIS

    Directory of Open Access Journals (Sweden)

    P. Azari

    2017-09-01

    Full Text Available Natural gas is considered an important source of energy in the world. By increasing growth of urbanization, urban gas pipelines which transmit natural gas from transmission pipelines to consumers, will become a dense network. The increase in the density of urban pipelines will influence probability of occurring bad accidents in urban areas. These accidents have a catastrophic effect on people and their property. Within the next few years, risk mapping will become an important component in urban planning and management of large cities in order to decrease the probability of accident and to control them. Therefore, it is important to assess risk values and determine their location on urban map using an appropriate method. In the history of risk analysis of urban natural gas pipeline networks, the pipelines has always been considered one by one and their density in urban area has not been considered. The aim of this study is to determine the effect of several pipelines on the risk value of a specific grid point. This paper outlines a quantitative risk assessment method for analysing the risk of urban natural gas pipeline networks. It consists of two main parts: failure rate calculation where the EGIG historical data are used and fatal length calculation that involves calculation of gas release and fatality rate of consequences. We consider jet fire, fireball and explosion for investigating the consequences of gas pipeline failure. The outcome of this method is an individual risk and is shown as a risk map.

  13. Performance of the surface observation network during MAP

    Energy Technology Data Exchange (ETDEWEB)

    Haeberli, C. [Dept. of Meteorology and Geophysics, Univ. of Vienna (Austria); Federal Office of Meteorology and Climatology (MeteoSwiss), Zurich (Switzerland); Groehn, I.; Steinacker, R.; Poettschacher, W.; Dorninger, M. [Dept. of Meteorology and Geophysics, Univ. of Vienna (Austria)

    2004-04-01

    The comprehensive data collection effort in the framework of the mesoscale alpine programme (MAP) offers the unprecedented possibility to carry out a careful evaluation of the performance of one of the densest surface observational networks of the world. Quality control of meteorological data today is usually seen as an integrated step of prognostic model initialization. If mesoscale models should be validated independently, however, a model independent quality checking procedure becomes important, especially when operating over complex terrain. For that reason DAQUAMAP, a project sponsored by the EUMETNET programme MAP-NWS, was conducted to make a high quality data set available to the scientific community testing high resolution numerical weather forecast models as well as performing diagnostic studies. The applied method of quality control consists of an automatic spatial consistency check of primary atmospheric variables. It allows to recognize gross errors and biases of individual station data and to derive station characteristics as well. The latter is especially important when validating model results with single station data. Due to a separate treatment of GTS and combined GTS and non-GTS station data a distinction of the performance of both networks could be achieved. Also a comparison between a similar exercise done with the ALPEX data set in 1982 and the MAP data set has been carried out. This allows to assess the effect of automatization in the meteorological observation networks which has taken place during the last 20 years. (orig.)

  14. Using Genealogical Mapping and Genetic Neighborhood Sizes to Quantify Dispersal Distances in the Neotropical Passerine, the Black-Capped Vireo.

    Science.gov (United States)

    Athrey, Giridhar; Lance, Richard F; Leberg, Paul L

    2015-01-01

    Dispersal is a key demographic process, ultimately responsible for genetic connectivity among populations. Despite its importance, quantifying dispersal within and between populations has proven difficult for many taxa. Even in passerines, which are among the most intensely studied, individual movement and its relation to gene flow remains poorly understood. In this study we used two parallel genetic approaches to quantify natal dispersal distances in a Neotropical migratory passerine, the black-capped vireo. First, we employed a strategy of sampling evenly across the landscape coupled with parentage assignment to map the genealogical relationships of individuals across the landscape, and estimate dispersal distances; next, we calculated Wright's neighborhood size to estimate gene dispersal distances. We found that a high percentage of captured individuals were assigned at short distances within the natal population, and males were assigned to the natal population more often than females, confirming sex-biased dispersal. Parentage-based dispersal estimates averaged 2400m, whereas gene dispersal estimates indicated dispersal distances ranging from 1600-4200 m. Our study was successful in quantifying natal dispersal distances, linking individual movement to gene dispersal distances, while also providing a detailed look into the dispersal biology of Neotropical passerines. The high-resolution information was obtained with much reduced effort (sampling only 20% of breeding population) compared to mark-resight approaches, demonstrating the potential applicability of parentage-based approaches for quantifying dispersal in other vagile passerine species.

  15. Analysis of Double Meridian Distance for a Closed Traverse Area towards Developing a Contour Map and Land Title

    Directory of Open Access Journals (Sweden)

    T. U. Ganiron Jr

    2014-07-01

    Full Text Available This research aimed to analyze double meridian distance for a closed traverse area in developing a land title for a propose gymnasium in Qassim University. Theodolite, leveling rod and steel tape plays an important role in measuring elevations, bearings and distances of the boundaries of a lot. Contour map is necessary to determine the traces of level surfaces of successive elevation. This will enable to identify the type of contour map and type of contour lines necessary for this project. Corel draw software is used to draw contour map and guide to interpret the significance of the variables. It is essential to check the error of closure for interior angles and for both latitude and departure before applying the Double Meridian Distance (DMD method to obtain the total area of the lot. Technical descriptions of the land such as distance, bearing, boundaries and area are necessary to visualize the shape & exact location of the land. Developing a land title will be obtained using the technical descriptions of the lot in preparation for the type of gymnasium necessary for Qassim University.

  16. Low-Cost Ultrasonic Distance Sensor Arrays with Networked Error Correction

    Directory of Open Access Journals (Sweden)

    Tianzhou Chen

    2013-09-01

    Full Text Available Distance has been one of the basic factors in manufacturing and control fields, and ultrasonic distance sensors have been widely used as a low-cost measuring tool. However, the propagation of ultrasonic waves is greatly affected by environmental factors such as temperature, humidity and atmospheric pressure. In order to solve the problem of inaccurate measurement, which is significant within industry, this paper presents a novel ultrasonic distance sensor model using networked error correction (NEC trained on experimental data. This is more accurate than other existing approaches because it uses information from indirect association with neighboring sensors, which has not been considered before. The NEC technique, focusing on optimization of the relationship of the topological structure of sensor arrays, is implemented for the compensation of erroneous measurements caused by the environment. We apply the maximum likelihood method to determine the optimal fusion data set and use a neighbor discovery algorithm to identify neighbor nodes at the top speed. Furthermore, we adopt the NEC optimization algorithm, which takes full advantage of the correlation coefficients for neighbor sensors. The experimental results demonstrate that the ranging errors of the NEC system are within 2.20%; furthermore, the mean absolute percentage error is reduced to 0.01% after three iterations of this method, which means that the proposed method performs extremely well. The optimized method of distance measurement we propose, with the capability of NEC, would bring a significant advantage for intelligent industrial automation.

  17. Low-cost ultrasonic distance sensor arrays with networked error correction.

    Science.gov (United States)

    Dai, Hongjun; Zhao, Shulin; Jia, Zhiping; Chen, Tianzhou

    2013-09-05

    Distance has been one of the basic factors in manufacturing and control fields, and ultrasonic distance sensors have been widely used as a low-cost measuring tool. However, the propagation of ultrasonic waves is greatly affected by environmental factors such as temperature, humidity and atmospheric pressure. In order to solve the problem of inaccurate measurement, which is significant within industry, this paper presents a novel ultrasonic distance sensor model using networked error correction (NEC) trained on experimental data. This is more accurate than other existing approaches because it uses information from indirect association with neighboring sensors, which has not been considered before. The NEC technique, focusing on optimization of the relationship of the topological structure of sensor arrays, is implemented for the compensation of erroneous measurements caused by the environment. We apply the maximum likelihood method to determine the optimal fusion data set and use a neighbor discovery algorithm to identify neighbor nodes at the top speed. Furthermore, we adopt the NEC optimization algorithm, which takes full advantage of the correlation coefficients for neighbor sensors. The experimental results demonstrate that the ranging errors of the NEC system are within 2.20%; furthermore, the mean absolute percentage error is reduced to 0.01% after three iterations of this method, which means that the proposed method performs extremely well. The optimized method of distance measurement we propose, with the capability of NEC, would bring a significant advantage for intelligent industrial automation.

  18. Wideband Spectrum Sensing Based on Riemannian Distance for Cognitive Radio Networks.

    Science.gov (United States)

    Lu, Qiuyuan; Yang, Shengzhi; Liu, Fan

    2017-03-23

    Detecting the signals of the primary users in the wideband spectrum is a key issue for cognitive radio networks. In this paper, we consider the multi-antenna based signal detection in a wideband spectrum scenario where the noise statistical characteristics are assumed to be unknown. We reason that the covariance matrices of the spectrum subbands have structural constraints and that they describe a manifold in the signal space. Thus, we propose a novel signal detection algorithm based on Riemannian distance and Riemannian mean which is different from the traditional eigenvalue-based detector (EBD) derived with the generalized likelihood ratio criterion. Using the moment matching method, we obtain the closed expression of the decision threshold. From the considered simulation settings, it is shown that the proposed Riemannian distance detector (RDD) has a better performance than the traditional EBD in wideband spectrum sensing.

  19. Protection lightpath-based hitless spectrum defragmentation for distance adaptive elastic optical networks.

    Science.gov (United States)

    Wang, Chao; Shen, Gangxiang; Peng, Limei

    2016-03-07

    Spectrum defragmentation can improve spectrum utilization for an elastic optical network (EON). However, most of the existing studies have focused on defragmentation for working lightpaths, which may affect upper-layer network services. This paper considers protection lightpath-based hitless spectrum defragmentation for distance adaptive elastic optical networks. Without affecting working lightpaths, but defragmenting spectra for protection lightpaths, we expect to achieve truly hitless spectrum defragmentation for an EON. Shared backup path protection (SBPP) technique is employed as a representative network protection technique to evaluate the benefit of the proposed defragmentation scheme. To smooth the network spectra for future arriving lightpath requests so as to reduce bandwidth blocking probability (BBP), we propose two defragmentation triggering mechanisms, namely, defragmentation upon blocking (BTD) and batch defragmentation (BD). For each of them, we also propose two spectrum defragmentation algorithms, namely, defragmentation with sequentially releasing and re-establishing protection lightpaths (SR-D) and defragmentation with jointly releasing and re-establishing protection lightpaths (JR-D). The performances of these proposed algorithms are evaluated from perspectives of BBP and average number of reconfigurations per successfully established lightpath service (ANR). Simulation results show that compared to the case without defragmentation, the proposed scheme is effective to reduce BBP, which trades off with ANR.

  20. Social networks improve leaderless group navigation by facilitating long-distance communication

    Directory of Open Access Journals (Sweden)

    Nikolai W. F. BODE, A. Jamie WOOD, Daniel W. FRANKS

    2012-04-01

    Full Text Available Group navigation is of great importance for many animals, such as migrating flocks of birds or shoals of fish. One theory states that group membership can improve navigational accuracy compared to limited or less accurate individual navigational ability in groups without leaders (“Many-wrongs principle”. Here, we simulate leaderless group navigation that includes social connections as preferential interactions between individuals. Our results suggest that underlying social networks can reduce navigational errors of groups and increase group cohesion. We use network summary statistics, in particular network motifs, to study which characteristics of networks lead to these improvements. It is networks in which preferences between individuals are not clustered, but spread evenly across the group that are advantageous in group navigation by effectively enhancing long-distance information exchange within groups. We suggest that our work predicts a base-line for the type of social structure we might expect to find in group-living animals that navigate without leaders [Current Zoology 58 (2: 329-341, 2012].

  1. Using Hybrid Angle/Distance Information for Distributed Topology Control in Vehicular Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chao-Chi Huang

    2014-10-01

    Full Text Available In a vehicular sensor network (VSN, the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs.

  2. Alteration of long-distance functional connectivity and network topology in patients with supratentorial gliomas

    Energy Technology Data Exchange (ETDEWEB)

    Park, Ji Eun; Kim, Ho Sung; Kim, Sang Joon; Shim, Woo Hyun [University of Ulsan College of Medicine, Department of Radiology and Research Institute of Radiology, Asan Medical Center, Songpa-Gu, Seoul (Korea, Republic of); Kim, Jeong Hoon [University of Ulsan College of Medicine, Department of Neurosurgery, Asan Medical Center, Seoul (Korea, Republic of)

    2016-03-15

    The need for information regarding functional alterations in patients with brain gliomas is increasing, but little is known about the functional consequences of focal brain tumors throughout the entire brain. Using resting-state functional MR imaging (rs-fMRI), this study assessed functional connectivity in patients with supratentorial brain gliomas with possible alterations in long-distance connectivity and network topology. Data from 36 patients with supratentorial brain gliomas and 12 healthy subjects were acquired using rs-fMRI. The functional connectivity matrix (FCM) was created using 32 pairs of cortical seeds on Talairach coordinates in each individual subject. Local and distant connectivity were calculated using z-scores in the individual patient's FCM, and the averaged FCM of patients was compared with that of healthy subjects. Weighted network analysis was performed by calculating local efficiency, global efficiency, clustering coefficient, and small-world topology, and compared between patients and healthy controls. When comparing the averaged FCM of patients with that of healthy controls, the patients showed decreased long-distance, inter-hemispheric connectivity (0.32 ± 0.16 in patients vs. 0. 42 ± 0.15 in healthy controls, p = 0.04). In network analysis, patients showed increased local efficiency (p < 0.05), but global efficiency, clustering coefficient, and small-world topology were relatively preserved compared to healthy subjects. Patients with supratentorial brain gliomas showed decreased long-distance connectivity while increased local efficiency and preserved small-world topology. The results of this small case series may provide a better understanding of the alterations of functional connectivity in patients with brain gliomas across the whole brain scale. (orig.)

  3. MAP-MATCHING IN COMPLEX URBAN ROAD NETWORKS

    Directory of Open Access Journals (Sweden)

    R. B. Noland

    2003-12-01

    Full Text Available Global Navigation Satellite Systems (GNSS such as GPS and digital road maps can be used for land vehicle navigation systems. However, GPS requires a level of augmentation with other navigation sensors and systems such as Dead Reckoning (DR devices, in order to achieve the required navigation performance (RNP in some areas such as urban canyons, streets with dense tree cover, and tunnels. One of the common solutions is to integrate GPS with DR by employing a Kalman Filter (Zhao et al., 2003. The integrated navigation systems usually rely on various types of sensors. Even with very good sensor calibration and sensor fusion technologies, inaccuracies in the positioning sensors are often inevitable. There are also errors associated with spatial road network data. This paper develops an improved probabilistic Map Matching (MM algorithm to reconcile inaccurate locational data with inaccurate digital road network data. The basic characteristics of the algorithm take into account the error sources associated with the positioning sensors, the historical trajectory of the vehicle, topological information on the road network (e.g., connectivity and orientation of links, and the heading and speed information of the vehicle. This then enables a precise identification of the correct link on which the vehicle is travelling. An optimal estimation technique to determine the vehicle position on the link has also been developed and is described. Positioning data was obtained from a comprehensive field test carried out in Central London. The algorithm was tested on a complex urban road network with a high resolution digital road map. The performance of the algorithm was found to be very good for different traffic maneuvers and a significant improvement over using just an integrated GPS/DR solution.

  4. Name-Based Address Mapping for Virtual Private Networks

    Science.gov (United States)

    Surányi, Péter; Shinjo, Yasushi; Kato, Kazuhiko

    IPv4 private addresses are commonly used in local area networks (LANs). With the increasing popularity of virtual private networks (VPNs), it has become common that a user connects to multiple LANs at the same time. However, private address ranges for LANs frequently overlap. In such cases, existing systems do not allow the user to access the resources on all LANs at the same time. In this paper, we propose name-based address mapping for VPNs, a novel method that allows connecting to hosts through multiple VPNs at the same time, even when the address ranges of the VPNs overlap. In name-based address mapping, rather than using the IP addresses used on the LANs (the real addresses), we assign a unique virtual address to each remote host based on its domain name. The local host uses the virtual addresses to communicate with remote hosts. We have implemented name-based address mapping for layer 3 OpenVPN connections on Linux and measured its performance. The communication overhead of our system is less than 1.5% for throughput and less than 0.2ms for each name resolution.

  5. Drones, information technology, and distance: mapping the moral epistemology of remote fighting

    NARCIS (Netherlands)

    Coeckelbergh, Mark

    2013-01-01

    Ethical reflection on drone fighting suggests that this practice does not only create physical distance, but also moral distance: far removed from one’s opponent, it becomes easier to kill. This paper discusses this thesis, frames it as a moral-epistemological problem, and explores the role of

  6. Mapping the follicle-stimulating hormone-induced signalling networks

    Directory of Open Access Journals (Sweden)

    Pauline eGloaguen

    2011-10-01

    Full Text Available Follicle-stimulating hormone (FSH is a central regulator of male and female reproductive function. Over the last decade, there has been a growing perception of the complexity associated with FSH-induced cellular signalling. It is now clear that the canonical Gs/cAMP/PKA pathway is not the sole mechanism that must be considered in FSH biological actions. In parallel, consistent with the emerging concept of biased agonism, several examples of ligand-mediated selective signalling pathway activation by gonadotropin receptors have been reported. In this context, it is important to gain an integrative view of the signalling pathways induced by FSH and how they interconnect to form a network. In this review, we propose a first attempt at building topological maps of various pathways known to be involved in the FSH-induced signalling network. We discuss the multiple facets of FSH-induced signalling and how they converge to the hormone integrated biological response. Despite of their incompleteness, these maps of the FSH-induced signalling network represent a first step towards gaining a system-level comprehension of this hormone’s actions, which may ultimately facilitate the discovery of novel regulatory processes and therapeutic strategies for infertilities and non-steroidal contraception.

  7. Geographic Information Systems Mapping of Diabetic Retinopathy in an Ocular Telemedicine Network.

    Science.gov (United States)

    Jani, Pooja D; Forbes, Lauren; McDaniel, Philip; Viera, Anthony; Garg, Seema

    2017-07-01

    Minimal information exists on the use of geographic information systems mapping for visualizing access barriers to eye care for patients with diabetes. To use geographic information systems mapping techniques to visualize (1) the locations of patients participating in the North Carolina Diabetic Retinopathy Telemedicine Network, (2) the locations of primary care clinicians and ophthalmologists across the state, and (3) the travel times associated with traveling to the 5 primary care clinics in our study. Cross-sectional study conducted from January 6, 2014, to November 1, 2015, at 5 Area Health Education Center primary care clinics that serve rural and underserved populations in North Carolina. In total, 1787 patients with diabetes received retinal screening photographs with remote expert interpretation to determine the presence and severity of diabetic retinopathy. Participants included patients 18 years or older with type 1 or type 2 diabetes who presented to these 5 clinics for their routine diabetes care. Development of qualitative maps illustrating the density of patients with diabetes and their distribution around the 5 North Carolina Diabetic Retinopathy Telemedicine Network sites by zip code and the density of ophthalmologists and primary care clinicians by zip code relative to US Census Urban Areas. A travel time map was also created using road network analysis to determine all areas that can be reached by car in a user-specified amount of time. Mean (SD) age of patients was 55.4 (12.7) years. Women made up 62.7% of the study population. The study included more African American patients (55.4%) compared with white (35.5%) and Hispanic (5.8%) patients. The mean (SD) hemoglobin A1c level was 7.8% (2.4%) (to convert to proportion of total hemoglobin, multiply by 0.01), and the mean (SD) duration of diabetes was 9.2 (8.2) years. Whereas the clinics located in Greensboro, Asheville, and Fayetteville screened patients from more immediate surrounding areas, the

  8. International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis.

    Science.gov (United States)

    Shen, Bin; Zhang, Jiang; Li, Yixiao; Zheng, Qiuhua; Li, Xingsen

    2015-01-01

    This paper models and analyzes international trade flows using open flow networks (OFNs) with the approaches of flow distances, which provide a novel perspective and effective tools for the study of international trade. We discuss the establishment of OFNs of international trade from two coupled viewpoints: the viewpoint of trading commodity flow and that of money flow. Based on the novel model with flow distance approaches, meaningful insights are gained. First, by introducing the concepts of trade trophic levels and niches, countries' roles and positions in the global supply chains (or value-added chains) can be evaluated quantitatively. We find that the distributions of trading "trophic levels" have the similar clustering pattern for different types of commodities, and summarize some regularities between money flow and commodity flow viewpoints. Second, we find that active and competitive countries trade a wide spectrum of products, while inactive and underdeveloped countries trade a limited variety of products. Besides, some abnormal countries import many types of goods, which the vast majority of countries do not need to import. Third, harmonic node centrality is proposed and we find the phenomenon of centrality stratification. All the results illustrate the usefulness of the model of OFNs with its network approaches for investigating international trade flows.

  9. Confession-building, long-distance networks, and the organization of Jesuit science.

    Science.gov (United States)

    Harris, S J

    1996-01-01

    The ability of the Society of Jesus to engage in a broad and enduring tradition of scientific activity is here addressed in terms of its programmatic commitment to the consolidation and extension of the Catholic confession (i.e., to a multipronged program of confession-building) and its mastery of the administrative apparatus necessary to operate long-distance networks. The Society's early move into two major apostolates, one in education and the other in the overseas missions, brought Jesuits into regular contact with the educated elites of Europe and at the same time placed the society's missionaries in remote parts of the natural world. The modes of organization of travel and communication required by the Society's long-distance networks (i.e., the training and deployment of reliable agents willing to work under direction in remote locations and capable of providing trustworthy reports and observations to their superiors through regular exchange of correspondence) not only facilitated scientific communication and collaboration within the order, it also provided Jesuits with the resources they needed to engage successfully in 'ministries among the learned'. Evidence of a sustained attempt by Jesuit authors to assume the role of Kulturträger is found in the several genres of scientific publications that dominate the society's scientific corpus. Thus the society's early recognition of the "apostolic value" of scientific publications in recruiting friends and allies among Europe's intellectual elites, I argue, allowed a robust interest in natural knowledge to emerge as a legitimate part of the Jesuit vocation.

  10. Traveling salesman problems with PageRank Distance on complex networks reveal community structure

    Science.gov (United States)

    Jiang, Zhongzhou; Liu, Jing; Wang, Shuai

    2016-12-01

    In this paper, we propose a new algorithm for community detection problems (CDPs) based on traveling salesman problems (TSPs), labeled as TSP-CDA. Since TSPs need to find a tour with minimum cost, cities close to each other are usually clustered in the tour. This inspired us to model CDPs as TSPs by taking each vertex as a city. Then, in the final tour, the vertices in the same community tend to cluster together, and the community structure can be obtained by cutting the tour into a couple of paths. There are two challenges. The first is to define a suitable distance between each pair of vertices which can reflect the probability that they belong to the same community. The second is to design a suitable strategy to cut the final tour into paths which can form communities. In TSP-CDA, we deal with these two challenges by defining a PageRank Distance and an automatic threshold-based cutting strategy. The PageRank Distance is designed with the intrinsic properties of CDPs in mind, and can be calculated efficiently. In the experiments, benchmark networks with 1000-10,000 nodes and varying structures are used to test the performance of TSP-CDA. A comparison is also made between TSP-CDA and two well-established community detection algorithms. The results show that TSP-CDA can find accurate community structure efficiently and outperforms the two existing algorithms.

  11. Within-host bacterial diversity hinders accurate reconstruction of transmission networks from genomic distance data.

    Science.gov (United States)

    Worby, Colin J; Lipsitch, Marc; Hanage, William P

    2014-03-01

    The prospect of using whole genome sequence data to investigate bacterial disease outbreaks has been keenly anticipated in many quarters, and the large-scale collection and sequencing of isolates from cases is becoming increasingly feasible. While sequence data can provide many important insights into disease spread and pathogen adaptation, it remains unclear how successfully they may be used to estimate individual routes of transmission. Several studies have attempted to reconstruct transmission routes using genomic data; however, these have typically relied upon restrictive assumptions, such as a shared topology of the phylogenetic tree and a lack of within-host diversity. In this study, we investigated the potential for bacterial genomic data to inform transmission network reconstruction. We used simulation models to investigate the origins, persistence and onward transmission of genetic diversity, and examined the impact of such diversity on our estimation of the epidemiological relationship between carriers. We used a flexible distance-based metric to provide a weighted transmission network, and used receiver-operating characteristic (ROC) curves and network entropy to assess the accuracy and uncertainty of the inferred structure. Our results suggest that sequencing a single isolate from each case is inadequate in the presence of within-host diversity, and is likely to result in misleading interpretations of transmission dynamics--under many plausible conditions, this may be little better than selecting transmission links at random. Sampling more frequently improves accuracy, but much uncertainty remains, even if all genotypes are observed. While it is possible to discriminate between clusters of carriers, individual transmission routes cannot be resolved by sequence data alone. Our study demonstrates that bacterial genomic distance data alone provide only limited information on person-to-person transmission dynamics.

  12. Mapping the Regulatory Network for Salmonella enterica Serovar Typhimurium Invasion

    Directory of Open Access Journals (Sweden)

    Carol Smith

    2016-09-01

    Full Text Available Salmonella enterica pathogenicity island 1 (SPI-1 encodes proteins required for invasion of gut epithelial cells. The timing of invasion is tightly controlled by a complex regulatory network. The transcription factor (TF HilD is the master regulator of this process and senses environmental signals associated with invasion. HilD activates transcription of genes within and outside SPI-1, including six other TFs. Thus, the transcriptional program associated with host cell invasion is controlled by at least 7 TFs. However, very few of the regulatory targets are known for these TFs, and the extent of the regulatory network is unclear. In this study, we used complementary genomic approaches to map the direct regulatory targets of all 7 TFs. Our data reveal a highly complex and interconnected network that includes many previously undescribed regulatory targets. Moreover, the network extends well beyond the 7 TFs, due to the inclusion of many additional TFs and noncoding RNAs. By comparing gene expression profiles of regulatory targets for the 7 TFs, we identified many uncharacterized genes that are likely to play direct roles in invasion. We also uncovered cross talk between SPI-1 regulation and other regulatory pathways, which, in turn, identified gene clusters that likely share related functions. Our data are freely available through an intuitive online browser and represent a valuable resource for the bacterial research community.

  13. On Line Segment Length and Mapping 4-regular Grid Structures in Network Infrastructures

    DEFF Research Database (Denmark)

    Riaz, Muhammad Tahir; Nielsen, Rasmus Hjorth; Pedersen, Jens Myrup

    2006-01-01

    The paper focuses on mapping the road network into 4-regular grid structures. A mapping algorithm is proposed. To model the road network GIS data have been used. The Geographic Information System (GIS) data for the road network are composed with different size of line segment lengths...

  14. From language identification to language distance

    Science.gov (United States)

    Gamallo, Pablo; Pichel, José Ramom; Alegria, Iñaki

    2017-10-01

    In this paper, we define two quantitative distances to measure how far apart two languages are. The distance measure that we have identified as more accurate is based on the perplexity of n-gram models extracted from text corpora. An experiment to compare forty-four European languages has been performed. For this purpose, we computed the distances for all the possible language pairs and built a network whose nodes are languages and edges are distances. The network we have built on the basis of linguistic distances represents the current map of similarities and divergences among the main languages of Europe.

  15. A Modified Hopfield Neural Network Algorithm (MHNNA Using ALOS Image for Water Quality Mapping

    Directory of Open Access Journals (Sweden)

    Ahmed Asal Kzar

    2015-12-01

    Full Text Available Decreasing water pollution is a big problem in coastal waters. Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA was used with remote sensing imagery to classify the total suspended solids (TSS concentrations in the waters of coastal Langkawi Island, Malaysia. The adopted remote sensing image is the Advanced Land Observation Satellite (ALOS image acquired on 18 January 2010. Our modification allows the Hopfield neural network to convert and classify color satellite images. The samples were collected from the study area simultaneously with the acquiring of satellite imagery. The sample locations were determined using a handheld global positioning system (GPS. The TSS concentration measurements were conducted in a lab and used for validation (real data, classification, and accuracy assessments. Mapping was achieved by using the MHNNA to classify the concentrations according to their reflectance values in band 1, band 2, and band 3. The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. The first group was used as source samples for supervisor classification via the MHNNA. The second group was used to test the MHNNA efficiency. After mapping, the locations of the second group in the produced classes were detected. Next, the correlation coefficient (R and root mean square error (RMSE were calculated between the two groups, according to their corresponding locations in the classes. The MHNNA exhibited a higher R (0.977 and lower RMSE (2.887. In addition, we test the MHNNA with noise, where it proves its accuracy with noisy images over a range of noise levels. All results have been compared with a minimum distance classifier (Min-Dis. Therefore, TSS mapping of polluted water in the coastal Langkawi Island, Malaysia can be performed using the

  16. Mapping Rice Cropping Systems in Vietnam Using an NDVI-Based Time-Series Similarity Measurement Based on DTW Distance

    Directory of Open Access Journals (Sweden)

    Xudong Guan

    2016-01-01

    Full Text Available Normalized Difference Vegetation Index (NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS time-series data has been widely used in the fields of crop and rice classification. The cloudy and rainy weather characteristics of the monsoon season greatly reduce the likelihood of obtaining high-quality optical remote sensing images. In addition, the diverse crop-planting system in Vietnam also hinders the comparison of NDVI among different crop stages. To address these problems, we apply a Dynamic Time Warping (DTW distance-based similarity measure approach and use the entire yearly NDVI time series to reduce the inaccuracy of classification using a single image. We first de-noise the NDVI time series using S-G filtering based on the TIMESAT software. Then, a standard NDVI time-series base for rice growth is established based on field survey data and Google Earth sample data. NDVI time-series data for each pixel are constructed and the DTW distance with the standard rice growth NDVI time series is calculated. Then, we apply thresholds to extract rice growth areas. A qualitative assessment using statistical data and a spatial assessment using sampled data from the rice-cropping map reveal a high mapping accuracy at the national scale between the statistical data, with the corresponding R2 being as high as 0.809; however, the mapped rice accuracy decreased at the provincial scale due to the reduced number of rice planting areas per province. An analysis of the results indicates that the 500-m resolution MODIS data are limited in terms of mapping scattered rice parcels. The results demonstrate that the DTW-based similarity measure of the NDVI time series can be effectively used to map large-area rice cropping systems with diverse cultivation processes.

  17. Improved Object Localization Using Accurate Distance Estimation in Wireless Multimedia Sensor Networks

    Science.gov (United States)

    Ur Rehman, Yasar Abbas; Tariq, Muhammad; Khan, Omar Usman

    2015-01-01

    Object localization plays a key role in many popular applications of Wireless Multimedia Sensor Networks (WMSN) and as a result, it has acquired a significant status for the research community. A significant body of research performs this task without considering node orientation, object geometry and environmental variations. As a result, the localized object does not reflect the real world scenarios. In this paper, a novel object localization scheme for WMSN has been proposed that utilizes range free localization, computer vision, and principle component analysis based algorithms. The proposed approach provides the best possible approximation of distance between a wmsn sink and an object, and the orientation of the object using image based information. Simulation results report 99% efficiency and an error ratio of 0.01 (around 1 ft) when compared to other popular techniques. PMID:26528919

  18. Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures

    Directory of Open Access Journals (Sweden)

    Daniel Carl Miner

    2014-11-01

    Full Text Available The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results.

  19. Slicing, sampling, and distance-dependent effects affect network measures in simulated cortical circuit structures.

    Science.gov (United States)

    Miner, Daniel C; Triesch, Jochen

    2014-01-01

    The neuroanatomical connectivity of cortical circuits is believed to follow certain rules, the exact origins of which are still poorly understood. In particular, numerous nonrandom features, such as common neighbor clustering, overrepresentation of reciprocal connectivity, and overrepresentation of certain triadic graph motifs have been experimentally observed in cortical slice data. Some of these data, particularly regarding bidirectional connectivity are seemingly contradictory, and the reasons for this are unclear. Here we present a simple static geometric network model with distance-dependent connectivity on a realistic scale that naturally gives rise to certain elements of these observed behaviors, and may provide plausible explanations for some of the conflicting findings. Specifically, investigation of the model shows that experimentally measured nonrandom effects, especially bidirectional connectivity, may depend sensitively on experimental parameters such as slice thickness and sampling area, suggesting potential explanations for the seemingly conflicting experimental results.

  20. Mapping epileptic activity: sources or networks for the clinicians?

    Directory of Open Access Journals (Sweden)

    Francesca ePittau

    2014-11-01

    Full Text Available Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localisation of relevant structural lesions and selection of patients for epilepsy surgery. Recent progresses in neuro-imaging and electro-physiology and combinations thereof have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in humans and animal models for characterizing network connectivity.

  1. How do general practice residents use social networking sites in asynchronous distance learning?

    Science.gov (United States)

    Maisonneuve, Hubert; Chambe, Juliette; Lorenzo, Mathieu; Pelaccia, Thierry

    2015-09-21

    Blended learning environments - involving both face-to-face and remote interactions - make it easier to adapt learning programs to constraints such as residents' location and low teacher-student ratio. Social networking sites (SNS) such as Facebook®, while not originally intended to be used as learning environments, may be adapted for the distance-learning part of training programs. The purpose of our study was to explore the use of SNS for asynchronous distance learning in a blended learning environment as well as its influence on learners' face-to-face interactions. We conducted a qualitative study and carried out semi-structured interviews. We performed purposeful sampling for maximal variation to include eight general practice residents in 2(nd) and 3(rd) year training. A thematic analysis was performed. The social integration of SNS facilitates the engagement of users in their learning tasks. This may also stimulate students' interactions and group cohesion when members meet up in person. Most of the general practice residents who work in the blended learning environment we studied had a positive appraisal on their use of SNS. In particular, we report a positive impact on their engagement in learning and their participation in discussions during face-to-face instruction. Further studies are needed in order to evaluate the effectiveness of SNS in blended learning environments and the appropriation of SNS by teachers.

  2. Making the Transition from Print: Integrating Concept Mapping and Online Communication with Traditional Distance Education Materials.

    Science.gov (United States)

    Kennedy, David M.; Reiman, Cornelis A.

    The move from traditional paper-based distance education subject materials to those of information and communication technologies (ICT) has increased the ways in which students can engage with their lecturers, peers and the unit materials. In this paper, strategies for enhancing print-based learning resources are discussed. These include concept…

  3. KEY ISSUES OF CONCEPTS' FORMATION OF THE NETWORK OF RESOURCE CENTER OF DISTANCE EDUCATION OF GENERAL EDUCATION INSTITUTIONS

    Directory of Open Access Journals (Sweden)

    Yuriy M. Bogachkov

    2013-06-01

    Full Text Available In the article the problem of constructing a network of resource centers for Distance Education to meet the needs of general secondary schools is presented. Modern educational trends in the use of Internet services in education are viewed.  Main contradictions, solution of which helps to create a network of resource centers, are identified. The definition of key terms related to the range of issues are given. The basic categories of participants, who  implementation of e-learning and networking are oriented on. There are considered the basic tasks of  distance education resource centers' functioning and types of supporting: personnel, regulatory, informative, systematic and  technical etc. The review of possible models of implementation of  students' distance education is reviewed . Three options for business models of resource centers, depending on funding  sources are offered.

  4. Representing the environment 3.0. Maps, models, networks.

    Directory of Open Access Journals (Sweden)

    Letizia Bollini

    2014-05-01

    Full Text Available Web 3.0 is changing the world we live and perceive the environment anthropomorphized, making a stratifation of levels of experience and mediated by the devices. If the urban landscape is designed, shaped and planned space, there is a social landscape that overwrite the territory of values, representations shared images, narratives of personal and collective history. Mobile technology introduces an additional parameter, a kind of non-place, which allows the coexistence of the here and elsewhere in an sort of digital landscape. The maps, mental models, the system of social networks become, then, the way to present, represented and represent themselves in a kind of ideal coring of the co-presence of levels of physical, cognitive and collective space.

  5. Gene transcription profiles associated with inter-modular hubs and connection distance in human functional magnetic resonance imaging networks.

    Science.gov (United States)

    Vértes, Petra E; Rittman, Timothy; Whitaker, Kirstie J; Romero-Garcia, Rafael; Váša, František; Kitzbichler, Manfred G; Wagstyl, Konrad; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T

    2016-10-05

    Human functional magnetic resonance imaging (fMRI) brain networks have a complex topology comprising integrative components, e.g. long-distance inter-modular edges, that are theoretically associated with higher biological cost. Here, we estimated intra-modular degree, inter-modular degree and connection distance for each of 285 cortical nodes in multi-echo fMRI data from 38 healthy adults. We used the multivariate technique of partial least squares (PLS) to reduce the dimensionality of the relationships between these three nodal network parameters and prior microarray data on regional expression of 20 737 genes. The first PLS component defined a transcriptional profile associated with high intra-modular degree and short connection distance, whereas the second PLS component was associated with high inter-modular degree and long connection distance. Nodes in superior and lateral cortex with high inter-modular degree and long connection distance had local transcriptional profiles enriched for oxidative metabolism and mitochondria, and for genes specific to supragranular layers of human cortex. In contrast, primary and secondary sensory cortical nodes in posterior cortex with high intra-modular degree and short connection distance had transcriptional profiles enriched for RNA translation and nuclear components. We conclude that, as predicted, topologically integrative hubs, mediating long-distance connections between modules, are more costly in terms of mitochondrial glucose metabolism.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.

  6. Indoor Positioning System Using Depth Maps and Wireless Networks

    Directory of Open Access Journals (Sweden)

    Jaime Duque Domingo

    2016-01-01

    Full Text Available This work presents a new Indoor Positioning System (IPS based on the combination of WiFi Positioning System (WPS and depth maps, for estimating the location of people. The combination of both technologies improves the efficiency of existing methods, based uniquely on wireless positioning techniques. While other positioning systems force users to wear special devices, the system proposed in this paper just requires the use of smartphones, besides the installation of RGB-D sensors in the sensing area. Furthermore, the system is not intrusive, being not necessary to know people’s identity. The paper exposes the method developed for putting together and exploiting both types of sensory information with positioning purposes: the measurements of the level of the signal received from different access points (APs of the wireless network and the depth maps provided by the RGB-D cameras. The obtained results show a significant improvement in terms of positioning with respect to common WiFi-based systems.

  7. Method and system for a network mapping service

    Energy Technology Data Exchange (ETDEWEB)

    Bynum, Leo

    2017-10-17

    A method and system of publishing a map includes providing access to a plurality of map data files or mapping services between at least one publisher and at least one subscriber; defining a map in a map context comprising parameters and descriptors to substantially duplicate a map by reference to mutually accessible data or mapping services, publishing a map to a channel in a table file on server; accessing the channel by at least one subscriber, transmitting the mapping context from the server to the at least one subscriber, executing the map context by the at least one subscriber, and generating the map on a display software associated with the at least one subscriber by reconstituting the map from the references and other data in the mapping context.

  8. Mapping collaboration networks in the world of Autism Research.

    Science.gov (United States)

    Goldstein, Neal D; Tager-Flusberg, Helen; Lee, Brian K

    2015-02-01

    In the era of globalization and with the emergence of autism spectrum disorder as a global concern, the landscape of autism research has expanded to encompass much of the world. Here, we seek to provide an overview of the world of autism research, by documenting collaboration underlying the International Meeting for Autism Research (IMFAR), the pre-eminent annual scientific meeting devoted to the presentation of the latest autism research. We analyzed published abstracts presented at IMFAR meetings, between 2008 and 2013, to determine patterns of collaboration. We described collaboration networks on the individual, institutional, and international levels, and visually depicted these results on spatial network maps. Consistent with findings from other scientific disciplines, we found that collaboration is correlated with research productivity. Collaborative hotspots of autism research throughout the years were clustered on the East and West coasts of the U.S., Canada, and northern Europe. In years when conferences were held outside of North America, the proportion of abstracts from Europe and Asia increased. While IMFAR has traditionally been dominated by a large North American presence, greater global representation may be attained by shifting meeting locations to other regions of the world. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

  9. Mapping effective connectivity within cortical networks with diffuse optical tomography.

    Science.gov (United States)

    Hassanpour, Mahlega S; Eggebrecht, Adam T; Peelle, Jonathan E; Culver, Joseph P

    2017-10-01

    Understanding how cortical networks interact in response to task demands is important both for providing insight into the brain's processing architecture and for managing neurological diseases and mental disorders. High-density diffuse optical tomography (HD-DOT) is a neuroimaging technique that offers the significant advantages of having a naturalistic, acoustically controllable environment and being compatible with metal implants, neither of which is possible with functional magnetic resonance imaging. We used HD-DOT to study the effective connectivity and assess the modulatory effects of speech intelligibility and syntactic complexity on functional connections within the cortical speech network. To accomplish this, we extend the use of a generalized psychophysiological interaction (PPI) analysis framework. In particular, we apply PPI methods to event-related HD-DOT recordings of cortical oxyhemoglobin activity during auditory sentence processing. We evaluate multiple approaches for selecting cortical regions of interest and for modeling interactions among these regions. Our results show that using subject-based regions has minimal effect on group-level connectivity maps. We also demonstrate that incorporating an interaction model based on estimated neural activity results in significantly stronger effective connectivity. Taken together our findings support the use of HD-DOT with PPI methods for noninvasively studying task-related modulations of functional connectivity.

  10. An integrated approach of analytical network process and fuzzy based spatial decision making systems applied to landslide risk mapping

    Science.gov (United States)

    Abedi Gheshlaghi, Hassan; Feizizadeh, Bakhtiar

    2017-09-01

    Landslides in mountainous areas render major damages to residential areas, roads, and farmlands. Hence, one of the basic measures to reduce the possible damage is by identifying landslide-prone areas through landslide mapping by different models and methods. The purpose of conducting this study is to evaluate the efficacy of a combination of two models of the analytical network process (ANP) and fuzzy logic in landslide risk mapping in the Azarshahr Chay basin in northwest Iran. After field investigations and a review of research literature, factors affecting the occurrence of landslides including slope, slope aspect, altitude, lithology, land use, vegetation density, rainfall, distance to fault, distance to roads, distance to rivers, along with a map of the distribution of occurred landslides were prepared in GIS environment. Then, fuzzy logic was used for weighting sub-criteria, and the ANP was applied to weight the criteria. Next, they were integrated based on GIS spatial analysis methods and the landslide risk map was produced. Evaluating the results of this study by using receiver operating characteristic curves shows that the hybrid model designed by areas under the curve 0.815 has good accuracy. Also, according to the prepared map, a total of 23.22% of the area, amounting to 105.38 km2, is in the high and very high-risk class. Results of this research are great of importance for regional planning tasks and the landslide prediction map can be used for spatial planning tasks and for the mitigation of future hazards in the study area.

  11. Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

    Science.gov (United States)

    Peng, Yefei

    2010-01-01

    An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

  12. Mapping the geography of science: distribution patterns and networks of relations among cities and institutes

    NARCIS (Netherlands)

    Leydesdorff, L.; Persson, O.

    2010-01-01

    Using Google Earth, Google Maps, and/or network visualization programs such as Pajek, one can overlay the network of relations among addresses in scientific publications onto the geographic map. The authors discuss the pros and cons of various options, and provide software (freeware) for bridging

  13. ANALYSIS RESOURCE AWARE FRAMEWORK BY COMBINING SUNSPOT AND IMOTE2 PLATFORM WIRELESS SENSOR NETWORKS USING DISTANCE VECTOR ALGORITHM

    Directory of Open Access Journals (Sweden)

    Muhammad Ilyas Syarif

    2012-07-01

    Full Text Available Efficiency energy and stream data mining on Wireless Sensor Networks (WSNs are a very interesting issue to be discussed. Routing protocols technology and resource-aware can be done to improve energy efficiency. In this paper we try to merge routing protocol technology using routing Distance Vector and Resource-Aware (RA framework on heterogeneity wireless sensor networks by combining sun-SPOT and Imote2 platform wireless sensor networks. RA perform resource monitoring process of the battery, memory and CPU load more optimally and efficiently. The process uses Light-Weight Clustering (LWC and Light Weight Frequent Item (LWF. The results obtained that by adapting Resource-Aware in wireless sensor networks, the lifetime of wireless sensor improve up to ± 16.62%. Efisiensi energi dan stream data mining pada Wireless Sensor Networks (WSN adalah masalah yang sangat menarik untuk dibahas. Teknologi Routing Protocol dan Resource-Aware dapat dilakukan untuk meningkatkan efisiensi energi. Dalam penelitian ini peneliti mencoba untuk menggabungkan teknologi Routing Protocol menggunakan routing Distance Vector dan Resource-Aware (RA framework pada Wireless Sensor Networks heterogen dengan menggabungkan sun-SPOT dan platform Imote2 Wireless Sensor Networks. RA melakukan proses pemantauan sumber daya dari memori, baterai, dan beban CPU lebih optimal dan efisien. Proses ini menggunakan Light-Weight Clustering (LWC dan Light Weight Frequent Item (LWF. Hasil yang diperoleh bahwa dengan mengadaptasi Resource-Aware dalam Wireless Sensor Networks, masa pakai wireless sensor meningkatkan sampai ± 16,62%.

  14. Real-time method for establishing a detection map for a network of sensors

    Science.gov (United States)

    Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

    2012-09-11

    A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

  15. Reducing distance errors for standard candles and standard sirens with weak-lensing shear and flexion maps

    Science.gov (United States)

    Hilbert, Stefan; Gair, Jonathan R.; King, Lindsay J.

    2011-04-01

    Gravitational lensing induces significant errors in the measured distances to high-redshift standard candles and standard sirens such as Type Ia supernovae, gamma-ray bursts and merging supermassive black hole binaries. There will therefore be a significant benefit from correcting for the lensing error by using independent and accurate estimates of the lensing magnification. Here, we investigate how accurately the magnification can be inferred from convergence maps reconstructed from galaxy shear and flexion data. We employ ray-tracing through the Millennium Simulation (MS) to simulate lensing observations in large fields, and perform a weak-lensing reconstruction on the simulated fields. We identify optimal ways to filter the reconstructed convergence maps and to convert them to magnification maps, and analyse the resulting relation between the estimated and true magnification for sources at redshifts zS= 1 to 5. We find that a deep shear survey with 100 galaxies arcmin-2 can help to reduce the lensing-induced distance errors for standard candles/sirens at redshifts zS≈ 1.5 (zS≈ 5) on average by 20 per cent (10 per cent), whereas a futuristic survey with shear and flexion estimates from 500 galaxies arcmin-2 yields much larger reductions of 50 per cent (35 per cent). For redshifts zS≥ 3, a further improvement by ˜5 per cent can be achieved, if the individual redshifts of the galaxies are used in the reconstruction. Moreover, the reconstruction allows one to identify regions for which the convergence is low, and in which an error reduction by up to 75 per cent can be achieved. Such strongly reduced magnification uncertainties will greatly improve the value of high-redshift standard candles/sirens as cosmological probes.

  16. MAPPING OF RIVER WATER QUALITY USING INVERSE DISTANCE WEIGHTED INTERPOLATION IN OGUN-OSUN RIVER BASIN, NIGERIA

    Directory of Open Access Journals (Sweden)

    ADEBAYO OLUBUKOLA OKE

    2013-09-01

    Full Text Available Sustainable management of water resources involves inventory, conservation, efficient utilization, and quality management. Although, activities relating to quantity assessment and management in terms of river discharge and water resources planning are given attention at the basin level, water quality assessment are still being done at specific locations of major concern. The use of Geographical Information System (GIS based water quality information system and spatial analysis with Inverse Distance Weighted interpolation enabled the mapping of water quality indicators in Ogun and Ona catchment of Ogun-Osun River Basin, Nigeria. Using 27 established gauging stations as sampling locations, water quality indicators were monitored over 12 months covering full hydrological season. Maps of seasonal variations in 10 water quality indicators as impacted by land-use types were produced. This ensured that trends of specific water quality indicator and diffuse pollution characteristics across the basin were better presented with the variations shown along the river courses than the traditional line graphs. The production of water quality maps will improve monitoring, enforcement of standards and regulations towards better pollution management and control. This strategy holds great potential for real time monitoring of water quality in the basin with adequate instrumentation.

  17. Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks With Jaccard Distance.

    Science.gov (United States)

    Yuan, Yading; Chao, Ming; Lo, Yeh-Chi

    2017-09-01

    Automatic skin lesion segmentation in dermoscopic images is a challenging task due to the low contrast between lesion and the surrounding skin, the irregular and fuzzy lesion borders, the existence of various artifacts, and various imaging acquisition conditions. In this paper, we present a fully automatic method for skin lesion segmentation by leveraging 19-layer deep convolutional neural networks that is trained end-to-end and does not rely on prior knowledge of the data. We propose a set of strategies to ensure effective and efficient learning with limited training data. Furthermore, we design a novel loss function based on Jaccard distance to eliminate the need of sample re-weighting, a typical procedure when using cross entropy as the loss function for image segmentation due to the strong imbalance between the number of foreground and background pixels. We evaluated the effectiveness, efficiency, as well as the generalization capability of the proposed framework on two publicly available databases. One is from ISBI 2016 skin lesion analysis towards melanoma detection challenge, and the other is the PH2 database. Experimental results showed that the proposed method outperformed other state-of-the-art algorithms on these two databases. Our method is general enough and only needs minimum pre- and post-processing, which allows its adoption in a variety of medical image segmentation tasks.

  18. A network of topographic numerosity maps in human association cortex

    NARCIS (Netherlands)

    Harvey, Ben M.; Dumoulin, Serge O.

    2017-01-01

    Sensory and motor cortices each contain multiple topographic maps with the structure of sensory organs (such as the retina or cochlea) mapped onto the cortical surface. These sensory maps are hierarchically organized. For example, visual field maps contain neurons that represent increasingly large

  19. A network of topographic numerosity maps in human association cortex.

    NARCIS (Netherlands)

    Harvey, Ben M.; Dumoulin, Serge O.

    2017-01-01

    Sensory and motor cortices each contain multiple topographic maps with the structure of sensory organs (such as the retina or cochlea) mapped onto the cortical surface. These sensory maps are hierarchically organized. For example, visual field maps contain neurons that represent increasingly large

  20. Exponential distance distribution of connected neurons in simulations of two-dimensional in vitro neural network development

    Science.gov (United States)

    Lv, Zhi-Song; Zhu, Chen-Ping; Nie, Pei; Zhao, Jing; Yang, Hui-Jie; Wang, Yan-Jun; Hu, Chin-Kun

    2017-06-01

    The distribution of the geometric distances of connected neurons is a practical factor underlying neural networks in the brain. It can affect the brain's dynamic properties at the ground level. Karbowski derived a power-law decay distribution that has not yet been verified by experiment. In this work, we check its validity using simulations with a phenomenological model. Based on the in vitro two-dimensional development of neural networks in culture vessels by Ito, we match the synapse number saturation time to obtain suitable parameters for the development process, then determine the distribution of distances between connected neurons under such conditions. Our simulations obtain a clear exponential distribution instead of a power-law one, which indicates that Karbowski's conclusion is invalid, at least for the case of in vitro neural network development in two-dimensional culture vessels.

  1. Logistic regression and artificial neural network models for mapping of regional-scale landslide susceptibility in volcanic mountains of West Java (Indonesia)

    Science.gov (United States)

    Ngadisih, Bhandary, Netra P.; Yatabe, Ryuichi; Dahal, Ranjan K.

    2016-05-01

    West Java Province is the most landslide risky area in Indonesia owing to extreme geo-morphological conditions, climatic conditions and densely populated settlements with immense completed and ongoing development activities. So, a landslide susceptibility map at regional scale in this province is a fundamental tool for risk management and land-use planning. Logistic regression and Artificial Neural Network (ANN) models are the most frequently used tools for landslide susceptibility assessment, mainly because they are capable of handling the nature of landslide data. The main objective of this study is to apply logistic regression and ANN models and compare their performance for landslide susceptibility mapping in volcanic mountains of West Java Province. In addition, the model application is proposed to identify the most contributing factors to landslide events in the study area. The spatial database built in GIS platform consists of landslide inventory, four topographical parameters (slope, aspect, relief, distance to river), three geological parameters (distance to volcano crater, distance to thrust and fault, geological formation), and two anthropogenic parameters (distance to road, land use). The logistic regression model in this study revealed that slope, geological formations, distance to road and distance to volcano are the most influential factors of landslide events while, the ANN model revealed that distance to volcano crater, geological formation, distance to road, and land-use are the most important causal factors of landslides in the study area. Moreover, an evaluation of the model showed that the ANN model has a higher accuracy than the logistic regression model.

  2. Addressing the Influence of Hidden State on Wireless Network Optimizations using Performance Maps

    DEFF Research Database (Denmark)

    Højgaard-Hansen, Kim; Madsen, Tatiana Kozlova; Schwefel, Hans-Peter

    2015-01-01

    Performance of wireless connectivity for network client devices is location dependent. It has been shown that it can be beneficial to collect network performance metrics along with location information to generate maps of the location dependent network performance. These performance maps can...... be used to optimize the use of the wireless net- work by predicting future network performance and scheduling the net- work communication for certain applications on mobile devices. However, other important factors influence the performance of the wireless communication such as changes in the propagation...... environment and resource sharing. In this work we extend the framework of performance maps for wireless networks by introducing network state as an abstraction for all other factors than location that influence the performance. Since network state might not always be directly observable the framework...

  3. DIMACS Workshop on Interconnection Networks and Mapping, and Scheduling Parallel Computations

    CERN Document Server

    Rosenberg, Arnold L; Sotteau, Dominique; NSF Science and Technology Center in Discrete Mathematics and Theoretical Computer Science; Interconnection networks and mapping and scheduling parallel computations

    1995-01-01

    The interconnection network is one of the most basic components of a massively parallel computer system. Such systems consist of hundreds or thousands of processors interconnected to work cooperatively on computations. One of the central problems in parallel computing is the task of mapping a collection of processes onto the processors and routing network of a parallel machine. Once this mapping is done, it is critical to schedule computations within and communication among processor from universities and laboratories, as well as practitioners involved in the design, implementation, and application of massively parallel systems. Focusing on interconnection networks of parallel architectures of today and of the near future , the book includes topics such as network topologies,network properties, message routing, network embeddings, network emulation, mappings, and efficient scheduling. inputs for a process are available where and when the process is scheduled to be computed. This book contains the refereed pro...

  4. Bifurcation behaviors of synchronized regions in logistic map networks with coupling delay

    Science.gov (United States)

    Tang, Longkun; Wu, Xiaoqun; Lü, Jinhu; Lu, Jun-an

    2015-03-01

    Network synchronized regions play an extremely important role in network synchronization according to the master stability function framework. This paper focuses on network synchronous state stability via studying the effects of nodal dynamics, coupling delay, and coupling way on synchronized regions in Logistic map networks. Theoretical and numerical investigations show that (1) network synchronization is closely associated with its nodal dynamics. Particularly, the synchronized region bifurcation points through which the synchronized region switches from one type to another are in good agreement with those of the uncoupled node system, and chaotic nodal dynamics can greatly impede network synchronization. (2) The coupling delay generally impairs the synchronizability of Logistic map networks, which is also dominated by the parity of delay for some nodal parameters. (3) A simple nonlinear coupling facilitates network synchronization more than the linear one does. The results found in this paper will help to intensify our understanding for the synchronous state stability in discrete-time networks with coupling delay.

  5. Nonlinear Maps for Design of Discrete Time Models of Neuronal Network Dynamics

    Science.gov (United States)

    2016-02-29

    SUPPLEMENTARY NOTES 14. ABSTRACT A new promising way to significantly improve computational efficiency of neurobiological network simulations is to design a...network activity. D· 1S. SUBJECT TERMS Map-based neuronal model, Discrete time spiking dynamics, Synapses, Neurons, Neurobiological Networks 16...advertisement for search of suitable candidate and posted it in several forum groups related to computational neurobiology . Task 1. Meanwhile I

  6. Artificial Neural Network Approach for Mapping Contrasting Tillage Practices

    Directory of Open Access Journals (Sweden)

    Terry Howell

    2010-02-01

    Full Text Available Tillage information is crucial for environmental modeling as it directly affects evapotranspiration, infiltration, runoff, carbon sequestration, and soil losses due to wind and water erosion from agricultural fields. However, collecting this information can be time consuming and costly. Remote sensing approaches are promising for rapid collection of tillage information on individual fields over large areas. Numerous regression-based models are available to derive tillage information from remote sensing data. However, these models require information about the complex nature of underlying watershed characteristics and processes. Unlike regression-based models, Artificial Neural Network (ANN provides an efficient alternative to map complex nonlinear relationships between an input and output datasets without requiring a detailed knowledge of underlying physical relationships. Limited or no information currently exist quantifying ability of ANN models to identify contrasting tillage practices from remote sensing data. In this study, a set of Landsat TM-based ANN models was developed to identify contrasting tillage practices in the Texas High Plains. Observed tillage data from Moore and Ochiltree Counties were used to develop and evaluate the models, respectively. The overall classification accuracy for the 15 models developed with the Moore County dataset varied from 74% to 91%. Statistical evaluation of these models against the Ochiltree County dataset produced results with an overall classification accuracy varied from 66% to 80%. The ANN models based on TM band 5 or indices of TM Band 5 may provide consistent and accurate tillage information when applied to the Texas High Plains.

  7. Empirical evidence of the effectiveness of concept mapping as a learning intervention for nuclear medicine technology students in a distance learning radiation protection and biology course.

    Science.gov (United States)

    Passmore, Gregory G; Owen, Mary Anne; Prabakaran, Krishnan

    2011-12-01

    Metacognitive learning strategies are based on instructional learning theory, which promotes deep, meaningful learning. Educators in a baccalaureate-level nuclear medicine technology program demonstrated that students enrolled in an online, distance learning section of an introductory radiation protection and radiobiology course performed better when traditional instruction was supplemented with nontraditional metacognitive learning strategies. The metacognitive learning strategy that was used is best known as concept mapping. The concept map, in addition to the standard homework problem assignment and opportunity for question-answer sessions, became the template for misconception identification and remediation interactions between the instructor and the student. The control group relied on traditional homework problems and question-answer sessions alone. Because students in both the "treatment" groups (i.e., students who used concept mapping) and the control group were distance learning students, all personal communications were conducted via e-mail or telephone. The final examination of the course was used to facilitate a quantitative comparison of the performance of students who used concept mapping and the performance of students who did not use concept mapping. The results demonstrated a significantly higher median final examination score for the concept mapping group than for the non-concept mapping group (z = -2.0381, P = 0.0415), with an appropriately large effect size (2.65). Concept mapping is a cognitive learning intervention that effectively enables meaningful learning and is suitable for use in the independent learner-oriented distance learning environments used by some nuclear medicine technology programs.

  8. Spectrum efficient distance-adaptive paths for fixed and fixed-alternate routing in elastic optical networks

    Science.gov (United States)

    Agrawal, Anuj; Bhatia, Vimal; Prakash, Shashi

    2018-01-01

    Efficient utilization of spectrum is a key concern in the soon to be deployed elastic optical networks (EONs). To perform routing in EONs, various fixed routing (FR), and fixed-alternate routing (FAR) schemes are ubiquitously used. FR, and FAR schemes calculate a fixed route, and a prioritized list of a number of alternate routes, respectively, between different pairs of origin o and target t nodes in the network. The route calculation performed using FR and FAR schemes is predominantly based on either the physical distance, known as k -shortest paths (KSP), or on the hop count (HC). For survivable optical networks, FAR usually calculates link-disjoint (LD) paths. These conventional routing schemes have been efficiently used for decades in communication networks. However, in this paper, it has been demonstrated that these commonly used routing schemes cannot utilize the network spectral resources optimally in the newly introduced EONs. Thus, we propose a new routing scheme for EON, namely, k -distance adaptive paths (KDAP) that efficiently utilizes the benefit of distance-adaptive modulation, and bit rate-adaptive superchannel capability inherited by EON to improve spectrum utilization. In the proposed KDAP, routes are found and prioritized on the basis of bit rate, distance, spectrum granularity, and the number of links used for a particular route. To evaluate the performance of KSP, HC, LD, and the proposed KDAP, simulations have been performed for three different sized networks, namely, 7-node test network (TEST7), NSFNET, and 24-node US backbone network (UBN24). We comprehensively assess the performance of various conventional, and the proposed routing schemes by solving both the RSA and the dual RSA problems under homogeneous and heterogeneous traffic requirements. Simulation results demonstrate that there is a variation amongst the performance of KSP, HC, and LD, depending on the o - t pair, and the network topology and its connectivity. However, the proposed

  9. Hop-distance relationship analysis with quasi-UDG model for node localization in wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Chen Ping

    2011-01-01

    Full Text Available Abstract In wireless sensor networks (WSNs, location information plays an important role in many fundamental services which includes geographic routing, target tracking, location-based coverage, topology control, and others. One promising approach in sensor network localization is the determination of location based on hop counts. A critical priori of this approach that directly influences the accuracy of location estimation is the hop-distance relationship. However, most of the related works on the hop-distance relationship assume the unit-disk graph (UDG model that is unrealistic in a practical scenario. In this paper, we formulate the hop-distance relationship for quasi-UDG model in WSNs where sensor nodes are randomly and independently deployed in a circular region based on a Poisson point process. Different from the UDG model, quasi-UDG model has the non-uniformity property for connectivity. We derive an approximated recursive expression for the probability of the hop count with a given geographic distance. The border effect and dependence problem are also taken into consideration. Furthermore, we give the expressions describing the distribution of distance with known hop counts for inner nodes and those suffered from the border effect where we discover the insignificance of the border effect. The analytical results are validated by simulations showing the accuracy of the employed approximation. Besides, we demonstrate the localization application of the formulated relationship and show the accuracy improvement in the WSN localization.

  10. Virtual Network Embedding: A Hybrid Vertex Mapping Solution for Dynamic Resource Allocation

    Directory of Open Access Journals (Sweden)

    Adil Razzaq

    2012-01-01

    Full Text Available Virtual network embedding (VNE is a key area in network virtualization, and the overall purpose of VNE is to map virtual networks onto an underlying physical network referred to as a substrate. Typically, the virtual networks have certain demands, such as resource requirements, that need to be satisfied by the mapping process. A virtual network (VN can be described in terms of vertices (nodes and edges (links with certain resource requirements, and, to embed a VN, substrate resources are assigned to these vertices and edges. Substrate networks have finite resources and utilizing them efficiently is an important objective for a VNE method. This paper analyzes two existing vertex mapping approaches—one which only considers if enough node resources are available for the current VN mapping and one which considers to what degree a node already is utilized by existing VN embeddings before doing the vertex mapping. The paper also proposes a new vertex mapping approach which minimizes complete exhaustion of substrate nodes while still providing good overall resource utilization. Experimental results are presented to show under what circumstances the proposed vertex mapping approach can provide superior VN embedding properties compared to the other approaches.

  11. Localization of networks with presence and distance constraints based on 1-hop and 2-hop mass–spring optimization

    Directory of Open Access Journals (Sweden)

    Gabriele Oliva

    2016-03-01

    Full Text Available In this paper we consider the localization of a sensor network where the nodes are heterogeneous, in that some of them are able to measure the distance from their neighbors, while some others are just able to detect their presence, and we provide a post-processing algorithm that can be used to improve an initial estimate for the location of the nodes, based on a mass–spring optimization approach, taking into account presence and distance information, as well as one-hop and two-hop information.

  12. A brief history of excitable map-based neurons and neural networks.

    Science.gov (United States)

    Girardi-Schappo, M; Tragtenberg, M H R; Kinouchi, O

    2013-11-15

    This review gives a short historical account of the excitable maps approach for modeling neurons and neuronal networks. Some early models, due to Pasemann (1993), Chialvo (1995) and Kinouchi and Tragtenberg (1996), are compared with more recent proposals by Rulkov (2002) and Izhikevich (2003). We also review map-based schemes for electrical and chemical synapses and some recent findings as critical avalanches in map-based neural networks. We conclude with suggestions for further work in this area like more efficient maps, compartmental modeling and close dynamical comparison with conductance-based models. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Bibliometric and Social Network Analysis of Doctoral Research: Research Trends in Distance Learning

    Science.gov (United States)

    Skinner, Jason Kirtland

    2015-01-01

    The study investigated research topics of doctoral dissertations that examined issues in distance learning from 2000-2014. Twelve reviews of research on distance learning, spanning from 1997-2015, were identified. It was found that only one of these reviews of research (Davies, Howell, & Petri, 2010) looked at doctoral dissertations. The…

  14. Landslide Susceptibility Mapping of Tegucigalpa, Honduras Using Artificial Neural Network, Bayesian Network and Decision Trees

    Science.gov (United States)

    Garcia Urquia, E. L.; Braun, A.; Yamagishi, H.

    2016-12-01

    Tegucigalpa, the capital city of Honduras, experiences rainfall-induced landslides on a yearly basis. The high precipitation regime and the rugged topography the city has been built in couple with the lack of a proper urban expansion plan to contribute to the occurrence of landslides during the rainy season. Thousands of inhabitants live at risk of losing their belongings due to the construction of precarious shelters in landslide-prone areas on mountainous terrains and next to the riverbanks. Therefore, the city is in the need for landslide susceptibility and hazard maps to aid in the regulation of future development. Major challenges in the context of highly dynamic urbanizing areas are the overlap of natural and anthropogenic slope destabilizing factors, as well as the availability and accuracy of data. Data-driven multivariate techniques have proven to be powerful in discovering interrelations between factors, identifying important factors in large datasets, capturing non-linear problems and coping with noisy and incomplete data. This analysis focuses on the creation of a landslide susceptibility map using different methods from the field of data mining, Artificial Neural Networks (ANN), Bayesian Networks (BN) and Decision Trees (DT). The input dataset of the study contains geomorphological and hydrological factors derived from a digital elevation model with a 10 m resolution, lithological factors derived from a geological map, and anthropogenic factors, such as information on the development stage of the neighborhoods in Tegucigalpa and road density. Moreover, a landslide inventory map that was developed in 2014 through aerial photo interpretation was used as target variable in the analysis. The analysis covers an area of roughly 100 km2, while 8.95 km2 are occupied by landslides. In a first step, the dataset was explored by assessing and improving the data quality, identifying unimportant variables and finding interrelations. Then, based on a training

  15. Distance Distributions and Proximity Estimation Given Knowledge of the Heterogeneous Network Layout

    OpenAIRE

    Xenakis, Dionysis; Merakos, Lazaros; Kountouris, Marios; Passas, Nikos; Verikoukis, Christos

    2015-01-01

    Today's heterogeneous wireless network (HWN) is a collection of ubiquitous wireless networking elements (WNEs) that support diverse functional capabilities and networking purposes. In such a heterogeneous networking environment, proximity estimation will play a key role for the seamless support of emerging applications that span from the direct exchange of localized traffic between homogeneous WNEs (peer-to-peer communications) to positioning for autonomous systems using location information ...

  16. Ischemia Detection Using Supervised Learning for Hierarchical Neural Networks Based on Kohonen-Maps

    National Research Council Canada - National Science Library

    Vladutu, L

    2001-01-01

    .... The motivation for developing the Supervising Network - Self Organizing Map (sNet-SOM) model is to design computationally effective solutions for the particular problem of ischemia detection and other similar applications...

  17. International collaboration in science: The global map and the network

    NARCIS (Netherlands)

    Leydesdorff, L.; Wagner, C.S.; Park, H.W.; Adams, J.

    2013-01-01

    The network of international co-authorship relations has been dominated by certain European nations and the USA, but this network is rapidly expanding at the global level. Between 40 and 50 countries appear in the center of the international network in 2011, and almost all (201) nations are nowadays

  18. Editorial ~ Does "Lean Thinking" Relate to Network-based Distance Education

    Directory of Open Access Journals (Sweden)

    Peter S. Cookson

    2003-10-01

    Full Text Available Pointing to the “objectivised, rationalized, technologically-based interaction,” Peters (1973 referred to the then prevailing correspondence forms of distance education as “the most industrialized form of education” (p. 313. With such features as assembly line methods; division of labor; centralized processes of teaching materials development, production and dispatching; student admissions enrollment systems; automated registration, course allocation, and student support, and personnel management systems, distance education institutions demonstrated management structures and practices utilized in industrial and business organizations. Large numbers of courses and students were thus “processed” in correspondence, radio, and television-based distance education systems.

  19. Mapping Ad Hoc Communications Network of a Large Number Fixed-Wing UAV Swarm

    Science.gov (United States)

    2017-03-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MAPPING AD HOC COMMUNICATIONS NETWORK OF A LARGE NUMBER FIXED-WING UAV SWARM by Alexis...SUBTITLE MAPPING AD HOC COMMUNICATIONS NETWORK OF A LARGE NUMBER FIXED-WING UAV SWARM 5. FUNDING NUMBERS 6. AUTHOR(S) Alexis Pospischil 7. PERFORMING... UAVs ) simultaneously as a self-organizing swarm. These vehicles were able to execute behaviors based on message notification from a single ground

  20. Satellites vs. fiber optics based networks and services - Road map to strategic planning

    Science.gov (United States)

    Marandi, James H. R.

    An overview of a generic telecommunications network and its components is presented, and the current developments in satellite and fiber optics technologies are discussed with an eye on the trends in industry. A baseline model is proposed, and a cost comparison of fiber- vs satellite-based networks is made. A step-by-step 'road map' to the successful strategic planning of telecommunications services and facilities is presented. This road map provides for optimization of the current and future networks and services through effective utilization of both satellites and fiber optics. The road map is then applied to different segments of the telecommunications industry and market place, to show its effectiveness for the strategic planning of executives of three types: (1) those heading telecommunications manufacturing concerns, (2) those leading communication service companies, and (3) managers of telecommunication/MIS departments of major corporations. Future networking issues, such as developments in integrated-services digital network standards and technologies, are addressed.

  1. Real-Time Water Vapor Maps from a GPS Surface Network: Construction, Validation, and Applications

    NARCIS (Netherlands)

    Haan, de S.; Holleman, I.; Holtslag, A.A.M.

    2009-01-01

    In this paper the construction of real-time integrated water vapor (IWV) maps from a surface network of global positioning system (GPS) receivers is presented. The IWV maps are constructed using a twodimensional variational technique with a persistence background that is 15 min old. The background

  2. Navigation Maps in a Computer-Networked Hypertext Learning System.

    Science.gov (United States)

    Chou, Chien; Lin, Hua

    A study of first-year college students (n=121) in Taiwan investigated the effects of navigation maps and learner cognitive styles on performance in searches for information, estimation of course scope, and the development of cognitive maps within a hypertext learning course. Students were tested to determine level of perceptual field dependence…

  3. Motifs, themes and thematic maps of an integrated Saccharomyces cerevisiae interaction network

    Directory of Open Access Journals (Sweden)

    Andrews Brenda

    2005-06-01

    Full Text Available Abstract Background Large-scale studies have revealed networks of various biological interaction types, such as protein-protein interaction, genetic interaction, transcriptional regulation, sequence homology, and expression correlation. Recurring patterns of interconnection, or 'network motifs', have revealed biological insights for networks containing either one or two types of interaction. Results To study more complex relationships involving multiple biological interaction types, we assembled an integrated Saccharomyces cerevisiae network in which nodes represent genes (or their protein products and differently colored links represent the aforementioned five biological interaction types. We examined three- and four-node interconnection patterns containing multiple interaction types and found many enriched multi-color network motifs. Furthermore, we showed that most of the motifs form 'network themes' – classes of higher-order recurring interconnection patterns that encompass multiple occurrences of network motifs. Network themes can be tied to specific biological phenomena and may represent more fundamental network design principles. Examples of network themes include a pair of protein complexes with many inter-complex genetic interactions – the 'compensatory complexes' theme. Thematic mapsnetworks rendered in terms of such themes – can simplify an otherwise confusing tangle of biological relationships. We show this by mapping the S. cerevisiae network in terms of two specific network themes. Conclusion Significantly enriched motifs in an integrated S. cerevisiae interaction network are often signatures of network themes, higher-order network structures that correspond to biological phenomena. Representing networks in terms of network themes provides a useful simplification of complex biological relationships.

  4. In-vivo dynamic and static three-dimensional joint space distance maps for assessment of cartilage thickness in the radiocarpal joint

    NARCIS (Netherlands)

    Foumani, M.; Strackee, S.D.; Van de Giessen, M.; Jonges, R.; Blankevoort, L.; Streekstra, G.J.

    2013-01-01

    Background The assessment of the joint space thickness is an important clinical parameter for diagnosing osteoarthritis. The accuracy of joint space thickness evaluation from radiographs is limited due to anatomical complexity of the wrist. We propose using distance maps estimated from 3-dimensional

  5. In-vivo dynamic and static three-dimensional joint space distance maps for assessment of cartilage thickness in the radiocarpal joint

    NARCIS (Netherlands)

    Foumani, M.; Strackee, S. D.; van de Giessen, M.; Jonges, R.; Blankevoort, L.; Streekstra, G. J.

    2013-01-01

    The assessment of the joint space thickness is an important clinical parameter for diagnosing osteoarthritis. The accuracy of joint space thickness evaluation from radiographs is limited due to anatomical complexity of the wrist. We propose using distance maps estimated from 3-dimensional and

  6. MAP3S precipitation chemistry network: sixth periodic summary report (1982)

    Energy Technology Data Exchange (ETDEWEB)

    Rothert, J.E.; Dana, M.T.

    1983-07-01

    This report contains complete field and chemical data from the MAP3S Precipitation Chemistry Network for the year 1982. Included is an update on network status and a summary of the USGS blind sample analysis program and laboratory sample exchanges during 1982. The statistical summary is deferred to a forthcoming publication.

  7. Computational solution to automatically map metabolite libraries in the context of genome scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Benjamin eMerlet

    2016-02-01

    Full Text Available This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc and flat file formats (SBML and Matlab files. We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics and Glasgow Polyomics on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks.In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks.In order to achieve this goal we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

  8. The MAP3S precipitation chemistry network: Eighth periodic summary report (1984)

    Energy Technology Data Exchange (ETDEWEB)

    Dana, M.T.

    1987-01-01

    This summary report, the eighth in the series, contains complete field and chemical data from the MAP3S Precipitation Chemistry Network for the year 1984. Sections cover Quality Assurance/Quality Control, network site information, and a brief statistical summary of the 1984 data.

  9. Ecological systems as computer networks: Long distance sea dispersal as a communication medium between island plant populations.

    Science.gov (United States)

    Sanaa, Adnen; Ben Abid, Samir; Boulila, Abdennacer; Messaoud, Chokri; Boussaid, Mohamed; Ben Fadhel, Najeh

    2016-06-01

    Ecological systems are known to exchange genetic material through animal species migration and seed dispersal for plants. Isolated plant populations have developed long distance dispersal as a means of propagation which rely on meteorological such as anemochory and hydrochory for coast, island and river bank dwelling species. Long distance dispersal by water, in particular, in the case of water current bound islands, calls for the analogy with computer networks, where each island and nearby mainland site plays the role of a network node, the water currents play the role of a transmission channel, and water borne seeds as data packets. In this paper we explore this analogy to model long distance dispersal of seeds among island and mainland populations, when traversed with water currents, in order to model and predict their future genetic diversity. The case of Pancratium maritimum L. populations in Tunisia is used as a proof of concept, where their genetic diversity is extrapolated. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  10. Depth map upsampling using joint edge-guided convolutional neural network for virtual view synthesizing

    Science.gov (United States)

    Dong, Yan; Lin, Chunyu; Zhao, Yao; Yao, Chao

    2017-07-01

    In texture-plus-depth format of three-dimensional visual data, both texture and depth maps are required to synthesize a desired view via depth-image-based rendering. However, the depth maps captured or estimated always exist with low resolution compared to their corresponding texture images. We introduce a joint edge-guided convolutional neural network that upsamples the resolution of a depth map on the premise of synthesized view quality. The network takes the low-resolution depth map as an input using a joint edge feature extracted from the depth map and the registered texture image as a reference, and then produces a high-resolution depth map. We further use local constraints that preserve smooth regions and sharp edges so as to improve the quality of the depth map and synthesized view. Finally, a global looping optimization is performed with virtual view quality as guidance in the recovery process. We train our model using pairs of depth maps and texture images and then make tests on other depth maps and video sequences. The experimental results demonstrate that our scheme outperforms existing methods both in the quality of the depth maps and synthesized views.

  11. The emotional cost of distance: Geographic social network dispersion and post-traumatic stress among survivors of Hurricane Katrina.

    Science.gov (United States)

    Morris, Katherine Ann; Deterding, Nicole M

    2016-09-01

    Social networks offer important emotional and instrumental support following natural disasters. However, displacement may geographically disperse network members, making it difficult to provide and receive support necessary for psychological recovery after trauma. We examine the association between distance to network members and post-traumatic stress using survey data, and identify potential mechanisms underlying this association using in-depth qualitative interviews. We use longitudinal, mixed-methods data from the Resilience in Survivors of Katrina (RISK) Project to capture the long-term effects of Hurricane Katrina on low-income mothers from New Orleans. Baseline surveys occurred approximately one year before the storm and follow-up surveys and in-depth interviews were conducted five years later. We use a sequential explanatory analytic design. With logistic regression, we estimate the association of geographic network dispersion with the likelihood of post-traumatic stress. With linear regressions, we estimate the association of network dispersion with the three post-traumatic stress sub-scales. Using maximal variation sampling, we use qualitative interview data to elaborate identified statistical associations. We find network dispersion is positively associated with the likelihood of post-traumatic stress, controlling for individual-level socio-demographic characteristics, exposure to hurricane-related trauma, perceived social support, and New Orleans residency. We identify two social-psychological mechanisms present in qualitative data: respondents with distant network members report a lack of deep belonging and a lack of mattering as they are unable to fulfill obligations to important distant ties. Results indicate the importance of physical proximity to emotionally-intimate network ties for long-term psychological recovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Topological data analysis of contagion maps for examining spreading processes on networks

    KAUST Repository

    Taylor, Dane

    2015-07-21

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth\\'s surface; however, in modern contagions long-range edges - for example, due to airline transportation or communication media - allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct \\'contagion maps\\' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

  13. Analysis of Road Traffic Network Cascade Failures with Coupled Map Lattice Method

    Directory of Open Access Journals (Sweden)

    Yanan Zhang

    2015-01-01

    Full Text Available In recent years, there is growing literature concerning the cascading failure of network characteristics. The object of this paper is to investigate the cascade failures on road traffic network, considering the aeolotropism of road traffic network topology and road congestion dissipation in traffic flow. An improved coupled map lattice (CML model is proposed. Furthermore, in order to match the congestion dissipation, a recovery mechanism is put forward in this paper. With a real urban road traffic network in Beijing, the cascading failures are tested using different attack strategies, coupling strengths, external perturbations, and attacked road segment numbers. The impacts of different aspects on road traffic network are evaluated based on the simulation results. The findings confirmed the important roles that these characteristics played in the cascading failure propagation and dissipation on road traffic network. We hope these findings are helpful to find out the optimal road network topology and avoid cascading failure on road network.

  14. Sparse short-distance connections enhance calcium wave propagation in a 3D model of astrocyte networks

    Science.gov (United States)

    Lallouette, Jules; De Pittà, Maurizio; Ben-Jacob, Eshel; Berry, Hugues

    2014-01-01

    Traditionally, astrocytes have been considered to couple via gap-junctions into a syncytium with only rudimentary spatial organization. However, this view is challenged by growing experimental evidence that astrocytes organize as a proper gap-junction mediated network with more complex region-dependent properties. On the other hand, the propagation range of intercellular calcium waves (ICW) within astrocyte populations is as well highly variable, depending on the brain region considered. This suggests that the variability of the topology of gap-junction couplings could play a role in the variability of the ICW propagation range. Since this hypothesis is very difficult to investigate with current experimental approaches, we explore it here using a biophysically realistic model of three-dimensional astrocyte networks in which we varied the topology of the astrocyte network, while keeping intracellular properties and spatial cell distribution and density constant. Computer simulations of the model suggest that changing the topology of the network is indeed sufficient to reproduce the distinct ranges of ICW propagation reported experimentally. Unexpectedly, our simulations also predict that sparse connectivity and restriction of gap-junction couplings to short distances should favor propagation while long–distance or dense connectivity should impair it. Altogether, our results provide support to recent experimental findings that point toward a significant functional role of the organization of gap-junction couplings into proper astroglial networks. Dynamic control of this topology by neurons and signaling molecules could thus constitute a new type of regulation of neuron-glia and glia-glia interactions. PMID:24795613

  15. The Geography of Distance Education--Bibliographic Characteristics of a Journal Network

    Science.gov (United States)

    Zawacki-Richter, Olaf; Anderson, Terry

    2011-01-01

    The publication of the results of research in distance education in peer-reviewed journals is an important means of communication, dissemination, discourse and reporting of practice in the field. This study is an attempt at analyzing the relationships and influences among these journals. It is based upon a sample of 1416 scholarly articles…

  16. Persistence in Distance Education: A Study Case Using Bayesian Network to Understand Retention

    Science.gov (United States)

    Eliasquevici, Marianne Kogut; da Rocha Seruffo, Marcos César; Resque, Sônia Nazaré Fernandes

    2017-01-01

    This article presents a study on the variables promoting student retention in distance undergraduate courses at Federal University of Pará, aiming to help school managers minimize student attrition and maximize retention until graduation. The theoretical background is based on Rovai's Composite Model and the methodological approach is conditional…

  17. Mapping of protein-protein interaction network of Alexander disease.

    Science.gov (United States)

    Saxena, A K; Saxena, V L; Dixit, S

    2016-05-30

    Alexander disease (ALXD) is slowly progressive neurodegenerative disorder which affects white matter of the central nervous system. The main cause of disorder is mutation in GFAP gene and mutation in some other genes were also reported. This study was aimed at getting a better insight into ALXD pathogenesis and identifying the important functional and highly interconnected nodes in human protein interaction network, identifying the important sub-networks in the system could be helpful in understanding the underlying molecular mechanism. The topological analysis of human protein interaction network strategy to identify highly interconnected sub-network modules from which six proteins are found i.e. GFAP, PLEC, CRYAB, NDUFV1, CASP3 and MAPK14 plays important role in disease. Further, the enrichment analysis of interaction network identifies crucial pathways in which most of the diseased proteins overlaps. Through system biology approach, the undirected human protein interaction network of ALXD is buildup with the help of Cytoscape tool and its various plugins helps to investigate network further. The systematic approach suggests the finding of previously known proteins, GFAP, PLEC, CRYAB, NDUFV1, CASP3 and MAPK14 can be used as a drug targets and potential treatment discovered also enrichment analysis will provide guidance for the future study on Alexander disease.

  18. Neural Networks through Shared Maps in Mobile Devices

    Directory of Open Access Journals (Sweden)

    William Raveane

    2014-12-01

    Full Text Available We introduce a hybrid system composed of a convolutional neural network and a discrete graphical model for image recognition. This system improves upon traditional sliding window techniques for analysis of an image larger than the training data by effectively processing the full input scene through the neural network in less time. The final result is then inferred from the neural network output through energy minimization to reach a more precize localization than what traditional maximum value class comparisons yield. These results are apt for applying this process in a mobile device for real time image recognition.

  19. Impaired Long Distance Functional Connectivity and Weighted Network Architecture in Alzheimer's Disease

    National Research Council Canada - National Science Library

    Liu, Yong; Yu, Chunshui; Zhang, Xinqing; Liu, Jieqiong; Duan, Yunyun; Alexander-Bloch, Aaron F; Liu, Bing; Jiang, Tianzi; Bullmore, Ed

    2014-01-01

    .... We explored abnormal functional magnetic resonance imaging (fMRI) resting-state dynamics, functional connectivity, and weighted functional networks, in a sample of patients with severe AD (N = 18...

  20. QUANTITATIVE RISK MAPPING OF URBAN GAS PIPELINE NETWORKS USING GIS

    National Research Council Canada - National Science Library

    P. Azari; M. Karimi

    2017-01-01

    Natural gas is considered an important source of energy in the world. By increasing growth of urbanization, urban gas pipelines which transmit natural gas from transmission pipelines to consumers, will become a dense network...

  1. Exploring empowerment in settings: mapping distributions of network power.

    Science.gov (United States)

    Neal, Jennifer Watling

    2014-06-01

    This paper brings together two trends in the empowerment literature-understanding empowerment in settings and understanding empowerment as relational-by examining what makes settings empowering from a social network perspective. Specifically, extending Neal and Neal's (Am J Community Psychol 48(3/4):157-167, 2011) conception of network power, an empowering setting is defined as one in which (1) actors have existing relationships that allow for the exchange of resources and (2) the distribution of network power among actors in the setting is roughly equal. The paper includes a description of how researchers can examine distributions of network power in settings. Next, this process is illustrated in both an abstract example and using empirical data on early adolescents' peer relationships in urban classrooms. Finally, implications for theory, methods, and intervention related to understanding empowering settings are explored.

  2. Mapping human brain networks with cortico-cortical evoked potentials

    National Research Council Canada - National Science Library

    Keller, Corey J; Honey, Christopher J; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D

    2014-01-01

    The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities...

  3. Quantization and analysis of hippocampal morphometric changes due to dementia of Alzheimer type using metric distances based on large deformation diffeomorphic metric mapping.

    Science.gov (United States)

    Ceyhan, Elvan; Beg, Mirza Faisal; Ceritoglu, Can; Wang, Lei; Morris, John C; Csernansky, John G; Miller, Michael I; Ratnanather, J Tilak

    2011-06-01

    The metric distance obtained from the large deformation diffeomorphic metric mapping (LDDMM) algorithm is used to quantize changes in morphometry of brain structures due to neuropsychiatric diseases. For illustrative purposes we consider changes in hippocampal morphometry (shape and size) due to very mild dementia of the Alzheimer type (DAT). LDDMM, which was previously used to calculate dense one-to-one correspondence vector fields between hippocampal shapes, measures the morphometric differences with respect to a template hippocampus by assigning metric distances on the space of anatomical images thereby allowing for direct comparison of morphometric differences. We characterize what information the metric distances provide in terms of size and shape given the hippocampal, brain and intracranial volumes. We demonstrate that metric distance is a measure of morphometry (i.e., shape and size) but mostly a measure of shape, while volume is mostly a measure of size. Moreover, we show how metric distances can be used in cross-sectional, longitudinal analysis, as well as left-right asymmetry comparisons, and provide how the metric distances can serve as a discriminative tool using logistic regression. Thus, we show that metric distances with respect to a template computed via LDDMM can be a powerful tool in detecting differences in shape. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. Disrupting the Implementation Gap with Digital Technology in Healthcare Distance Education: Critical Insights from an e-Mentoring Intensional Network Practitioner Research Project

    Science.gov (United States)

    Singh, Gurmit

    2013-01-01

    Effective professional distance education is urgently needed to develop a well-trained workforce and improve impact on healthcare. However, distance education initiatives have had mixed results in improving practice. Often, successful implementation fails to leverage insights on the social and emergent nature of learning in networks. This paper…

  5. IMPACT OF DISTANCES FROM PARTICIPANTS IN THE SUPPLY NETWORK ON COOPERATION OF INNOVATIVE ENTERPRISES OF FOOD INDUSTRY

    Directory of Open Access Journals (Sweden)

    Marek Tomaszewski

    2015-06-01

    Full Text Available  The aim of the article is to show the impact of market location and the distance from the supply network participants on the occurrence of innovative cooperation between the food industry companies and industry- and science-oriented entities. The methodological part of the article is based on probit modelling. The material necessary for the analyses present in this article has been collected by means of a questionnaire sent to the companies all over Poland. The conducted research confi rmed that the situation when the market or other participants of the supply network (suppliers, customers and competitors are localised in close proximity to the food industry company has a negative impact on the occurrence of innovative activity between the company and other food industry companies or science-oriented units. On the other hand, the location outside one’s own region stimulates this kind of collaboration.

  6. Mapping debris flow susceptibility using analytical network process ...

    Indian Academy of Sciences (India)

    54

    has been a commonly adopted tool in the areas of industrial management, economics. 24 and finance, forest ... climate is of a temperate type with an average maximum and minimum temperatures. 16 of 17° - 25° C and ...... Sujatha E R and Rajamanickam G V 2015 Landslide Hazard and Risk Mapping using. 8. Weighted ...

  7. Mapping debris flow susceptibility using analytical network process ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Earth System Science; Volume 126; Issue 8. Mapping debris flow ... Rapid debris flows, a mixture of unconsolidated sediments and water travelling at speeds >10 m/s are the most destructive water related mass movements that affect hill and mountain regions. The predisposing factors setting the ...

  8. Load Balanced Mapping of Distributed Objects to Minimize Network Communication

    NARCIS (Netherlands)

    Stoyenko, Alexander D.; Bosch, J.; Bosch, Jan; Aksit, Mehmet; Marlowe, Thomas J.

    1996-01-01

    This paper introduces a new load balancing and communica- tion minimizing heuristic used in the Inverse Remote Procedure Call (IRPC) system. While the paper briefly describes the IRPC system, the focus is on the new IRPC assignment heuristic. The IRPC compiler maps a distributed program to a graph

  9. [Design of a long-distance consultation system using wireless sensor networks].

    Science.gov (United States)

    Wang, Ji; Shen, Yuli; Xa, Guobao; Xie, Shiyi

    2010-02-01

    A remote interactive consultation system based on wireless sensor networks is proposed for family health care works and non-hospital special case patient monitoring. The sensor nodes are integrated into a local area network to collect a variety of human physiological information, which is uploaded to Internet through the Code-Division Multiple Access (CDMA) wireless network technology and sent to the database based on GIS spatial location query technology for achieving electronic diagnosis. Users or administrators can visit remote monitor region through Internet. The results show that the system, using a star passive topology of static gateway and mobile detection node, combines intelligent-distributed wireless sensing, computing and wireless communication technologies. Hence the proposed system has a great practical value.

  10. Distance-Based Access Modifiers Applied to Safety in Home Networks

    DEFF Research Database (Denmark)

    Mortensen, Kjeld Høyer; Schougaard, Kari Rye; Schultz, Ulrik Pagh

    2004-01-01

    Home networks and the interconnection of home appliances is a classical theme in ubiquitous computing research. Security is a recurring concern, but there is a lack of awareness of safety: preventing the computerized house from harming the inhabitants, even in a worst-case scenario where...... be performed within a physical proximity that ensures safety. We use a declarative approach integrated with an IDL language to express location-based restrictions on operations. This model has been implemented in a middleware for home audio-video devices, using infrared communication and a local-area network...

  11. Action and the representation of distance in cognitive maps acquired through imagined traversal: the development of a new methodology.

    Science.gov (United States)

    Bugmann, Davi; Coventry, Kenny R

    2008-04-01

    A new methodology examined the effects of action on memory for traversed distance using an imagined route traversal task. Blindfolded participants learned environments through auditory verbal description, imagining themselves walking in synchronization with metronome beats. Participants were turned during traversals, and performed an action at midroute. Memory for the newly learned environments was tested through recall (measured with metronome beats). Experiments 1-3 indicated that the number (but not amplitude) of turns while imagining walking a set distance leads to an increase in perceived distance at recall. Additionally, Experiment 2 found that rewalked distance immediately prior to performing an action at midroute was greater than rewalked distance immediately after action. However, Experiment 3 established that the effect was due to time spent at midroute rather than action per se. The similarity between spatial representation derived from imagined traversal and real traversal, and the relationship between distance and time estimation are discussed.

  12. A Fuzzy Neural Network Based on Non-Euclidean Distance Clustering for Quality Index Model in Slashing Process

    Directory of Open Access Journals (Sweden)

    Yuxian Zhang

    2015-01-01

    Full Text Available The quality index model in slashing process is difficult to build by reason of the outliers and noise data from original data. To the above problem, a fuzzy neural network based on non-Euclidean distance clustering is proposed in which the input space is partitioned into many local regions by the fuzzy clustering based on non-Euclidean distance so that the computation complexity is decreased, and fuzzy rule number is determined by validity function based on both the separation and the compactness among clusterings. Then, the premise parameters and consequent parameters are trained by hybrid learning algorithm. The parameters identification is realized; meanwhile the convergence condition of consequent parameters is obtained by Lyapunov function. Finally, the proposed method is applied to build the quality index model in slashing process in which the experimental data come from the actual slashing process. The experiment results show that the proposed fuzzy neural network for quality index model has lower computation complexity and faster convergence time, comparing with GP-FNN, BPNN, and RBFNN.

  13. Performance Analysis of Millimeter-Wave Multi-hop Machine-to-Machine Networks Based on Hop Distance Statistics.

    Science.gov (United States)

    Jung, Haejoon; Lee, In-Ho

    2018-01-12

    As an intrinsic part of the Internet of Things (IoT) ecosystem, machine-to-machine (M2M) communications are expected to provide ubiquitous connectivity between machines. Millimeter-wave (mmWave) communication is another promising technology for the future communication systems to alleviate the pressure of scarce spectrum resources. For this reason, in this paper, we consider multi-hop M2M communications, where a machine-type communication (MTC) device with the limited transmit power relays to help other devices using mmWave. To be specific, we focus on hop distance statistics and their impacts on system performances in multi-hop wireless networks (MWNs) with directional antenna arrays in mmWave for M2M communications. Different from microwave systems, in mmWave communications, wireless channel suffers from blockage by obstacles that heavily attenuate line-of-sight signals, which may result in limited per-hop progress in MWNs. We consider two routing strategies aiming at different types of applications and derive the probability distributions of their hop distances. Moreover, we provide their baseline statistics assuming the blockage-free scenario to quantify the impact of blockages. Based on the hop distance analysis, we propose a method to estimate the end-to-end performances (e.g., outage probability, hop count, and transmit energy) of the mmWave MWNs, which provides important insights into mmWave MWN design without time-consuming and repetitive end-to-end simulation.

  14. Numerical bifurcation analysis of distance-dependent on-center off-surround shunting neural networks.

    NARCIS (Netherlands)

    Molenaar, P.C.M.; Raijmakers, M.E.J.; van der Maas, H.L.J.

    1996-01-01

    On-center off-surround shunting neural networks are often applied as models for content-addressable memory (CAM), the equilibria being the stored memories. One important demand of biological plausible CAMs is that they function under a broad range of parameters, since several parameters vary due to

  15. Social interaction distance and stratification.

    Science.gov (United States)

    Bottero, Wendy; Prandy, Kenneth

    2003-06-01

    There have been calls from several sources recently for a renewal of class analysis that would encompass social and cultural, as well as economic elements. This paper explores a tradition in stratification that is founded on this idea: relational or social distance approaches to mapping hierarchy and inequality which theorize stratification as a social space. The idea of 'social space' is not treated as a metaphor of hierarchy nor is the nature of the structure determined a priori. Rather, the space is identified by mapping social interactions. Exploring the nature of social space involves mapping the network of social interaction--patterns of friendship, partnership and cultural similarity--which gives rise to relations of social closeness and distance. Differential association has long been seen as the basis of hierarchy, but the usual approach is first to define a structure composed of a set of groups and then to investigate social interaction between them. Social distance approaches reverse this, using patterns of interaction to determine the nature of the structure. Differential association can be seen as a way of defining proximity within a social space, from the distances between social groups, or between social groups and social objects (such as lifestyle items). The paper demonstrates how the very different starting point of social distance approaches also leads to strikingly different theoretical conclusions about the nature of stratification and inequality.

  16. Zombie projects, negative networks, and multigenerational science: The temporality of the International Map of the World.

    Science.gov (United States)

    Rankin, William

    2017-06-01

    The International Map of the World was a hugely ambitious scheme to create standardized maps of the entire world. It was first proposed in 1891 and remained a going concern until 1986. Over the course of the project's official life, nearly every country in the world took part, and map sheets were published showing all but a few areas of the planet. But the project ended quite unceremoniously, repudiated by cartographers and mapping institutions alike, and it is now remembered as a 'sad story' of network failure. How can we evaluate this kind of sprawling, multigenerational project? In order to move beyond practitioners' (and historians') habit of summarizing the entire endeavor using the blunt categories of success and failure, I propose a more temporally aware reading, one that both disaggregates the (persistent) project from the (always changing) network and sees project and network as invertible, with the possibility of zombie projects and negative networks that can remain robust even when disconnected from their original goals. I therefore see the abandonment of the International Map of the World as resulting from vigorous collaboration and new norms in cartography, not from lack of cooperation or other resources. New categories are required for analyzing science over the long durée.

  17. Foreground removal from Planck Sky Model temperature maps using a MLP neural network

    DEFF Research Database (Denmark)

    Nørgaard-Nielsen, Hans Ulrik; Hebert, K.

    2009-01-01

    with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them...... in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80% of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors....

  18. The high resolution mapping of the Venice Lagoon tidal network

    Science.gov (United States)

    Madricardo, Fantina; Foglini, Federica; Kruss, Aleksandra; Bellafiore, Debora; Trincardi, Fabio

    2017-04-01

    One of the biggest challenges of the direct observation of the ocean is to achieve a high resolution mapping of its seafloor morphology and benthic habitats. So far, sonars have mapped just 0.05% of the ocean floor with less than ten-meter resolution. The recent efforts of the scientific community have been devoted towards the mapping of both Deep Ocean and very shallow coastal areas. Coastal and transitional environments in particular undergo strong morphological changes due to natural and anthropogenic pressure. Nowadays, only about 5% of the seafloor of these environments † have been mapped: the shallowness of these environments has prevented the use of underwater acoustics to reveal their morphological features. The recent technological development of multibeam echosounder systems, however, enables these instruments to achieve very high performances also in such shallow environments. In this work, we present results and case studies of an extensive multibeam survey carried out in the Lagoon of Venice in 2013. The Lagoon of Venice is the biggest lagoon in the Mediterranean Sea with a surface of about 550 km2 and with an average depth of about 1 m. In the last century, the morphological and ecological properties of the lagoon changed dramatically: the surface of the salt marshes was reduced by 60% and some parts of the lagoon are deepening with a net sediment flux exiting from the inlets. Moreover, major engineering interventions are currently ongoing at the inlets (MOSE project). These changes at the inlets could affect substantially the lagoon environment. To understand and monitor the future evolution of the Lagoon of Venice, ISMAR within the project RITMARE (a National Research Programme funded by the Italian Ministry of University and Research) carried out an extensive survey, involving a team of more than 25 scientists, to collect high resolution (0.5 m) bathymetry of key study areas such as the tidal inlets and channels. Following a broad

  19. MapReduce Based Parallel Neural Networks in Enabling Large Scale Machine Learning

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2015-01-01

    Full Text Available Artificial neural networks (ANNs have been widely used in pattern recognition and classification applications. However, ANNs are notably slow in computation especially when the size of data is large. Nowadays, big data has received a momentum from both industry and academia. To fulfill the potentials of ANNs for big data applications, the computation process must be speeded up. For this purpose, this paper parallelizes neural networks based on MapReduce, which has become a major computing model to facilitate data intensive applications. Three data intensive scenarios are considered in the parallelization process in terms of the volume of classification data, the size of the training data, and the number of neurons in the neural network. The performance of the parallelized neural networks is evaluated in an experimental MapReduce computer cluster from the aspects of accuracy in classification and efficiency in computation.

  20. Navigating the massive world of reddit: using backbone networks to map user interests in social media

    Directory of Open Access Journals (Sweden)

    Randal S. Olson

    2015-05-01

    Full Text Available In the massive online worlds of social media, users frequently rely on organizing themselves around specific topics of interest to find and engage with like-minded people. However, navigating these massive worlds and finding topics of specific interest often proves difficult because the worlds are mostly organized haphazardly, leaving users to find relevant interests by word of mouth or using a basic search feature. Here, we report on a method using the backbone of a network to create a map of the primary topics of interest in any social network. To demonstrate the method, we build an interest map for the social news web site reddit and show how such a map could be used to navigate a social media world. Moreover, we analyze the network properties of the reddit social network and find that it has a scale-free, small-world, and modular community structure, much like other online social networks such as Facebook and Twitter. We suggest that the integration of interest maps into popular social media platforms will assist users in organizing themselves into more specific interest groups, which will help alleviate the overcrowding effect often observed in large online communities.

  1. Long distance seawater intrusion through a karst conduit network in the Woodville Karst Plain, Florida

    OpenAIRE

    Zexuan Xu; Seth Willis Bassett; Bill Hu; Scott Barrett Dyer

    2016-01-01

    Five periods of increased electrical conductivity have been found in the karst conduits supplying one of the largest first magnitude springs in Florida with water. Numerous well-developed conduit networks are distributed in the Woodville Karst Plain (WKP), Florida and connected to the Gulf of Mexico. A composite analysis of precipitation and electrical conductivity data provides strong evidence that the increases in conductivity are directly tied to seawater intrusion moving inland and travel...

  2. F-MAP: A Bayesian approach to infer the gene regulatory network using external hints.

    Science.gov (United States)

    Shahdoust, Maryam; Pezeshk, Hamid; Mahjub, Hossein; Sadeghi, Mehdi

    2017-01-01

    The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches.

  3. Mapping Engagement in Twitter-Based Support Networks for Adult Smoking Cessation.

    Science.gov (United States)

    Lakon, Cynthia M; Pechmann, Cornelia; Wang, Cheng; Pan, Li; Delucchi, Kevin; Prochaska, Judith J

    2016-08-01

    We examined engagement in novel quit-smoking private social support networks on Twitter, January 2012 to April 2014. We mapped communication patterns within 8 networks of adult smokers (n = 160) with network ties defined by participants' tweets over 3 time intervals, and examined tie reciprocity, tie strength, in-degree centrality (popularity), 3-person triangles, 4-person cliques, network density, and abstinence status. On average, more than 50% of ties were reciprocated in most networks and most ties were between abstainers and nonabstainers. Tweets formed into more aggregated patterns especially early in the study. Across networks, 35.00% (7 days after the quit date), 49.38% (30 days), and 46.88% (60 days) abstained from smoking. We demonstrated that abstainers and nonabstainers engaged with one another in dyads and small groups. This study preliminarily suggests potential for Twitter as a platform for adult smoking-cessation interventions.

  4. Mapping, Awareness, and Virtualization Network Administrator Training Tool (MAVNATT) Architecture and Framework

    Science.gov (United States)

    2015-06-01

    exporting, and sharing? 2. What are suitable libraries and application program interfaces (APIs) that can be utilized to create a graphical user...capable of all network monitoring areas and can also perform integrated network discovery with SNMP, LDAP, ICMP, SSH , and other protocols [24], [27], [28...based Mapping Yes (ICMP, SNMP, WMI) Yes (Plugin Dependent) Yes (ICMP, SNMP, WMI, LDAP, SSH ) 24 3. Virtualization Virtualization tools

  5. The MAP3S Precipitation Chemistry Network: Data and quality control summary for 1986 and 1987

    Energy Technology Data Exchange (ETDEWEB)

    Dana, M.T.; Barchet, W.R.

    1989-05-01

    This report, the tenth in a series documenting results from the MAP3S Precipitation Chemistry Network, contains a statistical summary of daily precipitation chemistry data from the nine-site network in the eastern United States, both for the years 1986 and 1987 individually and for the period 1977 through 1987. In addition, external quality assurance results for 1986 and 1987 are summarized. 17 refs., 21 figs., 20 tabs.

  6. The "path" not taken: exploring structural differences in mapped- versus shortest-network-path school travel routes.

    Science.gov (United States)

    Buliung, Ron N; Larsen, Kristian; Faulkner, Guy E J; Stone, Michelle R

    2013-09-01

    School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys = 45%, girls = 54%, unreported gender = 1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems-based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research.

  7. The “Path” Not Taken: Exploring Structural Differences in Mapped- Versus Shortest-Network-Path School Travel Routes

    Science.gov (United States)

    Larsen, Kristian; Faulkner, Guy E. J.; Stone, Michelle R.

    2013-01-01

    Objectives. School route measurement often involves estimating the shortest network path. We challenged the relatively uncritical adoption of this method in school travel research and tested the route discordance hypothesis that several types of difference exist between shortest network paths and reported school routes. Methods. We constructed the mapped and shortest path through network routes for a sample of 759 children aged 9 to 13 years in grades 5 and 6 (boys = 45%, girls = 54%, unreported gender = 1%), in Toronto, Ontario, Canada. We used Wilcoxon signed-rank tests to compare reported with shortest-path route measures including distance, route directness, intersection crossings, and route overlap. Measurement difference was explored by mode and location. Results. We found statistical evidence of route discordance for walkers and children who were driven and detected it more often for inner suburban cases. Evidence of route discordance varied by mode and school location. Conclusions. We found statistically significant differences for route structure and built environment variables measured along reported and geographic information systems–based shortest-path school routes. Uncertainty produced by the shortest-path approach challenges its conceptual and empirical validity in school travel research. PMID:23865648

  8. Node Identification Using Inter-Regional Correlation Analysis for Mapping Detailed Connections in Resting State Networks

    Directory of Open Access Journals (Sweden)

    Yong Jeong

    2017-05-01

    Full Text Available Brain function is often characterized by the connections and interactions between highly interconnected brain regions. Pathological disruptions in these networks often result in brain dysfunction, which manifests as brain disease. Typical analysis investigates disruptions in network connectivity based correlations between large brain regions. To obtain a more detailed description of disruptions in network connectivity, we propose a new method where functional nodes are identified in each region based on their maximum connectivity to another brain region in a given network. Since this method provides a unique approach to identifying functionally relevant nodes in a given network, we can provide a more detailed map of brain connectivity and determine new measures of network connectivity. We applied this method to resting state fMRI of Alzheimer's disease patients to validate our method and found decreased connectivity within the default mode network. In addition, new measure of network connectivity revealed a more detailed description of how the network connections deteriorate with disease progression. This suggests that analysis using key relative network hub regions based on regional correlation can be used to detect detailed changes in resting state network connectivity.

  9. Density and diversity of OpenStreetMap road networks in China

    OpenAIRE

    Zhang, Yingjia; Li, Xueming; Wang, Aiming; Bao, Tongliga; Tian, Shenzhen

    2015-01-01

    OpenStreetMap is a geographic information platform designed to provide real-time updates and user-generated content related to its freely available global map, and it is one of the most widely used examples of volunteered geographic information, a technique associated with so-called neogeography. This paper, based on the data from China’s OpenStreetMap road network in May 2014, taking 340 prefecture-level cities in China as its study area, presents the geometric-related (road density) and att...

  10. Differential recruitment of brain networks following route and cartographic map learning of spatial environments.

    Science.gov (United States)

    Zhang, Hui; Copara, Milagros; Ekstrom, Arne D

    2012-01-01

    An extensive neuroimaging literature has helped characterize the brain regions involved in navigating a spatial environment. Far less is known, however, about the brain networks involved when learning a spatial layout from a cartographic map. To compare the two means of acquiring a spatial representation, participants learned spatial environments either by directly navigating them or learning them from an aerial-view map. While undergoing functional magnetic resonance imaging (fMRI), participants then performed two different tasks to assess knowledge of the spatial environment: a scene and orientation dependent perceptual (SOP) pointing task and a judgment of relative direction (JRD) of landmarks pointing task. We found three brain regions showing significant effects of route vs. map learning during the two tasks. Parahippocampal and retrosplenial cortex showed greater activation following route compared to map learning during the JRD but not SOP task while inferior frontal gyrus showed greater activation following map compared to route learning during the SOP but not JRD task. We interpret our results to suggest that parahippocampal and retrosplenial cortex were involved in translating scene and orientation dependent coordinate information acquired during route learning to a landmark-referenced representation while inferior frontal gyrus played a role in converting primarily landmark-referenced coordinates acquired during map learning to a scene and orientation dependent coordinate system. Together, our results provide novel insight into the different brain networks underlying spatial representations formed during navigation vs. cartographic map learning and provide additional constraints on theoretical models of the neural basis of human spatial representation.

  11. Long distance seawater intrusion through a karst conduit network in the Woodville Karst Plain, Florida

    Science.gov (United States)

    Xu, Zexuan; Bassett, Seth Willis; Hu, Bill; Dyer, Scott Barrett

    2016-08-01

    Five periods of increased electrical conductivity have been found in the karst conduits supplying one of the largest first magnitude springs in Florida with water. Numerous well-developed conduit networks are distributed in the Woodville Karst Plain (WKP), Florida and connected to the Gulf of Mexico. A composite analysis of precipitation and electrical conductivity data provides strong evidence that the increases in conductivity are directly tied to seawater intrusion moving inland and traveling 11 miles against the prevailing regional hydraulic gradient from from Spring Creek Spring Complex (SCSC), a group of submarine springs at the Gulf Coast. A geochemical analysis of samples from the spring vent rules out anthropogenic contamination and upwelling regional recharge from the deep aquifer as sources of the rising conductivity. The interpretation is supported by the conceptual model established by prior researchers working to characterize the study area. This paper documents the first and longest case of seawater intrusion in the WKP, and also indicates significant possibility of seawater contamination through subsurface conduit networks in a coastal karst aquifer.

  12. Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure.

    Science.gov (United States)

    Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu; Scheuermann, Richard H

    2016-01-01

    Flow cytometry (FCM) is a fluorescence-based single-cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap-FR, a novel method for cell population mapping across FCM samples. FlowMap-FR is based on the Friedman-Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap-FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap-FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap-FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap-FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap-FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback-Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL-distance in distinguishing equivalent from nonequivalent cell

  13. Invertebrate diversity classification using self-organizing map neural network: with some special topological functions

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2014-06-01

    Full Text Available In present study we used self-organizing map (SOM neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.

  14. MAP3S Precipitation Chemistry Network: fifth periodic summary report (1981)

    Energy Technology Data Exchange (ETDEWEB)

    Dana, M.T.; Rothert, J.E.

    1983-02-01

    This, the fifth in a series of summary reports, contains complete field and chemical data from the MAP3 Precipitation Chemistry Network for the year 1981. The 1981 data were added to the previous data base, and an update of the previous five year statistical summary completed. Included are basic statistics, time trend analyses, and monthly averages.

  15. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NARCIS (Netherlands)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2016-01-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can

  16. Mapping network development of international new ventures with the use of company e-mails

    NARCIS (Netherlands)

    Wakkee, I.A.M.

    2006-01-01

    International new ventures use e-mail frequently to communicate with globally dispersed contacts. In this paper we present and discuss a qualitative research method to map international network development based on company e-mails. Our approach also allows for combinations of inductive and deductive

  17. A framework for mapping, visualisation and automatic model creation of signal-transduction networks.

    Science.gov (United States)

    Tiger, Carl-Fredrik; Krause, Falko; Cedersund, Gunnar; Palmér, Robert; Klipp, Edda; Hohmann, Stefan; Kitano, Hiroaki; Krantz, Marcus

    2012-04-24

    Intracellular signalling systems are highly complex. This complexity makes handling, analysis and visualisation of available knowledge a major challenge in current signalling research. Here, we present a novel framework for mapping signal-transduction networks that avoids the combinatorial explosion by breaking down the network in reaction and contingency information. It provides two new visualisation methods and automatic export to mathematical models. We use this framework to compile the presently most comprehensive map of the yeast MAP kinase network. Our method improves previous strategies by combining (I) more concise mapping adapted to empirical data, (II) individual referencing for each piece of information, (III) visualisation without simplifications or added uncertainty, (IV) automatic visualisation in multiple formats, (V) automatic export to mathematical models and (VI) compatibility with established formats. The framework is supported by an open source software tool that facilitates integration of the three levels of network analysis: definition, visualisation and mathematical modelling. The framework is species independent and we expect that it will have wider impact in signalling research on any system.

  18. Mentoring Entrepreneurial Networks: mapping conceptions of participants in technological-based business incubators in Brazil.

    Directory of Open Access Journals (Sweden)

    Pontes Regis, Helder

    2007-12-01

    Full Text Available The recent entrepreneurship research agenda includes the analysis of cognitive structures of successful entrepreneurs, revealing an important tool for the examination of an entrepreneurial career. Using techniques of cognitive maps, this study explores the concepts of a successful career and the network itself, as a whole, for career development. Fifty-three entrepreneurs were studied, in seven technological incubators in the city of Recife, Pernambuco, Brazil. Specifically, this study aimed to map the shared meanings of the incubated entrepreneurs regarding informal support networks. Such networks support the entrepreneurial career and the present study explores the characteristics and the conceptual model that underlies the networks. The data collection was achieved through interviews through a free evocation technique. The shared meanings indicate the existence of inherent thought categories that support network context in the incubator environment, mainly the mentoring networks. The results endorse the interpretation of an informal mentoring model emerging from the dominant evocations concerning a successful career and of the network itself as promoter of career development.

  19. The use of social networking sites for relationship maintenance in long-distance and geographically close romantic relationships.

    Science.gov (United States)

    Billedo, Cherrie Joy; Kerkhof, Peter; Finkenauer, Catrin

    2015-03-01

    Social networking sites (SNS) play an increasingly important role in maintaining geographically close romantic relationships (GCRR). However, knowledge about SNS use in long-distance romantic relationships (LDRR) is still lacking. The present study examined the relative importance of SNS in maintaining LDRR compared to GCRR, particularly with regard to the use of SNS to express involvement (via relational maintenance behaviors) and to gauge a partner's involvement (via partner surveillance and jealousy) in the relationship. An online survey was conducted among predominantly young adult Facebook users who were in a romantic relationship (N=272). Results showed that participants who were in a LDRR reported higher levels of relational maintenance behaviors through SNS than participants who were in a GCRR. Also, as compared to participants who were in a GCRR, participants who were in a LDRR used SNS more for partner surveillance and experienced higher levels of SNS jealousy.

  20. Modeling isotopomer distributions in biochemical networks using isotopomer mapping matrices

    DEFF Research Database (Denmark)

    Schmidt, Karsten; Carlsen, Morten; Nielsen, Jens Bredal

    1997-01-01

    Within the last decades NMR spectroscopy has undergone tremendous development and has become a powerful analytical tool for the investigation of intracellular flux distributions in biochemical networks using C-13-labeled substrates. Not only are the experiments much easier to conduct than...... of the isotopomer distribution in metabolite pools can be obtained. The isotopomer distribution is the maximum amount of information that in theory can be obtained from C-13-tracer studies. The wealth of information contained in NMR spectra frequently leads to overdetermined algebraic systems. Consequently, fluxes...... must be estimated by nonlinear least squares analysis, in which experimental labeling data is compared with simulated steady state isotopomer distributions. Hence, mathematical models are required to compute the steady state isotopomer distribution as a function of a given set of steady state fluxes...

  1. Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study.

    Science.gov (United States)

    Cole, Justin; Beare, Richard; Phan, Thanh G; Srikanth, Velandai; MacIsaac, Andrew; Tan, Christianne; Tong, David; Yee, Susan; Ho, Jesslyn; Layland, Jamie

    2017-01-01

    Recent evidence suggests hospitals fail to meet guideline specified time to percutaneous coronary intervention (PCI) for a proportion of ST elevation myocardial infarction (STEMI) presentations. Implicit in achieving this time is the rapid assembly of crucial catheter laboratory staff. As a proof-of-concept, we set out to create regional maps that graphically show the impact of traffic congestion and distance to destination on staff recall travel times for STEMI, thereby producing a resource that could be used by staff to improve reperfusion time for STEMI. Travel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6 p.m., and 7 a.m. were estimated using Google Maps Application Programming Interface. Computer modeling predictions were overlaid on metropolitan maps showing color coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times. Inner metropolitan hospital staff recall travel times were more affected by traffic congestion compared with outer metropolitan times, and the latter was more affected by distance. The estimated mean travel times to hospital during peak hour were greater than midnight travel times by 13.4 min to the inner and 6.0 min to the outer metropolitan hospital at 6 p.m. ( p  travel time can predict optimal residence of staff when on-call for PCI.

  2. A high-resolution reference genetic map positioning 8.8 K genes for the conifer white spruce: structural genomics implications and correspondence with physical distance.

    Science.gov (United States)

    Pavy, Nathalie; Lamothe, Manuel; Pelgas, Betty; Gagnon, France; Birol, Inanç; Bohlmann, Joerg; Mackay, John; Isabel, Nathalie; Bousquet, Jean

    2017-04-01

    Over the last decade, extensive genetic and genomic resources have been developed for the conifer white spruce (Picea glauca, Pinaceae), which has one of the largest plant genomes (20 Gbp). Draft genome sequences of white spruce and other conifers have recently been produced, but dense genetic maps are needed to comprehend genome macrostructure, delineate regions involved in quantitative traits, complement functional genomic investigations, and assist the assembly of fragmented genomic sequences. A greatly expanded P. glauca composite linkage map was generated from a set of 1976 full-sib progeny, with the positioning of 8793 expressed genes. Regions with significant low or high gene density were identified. Gene family members tended to be mapped on the same chromosomes, with tandemly arrayed genes significantly biased towards specific functional classes. The map was integrated with transcriptome data surveyed across eight tissues. In total, 69 clusters of co-expressed and co-localising genes were identified. A high level of synteny was found with pine genetic maps, which should facilitate the transfer of structural information in the Pinaceae. Although the current white spruce genome sequence remains highly fragmented, dozens of scaffolds encompassing more than one mapped gene were identified. From these, the relationship between genetic and physical distances was examined and the genome-wide recombination rate was found to be much smaller than most estimates reported for angiosperm genomes. This gene linkage map shall assist the large-scale assembly of the next-generation white spruce genome sequence and provide a reference resource for the conifer genomics community. © 2017 Her Majesty the Queen in Right of Canada. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

  3. Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

    Science.gov (United States)

    Kohira, K.; Masuda, H.

    2017-09-01

    A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

  4. THE APPLICATION OF DIGITAL LINE GRAPHS AND MAP IN THE NETWORK ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    X. Guo

    2012-07-01

    Full Text Available WebGIS is an important research field in GIS. W3C organization established SVG standard, which laid a foundation for WebGIS based on vector data. In China, Digital Line Graphs(DLG is a significant GIS product and it has been used in many medium and large WebGIS system. Geographic information-portrayal is the common method of DLG visualization. However, the inherent characteristics of Geographic information-portrayal may lead to a relatively higher data production input, still, the visualization effect is not ideal. We put forward a new product named Digital Line Graphs and Map(DLGM, which consists of DLG and DLG's cartographic presentation data. It provides visualization data based on the cartographic standards. Due to the manufacture and management of DLGM data that are independent from software and platform, its data can be used in many fields. Network application is one of them. This paper is to use DLGM in the network applications. First it reveals the connotation and characteristics of DLGM then analyses the model that DLGM organizes, manages DLG and map symbol data. After that, combined with SVG standards, we put forward DLGM’s SVG encoding method without any information loss. Finally we provide a web map system based on local area network by using 1:10000 DLGM data of a certain area. Based on this study, we conclude that DLGM can be used in the network environment providing high quality DLG and cartographic data for WebGIS.

  5. The Application of Digital Line Graphs and Map in the Network Environment

    Science.gov (United States)

    Guo, X.; Zhang, B.; Yu, J.; Ran, H.; Wang, L.

    2012-07-01

    WebGIS is an important research field in GIS. W3C organization established SVG standard, which laid a foundation for WebGIS based on vector data. In China, Digital Line Graphs(DLG) is a significant GIS product and it has been used in many medium and large WebGIS system. Geographic information-portrayal is the common method of DLG visualization. However, the inherent characteristics of Geographic information-portrayal may lead to a relatively higher data production input, still, the visualization effect is not ideal. We put forward a new product named Digital Line Graphs and Map(DLGM), which consists of DLG and DLG's cartographic presentation data. It provides visualization data based on the cartographic standards. Due to the manufacture and management of DLGM data that are independent from software and platform, its data can be used in many fields. Network application is one of them. This paper is to use DLGM in the network applications. First it reveals the connotation and characteristics of DLGM then analyses the model that DLGM organizes, manages DLG and map symbol data. After that, combined with SVG standards, we put forward DLGM's SVG encoding method without any information loss. Finally we provide a web map system based on local area network by using 1:10000 DLGM data of a certain area. Based on this study, we conclude that DLGM can be used in the network environment providing high quality DLG and cartographic data for WebGIS.

  6. A Cross-Layer Wireless Sensor Network Energy-Efficient Communication Protocol for Real-Time Monitoring of the Long-Distance Electric Transmission Lines

    Directory of Open Access Journals (Sweden)

    Jun Yu

    2015-01-01

    Full Text Available Optimization of energy consumption in Wireless Sensor Network (WSN nodes has become a critical link that constrains the engineering application of the smart grid due to the fact that the smart grid is characterized by long-distance transmission in a special environment. The paper proposes a linear hierarchical network topological structure specific to WSN energy conservation in environmental monitoring of the long-distance electric transmission lines in the smart grid. Based on the topological structural characteristics and optimization of network layers, the paper also proposes a Topological Structure be Layered Configurations (TSLC routing algorithm to improve the quality of WSN data transmission performance. Coprocessing of the network layer and the media access control (MAC layer is achieved by using the cross-layer design method, accessing the status for the nodes in the network layer and obtaining the status of the network nodes of the MAC layer. It efficiently saves the energy of the whole network, improves the quality of the network service performance, and prolongs the life cycle of the network.

  7. Mapping dynamic social networks in real life using participants' own smartphones

    Directory of Open Access Journals (Sweden)

    Tjeerd W. Boonstra

    2015-11-01

    Full Text Available Interpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing. Smartphones have great potential for measuring social networks in a real world setting. Here we tested the feasibility of using people's own smartphones as a data collection platform for face-to-face interactions. We developed an application for iOS and Android to collect Bluetooth data and acquired one week of data from 14 participants in our organization. The Bluetooth scanning statistics were used to quantify the time-resolved connection strength between participants and define the weights of a dynamic social network. We used network metrics to quantify changes in network topology over time and non-negative matrix factorization to identify cliques or subgroups that reoccurred during the week. The scanning rate varied considerably between smartphones running Android and iOS and egocentric networks metrics were correlated with the scanning rate. The time courses of two identified subgroups matched with two meetings that took place that week. These findings demonstrate the feasibility of using participants' own smartphones to map social network, whilst identifying current limitations of using generic smartphones. The bias introduced by variations in scanning rate and missing data is an important limitation that needs to be addressed in future studies.

  8. Mapping dynamic social networks in real life using participants' own smartphones.

    Science.gov (United States)

    Boonstra, Tjeerd W; E Larsen, Mark; Christensen, Helen

    2015-11-01

    Interpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing. Smartphones have great potential for measuring social networks in a real world setting. Here we tested the feasibility of using people's own smartphones as a data collection platform for face-to-face interactions. We developed an application for iOS and Android to collect Bluetooth data and acquired one week of data from 14 participants in our organization. The Bluetooth scanning statistics were used to quantify the time-resolved connection strength between participants and define the weights of a dynamic social network. We used network metrics to quantify changes in network topology over time and non-negative matrix factorization to identify cliques or subgroups that reoccurred during the week. The scanning rate varied considerably between smartphones running Android and iOS and egocentric networks metrics were correlated with the scanning rate. The time courses of two identified subgroups matched with two meetings that took place that week. These findings demonstrate the feasibility of using participants' own smartphones to map social network, whilst identifying current limitations of using generic smartphones. The bias introduced by variations in scanning rate and missing data is an important limitation that needs to be addressed in future studies.

  9. Measurement and interpolation uncertainties in rainfall maps from cellular communication networks

    Science.gov (United States)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received power of the electromagnetic signal at regular intervals. The decrease in power can be converted to rainfall intensity, and is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfils the continuous effort to obtain measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e. the errors involved in link rainfall retrievals, such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, dry weather baseline attenuation, quantization of the received power, drop size distribution (DSD), and multi-path propagation; and (2) those associated with mapping, i.e. the combined effect of the interpolation methodology and the spatial density of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of the Netherlands. Simulated link rainfall depths refer to path-averaged rainfall depths obtained from radar data. The ~ 3500 real and simulated rainfall maps were

  10. Ontology Mapping: An Information Retrieval and Interactive Activation Network Based Approach

    Science.gov (United States)

    Mao, Ming

    Ontology mapping is to find semantic correspondences between similar elements of different ontologies. It is critical to achieve semantic interoperability in the WWW. This paper proposes a new generic and scalable ontology mapping approach based on propagation theory, information retrieval technique and artificial intelligence model. The approach utilizes both linguistic and structural information, measures the similarity of different elements of ontologies in a vector space model, and deals with constraints using the interactive activation network. The results of pilot study, the PRIOR, are promising and scalable.

  11. Mapping the Networks in Hyperlink Movies: Rethinking the Concept of Cartography through Network Narratives

    Directory of Open Access Journals (Sweden)

    Maxime Labrecque

    2016-12-01

    Full Text Available Network narratives, hyperlink or ensemble movies are a seductive introduction to the complexity of our globalized world and our social interactions. Using two popular examples, Babel and Love Actually, I explore the uses and the limits of the social network, respectively through a global and deterritorialised network and a local one that reveals kinship. Using the dynamic of networks to represent the characters’ interactions, these types of films nonetheless need boundaries. In the context of globalization, hyperlink movies are the mirror of a new geography but cannot show the complexity and the extent of it all since they are restricted by their own limits, being a narrative medium with a specific length. Hyperlink movies therefore present an interesting compromise, using a popular narrative technique to showcase a complex phenomenon.

  12. Simulation and performance analysis of the AD HOC On-Demand Distance Vector Routing Protocol for tactical mobile ad hoc networks

    OpenAIRE

    Theriot, Tyrone P.

    2000-01-01

    This thesis presents a simulation and analysis of the Ad Hoc On- Demand Distance Vector Routing Protocol (AODV) for mobile ad hoc network (MANET) environments using the Network Simulator 2 (NS2) tool. AODV is being suggested for possible implementation in the Joint Tactical Radio System (JTRS) for the United States military. Utilizing an AODV model resident in NS2, the simulation focuses on key performance parameters that include the packet delivery fraction, routing loss, buffer loss, total ...

  13. Differential Recruitment of Brain Networks following Route and Cartographic Map Learning of Spatial Environments

    Science.gov (United States)

    Zhang, Hui; Copara, Milagros; Ekstrom, Arne D.

    2012-01-01

    An extensive neuroimaging literature has helped characterize the brain regions involved in navigating a spatial environment. Far less is known, however, about the brain networks involved when learning a spatial layout from a cartographic map. To compare the two means of acquiring a spatial representation, participants learned spatial environments either by directly navigating them or learning them from an aerial-view map. While undergoing functional magnetic resonance imaging (fMRI), participants then performed two different tasks to assess knowledge of the spatial environment: a scene and orientation dependent perceptual (SOP) pointing task and a judgment of relative direction (JRD) of landmarks pointing task. We found three brain regions showing significant effects of route vs. map learning during the two tasks. Parahippocampal and retrosplenial cortex showed greater activation following route compared to map learning during the JRD but not SOP task while inferior frontal gyrus showed greater activation following map compared to route learning during the SOP but not JRD task. We interpret our results to suggest that parahippocampal and retrosplenial cortex were involved in translating scene and orientation dependent coordinate information acquired during route learning to a landmark-referenced representation while inferior frontal gyrus played a role in converting primarily landmark-referenced coordinates acquired during map learning to a scene and orientation dependent coordinate system. Together, our results provide novel insight into the different brain networks underlying spatial representations formed during navigation vs. cartographic map learning and provide additional constraints on theoretical models of the neural basis of human spatial representation. PMID:23028661

  14. Frequency Count Attribute Oriented Induction of Corporate Network Data for Mapping Business Activity

    Science.gov (United States)

    Tanutama, Lukas

    2014-03-01

    Companies increasingly rely on Internet for effective and efficient business communication. As Information Technology infrastructure backbone for business activities, corporate network connects the company to Internet and enables its activities globally. It carries data packets generated by the activities of the users performing their business tasks. Traditionally, infrastructure operations mainly maintain data carrying capacity and network devices performance. It would be advantageous if a company knows what activities are running in its network. The research provides a simple method of mapping the business activity reflected by the network data. To map corporate users' activities, a slightly modified Attribute Oriented Induction (AOI) approach to mine the network data was applied. The frequency of each protocol invoked were counted to show what the user intended to do. The collected data was samples taken within a certain sampling period. Samples were taken due to the enormous data packets generated. Protocols of interest are only Internet related while intranet protocols are ignored. It can be concluded that the method could provide the management a general overview of the usage of its infrastructure and lead to efficient, effective and secure ICT infrastructure.

  15. A dropout-regularised neural network for mapping arsenic enrichment in SW England using MXNet

    OpenAIRE

    Kirkwood, Charlie

    2016-01-01

    This poster applies a dropout-regularised artifical neural network, constructed in the MXNet framework, to map arsenic enrichment in south west England. The network models the relationships between arsenic (as a centred log-ratio from XRF analyses of 3395 stream sediment samples) and high resolution geophysical data. The resultant model, trained to optimal accuracy using early stopping, achieves an R2 of 0.7 on held-out test data - a promising level of accuracy for predictions in a complex hy...

  16. Mapping network motif tunability and robustness in the design of synthetic signaling circuits.

    Directory of Open Access Journals (Sweden)

    Sergio Iadevaia

    Full Text Available Cellular networks are highly dynamic in their function, yet evolutionarily conserved in their core network motifs or topologies. Understanding functional tunability and robustness of network motifs to small perturbations in function and structure is vital to our ability to synthesize controllable circuits. In establishing core sets of network motifs, we selected topologies that are overrepresented in mammalian networks, including the linear, feedback, feed-forward, and bifan circuits. Static and dynamic tunability of network motifs were defined as the motif ability to respectively attain steady-state or transient outputs in response to pre-defined input stimuli. Detailed computational analysis suggested that static tunability is insensitive to the circuit topology, since all of the motifs displayed similar ability to attain predefined steady-state outputs in response to constant inputs. Dynamic tunability, in contrast, was tightly dependent on circuit topology, with some motifs performing superiorly in achieving observed time-course outputs. Finally, we mapped dynamic tunability onto motif topologies to determine robustness of motif structures to changes in topology and identify design principles for the rational assembly of robust synthetic networks.

  17. On network coding and modulation mapping for three-phase bidirectional relaying

    KAUST Repository

    Chang, Ronald Y.

    2015-12-03

    © 2015 IEEE. In this paper, we consider the network coding (NC) enabled three-phase protocol for information exchange between two users in a wireless two-way (bidirectional) relay network. Modulo-based (nonbinary) and XOR-based (binary) NC schemes are considered as information mixture schemes at the relay while all transmissions adopt pulse amplitude modulation (PAM). We first obtain the optimal constellation mapping at the relay that maximizes the decoding performance at the users for each NC scheme. Then, we compare the two NC schemes, each in conjunction with the optimal constellation mapping at the relay, in different conditions. Our results demonstrate that, in the low SNR regime, binary NC outperforms nonbinary NC with 4-PAM, while they have mixed performance with 8-PAM. This observation applies to quadrature amplitude modulation (QAM) composed of two parallel PAMs.

  18. Just a Facebook away: The use of social network sites for relationship maintenance in long-distance and geographically-close romantic relationships

    NARCIS (Netherlands)

    Billedo, C.J.; Kerkhof, P.; Finkenauer, C.

    2015-01-01

    Social networking sites (SNS) play an increasingly important role in maintaining geographically close romantic relationships (GCRR). However, knowledge about SNS use in long-distance romantic relationships (LDRR) is still lacking. The present study examined the relative importance of SNS in

  19. The Hetu'u Global Network: Measuring the Distance to the Sun Using the June 5th/6th Transit of Venus

    Science.gov (United States)

    Faherty, Jacqueline K.; Rodriguez, David R.; Miller, Scott T.

    2012-01-01

    In the spirit of historic astronomical endeavors, we invited school groups across the globe to collaborate in a solar distance measurement using the rare June 5/6th transit of Venus. In total, we recruited 19 school groups spread over 6 continents and 10 countries to participate in our Hetu'u Global Network. Applying the methods of French…

  20. Mapping Transcription Regulatory Networks with ChIP-seq and RNA-seq.

    Science.gov (United States)

    Wade, Joseph T

    2015-01-01

    Bacterial genomes encode numerous transcription factors, DNA-binding proteins that regulate transcription initiation. Identifying the regulatory targets of transcription factors is a major challenge of systems biology. Here I describe the use of two genome-scale approaches, ChIP-seq and RNA-seq, that are used to map transcription factor regulons. ChIP-seq maps the association of transcription factors with DNA, and RNA-seq determines changes in RNA levels associated with transcription factor perturbation. I discuss the strengths and weaknesses of these and related approaches, and I describe how ChIP-seq and RNA-seq can be combined to map individual transcription factor regulons and entire regulatory networks.

  1. Reducing Communication Overhead by Scheduling TCP Transfers on Mobile Devices using Wireless Network Performance Maps

    DEFF Research Database (Denmark)

    Højgaard-Hansen, Kim; Madsen, Tatiana Kozlova; Schwefel, Hans-Peter

    2012-01-01

    of such performance maps. We demonstrate how the framework can be used to reduce the retransmissions and to better utilise network resources when performing TCP-based file downloads in vehicular M2M communication scenarios. The approach works on top of a standard TCP stack hence has to map identified transmission...... intervals to predicted TCP data volumes. The file download optimisation is evaluated using extensive simulations comparing the TCP scheduling approach to a normal transfer. The performance map is generated by capturing round-trip time measurements and a threshold approach for the mean value for a given area...... potential for improvement in reducing the communication overhead compared with an ordinary TCP transfer....

  2. Mapping Speech Spectra from Throat Microphone to Close-Speaking Microphone: A Neural Network Approach

    Directory of Open Access Journals (Sweden)

    Yegnanarayana B

    2007-01-01

    Full Text Available Speech recorded from a throat microphone is robust to the surrounding noise, but sounds unnatural unlike the speech recorded from a close-speaking microphone. This paper addresses the issue of improving the perceptual quality of the throat microphone speech by mapping the speech spectra from the throat microphone to the close-speaking microphone. A neural network model is used to capture the speaker-dependent functional relationship between the feature vectors (cepstral coefficients of the two speech signals. A method is proposed to ensure the stability of the all-pole synthesis filter. Objective evaluations indicate the effectiveness of the proposed mapping scheme. The advantage of this method is that the model gives a smooth estimate of the spectra of the close-speaking microphone speech. No distortions are perceived in the reconstructed speech. This mapping technique is also used for bandwidth extension of telephone speech.

  3. The Resource Mapping Algorithm of Wireless Virtualized Networks for Saving Energy in Ultradense Small Cells

    Directory of Open Access Journals (Sweden)

    Sai Zou

    2015-01-01

    Full Text Available As the current network is designed for peak loads, it results in insufficient resource utilization and energy waste. Virtualized technology makes it possible that intelligent energy perception network could be deployed and resource sharing could become an effective energy saving technology. How to make more small cells into sleeping state for energy saving in ultradense small cell system has become a research hot spot. Based on the mapping feature of virtualized network, a new wireless resource mapping algorithm for saving energy in ultradense small cells has been put forward when wireless resource amount is satisfied in every small cell. First of all, the method divides the virtual cells. Again through the alternate updating between small cell mapping and wireless resource allocation, least amount of small cells is used and other small cells turn into sleeping state on the premise of guaranteeing users’ QoS. Next, the energy consumption of the wireless access system, wireless resource utilization, and the convergence of the proposed algorithm are analyzed in theory. Finally, the simulation results demonstrate that the algorithm can effectively reduce the system energy consumption and required wireless resource amount under the condition of satisfying users’ QoS.

  4. The neuronal network involved in self-attribution of an artificial hand: A lesion network-symptom-mapping study.

    Science.gov (United States)

    Wawrzyniak, Max; Klingbeil, Julian; Zeller, Daniel; Saur, Dorothee; Classen, Joseph

    2018-02-01

    The feeling of body-ownership can be experimentally manipulated using the rubber hand illusion (RHI) paradigm. Participants experience a sense of ownership over an artificial hand when their hidden real hand and the visible artificial hand are synchronously stroked. Using lesion masks and behavioral data from a previous study on RHI failure in acute stroke patients, we here employed lesion network-symptom-mapping (LNSM) based on normative functional connectome data to identify lesion-dependent network connectivity related to the experience of self-attribution of an artificial hand in the RHI paradigm. We found that failure to experience the RHI was associated with higher normative lesion-dependent network connectivity to the right temporoparietal junction (rTPJ), right anterior Insula (raI) and right inferior frontal gyrus (rIFG). Since these areas were spared by the infarction in most patients with RHI failure (89% for rTPJ and 94% for raI/rIFG), the analysis suggests that remote dysfunction in rTPJ, raI, and rIFG accounted for RHI failure. These results highlight the potential role of rTPJ, raI, and rIFG in bodily self-consciousness. LNSM is a powerful tool capable of delineating the architecture of functional networks underlying complex cognitive function. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. A Proposed Scalable Design and Simulation of Wireless Sensor Network-Based Long-Distance Water Pipeline Leakage Monitoring System

    Directory of Open Access Journals (Sweden)

    Abdulaziz S. Almazyad

    2014-02-01

    Full Text Available Anomalies such as leakage and bursts in water pipelines have severe consequences for the environment and the economy. To ensure the reliability of water pipelines, they must be monitored effectively. Wireless Sensor Networks (WSNs have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines. In this paper, we present a scalable design and simulation of a water pipeline leakage monitoring system using Radio Frequency IDentification (RFID and WSN technology. The proposed design targets long-distance aboveground water pipelines that have special considerations for maintenance, energy consumption and cost. The design is based on deploying a group of mobile wireless sensor nodes inside the pipeline and allowing them to work cooperatively according to a prescheduled order. Under this mechanism, only one node is active at a time, while the other nodes are sleeping. The node whose turn is next wakes up according to one of three wakeup techniques: location-based, time-based and interrupt-driven. In this paper, mathematical models are derived for each technique to estimate the corresponding energy consumption and memory size requirements. The proposed equations are analyzed and the results are validated using simulation.

  6. Using spatiotemporal models and distance sampling to map the space use and abundance of newly metamorphosed Western Toads (Anaxyrus boreas)

    Science.gov (United States)

    Chelgren, Nathan D.; Samora, Barbara; Adams, Michael J.; McCreary, Brome

    2011-01-01

    High variability in abundance, cryptic coloration, and small body size of newly metamorphosed anurans have limited demographic studies of this life-history stage. We used line-transect distance sampling and Bayesian methods to estimate the abundance and spatial distribution of newly metamorphosed Western Toads (Anaxyrus boreas) in terrestrial habitat surrounding a montane lake in central Washington, USA. We completed 154 line-transect surveys from the commencement of metamorphosis (15 September 2009) to the date of first snow accumulation in fall (1 October 2009), and located 543 newly metamorphosed toads. After accounting for variable detection probability associated with the extent of barren habitats, estimates of total surface abundance ranged from a posterior median of 3,880 (95% credible intervals from 2,235 to 12,600) in the first week of sampling to 12,150 (5,543 to 51,670) during the second week of sampling. Numbers of newly metamorphosed toads dropped quickly with increasing distance from the lakeshore in a pattern that differed over the three weeks of the study and contradicted our original hypotheses. Though we hypothesized that the spatial distribution of toads would initially be concentrated near the lake shore and then spread outward from the lake over time, we observed the opposite. Ninety-five percent of individuals occurred within 20, 16, and 15 m of shore during weeks one, two, and three respectively, probably reflecting continued emergence of newly metamorphosed toads from the lake and mortality or burrow use of dispersed individuals. Numbers of toads were highest near the inlet stream of the lake. Distance sampling may provide a useful method for estimating the surface abundance of newly metamorphosed toads and relating their space use to landscape variables despite uncertain and variable probability of detection. We discuss means of improving the precision of estimates of total abundance.

  7. Staff Recall Travel Time for ST Elevation Myocardial Infarction Impacted by Traffic Congestion and Distance: A Digitally Integrated Map Software Study

    Directory of Open Access Journals (Sweden)

    Justin Cole

    2018-01-01

    Full Text Available BackgroundRecent evidence suggests hospitals fail to meet guideline specified time to percutaneous coronary intervention (PCI for a proportion of ST elevation myocardial infarction (STEMI presentations. Implicit in achieving this time is the rapid assembly of crucial catheter laboratory staff. As a proof-of-concept, we set out to create regional maps that graphically show the impact of traffic congestion and distance to destination on staff recall travel times for STEMI, thereby producing a resource that could be used by staff to improve reperfusion time for STEMI.MethodsTravel times for staff recalled to one inner and one outer metropolitan hospital at midnight, 6 p.m., and 7 a.m. were estimated using Google Maps Application Programming Interface. Computer modeling predictions were overlaid on metropolitan maps showing color coded staff recall travel times for STEMI, occurring within non-peak and peak hour traffic congestion times.ResultsInner metropolitan hospital staff recall travel times were more affected by traffic congestion compared with outer metropolitan times, and the latter was more affected by distance. The estimated mean travel times to hospital during peak hour were greater than midnight travel times by 13.4 min to the inner and 6.0 min to the outer metropolitan hospital at 6 p.m. (p < 0.001. At 7 a.m., the mean difference was 9.5 min to the inner and 3.6 min to the outer metropolitan hospital (p < 0.001. Only 45% of inner metropolitan staff were predicted to arrive within 30 min at 6 p.m. compared with 100% at midnight (p < 0.001, and 56% of outer metropolitan staff at 6 p.m. (p = 0.021.ConclusionOur results show that integration of map software with traffic congestion data, distance to destination and travel time can predict optimal residence of staff when on-call for PCI.

  8. Mapping industrial networks as an approach to identify inter-organisational collaborative potential in new product development

    DEFF Research Database (Denmark)

    Parraguez, Pedro; Maier, Anja

    2012-01-01

    Increased industrial complexity and specialization is pushing organizations to participate more proactively in collaborative networks. These networks enable them to create new products and services requiring a pool of knowledge and capabilities going beyond the traditional organizational boundaries....... Consequently, identifying and selecting potential partners to establish collaboration agreements can be a key activity in the new product development process. This paper explores the implications of mapping industrial networks with the purpose of identifying inter-organisational collaborative potential....... The analysis is contextualized mapping the Danish Cleantech industry and depict the uses of the visualization and analysis of industrial networks in the selection of co-developing partners....

  9. 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

    2017-04-11

    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.

  10. Robust spatial memory maps in flickering neuronal networks: a topological model

    Science.gov (United States)

    Dabaghian, Yuri; Babichev, Andrey; Memoli, Facundo; Chowdhury, Samir; Rice University Collaboration; Ohio State University Collaboration

    It is widely accepted that the hippocampal place cells provide a substrate of the neuronal representation of the environment--the ``cognitive map''. However, hippocampal network, as any other network in the brain is transient: thousands of hippocampal neurons die every day and the connections formed by these cells constantly change due to various forms of synaptic plasticity. What then explains the remarkable reliability of our spatial memories? We propose a computational approach to answering this question based on a couple of insights. First, we propose that the hippocampal cognitive map is fundamentally topological, and hence it is amenable to analysis by topological methods. We then apply several novel methods from homology theory, to understand how dynamic connections between cells influences the speed and reliability of spatial learning. We simulate the rat's exploratory movements through different environments and study how topological invariants of these environments arise in a network of simulated neurons with ``flickering'' connectivity. We find that despite transient connectivity the network of place cells produces a stable representation of the topology of the environment.

  11. MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

    Science.gov (United States)

    Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming

    2017-09-01

    Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.

  12. Aging alterations in whole-brain networks during adulthood mapped with the minimum spanning tree indices: The interplay of density, connectivity cost and life-time trajectory

    NARCIS (Netherlands)

    Otte, W.M.; van Diessen, E.; Paul, S.; Ramaswamy, R.; Rallabandi, V.P.S.; Stam, C.J.; Roy, P.K.

    2015-01-01

    The organizational network changes in the human brain across the lifespan have been mapped using functional and structural connectivity data. Brain network changes provide valuable insights into the processes underlying senescence. Nonetheless, the altered network density in the elderly severely

  13. Aging alterations in whole-brain networks during adulthood mapped with the minimum spanning tree indices : The interplay of density, connectivity cost and life-time trajectory

    NARCIS (Netherlands)

    Otte, Wim; van Diessen, Eric; Paul, Subhadip; Ramaswamy, Rajiv; Subramanyam Rallabandi, V. P.; Stam, Cornelis J.; Roy, Prasun K.

    2015-01-01

    The organizational network changes in the human brain across the lifespan have been mapped using functional and structural connectivity data. Brain network changes provide valuable insights into the processes underlying senescence. Nonetheless, the altered network density in the elderly severely

  14. Analyzing the role of social networks in mapping knowledge flows: A case of a pharmaceutical company in India

    Directory of Open Access Journals (Sweden)

    V. Murale

    2014-03-01

    Full Text Available Knowledge Management literature lays emphasis on the fact that a major chunk of knowledge dissemination occurs through the various forms of social networks that exist within the organizations. A social network is a simple structure comprising of set of actors or nodes that may have relationships ties with one another. The social network analysis (SNA will help in mapping and measuring formal and informal relationships to understand what facilitates or impedes the knowledge flows that bind interacting units. This paper aims at studying the knowledge flows that happen through the social networks. It first, provides a conceptual framework and review of literature on the recent research and application of knowledge mapping and SNA, followed by a discussion on application of SNA for mapping knowledge flows in a pharmaceutical firm. In the last part, Knowledge maps are presented to illustrate the actual knowledge flow in firm.

  15. Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

    Science.gov (United States)

    Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

    2017-11-01

    Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

  16. The routing, modulation level, and spectrum allocation algorithm in the virtual optical network mapping

    Science.gov (United States)

    Wang, Yunyun; Li, Hui; Liu, Yuze; Ji, Yuefeng; Li, Hongfa

    2017-10-01

    With the development of large video services and cloud computing, the network is increasingly in the form of services. In SDON, the SDN controller holds the underlying physical resource information, thus allocating the appropriate resources and bandwidth to the VON service. However, for some services that require extremely strict QoT (quality of transmission), the shortest distance path algorithm is often unable to meet the requirements because it does not take the link spectrum resources into account. And in accordance with the choice of the most unoccupied links, there may be more spectrum fragments. So here we propose a new RMLSA (the routing, modulation Level, and spectrum allocation) algorithm to reduce the blocking probability. The results show about 40% less blocking probability than the shortest-distance algorithm and the minimum usage of the spectrum priority algorithm. This algorithm is used to satisfy strict request of QoT for demands.

  17. Data Access Based on a Guide Map of the Underwater Wireless Sensor Network.

    Science.gov (United States)

    Wei, Zhengxian; Song, Min; Yin, Guisheng; Song, Houbing; Wang, Hongbin; Ma, Xuefei; Cheng, Albert M K

    2017-10-17

    Underwater wireless sensor networks (UWSNs) represent an area of increasing research interest, as data storage, discovery, and query of UWSNs are always challenging issues. In this paper, a data access based on a guide map (DAGM) method is proposed for UWSNs. In DAGM, the metadata describes the abstracts of data content and the storage location. The center ring is composed of nodes according to the shortest average data query path in the network in order to store the metadata, and the data guide map organizes, diffuses and synchronizes the metadata in the center ring, providing the most time-saving and energy-efficient data query service for the user. For this method, firstly the data is stored in the UWSN. The storage node is determined, the data is transmitted from the sensor node (data generation source) to the storage node, and the metadata is generated for it. Then, the metadata is sent to the center ring node that is the nearest to the storage node and the data guide map organizes the metadata, diffusing and synchronizing it to the other center ring nodes. Finally, when there is query data in any user node, the data guide map will select a center ring node nearest to the user to process the query sentence, and based on the shortest transmission delay and lowest energy consumption, data transmission routing is generated according to the storage location abstract in the metadata. Hence, specific application data transmission from the storage node to the user is completed. The simulation results demonstrate that DAGM has advantages with respect to data access time and network energy consumption.

  18. Mapping the dengue scientific landscape worldwide: a bibliometric and network analysis

    Directory of Open Access Journals (Sweden)

    Fabio Batista Mota

    Full Text Available BACKGROUND Despite the current global trend of reduction in the morbidity and mortality of neglected diseases, dengue’s incidence has increased and occurrence areas have expanded. Dengue also persists as a scientific and technological challenge since there is no effective treatment, vaccine, vector control or public health intervention. Combining bibliometrics and social network analysis methods can support the mapping of dengue research and development (R&D activities worldwide. OBJECTIVES The aim of this paper is to map the scientific scenario related to dengue research worldwide. METHODS We use scientific publication data from Web of Science Core Collection - articles indexed in Science Citation Index Expanded (SCI-EXPANDED - and combine bibliometrics and social network analysis techniques to identify the most relevant journals, scientific references, research areas, countries and research organisations in the dengue scientific landscape. FINDINGS Our results show a significant increase of dengue publications over time; tropical medicine and virology as the most frequent research areas and biochemistry and molecular biology as the most central area in the network; USA and Brazil as the most productive countries; and Mahidol University and Fundação Oswaldo Cruz as the main research organisations and the Centres for Disease Control and Prevention as the most central organisation in the collaboration network. MAIN CONCLUSIONS Our findings can be used to strengthen a global knowledge platform guiding policy, planning and funding decisions as well as to providing directions to researchers and institutions. So that, by offering to the scientific community, policy makers and public health practitioners a mapping of the dengue scientific landscape, this paper has aimed to contribute to upcoming debates, decision-making and planning on dengue R&D and public health strategies worldwide.

  19. Mapping the dengue scientific landscape worldwide: a bibliometric and network analysis.

    Science.gov (United States)

    Mota, Fabio Batista; Fonseca, Bruna de Paula Fonseca E; Galina, Andréia Cristina; Silva, Roseli Monteiro da

    2017-05-01

    Despite the current global trend of reduction in the morbidity and mortality of neglected diseases, dengue's incidence has increased and occurrence areas have expanded. Dengue also persists as a scientific and technological challenge since there is no effective treatment, vaccine, vector control or public health intervention. Combining bibliometrics and social network analysis methods can support the mapping of dengue research and development (R&D) activities worldwide. The aim of this paper is to map the scientific scenario related to dengue research worldwide. We use scientific publication data from Web of Science Core Collection - articles indexed in Science Citation Index Expanded (SCI-EXPANDED) - and combine bibliometrics and social network analysis techniques to identify the most relevant journals, scientific references, research areas, countries and research organisations in the dengue scientific landscape. Our results show a significant increase of dengue publications over time; tropical medicine and virology as the most frequent research areas and biochemistry and molecular biology as the most central area in the network; USA and Brazil as the most productive countries; and Mahidol University and Fundação Oswaldo Cruz as the main research organisations and the Centres for Disease Control and Prevention as the most central organisation in the collaboration network. Our findings can be used to strengthen a global knowledge platform guiding policy, planning and funding decisions as well as to providing directions to researchers and institutions. So that, by offering to the scientific community, policy makers and public health practitioners a mapping of the dengue scientific landscape, this paper has aimed to contribute to upcoming debates, decision-making and planning on dengue R&D and public health strategies worldwide.

  20. Neural network models for spatial data mining, map production, and cortical direction selectivity

    Science.gov (United States)

    Parsons, Olga

    A family of ARTMAP neural networks for incremental supervised learning has been developed over the last decade. The Sensor Exploitation Group of MIT Lincoln Laboratory (LL) has incorporated an early version of this network as the recognition engine of a hierarchical system for fusion and data mining of multiple registered geospatial images. The LL system has been successfully fielded, but it is limited to target vs. non-target identifications and does not produce whole maps. This dissertation expands the capabilities of the LL system so that it learns to identify arbitrarily many target classes at once and can thus produce a whole map. This new spatial data mining system is designed particularly to cope with the highly skewed class distributions of typical mapping problems. Specification of a consistent procedure and a benchmark testbed has permitted the evaluation of candidate recognition networks as well as pre- and post-processing and feature extraction options. The resulting default ARTMAP network and mapping methodology set a standard for a variety of related mapping problems and application domains. The second part of the dissertation investigates the development of cortical direction selectivity. The possible role of visual experience and oculomotor behavior in the maturation of cells in the primary visual cortex is studied. The responses of neurons in the thalamus and cortex of the cat are modeled when natural scenes are scanned by several types of eye movements. Inspired by the Hebbian-like synaptic plasticity, which is based upon correlations between cell activations, the second-order statistical structure of thalamo-cortical activity is examined. In the simulations, patterns of neural activity that lead to a correct refinement of cell responses are observed during visual fixation, when small ocular movements occur, but are not observed in the presence of large saccades. Simulations also replicate experiments in which kittens are reared under stroboscopic

  1. Association of medial meniscal extrusion with medial tibial osteophyte distance detected by T2 mapping MRI in patients with early-stage knee osteoarthritis.

    Science.gov (United States)

    Hada, Shinnosuke; Ishijima, Muneaki; Kaneko, Haruka; Kinoshita, Mayuko; Liu, Lizu; Sadatsuki, Ryo; Futami, Ippei; Yusup, Anwajan; Takamura, Tomohiro; Arita, Hitoshi; Shiozawa, Jun; Aoki, Takako; Takazawa, Yuji; Ikeda, Hiroshi; Aoki, Shigeki; Kurosawa, Hisashi; Okada, Yasunori; Kaneko, Kazuo

    2017-09-12

    Medial meniscal extrusion (MME) is associated with progression of medial knee osteoarthritis (OA), but no or little information is available for relationships between MME and osteophytes, which are found in cartilage and bone parts. Because of the limitation in detectability of the cartilage part of osteophytes by radiography or conventional magnetic resonance imaging (MRI), the rate of development and size of osteophytes appear to have been underestimated. Because T2 mapping MRI may enable us to evaluate the cartilage part of osteophytes, we aimed to examine the association between MME and OA-related changes, including osteophytes, by using conventional and T2 mapping MRI. Patients with early-stage knee OA (n = 50) were examined. MRI-detected OA-related changes, in addition to MME, were evaluated according to the Whole-Organ Magnetic Resonance Imaging Score. T2 values of the medial meniscus and osteophytes were measured on T2 mapping images. Osteophytes surgically removed from patients with end-stage knee OA were histologically analyzed and compared with findings derived by radiography and MRI. Medial side osteophytes were detected by T2 mapping MRI in 98% of patients with early-stage knee OA, although the detection rate was 48% by conventional MRI and 40% by radiography. Among the OA-related changes, medial tibial osteophyte distance was most closely associated with MME, as determined by multiple logistic regression analysis, in the patients with early-stage knee OA (β = 0.711, p early-stage knee OA, who showed ≥ 3 mm of MME (r = 0.58, p = 0.003). The accuracy of osteophyte evaluation by T2 mapping MRI was confirmed by histological analysis of the osteophytes removed from patients with end-stage knee OA. Our study demonstrates that medial tibial osteophyte evaluated by T2 mapping MRI is frequently observed in the patients with early-stage knee OA, showing close association with MME, and that MME is positively correlated with the meniscal

  2. Social Network Analysis by Geo-Map: the relations of the UFMT / Brazil

    Directory of Open Access Journals (Sweden)

    Adilson Luiz Pinto

    2013-03-01

    Full Text Available This study has the objective to identify the scientific representation of the Federal University of the Mato Grosso (UFMT, relationed to the participation on the programs Google Earth and Google Maps, where the most important relationships are showing with more than 5 articles published on Web of Science. For recover data, was used a search by the institutional affiliation (C1 while the treatment was done on Excel using GPS Visualizer’s, for to map the longitudes and latitudes. At a later time was created a page for to support the structure on the format .Kml, language that can be read by the Google Maps and Google Earth. On the network analysis, the origination of relation map it passes for big changes becoming a trend for to indentify relations in a higher level, one of the ways to gain global visibility of a research institution related to the employees, scientific colleague, finding the key on the scale of transposition that the Federal University of Mato Grosso could sign importants agreements in their scientific cooperation (with the participation of the Universities: USP, UFRJ, Federal de Visçosa, Unicamp and Unesp and on the foreign countries with Institute Max Planck of limnology and from Darmstadt Technology University, whom had been the most prominent on the productive scale. In scientific areas was detached in relations on Medicine, Agriculture, Engineering, Physics, Chemistry and Animal Production.

  3. xiNET: Cross-link Network Maps With Residue Resolution*

    Science.gov (United States)

    Combe, Colin W.; Fischer, Lutz; Rappsilber, Juri

    2015-01-01

    xiNET is a visualization tool for exploring cross-linking/mass spectrometry results. The interactive maps of the cross-link network that it generates are a type of node-link diagram. In these maps xiNET displays: (1) residue resolution positional information including linkage sites and linked peptides; (2) all types of cross-linking reaction product; (3) ambiguous results; and, (4) additional sequence information such as domains. xiNET runs in a browser and exports vector graphics which can be edited in common drawing packages to create publication quality figures. Availability: xiNET is open source, released under the Apache version 2 license. Results can be viewed by uploading data to http://crosslinkviewer.org/ or by downloading the software from http://github.com/colin-combe/crosslink-viewer and running it locally. PMID:25648531

  4. xiNET: cross-link network maps with residue resolution.

    Science.gov (United States)

    Combe, Colin W; Fischer, Lutz; Rappsilber, Juri

    2015-04-01

    xiNET is a visualization tool for exploring cross-linking/mass spectrometry results. The interactive maps of the cross-link network that it generates are a type of node-link diagram. In these maps xiNET displays: (1) residue resolution positional information including linkage sites and linked peptides; (2) all types of cross-linking reaction product; (3) ambiguous results; and, (4) additional sequence information such as domains. xiNET runs in a browser and exports vector graphics which can be edited in common drawing packages to create publication quality figures. xiNET is open source, released under the Apache version 2 license. Results can be viewed by uploading data to http://crosslinkviewer.org/ or by downloading the software from http://github.com/colin-combe/crosslink-viewer and running it locally. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  5. Mapping of the aquatic plants infestation in reservoirs using multiscale image and artificial neural networks

    Directory of Open Access Journals (Sweden)

    Narjara C. da Cruz

    2005-08-01

    Full Text Available In past few years, infestations of aquatic plants in reservoirs have been studied as an effect of the environmental unbalance caused by pollution and damming of rivers. The excessive amount of plants, deriving from this unbalance, makes navigation and the production of electricity difficult. This kind of occurrence, as well as the appearance of some substances in the water, cause changes in the water radiance detected by satellite sensors. Thus, processing techniques of remote sensing and data analysis may be used as a complementary data source to give information related to the degree of infestation of these plants in reservoirs. So, this research aimed at verifying the influence of the spatial resolution of multispectral images in the detection and mapping of areas infested by aquatic plants in a small reservoir, using multiscale analysis procedures and supervised classification by artificial neural networks. Multispectral images IKONOS of the Salto Grande reservoir, in the city of Americana-SP were used. At first, a multiscale image was generated, resulting in images of 8, 16 and 32 meters of spatial resolution. In the classification of these images, the input data for artificial neural networks was constituted of multispectral images IKONOS, texture data, and a vegetation index image and allowed represent the spectral variations of the water body and infested areas of aquatic plants in the various levels of spatial resolution. Furthermore, an analysis was made comparing classified multiscale images by using cross tabulation, which permits comparing the results obtained in the multiscale levels. As result is pointed out that the thematic maps were representative for the 4 levels of spatial resolution. The method used was adequate to map the spectral variation of the water body and to detect infested areas of aquatic plants in the various levels of resolution of the image. The classification by neural network using parameters defined for the

  6. Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

    Directory of Open Access Journals (Sweden)

    César da Silva Chagas

    2013-04-01

    Full Text Available Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI, derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs was greater than of the classic Maximum Likelihood Classifier (MLC. Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 % was superior to the MLC map (57.94 %. The main errors when using the two classifiers were caused by: a the geological heterogeneity of the area coupled with problems related to the geological map; b the depth of lithic contact and/or rock exposure, and c problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

  7. International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes

    DEFF Research Database (Denmark)

    Bal-Price, Anna; Crofton, Kevin M.; Leist, Marcel

    2015-01-01

    of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing...... as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment...

  8. Nanometric resolution magnetic resonance imaging methods for mapping functional activity in neuronal networks.

    Science.gov (United States)

    Boretti, Albert; Castelletto, Stefania

    2016-01-01

    This contribution highlights and compares some recent achievements in the use of k-space and real space imaging (scanning probe and wide-filed microscope techniques), when applied to a luminescent color center in diamond, known as nitrogen vacancy (NV) center. These techniques combined with the optically detected magnetic resonance of NV, provide a unique platform to achieve nanometric magnetic resonance imaging (MRI) resolution of nearby nuclear spins (known as nanoMRI), and nanometric NV real space localization. •Atomic size optically detectable spin probe.•High magnetic field sensitivity and nanometric resolution.•Non-invasive mapping of functional activity in neuronal networks.

  9. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps

    Directory of Open Access Journals (Sweden)

    Javier Blesa

    2009-11-01

    Full Text Available The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps, in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

  10. Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps.

    Science.gov (United States)

    Moya, José M; Araujo, Alvaro; Banković, Zorana; de Goyeneche, Juan-Mariano; Vallejo, Juan Carlos; Malagón, Pedro; Villanueva, Daniel; Fraga, David; Romero, Elena; Blesa, Javier

    2009-01-01

    The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

  11. Risk mapping of Rinderpest sero-prevalence in Central and Southern Somalia based on spatial and network risk factors

    Directory of Open Access Journals (Sweden)

    Aden Hussein H

    2010-04-01

    Full Text Available Abstract Background In contrast to most pastoral systems, the Somali livestock production system is oriented towards domestic trade and export with seasonal movement patterns of herds/flocks in search of water and pasture and towards export points. Data from a rinderpest survey and other data sources have been integrated to explore the topology of a contact network of cattle herds based on a spatial proximity criterion and other attributes related to cattle herd dynamics. The objective of the study is to integrate spatial mobility and other attributes with GIS and network approaches in order to develop a predictive spatial model of presence of rinderpest. Results A spatial logistic regression model was fitted using data for 562 point locations. It includes three statistically significant continuous-scale variables that increase the risk of rinderpest: home range radius, herd density and clustering coefficient of the node of the network whose link was established if the sum of the home ranges of every pair of nodes was equal or greater than the shortest distance between the points. The sensitivity of the model is 85.1% and the specificity 84.6%, correctly classifying 84.7% of the observations. The spatial autocorrelation not accounted for by the model is negligible and visual assessment of a semivariogram of the residuals indicated that there was no undue amount of spatial autocorrelation. The predictive model was applied to a set of 6176 point locations covering the study area. Areas at high risk of having serological evidence of rinderpest are located mainly in the coastal districts of Lower and Middle Juba, the coastal area of Lower Shabele and in the regions of Middle Shabele and Bay. There are also isolated spots of high risk along the border with Kenya and the southern area of the border with Ethiopia. Conclusions The identification of point locations and areas with high risk of presence of rinderpest and their spatial visualization as a

  12. Comparison between genetic algorithm and self organizing map to detect botnet network traffic

    Science.gov (United States)

    Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

    2017-11-01

    In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

  13. A Mobile Sensor Network to Map CO2 in Urban Environments

    Science.gov (United States)

    Lee, J.; Christen, A.; Nesic, Z.; Ketler, R.

    2014-12-01

    Globally, an estimated 80% of all fuel-based CO2 emissions into the atmosphere are attributable to cities, but there is still a lack of tools to map, visualize and monitor emissions to the scales at which emissions reduction strategies can be implemented - the local and urban scale. Mobile CO2 sensors, such as those attached to taxis and other existing mobile platforms, may be a promising way to observe and map CO2 mixing ratios across heterogenous urban environments with a limited number of sensors. Emerging modular open source technologies, and inexpensive compact sensor components not only enable rapid prototyping and replication, but also are allowing for the miniaturization and mobilization of traditionally fixed sensor networks. We aim to optimize the methods and technologies for monitoring CO2 in cities using a network of CO2 sensors deployable on vehicles and bikes. Our sensor technology is contained in a compact weather-proof case (35.8cm x 27.8cm x 11.8cm), powered independently by battery or by car, and includes the Li-Cor Li-820 infrared gas analyzer (Licor Inc, lincoln, NB, USA), Arduino Mega microcontroller (Arduino CC, Italy) and Adafruit GPS (Adafruit Technologies, NY, USA), and digital air temperature thermometer which measure CO2 mixing ratios (ppm), geolocation and speed, pressure and temperature, respectively at 1-second intervals. With the deployment of our sensor technology, we will determine if such a semi-autonomous mobile approach to monitoring CO2 in cities can determine excess urban CO2 mixing ratios (i.e. the 'urban CO2 dome') when compared to values measured at a fixed, remote background site. We present results from a pilot study in Vancouver, BC, where the a network of our new sensors was deployed both in fixed network and in a mobile campaign and examine the spatial biases of the two methods.

  14. Gender differences in working memory networks: a BrainMap meta-analysis.

    Science.gov (United States)

    Hill, Ashley C; Laird, Angela R; Robinson, Jennifer L

    2014-10-01

    Gender differences in psychological processes have been of great interest in a variety of fields. While the majority of research in this area has focused on specific differences in relation to test performance, this study sought to determine the underlying neurofunctional differences observed during working memory, a pivotal cognitive process shown to be predictive of academic achievement and intelligence. Using the BrainMap database, we performed a meta-analysis and applied activation likelihood estimation to our search set. Our results demonstrate consistent working memory networks across genders, but also provide evidence for gender-specific networks whereby females consistently activate more limbic (e.g., amygdala and hippocampus) and prefrontal structures (e.g., right inferior frontal gyrus), and males activate a distributed network inclusive of more parietal regions. These data provide a framework for future investigations using functional or effective connectivity methods to elucidate the underpinnings of gender differences in neural network recruitment during working memory tasks. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Isoseismal map of the 2015 Nepal earthquake and its relationships with ground-motion parameters, distance and magnitude

    Science.gov (United States)

    Prajapati, Sanjay K.; Dadhich, Harendra K.; Chopra, Sumer

    2017-01-01

    A devastating earthquake of Mw 7.8 struck central Nepal on 25th April, 2015 (6:11:25 UT) which resulted in more than ∼9000 deaths, and destroyed millions of houses. Standing buildings, roads and electrical installations worth 25-30 billions of dollars are reduced to rubbles. The earthquake was widely felt in the northern parts of India and moderate damage have been observed in the northern part of UP and Bihar region of India. Maximum intensity IX, according to the USGS report, was observed in the meizoseismal zone, surrounding the Kathmandu region. In the present study, we have compiled available information from the print, electronic media and various reports of damages and other effects caused by the event, and interpreted them to obtain Modified Mercalli Intensities (MMI) at over 175 locations spread over Nepal and surrounding Indian and Tibet region. We have also obtained a number of strong motion recordings from India and Nepal seismic network and developed an empirical relationship between the MMI and peak ground acceleration (PGA), peak ground velocity (PGV). We have used least square regression technique to derive the empirical relation between the MMI and ground motion parameters and compared them with the empirical relationships available for other regions of the world. Further, seismic intensity information available for historical earthquakes, which have occurred in the Nepal Himalaya along with the present intensity data has been utilized for developing an attenuation relationship for the studied region using two step regression analyses. The derived attenuation relationship is useful for assessing damage of a potential future large earthquake (earthquake scenario-based planning purposes) in the region.

  16. Map as a Service: A Framework for Visualising and Maximising Information Return from Multi-ModalWireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mohammad Hammoudeh

    2015-09-01

    Full Text Available This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service.

  17. A compendium of inborn errors of metabolism mapped onto the human metabolic network.

    Science.gov (United States)

    Sahoo, Swagatika; Franzson, Leifur; Jonsson, Jon J; Thiele, Ines

    2012-10-01

    Inborn errors of metabolism (IEMs) are hereditary metabolic defects, which are encountered in almost all major metabolic pathways occurring in man. Many IEMs are screened for in neonates through metabolomic analysis of dried blood spot samples. To enable the mapping of these metabolomic data onto the published human metabolic reconstruction, we added missing reactions and pathways involved in acylcarnitine (AC) and fatty acid oxidation (FAO) metabolism. Using literary data, we reconstructed an AC/FAO module consisting of 352 reactions and 139 metabolites. When this module was combined with the human metabolic reconstruction, the synthesis of 39 acylcarnitines and 22 amino acids, which are routinely measured, was captured and 235 distinct IEMs could be mapped. We collected phenotypic and clinical features for each IEM enabling comprehensive classification. We found that carbohydrate, amino acid, and lipid metabolism were most affected by the IEMs, while the brain was the most commonly affected organ. Furthermore, we analyzed the IEMs in the context of metabolic network topology to gain insight into common features between metabolically connected IEMs. While many known examples were identified, we discovered some surprising IEM pairs that shared reactions as well as clinical features but not necessarily causal genes. Moreover, we could also re-confirm that acetyl-CoA acts as a central metabolite. This network based analysis leads to further insight of hot spots in human metabolism with respect to IEMs. The presented comprehensive knowledge base of IEMs will provide a valuable tool in studying metabolic changes involved in inherited metabolic diseases.

  18. Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

    Science.gov (United States)

    Inoue, Kentaro; Shimozono, Shinichi; Yoshida, Hideaki; Kurata, Hiroyuki

    2012-01-01

    For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

  19. Development of the Social Network-Based Intervention "Powerful Together with Diabetes" Using Intervention Mapping.

    Science.gov (United States)

    Vissenberg, Charlotte; Nierkens, Vera; Uitewaal, Paul J M; Middelkoop, Barend J C; Nijpels, Giel; Stronks, Karien

    2017-01-01

    This article describes the development of the social network-based intervention Powerful Together with Diabetes which aims to improve diabetes self-management (DSM) among patients with type 2 diabetes living in socioeconomically deprived neighborhoods by stimulating social support for DSM and diminishing social influences hindering DSM (e.g., peer pressure and social norms). The intervention was specifically developed for patients with Dutch, Turkish, Moroccan, and Surinamese backgrounds. The intervention was developed according to Intervention Mapping. This article describes the first four steps of Intervention Mapping: (1) the needs assessment; (2) development of performance and change objectives; (3) selection of theory-based methods and strategies; and (4) the translation of these into an organized program. These four steps resulted in Powerful Together with Diabetes, a 10-month group-based intervention consisting of 24 meetings, 6 meetings for significant others, and 2 meetings for participants and their spouses. The IM method resulted in a tailored approach with a specific focus on the social networks of its participants. This article concludes that the IM method helped our planning team to tailor the intervention to the needs of our target population and facilitated our evaluation design. However, in hindsight, the intervention could have been improved by investing more in participatory planning and community involvement.

  20. Minimum Map of Social Institutional Network: a multidimensional strategy for research in Nursing.

    Science.gov (United States)

    Carlos, Diene Monique; Pádua, Elisabete Matallo Marchesini de; Nakano, Ana Márcia Spanó; Ferriani, Maria das Graças Carvalho

    2016-06-01

    To analyze the use of methodological strategies in qualitative research - Minimum Maps of Social Institutional Network, as proposed to understand the phenomena in the multidimensional perspective. Methodological theoretical essay in which we aimed to reflect on the use of innovative methodological strategies in nursing research, supported in Complex Paradigm fundamentals. The minimum map of Social Institutional External Network aims to identify institutional linkages and gaps for the intervention work of the surveyed institutions. The use of these maps provided important advances in know-how qualitative research in Health and Nursing. In this perspective, the use of minimum Social Intitutional Network maps can be stimulated and enhanced to meet the current demands of the contemporary world, particularly for its flexibility in adapting to various research subjects; breadth and depth of discussion; and possibilities with health services. Analisar o uso de estratégias metodológicas em pesquisas qualitativas - Mapa mínimo da Rede Social Institucional, como proposta para compreender os fenômenos na perspectiva multidimensional. Ensaio teórico metodológico em que buscou-se refletir sobre o uso de estratégias metodológicas inovadoras de pesquisa na enfermagem, sustentada nos fundamentos do Pensamento Complexo. O mapa mínimo da Rede Social Institucional Externa tem o objetivo de identificar os vínculos institucionais e lacunas para o trabalho de intervenção das instituições pesquisadas. O uso destes mapas proporcionou avanços importantes no saber-fazer pesquisa qualitativa em Saúde e Enfermagem. Nessa perspectiva, o uso de mapas mínimos da Rede Social Institucional pode ser estimulado e potencializado para responder às atuais demandas da contemporaneidade, em especial pela sua flexibilidade na adequação a diversos objetos de pesquisa; amplitude e profundidade de discussão; e possibilidades de articulação com a prática dos serviços.

  1. Applications of Hybrid Algorithm (Successive Over Relaxation and Inverse Distance Weighting) for Interpolating Rainfall Data Obtained from a Dense Network of Meteorological Stations in Metro Manila, Philippines

    Science.gov (United States)

    Yao, J. G.; Lagrosas, N.; Ampil, L. J. Y.; Lorenzo, G. R. H.; Simpas, J.

    2016-12-01

    A hybrid piecewise rainfall value interpolation algorithm was formulated using the commonly known Inverse Distance Weighting (IDW) and Gauss-Seidel variant Successive Over Relaxation (SOR) to interpolate rainfall values over Metro Manila, Philippines. Due to the fact that the SOR requires boundary values for its algorithm to work, the IDW method has been used to estimate rainfall values at the boundary. Iterations using SOR were then done on the defined boundaries to obtain the desired results corresponding to the lowest RMSE value. The hybrid method was applied to rainfall datasets obtained from a dense network of 30 stations in Metro Manila which has been collecting meteorological data every 5 minutes since 2012. Implementing the Davis Vantage Pro 2 Plus weather monitoring system, each station sends data to a central server which could be accessed through the website metroweather.com.ph. The stations are spread over approximately 625 sq km of area such that each station is approximately within 25 sq km from each other. The locations of the stations determined by the Metro Manila Development Authority (MMDA) are in critical sections of Metro Manila such as watersheds and flood-prone areas. Three cases have been investigated in this study, one for each type of rainfall present in Metro Manila: monsoon-induced (8/20/13), typhoon (6/29/13), and thunderstorm (7/3/15 & 7/4/15). The area where the rainfall stations are located is divided such that large measured rainfall values are used as part of the boundaries for the SOR. Measured station values found inside the area where SOR is implemented are compared with results from interpolated values. Root mean square error (RMSE) and correlation trends between measured and interpolated results are quantified. Results from typhoon, thunderstorm and monsoon cases show RMSE values ranged from 0.25 to 2.46 mm for typhoons, 1.55 to 10.69 mm for monsoon-induced rain and 0.01 to 6.27 mm for thunderstorms. R2 values, on the other

  2. Digital Mapping of Soil Texture Using Regression Tree and Artificial Neural Network in Bijar, Kurdistan

    Directory of Open Access Journals (Sweden)

    kamal nabiollahi

    2015-06-01

    Full Text Available Soil texture is an important soil physical property that governs most physical, chemical, biological, and hydrological processes in soils. Detailed information on soil texture variability is crucial for proper crop and land management and environmental studies. Therefore, at present research, 103 soil profiles were dogged and then sampled in order to prepare digital map of soil texture in Bijar, Kurdistan. Auxiliary data used in this study to represent predictive soil forming factors were terrain attributes, Landsat 7 ETM+ data and a geomorphologic surfaces map. To make a relationship between the soil data set (i.e. Clay, sand and silt and auxiliary data, regression tree (RT and artificial neural network (ANN were applied. Results showed that the RT had the higher accuracy than ANN for spatial prediction of three parameters. For the clay fraction, determination of coefficient (R2 and root mean square root (RMSE calculated for two models were 0.46, 0.81 and 17.10, 12.50, based on validation data set (20%. Our results showed some auxiliary variables had more influence on predictive soil class model which included: geomorphology map, wetness index, multi-resolution index of valley bottom flatness, elevation, slope length, and B3. In general, results showed that decision tree models had higher accuracy than ANN models and also their results are more convenient for interpretation. Therefore, it is suggested using of decision tree models for spatial prediction of soil properties in future studies.

  3. Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network

    Science.gov (United States)

    Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong

    2016-02-01

    We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods.

  4. Mapping regional forest fire probability using artificial neural network model in a Mediterranean forest ecosystem

    Directory of Open Access Journals (Sweden)

    Onur Satir

    2016-09-01

    Full Text Available Forest fires are one of the most important factors in environmental risk assessment and it is the main cause of forest destruction in the Mediterranean region. Forestlands have a number of known benefits such as decreasing soil erosion, containing wild life habitats, etc. Additionally, forests are also important player in carbon cycle and decreasing the climate change impacts. This paper discusses forest fire probability mapping of a Mediterranean forestland using a multiple data assessment technique. An artificial neural network (ANN method was used to map forest fire probability in Upper Seyhan Basin (USB in Turkey. Multi-layer perceptron (MLP approach based on back propagation algorithm was applied in respect to physical, anthropogenic, climate and fire occurrence datasets. Result was validated using relative operating characteristic (ROC analysis. Coefficient of accuracy of the MLP was 0.83. Landscape features input to the model were assessed statistically to identify the most descriptive factors on forest fire probability mapping using the Pearson correlation coefficient. Landscape features like elevation (R = −0.43, tree cover (R = 0.93 and temperature (R = 0.42 were strongly correlated with forest fire probability in the USB region.

  5. Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors

    Directory of Open Access Journals (Sweden)

    Arturo Gil

    2010-05-01

    Full Text Available In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.

  6. Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network.

    Science.gov (United States)

    Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong

    2016-02-11

    We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods.

  7. Three Years of Country-Wide Rainfall Maps from Cellular Communication Networks

    Science.gov (United States)

    Overeem, Aart; Rios Gaona, Manuel Felipe; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular communication networks may be used for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. This is particularly interesting for those countries where few surface rainfall observations are available. A data set from a commercial microwave link network over the Netherlands is analyzed. The data set runs from January 2011 - January 2014 and consists of roughly 2,000 links covering the land surface of the Netherlands (35,500 square kilometers). From this 3-year data set country-wide rainfall maps are retrieved, which are compared to a gauge-adjusted radar data set. The ability of cellular communication networks to estimate rainfall is studied for different temporal and spatial scales (including the catchment scale). To summarize, the results further confirm the potential of these networks for rainfall monitoring for hydrological applications.

  8. Distance Learning

    National Research Council Canada - National Science Library

    Braddock, Joseph

    1997-01-01

    A study reviewing the existing Army Distance Learning Plan (ADLP) and current Distance Learning practices, with a focus on the Army's training and educational challenges and the benefits of applying Distance Learning techniques...

  9. Short term forecasting for HFSWR sea surface current mapping using artificial neural network

    Science.gov (United States)

    Lai, J. W.; Lu, Y. C.; Hsieh, C. M.; Liau, J. M.; Yang, W. C.

    2016-02-01

    Taiwan Ocean Research Institute (TORI) established the Taiwan Ocean Radar Observing System (TOROS) based on the CODAR high frequency surface wave radar (HFSWR). The TOROS is the first network having complete, contiguous HFSWR coverage of nation's coastline in the world. This network consisting of 17 SeaSonde radars offers coverage across approximately 190,000 square kilometers an area, over five times the size of Taiwan's entire land mass. In the southernmost and narrowest part of Taiwan, two 13 MHz and one 24 MHz radars were established along the NanWan Bay since June, 2014. NanWan Bay, the southern tip of Taiwan, is a southward semi-enclosed basin bounded by two capes and is open to the Luzon Strait. The distance between the two caps is around 12 km, and the distance from the northernmost point of the bay to the caps are 5 and 11 km, respectively. Strong tidal currents dominate the ocean circulation in the NanWan Bay and induce obvious upwelling of cold water that intrudes on to the shallow regions of NanWan Bay around spring tides. From late fall to early spring, the seaward wind dominated by the northeast monsoon often destratifies the water column and decreases the sea surface temperature inside the Bay (Lee et al, 1997). Furthermore, the Nanwan Bay is famous with well-developed fringing reefs distributed along the shoreline. In this area, 230 species of scleractinian corals, nine species of non-scleractinian reef-building corals, and 40 species of alcyonacean corals have been recorded (Dai, 1991). NanWan, in the shape of a beautiful arch, attracts large crowds of people to take all kinds of beach or water activities every summer. In order to improve the applicability of HFSWR ocean surface current data on search and rescue issue and evaluation of coral spawn dispersal, a short term forecasting model using artificial neural network (ANN) was developed in this study. That ocean surface current vectors obtained from tidal theory are added as inputs in artificial

  10. Assessment of predictive ability of artificial neural networks using holographic mapping.

    Science.gov (United States)

    Tompos, András; Végvári, Lajos; Tfirst, Ernö; Margitfalvi, József L

    2007-02-01

    In this study, artificial neural networks (ANNs) were used to reveal a quantitative relationship between catalytic composition and catalytic activity. This relationship was predefined using a hypothetical experimental space described by a multidimensional polynomial. The predictive ability of ANNs was investigated, i.e. an attempt was done to evaluate how ANNs can envisage a given hypothetical experimental space. Data sets for training, validation and testing of ANNs were obtained from the hypothetical experimental space using two different ways of sampling. Data were selected, (i) by means of our optimization algorithm called Holographic Research Strategy (HRS); and (ii) randomly. In order to model real experimentation, data were also generated with error. The relationship between the complexity of different network topologies and their predictive ability was investigated. It was shown that when data used for training have been perturbed with a given level of noise, less complex network architectures give acceptable accuracy. Additionally, estimated experimental spaces were visualized in a 2D layout by means of Holographic Mappings (HMs). Analysis of HMs revealed that ANNs trained by data sets obtained upon an optimization procedure provides better description of the experimental space in the vicinity of the optimum than ANNs trained by randomly selected data sets. This fact indicates again the importance of the optimization in combinatorial catalyst library design.

  11. Broad integration of expression maps and co-expression networks compassing novel gene functions in the brain.

    Science.gov (United States)

    Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

    2014-11-10

    Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas.

  12. Big Data: A Parallel Particle Swarm Optimization-Back-Propagation Neural Network Algorithm Based on MapReduce.

    Science.gov (United States)

    Cao, Jianfang; Cui, Hongyan; Shi, Hao; Jiao, Lijuan

    2016-01-01

    A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To improve the classification accuracy and runtime efficiency of the BP neural network algorithm, we proposed a parallel design and realization method for a particle swarm optimization (PSO)-optimized BP neural network based on MapReduce on the Hadoop platform using both the PSO algorithm and a parallel design. The PSO algorithm was used to optimize the BP neural network's initial weights and thresholds and improve the accuracy of the classification algorithm. The MapReduce parallel programming model was utilized to achieve parallel processing of the BP algorithm, thereby solving the problems of hardware and communication overhead when the BP neural network addresses big data. Datasets on 5 different scales were constructed using the scene image library from the SUN Database. The classification accuracy of the parallel PSO-BP neural network algorithm is approximately 92%, and the system efficiency is approximately 0.85, which presents obvious advantages when processing big data. The algorithm proposed in this study demonstrated both higher classification accuracy and improved time efficiency, which represents a significant improvement obtained from applying parallel processing to an intelligent algorithm on big data.

  13. Outcomes of Interorganizational Networks in Canada for Chronic Disease Prevention: Insights From a Concept Mapping Study, 2015

    Science.gov (United States)

    Kernoghan, Alison; Riley, Barbara; Popp, Janice; Best, Allan; Milward, H. Brinton

    2015-01-01

    Introduction We conducted a mixed methods study from June 2014 to March 2015 to assess the perspectives of stakeholders in networks that adopt a population approach for chronic disease prevention (CDP). The purpose of the study was to identify important and feasible outcome measures for monitoring network performance. Methods Participants from CDP networks in Canada completed an online concept mapping exercise, which was followed by interviews with network stakeholders to further understand the findings. Results Nine concepts were considered important outcomes of CDP networks: enhanced learning, improved use of resources, enhanced or increased relationships, improved collaborative action, network cohesion, improved system outcomes, improved population health outcomes, improved practice and policy planning, and improved intersectoral engagement. Three themes emerged from participant interviews related to measurement of the identified concepts: the methodological difficulties in measuring network outcomes, the dynamic nature of network evolution and function and implications for outcome assessment, and the challenge of measuring multisectoral engagement in CDP networks. Conclusion Results from this study provide initial insights into concepts that can be used to describe the outcomes of networks for CDP and may offer foundations for strengthening network outcome-monitoring strategies and methodologies. PMID:26583571

  14. Digital Topographic Mapping in Urban Obstructed Environment Based on Multi-GNSS Network RTK Technology

    Science.gov (United States)

    Guo, Qiuying; Zhao, Tonglong; Zhang, Chao; Wu, Xuxiang

    2017-10-01

    Digital topographic mapping experiments were carried out based on network RTK technology using GPS/BEIDOU/GLONASS multi-constellation compatible GNSS receivers in urban obstructed environment. Operation scheme and technique flow were discussed. Experimental results show that the horizontal position and elevation of the points measured by RTK can reach 2cm and 3cm precision level respectively in open environment. RTK initialization time needs about 3-5s. While in obstructed environment, such as high building and tree shanding, the RTK initialization time needs about dozens of seconds or tens of seconds, and sometimes floating solutions or even differential solutions were obtained. The impact of dense and tall building on RTK measurement is more seriously. It is more likely to get RTK fixed solution in the south side of high building than the north side of the building.

  15. Exploring the Use of MXit: A Cell-Phone Social Network to Facilitate Learning in Distance Education

    Science.gov (United States)

    Makoe, Mpine

    2010-01-01

    The aim of this paper is to investigate the pedagogical suitability of using cell phones to enhance learning through social interaction in distance education. Social interaction was used as a conceptual framework to explore the potential for using "MXit"--a cell-phone instant messaging system--to support and enhance learning for distance…

  16. On the relationship between travel time and travel distance of commuters. Reported versus network travel data in the Netherlands

    NARCIS (Netherlands)

    Rietveld, P.; Zwart, B.; van Wee, B.; van Hoorn, T.

    1999-01-01

    This paper gives a detailed empirical analysis of the relationships between different indicators of costs of commuting trips by car: difference as the crow flies, shortest travel time according to route planner, corresponding travel distance, and reported travel time. Reported travel times are

  17. Spatial interpolation and radiological mapping of ambient gamma dose rate by using artificial neural networks and fuzzy logic methods.

    Science.gov (United States)

    Yeşilkanat, Cafer Mert; Kobya, Yaşar; Taşkın, Halim; Çevik, Uğur

    2017-09-01

    The aim of this study was to determine spatial risk dispersion of ambient gamma dose rate (AGDR) by using both artificial neural network (ANN) and fuzzy logic (FL) methods, compare the performances of methods, make dose estimations for intermediate stations with no previous measurements and create dose rate risk maps of the study area. In order to determine the dose distribution by using artificial neural networks, two main networks and five different network structures were used; feed forward ANN; Multi-layer perceptron (MLP), Radial basis functional neural network (RBFNN), Quantile regression neural network (QRNN) and recurrent ANN; Jordan networks (JN), Elman networks (EN). In the evaluation of estimation performance obtained for the test data, all models appear to give similar results. According to the cross-validation results obtained for explaining AGDR distribution, Pearson's r coefficients were calculated as 0.94, 0.91, 0.89, 0.91, 0.91 and 0.92 and RMSE values were calculated as 34.78, 43.28, 63.92, 44.86, 46.77 and 37.92 for MLP, RBFNN, QRNN, JN, EN and FL, respectively. In addition, spatial risk maps showing distributions of AGDR of the study area were created by all models and results were compared with geological, topological and soil structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. The Annotation, Mapping, Expression and Network (AMEN suite of tools for molecular systems biology

    Directory of Open Access Journals (Sweden)

    Primig Michael

    2008-02-01

    Full Text Available Abstract Background High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently. Results We developed the Annotation, Mapping, Expression and Network (AMEN software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i uploading and pre-processing data from microarray expression profiling experiments, (ii detecting groups of significantly co-expressed genes, and (iii searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human. Conclusion AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.

  19. The value of the participatory network mapping tool to facilitate and evaluate coordinated action in health promotion networks: two Dutch case studies.

    Science.gov (United States)

    Wijenberg, Evianne; Wagemakers, Annemarie; Herens, Marion; Hartog, Franciska den; Koelen, Maria

    2017-08-01

    Facilitating processes for coordinated action in the field of health promotion is a challenge. Poorthuis and Bijl's (2006) Participatory Network Mapping Tool (PNMT) uses visualization and discussion to map the positions and roles of network actors, stimulate learning processes, and elicit actionable knowledge. This article describes the results from the application of the PNMT in networks of two Dutch health promotion programmes (Health Race and BeweegKuur) with the aim of determining the value of the PNMT to partners in health promotions networks. A qualitative secondary analysis (QSA) was conducted to clarify positions and roles, learning processes, and actionable knowledge of network actors in existing data sets including five group interviews of the Health Race programme and 16 individual interviews and 15 group interviews of the BeweegKuur programme. The PNMT maps both positions and roles of (missing) actors and makes successes (e.g. knowing each other) and challenges (e.g. implementing new activities) visible. Thus, the PNMT provides a starting point for discussion and reflection and eliciting actionable knowledge such as involving new actors and target populations in the programme. The PNMT contributes to the facilitation of coordinated action in health promotion networks by making positions and roles of network partners visible. In combination with dialogue and reflection the PNMT helps to elucidate factors influencing coordinated action and outcomes. The PNMT is valuable in grasping intangible aspects between actors by stimulating collective learning. These insights can be used by researchers and network actors to achieve more successful coordinated action for health promotion.

  20. Mapping and Dynamics of Regulatory DNA and Transcription Factor Networks in A. thaliana

    Directory of Open Access Journals (Sweden)

    Alessandra M. Sullivan

    2014-09-01

    Full Text Available Our understanding of gene regulation in plants is constrained by our limited knowledge of plant cis-regulatory DNA and its dynamics. We mapped DNase I hypersensitive sites (DHSs in A. thaliana seedlings and used genomic footprinting to delineate ∼700,000 sites of in vivo transcription factor (TF occupancy at nucleotide resolution. We show that variation associated with 72 diverse quantitative phenotypes localizes within DHSs. TF footprints encode an extensive cis-regulatory lexicon subject to recent evolutionary pressures, and widespread TF binding within exons may have shaped codon usage patterns. The architecture of A. thaliana TF regulatory networks is strikingly similar to that of animals in spite of diverged regulatory repertoires. We analyzed regulatory landscape dynamics during heat shock and photomorphogenesis, disclosing thousands of environmentally sensitive elements and enabling mapping of key TF regulatory circuits underlying these fundamental responses. Our results provide an extensive resource for the study of A. thaliana gene regulation and functional biology.

  1. Navigation Behaviors Based on Fuzzy ArtMap Neural Networks for Intelligent Autonomous Vehicles

    Directory of Open Access Journals (Sweden)

    Amine Chohra

    2011-01-01

    Full Text Available The use of hybrid intelligent systems (HISs is necessary to bring the behavior of intelligent autonomous vehicles (IAVs near the human one in recognition, learning, adaptation, generalization, decision making, and action. First, the necessity of HIS and some navigation approaches based on fuzzy ArtMap neural networks (FAMNNs are discussed. Indeed, such approaches can provide IAV with more autonomy, intelligence, and real-time processing capabilities. Second, an FAMNN-based navigation approach is suggested. Indeed, this approach must provide vehicles with capability, after supervised fast stable learning: simplified fuzzy ArtMap (SFAM, to recognize both target-location and obstacle-avoidance situations using FAMNN1 and FAMNN2, respectively. Afterwards, the decision making and action consist of two association stages, carried out by reinforcement trial and error learning, and their coordination using NN3. Then, NN3 allows to decide among the five (05 actions to move towards 30∘, 60∘, 90∘, 120∘, and 150∘. Third, simulation results display the ability of the FAMNN-based approach to provide IAV with intelligent behaviors allowing to intelligently navigate in partially structured environments. Finally, a discussion, dealing with the suggested approach and how its robustness would be if implemented on real vehicle, is given.

  2. Similarity Analysis of EEG Data Based on Self Organizing Map Neural Network

    Directory of Open Access Journals (Sweden)

    Ibrahim Salem Jahan

    2014-01-01

    Full Text Available The Electroencephalography (EEG is the recording of electrical activity along the scalp. This recorded data are very complex. EEG has a big role in several applications such as in the diagnosis of human brain diseases and epilepsy. Also, we can use the EEG signals to control an external device via Brain Computer Interface (BCI by our mind. There are many algorithms to analyse the recorded EEG data, but it still remains one of the big challenges in the world. In this article, we extended our previous proposed method. Our extended method uses Self-organizing Map (SOM as an EEG data classifier. The proposed method we can divide in following steps: capturing EEG raw data from the sensors, applying filters on this data, we will use the frequencies in the range from 0.5~Hz to 60~Hz, smoothing the data with 15-th order of Polynomial Curve Fitting, converting filtered data into text using Turtle Graphic, Lempel-Ziv complexity for measuring similarity between two EEG data trials and Self-Organizing Map Neural Network as a final classifiers. The experiment results show that our model is able to detect up to 96% finger movements correctly.

  3. Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks

    Directory of Open Access Journals (Sweden)

    De Momi Elena

    2006-10-01

    Full Text Available Abstract Background The design of an optimal neuroprostheses controller and its clinical use presents several challenges. First, the physiological system is characterized by highly inter-subjects varying properties and also by non stationary behaviour with time, due to conditioning level and fatigue. Secondly, the easiness to use in routine clinical practice requires experienced operators. Therefore, feedback controllers, avoiding long setting procedures, are required. Methods The error mapping controller (EMC here proposed uses artificial neural networks (ANNs both for the design of an inverse model and of a feedback controller. A neuromuscular model is used to validate the performance of the controllers in simulations. The EMC performance is compared to a Proportional Integral Derivative (PID included in an anti wind-up scheme (called PIDAW and to a controller with an ANN as inverse model and a PID in the feedback loop (NEUROPID. In addition tests on the EMC robustness in response to variations of the Plant parameters and to mechanical disturbances are carried out. Results The EMC shows improvements with respect to the other controllers in tracking accuracy, capability to prolong exercise managing fatigue, robustness to parameter variations and resistance to mechanical disturbances. Conclusion Different from the other controllers, the EMC is capable of balancing between tracking accuracy and mapping of fatigue during the exercise. In this way, it avoids overstressing muscles and allows a considerable prolongation of the movement. The collection of the training sets does not require any particular experimental setting and can be introduced in routine clinical practice.

  4. Oxygen extraction fraction mapping at 3 Tesla using an artificial neural network: A feasibility study.

    Science.gov (United States)

    Domsch, Sebastian; Mürle, Bettina; Weingärtner, Sebastian; Zapp, Jascha; Wenz, Frederik; Schad, Lothar R

    2018-02-01

    The oxygen extraction fraction (OEF) is an important biomarker for tissue-viability. MRI enables noninvasive estimation of the OEF based on the blood-oxygenation-level-dependent (BOLD) effect. Quantitative OEF-mapping is commonly applied using least-squares regression (LSR) to an analytical tissue model. However, the LSR method has not yet become clinically established due to the necessity for long acquisition times. Artificial neural networks (ANNs) recently have received increasing interest for robust curve-fitting and might pose an alternative to the conventional LSR method for reduced acquisition times. This study presents in vivo OEF mapping results using the conventional LSR and the proposed ANN method. In vivo data of five healthy volunteers and one patient with a primary brain tumor were acquired at 3T using a gradient-echo sampled spin-echo (GESSE) sequence. The ANN was trained with simulated BOLD data. In healthy subjects, the mean OEF was 36 ± 2% (LSR) and 40 ± 1% (ANN). The OEF variance within subjects was reduced from 8% to 6% using the ANN method. In the patient, both methods revealed a distinct OEF hotspot in the tumor area, whereas ANN showed less apparent artifacts in surrounding tissue. In clinical scan times, the ANN analysis enables OEF mapping with reduced variance, which could facilitate its integration into clinical protocols. Magn Reson Med 79:890-899, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  5. Atlas of Cancer Signalling Network: a systems biology resource for integrative analysis of cancer data with Google Maps.

    Science.gov (United States)

    Kuperstein, I; Bonnet, E; Nguyen, H-A; Cohen, D; Viara, E; Grieco, L; Fourquet, S; Calzone, L; Russo, C; Kondratova, M; Dutreix, M; Barillot, E; Zinovyev, A

    2015-07-20

    Cancerogenesis is driven by mutations leading to aberrant functioning of a complex network of molecular interactions and simultaneously affecting multiple cellular functions. Therefore, the successful application of bioinformatics and systems biology methods for analysis of high-throughput data in cancer research heavily depends on availability of global and detailed reconstructions of signalling networks amenable for computational analysis. We present here the Atlas of Cancer Signalling Network (ACSN), an interactive and comprehensive map of molecular mechanisms implicated in cancer. The resource includes tools for map navigation, visualization and analysis of molecular data in the context of signalling network maps. Constructing and updating ACSN involves careful manual curation of molecular biology literature and participation of experts in the corresponding fields. The cancer-oriented content of ACSN is completely original and covers major mechanisms involved in cancer progression, including DNA repair, cell survival, apoptosis, cell cycle, EMT and cell motility. Cell signalling mechanisms are depicted in detail, together creating a seamless 'geographic-like' map of molecular interactions frequently deregulated in cancer. The map is browsable using NaviCell web interface using the Google Maps engine and semantic zooming principle. The associated web-blog provides a forum for commenting and curating the ACSN content. ACSN allows uploading heterogeneous omics data from users on top of the maps for visualization and performing functional analyses. We suggest several scenarios for ACSN application in cancer research, particularly for visualizing high-throughput data, starting from small interfering RNA-based screening results or mutation frequencies to innovative ways of exploring transcriptomes and phosphoproteomes. Integration and analysis of these data in the context of ACSN may help interpret their biological significance and formulate mechanistic hypotheses

  6. Numerical distance protection

    CERN Document Server

    Ziegler, Gerhard

    2011-01-01

    Distance protection provides the basis for network protection in transmission systems and meshed distribution systems. This book covers the fundamentals of distance protection and the special features of numerical technology. The emphasis is placed on the application of numerical distance relays in distribution and transmission systems.This book is aimed at students and engineers who wish to familiarise themselves with the subject of power system protection, as well as the experienced user, entering the area of numerical distance protection. Furthermore it serves as a reference guide for s

  7. Mnemonic networks in the hippocampal formation: from spatial maps to temporal and conceptual codes.

    Science.gov (United States)

    Milivojevic, Branka; Doeller, Christian F

    2013-11-01

    The hippocampal formation has been associated with a wide variety of functions including spatial navigation and planning, memory encoding and retrieval, relational processing, novelty detection, and imagination. These functions are dissimilar in terms of their behavioral consequences and modality of representation. Consequently, theoretical standpoints have focused on explaining the role of the hippocampal formation in terms of either its spatial or nonspatial functions. Contrary to this dichotomy, we propose that it is essential to look beyond these traditional boundaries between mnemonic and spatial functions and focus instead on the processes that these functions have in common. In this framework, we use electrophysiology data from the spatial domain to predict effects on the systems level, both in spatial and nonspatial domains. We initially outline the results of studies that have used findings from spatial navigation in rodents to predict the patterns of brain activity observable in people who are exploring virtual environments. We discuss how certain properties of space-defining neurons enable space to be represented as a mental map of interconnected locations, which are expressed at multiple spatial scales in separate modules in the hippocampal formation. We then suggest that memories are also organized in networks, characterized by mnemonic and temporal hierarchies. We finish by discussing how virtual-reality techniques can be used to create novel lifelike episodes allowing us to look at episodic memory processes while multivariate analysis tools can be used to explore the organizational structure of mnemonic networks. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  8. Untangling perceptual memory: hysteresis and adaptation map into separate cortical networks.

    Science.gov (United States)

    Schwiedrzik, Caspar M; Ruff, Christian C; Lazar, Andreea; Leitner, Frauke C; Singer, Wolf; Melloni, Lucia

    2014-05-01

    Perception is an active inferential process in which prior knowledge is combined with sensory input, the result of which determines the contents of awareness. Accordingly, previous experience is known to help the brain "decide" what to perceive. However, a critical aspect that has not been addressed is that previous experience can exert 2 opposing effects on perception: An attractive effect, sensitizing the brain to perceive the same again (hysteresis), or a repulsive effect, making it more likely to perceive something else (adaptation). We used functional magnetic resonance imaging and modeling to elucidate how the brain entertains these 2 opposing processes, and what determines the direction of such experience-dependent perceptual effects. We found that although affecting our perception concurrently, hysteresis and adaptation map into distinct cortical networks: a widespread network of higher-order visual and fronto-parietal areas was involved in perceptual stabilization, while adaptation was confined to early visual areas. This areal and hierarchical segregation may explain how the brain maintains the balance between exploiting redundancies and staying sensitive to new information. We provide a Bayesian model that accounts for the coexistence of hysteresis and adaptation by separating their causes into 2 distinct terms: Hysteresis alters the prior, whereas adaptation changes the sensory evidence (the likelihood function).

  9. Aberrant emotion networks in early major depressive disorder patients: an eigenvector centrality mapping study.

    Science.gov (United States)

    Song, Z; Zhang, M; Huang, P

    2016-05-24

    Major depressive disorder (MDD) is a serious mental disorder that negatively affects the quality of life of many individuals, and is a heavy economic burden to society. In recent years it was thought that depression is a 'disconnection syndrome'. Disorganized brain activity and un-modulated emotion responses were considered the key neuropathologies underlying depression. In the present study, we investigated the alteration of whole brain network connectivity in 28 first-episode, drug-naive patients, using resting-state functional magnetic resonance imaging and a new analytical method called voxel-based eigenvector centrality mapping. We found that compared with normal controls, MDD patients had lower functional connectivity in the bilateral middle frontal gyrus, insula, hippocampus, amygdala and cerebellum, and higher functional connectivity in the medial prefrontal cortex. The functional connectivity strength at the right hippocampus (r=-0.413, P=0.032) and the right insula (r=-0.372, P=0.041) negatively correlated with the severity of the disease. We further examined coordination among these regions, and found that frontal-subcortical connection was reduced and insula-medial prefrontal cortex (mPFC) connection was increased. These results are consistent with previous hypotheses on the neural mechanism of MDD, and provide further evidence that emotion networks are already interrupted in early stages of depression.

  10. Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network

    Directory of Open Access Journals (Sweden)

    Mutasem Sh. Alkhasawneh

    2013-01-01

    Full Text Available Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.

  11. Building disease-specific drug-protein connectivity maps from molecular interaction networks and PubMed abstracts.

    Directory of Open Access Journals (Sweden)

    Jiao Li

    2009-07-01

    Full Text Available The recently proposed concept of molecular connectivity maps enables researchers to integrate experimental measurements of genes, proteins, metabolites, and drug compounds under similar biological conditions. The study of these maps provides opportunities for future toxicogenomics and drug discovery applications. We developed a computational framework to build disease-specific drug-protein connectivity maps. We integrated gene/protein and drug connectivity information based on protein interaction networks and literature mining, without requiring gene expression profile information derived from drug perturbation experiments on disease samples. We described the development and application of this computational framework using Alzheimer's Disease (AD as a primary example in three steps. First, molecular interaction networks were incorporated to reduce bias and improve relevance of AD seed proteins. Second, PubMed abstracts were used to retrieve enriched drug terms that are indirectly associated with AD through molecular mechanistic studies. Third and lastly, a comprehensive AD connectivity map was created by relating enriched drugs and related proteins in literature. We showed that this molecular connectivity map development approach outperformed both curated drug target databases and conventional information retrieval systems. Our initial explorations of the AD connectivity map yielded a new hypothesis that diltiazem and quinidine may be investigated as candidate drugs for AD treatment. Molecular connectivity maps derived computationally can help study molecular signature differences between different classes of drugs in specific disease contexts. To achieve overall good data coverage and quality, a series of statistical methods have been developed to overcome high levels of data noise in biological networks and literature mining results. Further development of computational molecular connectivity maps to cover major disease areas will likely set

  12. Risk and Resilience Analysis of Complex Network Systems Considering Cascading Failure and Recovery Strategy Based on Coupled Map Lattices

    OpenAIRE

    Fuchun Ren; Tingdi Zhao; Hongli Wang

    2015-01-01

    Risk and resilience are important and challenging issues in complex network systems since a single failure may trigger a whole collapse of the systems due to cascading effect. New theories, models, and methods are urgently demanded to deal with this challenge. In this paper, a coupled map lattices (CML) based approach is adopted to analyze the risk of cascading process in Watts-Strogatz (WS) small-world network and Barabási and Albert (BA) scale-free network, respectively. Then, to achieve an...

  13. Path integration and cognitive mapping in a continuous attractor neural network model.

    Science.gov (United States)

    Samsonovich, A; McNaughton, B L

    1997-08-01

    A minimal synaptic architecture is proposed for how the brain might perform path integration by computing the next internal representation of self-location from the current representation and from the perceived velocity of motion. In the model, a place-cell assembly called a "chart" contains a two-dimensional attractor set called an "attractor map" that can be used to represent coordinates in any arbitrary environment, once associative binding has occurred between chart locations and sensory inputs. In hippocampus, there are different spatial relations among place fields in different environments and behavioral contexts. Thus, the same units may participate in many charts, and it is shown that the number of uncorrelated charts that can be encoded in the same recurrent network is potentially quite large. According to this theory, the firing of a given place cell is primarily a cooperative effect of the activity of its neighbors on the currently active chart. Therefore, it is not particularly useful to think of place cells as encoding any particular external object or event. Because of its recurrent connections, hippocampal field CA3 is proposed as a possible location for this "multichart" architecture; however, other implementations in anatomy would not invalidate the main concepts. The model is implemented numerically both as a network of integrate-and-fire units and as a "macroscopic" (with respect to the space of states) description of the system, based on a continuous approximation defined by a system of stochastic differential equations. It provides an explanation for a number of hitherto perplexing observations on hippocampal place fields, including doubling, vanishing, reshaping in distorted environments, acquiring directionality in a two-goal shuttling task, rapid formation in a novel environment, and slow rotation after disorientation. The model makes several new predictions about the expected properties of hippocampal place cells and other cells of the

  14. Bottle-neck type of neural network as a mapping device towards food specifications.

    Science.gov (United States)

    Novic, Marjana; Groselj, Neva

    2009-09-01

    A novel methodology is proposed for food specifications associated with the origin of food. The methodology was tested on honey samples collected within the TRACE EU project. The data were sampled in various regions in Europe and analysed for the trace elements content. The sampling sites were characterized by different geological origins, such as limestone, shale, or magmatic. We have chosen 14 elements, B, Na, Mg, A, K, Ca, Mn, Co, Ni, Cu, Zn, Rb, Sr, and Ba, due to their influence on the separation of samples regarding the geology of the sampling sites. A special architecture of an error back-propagation neural network, so called bottle-neck type of neural network was used to project the data into a 2D plane. The data were fed into the 14-nodes input layer and then transferred through the 2-nodes hidden layer (compared to a bottle-neck) to the 14-nodes output layer. The two hidden nodes representing the two coordinates of the projection plane enable us to map the samples used for training of the bottle-neck network. With the knowledge about the classes of individual samples we determine the clusters in the projection plane and consequently obtain the coordinates of the centroid (gravity point) of a particular cluster. The clusters are characterized with an ellipse shape borders spanning the length of up to 3sigma in each dimension. Since the data were classified as regard to the geology, three main clusters were sought: (i) limestone, (ii) shale/mudstone/clay/loess, and (iii) acid-magmatic origin of honey samples. The novel methodology proposed for food specifications was demonstrated on a reduced set of samples, which shows good clustering of all three classes in the projection plane, and on the third class of the original data set.

  15. Connectivity-consistent mapping method for 2-D discrete fracture networks

    Science.gov (United States)

    Roubinet, Delphine; de Dreuzy, Jean-Raynald; Davy, Philippe

    2010-07-01

    We present a new flow computation method in 2-D discrete fracture networks (DFN) intermediary between the classical DFN flow simulation method and the projection onto continuous grids. The method divides the simulation complexity by solving for flows successively at a local mesh scale and at the global domain scale. At the local mesh scale, flows are determined by classical DFN flow simulations and approximated by an equivalent hydraulic matrix (EHM) relating heads and flow rates discretized on the mesh borders. Assembling the equivalent hydraulic matrices provides for a domain-scale discretization of the flow equation. The equivalent hydraulic matrices transfer the connectivity and flow structure complexities from the local mesh scale to the domain scale. Compared to existing geometrical mapping or equivalent tensor methods, the EHM method broadens the simulation range of flow to all types of 2-D fracture networks both below and above the representative elementary volume (REV). Additional computation linked to the derivation of the local mesh-scale equivalent hydraulic matrices increases the accuracy and reliability of the method. Compared to DFN methods, the EHM method first provides a simpler domain-scale alternative permeability model. Second, it enhances the simulation capacities to larger fracture networks where flow discretization on the DFN structure yields system sizes too large to be solved using the most advanced multigrid and multifrontal methods. We show that the EHM method continuously moves from the DFN method to the tensor representation as a function of the local mesh-scale discretization. The balance between accuracy and model simplification can be optimally controlled by adjusting the domain-scale and local mesh-scale discretizations.

  16. NetMap - Creating a Map of Application Layer QoS Metrics of Mobile Networks Using Crowd Sourcing

    DEFF Research Database (Denmark)

    Mikkelsen, Lars Møller; Thomsen, Steffen Riber; Pedersen, Michael Sølvkjær

    2014-01-01

    on crowd sourcing, that utilizes end user smart devices in automatically measuring and gathering network performance metrics on mobile networks. Metrics measured include throughput, round trip times, connectivity, and signal strength, and are accompanied by a wide range of context information about...

  17. Suggestions for planning a migration-monitoring network based on the experience of establishing and operating the maps program

    Science.gov (United States)

    David F. DeSante

    2005-01-01

    Based on the experience of creating and implementing the Monitoring Avian Productivity and Survivorship (MAPS) program, I suggest that, to be successful, a migration-monitoring network must: (1) provide strong justification for the data it proposes to collect; (2) provide direct links between those monitoring data and both research and management goals; (3) provide...

  18. Self-Organizing Neural Network Map for the Purpose of Visualizing the Concept Images of Students on Angles

    Science.gov (United States)

    Kaya, Deniz

    2017-01-01

    The purpose of the study is to perform a less-dimensional thorough visualization process for the purpose of determining the images of the students on the concept of angle. The Ward clustering analysis combined with Self-Organizing Neural Network Map (SOM) has been used for the dimension process. The Conceptual Understanding Tool, which consisted…

  19. Integrating Imaging spectrometry and Neural Networks to map tropical grass quality in the Kruger National Park, South Africa

    NARCIS (Netherlands)

    Mutanga, O.; Skidmore, A.K.

    2004-01-01

    A new integrated approach, involving continuum-removed absorption features, the red edge position and neural networks, is developed and applied to map grass nitrogen concentration in an African savanna rangeland. Nitrogen, which largely determines the nutritional quality of grasslands, is commonly

  20. 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

  1. SURFmap: A Network Monitoring Tool Based on the Google Maps API

    NARCIS (Netherlands)

    Hofstede, R.J.; Hofstede, R. J.; Fioreze, Tiago

    2009-01-01

    Network monitoring allows network managers to get a better insight in the network traffic transiting in a managed network. In order to make the tasks of a network manager easier, many network monitoring tools are made available for a wide range of purposes (e.g., traffic accounting, performance

  2. Improved Heterogeneous Distance Functions

    OpenAIRE

    Wilson, D. R.; Martinez, T. R.

    1996-01-01

    Instance-based learning techniques typically handle continuous and linear input values well, but often do not handle nominal input attributes appropriately. The Value Difference Metric (VDM) was designed to find reasonable distance values between nominal attribute values, but it largely ignores continuous attributes, requiring discretization to map continuous values into nominal values. This paper proposes three new heterogeneous distance functions, called the Heterogeneous Value Difference M...

  3. Second Language Word Learning through Repetition and Imitation: Functional Networks as a Function of Learning Phase and Language Distance

    Directory of Open Access Journals (Sweden)

    Ladan Ghazi-Saidi

    2017-09-01

    Full Text Available Introduction and Aim: Repetition and imitation are among the oldest second language (L2 teaching approaches and are frequently used in the context of L2 learning and language therapy, despite some heavy criticism. Current neuroimaging techniques allow the neural mechanisms underlying repetition and imitation to be examined. This fMRI study examines the influence of verbal repetition and imitation on network configuration. Integration changes within and between the cognitive control and language networks were studied, in a pair of linguistically close languages (Spanish and French, and compared to our previous work on a distant language pair (Ghazi-Saidi et al., 2013.Methods: Twelve healthy native Spanish-speaking (L1 adults, and 12 healthy native Persian-speaking adults learned 130 new French (L2 words, through a computerized audiovisual repetition and imitation program. The program presented colored photos of objects. Participants were instructed to look at each photo and pronounce its name as closely as possible to the native template (imitate. Repetition was encouraged as many times as necessary to learn the object’s name; phonological cues were provided if necessary. Participants practiced for 15 min, over 30 days, and were tested while naming the same items during fMRI scanning, at week 1 (shallow learning phase and week 4 (consolidation phase of training. To compare this set of data with our previous work on Persian speakers, a similar data analysis plan including accuracy rates (AR, response times (RT, and functional integration values for the language and cognitive control network at each measure point was included, with further L1-L2 direct comparisons across the two populations.Results and Discussion: The evidence shows that learning L2 words through repetition induces neuroplasticity at the network level. Specifically, L2 word learners showed increased network integration after 3 weeks of training, with both close and distant

  4. Second Language Word Learning through Repetition and Imitation: Functional Networks as a Function of Learning Phase and Language Distance.

    Science.gov (United States)

    Ghazi-Saidi, Ladan; Ansaldo, Ana Ines

    2017-01-01

    Introduction and Aim: Repetition and imitation are among the oldest second language (L2) teaching approaches and are frequently used in the context of L2 learning and language therapy, despite some heavy criticism. Current neuroimaging techniques allow the neural mechanisms underlying repetition and imitation to be examined. This fMRI study examines the influence of verbal repetition and imitation on network configuration. Integration changes within and between the cognitive control and language networks were studied, in a pair of linguistically close languages (Spanish and French), and compared to our previous work on a distant language pair (Ghazi-Saidi et al., 2013). Methods: Twelve healthy native Spanish-speaking (L1) adults, and 12 healthy native Persian-speaking adults learned 130 new French (L2) words, through a computerized audiovisual repetition and imitation program. The program presented colored photos of objects. Participants were instructed to look at each photo and pronounce its name as closely as possible to the native template (imitate). Repetition was encouraged as many times as necessary to learn the object's name; phonological cues were provided if necessary. Participants practiced for 15 min, over 30 days, and were tested while naming the same items during fMRI scanning, at week 1 (shallow learning phase) and week 4 (consolidation phase) of training. To compare this set of data with our previous work on Persian speakers, a similar data analysis plan including accuracy rates (AR), response times (RT), and functional integration values for the language and cognitive control network at each measure point was included, with further L1-L2 direct comparisons across the two populations. Results and Discussion: The evidence shows that learning L2 words through repetition induces neuroplasticity at the network level. Specifically, L2 word learners showed increased network integration after 3 weeks of training, with both close and distant language pairs

  5. A Unified Approach to Mapping and Routing on a Network-on-Chip for Both Best-Effort and Guaranteed Service Traffic

    NARCIS (Netherlands)

    Hansson, A.; Goossens, K.; R?dulescu, A.

    2007-01-01

    One of the key steps in Network-on-Chip-based design is spatial mapping of cores and routing of the communication between those cores. Known solutions to the mapping and routing problems first map cores onto a topology and then route communication, using separate and possibly conflicting objective

  6. Mapping networks of physical interactions between genomic elements using 5C technology.

    Science.gov (United States)

    Dostie, Josée; Dekker, Job

    2007-01-01

    Genomic elements separated by large genomic distances can physically interact to mediate long-range gene regulation and other chromosomal processes. Interactions between genomic elements can be detected using the chromosome conformation capture (3C) technology. We recently developed a high-throughput adaptation of 3C, 3C-carbon copy (5C), that is used to measure networks of millions of chromatin interactions in parallel. As in 3C, cells are treated with formaldehyde to cross-link chromatin interactions. The chromatin is solubilized, digested with a restriction enzyme and ligated at low DNA concentration to promote intra-molecular ligation of cross-linked DNA fragments. Ligation products are subsequently purified to generate a 3C library. The 5C technology then employs highly multiplexed ligation-mediated amplification (LMA) to detect and amplify 3C ligation junctions. The resulting 5C library of ligated primers is analyzed using either microarray detection or ultra-high-throughput DNA sequencing. The 5C protocol described here can be completed in 13 d.

  7. Mapping debris flow susceptibility using analytical network process in Kodaikkanal Hills, Tamil Nadu (India)

    Science.gov (United States)

    Sujatha, Evangelin Ramani; Sridhar, Venkataramana

    2017-12-01

    Rapid debris flows, a mixture of unconsolidated sediments and water travelling at speeds > 10 m/s are the most destructive water related mass movements that affect hill and mountain regions. The predisposing factors setting the stage for the event are the availability of materials, type of materials, stream power, slope gradient, aspect and curvature, lithology, land use and land cover, lineament density, and drainage. Rainfall is the most common triggering factor that causes debris flow in the Palar subwatershed and seismicity is not considered as it is a stable continental region and moderate seismic zone. Also, there are no records of major seismic activities in the past. In this study, one of the less explored heuristic methods known as the analytical network process (ANP) is used to map the spatial propensity of debris flow. This method is based on top-down decision model and is a multi-criteria, decision-making tool that translates subjective assessment of relative importance to weights or scores and is implemented in the Palar subwatershed which is part of the Western Ghats in southern India. The results suggest that the factors influencing debris flow susceptibility in this region are the availability of material on the slope, peak flow, gradient of the slope, land use and land cover, and proximity to streams. Among all, peak discharge is identified as the chief factor causing debris flow. The use of micro-scale watersheds demonstrated in this study to develop the susceptibility map can be very effective for local level planning and land management.

  8. A MapReduce Based High Performance Neural Network in Enabling Fast Stability Assessment of Power Systems

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-01-01

    Full Text Available Transient stability assessment is playing a vital role in modern power systems. For this purpose, machine learning techniques have been widely employed to find critical conditions and recognize transient behaviors based on massive data analysis. However, an ever increasing volume of data generated from power systems poses a number of challenges to traditional machine learning techniques, which are computationally intensive running on standalone computers. This paper presents a MapReduce based high performance neural network to enable fast stability assessment of power systems. Hadoop, which is an open-source implementation of the MapReduce model, is first employed to parallelize the neural network. The parallel neural network is further enhanced with HaLoop to reduce the computation overhead incurred in the iteration process of the neural network. In addition, ensemble techniques are employed to accommodate the accuracy loss of the parallelized neural network in classification. The parallelized neural network is evaluated with both the IEEE 68-node system and a real power system from the aspects of computation speedup and stability assessment.

  9. Moving from theory to practice: A participatory social network mapping approach to address unmet need for family planning in Benin.

    Science.gov (United States)

    Igras, Susan; Diakité, Mariam; Lundgren, Rebecka

    2017-07-01

    In West Africa, social factors influence whether couples with unmet need for family planning act on birth-spacing desires. Tékponon Jikuagou is testing a social network-based intervention to reduce social barriers by diffusing new ideas. Individuals and groups judged socially influential by their communities provide entrée to networks. A participatory social network mapping methodology was designed to identify these diffusion actors. Analysis of monitoring data, in-depth interviews, and evaluation reports assessed the methodology's acceptability to communities and staff and whether it produced valid, reliable data to identify influential individuals and groups who diffuse new ideas through their networks. Results indicated the methodology's acceptability. Communities were actively and equitably engaged. Staff appreciated its ability to yield timely, actionable information. The mapping methodology also provided valid and reliable information by enabling communities to identify highly connected and influential network actors. Consistent with social network theory, this methodology resulted in the selection of informal groups and individuals in both informal and formal positions. In-depth interview data suggest these actors were diffusing new ideas, further confirming their influence/connectivity. The participatory methodology generated insider knowledge of who has social influence, challenging commonly held assumptions. Collecting and displaying information fostered staff and community learning, laying groundwork for social change.

  10. Research on biodiversity and climate change at a distance: Collaboration networks between europe and latin america and the caribbean

    OpenAIRE

    Olivier Dangles; Jean Loirat; Claire Freour; Sandrine Serre; Jean Vacher; Xavier Le Roux

    2016-01-01

    Biodiversity loss and climate change are both globally significant issues that must be addressed through collaboration across countries and disciplines. With the December 2015 COP21 climate conference in Paris and the recent creation of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), it has become critical to evaluate the capacity for global research networks to develop at the interface between biodiversity and climate change. In the context of the European Unio...

  11. Mapping the optimal forest road network based on the multicriteria evaluation technique: the case study of Mediterranean Island of Thassos in Greece.

    Science.gov (United States)

    Tampekis, Stergios; Sakellariou, Stavros; Samara, Fani; Sfougaris, Athanassios; Jaeger, Dirk; Christopoulou, Olga

    2015-11-01

    The sustainable management of forest resources can only be achieved through a well-organized road network designed with the optimal spatial planning and the minimum environmental impacts. This paper describes the spatial layout mapping for the optimal forest road network and the environmental impacts evaluation that are caused to the natural environment based on the multicriteria evaluation (MCE) technique at the Mediterranean island of Thassos in Greece. Data analysis and its presentation are achieved through a spatial decision support system using the MCE method with the contribution of geographic information systems (GIS). With the use of the MCE technique, we evaluated the human impact intensity to the forest ecosystem as well as the ecosystem's absorption from the impacts that are caused from the forest roads' construction. For the human impact intensity evaluation, the criteria that were used are as follows: the forest's protection percentage, the forest road density, the applied skidding means (with either the use of tractors or the cable logging systems in timber skidding), the timber skidding direction, the visitors' number and truck load, the distance between forest roads and streams, the distance between forest roads and the forest boundaries, and the probability that the forest roads are located on sights with unstable soils. In addition, for the ecosystem's absorption evaluation, we used forestry, topographical, and social criteria. The recommended MCE technique which is described in this study provides a powerful, useful, and easy-to-use implement in order to combine the sustainable utilization of natural resources and the environmental protection in Mediterranean ecosystems.

  12. Long distance quantum teleportation

    Science.gov (United States)

    Xia, Xiu-Xiu; Sun, Qi-Chao; Zhang, Qiang; Pan, Jian-Wei

    2018-01-01

    Quantum teleportation is a core protocol in quantum information science. Besides revealing the fascinating feature of quantum entanglement, quantum teleportation provides an ultimate way to distribute quantum state over extremely long distance, which is crucial for global quantum communication and future quantum networks. In this review, we focus on the long distance quantum teleportation experiments, especially those employing photonic qubits. From the viewpoint of real-world application, both the technical advantages and disadvantages of these experiments are discussed.

  13. The smart grid research network: Road map for Smart Grid research, development and demonstration up to 2020

    Energy Technology Data Exchange (ETDEWEB)

    Troi, A. [Technical Univ. of Denmark. DTU Electrical Engineering, DTU Risoe Campus, Roskilde (Denmark); Noerregaard Joergensen, B. [Syddansk Univ. (SDU), Odense (Denmark); Mahler Larsen, E. [Technical Univ. of Denmark. DTU Electrical Engineering, Kgs. Lyngby (Denmark)] [and others

    2013-01-15

    This road map is a result of part-recommendation no. 25 in 'MAIN REPORT - The Smart Grid Network's recommendations', written by the Smart Grid Network for the Danish Ministry of Climate, Energy and Building in October 2011. This part-recommendation states: ''Part-recommendation 25 - A road map for Smart Grid research, development and demonstration It is recommended that the electricity sector invite the Ministry to participate in the creation of a road map to ensure that solutions are implemented and coordinated with related policy areas. The sector should also establish a fast-acting working group with representatives from universities, distribution companies and the electric industry, in order to produce a mutual, binding schedule for the RDD of the Smart Grid in Denmark. Time prioritisation of part-recommendation: 2011-2012 Responsibility for implementation of part-recommendation: Universities, along with relevant electric-industry actors, should establish a working group for the completion of a consolidated road map by the end of 2012.'' In its work on this report, the Smart Grid Research Network has focused particularly on part-recommendations 26, 27 and 28 in 'MAIN REPORT - The Smart Grid Network's recommendations', which relate to strengthening and marketing the research infrastructure that will position Denmark as the global hub for Smart Grid development; strengthening basic research into the complex relationships in electric systems with large quantities of independent parties; and improved understanding of consumer behaviour and social economics. Naturally the work has spread to related areas along the way. The work has been conducted by the Smart Grid Research Network. (Author)

  14. Risk and Resilience Analysis of Complex Network Systems Considering Cascading Failure and Recovery Strategy Based on Coupled Map Lattices

    Directory of Open Access Journals (Sweden)

    Fuchun Ren

    2015-01-01

    Full Text Available Risk and resilience are important and challenging issues in complex network systems since a single failure may trigger a whole collapse of the systems due to cascading effect. New theories, models, and methods are urgently demanded to deal with this challenge. In this paper, a coupled map lattices (CML based approach is adopted to analyze the risk of cascading process in Watts-Strogatz (WS small-world network and Barabási and Albert (BA scale-free network, respectively. Then, to achieve an effective and robust system and provide guidance in countering the cascading failure, a modified CML model with recovery strategy factor is proposed. Numerical simulations are put forward based on small-world CML and scale-free CML. The simulation results reveal that appropriate recovery strategies would significantly improve the resilience of networks.

  15. MAP3S precipitation chemistry network. Third periodic summary report, July 1978-December 1979

    Energy Technology Data Exchange (ETDEWEB)

    1980-05-01

    The MAP3S Precipitation Chemistry Network consists of eight collection sites in the northeastern United States. Precipitation event samples are collected by cooperating site operators, using specially developed sampling equipment. In this, the third periodic summary report, are listed field and concentration data for the period July 1, 1978 to December 31, 1979. Over three years' samples have been collected at most of the sites, which went into operation between September 1976 and October 1978. Samples are chemically analyzed at a central laboratory for 13 pollutant species. Weekly samples in addition to event samples were collected over a 1 1/2 year period at three sites. Analysis of one year's results indicates that there is little difference between the concentrations collected by the two methods in terms of seasonal precipitation-weighted means for all species except dissolved SO/sub 2/. Event samples tend to average about 25% higher in SO/sub 2/ than weekly samples.

  16. Improving the analysis of dependable systems by mapping fault trees into Bayesian networks

    Energy Technology Data Exchange (ETDEWEB)

    Bobbio, A.; Portinale, L.; Minichino, M.; Ciancamerla, E

    2001-03-01

    Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of dependability. The present paper is aimed at exploring the capabilities of the BN formalism in the analysis of dependable systems. To this end, the paper compares BN with one of the most popular techniques for dependability analysis of large, safety critical systems, namely Fault Trees (FT). The paper shows that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former (i.e. reliability of the Top Event or of any sub-system, criticality of components, etc). Moreover, by using BN, some additional power can be obtained, both at the modeling and at the analysis level. At the modeling level, several restrictive assumptions implicit in the FT methodology can be removed and various kinds of dependencies among components can be accommodated. At the analysis level, a general diagnostic analysis can be performed. The comparison of the two methodologies is carried out by means of a running example, taken from the literature, that consists of a redundant multiprocessor system.

  17. Eurosdr - the Pan-European Network for Mapping Agencies and Academia

    Science.gov (United States)

    Streilein, A.; Remondino, F.; Pfeifer, N.; Trollvik, J. A.; Stoter, J.; Crompvoets, J.; Potůčková, M.

    2016-06-01

    EuroSDR (http://www.eurosdr.net/) is a non-profit organisation that provides a pan-European network that brings together mapping / cadastre agencies and academia for the purpose of applied research, and securing timely, research-based knowledge that allows the agencies to play their role as content providers and government competence centres for geographic information and spatial data infrastructures. EuroSDR is the recognised provider of research-based knowledge to a Europe where citizens can readily benefit from geographic information. Its mission is to develop and improve methods, systems and standards for the acquisition, processing, production, maintenance, management, visualization, and dissemination of geographic reference data in support of applications and service delivery. EuroSDR delivers advanced research-based knowledge. Its value is generated by facilitating interaction between research organisations and the public and private sector with the aim of exchanging ideas and knowledge about relevant research topics; by facilitating and contributing to research projects; and by transferring knowledge and research results to real world applications. The paper gives an overview about EuroSDR research principles, research alliances, objectives and action plans of each of the technical commissions.

  18. Nonintrusive Energy Monitoring for Microgrids Using Hybrid Self-Organizing Feature-Mapping Networks

    Directory of Open Access Journals (Sweden)

    Jing-Han Chou

    2012-07-01

    Full Text Available Microgrids can increase power penetration from distributed generation (DG in the power system. The interface (i.e., the point of common coupling, PCC between the microgrid and the power utility must satisfy certain standards, such as IEEE Sd. 1547. Energy monitoring of the microgrid at the PCC by the power utility is crucial if the utility cannot install advanced meters at different locations in the microgrid (e.g., a factory. This paper presents a new nonintrusive energy monitoring method using a hybrid self-organizing feature-mapping neural network (SOFMNN. The components of the FFT spectra for voltage, current, kW and kVAR, measured at the PCC, serve as the signatures for the hybrid SOFMNN inputs. The nonintrusive energy monitoring at the PCC identifies different load levels for individual linear/nonlinear loads and output levels for wind power generators in the microgrid. Using this energy monitoring result, the power utility can establish an energy management policy. The simulation results from a microgrid, consisting of a diesel generator, a wind-turbine-generator, a rectifier and a cyclo-converter, show the practicability of the proposed method.

  19. MAP3S Precipitation Chemistry Network: second periodic summary report, July 1977--June 1978

    Energy Technology Data Exchange (ETDEWEB)

    1979-01-01

    The MAP3S Precipitation Chemistry Network consists of eight sites located in the northeastern United States. Precipitation event samples are collected by cooperating site operators, using specially developed sampling equipment. The concentration data collected over the period July 1, 1977 to July 1, 1978, are listed as a summary of the data reported monthly throughout the year. Samples were chemically analyzed at a central laboratory for 13 pollutant species - pH, conductivity, SO/sub 2/, SO/sub 4//sup =/, NH/sub 4//sup +/, NO/sub 2//sup -/, NO/sub 3//sup -/, Cl/sup -/, PO/sub 4//sup 3 -/, Na/sup +/, K/sup +/, Ca/sup + +/, and Mg/sup + +/ - using ion chromatography, automated wet chemistry, atomic absorption spectrophotometry, and electrode techniques. Second-year developments included: the installation of refrigeration equipment in all Battelle collectors; the initiation of an externally administered quality control program; and use of ion chromatography for cation as well as anion species. Supplementary research efforts included a special collector comparison study at the Pennsylvania State site and further analysis of sulfite versus sulfate deposition.

  20. Pattern recognition in lithology classification: modeling using neural networks, self-organizing maps and genetic algorithms

    Science.gov (United States)

    Sahoo, Sasmita; Jha, Madan K.

    2017-03-01

    Effective characterization of lithology is vital for the conceptualization of complex aquifer systems, which is a prerequisite for the development of reliable groundwater-flow and contaminant-transport models. However, such information is often limited for most groundwater basins. This study explores the usefulness and potential of a hybrid soft-computing framework; a traditional artificial neural network with gradient descent-momentum training (ANN-GDM) and a traditional genetic algorithm (GA) based ANN (ANN-GA) approach were developed and compared with a novel hybrid self-organizing map (SOM) based ANN (SOM-ANN-GA) method for the prediction of lithology at a basin scale. This framework is demonstrated through a case study involving a complex multi-layered aquifer system in India, where well-log sites were clustered on the basis of sand-layer frequencies; within each cluster, subsurface layers were reclassified into four depth classes based on the maximum drilling depth. ANN models for each depth class were developed using each of the three approaches. Of the three, the hybrid SOM-ANN-GA models were able to recognize incomplete geologic pattern more reasonably, followed by ANN-GA and ANN-GDM models. It is concluded that the hybrid soft-computing framework can serve as a promising tool for characterizing lithology in groundwater basins with missing lithologic patterns.

  1. Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities

    Science.gov (United States)

    Yusufaly, Tahir I.; Boedicker, James Q.

    2017-08-01

    Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely understood in heterogeneous communities, where variant bacterial strains possess distinct QS systems that produce chemically unique AIs. AI molecules bind to ‘cognate’ receptors, but also to ‘non-cognate’ receptors found in other strains, resulting in inter-strain crosstalk. Understanding these interactions is a prerequisite for deciphering the consequences of crosstalk in real ecosystems, where multiple AIs are regularly present in the same environment. As a step towards this goal, we map crosstalk in a heterogeneous community of variant QS strains onto an artificial neural network model. This formulation allows us to systematically analyze how crosstalk regulates the community’s capacity for flexible decision making, as quantified by the Boltzmann entropy of all QS gene expression states of the system. In a mean-field limit of complete cross-inhibition between variant strains, the model is exactly solvable, allowing for an analytical formula for the number of variants that maximize capacity as a function of signal kinetics and activation parameters. An analysis of previous experimental results on the Staphylococcus aureus two-component Agr system indicates that the observed combination of variant numbers, gene expression rates and threshold concentrations lies near this critical regime of parameter space where capacity peaks. The results are suggestive of a potential evolutionary driving force for diversification in certain QS systems.

  2. A mobile sensor network to map carbon dioxide emissions in urban environments

    Science.gov (United States)

    Lee, Joseph K.; Christen, Andreas; Ketler, Rick; Nesic, Zoran

    2017-03-01

    A method for directly measuring carbon dioxide (CO2) emissions using a mobile sensor network in cities at fine spatial resolution was developed and tested. First, a compact, mobile system was built using an infrared gas analyzer combined with open-source hardware to control, georeference, and log measurements of CO2 mixing ratios on vehicles (car, bicycles). Second, two measurement campaigns, one in summer and one in winter (heating season) were carried out. Five mobile sensors were deployed within a 1 × 12. 7 km transect across the city of Vancouver, BC, Canada. The sensors were operated for 3.5 h on pre-defined routes to map CO2 mixing ratios at street level, which were then averaged to 100 × 100 m grid cells. The averaged CO2 mixing ratios of all grids in the study area were 417.9 ppm in summer and 442.5 ppm in winter. In both campaigns, mixing ratios were highest in the grid cells of the downtown core and along arterial roads and lowest in parks and well vegetated residential areas. Third, an aerodynamic resistance approach to calculating emissions was used to derive CO2 emissions from the gridded CO2 mixing ratio measurements in conjunction with mixing ratios and fluxes collected from a 28 m tall eddy-covariance tower located within the study area. These measured emissions showed a range of -12 to 226 CO2 ha-1 h-1 in summer and of -14 to 163 kg CO2 ha-1 h-1 in winter, with an average of 35.1 kg CO2 ha-1 h-1 (summer) and 25.9 kg CO2 ha-1 h-1 (winter). Fourth, an independent emissions inventory was developed for the study area using buildings energy simulations from a previous study and routinely available traffic counts. The emissions inventory for the same area averaged to 22.06 kg CO2 ha-1 h-1 (summer) and 28.76 kg CO2 ha-1 h-1 (winter) and was used to compare against the measured emissions from the mobile sensor network. The comparison on a grid-by-grid basis showed linearity between CO2 mixing ratios and the emissions inventory (R2 = 0. 53 in summer and R

  3. Mapping and discrimination of networks in the complexity-entropy plane

    Science.gov (United States)

    Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

    2017-10-01

    Complex networks are usually characterized in terms of their topological, spatial, or information-theoretic properties and combinations of the associated metrics are used to discriminate networks into different classes or categories. However, even with the present variety of characteristics at hand it still remains a subject of current research to appropriately quantify a network's complexity and correspondingly discriminate between different types of complex networks, like infrastructure or social networks, on such a basis. Here we explore the possibility to classify complex networks by means of a statistical complexity measure that has formerly been successfully applied to distinguish different types of chaotic and stochastic time series. It is composed of a network's averaged per-node entropic measure characterizing the network's information content and the associated Jenson-Shannon divergence as a measure of disequilibrium. We study 29 real-world networks and show that networks of the same category tend to cluster in distinct areas of the resulting complexity-entropy plane. We demonstrate that within our framework, connectome networks exhibit among the highest complexity while, e.g., transportation and infrastructure networks display significantly lower values. Furthermore, we demonstrate the utility of our framework by applying it to families of random scale-free and Watts-Strogatz model networks. We then show in a second application that the proposed framework is useful to objectively construct threshold-based networks, such as functional climate networks or recurrence networks, by choosing the threshold such that the statistical network complexity is maximized.

  4. Online Communication in Organizations Does Not Kill Distance

    DEFF Research Database (Denmark)

    Hage, Eveline; Tan, Chee-Wee

    Debates on the effects of online communication on distance within organizational networks have persisted within extant literature. Early contributions, which focus primarily on geographical distance, have highlighted the negative impact of distance on network evolution and sustenance, alluding to...

  5. Research on Biodiversity and Climate Change at a Distance: Collaboration Networks between Europe and Latin America and the Caribbean.

    Science.gov (United States)

    Dangles, Olivier; Loirat, Jean; Freour, Claire; Serre, Sandrine; Vacher, Jean; Le Roux, Xavier

    2016-01-01

    Biodiversity loss and climate change are both globally significant issues that must be addressed through collaboration across countries and disciplines. With the December 2015 COP21 climate conference in Paris and the recent creation of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), it has become critical to evaluate the capacity for global research networks to develop at the interface between biodiversity and climate change. In the context of the European Union (EU) strategy to stand as a world leader in tackling global challenges, the European Commission has promoted ties between the EU and Latin America and the Caribbean (LAC) in science, technology and innovation. However, it is not clear how these significant interactions impact scientific cooperation at the interface of biodiversity and climate change. We looked at research collaborations between two major regions-the European Research Area (ERA) and LAC-that addressed both biodiversity and climate change. We analysed the temporal evolution of these collaborations, whether they were led by ERA or LAC teams, and which research domains they covered. We surveyed publications listed on the Web of Science that were authored by researchers from both the ERA and LAC and that were published between 2003 and 2013. We also run similar analyses on other topics and other continents to provide baseline comparisons. Our results revealed a steady increase in scientific co-authorships between ERA and LAC countries as a result of the increasingly complex web of relationships that has been weaved among scientists from the two regions. The ERA-LAC co-authorship increase for biodiversity and climate change was higher than those reported for other topics and for collaboration with other continents. We also found strong differences in international collaboration patterns within the LAC: co-publications were fewest from researchers in low- and lower-middle-income countries and most prevalent from

  6. Research on Biodiversity and Climate Change at a Distance: Collaboration Networks between Europe and Latin America and the Caribbean.

    Directory of Open Access Journals (Sweden)

    Olivier Dangles

    Full Text Available Biodiversity loss and climate change are both globally significant issues that must be addressed through collaboration across countries and disciplines. With the December 2015 COP21 climate conference in Paris and the recent creation of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES, it has become critical to evaluate the capacity for global research networks to develop at the interface between biodiversity and climate change. In the context of the European Union (EU strategy to stand as a world leader in tackling global challenges, the European Commission has promoted ties between the EU and Latin America and the Caribbean (LAC in science, technology and innovation. However, it is not clear how these significant interactions impact scientific cooperation at the interface of biodiversity and climate change. We looked at research collaborations between two major regions-the European Research Area (ERA and LAC-that addressed both biodiversity and climate change. We analysed the temporal evolution of these collaborations, whether they were led by ERA or LAC teams, and which research domains they covered. We surveyed publications listed on the Web of Science that were authored by researchers from both the ERA and LAC and that were published between 2003 and 2013. We also run similar analyses on other topics and other continents to provide baseline comparisons. Our results revealed a steady increase in scientific co-authorships between ERA and LAC countries as a result of the increasingly complex web of relationships that has been weaved among scientists from the two regions. The ERA-LAC co-authorship increase for biodiversity and climate change was higher than those reported for other topics and for collaboration with other continents. We also found strong differences in international collaboration patterns within the LAC: co-publications were fewest from researchers in low- and lower-middle-income countries and most

  7. A fully-automated neural network analysis of AFM force-distance curves for cancer tissue diagnosis

    Science.gov (United States)

    Minelli, Eleonora; Ciasca, Gabriele; Sassun, Tanya Enny; Antonelli, Manila; Palmieri, Valentina; Papi, Massimiliano; Maulucci, Giuseppe; Santoro, Antonio; Giangaspero, Felice; Delfini, Roberto; Campi, Gaetano; De Spirito, Marco

    2017-10-01

    Atomic Force Microscopy (AFM) has the unique capability of probing the nanoscale mechanical properties of biological systems that affect and are affected by the occurrence of many pathologies, including cancer. This capability has triggered growing interest in the translational process of AFM from physics laboratories to clinical practice. A factor still hindering the current use of AFM in diagnostics is related to the complexity of AFM data analysis, which is time-consuming and needs highly specialized personnel with a strong physical and mathematical background. In this work, we demonstrate an operator-independent neural-network approach for the analysis of surgically removed brain cancer tissues. This approach allowed us to distinguish—in a fully automated fashion—cancer from healthy tissues with high accuracy, also highlighting the presence and the location of infiltrating tumor cells.

  8. Learning to Classify Map Data with Cascaded VLSI Neural Network Building Block Chips

    Science.gov (United States)

    Brown, T. X.; Duong, T.; Eberhardt, S. P.; Tran, M. D.; Daud, T.; Thakoor, A. P.

    1993-01-01

    Paper maps are an important but unwieldy data format. To increase its utility, copious amounts of map data have been scanned into a digital map knowledge base. The next task in this knowledge base is to reduce this data to its underlying feature form suitable for analysis.

  9. Assessment of applicability domain for multivariate counter-propagation artificial neural network predictive models by minimum euclidean distance space analysis: a case study.

    Science.gov (United States)

    Minovski, Nikola; Župerl, Špela; Drgan, Viktor; Novič, Marjana

    2013-01-08

    Alongside the validation, the concept of applicability domain (AD) is probably one of the most important aspects which determine the quality as well as reliability of the established quantitative structure-activity relationship (QSAR) models. To date, a variety of approaches for AD estimation have been devised which can be applied to particular type of QSAR models and their practical utilization is extensively elaborated in the literature. The present study introduces a novel, simple, and effective distance-based method for estimation of the AD in case of developed and validated predictive counter-propagation artificial neural network (CP ANN) models through a proficient exploitation of the euclidean distance (ED) metric in the structure-representation vector space. The performance of the method was evaluated and explained in a case study by using a pre-built and validated CP ANN model for prediction of the transport activity of the transmembrane protein bilitranslocase for a diverse set of compounds. The method was tested on two more datasets in order to confirm its performance for evaluation of the applicability domain in CP ANN models. The chemical compounds determined as potential outliers, i.e., outside of the CP ANN model AD, were confirmed in a comparative AD assessment by using the leverage approach. Moreover, the method offers a graphical depiction of the AD for fast and simple determination of the extreme points. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. The Rise of Network Ecology: Maps of the topic diversity and scientific collaboration

    OpenAIRE

    Borrett, Stuart R.; Moody, James; Edelmann, Achim

    2013-01-01

    Network ecologists investigate the structure, function, and evolution of ecological systems using network models and analyses. For example, network techniques have been used to study community interactions (i.e., food-webs, mutualisms), gene flow across landscapes, and the sociality of individuals in populations. The work presented here uses a bibliographic and network approach to (1) document the rise of Network Ecology, (2) identify the diversity of topics addressed in the field, and (3) ma...

  11. Retrieving quantifiable social media data from human sensor networks for disaster modeling and crisis mapping

    Science.gov (United States)

    Aulov, Oleg

    This dissertation presents a novel approach that utilizes quantifiable social media data as a human aware, near real-time observing system, coupled with geophysical predictive models for improved response to disasters and extreme events. It shows that social media data has the potential to significantly improve disaster management beyond informing the public, and emphasizes the importance of different roles that social media can play in management, monitoring, modeling and mitigation of natural and human-caused extreme disasters. In the proposed approach Social Media users are viewed as "human sensors" that are "deployed" in the field, and their posts are considered to be "sensor observations", thus different social media outlets all together form a Human Sensor Network. We utilized the "human sensor" observations, as boundary value forcings, to show improved geophysical model forecasts of extreme disaster events when combined with other scientific data such as satellite observations and sensor measurements. Several recent extreme disasters are presented as use case scenarios. In the case of the Deepwater Horizon oil spill disaster of 2010 that devastated the Gulf of Mexico, the research demonstrates how social media data from Flickr can be used as a boundary forcing condition of GNOME oil spill plume forecast model, and results in an order of magnitude forecast improvement. In the case of Hurricane Sandy NY/NJ landfall impact of 2012, we demonstrate how the model forecasts, when combined with social media data in a single framework, can be used for near real-time forecast validation, damage assessment and disaster management. Owing to inherent uncertainties in the weather forecasts, the NOAA operational surge model only forecasts the worst-case scenario for flooding from any given hurricane. Geolocated and time-stamped Instagram photos and tweets allow near real-time assessment of the surge levels at different locations, which can validate model forecasts, give

  12. RLAM: A Dynamic and Efficient Reinforcement Learning-Based Adaptive Mapping Scheme in Mobile WiMAX Networks

    OpenAIRE

    M. Louta; Sarigiannidis, P.; Misra, S.; P. Nicopolitidis; Papadimitriou, G.

    2014-01-01

    WiMAX (Worldwide Interoperability for Microwave Access) constitutes a candidate networking technology towards the 4G vision realization. By adopting the Orthogonal Frequency Division Multiple Access (OFDMA) technique, the latest IEEE 802.16x amendments manage to provide QoS-aware access services with full mobility support. A number of interesting scheduling and mapping schemes have been proposed in research literature. However, they neglect a considerable asset of the OFDMA-based wireless sys...

  13. MQARR-AODV: A NOVEL MULTIPATH QOS AWARE RELIABLE REVERSE ON-DEMAND DISTANCE VECTOR ROUTING PROTOCOL FOR MOBILE AD-HOC NETWORKS

    Directory of Open Access Journals (Sweden)

    K.G. Santhiya

    2012-12-01

    Full Text Available MANET (Mobile Ad-hoc Network is an infra structure less wireless ad-hoc network that does not require any basic central control. The topology of the network changes drastically due to very fast mobility of nodes. So an adaptive routing protocol is needed for routing in MANET. AODV (Ad-hoc On-demand Distance Vector routing is the effective and prominent on-demand Ad-hoc routing protocols. During route establishment phase in traditional AODV, only one route reply message will be sent in the reverse path to establish routing path. The high mobility of nodes may affect the reply messages which lead to the retransmission of route request message by the sender which in turn leads to higher communication delay, power consumption and the reduction in the ratio of packets delivered. Sending multiple route reply messages and establishing multiple paths in a single path discovery will reduce the routing overhead involved in maintaining the connection between source and destination nodes. Multipath routing can render high scalability, end-to-end throughput and provide load balancing in MANET. The new proposed novel Multipath QoS aware reliable routing protocol establishes two routes of maximum node disjoint paths and the data transfer is carried out in the two paths simultaneously. To select best paths, the new proposed protocol uses three parameters Link Eminence, MAC overhead and node residual energy. The experimental values prove that the MQARR-AODV protocol achieves high reliability, stability, low latency and outperforms AODV by the less energy consumption, overhead and delay.

  14. Mapping dynamic social networks in real life using participants' own smartphones

    NARCIS (Netherlands)

    Boonstra, T.W.; Larsen, M.E.; Christensen, H.

    2015-01-01

    Interpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing.

  15. Map images portraying flight paths of low-altitude transects over the Arctic Network of national park units and Selawik National Wildlife Refuge, Alaska, July 2013

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — Maps portraying the flight paths for low altitude transects conducted from small aircraft over the National Park Service’s Arctic Network (Bering Land Bridge...

  16. Mapping the Structure of Directed Networks: Beyond the Bow-Tie Diagram

    Science.gov (United States)

    Timár, G.; Goltsev, A. V.; Dorogovtsev, S. N.; Mendes, J. F. F.

    2017-02-01

    We reveal a hierarchical, multilayer organization of finite components—i.e., tendrils and tubes—around the giant connected components in directed networks and propose efficient algorithms allowing one to uncover the entire organization of key real-world directed networks, such as the World Wide Web, the neural network of Caenorhabditis elegans, and others. With increasing damage, the giant components decrease in size while the number and size of tendril layers increase, enhancing the susceptibility of the networks to damage.

  17. Distributing stand inventory data and maps over a wide area network

    Science.gov (United States)

    Thomas E. Burk

    2000-01-01

    High-speed networks connecting multiple levels of management are becoming commonplace among forest resources organizations. Such networks can be used to deliver timely spatial and aspatial data relevant to the management of stands to field personnel. A network infrastructure allows maintenance of cost-effective, centralized databases with the potential for updating by...

  18. Mapping the Field of Educational Administration Research: A Journal Citation Network Analysis

    Science.gov (United States)

    Wang, Yinying; Bowers, Alex J.

    2016-01-01

    Purpose: The purpose of this paper is to uncover how knowledge is exchanged and disseminated in the educational administration research literature through the journal citation network. Design/ Methodology/Approach: Drawing upon social network theory and citation network studies in other disciplines, the authors constructed an educational…

  19. Stable learning of functional maps in self-organizing spiking neural networks with continuous synaptic plasticity.

    Science.gov (United States)

    Srinivasa, Narayan; Jiang, Qin

    2013-01-01

    This study describes a spiking model that self-organizes for stable formation and maintenance of orientation and ocular dominance maps in the visual cortex (V1). This self-organization process simulates three development phases: an early experience-independent phase, a late experience-independent phase and a subsequent refinement phase during which experience acts to shape the map properties. The ocular dominance maps that emerge accommodate the two sets of monocular inputs that arise from the lateral geniculate nucleus (LGN) to layer 4 of V1. The orientation selectivity maps that emerge feature well-developed iso-orientation domains and fractures. During the last two phases of development the orientation preferences at some locations appear to rotate continuously through ±180° along circular paths and referred to as pinwheel-like patterns but without any corresponding point discontinuities in the orientation gradient maps. The formation of these functional maps is driven by balanced excitatory and inhibitory currents that are established via synaptic plasticity based on spike timing for both excitatory and inhibitory synapses. The stability and maintenance of the formed maps with continuous synaptic plasticity is enabled by homeostasis caused by inhibitory plasticity. However, a prolonged exposure to repeated stimuli does alter the formed maps over time due to plasticity. The results from this study suggest that continuous synaptic plasticity in both excitatory neurons and interneurons could play a critical role in the formation, stability, and maintenance of functional maps in the cortex.

  20. Participating in the Geospatial Web: Collaborative Mapping, Social Networks and Participatory GIS

    Science.gov (United States)

    Rouse, L. Jesse; Bergeron, Susan J.; Harris, Trevor M.

    In 2005, Google, Microsoft and Yahoo! released free Web mapping applications that opened up digital mapping to mainstream Internet users. Importantly, these companies also released free APIs for their platforms, allowing users to geo-locate and map their own data. These initiatives have spurred the growth of the Geospatial Web and represent spatially aware online communities and new ways of enabling communities to share information from the bottom up. This chapter explores how the emerging Geospatial Web can meet some of the fundamental needs of Participatory GIS projects to incorporate local knowledge into GIS, as well as promote public access and collaborative mapping.

  1. Documenting Uncertainty and Error in Gridded Growing Degree Day and Spring Onset Maps Generated by the USA National Phenology Network

    Science.gov (United States)

    Crimmins, T. M.; Switzer, J.; Rosemartin, A.; Marsh, L.; Gerst, K.; Crimmins, M.; Weltzin, J. F.

    2016-12-01

    Since 2016 the USA National Phenology Network (USA-NPN; www.usanpn.org) has produced and delivered daily maps and short-term forecasts of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States. Because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening, and migration, these data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. We will be expanding the suite of gridded map products offered by the USA-NPN to include predictive species-specific maps of phenological transitions in plants and animals at fine spatial and temporal resolution in the future. Data products, such as the gridded maps currently produced by the USA-NPN, inherently contain uncertainty and error arising from multiple sources, including error propagated forward from underlying climate data and from the models implemented. As providing high-quality, vetted data in a transparent way is central to the USA-NPN, we aim to identify and report the sources and magnitude of uncertainty and error in gridded maps and forecast products. At present, we compare our real-time gridded products to independent, trustworthy data sources, such as the Climate Reference Network, on a daily basis and report Mean Absolute Error and bias through an interactive online dashboard.

  2. Social Distance Evaluation in Human Parietal Cortex

    Science.gov (United States)

    Yamakawa, Yoshinori; Kanai, Ryota; Matsumura, Michikazu; Naito, Eiichi

    2009-01-01

    Across cultures, social relationships are often thought of, described, and acted out in terms of physical space (e.g. “close friends” “high lord”). Does this cognitive mapping of social concepts arise from shared brain resources for processing social and physical relationships? Using fMRI, we found that the tasks of evaluating social compatibility and of evaluating physical distances engage a common brain substrate in the parietal cortex. The present study shows the possibility of an analytic brain mechanism to process and represent complex networks of social relationships. Given parietal cortex's known role in constructing egocentric maps of physical space, our present findings may help to explain the linguistic, psychological and behavioural links between social and physical space. PMID:19204791

  3. Mapping marine habitat suitability and uncertainty of Bayesian networks: a case study using Pacific benthic macrofauna

    Science.gov (United States)

    Andrea Havron; Chris Goldfinger; Sarah Henkel; Bruce G. Marcot; Chris Romsos; Lisa Gilbane

    2017-01-01

    Resource managers increasingly use habitat suitability map products to inform risk management and policy decisions. Modeling habitat suitability of data-poor species over large areas requires careful attention to assumptions and limitations. Resulting habitat suitability maps can harbor uncertainties from data collection and modeling processes; yet these limitations...

  4. Estimating missing hourly climatic data using artificial neural network for energy balance based ET mapping applications

    Science.gov (United States)

    Remote sensing based evapotranspiration (ET) mapping has become an important tool for water resources management at a regional scale. Accurate hourly climatic data and reference ET are crucial input for successfully implementing remote sensing based ET models such as Mapping ET with internal calibra...

  5. THE RAILMAPPER – A DEDICATED MOBILE LIDAR MAPPING SYSTEM FOR RAILWAY NETWORKS

    Directory of Open Access Journals (Sweden)

    J. Kremer

    2012-07-01

    Full Text Available The Mobile LiDAR Mapping System StreetMapper from IGI and 3D Laser Mapping (Bingham Nottingham, UK is mounted on a large variety of road vehicles to cover different mission specifications. In addition to the operation on the road, the system finds its applications on other kinds of vehicles, like boats or trains. The modular and flexible system concept even allows utilizing the same LiDAR Mapping system for Mobile Mapping on the ground and for airborne missions on helicopters, respectively. Besides this general flexibility, each application has its own special requirements. Special hardware and software components are needed to complete the core components, like the laser scanner and the GNSS/IMU systems, to build a dedicated system for the chosen task. Compared to the typical dynamics of a road vehicle mounted Mobile Mapping system, a dedicated rail mapping system operates under conditions that are much more challenging for a high accuracy GNSS/IMU trajectory determination. Furthermore, the typical rail mapping tasks, like the exact measurement of the rail track geometry, require the operation of the most accurate laser scanners and of specialized post-processing software. In this paper, the RailMapper, a specialized Mobile Mapping system for railway surveys is presented. The system is described with focus on the railway specific requirements and results of practical surveys are given.

  6. Animal movement network analysis as a tool to map farms serving as contamination source in cattle cysticercosis

    Directory of Open Access Journals (Sweden)

    Samuel C. Aragão

    Full Text Available ABSTRACT: Bovine cysticercosis is a problem distributed worldwide that result in economic losses mainly due to the condemnation of infected carcasses. One of the difficulties in applying control measures is the identification of the source of infection, especially because cattle are typically acquired from multiple farms. Here, we tested the utility of an animal movement network constructed with data from a farm that acquires cattle from several other different farms to map the major contributors of cysticercosis propagation. Additionally, based on the results of the network analysis, we deployed a sanitary management and drug treatment scheme to decrease cysticercosis’ occurrence in the farm. Six farms that had commercial trades were identified by the animal movement network and characterized as the main contributors to the occurrence of cysticercosis in the studied farm. The identification of farms with a putative risk of Taenia saginata infection using the animal movement network along with the proper sanitary management and drug treatment resulted in a gradual decrease in cysticercosis prevalence, from 25% in 2010 to 3.7% in 2011 and 1.8% in 2012. These results suggest that the animal movement network can contribute towards controlling bovine cysticercosis, thus minimizing economic losses and preventing human taeniasis.

  7. Extraction of Knowledge from the Topographic Attentive Mapping Network and its Application in Skill Analysis of Table Tennis

    Directory of Open Access Journals (Sweden)

    Hayashi Isao

    2017-01-01

    Full Text Available The Topographic Attentive Mapping (TAM network is a biologically-inspired classifier that bears similarities to the human visual system. In case of wrong classification during training, an attentional top-down signal modulates synaptic weights in intermediate layers to reduce the difference between the desired output and the classifier’s output. When used in a TAM network, the proposed pruning algorithm improves classification accuracy and allows extracting knowledge as represented by the network structure. In this paper, sport technique evaluation of motion analysis modelled by the TAM network was discussed. The trajectory pattern of forehand strokes of table tennis players was analyzed with nine sensor markers attached to the right upper arm of players. With the TAM network, input attributes and technique rules were extracted in order to classify the skill level of players of table tennis from the sensor data. In addition, differences between the elite player, middle level player and beginner were clarified; furthermore, we discussed how to improve skills specific to table tennis from the view of data analysis.

  8. Extraction of Knowledge from the Topographic Attentive Mapping Network and its Application in Skill Analysis of Table Tennis.

    Science.gov (United States)

    Hayashi, Isao; Fujii, Masanori; Maeda, Toshiyuki; Leveille, Jasmin; Tasaka, Tokio

    2017-01-01

    The Topographic Attentive Mapping (TAM) network is a biologically-inspired classifier that bears similarities to the human visual system. In case of wrong classification during training, an attentional top-down signal modulates synaptic weights in intermediate layers to reduce the difference between the desired output and the classifier's output. When used in a TAM network, the proposed pruning algorithm improves classification accuracy and allows extracting knowledge as represented by the network structure. In this paper, sport technique evaluation of motion analysis modelled by the TAM network was discussed. The trajectory pattern of forehand strokes of table tennis players was analyzed with nine sensor markers attached to the right upper arm of players. With the TAM network, input attributes and technique rules were extracted in order to classify the skill level of players of table tennis from the sensor data. In addition, differences between the elite player, middle level player and beginner were clarified; furthermore, we discussed how to improve skills specific to table tennis from the view of data analysis.

  9. Network analysis: a novel method for mapping neonatal acute transport patterns in California.

    Science.gov (United States)

    Kunz, S N; Zupancic, J A F; Rigdon, J; Phibbs, C S; Lee, H C; Gould, J B; Leskovec, J; Profit, J

    2017-06-01

    The objectives of this study are to use network analysis to describe the pattern of neonatal transfers in California, to compare empirical sub-networks with established referral regions and to determine factors associated with transport outside the originating sub-network. This cross-sectional database study included 6546 infants graph representing acute transfers between hospitals (n=6696), we used community detection techniques to identify more tightly connected sub-networks. These empirically derived sub-networks were compared with state-defined regional referral networks. Reasons for transfer between empirical sub-networks were assessed using logistic regression. Empirical sub-networks showed significant overlap with regulatory regions (P<0.001). Transfer outside the empirical sub-network was associated with major congenital anomalies (P<0.001), need for surgery (P=0.01) and insurance as the reason for transfer (P<0.001). Network analysis accurately reflected empirical neonatal transfer patterns, potentially facilitating quantitative, rather than qualitative, analysis of regionalized health care delivery systems.

  10. Network Analysis: A Novel Method for Mapping Neonatal Acute Transport Patterns in California

    Science.gov (United States)

    Kunz, Sarah N.; Zupancic, John A. F.; Rigdon, Joseph; Phibbs, Ciaran S.; Lee, Henry C.; Gould, Jeffrey B.; Leskovec, Jure; Profit, Jochen

    2017-01-01

    Objective To use network analysis to describe the pattern of neonatal transfers in California, to compare empirical sub-networks with established referral regions, and to determine factors associated with transport outside the originating sub-network. Study Design This cross-sectional database study included 6546 infants <28 days old transported within California in 2012. After generating a graph representing acute transfers between hospitals (n=6696), we used community detection techniques to identify more tightly connected sub-networks. These empirically-derived sub-networks were compared to state-defined regional referral networks. Reasons for transfer between empirical sub-networks were assessed using logistic regression. Results Empirical sub-networks showed significant overlap with regulatory regions (p <0.001). Transfer outside the empirical sub-network was associated with major congenital anomalies (p<0.001), need for surgery (p=0.01), and insurance as the reason for transfer (p<0.001). Conclusion Network analysis accurately reflected empirical neonatal transfer patterns, potentially facilitating quantitative, rather than qualitative, analysis of regionalized health care delivery systems. PMID:28333155

  11. Detecting tactical patterns in basketball: comparison of merge self-organising maps and dynamic controlled neural networks.

    Science.gov (United States)

    Kempe, Matthias; Grunz, Andreas; Memmert, Daniel

    2015-01-01

    The soaring amount of data, especially spatial-temporal data, recorded in recent years demands for advanced analysis methods. Neural networks derived from self-organizing maps established themselves as a useful tool to analyse static and temporal data. In this study, we applied the merge self-organising map (MSOM) to spatio-temporal data. To do so, we investigated the ability of MSOM's to analyse spatio-temporal data and compared its performance to the common dynamical controlled network (DyCoN) approach to analyse team sport position data. The position data of 10 players were recorded via the Ubisense tracking system during a basketball game. Furthermore, three different pre-selected plays were recorded for classification. Following data preparation, the different nets were trained with the data of the first half. The training success of both networks was evaluated by achieved entropy. The second half of the basketball game was presented to both nets for automatic classification. Both approaches were able to present the trained data extremely well and to detect the pre-selected plays correctly. In conclusion, MSOMs are a useful tool to analyse spatial-temporal data, especially in team sports. By their direct inclusion of different time length of tactical patterns, they open up new opportunities within team sports.

  12. Naturalistic fMRI Mapping Reveals Superior Temporal Sulcus as the Hub for the Distributed Brain Network for Social Perception

    Science.gov (United States)

    Lahnakoski, Juha M.; Glerean, Enrico; Salmi, Juha; Jääskeläinen, Iiro P.; Sams, Mikko; Hari, Riitta; Nummenmaa, Lauri

    2012-01-01

    Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-T functional magnetic resonance imaging (fMRI), a set of 137 short (approximately 16 s each, total 27 min) audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech) and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action, and non-human sounds) lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS) responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: (1) a fronto-temporal network responding to multiple social categories, (2) a fronto-parietal network preferentially activated to bodies, motion, and pain, (3) a temporo-amygdalar network responding to faces, social interaction, and speech, and (4) a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the pSTS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life. PMID:22905026

  13. Naturalistic fMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception

    Directory of Open Access Journals (Sweden)

    Juha Marko Lahnakoski

    2012-08-01

    Full Text Available Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-tesla functional magnetic imaging (fMRI, a set of 137 short (~16 s each, total 27 min audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action and non-human sounds lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: 1 a fronto-temporal network responding to multiple social categories, 2 a fronto-parietal network preferentially activated to bodies, motion and pain, 3 a temporo-amygdalar network responding to faces, social interaction and speech, and 4 a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the posterior STS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life.

  14. Naturalistic FMRI mapping reveals superior temporal sulcus as the hub for the distributed brain network for social perception.

    Science.gov (United States)

    Lahnakoski, Juha M; Glerean, Enrico; Salmi, Juha; Jääskeläinen, Iiro P; Sams, Mikko; Hari, Riitta; Nummenmaa, Lauri

    2012-01-01

    Despite the abundant data on brain networks processing static social signals, such as pictures of faces, the neural systems supporting social perception in naturalistic conditions are still poorly understood. Here we delineated brain networks subserving social perception under naturalistic conditions in 19 healthy humans who watched, during 3-T functional magnetic resonance imaging (fMRI), a set of 137 short (approximately 16 s each, total 27 min) audiovisual movie clips depicting pre-selected social signals. Two independent raters estimated how well each clip represented eight social features (faces, human bodies, biological motion, goal-oriented actions, emotion, social interaction, pain, and speech) and six filler features (places, objects, rigid motion, people not in social interaction, non-goal-oriented action, and non-human sounds) lacking social content. These ratings were used as predictors in the fMRI analysis. The posterior superior temporal sulcus (STS) responded to all social features but not to any non-social features, and the anterior STS responded to all social features except bodies and biological motion. We also found four partially segregated, extended networks for processing of specific social signals: (1) a fronto-temporal network responding to multiple social categories, (2) a fronto-parietal network preferentially activated to bodies, motion, and pain, (3) a temporo-amygdalar network responding to faces, social interaction, and speech, and (4) a fronto-insular network responding to pain, emotions, social interactions, and speech. Our results highlight the role of the pSTS in processing multiple aspects of social information, as well as the feasibility and efficiency of fMRI mapping under conditions that resemble the complexity of real life.

  15. Mapping dynamic social networks in real life using participants' own smartphones

    OpenAIRE

    Boonstra, Tjeerd W.; E. Larsen, Mark; Christensen, Helen

    2015-01-01

    Interpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing. Smartphones have great potential for measuring social networks in a real world setting. Here we tested the feasibility of using people's own smartphones as a data collection platform for face-to-face interac...

  16. Interactive Multimedia Distance Learning (IMDL)

    National Research Council Canada - National Science Library

    Christinaz, Daniel

    1999-01-01

    .... One avenue of investigation has been to evaluate emerging computer and network technologies to determine if training can be delivered at a distance more efficiently than traditional classroom training...

  17. The sound of distance.

    Science.gov (United States)

    Rabaglia, Cristina D; Maglio, Sam J; Krehm, Madelaine; Seok, Jin H; Trope, Yaacov

    2016-07-01

    Human languages may be more than completely arbitrary symbolic systems. A growing literature supports sound symbolism, or the existence of consistent, intuitive relationships between speech sounds and specific concepts. Prior work establishes that these sound-to-meaning mappings can shape language-related judgments and decisions, but do their effects generalize beyond merely the linguistic and truly color how we navigate our environment? We examine this possibility, relating a predominant sound symbolic distinction (vowel frontness) to a novel associate (spatial proximity) in five studies. We show that changing one vowel in a label can influence estimations of distance, impacting judgment, perception, and action. The results (1) provide the first experimental support for a relationship between vowels and spatial distance and (2) demonstrate that sound-to-meaning mappings have outcomes that extend beyond just language and can - through a single sound - influence how we perceive and behave toward objects in the world. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers

    Science.gov (United States)

    Chen, Hao; Zhu, Zhitu; Zhu, Yichun; Wang, Jian; Mei, Yunqing; Cheng, Yunfeng

    2015-01-01

    It is known that a disease is rarely a consequence of an abnormality of a single gene, but reflects the interactions of various processes in a complex network. Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers. The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein–protein or gene–gene interactions that can be monitored and evaluated at different stages and time-points during development of disease. Clinical bioinformatics as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics is crucial to translate biomarkers into clinical application, validate the disease specificity, and understand the role of biomarkers in clinical settings. In this article, the recent advances and developments on network biomarkers and DNBs are comprehensively reviewed. How network biomarkers help a better understanding of molecular mechanism of diseases, the advantages and constraints of network biomarkers for clinical application, clinical bioinformatics as a bridge to the development of diseases-specific, stage-specific, severity-specific and therapy predictive biomarkers, and the potentials of network biomarkers are also discussed. PMID:25560835

  19. Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers.

    Science.gov (United States)

    Chen, Hao; Zhu, Zhitu; Zhu, Yichun; Wang, Jian; Mei, Yunqing; Cheng, Yunfeng

    2015-02-01

    It is known that a disease is rarely a consequence of an abnormality of a single gene, but reflects the interactions of various processes in a complex network. Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers. The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein-protein or gene-gene interactions that can be monitored and evaluated at different stages and time-points during development of disease. Clinical bioinformatics as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics is crucial to translate biomarkers into clinical application, validate the disease specificity, and understand the role of biomarkers in clinical settings. In this article, the recent advances and developments on network biomarkers and DNBs are comprehensively reviewed. How network biomarkers help a better understanding of molecular mechanism of diseases, the advantages and constraints of network biomarkers for clinical application, clinical bioinformatics as a bridge to the development of diseases-specific, stage-specific, severity-specific and therapy predictive biomarkers, and the potentials of network biomarkers are also discussed. © 2015 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

  20. Single-subject morphological brain networks: connectivity mapping, topological characterization and test-retest reliability.

    Science.gov (United States)

    Wang, Hao; Jin, Xiaoqing; Zhang, Ye; Wang, Jinhui

    2016-04-01

    Structural MRI has long been used to characterize local morphological features of the human brain. Coordination patterns of the local morphological features among regions, however, are not well understood. Here, we constructed individual-level morphological brain networks and systematically examined their topological organization and long-term test-retest reliability under different analytical schemes of spatial smoothing, brain parcellation, and network type. This study included 57 healthy participants and all participants completed two MRI scan sessions. Individual morphological brain networks were constructed by estimating interregional similarity in the distribution of regional gray matter volume in terms of the Kullback-Leibler divergence measure. Graph-based global and nodal network measures were then calculated, followed by the statistical comparison and intra-class correlation analysis. The morphological brain networks were highly reproducible between sessions with significantly larger similarities for interhemispheric connections linking bilaterally homotopic regions. Further graph-based analyses revealed that the morphological brain networks exhibited nonrandom topological organization of small-worldness, high parallel efficiency and modular architecture regardless of the analytical choices of spatial smoothing, brain parcellation and network type. Moreover, several paralimbic and association regions were consistently revealed to be potential hubs. Nonetheless, the three studied factors particularly spatial smoothing significantly affected quantitative characterization of morphological brain networks. Further examination of long-term reliability revealed that all the examined network topological properties showed fair to excellent reliability irrespective of the analytical strategies, but performing spatial smoothing significantly improved reliability. Interestingly, nodal centralities were positively correlated with their reliabilities, and nodal degree

  1. Basic Geomagnetic Network of the Republic of Croatia 2004 – 2012, with Geomagnetic Field Maps for 2009.5 epoch

    Directory of Open Access Journals (Sweden)

    Mario Brkić

    2013-12-01

    Full Text Available After more than half a century, scientific book Basic Geomagnetic Network of the Republic of Croatia 2004 – 2012, with Geomagnetic Field Maps for 2009.5 epoch describes the recent geomagnetic field on Croatian territory. A review of research in the past decade as well as the original solutions makes the book a document of contribution to geodesy and geomagnetism in Croatia.The book’s introduction gives an overview of two centuries of history and the strategic, security, economic and scientific significance of knowing the geomagnetic field on the Croatian territory. All the activities related to the updating of the geomagnetic information, which took place in the last decade, signified a big step toward the countries where geomagnetic survey is a mature scientific and technical discipline, and a scientific contribution to understanding of the nature of the Earth's magnetism.The declination, inclination and total intensity maps (along with the normal annual changes for the epoch 2009.5 are given in the Appendix. The book Basic Geomagnetic Network of the Republic of Croatia 2004 – 2012, with Geomagnetic Field Maps for 2009.5 epoch (ISBN 978-953-293-521-9 is published by the State Geodetic Administration of the Republic of Croatia. Beside editor in chief, M. Brkić, the authors are: E. Vujić, D. Šugar, E. Jungwirth, D. Markovinović, M. Rezo, M. Pavasović, O. Bjelotomić, M. Šljivarić, M. Varga and V. Poslončec-Petrić. The book contains 48 pages and 3 maps, and is published in 200 copies. CIP record is available in digital catalogue of the National and University Library in Zagreb under number 861937.

  2. Development of a flood-warning network and flood-inundation mapping for the Blanchard River in Ottawa, Ohio

    Science.gov (United States)

    Whitehead, Matthew T.

    2011-01-01

    Digital flood-inundation maps of the Blanchard River in Ottawa, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service and the Village of Ottawa, Ohio. The maps, which correspond to water levels (stages) at the USGS streamgage at Ottawa (USGS streamgage site number 04189260), were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning Network that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. Flood profiles were computed by means of a step-backwater model calibrated to recent field measurements of streamflow. The step-backwater model was then used to determine water-surface-elevation profiles for 12 flood stages with corresponding streamflows ranging from less than the 2-year and up to nearly the 500-year recurrence-interval flood. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of the Village of Ottawa showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. As part of this flood-warning network, the USGS upgraded one streamgage and added two new streamgages, one on the Blanchard River and one on Riley Creek, which is tributary to the Blanchard River. The streamgage sites were equipped with both satellite and telephone telemetry. The telephone telemetry provides dual functionality, allowing village officials and the public to monitor current stage conditions and enabling the streamgage to call village officials with automated warnings regarding flood stage and/or predetermined rates of stage increase. Data from the streamgages serve as a flood warning that emergency management personnel can use in conjunction with the flood-inundation maps by to determine a course of action when flooding is imminent.

  3. Current Trends in Distance Education.

    Science.gov (United States)

    Gaspar, Richard F.; Thompson, Theron D.

    1995-01-01

    Defines distance education; provides a historical background; discusses emerging modes of instruction, including interactive television, computer-mediated communication, electronic mail, and national and international networks; and considers the future of distance education, including the use of the Internet, multimedia, and a new paradigm for…

  4. Transient analysis of a queue with queue-length dependent MAP and its application to SS7 network

    Directory of Open Access Journals (Sweden)

    Bong Dae Choi

    1999-01-01

    Full Text Available We analyze the transient behavior of a Markovian arrival queue with congestion control based on a double of thresholds, where the arrival process is a queue-length dependent Markovian arrival process. We consider Markov chain embedded at arrival epochs and derive the one-step transition probabilities. From these results, we obtain the mean delay and the loss probability of the nth arrival packet. Before we study this complex model, first we give a transient analysis of an MAP/M/1 queueing system without congestion control at arrival epochs. We apply our result to a signaling system No. 7 network with a congestion control based on thresholds.

  5. Sign conditions for injectivity of generalized polynomial maps with applications to chemical reaction networks and real algebraic geometry

    DEFF Research Database (Denmark)

    Müller, Stefan; Feliu, Elisenda; Regensburger, Georg

    2016-01-01

    We give necessary and sufficient conditions in terms of sign vectors for the injectivity of families of polynomials maps with arbitrary real exponents defined on the positive orthant. Our work relates and extends existing injectivity conditions expressed in terms of Jacobian matrices...... and determinants. In the context of chemical reaction networks with power-law kinetics, our results can be used to preclude as well as to guarantee multiple positive steady states. In the context of real algebraic geometry, our results reveal the first ...

  6. Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics

    Science.gov (United States)

    2016-03-31

    distribution unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT A new promising way to significantly improve computational efficiency of neurobiological network... Neurobiological Networks 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18. NUMBER 19a. NAME OF RESPONSIBLE PERSON a. REPORT b. ABSTRACT c. THIS

  7. Use of Tabu Search in a Solver to Map Complex Networks onto Emulab Testbeds

    Science.gov (United States)

    2007-03-01

    large number of chemical interactions between genes and proteins. • Complex networks often display a non-uniform distribution of connectivity among...02-base.html. 15. Huffaker, Bradley, Evi Nemeth, and K Claffy. “Otter: A General-purpose Network Visualization Tool”. In Proceedings of INET 1999

  8. Macroscopic networks in the human brain: mapping connectivity in healthy and damaged brains

    NARCIS (Netherlands)

    Nijhuis, E.H.J.

    2013-01-01

    The human brain contains a network of interconnected neurons. Recent advances in functional and structural in-vivo magnetic resonance neuroimaging (MRI) techniques have provided opportunities to model the networks of the human brain on a macroscopic scale. This dissertation investigates the

  9. Embedding global and collective in a torus network with message class map based tree path selection

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Dong; Coteus, Paul W.; Eisley, Noel A.; Gara, Alan; Heidelberger, Philip; Senger, Robert M; Salapura, Valentina; Steinmacher-Burow, Burkhard; Sugawara, Yutaka; Takken, Todd E.

    2016-06-21

    Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computer program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.

  10. [Map of the family social support network for the promotion of child development].

    Science.gov (United States)

    Alexandre, Ana Maria Cosvoski; Labronici, Liliana Maria; Maftum, Mariluci Alves; Mazza, Verônica de Azevedo

    2012-04-01

    This descriptive, qualitative study was performed from September to November 2009, at a Family Health Strategy unit in a city in the metropolitan region of Curitiba-PR. Participants were eight families, represented by mothers, fathers and grandmothers. The study objective was to identify the family social support network for the promotion of child development, from the family's perspective. Data were collected through focal groups and subjected to content analysis. The family social support network was classified as located, consisting of 16 members distributed between the informal and formal network, established by close relationships, with a smaller level of commitment, and occasional. It is considered that the health workers' understanding regarding the role and importance of this network favors the networking proposal between members that contribute to supporting families in the promotion of child development.

  11. Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

    Science.gov (United States)

    Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S

    2015-01-01

    The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.

  12. Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks

    Science.gov (United States)

    Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S.

    2015-01-01

    The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the “critical degree” (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology. PMID:26207631

  13. Mahalanobis Distance

    Indian Academy of Sciences (India)

    and G 2 might represent girls and boys, respectively or, in a medical diagnosis ... Representation of. Mahalanobis distance for the univariate case. GENERAL I ARTICLE. If the variables in X were uncorrelated in each group and were scaled so that they had ... have been proposed, and about thirty are known in the literature.

  14. DISTANCE EDUCATION

    African Journals Online (AJOL)

    take a longer period to get a degree and a greater number of learners can be reached than is possi- ble through .... distance learners and available funds, in short, a collection development policy. Infrastructure. In the long ..... gional centres could double as administrators. journal of science and technology, volume 25, no.

  15. Distance Education.

    Science.gov (United States)

    Feasley, Charles E.

    The magnitude, diversity, and impact of distance education are discussed in this international review of its implementation in economically diverse countries. Uses of the following media are described: (1) print--correspondence study, programmed instruction, modularized instruction, newspaper; (2) audio media--telephone, radio, subsidiary…

  16. [Distance Education.

    Science.gov (United States)

    Wallace, Teri, Ed.; Weatherman, Dick, Ed.

    1995-01-01

    This newsletter theme issue on distance education serving individuals with disabilities considers historical developments, technology, staff training strategies, and staff training materials. It is noted that improving access to training for staff members can improve the quality of services for individuals with disabilities. The following articles…

  17. Canceled connections: Lesion-derived network mapping helps explain differences in performance on a complex decision-making task

    Science.gov (United States)

    Sutterer, Matthew J.; Bruss, Joel; Boes, Aaron D.; Voss, Michelle W.; Bechara, Antoine; Tranel, Daniel

    2016-01-01

    Studies of patients with brain damage have highlighted a broad neural network of limbic and prefrontal areas as important for adaptive decision-making. However, some patients with damage outside these regions have impaired decision-making behavior, and the behavioral impairments observed in these cases are often attributed to the general variability in behavior following brain damage, rather than a deficit in a specific brain-behavior relationship. A novel approach, lesion-derived network mapping, uses healthy subject resting-state functional connectivity (RSFC) data to infer the areas that would be connected with each patient’s lesion area in healthy adults. Here, we used this approach to investigate whether there was a systematic pattern of connectivity associated with decision-making performance in patients with focal damage in areas not classically associated with decision-making. These patients were categorized a priori into “impaired” or “unimpaired” groups based on their performance on the Iowa Gambling Task (IGT). Lesion-derived network maps based on the impaired patients showed overlap in somatosensory, motor and insula cortices, to a greater extent than patients who showed unimpaired IGT performance. Akin to the classic concept of “diaschisis” (von Monakow, 1914), this focus on the remote effects that focal damage can have on large-scale distributed brain networks has the potential to inform not only differences in decision-making behavior, but also other cognitive functions or neurological syndromes where a distinct phenotype has eluded neuroanatomical classification and brain-behavior relationships appear highly heterogeneous. PMID:26994344

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

    Science.gov (United States)

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

    2017-11-01

    Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information, but relating the detected events to brain function remains a challenge. In this study, we developed a decoding method for SPFM using a coordinate-based meta-analysis method of activation likelihood estimation (ALE). We defined meta-maps of statistically significant ALE values that correspond to types of events and calculated a summation overlap between the normalized meta-maps and SPFM maps. As a proof of concept, this framework was applied to relate SPFM-detected events in the sensorimotor network (SMN) to six motor functions (left/right fingers, left/right toes, swallowing, and eye blinks). We validated the framework using simultaneous electromyography (EMG)-fMRI experiments and motor tasks with short and long duration, and random interstimulus interval. The decoding scores were considerably lower for eye movements relative to other movement types tested. The average successful rate for short and long motor events were 77 ± 13% and 74 ± 16%, respectively, excluding eye movements. We found good agreement between the decoding results and EMG for most events and subjects, with a range in sensitivity between 55% and 100%, excluding eye movements. The proposed method was then used to classify the movement types of spontaneous single-trial events in the SMN during resting state, which produced an average successful rate of 22 ± 12%. Finally, this article discusses methodological implications and improvements to increase the decoding performance. Hum Brain Mapp 38:5778-5794, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  19. Distributed algorithm to train neural networks using the Map Reduce paradigm

    Directory of Open Access Journals (Sweden)

    Cristian Mihai BARCA

    2017-07-01

    Full Text Available With rapid development of powerful computer systems during past decade, parallel and distributed processing becomes a significant resource for fast neural network training, even for real-time processing. Different parallel computing based methods have been proposed in recent years for the development of system performance. The two main methods are to distribute the patterns that are used for training - training set level parallelism, or to distribute the computation performed by the neural network - neural network level parallelism. In the present research work we have focused on the first method.

  20. The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults.

    Science.gov (United States)

    Habeck, C; Gazes, Y; Razlighi, Q; Steffener, J; Brickman, A; Barulli, D; Salthouse, T; Stern, Y

    2016-01-15

    Analyses of large test batteries administered to individuals ranging from young to old have consistently yielded a set of latent variables representing reference abilities (RAs) that capture the majority of the variance in age-related cognitive change: Episodic Memory, Fluid Reasoning, Perceptual Processing Speed, and Vocabulary. In a previous paper (Stern et al., 2014), we introduced the Reference Ability Neural Network Study, which administers 12 cognitive neuroimaging tasks (3 for each RA) to healthy adults age 20-80 in order to derive unique neural networks underlying these 4 RAs and investigate how these networks may be affected by aging. We used a multivariate approach, linear indicator regression, to derive a unique covariance pattern or Reference Ability Neural Network (RANN) for each of the 4 RAs. The RANNs were derived from the neural task data of 64 younger adults of age 30 and below. We then prospectively applied the RANNs to fMRI data from the remaining sample of 227 adults of age 31 and above in order to classify each subject-task map into one of the 4 possible reference domains. Overall classification accuracy across subjects in the sample age 31 and above was 0.80±0.18. Classification accuracy by RA domain was also good, but variable; memory: 0.72±0.32; reasoning: 0.75±0.35; speed: 0.79±0.31; vocabulary: 0.94±0.16. Classification accuracy was not associated with cross-sectional age, suggesting that these networks, and their specificity to the respective reference domain, might remain intact throughout the age range. Higher mean brain volume was correlated with increased overall classification accuracy; better overall performance on the tasks in the scanner was also associated with classification accuracy. For the RANN network scores, we observed for each RANN that a higher score was associated with a higher corresponding classification accuracy for that reference ability. Despite the absence of behavioral performance information in the

  1. Fast multi-class distance transforms for video surveillance

    NARCIS (Netherlands)

    Schouten, Theo E.; van den Broek, Egon; Kehtarnavaz, Nasser; Carlsohn, Matthias F.

    2008-01-01

    A distance transformation (DT) takes a binary image as input and generates a distance map image in which the value of each pixel is its distance to a given set of object pixels in the binary image. In this research, DT’s for multi class data (MCDTs) are developed which generate both a distance map

  2. Predicting functional neuroanatomical maps from fusing brain networks with genetic information.

    Science.gov (United States)

    Ganglberger, Florian; Kaczanowska, Joanna; Penninger, Josef M; Hess, Andreas; Bühler, Katja; Haubensak, Wulf

    2017-09-04

    Functional neuroanatomical maps provide a mesoscale reference framework for studies from molecular to systems neuroscience and psychiatry. The underlying structure-function relationships are typically derived from functional manipulations or imaging approaches. Although highly informative, these are experimentally costly. The increasing amount of publicly available brain and genetic data offers a rich source that could be mined to address this problem computationally. Here, we developed an algorithm that fuses gene expression and connectivity data with functional genetic meta data and exploits cumulative effects to derive neuroanatomical maps related to multi-genic functions. We validated the approach by using public available mouse and human data. The generated neuroanatomical maps recapture known functional anatomical annotations from literature and functional MRI data. When applied to multi-genic meta data from mouse quantitative trait loci (QTL) studies and human neuropsychiatric databases, this method predicted known functional maps underlying behavioral or psychiatric traits. Taken together, genetically weighted connectivity analysis (GWCA) allows for high throughput functional exploration of brain anatomy in silico. It maps functional genetic associations onto brain circuitry for refining functional neuroanatomy, or identifying trait-associated brain circuitry, from genetic data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  3. Using Co-authorship Networks to Map and Analyse Global Neglected Tropical Disease Research with an Affiliation to Germany.

    Directory of Open Access Journals (Sweden)

    Max Ernst Bender

    2015-12-01

    Full Text Available Research on Neglected Tropical Diseases (NTDs has increased in recent decades, and significant need-gaps in diagnostic and treatment tools remain. Analysing bibliometric data from published research is a powerful method for revealing research efforts, partnerships and expertise. We aim to identify and map NTD research networks in Germany and their partners abroad to enable an informed and transparent evaluation of German contributions to NTD research.A SCOPUS database search for articles with German author affiliations that were published between 2002 and 2012 was conducted for kinetoplastid and helminth diseases. Open-access tools were used for data cleaning and scientometrics (OpenRefine, geocoding (OpenStreetMaps and to create (Table2Net, visualise and analyse co-authorship networks (Gephi. From 26,833 publications from around the world that addressed 11 diseases, we identified 1,187 (4.4% with at least one German author affiliation, and we processed 972 publications for the five most published-about diseases. Of those, we extracted 4,007 individual authors and 863 research institutions to construct co-author networks. The majority of co-authors outside Germany were from high-income countries and Brazil. Collaborations with partners on the African continent remain scattered. NTD research within Germany was distributed among 220 research institutions. We identified strong performers on an individual level by using classic parameters (number of publications, h-index and social network analysis parameters (betweenness centrality. The research network characteristics varied strongly between diseases.The share of NTD publications with German affiliations is approximately half of its share in other fields of medical research. This finding underlines the need to identify barriers and expand Germany's otherwise strong research activities towards NTDs. A geospatial analysis of research collaborations with partners abroad can support decisions to

  4. Foreground removal from WMAP 5 yr temperature maps using an MLP neural network

    DEFF Research Database (Denmark)

    Nørgaard-Nielsen, Hans Ulrik

    2010-01-01

    CMB signal makes it essential to minimize the systematic errors in the CMB temperature determinations. Methods. The feasibility of using simple neural networks to extract the CMB signal from detailed simulated data has already been demonstrated. Here, simple neural networks are applied to the WMAP 5...... yr temperature data without using any auxiliary data. Results. A simple multilayer perceptron neural network with two hidden layers provides temperature estimates over more than 75 per cent of the sky with random errors significantly below those previously extracted from these data. Also......, the systematic errors, i.e. errors correlated with the Galactic foregrounds, are very small. Conclusions. With these results the neural network method is well prepared for dealing with the high-quality CMB data from the ESA Planck Surveyor satellite. © ESO, 2010....

  5. The Social Networks of Small Arms Proliferation: Mapping an Aviation Enabled Supply Chain

    National Research Council Canada - National Science Library

    Curwen, Philip A

    2007-01-01

    A complex network of dealers, brokers, financiers, and traffickers continue to funnel large quantities of small arms and ammunition into African conflict zones despite the presence of United Nations arms embargoes...

  6. Measurement and interpolation uncertainties in rainfall maps from cellular communication networks

    NARCIS (Netherlands)

    Rios Gaona, M.F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-01-01

    Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received

  7. Development of the Social Network-Based Intervention “Powerful Together with Diabetes” Using Intervention Mapping

    Directory of Open Access Journals (Sweden)

    Charlotte Vissenberg

    2017-12-01

    Full Text Available This article describes the development of the social network-based intervention Powerful Together with Diabetes which aims to improve diabetes self-management (DSM among patients with type 2 diabetes living in socioeconomically deprived neighborhoods by stimulating social support for DSM and diminishing social influences hindering DSM (e.g., peer pressure and social norms. The intervention was specifically developed for patients with Dutch, Turkish, Moroccan, and Surinamese backgrounds. The intervention was developed according to Intervention Mapping. This article describes the first four steps of Intervention Mapping: (1 the needs assessment; (2 development of performance and change objectives; (3 selection of theory-based methods and strategies; and (4 the translation of these into an organized program. These four steps resulted in Powerful Together with Diabetes, a 10-month group-based intervention consisting of 24 meetings, 6 meetings for significant others, and 2 meetings for participants and their spouses. The IM method resulted in a tailored approach with a specific focus on the social networks of its participants. This article concludes that the IM method helped our planning team to tailor the intervention to the needs of our target population and facilitated our evaluation design. However, in hindsight, the intervention could have been improved by investing more in participatory planning and community involvement.

  8. Distance learning

    Directory of Open Access Journals (Sweden)

    Katarina Pucelj

    2006-12-01

    Full Text Available I would like to underline the role and importance of knowledge, which is acquired by individuals as a result of a learning process and experience. I have established that a form of learning, such as distance learning definitely contributes to a higher learning quality and leads to innovative, dynamic and knowledgebased society. Knowledge and skills enable individuals to cope with and manage changes, solve problems and also create new knowledge. Traditional learning practices face new circumstances, new and modern technologies appear, which enable quick and quality-oriented knowledge implementation. The centre of learning process at distance learning is to increase the quality of life of citizens, their competitiveness on the workforce market and ensure higher economic growth. Intellectual capital is the one, which represents the biggest capital of each society and knowledge is the key factor for succes of everybody, who are fully aware of this. Flexibility, openness and willingness of people to follow new IT solutions form suitable environment for developing and deciding to take up distance learning.

  9. Battlefield Tourism at Gallipoli: The Revival of Collective Memory, the Construction of National Identity and the Making of a Long-distance Tourism Network

    Directory of Open Access Journals (Sweden)

    Elif Yeneroglu Kutbay

    2016-11-01

    Full Text Available The Battle of the Dardanelles (Çanakkale, also known as the Gallipoli Campaign, played a crucial role in the construction and endorsement of national identity, irrespective of the immediate consequences such as the prolongation of the war or the resignation of Winston Churchill upon failure. The Battle of the Dardanelles is commemorated every year in Turkey, Australia and New Zealand, as a day of remembrance. The battlefields at Dardanelles were reinstated as the Gallipoli Peninsula Historical National Park in 1973. The park covers numerous cemeteries of soldiers from both sides, memorials, museums and the battlefields in an area of 33,000 hectares. The park provides a vivid setting and depiction of the war experience, and stands out as the most important battlefield site in Turkey.The aim of this paper is to analyze battlefield tourism in Çanakkale in terms of its components and its impact on domestic and international tourism in Turkey. Battlefield tourism in Çanakkale encompasses not only the battlefield itself, but also the Çanakkale Victory Day in Turkey, March 18th, and the Anzac Day in Australia, April 25th. While domestic tourism contributes to the revival of collective memory and to the building of national identity, international tourism provides representations of national heritage as a source of political legitimacy. Unique to this case, battlefield tourism plays a significant role in the construction of a long-distance tourism network between Australia, and Turkey. The annual flow of descendants of ANZAC (Australian and New Zealand Army Corps soldiers is an important source of tourism activity in the area.

  10. VESGEN 2D: Automated, User-Interactive Software for Vascular Quantification and Mapping of Angiogenic and Lymphangiogenic Trees and Networks

    Science.gov (United States)

    Vickerman, Mary B.; Keith, Patricia A.; McKay, Terri L.; Gedeon, Dan J.; Watanabe, Michiko; Montano, Monica; Karunamuni, Ganga; Kaiser, Peter K.; Sears, Jonathan E.; Ebrahem, Quteba; Ribita, Daniela; Hylton, Alan G.; Parsons-Wingerter, Patricia

    2010-01-01

    Quantification of microvascular remodeling as a meaningful discovery tool requires mapping and measurement of site-specific changes within vascular trees and networks. Vessel density and other critical vascular parameters are often modulated by molecular regulators as determined by local vascular architecture. For example, enlargement of vessel diameter by vascular endothelial growth factor (VEGF) is restricted to specific generations of vessel branching (Microvascular Research 72(3):91, 2006). The averaging of vessel diameter over many successively smaller generations is therefore not particularly useful. The newly automated, user-interactive software VESGEN (VESsel GENeration Analysis) quantifies major vessel parameters within two-dimensional (2D) vascular trees, networks, and tree-network composites. This report reviews application of VESGEN 2D to angiogenic and lymphangiogenic tissues that includes the human and murine retina, embryonic coronary vessels, and avian chorioallantoic membrane (CAM). Software output includes colorized image maps with quantification of local vessel diameter, fractal dimension, tortuosity and avascular spacing. The density of parameters such as vessel area, length, number and branch point are quantified according to site-specific generational branching within vascular trees. The sole user input requirement is a binary (black/white) vascular image. Future applications of VESGEN will include analysis of 3D vascular architecture and bioinformatic dimensions such as blood flow and receptor localization. Branching analysis by VESGEN has demonstrated that numerous regulators including VEGF165, basic fibroblast growth factor (bFGF), transforming growth factor β-1 (TGFβ-1), angiostatin and the clinical steroid triamcinolone acetonide induce ‘fingerprint’ or ‘signature’ changes in vascular patterning that provide unique readouts of dominant molecular signaling. PMID:19248164

  11. Lung-MAP Launches: First Precision Medicine Trial From National Clinical Trials Network

    Science.gov (United States)

    A unique public-private collaboration today announced the initiation of the Lung Cancer Master Protocol (Lung-MAP) trial, a multi-drug, multi-arm, biomarker-driven clinical trial for patients with advanced squamous cell lung cancer. Squamous cell carcinom

  12. American cities, global networks: mapping the multiple geographies of globalization in the Americas

    NARCIS (Netherlands)

    Toly, N.J.; Bouteligier, S.; Smith, G.; Gibson, B.

    2012-01-01

    The mapping of advanced producer and financial service firms across global cities began to increase understanding of the role of cities in global governance, the presence and influence of cities in the shifting architecture of global political economy, and the role of globalization in shaping the

  13. Synchronous slowing down in coupled logistic maps via random network topology

    Science.gov (United States)

    Wang, Sheng-Jun; Du, Ru-Hai; Jin, Tao; Wu, Xing-Sen; Qu, Shi-Xian

    2016-03-01

    The speed and paths of synchronization play a key role in the function of a system, which has not received enough attention up to now. In this work, we study the synchronization process of coupled logistic maps that reveals the common features of low-dimensional dissipative systems. A slowing down of synchronization process is observed, which is a novel phenomenon. The result shows that there are two typical kinds of transient process before the system reaches complete synchronization, which is demonstrated by both the coupled multiple-period maps and the coupled multiple-band chaotic maps. When the coupling is weak, the evolution of the system is governed mainly by the local dynamic, i.e., the node states are attracted by the stable orbits or chaotic attractors of the single map and evolve toward the synchronized orbit in a less coherent way. When the coupling is strong, the node states evolve in a high coherent way toward the stable orbit on the synchronized manifold, where the collective dynamics dominates the evolution. In a mediate coupling strength, the interplay between the two paths is responsible for the slowing down. The existence of different synchronization paths is also proven by the finite-time Lyapunov exponent and its distribution.

  14. Mapping of rock types using a joint approach by combining the multivariate statistics, self-organizing map and Bayesian neural networks: an example from IODP 323 site

    Science.gov (United States)

    Karmakar, Mampi; Maiti, Saumen; Singh, Amrita; Ojha, Maheswar; Maity, Bhabani Sankar

    2017-07-01

    Modeling and classification of the subsurface lithology is very important to understand the evolution of the earth system. However, precise classification and mapping of lithology using a single framework are difficult due to the complexity and the nonlinearity of the problem driven by limited core sample information. Here, we implement a joint approach by combining the unsupervised and the supervised methods in a single framework for better classification and mapping of rock types. In the unsupervised method, we use the principal component analysis (PCA), K-means cluster analysis (K-means), dendrogram analysis, Fuzzy C-means (FCM) cluster analysis and self-organizing map (SOM). In the supervised method, we use the Bayesian neural networks (BNN) optimized by the Hybrid Monte Carlo (HMC) (BNN-HMC) and the scaled conjugate gradient (SCG) (BNN-SCG) techniques. We use P-wave velocity, density, neutron porosity, resistivity and gamma ray logs of the well U1343E of the Integrated Ocean Drilling Program (IODP) Expedition 323 in the Bering Sea slope region. While the SOM algorithm allows us to visualize the clustering results in spatial domain, the combined classification schemes (supervised and unsupervised) uncover the different patterns of lithology such of as clayey-silt, diatom-silt and silty-clay from an un-cored section of the drilled hole. In addition, the BNN approach is capable of estimating uncertainty in the predictive modeling of three types of rocks over the entire lithology section at site U1343. Alternate succession of clayey-silt, diatom-silt and silty-clay may be representative of crustal inhomogeneity in general and thus could be a basis for detail study related to the productivity of methane gas in the oceans worldwide. Moreover, at the 530 m depth down below seafloor (DSF), the transition from Pliocene to Pleistocene could be linked to lithological alternation between the clayey-silt and the diatom-silt. The present results could provide the basis for

  15. Foreground removal from CMB temperature maps using an MLP neural network

    DEFF Research Database (Denmark)

    Nørgaard-Nielsen, Hans Ulrik; Jørgensen, H.E.

    2008-01-01

    CMB signal it is essential to minimize the systematic errors in the CMB temperature determinations. Following the available knowledge of the spectral behavior of the Galactic foregrounds simple power law-like spectra have been assumed. The feasibility of using a simple neural network for extracting...... the CMB temperature signal from the combined signal CMB and the foregrounds has been investigated. As a specific example, we have analysed simulated data, as expected from the ESA Planck CMB mission. A simple multilayer perceptron neural network with 2 hidden layers can provide temperature estimates over...... more than 80 per cent of the sky that are to a high degree uncorrelated with the foreground signals. A single network will be able to cover the dynamic range of the Planck noise level over the entire sky....

  16. Redrawing the map of Great Britain from a network of human interactions.

    Directory of Open Access Journals (Sweden)

    Carlo Ratti

    Full Text Available Do regional boundaries defined by governments respect the more natural ways that people interact across space? This paper proposes a novel, fine-grained approach to regional delineation, based on analyzing networks of billions of individual human transactions. Given a geographical area and some measure of the strength of links between its inhabitants, we show how to partition the area into smaller, non-overlapping regions while minimizing the disruption to each person's links. We tested our method on the largest non-Internet human network, inferred from a large telecommunications database in Great Britain. Our partitioning algorithm yields geographically cohesive regions that correspond remarkably well with administrative regions, while unveiling unexpected spatial structures that had previously only been hypothesized in the literature. We also quantify the effects of partitioning, showing for instance that the effects of a possible secession of Wales from Great Britain would be twice as disruptive for the human network than that of Scotland.

  17. Mapping Judicial Dialogue across National Borders: An Exploratory Network Study of Learning from Lobbying among European Intellectual Property Judges

    Directory of Open Access Journals (Sweden)

    Emmanuel Lazega

    2012-05-01

    Full Text Available This paper looks at dialogue and collective learning across borders through personal networks of judges. We focus on judges participating in the Venice Forum, bringing together European patent judges involved in institutional lobbying for the construction of a European Patent Court. Empirical observation shows that personal networks of discussion with foreign judges, reading of their work and references to their decisions do exist in this milieu and can be mapped. Our network study shows that judges from some European countries are more active in this dialogue than judges from other countries. The learning process is driven, to some extent, by a small subset of super-central judges who frame this dialogue and can be considered to be opinion leaders in this social milieu. We measure a strong level of consensus among the judges on several controversial issues surrounding the procedure of a possible future European Patent Court. But strong differences between them remain. Dialogue and collective learning do not, by themselves, lead to convergence towards a uniform position in these controversies.

  18. "It's not necessarily the distance on the map...": using place as an analytic tool to elucidate geographic issues central to rural palliative care.

    Science.gov (United States)

    Castleden, Heather; Crooks, Valorie A; Schuurman, Nadine; Hanlon, Neil

    2010-03-01

    Palliative care is intimately connected with place, yet little research has explored these relationships in depth, especially with respect to rural and remote settings. This paper uses multiple dimensions of the concept 'place' as an analytic tool to understand the nature of palliative care provision in a rural region of British Columbia, Canada. We draw upon primary data from formal and informal providers (n = 31) to explore the social and physical place of rural palliative care. We unpack four highly geographic issues raised by participants, namely: (1) distance, (2) location, (3) aesthetics, and (4) sites of care. This analysis reveals a rich and complex experience of rural care-giving long overlooked in palliative care research and policy. Copyright 2009 Elsevier Ltd. All rights reserved.

  19. Social Network Trend Analysis Using Frequent Pattern Mining and Self Organizing Maps

    Science.gov (United States)

    Nohuddin, Puteri N. E.; Christley, Rob; Coenen, Frans; Patel, Yogesh; Setzkorn, Christian; Williams, Shane

    A technique for identifying, grouping and analysing trends in social networks is described. The trends of interest are defined in terms of sequences of support values for specific patterns that appear across a given social network. The trends are grouped using a SOM technique so that similar tends are clustered together. A cluster analysis technique is then applied to identify "interesting" trends. The focus of the paper is the Cattle Tracing System (CTS) database in operation in Great Britain, and this is therefore the focus of the evaluation. However, to illustrate the wider applicability of the trend mining technique, experiments using a more standard, car insurance, temporal database are also described.

  20. GOING THE DISTANCE: MAPPING HOST GALAXIES OF LIGO AND VIRGO SOURCES IN THREE DIMENSIONS USING LOCAL COSMOGRAPHY AND TARGETED FOLLOW-UP

    Energy Technology Data Exchange (ETDEWEB)

    Singer, Leo P.; Cenko, S. Bradley; Gehrels, Neil; Cannizzo, John [Astroparticle Physics Laboratory, NASA Goddard Space Flight Center, Mail Code 661, Greenbelt, MD 20771 (United States); Chen, Hsin-Yu; Holz, Daniel E.; Farr, Ben [Department of Physics, Enrico Fermi Institute, and Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637 (United States); Farr, Will M.; Veitch, John; Berry, Christopher P. L.; Mandel, Ilya [School of Physics and Astronomy, University of Birmingham, Birmingham, B15 2TT (United Kingdom); Price, Larry R.; Raymond, Vivien [LIGO Laboratory, California Institute of Technology, Pasadena, CA 91125 (United States); Kasliwal, Mansi M. [Cahill Center for Astrophysics, California Institute of Technology, Pasadena, CA 91125 (United States); Nissanke, Samaya [Institute of Mathematics, Astrophysics and Particle Physics, Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen (Netherlands); Coughlin, Michael [Department of Physics and Astronomy, Harvard University, Cambridge, MA 02138 (United States); Urban, Alex L. [Leonard E. Parker Center for Gravitation, Cosmology, and Astrophysics, University of Wisconsin–Milwaukee, Milwaukee, WI 53201 (United States); Vitale, Salvatore; Mohapatra, Satya [LIGO Laboratory, Massachusetts Institute of Technology, 185 Albany Street, Cambridge, MA 02139 (United States); Graff, Philip [Department of Physics, University of Maryland, College Park, MD 20742 (United States)

    2016-09-20

    The Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) discovered gravitational waves (GWs) from a binary black hole merger in 2015 September and may soon observe signals from neutron star mergers. There is considerable interest in searching for their faint and rapidly fading electromagnetic (EM) counterparts, though GW position uncertainties are as coarse as hundreds of square degrees. Because LIGO’s sensitivity to binary neutron stars is limited to the local universe, the area on the sky that must be searched could be reduced by weighting positions by mass, luminosity, or star formation in nearby galaxies. Since GW observations provide information about luminosity distance, combining the reconstructed volume with positions and redshifts of galaxies could reduce the area even more dramatically. A key missing ingredient has been a rapid GW parameter estimation algorithm that reconstructs the full distribution of sky location and distance. We demonstrate the first such algorithm, which takes under a minute, fast enough to enable immediate EM follow-up. By combining the three-dimensional posterior with a galaxy catalog, we can reduce the number of galaxies that could conceivably host the event by a factor of 1.4, the total exposure time for the Swift X-ray Telescope by a factor of 2, the total exposure time for a synoptic optical survey by a factor of 2, and the total exposure time for a narrow-field optical telescope by a factor of 3. This encourages us to suggest a new role for small field of view optical instruments in performing targeted searches of the most massive galaxies within the reconstructed volumes.

  1. ShakeMap

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — ShakeMap is a product of the USGS Earthquake Hazards Program in conjunction with the regional seismic networks. ShakeMaps provide near-real-time maps of ground...

  2. Mapping the structural and functional network architecture of the medial temporal lobe using 7T MRI.

    Science.gov (United States)

    Shah, Preya; Bassett, Danielle S; Wisse, Laura E M; Detre, John A; Stein, Joel M; Yushkevich, Paul A; Shinohara, Russell T; Pluta, John B; Valenciano, Elijah; Daffner, Molly; Wolk, David A; Elliott, Mark A; Litt, Brian; Davis, Kathryn A; Das, Sandhitsu R

    2018-02-01

    Medial temporal lobe (MTL) subregions play integral roles in memory function and are differentially affected in various neurological and psychiatric disorders. The ability to structurally and functionally characterize these subregions may be important to understanding MTL physiology and diagnosing diseases involving the MTL. In this study, we characterized network architecture of the MTL in healthy subjects (n = 31) using both resting state functional MRI and MTL-focused T2-weighted structural MRI at 7 tesla. Ten MTL subregions per hemisphere, including hippocampal subfields and cortical regions of the parahippocampal gyrus, were segmented for each subject using a multi-atlas algorithm. Both structural covariance matrices from correlations of subregion volumes across subjects, and functional connectivity matrices from correlations between subregion BOLD time series were generated. We found a moderate structural and strong functional inter-hemispheric symmetry. Several bilateral hippocampal subregions (CA1, dentate gyrus, and subiculum) emerged as functional network hubs. We also observed that the structural and functional networks naturally separated into two modules closely corresponding to (a) bilateral hippocampal formations, and (b) bilateral extra-hippocampal structures. Finally, we found a significant correlation in structural and functional connectivity (r = 0.25). Our findings represent a comprehensive analysis of network topology of the MTL at the subregion level. We share our data, methods, and findings as a reference for imaging methods and disease-based research. © 2017 Wiley Periodicals, Inc.

  3. Digital Mapping of Soil Texture Using Regression Tree and Artificial Neural Network in Bijar, Kurdistan

    OpenAIRE

    kamal nabiollahi; ahmad haidari; rohollah taghizade mehrjardi

    2015-01-01

    Soil texture is an important soil physical property that governs most physical, chemical, biological, and hydrological processes in soils. Detailed information on soil texture variability is crucial for proper crop and land management and environmental studies. Therefore, at present research, 103 soil profiles were dogged and then sampled in order to prepare digital map of soil texture in Bijar, Kurdistan. Auxiliary data used in this study to represent predictive soil forming factors were ter...

  4. American cities, global networks: mapping the multiple geographies of globalization in the Americas

    OpenAIRE

    Toly, N.J.; Bouteligier, S.; Smith, G.; Gibson, B.

    2012-01-01

    The mapping of advanced producer and financial service firms across global cities began to increase understanding of the role of cities in global governance, the presence and influence of cities in the shifting architecture of global political economy, and the role of globalization in shaping the landscape of local and re- gional governance. The literature that emerged from such studies has also emphasized 1) increasing levels of inequality in global cities and 2) attendant contests over loca...

  5. Integrating Lesion-Symptom Mapping with Other Methods to Investigate Language Networks and Aphasia Recovery

    Directory of Open Access Journals (Sweden)

    Peter E Turkeltaub

    2015-04-01

    Full Text Available Voxel-based lesion-symptom mapping (VLSM has provided valuable insights into the neural underpinnings of various language functions. Integrating lesion mapping methods with other neuroscience techniques may provide new opportunities to investigate questions related both to the neurobiology of language and to plasticity after brain injury. For example, recent diffusion tensor imaging studies have explored relationships between aphasia symptomology and damage in specific white matter tracts (Forkel et al., 2014 or disruption of the white matter connectome (Bonilha, Rorden, & Fridriksson, 2014. VLSM has also recently been used to assess correlations between lesion location and response to transcranial direct current stimulation aphasia treatment (Campana, Caltagirone, & Marangolo, 2015. We have recently undertaken studies integrating VLSM with other techniques, including voxel-based morphometry (VBM and functional MRI, in order to investigate how parts of the brain spared by stroke contribute to recovery. VLSM can be used in this context to map lesions associated with particular patterns of plasticity in brain structure, function, or connectivity. We have also used VLSM to estimate the variance in behavior due to the stroke itself so that this lesion-symptom relationship can be controlled for when examining the contributions of the rest of the brain. Using this approach in combination with VBM, we have identified areas of the right temporoparietal cortex that appear to undergo hypertrophy after stroke and compensate for speech production deficits. In this talk, I will review recent advances in integrating lesion-symptom mapping with other imaging and brain stimulation techniques in order to better understand the brain basis of language and of aphasia recovery.

  6. A Monitoring Network to Map and Assess Landslide Activity in a Highly Anthropized Area

    Directory of Open Access Journals (Sweden)

    Giulia Bossi

    2016-09-01

    Full Text Available Mapping landslide activity in a highly anthropized area entails specific problems. The integration of different monitoring techniques in order to measure the displacements rate within the slope is mandatory. We describe our activity for the Mortisa landslide which is located on the western flank of the Cortina d’Ampezzo valley (northeastern Italy in a highly anthropized area in the heart of the Dolomites, a UNESCO world heritage site. The mass movement threatens some houses, an important national road, and part of the area that will be the venue for the upcoming 2021 Alpine Skiing World Championship. The hazardous context along with its prestigious location makes the construction of new settlements and infrastructure very challenging. Owing to that, precise mapping and assessment of the activity of the Mortisa landslide is extremely important. To achieve this task, multitemporal aerial photo interpretation, A-DInSAR analysis, Global Navigation Satellite System (GNSS surveys, and inclinometric measurements were performed. Through the integration of the monitoring data and geomorphological interpretation, a hazard map of the Mortisa area was produced with the intent to assist the local authorities in the definition of the new urban development plan.

  7. Intraoperative dorsal language network mapping by using single-pulse electrical stimulation.

    Science.gov (United States)

    Yamao, Yukihiro; Matsumoto, Riki; Kunieda, Takeharu; Arakawa, Yoshiki; Kobayashi, Katsuya; Usami, Kiyohide; Shibata, Sumiya; Kikuchi, Takayuki; Sawamoto, Nobukatsu; Mikuni, Nobuhiro; Ikeda, Akio; Fukuyama, Hidenao; Miyamoto, Susumu

    2014-09-01

    The preservation of language function during brain surgery still poses a challenge. No intraoperative methods have been established to monitor the language network reliably. We aimed to establish intraoperative language network monitoring by means of cortico-cortical evoked potentials (CCEPs). Subjects were six patients with tumors located close to the arcuate fasciculus (AF) in the language-dominant left hemisphere. Under general anesthesia, the anterior perisylvian language area (AL) was first defined by the CCEP connectivity patterns between the ventrolateral frontal and temporoparietal area, and also by presurgical neuroimaging findings. We then monitored the integrity of the language network by stimulating AL and by recording CCEPs from the posterior perisylvian language area (PL) consecutively during both general anesthesia and awake condition. High-frequency electrical stimulation (ES) performed during awake craniotomy confirmed language function at AL in all six patients. Despite an amplitude decline (≤32%) in two patients, CCEP monitoring successfully prevented persistent language impairment. After tumor removal, single-pulse ES was applied to the white matter tract beneath the floor of the removal cavity in five patients, in order to trace its connections into the language cortices. In three patients in whom high-frequency ES of the white matter produced naming impairment, this "eloquent" subcortical site directly connected AL and PL, judging from the latencies and distributions of cortico- and subcortico-cortical evoked potentials. In conclusion, this study provided the direct evidence that AL, PL, and AF constitute the dorsal language network. Intraoperative CCEP monitoring is clinically useful for evaluating the integrity of the language network. Copyright © 2014 Wiley Periodicals, Inc.

  8. Mapping the structure and dynamics of genomics-related MeSH terms complex networks.

    Directory of Open Access Journals (Sweden)

    Jesús M Siqueiros-García

    Full Text Available It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appearance of the term Genomics to 2011, categorized by means of the Medical Subheadings (MeSH content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s. The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-structure, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms.

  9. Mapping the structure and dynamics of genomics-related MeSH terms complex networks.

    Science.gov (United States)

    Siqueiros-García, Jesús M; Hernández-Lemus, Enrique; García-Herrera, Rodrigo; Robina-Galatas, Andrea

    2014-01-01

    It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appearance of the term Genomics) to 2011, categorized by means of the Medical Subheadings (MeSH) content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s). The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-structure, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms.

  10. An eQTL mapping approach reveals that rare variants in the SEMA5A regulatory network impact autism risk.

    Science.gov (United States)

    Cheng, Ye; Quinn, Jeffrey Francis; Weiss, Lauren Anne

    2013-07-15

    To date, genome-wide single nucleotide polymorphism (SNP) and copy number variant (CNV) association studies of autism spectrum disorders (ASDs) have led to promising signals but not to easily interpretable or translatable results. Our own genome-wide association study (GWAS) showed significant association to an intergenic SNP near Semaphorin 5A (SEMA5A) and provided evidence for reduced expression of the same gene. In a novel GWAS follow-up approach, we map an expression regulatory pathway for a GWAS candidate gene, SEMA5A, in silico by using population expression and genotype data sets. We find that the SEMA5A regulatory network significantly overlaps rare autism-specific CNVs. The SEMA5A regulatory network includes previous autism candidate genes and regions, including MACROD2, A2BP1, MCPH1, MAST4, CDH8, CADM1, FOXP1, AUTS2, MBD5, 7q21, 20p, USH2A, KIRREL3, DBF4B and RELN, among others. Our results provide: (i) a novel data-derived network implicated in autism, (ii) evidence that the same pathway seeded by an initial SNP association shows association with rare genetic variation in ASDs, (iii) a potential mechanism of action and interpretation for the previous autism candidate genes and genetic variants that fall in this network, and (iv) a novel approach that can be applied to other candidate genes for complex genetic disorders. We take a step towards better understanding of the significance of SEMA5A pathways in autism that can guide interpretation of many other genetic results in ASDs.

  11. Mapping Power Law Distributions in Digital Health Social Networks: Methods, Interpretations, and Practical Implications.

    Science.gov (United States)

    van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

    2015-06-25

    Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R(2) values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns can be replicated in networks that are managed by

  12. Distance hijacking attacks on distance bounding protocols

    OpenAIRE

    Cremers, Cas; Rasmussen, Kasper Bonne; Čapkun, Srdjan

    2011-01-01

    Distance bounding protocols are typically analyzed with respect to three types of attacks: Distance Fraud, Mafia Fraud, and Terrorist Fraud. We define and analyze a fourth main type of attack on distance bounding protocols, called Distance Hijacking. We show that many proposed distance bounding protocols are vulnerable to this type of attack, and we propose solutions to make these protocols resilient to Distance Hijacking. We further show that verifying distance bounding protocols using exist...

  13. Distance hijacking attacks on distance bounding protocols

    OpenAIRE

    Cremers, Cas; Rasmussen, Kasper Bonne; Čapkun, Srdjan

    2011-01-01

    Distance bounding protocols are typically analyzed with respect to three types of attacks: Distance Fraud, Mafia Fraud, and Terrorist Fraud. We define a fourth main type of attacks on distance bounding protocols, called Distance Hijacking attacks. We show that many proposed distance bounding protocols are vulnerable to these attacks, and we propose solutions to make these protocols resilient to Distance Hijacking. Additionally, we generalize Distance Hijacking to Location Hijacking, to which ...

  14. Mapping the social class structure: From occupational mobility to social class categories using network analysis

    DEFF Research Database (Denmark)

    Toubøl, Jonas; Larsen, Anton Grau

    2017-01-01

    This article develops a new explorative method for deriving social class categories from patterns of occupational mobility. In line with Max Weber, our research is based on the notion that, if class boundaries do not inhibit social mobility then the class categories are of little value. Thus......, unlike dominant, theoretically defined class schemes, this article derives social class categories from observed patterns in a mobility network covering intra-generational mobility. The network is based on a mobility table of 109 occupational categories tied together by 1,590,834 job shifts on the Danish...... labour market 2001–2007. The number of categories are reduced from 109 to 34 by applying a new clustering algorithm specifically designed for the study of mobility tables (MONECA). These intra-generational social class categories are related to the central discussions of gender, income, education...

  15. A social network analysis of Twitter: Mapping the digital humanities community

    Directory of Open Access Journals (Sweden)

    Martin Grandjean

    2016-12-01

    Full Text Available Defining digital humanities might be an endless debate if we stick to the discussion about the boundaries of this concept as an academic “discipline”. In an attempt to concretely identify this field and its actors, this paper shows that it is possible to analyse them through Twitter, a social media widely used by this “community of practice”. Based on a network analysis of 2,500 users identified as members of this movement, the visualisation of the “who’s following who?” graph allows us to highlight the structure of the network’s relationships, and identify users whose position is particular. Specifically, we show that linguistic groups are key factors to explain clustering within a network whose characteristics look similar to a small world.

  16. Analysis of short single rest/activation epoch fMRI by self-organizing map neural network

    Science.gov (United States)

    Erberich, Stephan G.; Dietrich, Thomas; Kemeny, Stefan; Krings, Timo; Willmes, Klaus; Thron, Armin; Oberschelp, Walter

    2000-04-01

    Functional magnet resonance imaging (fMRI) has become a standard non invasive brain imaging technique delivering high spatial resolution. Brain activation is determined by magnetic susceptibility of the blood oxygen level (BOLD effect) during an activation task, e.g. motor, auditory and visual tasks. Usually box-car paradigms have 2 - 4 rest/activation epochs with at least an overall of 50 volumes per scan in the time domain. Statistical test based analysis methods need a large amount of repetitively acquired brain volumes to gain statistical power, like Student's t-test. The introduced technique based on a self-organizing neural network (SOM) makes use of the intrinsic features of the condition change between rest and activation epoch and demonstrated to differentiate between the conditions with less time points having only one rest and one activation epoch. The method reduces scan and analysis time and the probability of possible motion artifacts from the relaxation of the patients head. Functional magnet resonance imaging (fMRI) of patients for pre-surgical evaluation and volunteers were acquired with motor (hand clenching and finger tapping), sensory (ice application), auditory (phonological and semantic word recognition task) and visual paradigms (mental rotation). For imaging we used different BOLD contrast sensitive Gradient Echo Planar Imaging (GE-EPI) single-shot pulse sequences (TR 2000 and 4000, 64 X 64 and 128 X 128, 15 - 40 slices) on a Philips Gyroscan NT 1.5 Tesla MR imager. All paradigms were RARARA (R equals rest, A equals activation) with an epoch width of 11 time points each. We used the self-organizing neural network implementation described by T. Kohonen with a 4 X 2 2D neuron map. The presented time course vectors were clustered by similar features in the 2D neuron map. Three neural networks were trained and used for labeling with the time course vectors of one, two and all three on/off epochs. The results were also compared by using a

  17. Improving the Understanding of Pathogenesis of Human Papillomavirus 16 via Mapping Protein-Protein Interaction Network

    OpenAIRE

    Yongcheng Dong; Qifan Kuang; Xu Dai; Rong Li; Yiming Wu; Weijia Leng; Yizhou Li; Menglong Li

    2015-01-01

    The human papillomavirus 16 (HPV16) has high risk to lead various cancers and afflictions, especially, the cervical cancer. Therefore, investigating the pathogenesis of HPV16 is very important for public health. Protein-protein interaction (PPI) network between HPV16 and human was used as a measure to improve our understanding of its pathogenesis. By adopting sequence and topological features, a support vector machine (SVM) model was built to predict new interactions between HPV16 and human p...

  18. Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

    Directory of Open Access Journals (Sweden)

    Sriram Chandrasekaran

    2017-12-01

    Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

  19. Mapping university students’ epistemic framing of computational physics using network analysis

    Directory of Open Access Journals (Sweden)

    Madelen Bodin

    2012-04-01

    Full Text Available Solving physics problem in university physics education using a computational approach requires knowledge and skills in several domains, for example, physics, mathematics, programming, and modeling. These competences are in turn related to students’ beliefs about the domains as well as about learning. These knowledge and beliefs components are referred to here as epistemic elements, which together represent the students’ epistemic framing of the situation. The purpose of this study was to investigate university physics students’ epistemic framing when solving and visualizing a physics problem using a particle-spring model system. Students’ epistemic framings are analyzed before and after the task using a network analysis approach on interview transcripts, producing visual representations as epistemic networks. The results show that students change their epistemic framing from a modeling task, with expectancies about learning programming, to a physics task, in which they are challenged to use physics principles and conservation laws in order to troubleshoot and understand their simulations. This implies that the task, even though it is not introducing any new physics, helps the students to develop a more coherent view of the importance of using physics principles in problem solving. The network analysis method used in this study is shown to give intelligible representations of the students’ epistemic framing and is proposed as a useful method of analysis of textual data.

  20. Polarization-interference Jones-matrix mapping of biological crystal networks

    Science.gov (United States)

    Ushenko, O. G.; Dubolazov, O. V.; Pidkamin, L. Y.; Sidor, M. I.; Pavlyukovich, N.; Pavlyukovich, O.

    2018-01-01

    The paper consists of two parts. The first part presents short theoretical basics of the method of Jones-matrix mapping with the help of reference wave. It was provided experimentally measured coordinate distributions of modulus of Jones-matrix elements of polycrystalline film of bile. It was defined the values and ranges of changing of statistic moments, which characterize such distributions. The second part presents the data of statistic analysis of the distributions of matrix elements of polycrystalline film of urine of donors and patients with albuminuria. It was defined the objective criteria of differentiation of albuminuria.

  1. A compendium of inborn errors of metabolism mapped onto the human metabolic network.

    OpenAIRE

    Sahoo, Swagatika; Franzson, Leifur; Jonsson, Jon J; Thiele, Ines

    2012-01-01

    Efst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn Inborn errors of metabolism (IEMs) are hereditary metabolic defects, which are encountered in almost all major metabolic pathways occurring in man. Many IEMs are screened for in neonates through metabolomic analysis of dried blood spot samples. To enable the mapping of these metabolomic data onto the published human metabolic reconstruction, we added missing reactions and pathways involved in acylcarnitin...

  2. 3D reconstruction and standardization of the rat facial nucleus for precise mapping of vibrissal motor networks.

    Science.gov (United States)

    Guest, Jason M; Seetharama, Mythreya M; Wendel, Elizabeth S; Strick, Peter L; Oberlaender, Marcel

    2017-09-27

    The rodent facial nucleus (FN) comprises motoneurons (MNs) that control the facial musculature. In the lateral part of the FN, populations of vibrissal motoneurons (vMNs) innervate two groups of muscles that generate movements of the whiskers. Vibrissal MNs thus represent the terminal point of the neuronal networks that generate rhythmic whisking during exploratory behaviors and that modify whisker movements based on sensory-motor feedback during tactile-based perception. Here, we combined retrograde tracer injections into whisker-specific muscles, with large-scale immunohistochemistry and digital reconstructions to generate an average model of the rat FN. The model incorporates measurements of the FN geometry, its cellular organization and a whisker row-specific map formed by vMNs. Furthermore, the model provides a digital 3D reference frame that allows registering structural data - obtained across scales and animals - into a common coordinate system with a precision of ∼60 µm. We illustrate the registration method by injecting replication competent rabies virus into the muscle of a single whisker. Retrograde transport of the virus to vMNs enabled reconstruction of their dendrites. Subsequent trans-synaptic transport enabled mapping the presynaptic neurons of the reconstructed vMNs. Registration of these data to the FN reference frame provides a first account of the morphological and synaptic input variability within a population of vMNs that innervate the same muscle. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks

    Science.gov (United States)

    Meng, Qinggang; Lee, M. H.

    2007-03-01

    Advanced autonomous artificial systems will need incremental learning and adaptive abilities similar to those seen in humans. Knowledge from biology, psychology and neuroscience is now inspiring new approaches for systems that have sensory-motor capabilities and operate in complex environments. Eye/hand coordination is an important cross-modal cognitive function, and is also typical of many of the other coordinations that must be involved in the control and operation of embodied intelligent systems. This paper examines a biologically inspired approach for incrementally constructing compact mapping networks for eye/hand coordination. We present a simplified node-decoupled extended Kalman filter for radial basis function networks, and compare this with other learning algorithms. An experimental system consisting of a robot arm and a pan-and-tilt head with a colour camera is used to produce results and test the algorithms in this paper. We also present three approaches for adapting to structural changes during eye/hand coordination tasks, and the robustness of the algorithms under noise are investigated. The learning and adaptation approaches in this paper have similarities with current ideas about neural growth in the brains of humans and animals during tool-use, and infants during early cognitive development.

  4. Mapping the neuropsychological profile of temporal lobe epilepsy using cognitive network topology and graph theory.

    Science.gov (United States)

    Kellermann, Tanja S; Bonilha, Leonardo; Eskandari, Ramin; Garcia-Ramos, Camille; Lin, Jack J; Hermann, Bruce P

    2016-10-01

    Normal cognitive function is defined by harmonious interaction among multiple neuropsychological domains. Epilepsy has a disruptive effect on cognition, but how diverse cognitive abilities differentially interact with one another compared with healthy controls (HC) is unclear. This study used graph theory to analyze the community structure of cognitive networks in adults with temporal lobe epilepsy (TLE) compared with that in HC. Neuropsychological assessment was performed in 100 patients with TLE and 82 HC. For each group, an adjacency matrix was constructed representing pair-wise correlation coefficients between raw scores obtained in each possible test combination. For each cognitive network, each node corresponded to a cognitive test; each link corresponded to the correlation coefficient between tests. Global network structure, community structure, and node-wise graph theory properties were qualitatively assessed. The community structure in patients with TLE was composed of fewer, larger, more mixed modules, characterizing three main modules representing close relationships between the following: 1) aspects of executive function (EF), verbal and visual memory, 2) speed and fluency, and 3) speed, EF, perception, language, intelligence, and nonverbal memory. Conversely, controls exhibited a relative division between cognitive functions, segregating into more numerous, smaller modules consisting of the following: 1) verbal memory, 2) language, perception, and intelligence, 3) speed and fluency, and 4) visual memory and EF. Overall node-wise clustering coefficient and efficiency were increased in TLE. Adults with TLE demonstrate a less clear and poorly structured segregation between multiple cognitive domains. This panorama suggests a higher degree of interdependency across multiple cognitive domains in TLE, possibly indicating compensatory mechanisms to overcome functional impairments. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Building high-resolution synthetic lethal networks: a 'Google map' of the cancer cell.

    Science.gov (United States)

    Paul, James M; Templeton, Shaina D; Baharani, Akanksha; Freywald, Andrew; Vizeacoumar, Franco J

    2014-12-01

    The most commonly used therapies for cancer involve delivering high doses of radiation or toxic chemicals to the patient that also cause substantial damage to normal tissue. To overcome this, researchers have recently resorted to a basic biological concept called 'synthetic lethality' (SL) that takes advantage of interactions between gene pairs. The identification of SL interactions is of considerable therapeutic interest because if a particular gene is SL with a tumor-causing mutation, then the targeting that gene carries therapeutic advantages. Mapping these interactions in the context of human cancer cells could hold the key to effective, targeted cancer treatments. In this review, we cover the recent advances that aim to identify these SL interactions using unbiased genetic screens. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Mapping transcription factor interactome networks using HaloTag protein arrays.

    Science.gov (United States)

    Yazaki, Junshi; Galli, Mary; Kim, Alice Y; Nito, Kazumasa; Aleman, Fernando; Chang, Katherine N; Carvunis, Anne-Ruxandra; Quan, Rosa; Nguyen, Hien; Song, Liang; Alvarez, José M; Huang, Shao-Shan Carol; Chen, Huaming; Ramachandran, Niroshan; Altmann, Stefan; Gutiérrez, Rodrigo A; Hill, David E; Schroeder, Julian I; Chory, Joanne; LaBaer, Joshua; Vidal, Marc; Braun, Pascal; Ecker, Joseph R

    2016-07-19

    Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

  7. Aggregated journal–journal citation relations in scopus and web of science matched and compared in terms of networks, maps, and interactive overlays

    NARCIS (Netherlands)

    Leydesdorff, L.; de Moya-Anegón, F.; de Nooy, W.

    We compare the network of aggregated journal–journal citation relations provided by the Journal Citation Reports (JCR) 2012 of the Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) with similar data based on Scopus 2012. First, global and overlay maps were developed for the 2

  8. The Path Planning of AUV Based on D-S Information Fusion Map Building and Bio-Inspired Neural Network in Unknown Dynamic Environment

    Directory of Open Access Journals (Sweden)

    Daqi Zhu

    2014-03-01

    Full Text Available In this paper a biologically inspired neural dynamics and map planning based approach are simultaneously proposed for AUV (Autonomous Underwater Vehicle path planning and obstacle avoidance in an unknown dynamic environment. Firstly the readings of an ultrasonic sensor are fused into the map using the D-S (Dempster-Shafer inference rule and a two-dimensional occupancy grid map is built. Secondly the dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation. The AUV path is autonomously generated from the dynamic activity landscape of the neural network and previous AUV location. Finally, simulation results show high quality path optimization and obstacle avoidance behaviour for the AUV.

  9. A new approach for supply chain risk management: Mapping SCOR into Bayesian network

    Directory of Open Access Journals (Sweden)

    Mahdi Abolghasemi

    2015-01-01

    Full Text Available Purpose: Increase of costs and complexities in organizations beside the increase of uncertainty and risks have led the managers to use the risk management in order to decrease risk taking and deviation from goals. SCRM has a close relationship with supply chain performance. During the years different methods have been used by researchers in order to manage supply chain risk but most of them are either qualitative or quantitative. Supply chain operation reference (SCOR is a standard model for SCP evaluation which have uncertainty in its metrics. In This paper by combining qualitative and quantitative metrics of SCOR, supply chain performance will be measured by Bayesian Networks. Design/methodology/approach: First qualitative assessment will be done by recognizing uncertain metrics of SCOR model and then by quantifying them, supply chain performance will be measured by Bayesian Networks (BNs and supply chain operations reference (SCOR in which making decision on uncertain variables will be done by predictive and diagnostic capabilities. Findings: After applying the proposed method in one of the biggest automotive companies in Iran, we identified key factors of supply chain performance based on SCOR model through predictive and diagnostic capability of Bayesian Networks. After sensitivity analysis, we find out that ‘Total cost’ and its criteria that include costs of labors, warranty, transportation and inventory have the widest range and most effect on supply chain performance. So, managers should take their importance into account for decision making. We can make decisions simply by running model in different situations. Research limitations/implications: A more precise model consisted of numerous factors but it is difficult and sometimes impossible to solve big models, if we insert all of them in a Bayesian model. We have adopted real world characteristics with our software and method abilities. On the other hand, fewer data exist for some

  10. A functional magnetic resonance imaging study mapping the episodic memory encoding network in temporal lobe epilepsy

    Science.gov (United States)

    Sidhu, Meneka K.; Stretton, Jason; Winston, Gavin P.; Bonelli, Silvia; Centeno, Maria; Vollmar, Christian; Symms, Mark; Thompson, Pamela J.; Koepp, Matthias J.

    2013-01-01

    Functional magnetic resonance imaging has demonstrated reorganization of memory encoding networks within the temporal lobe in temporal lobe epilepsy, but little is known of the extra-temporal networks in these patients. We investigated the temporal and extra-temporal reorganization of memory encoding networks in refractory temporal lobe epilepsy and the neural correlates of successful subsequent memory formation. We studied 44 patients with unilateral temporal lobe epilepsy and hippocampal sclerosis (24 left) and 26 healthy control subjects. All participants performed a functional magnetic resonance imaging memory encoding paradigm of faces and words with subsequent out-of-scanner recognition assessments. A blocked analysis was used to investigate activations during encoding and neural correlates of subsequent memory were investigated using an event-related analysis. Event-related activations were then correlated with out-of-scanner verbal and visual memory scores. During word encoding, control subjects activated the left prefrontal cortex and left hippocampus whereas patients with left hippocampal sclerosis showed significant additional right temporal and extra-temporal activations. Control subjects displayed subsequent verbal memory effects within left parahippocampal gyrus, left orbitofrontal cortex and fusiform gyrus whereas patients with left hippocampal sclerosis activated only right posterior hippocampus, parahippocampus and fusiform gyrus. Correlational analysis showed that patients with left hippocampal sclerosis with better verbal memory additionally activated left orbitofrontal cortex, anterior cingulate cortex and left posterior hippocampus. During face encoding, control subjects showed right lateralized prefrontal cortex and bilateral hippocampal activations. Patients with right hippocampal sclerosis showed increased temporal activations within the superior temporal gyri bilaterally and no increased extra-temporal areas of activation compared with

  11. Revealing the cerebral regions and networks mediating vulnerability to depression: oxidative metabolism mapping of rat brain.

    Science.gov (United States)

    Harro, Jaanus; Kanarik, Margus; Kaart, Tanel; Matrov, Denis; Kõiv, Kadri; Mällo, Tanel; Del Río, Joaquin; Tordera, Rosa M; Ramirez, Maria J

    2014-07-01

    The large variety of available animal models has revealed much on the neurobiology of depression, but each model appears as specific to a significant extent, and distinction between stress response, pathogenesis of depression and underlying vulnerability is difficult to make. Evidence from epidemiological studies suggests that depression occurs in biologically predisposed subjects under impact of adverse life events. We applied the diathesis-stress concept to reveal brain regions and functional networks that mediate vulnerability to depression and response to chronic stress by collapsing data on cerebral long term neuronal activity as measured by cytochrome c oxidase histochemistry in distinct animal models. Rats were rendered vulnerable to depression either by partial serotonergic lesion or by maternal deprivation, or selected for a vulnerable phenotype (low positive affect, low novelty-related activity or high hedonic response). Environmental adversity was brought about by applying chronic variable stress or chronic social defeat. Several brain regions, most significantly median raphe, habenula, retrosplenial cortex and reticular thalamus, were universally implicated in long-term metabolic stress response, vulnerability to depression, or both. Vulnerability was associated with higher oxidative metabolism levels as compared to resilience to chronic stress. Chronic stress, in contrast, had three distinct patterns of effect on oxidative metabolism in vulnerable vs. resilient animals. In general, associations between regional activities in several brain circuits were strongest in vulnerable animals, and chronic stress disrupted this interrelatedness. These findings highlight networks that underlie resilience to stress, and the distinct response to stress that occurs in vulnerable subjects. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Creating Communications, Computing, and Networking Technology Development Road Maps for Future NASA Human and Robotic Missions

    Science.gov (United States)

    Bhasin, Kul; Hayden, Jeffrey L.

    2005-01-01

    For human and robotic exploration missions in the Vision for Exploration, roadmaps are needed for capability development and investments based on advanced technology developments. A roadmap development process was undertaken for the needed communications, and networking capabilities and technologies for the future human and robotics missions. The underlying processes are derived from work carried out during development of the future space communications architecture, an d NASA's Space Architect Office (SAO) defined formats and structures for accumulating data. Interrelationships were established among emerging requirements, the capability analysis and technology status, and performance data. After developing an architectural communications and networking framework structured around the assumed needs for human and robotic exploration, in the vicinity of Earth, Moon, along the path to Mars, and in the vicinity of Mars, information was gathered from expert participants. This information was used to identify the capabilities expected from the new infrastructure and the technological gaps in the way of obtaining them. We define realistic, long-term space communication architectures based on emerging needs and translate the needs into interfaces, functions, and computer processing that will be required. In developing our roadmapping process, we defined requirements for achieving end-to-end activities that will be carried out by future NASA human and robotic missions. This paper describes: 10 the architectural framework developed for analysis; 2) our approach to gathering and analyzing data from NASA, industry, and academia; 3) an outline of the technology research to be done, including milestones for technology research and demonstrations with timelines; and 4) the technology roadmaps themselves.

  13. Interpreting participatory Fuzzy Cognitive Maps as complex networks in the social-ecological systems of the Amazonian forests

    Science.gov (United States)

    Varela, Consuelo; Tarquis, Ana M.; Blanco-Gutiérrez, Irene; Estebe, Paloma; Toledo, Marisol; Martorano, Lucieta

    2015-04-01

    Social-ecological systems are linked complex systems that represent interconnected human and biophysical processes evolving and adapting across temporal and spatial scales. In the real world, social-ecological systems pose substantial challenges for modeling. In this regard, Fuzzy Cognitive Maps (FCMs) have proven to be a useful method for capturing the functioning of this type of systems. FCMs are a semi-quantitative type of cognitive map that represent a system composed of relevant factors and weighted links showing the strength and direction of cause-effects relationships among factors. Therefore, FCMs can be interpreted as complex system structures or complex networks. In this sense, recent research has applied complex network concepts for the analysis of FCMs that represent social-ecological systems. Key to FCM the tool is its potential to allow feedback loops and to include stakeholder knowledge in the construction of the tool. Also, previous research has demonstrated their potential to represent system dynamics and simulate the effects of changes in the system, such as policy interventions. For illustrating this analysis, we have developed a series of participatory FCM for the study of the ecological and human systems related to biodiversity conservation in two case studies of the Amazonian region, the Bolivia lowlands of Guarayos and the Brazil Tapajos National forest. The research is carried out in the context of the EU project ROBIN1 and it is based on the development of a series of stakeholder workshops to analyze the current state of the socio-ecological environment in the Amazonian forest, reflecting conflicts and challenges for biodiversity conservation and human development. Stakeholders included all relevant actors in the local case studies, namely farmers, environmental groups, producer organizations, local and provincial authorities and scientists. In both case studies we illustrate the use of complex networks concepts, such as the adjacency

  14. Improving the Understanding of Pathogenesis of Human Papillomavirus 16 via Mapping Protein-Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Yongcheng Dong

    2015-01-01

    Full Text Available The human papillomavirus 16 (HPV16 has high risk to lead various cancers and afflictions, especially, the cervical cancer. Therefore, investigating the pathogenesis of HPV16 is very important for public health. Protein-protein interaction (PPI network between HPV16 and human was used as a measure to improve our understanding of its pathogenesis. By adopting sequence and topological features, a support vector machine (SVM model was built to predict new interactions between HPV16 and human proteins. All interactions were comprehensively investigated and analyzed. The analysis indicated that HPV16 enlarged its scope of influence by interacting with human proteins as much as possible. These interactions alter a broad array of cell cycle progression. Furthermore, not only was HPV16 highly prone to interact with hub proteins and bottleneck proteins, but also it could effectively affect a breadth of signaling pathways. In addition, we found that the HPV16 evolved into high carcinogenicity on the condition that its own reproduction had been ensured. Meanwhile, this work will contribute to providing potential new targets for antiviral therapeutics and help experimental research in the future.

  15. Investigating Nonlinear Shoreline Multiperiod Change from Orthophoto Map Information by Using a Neural Network Model

    Directory of Open Access Journals (Sweden)

    Tienfuan Kerh

    2014-01-01

    Full Text Available The effects of extreme weather and overdevelopment may cause some coastal areas to exhibit erosion problems, which in turn may contribute to creating disasters of varying scale, particularly in regions comprising islands. This study used aerial survey information from three periods (1990, 2001, and 2010 and used graphical software to establish the spatial data of six beaches surrounding the island of Taiwan. An overlaying technique was then implemented to compare the sandy area of each beach in the aforementioned study periods. In addition, an artificial neural network model was developed based on available digitised coordinates for predicting coastline variation for 2015 and 2020. An onsite investigation was performed using a global positioning system for comparing the beaches. The results revealed that two beaches from this study may have experienced significant changes in total sandy areas under a statistical 95% confidence interval. The proposed method and the result of this study may provide a valuable reference in follow-up research and applications.

  16. Mapping the nomological network of employee self-determined safety motivation: A preliminary measure in China.

    Science.gov (United States)

    Jiang, Li; Tetrick, Lois E

    2016-09-01

    The present study introduced a preliminary measure of employee safety motivation based on the definition of self-determination theory from Fleming (2012) research and validated the structure of self-determined safety motivation (SDSM) by surveying 375 employees in a Chinese high-risk organization. First, confirmatory factor analysis (CFA) was used to examine the factor structure of SDSM, and indices of five-factor model CFA met the requirements. Second, a nomological network was examined to provide evidence of the construct validity of SDSM. Beyond construct validity, the analysis also produced some interesting results concerning the relationship between leadership antecedents and safety motivation, and between safety motivation and safety behavior. Autonomous motivation was positively related to transformational leadership, negatively related to abusive supervision, and positively related to safety behavior. Controlled motivation with the exception of introjected regulation was negatively related to transformational leadership, positively related to abusive supervision, and negatively related to safety behavior. The unique role of introjected regulation and future research based on self-determination theory were discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Self-Organizing Map Neural Network-Based Nearest Neighbor Position Estimation Scheme for Continuous Crystal PET Detectors

    Science.gov (United States)

    Wang, Yonggang; Li, Deng; Lu, Xiaoming; Cheng, Xinyi; Wang, Liwei

    2014-10-01

    Continuous crystal-based positron emission tomography (PET) detectors could be an ideal alternative for current high-resolution pixelated PET detectors if the issues of high performance γ interaction position estimation and its real-time implementation are solved. Unfortunately, existing position estimators are not very feasible for implementation on field-programmable gate array (FPGA). In this paper, we propose a new self-organizing map neural network-based nearest neighbor (SOM-NN) positioning scheme aiming not only at providing high performance, but also at being realistic for FPGA implementation. Benefitting from the SOM feature mapping mechanism, the large set of input reference events at each calibration position is approximated by a small set of prototypes, and the computation of the nearest neighbor searching for unknown events is largely reduced. Using our experimental data, the scheme was evaluated, optimized and compared with the smoothed k-NN method. The spatial resolutions of full-width-at-half-maximum (FWHM) of both methods averaged over the center axis of the detector were obtained as 1.87 ±0.17 mm and 1.92 ±0.09 mm, respectively. The test results show that the SOM-NN scheme has an equivalent positioning performance with the smoothed k-NN method, but the amount of computation is only about one-tenth of the smoothed k-NN method. In addition, the algorithm structure of the SOM-NN scheme is more feasible for implementation on FPGA. It has the potential to realize real-time position estimation on an FPGA with a high-event processing throughput.

  18. Face-to-face and electronic communications in maintaining social networks : the influence of geographical and relational distance and of information content

    NARCIS (Netherlands)

    Tillema, Taede; Dijst, Martin; Schwanen, Tim

    Using data collected among 742 respondents, this article aims at gaining greater insight into (i) the interaction between face-to-face (F2F) and electronic contacts, (ii) the influence of information content and relational distance on the communication mode/service choice and (iii) the influence of

  19. Réseaux sociaux en ligne et espace distancié d'apprentissage – Quelle transférabilité ? Social networks on line and distance learning: Can they be integrated?

    Directory of Open Access Journals (Sweden)

    Philippe Teutsch

    2012-06-01

    Full Text Available La construction d'une synergie entre pratique d'apprentissage en ligne et pratique du web par le biais des réseaux sociaux apparaît comme un enjeu possible avec le développement du web 2.0. L'article se propose d'en dégager les conditions de possibilité en montrant, par l'analyse de deux tentatives de transfert conduites par des étudiantes du master 2 "Didactique des langues et environnements informatiques", combien les pratiques peuvent être dépendantes de leur contexte d'émergence et combien leur possible transférabilité suppose le développement d'un continuum donnant sens à leur réemploi. Différentes approches seront utilisées pour qualifier la relation identitaire qui s'exerce dans la construction de réseaux en ligne ; elles servent aussi à préciser en quoi la gestion d'espaces relationnels différents (formatifs ou conviviaux est un enjeu central dans ce qui apparaît comme l'élément décisif de tout transfert : la construction d'un cadre interprétatif.The creation of a synergy between e-learning and the Web using existing social networks would seem to be increasingly plausible with the development of Web 2.0 functionalities. The paper analyses two attempts at such a transfer, showing to what extent practicability can be dependent on the context of emergence and how transferability is dependent upon a built-in "continuum" of interpretation, taking reusability into account. Various approaches are applied to describe the identificational relationship involved in the construction of online networks; they also serve to specify how the management of relational spaces is at the core of what appears to be the decisive element of any transfer: the construction of an interpretative framework.

  20. A digital network for long-distance echocardiographic image and data transmission in clinical trials: the CEDIM (Carnitina, Ecocardiografia Digitalizzata, Infarto Miocardico) study experience.

    Science.gov (United States)

    Iliceto, S; D'Ambrosio, G; Scrutinio, D; Marangelli, V; Boni, L; Rizzon, P

    1993-01-01

    A special computer network has been specifically designed and realized to connect 36 Italian cardiological institutions to a central core laboratory. This network, which has been created to run the CEDIM Multicenter Trial (effects of L-carnitine on left ventricular function in patients with myocardial infarction assessed by digital echocardiography), enables automatic verification, via computer, 24 hours a day, of patient eligibility criteria, randomization, transmission, and filing of real-time left ventricular echocardiographic examinations. All the investigators participating in the CEDIM trial underwent several training courses as well as dummy run procedures to achieve optimal performance of all the operational procedures required for the network to function smoothly and correctly. This paper describes the aims of this special network, its technical characteristics, and the investigator training and dummy run procedures.