Science.gov

Sample records for setting network eaprasnet

  1. Boosting Set Constraint Propagation for Network Design

    NASA Astrophysics Data System (ADS)

    Yip, Justin; van Hentenryck, Pascal; Gervet, Carmen

    This paper reconsiders the deployment of synchronous optical networks (SONET), an optimization problem naturally expressed in terms of set variables. Earlier approaches, using either MIP or CP technologies, focused on symmetry breaking, including the use of SBDS, and the design of effective branching strategies. This paper advocates an orthogonal approach and argues that the thrashing behavior experienced in earlier attempts is primarily due to a lack of pruning. It studies how to improve domain filtering by taking a more global view of the application and imposing redundant global constraints. The technical results include novel hardness results, propagation algorithms for global constraints, and inference rules. The paper also evaluates the contributions experimentally by presenting a novel model with static symmetric-breaking constraints and a static variable ordering which is many orders of magnitude faster than existing approaches.

  2. Local Area Networks in the School Setting.

    ERIC Educational Resources Information Center

    Bluhm, Harry P.

    1986-01-01

    Defines local area networks (LANs); describes basic components and configurations of LANs; and discusses LANs benefits (reduced costs, better management of computer resources, enhanced communications) and pitfalls (hidden costs, time delays, network maintenance, lack of standardization, network security breaches, lack of network compatible…

  3. Securing Mobile Networks in an Operational Setting

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Stewart, David H.; Bell, Terry L.; Paulsen, Phillip E.; Shell, Dan

    2004-01-01

    This paper describes a network demonstration and three month field trial of mobile networking using mobile-IPv4. The network was implemented as part of the US Coast Guard operational network which is a ".mil" network and requires stringent levels of security. The initial demonstrations took place in November 2002 and a three month field trial took place from July through September of 2003. The mobile network utilized encryptors capable of NSA-approved Type 1 algorithms, mobile router from Cisco Systems and 802.11 and satellite wireless links. This paper also describes a conceptual architecture for wide-scale deployment of secure mobile networking in operational environments where both private and public infrastructure is used. Additional issues presented include link costs, placement of encryptors and running routing protocols over layer-3 encryption devices.

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

    PubMed

    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. PMID:24213301

  5. Utilizing Maximal Independent Sets as Dominating Sets in Scale-Free Networks

    NASA Astrophysics Data System (ADS)

    Derzsy, N.; Molnar, F., Jr.; Szymanski, B. K.; Korniss, G.

    Dominating sets provide key solution to various critical problems in networked systems, such as detecting, monitoring, or controlling the behavior of nodes. Motivated by graph theory literature [Erdos, Israel J. Math. 4, 233 (1966)], we studied maximal independent sets (MIS) as dominating sets in scale-free networks. We investigated the scaling behavior of the size of MIS in artificial scale-free networks with respect to multiple topological properties (size, average degree, power-law exponent, assortativity), evaluated its resilience to network damage resulting from random failure or targeted attack [Molnar et al., Sci. Rep. 5, 8321 (2015)], and compared its efficiency to previously proposed dominating set selection strategies. We showed that, despite its small set size, MIS provides very high resilience against network damage. Using extensive numerical analysis on both synthetic and real-world (social, biological, technological) network samples, we demonstrate that our method effectively satisfies four essential requirements of dominating sets for their practical applicability on large-scale real-world systems: 1.) small set size, 2.) minimal network information required for their construction scheme, 3.) fast and easy computational implementation, and 4.) resiliency to network damage. Supported by DARPA, DTRA, and NSF.

  6. Connected Dominating Set Based Topology Control in Wireless Sensor Networks

    ERIC Educational Resources Information Center

    He, Jing

    2012-01-01

    Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network.…

  7. Setting Up a Customer Network to Review Documentation.

    ERIC Educational Resources Information Center

    Bist, Gary; And Others

    1993-01-01

    Describes setting up a customer review network, using computer networks and fax machines, to collect customer feedback on documentation during the stages of designing and writing the information. Describes the electronic feedback from one customer in particular and how it was analyzed and used to modify the information before releasing it. (SR)

  8. A mesoscopic network model for permanent set in crosslinked elastomers

    SciTech Connect

    Weisgraber, T H; Gee, R H; Maiti, A; Clague, D S; Chinn, S; Maxwell, R S

    2009-01-29

    A mesoscopic computational model for polymer networks and composites is developed as a coarse-grained representation of the composite microstructure. Unlike more complex molecular dynamics simulations, the model only considers the effects of crosslinks on mechanical behavior. The elastic modulus, which depends only on the crosslink density and parameters in the bond potential, is consistent with rubber elasticity theory, and the network response satisfies the independent network hypothesis of Tobolsky. The model, when applied to a commercial filled silicone elastomer, quantitatively reproduces the experimental permanent set and stress-strain response due to changes in the crosslinked network from irradiation.

  9. Designing application software in wide area network settings

    NASA Technical Reports Server (NTRS)

    Makpangou, Mesaac; Birman, Ken

    1990-01-01

    Progress in methodologies for developing robust local area network software has not been matched by similar results for wide area settings. The design of application software spanning multiple local area environments is examined. For important classes of applications, simple design techniques are presented that yield fault tolerant wide area programs. An implementation of these techniques as a set of tools for use within the ISIS system is described.

  10. Collaborative Teaching and Learning in a Networked Course Setting

    ERIC Educational Resources Information Center

    Kontopoulos, Ourania; Ford, Vivian; Roth, Stacy

    2007-01-01

    We report on a partnership between a librarian and two other community college teachers (a humanist and a social scientist) working to establish "networked courses" that use the model and techniques of collaborative teaching and learning in an interdisciplinary setting. In this partnership--and, in fact, in any interdisciplinary context--the role…

  11. Minimum steering node set of complex networks and its applications to biomolecular networks.

    PubMed

    Wu, Lin; Li, Min; Wang, Jianxin; Wu, Fang-Xiang

    2016-06-01

    Many systems of interests in practices can be represented as complex networks. For biological systems, biomolecules do not perform their functions alone but interact with each other to form so-called biomolecular networks. A system is said to be controllable if it can be steered from any initial state to any other final state in finite time. The network controllability has become essential to study the dynamics of the networks and understand the importance of individual nodes in the networks. Some interesting biological phenomena have been discovered in terms of the structural controllability of biomolecular networks. Most of current studies investigate the structural controllability of networks in notion of the minimum driver node sets (MDSs). In this study, the authors analyse the network structural controllability in notion of the minimum steering node sets (MSSs). They first develop a graph-theoretic algorithm to identify the MSS for a given network and then apply it to several biomolecular networks. Application results show that biomolecules identified in the MSSs play essential roles in corresponding biological processes. Furthermore, the application results indicate that the MSSs can reflect the network dynamics and node importance in controlling the networks better than the MDSs. PMID:27187990

  12. Evaluation of social network user sentiments based on fuzzy sets

    NASA Astrophysics Data System (ADS)

    Luneva, E. E.; Banokin, P. I.; Yefremov, A. A.

    2015-10-01

    The article introduces social network user sentiment evaluation with proposed technique based on fuzzy sets. The advantage of proposed technique consists in ability to take into account user's influence as well as the fact that a user could be an author of several messages. Results presented in this paper can be used in mechanical engineering to analyze reviews on products as well as in robotics for developing user communication interface. The paper contains experimental data and shows the steps of sentiment value calculation of resulting messages on a certain topic. Application of proposed technique is demonstrated on experimental data from Twitter social network.

  13. Network enrichment analysis: extension of gene-set enrichment analysis to gene networks

    PubMed Central

    2012-01-01

    Background Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis. Results We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study. Conclusions The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps. PMID:22966941

  14. Identifying a set of influential spreaders in complex networks

    PubMed Central

    Zhang, Jian-Xiong; Chen, Duan-Bing; Dong, Qiang; Zhao, Zhi-Dan

    2016-01-01

    Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading. A simple strategy is to choose top-r ranked nodes as spreaders according to influence ranking method such as PageRank, ClusterRank and k-shell decomposition. Besides, some heuristic methods such as hill-climbing, SPIN, degree discount and independent set based are also proposed. However, these approaches suffer from a possibility that some spreaders are so close together that they overlap sphere of influence or time consuming. In this report, we present a simply yet effectively iterative method named VoteRank to identify a set of decentralized spreaders with the best spreading ability. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of elected spreader will be decreased in subsequent turn. Experimental results on four real networks show that under Susceptible-Infected-Recovered (SIR) and Susceptible-Infected (SI) models, VoteRank outperforms the traditional benchmark methods on both spreading rate and final affected scale. What’s more, VoteRank has superior computational efficiency. PMID:27296252

  15. Identifying a set of influential spreaders in complex networks

    NASA Astrophysics Data System (ADS)

    Zhang, Jian-Xiong; Chen, Duan-Bing; Dong, Qiang; Zhao, Zhi-Dan

    2016-06-01

    Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading. A simple strategy is to choose top-r ranked nodes as spreaders according to influence ranking method such as PageRank, ClusterRank and k-shell decomposition. Besides, some heuristic methods such as hill-climbing, SPIN, degree discount and independent set based are also proposed. However, these approaches suffer from a possibility that some spreaders are so close together that they overlap sphere of influence or time consuming. In this report, we present a simply yet effectively iterative method named VoteRank to identify a set of decentralized spreaders with the best spreading ability. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of elected spreader will be decreased in subsequent turn. Experimental results on four real networks show that under Susceptible-Infected-Recovered (SIR) and Susceptible-Infected (SI) models, VoteRank outperforms the traditional benchmark methods on both spreading rate and final affected scale. What’s more, VoteRank has superior computational efficiency.

  16. Identifying a set of influential spreaders in complex networks.

    PubMed

    Zhang, Jian-Xiong; Chen, Duan-Bing; Dong, Qiang; Zhao, Zhi-Dan

    2016-01-01

    Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading. A simple strategy is to choose top-r ranked nodes as spreaders according to influence ranking method such as PageRank, ClusterRank and k-shell decomposition. Besides, some heuristic methods such as hill-climbing, SPIN, degree discount and independent set based are also proposed. However, these approaches suffer from a possibility that some spreaders are so close together that they overlap sphere of influence or time consuming. In this report, we present a simply yet effectively iterative method named VoteRank to identify a set of decentralized spreaders with the best spreading ability. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of elected spreader will be decreased in subsequent turn. Experimental results on four real networks show that under Susceptible-Infected-Recovered (SIR) and Susceptible-Infected (SI) models, VoteRank outperforms the traditional benchmark methods on both spreading rate and final affected scale. What's more, VoteRank has superior computational efficiency. PMID:27296252

  17. On correlated reaction sets and coupled reaction sets in metabolic networks.

    PubMed

    Marashi, Sayed-Amir; Hosseini, Zhaleh

    2015-08-01

    Two reactions are in the same "correlated reaction set" (or "Co-Set") if their fluxes are linearly correlated. On the other hand, two reactions are "coupled" if nonzero flux through one reaction implies nonzero flux through the other reaction. Flux correlation analysis has been previously used in the analysis of enzyme dysregulation and enzymopathy, while flux coupling analysis has been used to predict co-expression of genes and to model network evolution. The goal of this paper is to emphasize, through a few examples, that these two concepts are inherently different. In other words, except for the case of full coupling, which implies perfect correlation between two fluxes (R(2) = 1), there are no constraints on Pearson correlation coefficients (CC) in case of any other type of (un)coupling relations. In other words, Pearson CC can take any value between 0 and 1 in other cases. Furthermore, by analyzing genome-scale metabolic networks, we confirm that there are some examples in real networks of bacteria, yeast and human, which approve that flux coupling and flux correlation cannot be used interchangeably. PMID:25747383

  18. The Murrumbidgee soil moisture monitoring network data set

    NASA Astrophysics Data System (ADS)

    Smith, A. B.; Walker, J. P.; Western, A. W.; Young, R. I.; Ellett, K. M.; Pipunic, R. C.; Grayson, R. B.; Siriwardena, L.; Chiew, F. H. S.; Richter, H.

    2012-07-01

    This paper describes a soil moisture data set from the 82,000 km2 Murrumbidgee River Catchment in southern New South Wales, Australia. Data have been archived from the Murrumbidgee Soil Moisture Monitoring Network (MSMMN) since its inception in September 2001. The Murrumbidgee Catchment represents a range of conditions typical of much of temperate Australia, with climate ranging from semiarid to humid and land use including dry land and irrigated agriculture, remnant native vegetation, and urban areas. There are a total of 38 soil moisture-monitoring sites across the Murrumbidgee Catchment, with a concentration of sites in three subareas. The data set is composed of 0-5 (or 0-8), 0-30, 30-60, and 60-90 cm average soil moisture, soil temperature, precipitation, and other land surface model forcing at all sites, together with other ancillary data. These data are available on the World Wide Web at http://www.oznet.org.au.

  19. Minimum dominating set-based methods for analyzing biological networks.

    PubMed

    Nacher, Jose C; Akutsu, Tatsuya

    2016-06-01

    The fast increase of 'multi-omics' data does not only pose a computational challenge for its analysis but also requires novel algorithmic methodologies to identify complex biological patterns and decipher the ultimate roots of human disorders. To that end, the massive integration of omics data with disease phenotypes is offering a new window into the cell functionality. The minimum dominating set (MDS) approach has rapidly emerged as a promising algorithmic method to analyze complex biological networks integrated with human disorders, which can be composed of a variety of omics data, from proteomics and transcriptomics to metabolomics. Here we review the main theoretical foundations of the methodology and the key algorithms, and examine the recent applications in which biological systems are analyzed by using the MDS approach. PMID:26773457

  20. Products pipeline network plans set out for North Yemen

    SciTech Connect

    Venus, C.

    1984-02-13

    The growth of oil-products demand in future years is leading the Yemen Arab Republic (Y.A.R.) to improve the distribution network for the products by constructing a pipeline system. Petroleum products are currently distributed by road tankers only between the receiving terminals and the main cities, which represent the most important consumption centers, together with new industrial plants such as cement factories, power plants, etc. The technical design and economic and financial feasibility study of the project was entrusted to Omnium Technique des Transports par Pipelines (OTP). The scope covers the setting up in the Y.A.R. of the basic equipment for the supply, storage, and land transportation of petroleum products with a view to: Meeting the national demand for the next 25 years. Providing an adequate strategic reserve of petroleum products with a total storage capacity amounting to 3 months of consumption. The only exception in the transportation of the petroleum products will involve heavy fuel oil which will continue to be transported by road tankers. This article describes the basic facilities which have to be installed before the start-up of the projected network. The project includes a marine terminal in Salif and a pipeline to Sana'a with the related storage, truck loading, and pumping facilities for white products and gas oil which will be transported by pipeline.

  1. Computer networking in an ambulatory health care setting.

    PubMed

    Alger, R; Berkowitz, L L; Bergeron, B; Buskett, D

    1999-01-01

    Computers are a ubiquitous part of the ambulatory health care environment. Although stand-alone computers may be adequate for a small practice, networked computers can create much more powerful and cost-effective computerized systems. Local area networks allow groups of computers to share peripheral devices and computerized information within an office or cluster of offices. Wide area networks allow computers to securely share devices and information across a large geographical area. Either singly or in combination, these networks can be used to create robust systems to help physicians automate their practices and improve their access to important clinical information. In this article, we will examine common network configurations, explain how they function, and provide examples of real-world implementations of networking technology in health care. PMID:10662271

  2. Building Damage-Resilient Dominating Sets in Complex Networks against Random and Targeted Attacks

    PubMed Central

    Molnár, F.; Derzsy, N.; Szymanski, B. K.; Korniss, G.

    2015-01-01

    We study the vulnerability of dominating sets against random and targeted node removals in complex networks. While small, cost-efficient dominating sets play a significant role in controllability and observability of these networks, a fixed and intact network structure is always implicitly assumed. We find that cost-efficiency of dominating sets optimized for small size alone comes at a price of being vulnerable to damage; domination in the remaining network can be severely disrupted, even if a small fraction of dominator nodes are lost. We develop two new methods for finding flexible dominating sets, allowing either adjustable overall resilience, or dominating set size, while maximizing the dominated fraction of the remaining network after the attack. We analyze the efficiency of each method on synthetic scale-free networks, as well as real complex networks. PMID:25662371

  3. Setting Up a Public Use Local Area Network.

    ERIC Educational Resources Information Center

    Flower, Eric; Thulstrup, Lisa

    1988-01-01

    Describes a public use microcomputer cluster at the University of Maine, Orono. Various network topologies, hardware and software options, installation problems, system management, and performance are discussed. (MES)

  4. Mesoscopic structures reveal the network between the layers of multiplex data sets

    NASA Astrophysics Data System (ADS)

    Iacovacci, Jacopo; Wu, Zhihao; Bianconi, Ginestra

    2015-10-01

    Multiplex networks describe a large variety of complex systems, whose elements (nodes) can be connected by different types of interactions forming different layers (networks) of the multiplex. Multiplex networks include social networks, transportation networks, or biological networks in the cell or in the brain. Extracting relevant information from these networks is of crucial importance for solving challenging inference problems and for characterizing the multiplex networks microscopic and mesoscopic structure. Here we propose an information theory method to extract the network between the layers of multiplex data sets, forming a "network of networks." We build an indicator function, based on the entropy of network ensembles, to characterize the mesoscopic similarities between the layers of a multiplex network, and we use clustering techniques to characterize the communities present in this network of networks. We apply the proposed method to study the Multiplex Collaboration Network formed by scientists collaborating on different subjects and publishing in the American Physical Society journals. The analysis of this data set reveals the interplay between the collaboration networks and the organization of knowledge in physics.

  5. Cut set-based risk and reliability analysis for arbitrarily interconnected networks

    DOEpatents

    Wyss, Gregory D.

    2000-01-01

    Method for computing all-terminal reliability for arbitrarily interconnected networks such as the United States public switched telephone network. The method includes an efficient search algorithm to generate minimal cut sets for nonhierarchical networks directly from the network connectivity diagram. Efficiency of the search algorithm stems in part from its basis on only link failures. The method also includes a novel quantification scheme that likewise reduces computational effort associated with assessing network reliability based on traditional risk importance measures. Vast reductions in computational effort are realized since combinatorial expansion and subsequent Boolean reduction steps are eliminated through analysis of network segmentations using a technique of assuming node failures to occur on only one side of a break in the network, and repeating the technique for all minimal cut sets generated with the search algorithm. The method functions equally well for planar and non-planar networks.

  6. Functional-Network-Based Gene Set Analysis Using Gene-Ontology

    PubMed Central

    Chang, Billy; Kustra, Rafal; Tian, Weidong

    2013-01-01

    To account for the functional non-equivalence among a set of genes within a biological pathway when performing gene set analysis, we introduce GOGANPA, a network-based gene set analysis method, which up-weights genes with functions relevant to the gene set of interest. The genes are weighted according to its degree within a genome-scale functional network constructed using the functional annotations available from the gene ontology database. By benchmarking GOGANPA using a well-studied P53 data set and three breast cancer data sets, we will demonstrate the power and reproducibility of our proposed method over traditional unweighted approaches and a competing network-based approach that involves a complex integrated network. GOGANPA’s sole reliance on gene ontology further allows GOGANPA to be widely applicable to the analysis of any gene-ontology-annotated genome. PMID:23418449

  7. Establishing communication networks for health promotion in industrial settings.

    PubMed

    Heirich, M A; Cameron, V; Erfurt, J C; Foote, A; Gregg, W

    1989-11-01

    Abstract Health educators, medical personnel, and managers interested in worksite efforts to change health behaviors often face problems in communicating effectively with rank and file members of the workforce. This article describes an effective strategy for getting health information flowing among an industrial workforce and changing health behaviors. Identifying effective communication routes at a worksite and creating new ones, establishing relationships with key information carriers, and making health information salient to potential communicators are keys to successful information flow. Wellness Committees can provide access to formal communication routes, which may or may not work for health information. One-to-one counseling and development of buddy systems, however, create short-link, health-oriented communication networks. If people whom large numbers of employees contact for plant business get recruited into these health networks, information spreads rapidly. Poster posting can generate interaction with people so that they read and talk about health messages. Unusual motion, sound, and messages can call attention to special events. Using these methods has increased participation in specific health activities from a handful to between fifty and one hundred people at a time. PMID:22204404

  8. Issue Obtrusiveness and the Agenda-Setting Effects of National Network News.

    ERIC Educational Resources Information Center

    Demers, David Pearce; And Others

    1989-01-01

    Examines effects of issue obtrusiveness on network news agenda-setting. Tests two competing models: (1) obtrusive contingency (agenda-setting effects decrease as personal experience with issues increase); and (2) cognitive-priming contingency (agenda-setting effects increase as obtrusiveness increases). Finds no support for obtrusive contingency…

  9. Experimental Study of Independent and Dominating Sets in Wireless Sensor Networks Using Graph Coloring Algorithms

    NASA Astrophysics Data System (ADS)

    Mahjoub, Dhia; Matula, David W.

    The domatic partition problem seeks to maximize the partitioning of the nodes of the network into disjoint dominating sets. These sets represent a series of virtual backbones for wireless sensor networks to be activated successively, resulting in more balanced energy consumption and increased network robustness. In this study, we address the domatic partition problem in random geometric graphs by investigating several vertex coloring algorithms both topology and geometry-aware, color-adaptive and randomized. Graph coloring produces color classes with each class representing an independent set of vertices. The disjoint maximal independent sets constitute a collection of disjoint dominating sets that offer good network coverage. Furthermore, if we relax the full domination constraint then we obtain a partitioning of the network into disjoint dominating and nearly-dominating sets of nearly equal size, providing better redundancy and a near-perfect node coverage yield. In addition, these independent sets can be the basis for clustering a very large sensor network with minimal overlap between the clusters leading to increased efficiency in routing, wireless transmission scheduling and data-aggregation. We also observe that in dense random deployments, certain coloring algorithms yield a packing of the nodes into independent sets each of which is relatively close to the perfect placement in the triangular lattice.

  10. Strengthening an Interagency Network for Geoscience Data Sets

    NASA Astrophysics Data System (ADS)

    Ma, Xiaogang; Fox, Peter; Mayernik, Matthew S.

    2014-11-01

    More than 85 invited participants from government, academia, and the private sector attended the GeoData 2014 Workshop. The GeoData in the title of this workshop represents data sets collected and curated by the broad "Geo" community supported by numerous U.S. federal agencies: the Department of Energy, the Environmental Protection Agency, NASA, the National Oceanic and Atmospheric Administration, the National Science Foundation (NSF), the Department of Agriculture, and the U.S. Geological Survey, among others.

  11. Measuring Social Networks for Medical Research in Lower-Income Settings

    PubMed Central

    Kelly, Laura; Patel, Shivani A.; Narayan, K. M. Venkat; Prabhakaran, Dorairaj; Cunningham, Solveig A.

    2014-01-01

    Social networks are believed to affect health-related behaviors and health. Data to examine the links between social relationships and health in low- and middle-income country settings are limited. We provide guidance for introducing an instrument to collect social network data as part of epidemiological surveys, drawing on experience in urban India. We describe development and fielding of an instrument to collect social network information relevant to health behaviors among adults participating in a large, population-based study of non-communicable diseases in Delhi, India. We discuss basic characteristics of social networks relevant to health including network size, health behaviors of network partners (i.e., network exposures), network homogeneity, network diversity, strength of ties, and multiplexity. Data on these characteristics can be collected using a short instrument of 11 items asked about up to 5 network members and 3 items about the network generally, administered in approximately 20 minutes. We found high willingness to respond to questions about social networks (97% response). Respondents identified an average of 3.8 network members, most often relatives (80% of network ties), particularly blood relationships. Ninety-one percent of respondents reported that their primary contacts for discussing health concerns were relatives. Among all listed ties, 91% of most frequent snack partners and 64% of exercise partners in the last two weeks were relatives. These results demonstrate that family relationships are the crux of social networks in some settings, including among adults in urban India. Collecting basic information about social networks can be feasibly and effectively done within ongoing epidemiological studies. PMID:25153127

  12. Identifying generalities in data sets using periodic Hopfield networks : initial status report.

    SciTech Connect

    Link, Hamilton E.; Backer, Alejandro

    2004-12-01

    We present a novel class of dynamic neural networks that is capable of learning, in an unsupervised manner, attractors that correspond to generalities in a data set. Upon presentation of a test stimulus, the networks follow a sequence of attractors that correspond to subsets of increasing size or generality in the original data set. The networks, inspired by those of the insect antennal lobe, build upon a modified Hopfield network in which nodes are periodically suppressed, global inhibition is gradually strengthened, and the weight of input neurons is gradually decreased relative to recurrent connections. This allows the networks to converge on a Hopfield network's equilibrium within each suppression cycle, and to switch between attractors in between cycles. The fast mutually reinforcing excitatory connections that dominate dynamics within cycles ensures the robust error-tolerant behavior that characterizes Hopfield networks. The cyclic inhibition releases the network from what would otherwise be stable equilibriums or attractors. Increasing global inhibition and decreasing dependence on the input leads successive attractors to differ, and to display increasing generality. As the network is faced with stronger inhibition, only neurons connected with stronger mutually excitatory connections will remain on; successive attractors will consist of sets of neurons that are more strongly correlated, and will tend to select increasingly generic characteristics of the data. Using artificial data, we were able to identify configurations of the network that appeared to produce a sequence of increasingly general results. The next logical steps are to apply these networks to suitable real-world data that can be characterized by a hierarchy of increasing generality and observe the network's performance. This report describes the work, data, and results, the current understanding of the results, and how the work could be continued. The code, data, and preliminary results are

  13. Using fuzzy sets to model the uncertainty in the fault location process of distribution networks

    SciTech Connect

    Jaerventausta, P.; Verho, P.; Partanen, J. )

    1994-04-01

    In the computerized fault diagnosis of distribution networks the heuristic knowledge of the control center operators can be combined with the information obtained from the network data base and SCADA system. However, the nature of the heuristic knowledge is inexact and uncertain. Also the information obtained from the remote control system contains uncertainty and may be incorrect, conflicting or inadequate. This paper proposes a method based on fuzzy set theory to deal with the uncertainty involved in the process of locating faults in distribution networks. The method is implemented in a prototype version of the distribution network operation support system.

  14. Fine Registration of Kilo-Station Networks - a Modern Procedure for Terrestrial Laser Scanning Data Sets

    NASA Astrophysics Data System (ADS)

    Hullo, J.-F.

    2016-06-01

    We propose a complete methodology for the fine registration and referencing of kilo-station networks of terrestrial laser scanner data currently used for many valuable purposes such as 3D as-built reconstruction of Building Information Models (BIM) or industrial asbuilt mock-ups. This comprehensive target-based process aims to achieve the global tolerance below a few centimetres across a 3D network including more than 1,000 laser stations spread over 10 floors. This procedure is particularly valuable for 3D networks of indoor congested environments. In situ, the use of terrestrial laser scanners, the layout of the targets and the set-up of a topographic control network should comply with the expert methods specific to surveyors. Using parametric and reduced Gauss-Helmert models, the network is expressed as a set of functional constraints with a related stochastic model. During the post-processing phase inspired by geodesy methods, a robust cost function is minimised. At the scale of such a data set, the complexity of the 3D network is beyond comprehension. The surveyor, even an expert, must be supported, in his analysis, by digital and visual indicators. In addition to the standard indicators used for the adjustment methods, including Baarda's reliability, we introduce spectral analysis tools of graph theory for identifying different types of errors or a lack of robustness of the system as well as in fine documenting the quality of the registration.

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

    SciTech Connect

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

    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.

  16. Characterizing gene sets using discriminative random walks with restart on heterogeneous biological networks

    PubMed Central

    Blatti, Charles; Sinha, Saurabh

    2016-01-01

    Motivation: Analysis of co-expressed gene sets typically involves testing for enrichment of different annotations or ‘properties’ such as biological processes, pathways, transcription factor binding sites, etc., one property at a time. This common approach ignores any known relationships among the properties or the genes themselves. It is believed that known biological relationships among genes and their many properties may be exploited to more accurately reveal commonalities of a gene set. Previous work has sought to achieve this by building biological networks that combine multiple types of gene–gene or gene–property relationships, and performing network analysis to identify other genes and properties most relevant to a given gene set. Most existing network-based approaches for recognizing genes or annotations relevant to a given gene set collapse information about different properties to simplify (homogenize) the networks. Results: We present a network-based method for ranking genes or properties related to a given gene set. Such related genes or properties are identified from among the nodes of a large, heterogeneous network of biological information. Our method involves a random walk with restarts, performed on an initial network with multiple node and edge types that preserve more of the original, specific property information than current methods that operate on homogeneous networks. In this first stage of our algorithm, we find the properties that are the most relevant to the given gene set and extract a subnetwork of the original network, comprising only these relevant properties. We then re-rank genes by their similarity to the given gene set, based on a second random walk with restarts, performed on the above subnetwork. We demonstrate the effectiveness of this algorithm for ranking genes related to Drosophila embryonic development and aggressive responses in the brains of social animals. Availability and Implementation: DRaWR was implemented as

  17. Balance between noise and information flow maximizes set complexity of network dynamics.

    PubMed

    Mäki-Marttunen, Tuomo; Kesseli, Juha; Nykter, Matti

    2013-01-01

    Boolean networks have been used as a discrete model for several biological systems, including metabolic and genetic regulatory networks. Due to their simplicity they offer a firm foundation for generic studies of physical systems. In this work we show, using a measure of context-dependent information, set complexity, that prior to reaching an attractor, random Boolean networks pass through a transient state characterized by high complexity. We justify this finding with a use of another measure of complexity, namely, the statistical complexity. We show that the networks can be tuned to the regime of maximal complexity by adding a suitable amount of noise to the deterministic Boolean dynamics. In fact, we show that for networks with Poisson degree distributions, all networks ranging from subcritical to slightly supercritical can be tuned with noise to reach maximal set complexity in their dynamics. For networks with a fixed number of inputs this is true for near-to-critical networks. This increase in complexity is obtained at the expense of disruption in information flow. For a large ensemble of networks showing maximal complexity, there exists a balance between noise and contracting dynamics in the state space. In networks that are close to critical the intrinsic noise required for the tuning is smaller and thus also has the smallest effect in terms of the information processing in the system. Our results suggest that the maximization of complexity near to the state transition might be a more general phenomenon in physical systems, and that noise present in a system may in fact be useful in retaining the system in a state with high information content. PMID:23516395

  18. Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

    NASA Technical Reports Server (NTRS)

    Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

    1990-01-01

    Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

  19. Evolution of Autocatalytic Sets in Computational Models of Chemical Reaction Networks

    NASA Astrophysics Data System (ADS)

    Hordijk, Wim

    2016-06-01

    Several computational models of chemical reaction networks have been presented in the literature in the past, showing the appearance and (potential) evolution of autocatalytic sets. However, the notion of autocatalytic sets has been defined differently in different modeling contexts, each one having some shortcoming or limitation. Here, we review four such models and definitions, and then formally describe and analyze them in the context of a mathematical framework for studying autocatalytic sets known as RAF theory. The main results are that: (1) RAF theory can capture the various previous definitions of autocatalytic sets and is therefore more complete and general, (2) the formal framework can be used to efficiently detect and analyze autocatalytic sets in all of these different computational models, (3) autocatalytic (RAF) sets are indeed likely to appear and evolve in such models, and (4) this could have important implications for a possible metabolism-first scenario for the origin of life.

  20. Evolution of Autocatalytic Sets in Computational Models of Chemical Reaction Networks.

    PubMed

    Hordijk, Wim

    2016-06-01

    Several computational models of chemical reaction networks have been presented in the literature in the past, showing the appearance and (potential) evolution of autocatalytic sets. However, the notion of autocatalytic sets has been defined differently in different modeling contexts, each one having some shortcoming or limitation. Here, we review four such models and definitions, and then formally describe and analyze them in the context of a mathematical framework for studying autocatalytic sets known as RAF theory. The main results are that: (1) RAF theory can capture the various previous definitions of autocatalytic sets and is therefore more complete and general, (2) the formal framework can be used to efficiently detect and analyze autocatalytic sets in all of these different computational models, (3) autocatalytic (RAF) sets are indeed likely to appear and evolve in such models, and (4) this could have important implications for a possible metabolism-first scenario for the origin of life. PMID:26499126

  1. Stability of Dominating Sets in Complex Networks against Random and Targeted Attacks

    NASA Astrophysics Data System (ADS)

    Molnar, F.; Derzsy, N.; Szymanski, B. K.; Korniss, G.

    2014-03-01

    Minimum dominating sets (MDS) are involved in efficiently controlling and monitoring many social and technological networks. However, MDS influence over the entire network may be significantly reduced when some MDS nodes are disabled due to random breakdowns or targeted attacks against nodes in the network. We investigate the stability of domination in scale-free networks in such scenarios. We define stability as the fraction of nodes in the network that are still dominated after some nodes have been removed, either randomly, or by targeting the highest-degree nodes. We find that although the MDS is the most cost-efficient solution (requiring the least number of nodes) for reaching every node in an undamaged network, it is also very sensitive to damage. Further, we investigate alternative methods for finding dominating sets that are less efficient (more costly) than MDS but provide better stability. Finally we construct an algorithm based on greedy node selection that allows us to precisely control the balance between domination stability and cost, to achieve any desired stability at minimum cost, or the best possible stability at any given cost. Analysis of our method shows moderate improvement of domination cost efficiency against random breakdowns, but substantial improvements against targeted attacks. Supported by DARPA, DTRA, ARL NS-CTA, ARO, and ONR.

  2. A Technique for Moving Large Data Sets over High-Performance Long Distance Networks

    SciTech Connect

    Settlemyer, Bradley W; Dobson, Jonathan D; Hodson, Stephen W; Kuehn, Jeffery A; Poole, Stephen W; Ruwart, Thomas

    2011-01-01

    In this paper 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 the data to a remote 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.

  3. How Do Social Networks Influence Learning Outcomes? A Case Study in an Industrial Setting

    ERIC Educational Resources Information Center

    Maglajlic, Seid; Helic, Denis

    2012-01-01

    and Purpose: The purpose of this research is to shed light on the impact of implicit social networks to the learning outcome of e-learning participants in an industrial setting. Design/methodology/approach: The paper presents a theoretical framework that allows the authors to measure correlation coefficients between the different affiliations that…

  4. LandScape Command Set: Local Area Network Distributed Supervisory Control and Programming Environment

    SciTech Connect

    Burchard, R.L.; Small, D.E.

    1999-01-01

    This paper presents the Local Area Network Distributed Supervisory Control and Programming Environment (LandScape) commands set that provides a Generic Device Subsystem Application Programmers Interface (API). These commands are implemented using the Common Object Request Broker Architecture (CORBA) specification with Orbix from Iona Technologies.

  5. Node Deployment Algorithm for Underwater Sensor Networks Based on Connected Dominating Set

    PubMed Central

    Jiang, Peng; Liu, Jun; Wu, Feng; Wang, Jianzhong; Xue, Anke

    2016-01-01

    Existing node deployment algorithms for underwater sensor networks are nearly unable to improve the network coverage rate under the premise of ensuring the full network connectivity and do not optimize the communication and move energy consumption during the deployment. Hence, a node deployment algorithm based on connected dominating set (CDS) is proposed. After randomly sowing the nodes in 3D monitoring underwater space, disconnected nodes move to the sink node until the network achieves full connectivity. The sink node then performs centralized optimization to determine the CDS and adjusts the locations of dominated nodes. Simulation results show that the proposed algorithm can achieve a high coverage rate while ensuring full connectivity and decreases the communication and movement energy consumption during deployment. PMID:26999147

  6. Node Deployment Algorithm for Underwater Sensor Networks Based on Connected Dominating Set.

    PubMed

    Jiang, Peng; Liu, Jun; Wu, Feng; Wang, Jianzhong; Xue, Anke

    2016-01-01

    Existing node deployment algorithms for underwater sensor networks are nearly unable to improve the network coverage rate under the premise of ensuring the full network connectivity and do not optimize the communication and move energy consumption during the deployment. Hence, a node deployment algorithm based on connected dominating set (CDS) is proposed. After randomly sowing the nodes in 3D monitoring underwater space, disconnected nodes move to the sink node until the network achieves full connectivity. The sink node then performs centralized optimization to determine the CDS and adjusts the locations of dominated nodes. Simulation results show that the proposed algorithm can achieve a high coverage rate while ensuring full connectivity and decreases the communication and movement energy consumption during deployment. PMID:26999147

  7. Noisy attractors and ergodic sets in models of gene regulatory networks.

    PubMed

    Ribeiro, Andre S; Kauffman, Stuart A

    2007-08-21

    We investigate the hypothesis that cell types are attractors. This hypothesis was criticized with the fact that real gene networks are noisy systems and, thus, do not have attractors [Kadanoff, L., Coppersmith, S., Aldana, M., 2002. Boolean Dynamics with Random Couplings. http://www.citebase.org/abstract?id=oai:arXiv.org:nlin/0204062]. Given the concept of "ergodic set" as a set of states from which the system, once entering, does not leave when subject to internal noise, first, using the Boolean network model, we show that if all nodes of states on attractors are subject to internal state change with a probability p due to noise, multiple ergodic sets are very unlikely. Thereafter, we show that if a fraction of those nodes are "locked" (not subject to state fluctuations caused by internal noise), multiple ergodic sets emerge. Finally, we present an example of a gene network, modelled with a realistic model of transcription and translation and gene-gene interaction, driven by a stochastic simulation algorithm with multiple time-delayed reactions, which has internal noise and that we also subject to external perturbations. We show that, in this case, two distinct ergodic sets exist and are stable within a wide range of parameters variations and, to some extent, to external perturbations. PMID:17543998

  8. Set processing in a network environment. [data bases and magnetic disks and tapes

    NASA Technical Reports Server (NTRS)

    Hardgrave, W. T.

    1975-01-01

    A combination of a local network, a mass storage system, and an autonomous set processor serving as a data/storage management machine is described. Its characteristics include: content-accessible data bases usable from all connected devices; efficient storage/access of large data bases; simple and direct programming with data manipulation and storage management handled by the set processor; simple data base design and entry from source representation to set processor representation with no predefinition necessary; capability available for user sort/order specification; significant reduction in tape/disk pack storage and mounts; flexible environment that allows upgrading hardware/software configuration without causing major interruptions in service; minimal traffic on data communications network; and improved central memory usage on large processors.

  9. Gene regulatory network inference using fused LASSO on multiple data sets

    PubMed Central

    Omranian, Nooshin; Eloundou-Mbebi, Jeanne M. O.; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2016-01-01

    Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions. PMID:26864687

  10. Deficits in task-set maintenance and execution networks in Parkinson's disease.

    PubMed

    Tinaz, Sule; Lauro, Peter; Hallett, Mark; Horovitz, Silvina G

    2016-04-01

    Patients with Parkinson's disease have difficulties with self-initiating a task and maintaining a steady task performance. We hypothesized that these difficulties relate to reorganization in the sensorimotor execution, cingulo-opercular task-set maintenance, and frontoparietal adaptive control networks. We tested this hypothesis using graph theory-based network analysis of a composite network including a total of 86 nodes, derived from the three networks of interest. Resting-state functional magnetic resonance images were collected from 30 patients with Parkinson's disease (age 42-75 years, 11 females; Hoehn and Yahr score 2-3, average 2.4 ± 0.4) in their off-medication state and 30 matched control subjects (age 44-75 years, 10 females). For each node, we calculated strength as a general measure of connectivity, global efficiency and betweenness centrality as measures of functional integration, and clustering coefficient and local efficiency as measures of functional segregation. We found reduced node strength, clustering, and local efficiency in sensorimotor and posterior temporal nodes. There was also reduced node strength and betweenness centrality in the dorsal anterior insula and temporoparietal junction nodes of the cingulo-opercular network. These nodes are involved in integrating multimodal information, specifically related to self-awareness, sense of agency, and ultimately to intact perception of self-in-action. Moreover, we observed significant correlations between global disease severity and averaged graph metrics of the whole network. In addition to the well-known task-related frontostriatal mechanisms, we propose that the resting-state reorganization in the composite network can contribute to problems with self-initiation and task-set maintenance in Parkinson's disease. PMID:25567420

  11. Associating Human-Centered Concepts with Social Networks Using Fuzzy Sets

    NASA Astrophysics Data System (ADS)

    Yager, Ronald R.

    that allows us to determine how true it is that a particular node is a leader. In this work we look at the use of fuzzy set methodologies [8-10] to provide a bridge between the human analyst and the formal model of the network.

  12. Learning contextual gene set interaction networks of cancer with condition specificity

    PubMed Central

    2013-01-01

    Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further

  13. SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining.

    PubMed

    Takahashi, Kei-ichiro; Takigawa, Ichigaku; Mamitsuka, Hiroshi

    2013-01-01

    Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp. PMID:24386124

  14. SiBIC: A Web Server for Generating Gene Set Networks Based on Biclusters Obtained by Maximal Frequent Itemset Mining

    PubMed Central

    Takahashi, Kei-ichiro; Takigawa, Ichigaku; Mamitsuka, Hiroshi

    2013-01-01

    Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp. PMID:24386124

  15. A dynamic evolutionary clustering perspective: Community detection in signed networks by reconstructing neighbor sets

    NASA Astrophysics Data System (ADS)

    Chen, Jianrui; Wang, Hua; Wang, Lina; Liu, Weiwei

    2016-04-01

    Community detection in social networks has been intensively studied in recent years. In this paper, a novel similarity measurement is defined according to social balance theory for signed networks. Inter-community positive links are found and deleted due to their low similarity. The positive neighbor sets are reconstructed by this method. Then, differential equations are proposed to imitate the constantly changing states of nodes. Each node will update its state based on the difference between its state and average state of its positive neighbors. Nodes in the same community will evolve together with time and nodes in the different communities will evolve far away. Communities are detected ultimately when states of nodes are stable. Experiments on real world and synthetic networks are implemented to verify detection performance. The thorough comparisons demonstrate the presented method is more efficient than two acknowledged better algorithms.

  16. A jazz-based approach for optimal setting of pressure reducing valves in water distribution networks

    NASA Astrophysics Data System (ADS)

    De Paola, Francesco; Galdiero, Enzo; Giugni, Maurizio

    2016-05-01

    This study presents a model for valve setting in water distribution networks (WDNs), with the aim of reducing the level of leakage. The approach is based on the harmony search (HS) optimization algorithm. The HS mimics a jazz improvisation process able to find the best solutions, in this case corresponding to valve settings in a WDN. The model also interfaces with the improved version of a popular hydraulic simulator, EPANET 2.0, to check the hydraulic constraints and to evaluate the performances of the solutions. Penalties are introduced in the objective function in case of violation of the hydraulic constraints. The model is applied to two case studies, and the obtained results in terms of pressure reductions are comparable with those of competitive metaheuristic algorithms (e.g. genetic algorithms). The results demonstrate the suitability of the HS algorithm for water network management and optimization.

  17. Turbine set with a generator feeding a network of constant frequency

    SciTech Connect

    Spirk, F.

    1983-01-11

    In a turbine set with an axial flow which is traversed by water and which is coupled to a generator feeding a network of constant frequency, the flow turbine is a propeller turbine with nonadjustable blades. The stator winding of the generator is connected to the network by means of a frequency-controllable converter, in particular a direct converter. The speed of rotation of the turbine set is controllable continuously according to the power to be delivered. In the case of an asynchronous design of the generator, it is advisable to provide the stator with a waterproof jacket on the inside and to flange it into the turbine tube, since the rotor with its cage winding is swept by water.

  18. Risk Assessment of Communication Network of Power Company Based on Rough Set Theory and Multiclass SVM

    NASA Astrophysics Data System (ADS)

    He, Xi; Wang, Wei; Liu, Xinyu; Ji, Yong

    This paper proposes a new risk assessment method based on the attribute reduction theory of rough set and multiclass SVM classification. Rough set theory is introduced for data attribute reduction and multiclass SVM is used for automatic assessment of risk levels. Redundant features of data are deleted that can reduce the computation complexity of multiclass SVM and improve the learning and the generalization ability. Multiclass SVM trained with the empirical data can predict the risk level. Experiment shows that the predict result has relatively high precision, and the method is validity for power network risk assessment.

  19. Experience in Strategic Networking to Promote Palliative Care in a Clinical Academic Setting in India

    PubMed Central

    Nair, Shoba; Tarey, SD; Barathi, B; Mary, Thiophin Regina; Mathew, Lovely; Daniel, Sudha Pauline

    2016-01-01

    Background: Palliative care in low and middle-income countries is a new discipline, responding to a greater patient need, than in high-income countries. By its very nature, palliative as a specialty has to network with other specialties to provide quality care to patients. For any medical discipline to grow as a specialty, it should be well established in the teaching medical institutions of that country. Data show that palliative care is more likely to establish and grow in an academic health care institution. It is a necessity that multiple networking strategies are adopted to reach this goal. Objectives: (1) To describe a strategic approach to palliative care service development and integration into clinical academic setting. (2) To present the change in metrics to evaluate progress. Design and Setting: This is a descriptive study wherein, the different strategies that are adopted by the Department of Palliative Medicine for networking in an academic health care institution and outside the institution are scrutinized. Measurement: The impact of this networking was assessed, one, at the level of academics and the other, at the level of service. The number of people who attended various training programs conducted by the department and the number of patients who availed palliative care service over the years were assessed. Results: Ten different strategies were identified that helped with networking of palliative care in the institution. During this time, the referrals to the department increased both for malignant diseases (52–395) and nonmalignant diseases (5–353) from 2000 to 2013. The academic sessions conducted by the department for undergraduates also saw an increase in the number of hours from 6 to 12, apart from the increase in a number of courses conducted by the department for doctors and nurses. Conclusion: Networking is an essential strategy for the establishment of a relatively new medical discipline like palliative care in a developing and

  20. Neuron-synapse IC chip-set for large-scale chaotic neural networks.

    PubMed

    Horio, Y; Aihara, K; Yamamoto, O

    2003-01-01

    We propose a neuron-synapse integrated circuit (IC) chip-set for large-scale chaotic neural networks. We use switched-capacitor (SC) circuit techniques to implement a three-internal-state transiently-chaotic neural network model. The SC chaotic neuron chip faithfully reproduces complex chaotic dynamics in real numbers through continuous state variables of the analog circuitry. We can digitally control most of the model parameters by means of programmable capacitive arrays embedded in the SC chaotic neuron chip. Since the output of the neuron is transfered into a digital pulse according to the all-or-nothing property of an axon, we design a synapse chip with digital circuits. We propose a memory-based synapse circuit architecture to achieve a rapid calculation of a vast number of weighted summations. Both of the SC neuron and the digital synapse circuits have been fabricated as IC forms. We have tested these IC chips extensively, and confirmed the functions and performance of the chip-set. The proposed neuron-synapse IC chip-set makes it possible to construct a scalable and reconfigurable large-scale chaotic neural network with 10000 neurons and 10000/sup 2/ synaptic connections. PMID:18244585

  1. Reduced Functional Connectivity of Default Mode and Set-Maintenance Networks in Ornithine Transcarbamylase Deficiency

    PubMed Central

    Pacheco-Colón, Ileana; Washington, Stuart D.; Sprouse, Courtney; Helman, Guy; Gropman, Andrea L.; VanMeter, John W.

    2015-01-01

    Background and Purpose Ornithine transcarbamylase deficiency (OTCD) is an X-chromosome linked urea cycle disorder (UCD) that causes hyperammonemic episodes leading to white matter injury and impairments in executive functioning, working memory, and motor planning. This study aims to investigate differences in functional connectivity of two resting-state networks—default mode and set-maintenance—between OTCD patients and healthy controls. Methods Sixteen patients with partial OTCD and twenty-two control participants underwent a resting-state scan using 3T fMRI. Combining independent component analysis (ICA) and region-of-interest (ROI) analyses, we identified the nodes that comprised each network in each group, and assessed internodal connectivity. Results Group comparisons revealed reduced functional connectivity in the default mode network (DMN) of OTCD patients, particularly between the anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC) node and bilateral inferior parietal lobule (IPL), as well as between the ACC/mPFC node and the posterior cingulate cortex (PCC) node. Patients also showed reduced connectivity in the set-maintenance network, especially between right anterior insula/frontal operculum (aI/fO) node and bilateral superior frontal gyrus (SFG), as well as between the right aI/fO and ACC and between the ACC and right SFG. Conclusion Internodal functional connectivity in the DMN and set-maintenance network is reduced in patients with partial OTCD compared to controls, most likely due to hyperammonemia-related white matter damage. Because several of the affected areas are involved in executive functioning, it is postulated that this reduced connectivity is an underlying cause of the deficits OTCD patients display in this cognitive domain. PMID:26067829

  2. Online social networking sites-a novel setting for health promotion?

    PubMed

    Loss, Julika; Lindacher, Verena; Curbach, Janina

    2014-03-01

    Among adolescents, online social networking sites (SNS) such as Facebook are popular platforms for social interaction and may therefore be considered as 'novel settings' that could be exploited for health promotion. In this article, we examine the relevant definitions in health promotion and literature in order to analyze whether key characteristics of 'settings for health promotion' and the socio-ecological settings approach can be transferred to SNS. As many of our daily activities have shifted to cyberspace, we argue that online social interaction may gain more importance than geographic closeness for defining a 'setting'. While exposition to positive references to risk behavior by peers may render the SNS environment detrimental to health, SNS may allow people to create their own content and therefore foster participation. However, those health promotion projects delivered on SNS up until today solely relied on health education directed at end users. It remains unclear how health promotion on SNS can meet other requirements of the settings approach (e.g. building partnerships, changing the environment). As yet, one should be cautious in terming SNS a 'setting'. PMID:24457613

  3. Linking Plant Specialization to Dependence in Interactions for Seed Set in Pollination Networks

    PubMed Central

    Tur, Cristina; Castro-Urgal, Rocío; Traveset, Anna

    2013-01-01

    Studies on pollination networks have provided valuable information on the number, frequency, distribution and identity of interactions between plants and pollinators. However, little is still known on the functional effect of these interactions on plant reproductive success. Information on the extent to which plants depend on such interactions will help to make more realistic predictions of the potential impacts of disturbances on plant-pollinator networks. Plant functional dependence on pollinators (all interactions pooled) can be estimated by comparing seed set with and without pollinators (i.e. bagging flowers to exclude them). Our main goal in this study was thus to determine whether plant dependence on current insect interactions is related to plant specialization in a pollination network. We studied two networks from different communities, one in a coastal dune and one in a mountain. For ca. 30% of plant species in each community, we obtained the following specialization measures: (i) linkage level (number of interactions), (ii) diversity of interactions, and (iii) closeness centrality (a measure of how much a species is connected to other plants via shared pollinators). Phylogenetically controlled regression analyses revealed that, for the largest and most diverse coastal community, plants highly dependent on pollinators were the most generalists showing the highest number and diversity of interactions as well as occupying central positions in the network. The mountain community, by contrast, did not show such functional relationship, what might be attributable to their lower flower-resource heterogeneity and diversity of interactions. We conclude that plants with a wide array of pollinator interactions tend to be those that are more strongly dependent upon them for seed production and thus might be those more functionally vulnerable to the loss of network interaction, although these outcomes might be context-dependent. PMID:24205187

  4. Neural network and rough set hybrid scheme for prediction of missing associations.

    PubMed

    Anitha, A; Acharjya, D P

    2015-01-01

    Currently, internet is the best tool for distributed computing, which involves spreading of data geographically. But, retrieving information from huge data is critical and has no relevance unless it provides certain information. Prediction of missing associations can be viewed as fundamental problems in machine learning where the main objective is to determine decisions for the missing associations. Mathematical models such as naive Bayes structure, human composed network structure, Bayesian network modelling, etc., were developed to this end. But, it has certain limitations and failed to include uncertainties. Therefore, effort has been made to process inconsistencies in the data with the introduction of rough set theory. This paper uses two processes, pre-process and post-process, to predict the decisions for the missing associations in the attribute values. In preprocess, rough set is used to reduce the dimensionality, whereas neural network is used in postprocess to explore the decision for the missing associations. A real-life example is provided to show the viability of the proposed research. PMID:26642360

  5. A restricted branch and bound approach for setting the left turn phase sequences in signalized networks

    SciTech Connect

    Pillai, R.S.; Rathi, A.K.; Cohen, S.

    1994-07-01

    The main objective of synchronized signal timing is to keep traffic moving along arterial in platoons throughout the signal system by proper setting of left turn phase sequence at signals along the arterials/networks. The synchronization of traffic signals located along the urban/suburban arterials in metropolitan areas is perhaps one of the most cost-effective method for improving traffic flow along these streets. The popular technique for solving this problem formulates it as a mixed integer linear program and used Land and Powell branch and bound search to arrive at the optimal solution. The computation time tends to be excessive for realistic multiarterial network problems due to the exhaustive nature of the branch and bound search technique. Furthermore, the Land and Powell branch and bound code is known to be numerically unstable, which results in suboptimal solutions for network problems with a range on the cycle time variable. This paper presents the development of a fast and numerically stable heuristic, developed using MINOS linear programming solver. The new heuristic can generate optimal/near-optimal solutions in a fraction of the time needed to compute the optimal solution by Land and Powell code. The solution technique is based on restricted search using branch and bound technique. The efficiency of the heuristic approach is demonstrated by numerical results for a set of test problems.

  6. Set selection dynamical system neural networks with partial memories, with applications to Sudoku and KenKen puzzles.

    PubMed

    Boreland, B; Clement, G; Kunze, H

    2015-08-01

    After reviewing set selection and memory model dynamical system neural networks, we introduce a neural network model that combines set selection with partial memories (stored memories on subsets of states in the network). We establish that feasible equilibria with all states equal to ± 1 correspond to answers to a particular set theoretic problem. We show that KenKen puzzles can be formulated as a particular case of this set theoretic problem and use the neural network model to solve them; in addition, we use a similar approach to solve Sudoku. We illustrate the approach in examples. As a heuristic experiment, we use online or print resources to identify the difficulty of the puzzles and compare these difficulties to the number of iterations used by the appropriate neural network solver, finding a strong relationship. PMID:25984696

  7. Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

    NASA Astrophysics Data System (ADS)

    Li, Huajiao; Fang, Wei; An, Haizhong; Gao, Xiangyun; Yan, Lili

    2016-05-01

    Economic networks in the real world are not homogeneous; therefore, it is important to study economic networks with heterogeneous nodes and edges to simulate a real network more precisely. In this paper, we present an empirical study of the one-mode derivative holding-based network constructed by the two-mode affiliation network of two sets of actors using the data of worldwide listed energy companies and their shareholders. First, we identify the primitive relationship in the two-mode affiliation network of the two sets of actors. Then, we present the method used to construct the derivative network based on the shareholding relationship between two sets of actors and the affiliation relationship between actors and events. After constructing the derivative network, we analyze different topological features on the node level, edge level and entire network level and explain the meanings of the different values of the topological features combining the empirical data. This study is helpful for expanding the usage of complex networks to heterogeneous economic networks. For empirical research on the worldwide listed energy stock market, this study is useful for discovering the inner relationships between the nations and regions from a new perspective.

  8. Knowledge Mining from Clinical Datasets Using Rough Sets and Backpropagation Neural Network

    PubMed Central

    Nahato, Kindie Biredagn; Harichandran, Khanna Nehemiah; Arputharaj, Kannan

    2015-01-01

    The availability of clinical datasets and knowledge mining methodologies encourages the researchers to pursue research in extracting knowledge from clinical datasets. Different data mining techniques have been used for mining rules, and mathematical models have been developed to assist the clinician in decision making. The objective of this research is to build a classifier that will predict the presence or absence of a disease by learning from the minimal set of attributes that has been extracted from the clinical dataset. In this work rough set indiscernibility relation method with backpropagation neural network (RS-BPNN) is used. This work has two stages. The first stage is handling of missing values to obtain a smooth data set and selection of appropriate attributes from the clinical dataset by indiscernibility relation method. The second stage is classification using backpropagation neural network on the selected reducts of the dataset. The classifier has been tested with hepatitis, Wisconsin breast cancer, and Statlog heart disease datasets obtained from the University of California at Irvine (UCI) machine learning repository. The accuracy obtained from the proposed method is 97.3%, 98.6%, and 90.4% for hepatitis, breast cancer, and heart disease, respectively. The proposed system provides an effective classification model for clinical datasets. PMID:25821508

  9. Reconstructing Protein Structures by Neural Network Pairwise Interaction Fields and Iterative Decoy Set Construction

    PubMed Central

    Mirabello, Claudio; Adelfio, Alessandro; Pollastri, Gianluca

    2014-01-01

    Predicting the fold of a protein from its amino acid sequence is one of the grand problems in computational biology. While there has been progress towards a solution, especially when a protein can be modelled based on one or more known structures (templates), in the absence of templates, even the best predictions are generally much less reliable. In this paper, we present an approach for predicting the three-dimensional structure of a protein from the sequence alone, when templates of known structure are not available. This approach relies on a simple reconstruction procedure guided by a novel knowledge-based evaluation function implemented as a class of artificial neural networks that we have designed: Neural Network Pairwise Interaction Fields (NNPIF). This evaluation function takes into account the contextual information for each residue and is trained to identify native-like conformations from non-native-like ones by using large sets of decoys as a training set. The training set is generated and then iteratively expanded during successive folding simulations. As NNPIF are fast at evaluating conformations, thousands of models can be processed in a short amount of time, and clustering techniques can be adopted for model selection. Although the results we present here are very preliminary, we consider them to be promising, with predictions being generated at state-of-the-art levels in some of the cases. PMID:24970210

  10. Agenda setting for maternal survival: the power of global health networks and norms.

    PubMed

    Smith, Stephanie L; Rodriguez, Mariela A

    2016-04-01

    Nearly 300 000 women-almost all poor women in low-income countries-died from pregnancy-related complications in 2010. This represents a decline since the 1980s, when an estimated half million women died each year, but is still far higher than the aims set in the United Nations Millennium Development Goals (MDGs) at the turn of the century. The 1970s, 1980s and 1990s witnessed a shift from near complete neglect of the issue to emergence of a network of individuals and organizations with a shared concern for reducing maternal deaths and growth in the number of organizations and governments with maternal health strategies and programmes. Maternal health experienced a marked change in agenda status in the 2000s, attracting significantly higher level attention (e.g. from world leaders) and greater resource commitments (e.g. as one issue addressed by US$40 billion in pledges to the 2010Global Strategy for Women's and Children's Health) than ever before. Several differences between network and actor features, issue characteristics and the policy environment pre- and post-2000 help to explain the change in agenda status for global maternal mortality reduction. Significantly, a strong poverty reduction norm emerged at the turn of the century; represented by the United Nations MDGs framework, the norm set unusually strong expectations for international development actors to advance included issues. As the norm grew, it drew policy attention to the maternal health goal (MDG 5). Seeking to advance the goals agenda, world leaders launched initiatives addressing maternal and child health. New network governance and framing strategies that closely linked maternal, newborn and child health shaped the initiatives. Diverse network composition-expanding beyond a relatively narrowly focused and technically oriented group to encompass allies and leaders that brought additional resources to bear on the problem-was crucial to maternal health's rise on the agenda in the 2000s. PMID

  11. Structural damage identification based on rough sets and artificial neural network.

    PubMed

    Liu, Chengyin; Wu, Xiang; Wu, Ning; Liu, Chunyu

    2014-01-01

    This paper investigates potential applications of the rough sets (RS) theory and artificial neural network (ANN) method on structural damage detection. An information entropy based discretization algorithm in RS is applied for dimension reduction of the original damage database obtained from finite element analysis (FEA). The proposed approach is tested with a 14-bay steel truss model for structural damage detection. The experimental results show that the damage features can be extracted efficiently from the combined utilization of RS and ANN methods even the volume of measurement data is enormous and with uncertainties. PMID:25013847

  12. Structural Damage Identification Based on Rough Sets and Artificial Neural Network

    PubMed Central

    Liu, Chengyin; Wu, Xiang; Wu, Ning; Liu, Chunyu

    2014-01-01

    This paper investigates potential applications of the rough sets (RS) theory and artificial neural network (ANN) method on structural damage detection. An information entropy based discretization algorithm in RS is applied for dimension reduction of the original damage database obtained from finite element analysis (FEA). The proposed approach is tested with a 14-bay steel truss model for structural damage detection. The experimental results show that the damage features can be extracted efficiently from the combined utilization of RS and ANN methods even the volume of measurement data is enormous and with uncertainties. PMID:25013847

  13. Adaptive dynamic networks as models for the immune system and autocatalytic sets

    SciTech Connect

    Farmer, J.D.; Kauffman, S.A.; Packard, N.H.; Perelson, A.S.

    1986-04-01

    A general class of network models is described that can be used to present complex adaptive systems. These models have two purposes: On a practical level they are closely based on real biological phenomena, and are intended to model detailed aspects of them. On a more general level, however, they provide a framework to address broader questions concerning evolution, pattern recognition, and other properties of living systems. This paper concentrates on the more general level, illustrating the basic concepts with two examples, a model of the immune system and a model for the spontaneous emergence of autocatalytic sets in a chemically reactive polymer soup. 10 refs., 3 figs.

  14. Breast mass segmentation in digital mammography based on pulse coupled neural network and level set method

    NASA Astrophysics Data System (ADS)

    Xie, Weiying; Ma, Yide; Li, Yunsong

    2015-05-01

    A novel approach to mammographic image segmentation, termed as PCNN-based level set algorithm, is presented in this paper. Just as its name implies, a method based on pulse coupled neural network (PCNN) in conjunction with the variational level set method for medical image segmentation. To date, little work has been done on detecting the initial zero level set contours based on PCNN algorithm for latterly level set evolution. When all the pixels of the input image are fired by PCNN, the small pixel value will be a much more refined segmentation. In mammographic image, the breast tumor presents big pixel value. Additionally, the mammographic image with predominantly dark region, so that we firstly obtain the negative of mammographic image with predominantly dark region except the breast tumor before all the pixels of an input image are fired by PCNN. Therefore, in here, PCNN algorithm is employed to achieve mammary-specific, initial mass contour detection. After that, the initial contours are all extracted. We define the extracted contours as the initial zero level set contours for automatic mass segmentation by variational level set in mammographic image analysis. What's more, a new proposed algorithm improves external energy of variational level set method in terms of mammographic images in low contrast. In accordance with the gray scale of mass region in mammographic image is higher than the region surrounded, so the Laplace operator is used to modify external energy, which could make the bright spot becoming much brighter than the surrounded pixels in the image. A preliminary evaluation of the proposed method performs on a known public database namely MIAS, rather than synthetic images. The experimental results demonstrate that our proposed approach can potentially obtain better masses detection results in terms of sensitivity and specificity. Ultimately, this algorithm could lead to increase both sensitivity and specificity of the physicians' interpretation of

  15. LS-44: An improved deep space network station location set for Viking navigation

    NASA Technical Reports Server (NTRS)

    Koble, H. M.; Pease, G. E.; Yip, K. W.

    1976-01-01

    Improved estimates for the spin axis and longitude components of the Deep Space Network station locations were obtained from post-flight processing of radio metric data received from various Mariner planetary missions. The use of an upgraded set of ionospheric calibrations and the incorporation of near-Venus and near-Mercury radio metric data from the Mariner 10 spacecraft are the principal contributing effects to the improvement. These new estimates, designated Location Set (LS) 44, have supported Viking navigation activities in the vicinity of Mars. As such, the station locations were determined relative to the planetary positions inherent in JPL Development Ephemeris (DE) 84, which was used throughout the Viking mission. The article also presents and discusses a version of LS 44 based upon the latest planetary ephemeris, DE 96.

  16. Delineating Geographical Regions with Networks of Human Interactions in an Extensive Set of Countries

    PubMed Central

    Sobolevsky, Stanislav; Szell, Michael; Campari, Riccardo; Couronné, Thomas; Smoreda, Zbigniew; Ratti, Carlo

    2013-01-01

    Large-scale networks of human interaction, in particular country-wide telephone call networks, can be used to redraw geographical maps by applying algorithms of topological community detection. The geographic projections of the emerging areas in a few recent studies on single regions have been suggested to share two distinct properties: first, they are cohesive, and second, they tend to closely follow socio-economic boundaries and are similar to existing political regions in size and number. Here we use an extended set of countries and clustering indices to quantify overlaps, providing ample additional evidence for these observations using phone data from countries of various scales across Europe, Asia, and Africa: France, the UK, Italy, Belgium, Portugal, Saudi Arabia, and Ivory Coast. In our analysis we use the known approach of partitioning country-wide networks, and an additional iterative partitioning of each of the first level communities into sub-communities, revealing that cohesiveness and matching of official regions can also be observed on a second level if spatial resolution of the data is high enough. The method has possible policy implications on the definition of the borderlines and sizes of administrative regions. PMID:24367490

  17. GuMNet - Guadarrama Monitoring Network. Installation and set up of a high altitude monitoring network, north of Madrid. Spain

    NASA Astrophysics Data System (ADS)

    Santolaria-Canales, Edmundo

    2015-04-01

    An observational monitoring network in the Guadarrama Mountains is due to be operational at the end of 2015. This network integrates atmospheric measurements as well as subsurface observations in a high mountain climate, located up to 2.400 m.a.s.l. The data provided by GuMNet will help to improve the characterization of microclimate in high mountain areas, as well as land-atmosphere interations. The network information aims at meeting the needs of accuracy to be used for biological, agricultural, hydrological, meteorological and climatic investigations in this area. This initiative is supported and developed by research groups integrating the GuMNet Consortiuma from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Energetic Environmental and Technological Research Centre (CIEMAT), the Spanish National Meteorological Agency (AEMET), and the National Park Sierra de Guadarrama (PNSG). The starting setup includes seven meteorological stations compatible with WMO standards, to be installed in the central area of the massif. Including a four-component net radiation sensor, an ultrasonic snow height, a pluviometer specialized for snow capture, air temperature and humidity devices and wind speed/direction sensor. Along with these atmospheric measurements, each station will include a set of subsurface measurements of temperature in shallow boreholes ( 20 m depth ) and temperature and humidity in trenches up to 1 m depth. These compatible WMO stations will be complemented by a station specialized in eddy covariance measuremets with CO2 fluxes at low altitude pastureland near Madrid. Another portable station is available to develop ad hoc comparison studies. This setup is embedded in a broader network of meteorological stations run partly by AEMET and partly by the PNSG. Most of the AEMET stations are distributed over lower altitudes, and will provide a very reliable boundary information for the atmosphere state around the Sierra. In the same way

  18. A broadcast-based key agreement scheme using set reconciliation for wireless body area networks.

    PubMed

    Ali, Aftab; Khan, Farrukh Aslam

    2014-05-01

    Information and communication technologies have thrived over the last few years. Healthcare systems have also benefited from this progression. A wireless body area network (WBAN) consists of small, low-power sensors used to monitor human physiological values remotely, which enables physicians to remotely monitor the health of patients. Communication security in WBANs is essential because it involves human physiological data. Key agreement and authentication are the primary issues in the security of WBANs. To agree upon a common key, the nodes exchange information with each other using wireless communication. This information exchange process must be secure enough or the information exchange should be minimized to a certain level so that if information leak occurs, it does not affect the overall system. Most of the existing solutions for this problem exchange too much information for the sake of key agreement; getting this information is sufficient for an attacker to reproduce the key. Set reconciliation is a technique used to reconcile two similar sets held by two different hosts with minimal communication complexity. This paper presents a broadcast-based key agreement scheme using set reconciliation for secure communication in WBANs. The proposed scheme allows the neighboring nodes to agree upon a common key with the personal server (PS), generated from the electrocardiogram (EKG) feature set of the host body. Minimal information is exchanged in a broadcast manner, and even if every node is missing a different subset, by reconciling these feature sets, the whole network will still agree upon a single common key. Because of the limited information exchange, if an attacker gets the information in any way, he/she will not be able to reproduce the key. The proposed scheme mitigates replay, selective forwarding, and denial of service attacks using a challenge-response authentication mechanism. The simulation results show that the proposed scheme has a great deal of

  19. Forecasting of loading on the Deep Space Network for proposed future NASA mission sets

    NASA Technical Reports Server (NTRS)

    Webb, W. A.

    1979-01-01

    The paper describes a computer program, DSNLOAD, which provides the Deep Space Network (DSN) loading information given a proposed future NASA mission set. The DSNLOAD model includes required pre- and post-calibration periods, and station 'overhead' such as maintenance or 'down' time. The analysis is presented which transforms station view period data for the mission set into loading matrices used to assess loading requirement. Assessment of future loading on the DSN for a set of NASA missions by estimating the tracking situation and presenting the DSN loading data, and a flowchart for selecting a possible future mission, determining a heliocentric orbit for the mission, generating view period schedules, and converting these schedules into basic loading data for each mission for each station are given. The tracking schedule model which considers the tracking schedule to be represented by passes of maximum required length and centered within the view period of available tracking time for each mission is described, and, finally, an example of typical loading study is provided.

  20. Implementing evidence-based policy in a network setting: road safety policy in the Netherlands.

    PubMed

    Bax, Charlotte; de Jong, Martin; Koppenjan, Joop

    2010-01-01

    In the early 1990s, in order to improve road safety in The Netherlands, the Institute for Road Safety Research (SWOV) developed an evidence-based "Sustainable Safety" concept. Based on this concept, Dutch road safety policy, was seen as successful and as a best practice in Europe. In The Netherlands, the policy context has now changed from a sectoral policy setting towards a fragmented network in which safety is a facet of other transport-related policies. In this contribution, it is argued that the implementation strategy underlying Sustainable Safety should be aligned with the changed context. In order to explore the adjustments needed, two perspectives of policy implementation are discussed: (1) national evidence-based policies with sectoral implementation; and (2) decentralized negotiation on transport policy in which road safety is but one aspect. We argue that the latter approach matches the characteristics of the newly evolved policy context best, and conclude with recommendations for reformulating the implementation strategy. PMID:20925155

  1. Analysis of the Effect of Degree Correlation on the Size of Minimum Dominating Sets in Complex Networks

    PubMed Central

    2016-01-01

    Network controllability is an important topic in wide-ranging research fields. However, the relationship between controllability and network structure is poorly understood, although degree heterogeneity is known to determine the controllability. We focus on the size of a minimum dominating set (MDS), a measure of network controllability, and investigate the effect of degree-degree correlation, which is universally observed in real-world networks, on the size of an MDS. We show that disassortativity or negative degree-degree correlation reduces the size of an MDS using analytical treatments and numerical simulation, whereas positive correlations hardly affect the size of an MDS. This result suggests that disassortativity enhances network controllability. Furthermore, apart from the controllability issue, the developed techniques provide new ways of analyzing complex networks with degree-degree correlations. PMID:27327273

  2. Deconstructing myths, building alliances: a networking model to enhance tobacco control in hospital mental health settings.

    PubMed

    Ballbè, Montse; Gual, Antoni; Nieva, Gemma; Saltó, Esteve; Fernández, Esteve

    2016-01-01

    Life expectancy for people with severe mental disorders is up to 25 years less in comparison to the general population, mainly due to diseases caused or worsened by smoking. However, smoking is usually a neglected issue in mental healthcare settings. The aim of this article is to describe a strategy to improve tobacco control in the hospital mental healthcare services of Catalonia (Spain). To bridge this gap, the Catalan Network of Smoke-free Hospitals launched a nationwide bottom-up strategy in Catalonia in 2007. The strategy relied on the creation of a working group of key professionals from various hospitals -the early adopters- based on Rogers' theory of the Diffusion of Innovations. In 2016, the working group is composed of professionals from 17 hospitals (70.8% of all hospitals in the region with mental health inpatient units). Since 2007, tobacco control has improved in different areas such as increasing mental health professionals' awareness of smoking, training professionals on smoking cessation interventions and achieving good compliance with the national smoking ban. The working group has produced and disseminated various materials, including clinical practice and best practice guidelines, implemented smoking cessation programmes and organised seminars and training sessions on smoking cessation measures in patients with mental illnesses. The next challenge is to ensure effective follow-up for smoking cessation after discharge. While some areas of tobacco control within these services still require significant improvement, the aforementioned initiative promotes successful tobacco control in these settings. PMID:27325123

  3. The Roles of Reward, Default, and Executive Control Networks in Set-Shifting Impairments in Schizophrenia

    PubMed Central

    Waltz, James A.; Kasanova, Zuzana; Ross, Thomas J.; Salmeron, Betty J.; McMahon, Robert P.; Gold, James M.; Stein, Elliot A.

    2013-01-01

    Patients with schizophrenia (SZ) show deficits on tasks of rapid reinforcement learning, like probabilistic reversal learning (PRL), but the neural bases for those impairments are not known. Recent evidence of relatively intact sensitivity to negative outcomes in the ventral striatum (VS) in many SZ patients suggests that PRL deficits may be largely attributable to processes downstream from feedback processing, involving both the activation of executive control task regions and deactivation of default mode network (DMN) components. We analyzed data from 29 chronic SZ patients and 21 matched normal controls (NCs) performing a PRL task in an MRI scanner. Subjects were presented with eight pairs of fractal stimuli, for 50 trials each. For each pair, subjects learned to choose the more frequently-rewarded (better) stimulus. Each time a criterion was reached, the better stimulus became the worse one, and the worse became the better. Responses to feedback events were assessed through whole-brain and regions-of-interest (ROI) analyses in DMN. We also assessed correlations between BOLD signal contrasts and clinical measures in SZs. Relative to NCs, SZ patients showed comparable deactivation of VS in response to negative feedback, but reduced deactivation of DMN components including medial prefrontal cortex (mPFC). The magnitudes of patients' punishment-evoked deactivations in VS and ventromedial PFC correlated significantly with clinical ratings for avolition/anhedonia. These findings suggest that schizophrenia is associated with a reduced ability to deactivate components of default mode networks, following the presentation of informative feedback and that motivational deficits in SZ relate closely to feedback-evoked activity in reward circuit components. These results also confirm a role for ventrolateral and dorsomedial PFC in the execution of response-set shifts. PMID:23468948

  4. Determinants of Low Cloud Properties - An Artificial Neural Network Approach Using Observation Data Sets

    NASA Astrophysics Data System (ADS)

    Andersen, Hendrik; Cermak, Jan

    2015-04-01

    This contribution studies the determinants of low cloud properties based on the application of various global observation data sets in machine learning algorithms. Clouds play a crucial role in the climate system as their radiative properties and precipitation patterns significantly impact the Earth's energy balance. Cloud properties are determined by environmental conditions, as cloud formation requires the availability of water vapour ("precipitable water") and condensation nuclei in sufficiently saturated conditions. A main challenge in the research of aerosol-cloud interactions is the separation of aerosol effects from meteorological influence. To gain understanding of the processes that govern low cloud properties in order to increase accuracy of climate models and predictions of future changes in the climate system is thus of great importance. In this study, artificial neural networks are used to relate a selection of predictors (meteorological parameters, aerosol loading) to a set of predictands (cloud microphysical and optical properties). As meteorological parameters, wind direction and velocity, sea level pressure, static stability of the lower troposphere, atmospheric water vapour and temperature at the surface are used (re-analysis data by the European Centre for Medium-Range Weather Forecasts). In addition to meteorological conditions, aerosol loading is used as a predictor of cloud properties (MODIS collection 6 aerosol optical depth). The statistical model reveals significant relationships between predictors and predictands and is able to represent the aerosol-cloud-meteorology system better than frequently used bivariate relationships. The most important predictors can be identified by the additional error when excluding one predictor at a time. The sensitivity of each predictand to each of the predictors is analyzed.

  5. Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming

    PubMed Central

    Guziolowski, Carito; Videla, Santiago; Eduati, Federica; Thiele, Sven; Cokelaer, Thomas; Siegel, Anne; Saez-Rodriguez, Julio

    2013-01-01

    Motivation: Logic modeling is a useful tool to study signal transduction across multiple pathways. Logic models can be generated by training a network containing the prior knowledge to phospho-proteomics data. The training can be performed using stochastic optimization procedures, but these are unable to guarantee a global optima or to report the complete family of feasible models. This, however, is essential to provide precise insight in the mechanisms underlaying signal transduction and generate reliable predictions. Results: We propose the use of Answer Set Programming to explore exhaustively the space of feasible logic models. Toward this end, we have developed caspo, an open-source Python package that provides a powerful platform to learn and characterize logic models by leveraging the rich modeling language and solving technologies of Answer Set Programming. We illustrate the usefulness of caspo by revisiting a model of pro-growth and inflammatory pathways in liver cells. We show that, if experimental error is taken into account, there are thousands (11 700) of models compatible with the data. Despite the large number, we can extract structural features from the models, such as links that are always (or never) present or modules that appear in a mutual exclusive fashion. To further characterize this family of models, we investigate the input–output behavior of the models. We find 91 behaviors across the 11 700 models and we suggest new experiments to discriminate among them. Our results underscore the importance of characterizing in a global and exhaustive manner the family of feasible models, with important implications for experimental design. Availability: caspo is freely available for download (license GPLv3) and as a web service at http://caspo.genouest.org/. Supplementary information: Supplementary materials are available at Bioinformatics online. Contact: santiago.videla@irisa.fr PMID:23853063

  6. [Pediatric research in an office-setting network--a new dimension in pediatric research in Israel].

    PubMed

    Grossman, Z; Kahan, E; Gross, S; Ashkenazi, S; Shalit, I

    1999-06-15

    Pediatric care in the community is gradually replacing traditional care in hospitals. Despite that, research activity in the community setting is minimal due to objective difficulties. These are mainly constraints of time, office work and lack of research-supporting logistics. In the past decade, throughout the world, primary physicians interested in research have grouped together and formed research networks. The aim of such networks is to support and promote research in the community. An Israel Pediatric Research in Office-Setting network (IPROS) was established 2 years ago by the Israel Ambulatory Pediatric Association (IAPA). Today, there are over 140 pediatricians listed in IPROS, representing the heterogeneous composition of pediatricians in Israel. The network's policy is defined by a joint steering committee. The committee is composed of IAPA representatives, senior network members and Schneider Hospital senior investigators. The research subjects are diverse, and represent common practical issues. Effective intra-net communication is vital to the existence of the network, and is accomplished by 3 modalities: 1) semiannual updates by mail, 2) e-mail, using an electronic mailing list to facilitate connection between members, 3) semi-annual meetings. Research budgets are derived from public sources like the Ministry of Health and IAPA, and private sources such as pharmaceutical companies. The administration of the network is supported by Schneider Children's Medical Center, and financed by IAPA. PMID:10955149

  7. A level set method for solid-liquid interface tracking in texturally equilibrated pore networks

    NASA Astrophysics Data System (ADS)

    Ghanbarzadeh, Soheil; Hesse, Marc; Prodanovic, Masa

    2015-04-01

    The properties of some porous media are determined by their evolution towards textural equilibrium. Melt drainage from temperate glacier ice and the accumulation of hydrocarbons beneath rock salt are two examples in natural systems. In these materials, pore geometry evolves to minimize the solid-liquid interfacial energy while maintaining dihedral angle, θ, at solid-liquid contact lines. In this work we present the first computations of 3-D texturally equilibrated pore networks using a novel level set method. Interfacial energy minimization is achieved by evolving interface under surface diffusion to constant mean curvature surface. The porosity and dihedral angle constraints are added to the formulation using virtual velocity terms. A domain decomposition scheme is devised to restrict the computational domain and the coupling between the interfaces is achieved on the original computational domain. For the last 30 years, explicit representation of the interfaces limited the computations to highly idealized geometries. The presented model overcomes these limitations and opens the door to the exploration of the physics of these materials in realistic systems. For example, our results show that the fully wetted grain boundaries exist even for θ>0 which reconciles the theory with experimental observations. This work is sponsored by the Statoil Fellows Program at The University of Texas.

  8. A General Fuzzy Cerebellar Model Neural Network Multidimensional Classifier Using Intuitionistic Fuzzy Sets for Medical Identification.

    PubMed

    Zhao, Jing; Lin, Lo-Yi; Lin, Chih-Min

    2016-01-01

    The diversity of medical factors makes the analysis and judgment of uncertainty one of the challenges of medical diagnosis. A well-designed classification and judgment system for medical uncertainty can increase the rate of correct medical diagnosis. In this paper, a new multidimensional classifier is proposed by using an intelligent algorithm, which is the general fuzzy cerebellar model neural network (GFCMNN). To obtain more information about uncertainty, an intuitionistic fuzzy linguistic term is employed to describe medical features. The solution of classification is obtained by a similarity measurement. The advantages of the novel classifier proposed here are drawn out by comparing the same medical example under the methods of intuitionistic fuzzy sets (IFSs) and intuitionistic fuzzy cross-entropy (IFCE) with different score functions. Cross verification experiments are also taken to further test the classification ability of the GFCMNN multidimensional classifier. All of these experimental results show the effectiveness of the proposed GFCMNN multidimensional classifier and point out that it can assist in supporting for correct medical diagnoses associated with multiple categories. PMID:27298619

  9. A General Fuzzy Cerebellar Model Neural Network Multidimensional Classifier Using Intuitionistic Fuzzy Sets for Medical Identification

    PubMed Central

    Zhao, Jing; Lin, Lo-Yi

    2016-01-01

    The diversity of medical factors makes the analysis and judgment of uncertainty one of the challenges of medical diagnosis. A well-designed classification and judgment system for medical uncertainty can increase the rate of correct medical diagnosis. In this paper, a new multidimensional classifier is proposed by using an intelligent algorithm, which is the general fuzzy cerebellar model neural network (GFCMNN). To obtain more information about uncertainty, an intuitionistic fuzzy linguistic term is employed to describe medical features. The solution of classification is obtained by a similarity measurement. The advantages of the novel classifier proposed here are drawn out by comparing the same medical example under the methods of intuitionistic fuzzy sets (IFSs) and intuitionistic fuzzy cross-entropy (IFCE) with different score functions. Cross verification experiments are also taken to further test the classification ability of the GFCMNN multidimensional classifier. All of these experimental results show the effectiveness of the proposed GFCMNN multidimensional classifier and point out that it can assist in supporting for correct medical diagnoses associated with multiple categories. PMID:27298619

  10. Setting Access Permission through Transitive Relationship in Web-based Social Networks

    NASA Astrophysics Data System (ADS)

    Hong, Dan; Shen, Vincent Y.

    The rising popularity of various social networking websites has created a huge problem on Internet privacy. Although it is easy to post photos, comments, opinions on some events, etc. on the Web, some of these data (such as a person’s location at a particular time, criticisms of a politician, etc.) are private and should not be accessed by unauthorized users. Although social networks facilitate sharing, the fear of sending sensitive data to a third party without knowledge or permission of the data owners discourages people from taking full advantage of some social networking applications. We exploit the existing relationships on social networks and build a ‘‘trust network’’ with transitive relationship to allow controlled data sharing so that the privacy and preferences of data owners are respected. The trust network linking private data owners, private data requesters, and intermediary users is a directed weighted graph. The permission value for each private data requester can be automatically assigned in this network based on the transitive relationship. Experiments were conducted to confirm the feasibility of constructing the trust network from existing social networks, and to assess the validity of permission value assignments in the query process. Since the data owners only need to define the access rights of their closest contacts once, this privacy scheme can make private data sharing easily manageable by social network participants.

  11. A Ground-based Network Set Up for Soil Moisture Monitoring in West Wales, UK: the WSMN Network

    NASA Astrophysics Data System (ADS)

    Petropoulos, George P.; Purdy, Sarah; McCalmont, Jon P.; Ireland, Gareth

    2015-04-01

    Soil moisture (SM) is a significant component of climatological, hydrological and ecological systems. It has long been recognised as a key state variable of the global energy and water cycle due to its control on exchanges of energy and matter and physical processes. Thus, information on its variation over time and space domains is of key importance to both practitioners and researchers alike from a variety of disciplines. There is a breadth of options that can be considered for deriving estimates of SM, one of which is the use of ground instrumentation. In view of the requirement for information on the spatial distribution of SM, ground-based observational networks have also been developed worldwide, providing SM data operationally, and at no cost to the user's community globally. Such data is also pivotal in studies concerned with benchmarking related Earth Observation-based datasets, since ground measurements are often used as "reference" in validating satellite-derived products of SMC. In this context, we present herein our recent progress towards the establishment of an autonomous in-situ network - named WSMN (Wales Soil Moisture Monitoring Network) - for obtaining, on a long term basis and in near real-time, measurements of SM and related parameters for west Wales, United Kingdom. The WSMN network currently consists of six stations based close to the Aberystwyth region and has been collecting data since 2011. The network is now fully deployed distributing all collected data via the International Soil Moisture Network (ISMN) platform. Herein, we present results on SM trends from a time series analysis conducted analysing the data collected until end of 2014. The availability of this new in-situ dataset is of paramount importance to the region as it is expected to help advance our understanding on the physical processes involved in water and energy exchanges at the local scale. Moreover, in a boarder scale, this study assists towards an objective evaluation of

  12. Gene set enrichment and topological analyses based on interaction networks in pediatric acute lymphoblastic leukemia

    PubMed Central

    SUI, SHUXIANG; WANG, XIN; ZHENG, HUA; GUO, HUA; CHEN, TONG; JI, DONG-MEI

    2015-01-01

    Pediatric acute lymphoblastic leukemia (ALL) accounts for over one-quarter of all pediatric cancers. Interacting genes and proteins within the larger human gene interaction network of the human genome are rarely investigated by studies investigating pediatric ALL. In the present study, interaction networks were constructed using the empirical Bayesian approach and the Search Tool for the Retrieval of Interacting Genes/proteins database, based on the differentially-expressed (DE) genes in pediatric ALL, which were identified using the RankProd package. Enrichment analysis of the interaction network was performed using the network-based methods EnrichNet and PathExpand, which were compared with the traditional expression analysis systematic explored (EASE) method. In total, 398 DE genes were identified in pediatric ALL, and LIF was the most significantly DE gene. The co-expression network consisted of 272 nodes, which indicated genes and proteins, and 602 edges, which indicated the number of interactions adjacent to the node. Comparison between EASE and PathExpand revealed that PathExpand detected more pathways or processes that were closely associated with pediatric ALL compared with the EASE method. There were 294 nodes and 1,588 edges in the protein-protein interaction network, with the processes of hematopoietic cell lineage and porphyrin metabolism demonstrating a close association with pediatric ALL. Network enrichment analysis based on the PathExpand algorithm was revealed to be more powerful for the analysis of interaction networks in pediatric ALL compared with the EASE method. LIF and MLLT11 were identified as the most significantly DE genes in pediatric ALL. The process of hematopoietic cell lineage was the pathway most significantly associated with pediatric ALL. PMID:26788135

  13. Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis

    PubMed Central

    Lee, Won Jun; Kim, Sang Cheol; Yoon, Jung-Ho; Yoon, Sang Jun; Lim, Johan; Kim, You-Sun; Kwon, Sung Won; Park, Jeong Hill

    2016-01-01

    Generally, cancer stem cells have epithelial-to-mesenchymal-transition characteristics and other aggressive properties that cause metastasis. However, there have been no confident markers for the identification of cancer stem cells and comparative methods examining adherent and sphere cells are widely used to investigate mechanism underlying cancer stem cells, because sphere cells have been known to maintain cancer stem cell characteristics. In this study, we conducted a meta-analysis that combined gene expression profiles from several studies that utilized tumorsphere technology to investigate tumor stem-like breast cancer cells. We used our own gene expression profiles along with the three different gene expression profiles from the Gene Expression Omnibus, which we combined using the ComBat method, and obtained significant gene sets using the gene set analysis of our datasets and the combined dataset. This experiment focused on four gene sets such as cytokine-cytokine receptor interaction that demonstrated significance in both datasets. Our observations demonstrated that among the genes of four significant gene sets, six genes were consistently up-regulated and satisfied the p-value of < 0.05, and our network analysis showed high connectivity in five genes. From these results, we established CXCR4, CXCL1 and HMGCS1, the intersecting genes of the datasets with high connectivity and p-value of < 0.05, as significant genes in the identification of cancer stem cells. Additional experiment using quantitative reverse transcription-polymerase chain reaction showed significant up-regulation in MCF-7 derived sphere cells and confirmed the importance of these three genes. Taken together, using meta-analysis that combines gene set and network analysis, we suggested CXCR4, CXCL1 and HMGCS1 as candidates involved in tumor stem-like breast cancer cells. Distinct from other meta-analysis, by using gene set analysis, we selected possible markers which can explain the biological

  14. Setting Up the Speech Production Network: How Oscillations Contribute to Lateralized Information Routing

    PubMed Central

    Gehrig, Johannes; Wibral, Michael; Arnold, Christiane; Kell, Christian A.

    2012-01-01

    Speech production involves widely distributed brain regions. This MEG study focuses on the spectro-temporal dynamics that contribute to the setup of this network. In 21 participants performing a cue-target reading paradigm, we analyzed local oscillations during preparation for overt and covert reading in the time-frequency domain and localized sources using beamforming. Network dynamics were studied by comparing different dynamic causal models of beta phase coupling in and between hemispheres. While a broadband low frequency effect was found for any task preparation in bilateral prefrontal cortices, preparation for overt speech production was specifically associated with left-lateralized alpha and beta suppression in temporal cortices and beta suppression in motor-related brain regions. Beta phase coupling in the entire speech production network was modulated by anticipation of overt reading. We propose that the processes underlying the setup of the speech production network connect relevant brain regions by means of beta synchronization and prepare the network for left-lateralized information routing by suppression of inhibitory alpha and beta oscillations. PMID:22685442

  15. Secure Your Wireless Network: Going Wireless Comes with Its Own Special Set of Security Concerns

    ERIC Educational Resources Information Center

    Bloomquist, Jane; Musa, Atif

    2004-01-01

    Imagine a completely wireless school, an open network in which all students and staff can roam around using laptops or handheld computers to browse the Internet, access files and applications on the school server, and communicate with each other and the world via e-mail. It's a great picture--and at some schools the future is already here. But…

  16. A Network Sets Things in Motion: TEDD Celebrates its 5(th) Anniversary.

    PubMed

    2015-01-01

    At the Annual Meeting at ZHAW Waedenswil on 22 October 2015, the TEDD-Network (Tissue Engineering for Drug Development and Substance Testing) celebrated its 5(th) anniversary. Since its foundation, TEDD has become an internationally renowned competence centre and includes currently 91 members from academia and industry. They cover the entire development and value chain. PMID:26671055

  17. Summary information and data sets for the HBCU Solar Measurements Network

    SciTech Connect

    Marion, W.

    1994-08-01

    Since 1985, the National Renewable Energy Laboratory (NREL), formerly the Solar Energy Research Institute (SERI), has operated a solar radiation measurement network of six stations located at Historically Black Colleges and Universities (HBCUs) in the southeastern United States. NREL initiated this network to provide better regional coverage and to comply with President Reagan`s Executive Order 12320, dated September 15, 1981, directing all federal agencies to implement programs to strengthen the nation`s HBCUs. Funding for the HBCU network has been provided by the Department of Energy`s (DOE`s) Resource Assessment Program, Photovoltaic Program, and Solar Thermal Program, and it is currently funded by the Solar Radiation Resource Assessment Project. The objectives of the HBCU network are (1) To significantly improve the assessment of solar radiation resources in the southeastern United States; (2) To enlist the help of the HBCUs in collecting high-quality solar radiation data; (3) To encourage the distribution of solar radiation resource information and the development of solar energy applications in the Southeast; (4) To encourage the development of academic and research programs in solar energy at HBCUs.

  18. Summary information and data sets for the HBCU Solar Measurements Network

    NASA Astrophysics Data System (ADS)

    Marion, W.

    1994-08-01

    Since 1985, the National Renewable Energy Laboratory (NREL), formerly the Solar Energy Research Institute (SERI), has operated a solar radiation measurement network of six stations located at Historically Black Colleges and Universities (HBCU's) in the southeastern United States. NREL initiated this network to provide better regional coverage and to comply with President Reagan's Executive Order 12320, dated September 15, 1981, directing all federal agencies to implement programs to strengthen the nation's HBCU's. Funding for the HBCU network has been provided by the Department of Energy's (DOE's) Resource Assessment Program, Photovoltaic Program, and Solar Thermal Program, and it is currently funded by the Solar Radiation Resource Assessment Project. The objectives of the HBCU network are (1) To significantly improve the assessment of solar radiation resources in the southeastern United States; (2) To enlist the help of the HBCU's in collecting high-quality solar radiation data; (3) To encourage the distribution of solar radiation resource information and the development of solar energy applications in the Southeast; (4) To encourage the development of academic and research programs in solar energy at HBCU's.

  19. Before the year 2000: Artificial neural networks may set the standard

    SciTech Connect

    Michal, R.A.

    1994-07-01

    The use of artifical neural networks (ANNs) for monitoring of equipment and components in nuclear power plants could be commonplace before the turn of the century. Within five years, the relative inexpensiveness of neural networks could usher in a technology that will be used to detect incipient faults in machinery and increase effectiveness of maintenance scheduling. Working since November 1992 with the Electric Power Research Institute on research and development of the technology, SynEx and another Virginia-based company, A&T, Inc., will later this year demonstrate prototype ANN systems at Consolidated Edison Company and New York State Electric Gas fossil fuel power plants. (Fossil fuel plants were chosen for the project because of easier access, as opposed to the security measures in place at nuclear facilities.) The demonstration will utilize sensors and the neural network systems to detect abnormal equipment behavior, sending signals back to centralized monitoring boards located in each plant`s control room. The cost of the project, including research and development, will reach $1 million. However, the cost of installing a neural network at a nuclear plant within the next five years, according to Birdsall, could be as low as $10,000 to $15,000, with hopes of reducing the expenditure to just $5000.

  20. Recent developments in the setting up of the Malta Seismic Network

    NASA Astrophysics Data System (ADS)

    Agius, Matthew; Galea, Pauline; D'Amico, Sebastiano

    2015-04-01

    Weak to moderate earthquakes in the Sicily Channel have until now been either poorly located or left undetected. The number of seismic stations operated by various networks: Italy (INGV), Tunisia (TT), and Libya (LNSN) have now improved considerably, however most of the seismicity occurs offshore, in the central part of the Channel, away from the mainland stations. Seismic data availability from island stations across the Channel has been limited or had intermittent transmission hindering proper real-time earthquake monitoring and hypocentre relocation. In order to strengthen the seismic monitoring of the Sicily Channel, in particular the central parts of the Channel, the Seismic Monitoring and Research Unit (SMRU), University of Malta, has, in the last year, been installing a permanent seismic network across the Maltese archipelago: the Malta Seismic Network (ML). Furthermore the SMRU has upgraded its IT facilities to run a virtual regional seismic network composed of the stations on Pantelleria and Lampedusa, together with all the currently publicly available stations in the region. Selected distant seismic stations found elsewhere in the Mediterranean and across the globe have also been incorporated in the system in order to enhance the overall performance of the monitoring and to detect potentially damaging regional earthquakes. Data acquisition and processing of the seismic networks are run by SeisComP. The new installations are part of the project SIMIT (B1-2.19/11) funded by the Italia-Malta Operational Programme 2007-2013. The new system allows the SMRU to rapidly perform more accurate hypocentre locations in the region, and issue automatic SMS alert for potentially felt events in the Sicily Channel detected by the network and for strong earthquakes elsewhere. Within the SIMIT project, the alert system will include civil protection departments in Malta and Sicily. We present the recent developments of the real and virtual seismic network, and discuss the

  1. A new efficient algorithm generating all minimal S-T cut-sets in a graph-modeled network

    NASA Astrophysics Data System (ADS)

    Malinowski, Jacek

    2016-06-01

    A new algorithm finding all minimal s-t cut-sets in a graph-modeled network with failing links and nodes is presented. It is based on the analysis of the tree of acyclic s-t paths connecting a given pair of nodes in the considered structure. The construction of such a tree is required by many existing algorithms for s-t cut-sets generation in order to eliminate "stub" edges or subgraphs through which no acyclic path passes. The algorithm operates on the acyclic paths tree alone, i.e. no other analysis of the network's topology is necessary. It can be applied to both directed and undirected graphs, as well as partly directed ones. It is worth noting that the cut-sets can be composed of both links and failures, while many known algorithms do not take nodes into account, which is quite restricting from the practical point of view. The developed cut-sets generation technique makes the algorithm significantly faster than most of the previous methods, as proved by the experiments.

  2. LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

    PubMed

    Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

    2016-01-01

    Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher. PMID:26750448

  3. LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights

    PubMed Central

    Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

    2016-01-01

    Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher’s exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO’s usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher. PMID:26750448

  4. A Validated Set of MIDAS V5 Task Network Model Scenarios to Evaluate Nextgen Closely Spaced Parallel Operations Concepts

    NASA Technical Reports Server (NTRS)

    Gore, Brian Francis; Hooey, Becky Lee; Haan, Nancy; Socash, Connie; Mahlstedt, Eric; Foyle, David C.

    2013-01-01

    The Closely Spaced Parallel Operations (CSPO) scenario is a complex, human performance model scenario that tested alternate operator roles and responsibilities to a series of off-nominal operations on approach and landing (see Gore, Hooey, Mahlstedt, Foyle, 2013). The model links together the procedures, equipment, crewstation, and external environment to produce predictions of operator performance in response to Next Generation system designs, like those expected in the National Airspaces NextGen concepts. The task analysis that is contained in the present report comes from the task analysis window in the MIDAS software. These tasks link definitions and states for equipment components, environmental features as well as operational contexts. The current task analysis culminated in 3300 tasks that included over 1000 Subject Matter Expert (SME)-vetted, re-usable procedural sets for three critical phases of flight; the Descent, Approach, and Land procedural sets (see Gore et al., 2011 for a description of the development of the tasks included in the model; Gore, Hooey, Mahlstedt, Foyle, 2013 for a description of the model, and its results; Hooey, Gore, Mahlstedt, Foyle, 2013 for a description of the guidelines that were generated from the models results; Gore, Hooey, Foyle, 2012 for a description of the models implementation and its settings). The rollout, after landing checks, taxi to gate and arrive at gate illustrated in Figure 1 were not used in the approach and divert scenarios exercised. The other networks in Figure 1 set up appropriate context settings for the flight deck.The current report presents the models task decomposition from the tophighest level and decomposes it to finer-grained levels. The first task that is completed by the model is to set all of the initial settings for the scenario runs included in the model (network 75 in Figure 1). This initialization process also resets the CAD graphic files contained with MIDAS, as well as the embedded

  5. The European VLF/LF radio network to search for earthquake precursors: setting up and natural/man-made disturbances

    NASA Astrophysics Data System (ADS)

    Biagi, P. F.; Maggipinto, T.; Righetti, F.; Loiacono, D.; Schiavulli, L.; Ligonzo, T.; Ermini, A.; Moldovan, I. A.; Moldovan, A. S.; Buyuksarac, A.; Silva, H. G.; Bezzeghoud, M.; Contadakis, M. E.

    2011-02-01

    In the last years disturbances in VLF/LF radio signals related to seismic activity have been presented. The radio data were collected by receivers located on the ground or on satellites. The ground-based research implies systematic data collection by a network of receivers. Since 2000 the "Pacific VLF network", conducted by Japanese researchers, has been in operation. During 2008 a radio receiver was developed by the Italian factory Elettronika (Palo del Colle, Bari). The receiver is equipment working in VLF and LF bands. It can monitor 10 frequencies distributed in these bands and, for each of them, it saves the power level. At the beginning of 2009, five receivers were made for the realization of the "European VLF/LF Network"; two were planned for Italy and one for Greece, Turkey and Romania, respectively. In 2010 the network was enlarged to include a new receiver installed in Portugal. In this work, first the receiver and its setting up in the different places are described. Then, several disturbances in the radio signals related to the transmitters, receivers, meteorological/geomagnetic conditions are presented and described.

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

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

  7. Searching for optimal setting conditions in technological processes using parametric estimation models and neural network mapping approach: a tutorial.

    PubMed

    Fjodorova, Natalja; Novič, Marjana

    2015-09-01

    Engineering optimization is an actual goal in manufacturing and service industries. In the tutorial we represented the concept of traditional parametric estimation models (Factorial Design (FD) and Central Composite Design (CCD)) for searching optimal setting parameters of technological processes. Then the 2D mapping method based on Auto Associative Neural Networks (ANN) (particularly, the Feed Forward Bottle Neck Neural Network (FFBN NN)) was described in comparison with traditional methods. The FFBN NN mapping technique enables visualization of all optimal solutions in considered processes due to the projection of input as well as output parameters in the same coordinates of 2D map. This phenomenon supports the more efficient way of improving the performance of existing systems. Comparison of two methods was performed on the bases of optimization of solder paste printing processes as well as optimization of properties of cheese. Application of both methods enables the double check. This increases the reliability of selected optima or specification limits. PMID:26388367

  8. Structured Set Intra Prediction With Discriminative Learning in a Max-Margin Markov Network for High Efficiency Video Coding

    PubMed Central

    Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen

    2014-01-01

    This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829

  9. Paediatric Obesity Research in Early Childhood and the Primary Care Setting: The TARGet Kids! Research Network

    PubMed Central

    Morinis, Julia; Maguire, Jonathon; Khovratovich, Marina; McCrindle, Brian W.; Parkin, Patricia C.; Birken, Catherine S.

    2012-01-01

    Primary paediatric health care is the foundation for preventative child health. In light of the recent obesity epidemic, paediatricians find themselves at the frontline of identification and management of childhood obesity. However, it is well recognized that evidence based approaches to obesity prevention and subsequent translation of this evidence into practice are critically needed. This paper explores the role of primary care in obesity prevention and introduces a novel application and development of a primary care research network in Canada—TARGet Kids!—to develop and translate an evidence-base on effective screening and prevention of childhood obesity. PMID:22690197

  10. Heuristic method for searches on large data-sets organised using network models

    NASA Astrophysics Data System (ADS)

    Ruiz-Fernández, D.; Quintana-Pacheco, Y.

    2016-05-01

    Searches on large data-sets have become an important issue in recent years. An alternative, which has achieved good results, is the use of methods relying on data mining techniques, such as cluster-based retrieval. This paper proposes a heuristic search that is based on an organisational model that reflects similarity relationships among data elements. The search is guided by using quality estimators of model nodes, which are obtained by the progressive evaluation of the given target function for the elements associated with each node. The results of the experiments confirm the effectiveness of the proposed algorithm. High-quality solutions are obtained evaluating a relatively small percentage of elements in the data-sets.

  11. The Armutlu Network: An Investigation on seismotectonic setting of Armutlu-Yalova-Gemlik and Surrounding Regions

    NASA Astrophysics Data System (ADS)

    Tunc, Berna; Woith, Heiko; Ćaka, Deniz; Tunć, Süleyman; Bariş, Å.žErif; Fırat Özer, Mithat; Lühr, Birger; Serkan Irmak, Tahir; Günther, Erwin; Grosser, Helmut; Zschau, Jochen

    2010-05-01

    Yalova-Armutlu-Gemlik region is located on the Marmara Region and western-southwestern part of the 1999 Kocaeli rupture. This region is characterized by strong deformations and is located between two main strands of the North Anatolian Fault system. The Armutlu peninsula is believed to be adjacent to the Intra-Pontid Suture Zone or is even a part of it. This zone and region has a key role to understand neo-tectonic feature of the region and the interaction between high seismicity with high thermal activity and neo-tectonic faults originated by ongoing movement of the two branches of north and south of Armutlu. A horst and graben structure appears in this region whereby the Armutlu Peninsula represents a horst between two branches of the North Anatolian Fault System, resulting in a complex dextral zone. In order to have a better understanding of the relation between micro-earthquake activity, hydrothermal activity and recent stress state of the study region, ARNET (Armutlu Network) was installed by Kocaeli University Earth and Space Science Research Center (ESSRC-YUBAM) at September 2005 with 10 broadband seismic stations. After 6 months, another 10 short period REFTEK stations were added to the network. As a result, we now have 23 seismic stations and 5 hydrothermal stations in and around study area. In June 2009, we replaced REFTEK digitizers with GURALP digitizers at the short period seismic stations. The phase readings obtained from network are performed by zSacWin aigorithm. We also installed ADSL data transmission systems at 12 seismic stations. Currently, we are in the process of installing online communication system to the remaining seismic stations in our network. We also installed SeisComP3 software for data acquisition and automatic location procedure at September 2009. This system is now is in the testing phase. We obtained preliminary micro-earthquake activity of the said region and it shows that the (present) seismic activity increased after the 1999

  12. Spatial Fingerprints of Community Structure in Human Interaction Network for an Extensive Set of Large-Scale Regions

    PubMed Central

    Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor

    2015-01-01

    Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization. PMID:25993329

  13. SELPHI: correlation-based identification of kinase-associated networks from global phospho-proteomics data sets

    PubMed Central

    Petsalaki, Evangelia; Helbig, Andreas O.; Gopal, Anjali; Pasculescu, Adrian; Roth, Frederick P.; Pawson, Tony

    2015-01-01

    While phospho-proteomics studies have shed light on the dynamics of cellular signaling, they mainly describe global effects and rarely explore mechanistic details, such as kinase/substrate relationships. Tools and databases, such as NetworKIN and PhosphoSitePlus, provide valuable regulatory details on signaling networks but rely on prior knowledge. They therefore provide limited information on less studied kinases and fewer unexpected relationships given that better studied signaling events can mask condition- or cell-specific ‘network wiring’. SELPHI is a web-based tool providing in-depth analysis of phospho-proteomics data that is intuitive and accessible to non-bioinformatics experts. It uses correlation analysis of phospho-sites to extract kinase/phosphatase and phospho-peptide associations, and highlights the potential flow of signaling in the system under study. We illustrate SELPHI via analysis of phospho-proteomics data acquired in the presence of erlotinib—a tyrosine kinase inhibitor (TKI)—in cancer cells expressing TKI-resistant and -sensitive variants of the Epidermal Growth Factor Receptor. In this data set, SELPHI revealed information overlooked by the reporting study, including the known role of MET and EPHA2 kinases in conferring resistance to erlotinib in TKI sensitive strains. SELPHI can significantly enhance the analysis of phospho-proteomics data contributing to improved understanding of sample-specific signaling networks. SELPHI is freely available via http://llama.mshri.on.ca/SELPHI. PMID:25948583

  14. SELPHI: correlation-based identification of kinase-associated networks from global phospho-proteomics data sets.

    PubMed

    Petsalaki, Evangelia; Helbig, Andreas O; Gopal, Anjali; Pasculescu, Adrian; Roth, Frederick P; Pawson, Tony

    2015-07-01

    While phospho-proteomics studies have shed light on the dynamics of cellular signaling, they mainly describe global effects and rarely explore mechanistic details, such as kinase/substrate relationships. Tools and databases, such as NetworKIN and PhosphoSitePlus, provide valuable regulatory details on signaling networks but rely on prior knowledge. They therefore provide limited information on less studied kinases and fewer unexpected relationships given that better studied signaling events can mask condition- or cell-specific 'network wiring'. SELPHI is a web-based tool providing in-depth analysis of phospho-proteomics data that is intuitive and accessible to non-bioinformatics experts. It uses correlation analysis of phospho-sites to extract kinase/phosphatase and phospho-peptide associations, and highlights the potential flow of signaling in the system under study. We illustrate SELPHI via analysis of phospho-proteomics data acquired in the presence of erlotinib-a tyrosine kinase inhibitor (TKI)-in cancer cells expressing TKI-resistant and -sensitive variants of the Epidermal Growth Factor Receptor. In this data set, SELPHI revealed information overlooked by the reporting study, including the known role of MET and EPHA2 kinases in conferring resistance to erlotinib in TKI sensitive strains. SELPHI can significantly enhance the analysis of phospho-proteomics data contributing to improved understanding of sample-specific signaling networks. SELPHI is freely available via http://llama.mshri.on.ca/SELPHI. PMID:25948583

  15. Spatial fingerprints of community structure in human interaction network for an extensive set of large-scale regions.

    PubMed

    Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor

    2015-01-01

    Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization. PMID:25993329

  16. An Electronic Nose System Using Artificial Neural Networks with anEffective Initial Training Data Set

    NASA Astrophysics Data System (ADS)

    Charumporn, Bancha; Yoshioka, Michifumi; Omatu, Sigeru

    Nowadays there are several commercial electrical noses (ENs) applied in many applications, mainly in food and cosmetics industries. Most of them have been added with complicated mechanisms to control the measuring environment. Consequently, they are large in size and expensive. However, the reliability of those ENs can be achieved only at moderate levels. Therefore, a simple EN system with an effective method to analyze the data is proposed as an alternative way for classifying smells. The EN has not been added with a mechanism to control the measuring environment. Thus, the EN system is inexpensive, small and can be operated easily. However, a normalization method need to be utilized to reduce the effect of measuring environment. Then a method to select the representative training data for artificial neural networks (ANNs) based on a similarity index (SI) value is applied to reduce the training time. The results show the ability of the EN that is able to classify not only different kinds of smoke but also the same kind of smoke from different brands and different concentration levels quite precisely.

  17. Spiking neural networks with different reinforcement learning (RL) schemes in a multiagent setting.

    PubMed

    Christodoulou, Chris; Cleanthous, Aristodemos

    2010-12-31

    This paper investigates the effectiveness of spiking agents when trained with reinforcement learning (RL) in a challenging multiagent task. In particular, it explores learning through reward-modulated spike-timing dependent plasticity (STDP) and compares it to reinforcement of stochastic synaptic transmission in the general-sum game of the Iterated Prisoner's Dilemma (IPD). More specifically, a computational model is developed where we implement two spiking neural networks as two "selfish" agents learning simultaneously but independently, competing in the IPD game. The purpose of our system (or collective) is to maximise its accumulated reward in the presence of reward-driven competing agents within the collective. This can only be achieved when the agents engage in a behaviour of mutual cooperation during the IPD. Previously, we successfully applied reinforcement of stochastic synaptic transmission to the IPD game. The current study utilises reward-modulated STDP with eligibility trace and results show that the system managed to exhibit the desired behaviour by establishing mutual cooperation between the agents. It is noted that the cooperative outcome was attained after a relatively short learning period which enhanced the accumulation of reward by the system. As in our previous implementation, the successful application of the learning algorithm to the IPD becomes possible only after we extended it with additional global reinforcement signals in order to enhance competition at the neuronal level. Moreover it is also shown that learning is enhanced (as indicated by an increased IPD cooperative outcome) through: (i) strong memory for each agent (regulated by a high eligibility trace time constant) and (ii) firing irregularity produced by equipping the agents' LIF neurons with a partial somatic reset mechanism. PMID:21793357

  18. Providing Access to CD-ROM Databases in a Campus Setting. Part II: Networking CD-ROMs via a LAN.

    ERIC Educational Resources Information Center

    Koren, Judy

    1992-01-01

    The second part of a report on CD-ROM networking in libraries describes LAN (local area network) technology; networking software and towers; gateway software for connecting to campuswide networks; Macintosh LANs; and network licenses. Several product and software reviews are included, and a sidebar lists vendor addresses. (NRP)

  19. Universal set of dynamically protected gates for bipartite qubit networks: Soft pulse implementation of the [[5,1,3

    NASA Astrophysics Data System (ADS)

    De, Amrit; Pryadko, Leonid P.

    2016-04-01

    We model repetitive quantum error correction (QEC) with the single-error-correcting five-qubit code on a network of individually controlled qubits with always-on Ising couplings. We use our previously designed universal set of quantum gates based on sequences of shaped decoupling pulses. In addition to being accurate quantum gates, the sequences also provide dynamical decoupling (DD) of low-frequency phase noise. The simulation involves integrating the unitary dynamics of six qubits over the duration of tens of thousands of control pulses, using classical stochastic phase noise as a source of decoherence. The combined DD and QEC protocol dramatically improves the coherence, with the QEC alone being responsible for more than an order of magnitude infidelity reduction.

  20. The Setting-up of Multi-Site School Collaboratives: The Benefits of This Organizational Reform in Terms of Networking Opportunities and Their Effects

    ERIC Educational Resources Information Center

    Mifsud, Denise

    2015-01-01

    This article, which is set within the Maltese education scenario of unfolding decentralization through the setting-up of multi-site school collaboratives (legally termed "colleges") via a policy mandate, explores a particular aspect of this reform--that of "networking". This is examined in terms of the potential for…

  1. Energy-efficient key distribution using electrocardiograph biometric set for secure communications in wireless body healthcare networks.

    PubMed

    Shi, Jinyang; Lam, Kwok-Yan; Gu, Ming; Li, Mingze; Chung, Siu-Leung

    2011-10-01

    Wireless body sensor network (WBSN) has gained significant interests as an important infrastructure for real-time biomedical healthcare systems, while the security of the sensitive health information becomes one of the main challenges. Due to the constraints of limited power, traditional cryptographic key distribution schemes are not suitable for WBSN. This paper proposes a novel energy-efficient approach, BodyKey, which can distribute the keys using the electrocardiograph biometrics. BodyKey represents the biometric features as ordered set, and deals with the biometric variations using set reconciliation. In this way, only limited necessary information needs to be communicated for key agreement, and the total energy consumption for key distribution can thus be reduced. Experiments on the PhysioBank Database show that BodyKey can perform an energy consumption rate of 0.01 mJ/bit with an equal accuracy rate of 97.28%, allowing the system to be used as an energy-efficient key distribution scheme for secure communications in WBSN. PMID:20703727

  2. Practice-Based Research Networks, Part II: A Descriptive Analysis of the Athletic Training Practice-Based Research Network in the Secondary School Setting

    PubMed Central

    McLeod, Tamara C. Valovich; Lam, Kenneth C.; Bay, R. Curtis; Sauers, Eric L.; Valier, Alison R. Snyder

    2012-01-01

    Context Analysis of health care service models requires the collection and evaluation of basic practice characterization data. Practice-based research networks (PBRNs) provide a framework for gathering data useful in characterizing clinical practice. Objective To describe preliminary secondary school setting practice data from the Athletic Training Practice-Based Research Network (AT-PBRN). Design Descriptive study. Setting Secondary school athletic training facilities within the AT-PBRN. Patients or Other Participants Clinicians (n = 22) and their patients (n = 2523) from the AT-PBRN. Main Outcome Measure(s) A Web-based survey was used to obtain data on clinical practice site and clinician characteristics. Patient and practice characteristics were obtained via deidentified electronic medical record data collected between September 1, 2009, and April 1, 2011. Descriptive data regarding the clinician and CPS practice characteristics are reported as percentages and frequencies. Descriptive analysis of patient encounters and practice characteristic data was performed, with the percentages and frequencies of the type of injuries recorded at initial evaluation, type of treatment received at initial evaluation, daily treatment, and daily sign-in procedures. Results The AT-PBRN had secondary school sites in 7 states, and most athletic trainers at those sites (78.2%) had less than 5 years of experience. The secondary school sites within the AT-PBRN documented 2523 patients treated across 3140 encounters. Patients most frequently sought care for a current injury (61.3%), followed by preventive services (24.0%), and new injuries (14.7%). The most common diagnoses were ankle sprain/strain (17.9%), hip sprain/strain (12.5%), concussion (12.0%), and knee pain (2.5%). The most frequent procedures were athletic trainer evaluation (53.9%), hot- or cold-pack application (26.0%), strapping (10.3%), and therapeutic exercise (5.7%). The median number of treatments per injury was 3

  3. Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

    NASA Astrophysics Data System (ADS)

    Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

    2013-03-01

    Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

  4. Naturally-Emerging Technology-Based Leadership Roles in Three Independent Schools: A Social Network-Based Case Study Using Fuzzy Set Qualitative Comparative Analysis

    ERIC Educational Resources Information Center

    Velastegui, Pamela J.

    2013-01-01

    This hypothesis-generating case study investigates the naturally emerging roles of technology brokers and technology leaders in three independent schools in New York involving 92 school educators. A multiple and mixed method design utilizing Social Network Analysis (SNA) and fuzzy set Qualitative Comparative Analysis (FSQCA) involved gathering…

  5. A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations

    PubMed Central

    Lu, Le; Seff, Ari; Cherry, Kevin M.; Hoffman, Joanne; Wang, Shijun; Liu, Jiamin; Turkbey, Evrim; Summers, Ronald M.

    2015-01-01

    Automated Lymph Node (LN) detection is an important clinical diagnostic task but very challenging due to the low contrast of surrounding structures in Computed Tomography (CT) and to their varying sizes, poses, shapes and sparsely distributed locations. State-of-the-art studies show the performance range of 52.9% sensitivity at 3.1 false-positives per volume (FP/vol.), or 60.9% at 6.1 FP/vol. for mediastinal LN, by one-shot boosting on 3D HAAR features. In this paper, we first operate a preliminary candidate generation stage, towards ~100% sensitivity at the cost of high FP levels (~40 per patient), to harvest volumes of interest (VOI). Our 2.5D approach consequently decomposes any 3D VOI by resampling 2D reformatted orthogonal views N times, via scale, random translations, and rotations with respect to the VOI centroid coordinates. These random views are then used to train a deep Convolutional Neural Network (CNN) classifier. In testing, the CNN is employed to assign LN probabilities for all N random views that can be simply averaged (as a set) to compute the final classification probability per VOI. We validate the approach on two datasets: 90 CT volumes with 388 mediastinal LNs and 86 patients with 595 abdominal LNs. We achieve sensitivities of 70%/83% at 3 FP/vol. and 84%/90% at 6 FP/vol. in mediastinum and abdomen respectively, which drastically improves over the previous state-of-the-art work. PMID:25333158

  6. 78 FR 79649 - Energy Conservation Program: Proposed Determination of Set-Top Boxes and Network Equipment as a...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-12-31

    ... network equipment qualify as a covered product. 76 FR 34914. Subsequently, DOE initiated the rulemaking... procedures used by industry to measure the energy consumption of STBs and network equipment. 76 FR 78174. DOE... procedure focused exclusively on STBs. 78 FR 5076. DOE held a public meeting and requested...

  7. Instructor Experiences with a Social Networking Site in a Higher Education Setting: Expectations, Frustrations, Appropriation, and Compartmentalization

    ERIC Educational Resources Information Center

    Veletsianos, George; Kimmons, Royce; French, Karen D.

    2013-01-01

    Researchers and practitioners have suggested that the use of social networking sites in formal education may be a worthwhile endeavor. Toward this goal, emerging learning platforms have included social networking features. Nevertheless, empirical literature examining user experiences, and more specifically instructor experiences, with these tools…

  8. From global agenda-setting to domestic implementation: successes and challenges of the global health network on tobacco control.

    PubMed

    Gneiting, Uwe

    2016-04-01

    Global policy attention to tobacco control has increased significantly since the 1990 s and culminated in the first international treaty negotiated under the auspices of the World Health Organization--the Framework Convention on Tobacco Control (FCTC). Although the political process that led to the creation of the FCTC has been extensively researched, the FCTC's progression from an aspirational treaty towards a global health governance framework with tangible policy effects within FCTC member countries has not been well-understood to date. This article analyses the role of the global health network of tobacco control advocates and scientists, which formed during the FCTC negotiations during the late 1990 s, in translating countries' commitment to the FCTC into domestic policy change. By comparing the network's influence around two central tobacco control interventions (smoke-free environments and taxation), the study identifies several scope conditions, which have shaped the network's effectiveness around the FCTC's implementation: the complexity of the policy issue and the relative importance of non-health expertise, the required scope of domestic political buy-in, the role of the general public as network allies, and the strength of policy opposition. These political factors had a greater influence on the network's success than the evidence base for the effectiveness of tobacco control interventions. The network's variable success points to a trade-off faced by global health networks between their need to maintain internal cohesion and their ability to form alliances with actors in their social environment. PMID:26253698

  9. The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo

    PubMed Central

    2006-01-01

    We present a method (the Inferelator) for deriving genome-wide transcriptional regulatory interactions, and apply the method to predict a large portion of the regulatory network of the archaeon Halobacterium NRC-1. The Inferelator uses regression and variable selection to identify transcriptional influences on genes based on the integration of genome annotation and expression data. The learned network successfully predicted Halobacterium's global expression under novel perturbations with predictive power similar to that seen over training data. Several specific regulatory predictions were experimentally tested and verified. PMID:16686963

  10. How to Set Up a Telefacsimile Network--The Pennsylvania Libraries' Experience and Is There a FAX in Your Future?

    ERIC Educational Resources Information Center

    Wilson, Mark; Gordon, Helen A.

    1988-01-01

    Describes telefacsimile (FAX) technology and discusses the Associated College Libraries of Central Pennsylvania project which is planning to implement a FAX network for member libraries. Guidelines for FAX use within Pennsylvania are included, and sidebar reviews recent developments in FAX add-ons, standalones, and applications. (MES)

  11. Attitudes toward Using Social Networking Sites in Educational Settings with Underperforming Latino Youth: A Mixed Methods Study

    ERIC Educational Resources Information Center

    Howard, Keith E.; Curwen, Margie Sauceda; Howard, Nicol R.; Colón-Muñiz, Anaida

    2015-01-01

    The researchers examined the online social networking attitudes of underperforming Latino high school students in an alternative education program that uses technology as the prime venue for learning. A sequential explanatory mixed methods study was used to cross-check multiple sources of data explaining students' levels of comfort with utilizing…

  12. Networks.

    ERIC Educational Resources Information Center

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

    2001-01-01

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

  13. On the ecogeomorphological feedbacks that control tidal channel network evolution in a sandy mangrove setting

    PubMed Central

    van Maanen, B.; Coco, G.; Bryan, K. R.

    2015-01-01

    An ecomorphodynamic model was developed to study how Avicennia marina mangroves influence channel network evolution in sandy tidal embayments. The model accounts for the effects of mangrove trees on tidal flow patterns and sediment dynamics. Mangrove growth is in turn controlled by hydrodynamic conditions. The presence of mangroves was found to enhance the initiation and branching of tidal channels, partly because the extra flow resistance in mangrove forests favours flow concentration, and thus sediment erosion in between vegetated areas. The enhanced branching of channels is also the result of a vegetation-induced increase in erosion threshold. On the other hand, this reduction in bed erodibility, together with the soil expansion driven by organic matter production, reduces the landward expansion of channels. The ongoing accretion in mangrove forests ultimately drives a reduction in tidal prism and an overall retreat of the channel network. During sea-level rise, mangroves can potentially enhance the ability of the soil surface to maintain an elevation within the upper portion of the intertidal zone, while hindering both the branching and headward erosion of the landward expanding channels. The modelling results presented here indicate the critical control exerted by ecogeomorphological interactions in driving landscape evolution. PMID:26339195

  14. Networking.

    ERIC Educational Resources Information Center

    Duvall, Betty

    Networking is an information giving and receiving system, a support system, and a means whereby women can get ahead in careers--either in new jobs or in current positions. Networking information can create many opportunities: women can talk about how other women handle situations and tasks, and previously established contacts can be used in…

  15. Management of Type 2 Diabetes in the Primary Care Setting: A Practice-Based Research Network Study

    PubMed Central

    Spann, Stephen J.; Nutting, Paul A.; Galliher, James M.; Peterson, Kevin A.; Pavlik, Valory N.; Dickinson, L. Miriam; Volk, Robert J.

    2006-01-01

    PURPOSE We wanted to describe how primary care clinicians care for patients with type 2 diabetes. METHODS We undertook a cross-sectional study of 95 primary care clinicians and 822 of their established patients with type 2 diabetes from 4 practice-based, primary care research networks in the United States. Clinicians were surveyed about their training and practice. Patients completed a self-administered questionnaire about their care, and medical records were reviewed for complications, treatment, and diabetes-control indicators. RESULTS Participating clinicians (average age, 45.7 years) saw an average of 32.6 adult patients with diabetes per month. Patients (average age, 59.7 years) reported a mean duration of diabetes of 9.1 years, with 34.3% having had the disease more than 10 years. Nearly one half (47.5%) of the patients had at least 1 diabetes-related complication, and 60.8% reported a body mass index greater than 30. Mean glycosylated hemoglobin (HbA1c) level was 7.6% (SD 1.73), and 40.5% of patients had values <7%. Only 35.3% of patients had adequate blood pressure control (<130/85 mm Hg), and only 43.7% had low-density lipoprotein cholesterol (LDL-C) levels <100 mg/dL. Only 7.0% of patients met all 3 control targets. Multilevel models showed that patient ethnicity, practice type, involvement of midlevel clinicians, and treatment were associated with HbA1c level; patient age, education level, and practice type were associated with blood pressure control; and patient ethnicity was associated with LDL-C control. CONCLUSIONS Only modest numbers of patients achieve established targets of diabetes control. Reengineering primary care practice may be necessary to substantially improve care. PMID:16449393

  16. Event-based distributed set-membership filtering for a class of time-varying non-linear systems over sensor networks with saturation effects

    NASA Astrophysics Data System (ADS)

    Wei, Guoliang; Liu, Shuai; Wang, Licheng; Wang, Yongxiong

    2016-07-01

    In this paper, based on the event-triggered mechanism, the problem of distributed set-membership filtering is concerned for a class of time-varying non-linear systems over sensor networks subject to saturation effects. Different from the traditional periodic sample-data approach, the filter is updated only when the predefined event is satisfied, which the event is defined according to the measurement output. For each node, the proposed novel event-triggered mechanism can reduce the unnecessary information transmission between sensors and filters. The purpose of the addressed problem is to design a series of distributed set-membership filters, for all the admissible unknown but bounded noises, non-linearities and sensor saturation, such that the set of all possible states can be determined. The desired filter parameters are obtained by solving a recursive linear matrix inequality that can be computed recursively using the available MATLAB toolbox. Finally, a simulation example is exploited to show the effectiveness of the proposed design approach in this paper.

  17. Computer image analysis in obtaining characteristics of images: greenhouse tomatoes in the process of generating learning sets of artificial neural networks

    NASA Astrophysics Data System (ADS)

    Zaborowicz, M.; Przybył, J.; Koszela, K.; Boniecki, P.; Mueller, W.; Raba, B.; Lewicki, A.; Przybył, K.

    2014-04-01

    The aim of the project was to make the software which on the basis on image of greenhouse tomato allows for the extraction of its characteristics. Data gathered during the image analysis and processing were used to build learning sets of artificial neural networks. Program enables to process pictures in jpeg format, acquisition of statistical information of the picture and export them to an external file. Produced software is intended to batch analyze collected research material and obtained information saved as a csv file. Program allows for analysis of 33 independent parameters implicitly to describe tested image. The application is dedicated to processing and image analysis of greenhouse tomatoes. The program can be used for analysis of other fruits and vegetables of a spherical shape.

  18. Hydro-climatic data network (HCDN); a U.S. Geological Survey streamflow data set for the United States for the study of climate variations, 1874-1988

    USGS Publications Warehouse

    Slack, J.R.; Landwehr, Jurate Maciunas

    1992-01-01

    Records of streamflow can provide an account of climatic variation over a hydrologic basin. The ability to do so is conditioned on the absence of confounding factors that diminish the climate signal. A national data set of streamflow records that are relatively free of confounding anthropogenic influences has been developed for the purpose of studying the variation in surface-water conditions throughout the United States. Records in the U.S. Geological Survey (USGS) National Water Storage and Retrieval System (WATSTORE) data base for active and discontinued streamflow gaging stations through water year 1988 (that is, through September 30, 1988) were reviewed jointly with data specialists in each USGS District office. The resulting collection of stations, each with its respective period of record satisfying the qualifying criteria, is called the Hydro-Climatic Data Network, or HCDN. The HCDN consists of 1,659 sites throughout the United States and its territories, totaling 73,231 water years of daily mean discharge values. For each station in the HCDN, information necessary for its identification, along with any qualifying comments about the available record and a set of descriptive watershed characteristics are provided in tabular format in this report, both on paper and on computer disk (enclosed). For each station in the HCDN, the appropriate daily mean discharge values were compiled, and statistical characteristics, including monthly mean discharges and annual mean, minimum and maximum discharges, were derived. The discharge data values are provided in a companion report.

  19. Action Research Monographs. Complete Set. Pennsylvania Action Research Network, 1998-99. A Section 353 Project of the Pennsylvania Department of Education, Bureau of Adult Basic and Literacy Education. A Learning from Practice Project.

    ERIC Educational Resources Information Center

    Pennsylvania State Univ., McKeesport.

    This publication consists of the complete set of 23 monographs developed by the Pennsylvania Action Research Network to supplement the 67 monographs produced over the past 3 years. The specific audience are literacy, General Educational Development (GED), and English-as-a Second Language (ESL) practitioners. The titles are: "Use of Metacognitive…

  20. Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

    PubMed

    Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

    2013-12-01

    Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

  1. Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

    PubMed Central

    Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

    2013-01-01

    Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

  2. The Use of Alternative Social Networking Sites in Higher Educational Settings: A Case Study of the E-Learning Benefits of Ning in Education

    ERIC Educational Resources Information Center

    Brady, Kevin P.; Holcomb, Lori B.; Smith, Bethany V.

    2010-01-01

    Distance education as a primary means of instruction is expanding significantly at the college and university level. Simultaneously, the growth of social networking sites (SNS) including Facebook, LinkedIn, and MySpace is also rising among today's college students. An increasing number of higher education instructors are beginning to combine…

  3. Text Sets.

    ERIC Educational Resources Information Center

    Giorgis, Cyndi; Johnson, Nancy J.

    2002-01-01

    Presents annotations of approximately 30 titles grouped in text sets. Defines a text set as five to ten books on a particular topic or theme. Discusses books on the following topics: living creatures; pirates; physical appearance; natural disasters; and the Irish potato famine. (SG)

  4. Recent developments and applications of a real-time tool to detect magma migration in different volcanic settings and network optimization.

    NASA Astrophysics Data System (ADS)

    Taisne, B.; Aoki, Y.; Caudron, C.

    2014-12-01

    Triggering mechanism of a seismic swarm has to be identified with great confidence in real time. Crisis response will not be the same whether magma is involved or not. The recent developments of a method based on the Seismic Amplitude Ratio Analysis enable a rapid and unambiguous diagnosis to detect migrating micro-seismicity. The beauty of this method lies in the fact that the ratio of seismic energy, recorded at different stations, is independent of the seismic energy radiated at the source and depends only on the location of the source and attenuation of the medium. Since drastic changes in attenuation are unlikely to occur at the time scale of magma intrusion, temporal evolutions in the measured ratio have to be explained by a change in the source location. Based on simple assumptions, this technique can be used to assess the potential of existing monitoring seismic network to detect migrating events in real-time. Of much importance, it can also be used to design monitoring seismic network based on the available number of sensors, as well as from field constraints. The method will be implemented in MSNoise software (http://www.msnoise.org/). This allows us to mine existing datasets, to compare the different noise-based techniques, but also to use the method for monitoring purposes. We will present how the key question: "Migration or No Migration" could be answered in real time without need of complex calculation nor full knowledge of the site effect and attenuation of the medium.

  5. Heat-set gel-like networks of lipophilic Co(II) triazole complexes in organic media and their thermochromic structural transitions.

    PubMed

    Kuroiwa, Keita; Shibata, Tomoko; Takada, Akihiko; Nemoto, Norio; Kimizuka, Nobuo

    2004-02-25

    A novel class of thermally responsive supramolecular assemblies is formed from the lipophilic cobalt(II) complexes of 4-alkylated 1,2,4-triazoles. When an ether linkage is introduced in the alkylchain moiety, a blue gel-like phase is formed in chloroform, even at very low concentration (ca. 0.01 wt %, at room temperature). The blue color is accompanied by a structured absorption around 580-730 nm, which is characteristic of cobalt (II) in the tetrahedral (T(d)) coordination. Atomic force microscopy (AFM) and transmission electron microscopy (TEM) of the gel-like phase confirms the formation of networks of fibrous nanoassemblies with widths of 5-30 nm. The observed widths are larger than a molecular length of the triazole ligand (ca. 2.2 nm) and they are consisted of aggregates of T(d) coordination polymers. Very interestingly, the blue gel-like phase turned into a solution by cooling below 25 degrees C. A pale pink solution is obtained at 0 degrees C, indicating the formation of octahedral (O(h)) complexes. The observed thermochromic transition is totally reversible. The formation of gel-like networks by heating is contrary to the conventional organogels, which dissolve upon heating. Temperature dependence of the storage and loss moduli (G' and G") shows minima around at 27 degrees C, at which temperature they gave comparable values. On the other hand, G' exceeds G" both in the gel-like phase (temperature above 27 degrees C) and in the solution phase (temperature below 25 degrees C). These observations indicate that T(d) complexes are present as low-molecular weight species around at 25-27 degrees C. They are self-assembled to polymeric T(d) complexes by heating and form gel-like networks. Upon cooling the solution below 25 degrees C, T(d) complexes are converted to O(h) complexes and they also self-assemble into oligomeric or polymeric species at lower temperatures. The observed unique thermochromic transition (pink solution --> blue gel-like phase) is accompanied

  6. Setting Objectives

    ERIC Educational Resources Information Center

    Elkins, Aaron J.

    1977-01-01

    The author questions the extent to which educators have relied on "relevance" and learner participation in objective-setting in the past decade. He describes a useful approach to learner-oriented evaluation in which content relevance was not judged by participants until after they had been exposed to it. (MF)

  7. SETS. Set Equation Transformation System

    SciTech Connect

    Worrel, R.B.

    1992-01-13

    SETS is used for symbolic manipulation of Boolean equations, particularly the reduction of equations by the application of Boolean identities. It is a flexible and efficient tool for performing probabilistic risk analysis (PRA), vital area analysis, and common cause analysis. The equation manipulation capabilities of SETS can also be used to analyze noncoherent fault trees and determine prime implicants of Boolean functions, to verify circuit design implementation, to determine minimum cost fire protection requirements for nuclear reactor plants, to obtain solutions to combinatorial optimization problems with Boolean constraints, and to determine the susceptibility of a facility to unauthorized access through nullification of sensors in its protection system.

  8. What's on YOUR Facebook profile? Evaluation of an educational intervention to promote appropriate use of privacy settings by medical students on social networking sites

    PubMed Central

    Walton, Jennifer M.; White, Jonathan; Ross, Shelley

    2015-01-01

    Background The rise of social media has led to growing concerns about the potential implications of ‘unprofessional’ postings by physicians and medical students on individuals, institutions, and the medical profession. Relevant and effective guidelines have been difficult to develop and enforce, and there is a need for students and physicians to consider how their online activities may be perceived in the context of their professional roles. The purpose of this project was to examine the Internet presence of a graduating Canadian medical school class by scanning students’ public profiles on the social media site Facebook, incorporate this information into an educational activity addressing professionalism and social media, and evaluate the impact of this activity on student behavior. Methods A systematic search for public Facebook profiles of each member of the class was conducted, and data were collected on the types of publicly visible material. These were presented as part of an educational session on social media and professionalism. One month later, the Facebook search was repeated. Results Of 152 students in the class, profiles were found for 121 (79.8%). The majority of students used appropriately restrictive privacy settings; however, a significant minority had publicly visible information, including comments, photographs, location, and status as a medical student. The educational innovation was well received with more than 90% of students agreeing that this topic was important and well addressed. A follow-up search found that many students had altered their privacy settings to make less information publicly available. Conclusions A small but significant proportion of students share potentially unprofessional content on social media. An interactive educational intervention, which includes specific disclosure of how participants appear to others on social media, resulted in a significant change in student behavior. PMID:26198434

  9. PS1-23: Capitalizing on the HMO Cancer Research Network (CRN): The Optimal Setting to Conduct Studies of Rare Complex Diseases

    PubMed Central

    Johnson, Christine Cole; Chao, Chun; Engel, Larry; Feigelson, Heather; Fortuny, Joan; Habel, Laurel; Koshiol, Jill; Roblin, Douglas; Spangler, Leslie; Wells, Karen; Yood, Marianne Ulcickas

    2013-01-01

    Background/Aims Rare cancers are challenging to study, both epidemiologically and clinically, as it is difficult to ascertain enough cases to achieve adequate statistical power or to be representative of a vast range of exposures. Further, as the complexity of unraveling the natural history of disease has increased, a large investigator team with diverse expertise is required to optimize the scientific contributions that can be mined from research projects. The HMOCRN provides a setting that can overcome these barriers. Although many studies evaluate all lymphomas combined, lymphoma consists of over 50 rare histological subtypes with varying incidence and survival rates and epidemiological features. Ideally, each histological subtype should be considered separately in etiological studies, but even the most common, diffuse large B cell lymphoma, has a SEER incidence of only 7.5 per 100,000 in men and 5.0 per 100,000 in women. Other lymphoma types range in incidence from <0.1 cases per 100,000 for NKT cell lymphoma to 2.8 per 100,000 for Hodgkin’s Disease in all race-sex groups combined, to the highest rate found for a population subgroup, only 8.8 per 100,000 for multiple myeloma in African American men. Methods We have assembled a multi-disciplinary team interested in lymphoma and pharmacoepidemiology that includes investigators with clinical, epidemiological and biostatistical expertise from six HMORN sites, two US universities, the NCI, and an international investigator who first initiated the project. Results Combining data from these HMOCRN sites from 1998–2008, we ascertained 1479 Hodgkin’s Disease cases, 3385 multiple myelomas, 771 T-cell lymphomas, (including 390 mycosis fungoides cases and 158 mature T-cell lymphomas), 3000 chronic lymphocytic leukemias, 1357 mature B cell lymphomas, 3883 diffuse large B cell lymphomas, 2188 follicular lymphomas, and 992 marginal zone B cell lymphomas. Conclusions These numbers provide a unique opportunity to analyze

  10. Network morphospace

    PubMed Central

    Avena-Koenigsberger, Andrea; Goñi, Joaquín; Solé, Ricard; Sporns, Olaf

    2015-01-01

    The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. This raises important questions about their origin, for example whether such network attributes reflect common design principles or constraints imposed by selectional forces that have shaped the evolution of network topology. Is it possible to place the many patterns and forms of complex networks into a common space that reveals their relations, and what are the main rules and driving forces that determine which positions in such a space are occupied by systems that have actually evolved? We suggest that these questions can be addressed by combining concepts from two currently relatively unconnected fields. One is theoretical morphology, which has conceptualized the relations between morphological traits defined by mathematical models of biological form. The second is network science, which provides numerous quantitative tools to measure and classify different patterns of local and global network architecture across disparate types of systems. Here, we explore a new theoretical concept that lies at the intersection between both fields, the ‘network morphospace’. Defined by axes that represent specific network traits, each point within such a space represents a location occupied by networks that share a set of common ‘morphological’ characteristics related to aspects of their connectivity. Mapping a network morphospace reveals the extent to which the space is filled by existing networks, thus allowing a distinction between actual and impossible designs and highlighting the generative potential of rules and constraints that pervade the evolution of complex systems. PMID:25540237

  11. Network morphospace.

    PubMed

    Avena-Koenigsberger, Andrea; Goñi, Joaquín; Solé, Ricard; Sporns, Olaf

    2015-02-01

    The structure of complex networks has attracted much attention in recent years. It has been noted that many real-world examples of networked systems share a set of common architectural features. This raises important questions about their origin, for example whether such network attributes reflect common design principles or constraints imposed by selectional forces that have shaped the evolution of network topology. Is it possible to place the many patterns and forms of complex networks into a common space that reveals their relations, and what are the main rules and driving forces that determine which positions in such a space are occupied by systems that have actually evolved? We suggest that these questions can be addressed by combining concepts from two currently relatively unconnected fields. One is theoretical morphology, which has conceptualized the relations between morphological traits defined by mathematical models of biological form. The second is network science, which provides numerous quantitative tools to measure and classify different patterns of local and global network architecture across disparate types of systems. Here, we explore a new theoretical concept that lies at the intersection between both fields, the 'network morphospace'. Defined by axes that represent specific network traits, each point within such a space represents a location occupied by networks that share a set of common 'morphological' characteristics related to aspects of their connectivity. Mapping a network morphospace reveals the extent to which the space is filled by existing networks, thus allowing a distinction between actual and impossible designs and highlighting the generative potential of rules and constraints that pervade the evolution of complex systems. PMID:25540237

  12. A combined community- and facility-based approach to improve pregnancy outcomes in low-resource settings: a Global Network cluster randomized trial

    PubMed Central

    2013-01-01

    Background Fetal and neonatal mortality rates in low-income countries are at least 10-fold greater than in high-income countries. These differences have been related to poor access to and poor quality of obstetric and neonatal care. Methods This trial tested the hypothesis that teams of health care providers, administrators and local residents can address the problem of limited access to quality obstetric and neonatal care and lead to a reduction in perinatal mortality in intervention compared to control locations. In seven geographic areas in five low-income and one middle-income country, most with high perinatal mortality rates and substantial numbers of home deliveries, we performed a cluster randomized non-masked trial of a package of interventions that included community mobilization focusing on birth planning and hospital transport, community birth attendant training in problem recognition, and facility staff training in the management of obstetric and neonatal emergencies. The primary outcome was perinatal mortality at ≥28 weeks gestation or birth weight ≥1000 g. Results Despite extensive effort in all sites in each of the three intervention areas, no differences emerged in the primary or any secondary outcome between the intervention and control clusters. In both groups, the mean perinatal mortality was 40.1/1,000 births (P = 0.9996). Neither were there differences between the two groups in outcomes in the last six months of the project, in the year following intervention cessation, nor in the clusters that best implemented the intervention. Conclusions This cluster randomized comprehensive, large-scale, multi-sector intervention did not result in detectable impact on the proposed outcomes. While this does not negate the importance of these interventions, we expect that achieving improvement in pregnancy outcomes in these settings will require substantially more obstetric and neonatal care infrastructure than was available at the sites during this trial

  13. Introduction to Fuzzy Set Theory

    NASA Technical Reports Server (NTRS)

    Kosko, Bart

    1990-01-01

    An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

  14. Network opportunity

    NASA Astrophysics Data System (ADS)

    Catanzaro, Michele; Buchanan, Mark

    2013-03-01

    Our developing scientific understanding of complex networks is being usefully applied in a wide set of financial systems. What we've learned from the 2008 crisis could be the basis of better management of the economy -- and a means to avert future disaster.

  15. Mutually connected component of networks of networks with replica nodes

    NASA Astrophysics Data System (ADS)

    Bianconi, Ginestra; Dorogovtsev, Sergey N.; Mendes, José F. F.

    2015-01-01

    We describe the emergence of the giant mutually connected component in networks of networks in which each node has a single replica node in any layer and can be interdependent only on its replica nodes in the interdependent layers. We prove that if, in these networks, all the nodes of one network (layer) are interdependent on the nodes of the same other interconnected layer, then, remarkably, the mutually connected component does not depend on the topology of the network of networks. This component coincides with the mutual component of the fully connected network of networks constructed from the same set of layers, i.e., a multiplex network.

  16. Robustness of Interdependent Networks

    NASA Astrophysics Data System (ADS)

    Havlin, Shlomo

    2011-03-01

    In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of many interdependent networks. We will present a framework for understanding the robustness of interacting networks subject to such cascading failures and provide a basic analytic approach that may be useful in future studies. We present exact analytical solutions for the critical fraction of nodes that upon removal will lead to a failure cascade and to a complete fragmentation of two interdependent networks in a first order transition. Surprisingly, analyzing complex systems as a set of interdependent networks may alter a basic assumption that network theory has relied on: while for a single network a broader degree distribution of the network nodes results in the network being more robust to random failures, for interdependent networks, the broader the distribution is, the more vulnerable the networks become to random failure. We also show that reducing the coupling between the networks leads to a change from a first order percolation phase transition to a second order percolation transition at a critical point. These findings pose a significant challenge to the future design of robust networks that need to consider the unique properties of interdependent networks.

  17. News Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

    NASA Astrophysics Data System (ADS)

    2011-09-01

    Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

  18. News Conference: Bloodhound races into history Competition: School launches weather balloon Course: Update weekends inspire teachers Conference: Finland hosts GIREP conference Astronomy: AstroSchools sets up schools network to share astronomy knowledge Teaching: Delegates praise science events in Wales Resources: ELI goes from strength to strength International: South Sudan teachers receive training Workshop: Delegates experience universality

    NASA Astrophysics Data System (ADS)

    2011-11-01

    Conference: Bloodhound races into history Competition: School launches weather balloon Course: Update weekends inspire teachers Conference: Finland hosts GIREP conference Astronomy: AstroSchools sets up schools network to share astronomy knowledge Teaching: Delegates praise science events in Wales Resources: ELI goes from strength to strength International: South Sudan teachers receive training Workshop: Delegates experience universality

  19. Communication networks

    NASA Astrophysics Data System (ADS)

    Kennedy, R. S.; Wagner, S. S.; Sia, E. B.

    1984-01-01

    A research program to determine and demonstrate the principles to be followed in the design of local communication networks as typified by local area networks, private branch exchanges and internetted collections of such structures is planned. Two fundamental assumptions distinguish the research from much of the ongoing work: (1) a single integrated system is to provide a set of highly diverse communication services such as interactive terminal service, data base access, file transfers, graphics, and voice and video; and (2) a single mode optical fiber links with very wide bandwidths is economical. These assumptions are not satisfied by the networks now being designed, but based upon the perceived trend toward such integrated diverse services and the declining cost of single mode fiber technology. It is planned for the research to involve theoretical, experimental, and design activities.

  20. Optimal Network-Topology Design

    NASA Technical Reports Server (NTRS)

    Li, Victor O. K.; Yuen, Joseph H.; Hou, Ting-Chao; Lam, Yuen Fung

    1987-01-01

    Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.

  1. UpSet: Visualization of Intersecting Sets

    PubMed Central

    Lex, Alexander; Gehlenborg, Nils; Strobelt, Hendrik; Vuillemot, Romain; Pfister, Hanspeter

    2016-01-01

    Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections. UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. We also introduce several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability. UpSet is web-based and open source. We demonstrate its general utility in multiple use cases from various domains. PMID:26356912

  2. Extracting information from multiplex networks

    NASA Astrophysics Data System (ADS)

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  3. Extracting information from multiplex networks.

    PubMed

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ̃(S) for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science. PMID:27368796

  4. Intelligent metro network

    NASA Astrophysics Data System (ADS)

    Luo, Zhongsheng; Kan, Yulun; Wang, Licun

    2001-10-01

    Metro networks have evolved dynamically since its position in the network infrastructure. To gain competitive advantage in this attractive market, carriers should emphasize not only just the power of their networks in terms of the speed, number of channels, distance covered, but also the network's versatility in supporting variety of access interfaces, flexibility in bandwidth provisioning, ability of differentiated service offering, and capability of network management. Based on an overview of four emerging metro network technologies, an intelligent metro network control platform is introduced. The intelligent control platform is necessary for carriers to meet the new metro requirements. Intelligent control and management functions of the platform are proposed respectively. Intelligent metro network will bridge the metro gap and open up a whole new set of services and applications.

  5. Concurrency and network disassortativity.

    PubMed

    Khor, Susan

    2010-01-01

    The relationship between a network's degree-degree correlation and a loose version of graph coloring is studied on networks with broad degree distributions. We find that, given similar conditions on the number of nodes, number of links, and clustering levels, fewer colors are needed to color disassortative than assortative networks. Since fewer colors create fewer independent sets, our finding implies that disassortative networks may have higher concurrency potential than assortative networks. This in turn suggests another reason for the disassortative mixing pattern observed in biological networks such as those of protein-protein interaction and gene regulation. In addition to the functional specificity and stability suggested by Maslov and Sneppen, a disassortative network topology may also enhance the ability of cells to perform crucial tasks concurrently. Hence, increased concurrency may also be a driving force in the evolution of biological networks. PMID:20586579

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Neural Networks

    SciTech Connect

    Smith, Patrick I.

    2003-09-23

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  8. Identification of genetic networks.

    PubMed Central

    Xiong, Momiao; Li, Jun; Fang, Xiangzhong

    2004-01-01

    In this report, we propose the use of structural equations as a tool for identifying and modeling genetic networks and genetic algorithms for searching the most likely genetic networks that best fit the data. After genetic networks are identified, it is fundamental to identify those networks influencing cell phenotypes. To accomplish this task we extend the concept of differential expression of the genes, widely used in gene expression data analysis, to genetic networks. We propose a definition for the differential expression of a genetic network and use the generalized T2 statistic to measure the ability of genetic networks to distinguish different phenotypes. However, describing the differential expression of genetic networks is not enough for understanding biological systems because differences in the expression of genetic networks do not directly reflect regulatory strength between gene activities. Therefore, in this report we also introduce the concept of differentially regulated genetic networks, which has the potential to assess changes of gene regulation in response to perturbation in the environment and may provide new insights into the mechanism of diseases and biological processes. We propose five novel statistics to measure the differences in regulation of genetic networks. To illustrate the concepts and methods for reconstruction of genetic networks and identification of association of genetic networks with function, we applied the proposed models and algorithms to three data sets. PMID:15020486

  9. Quantifying randomness in real networks

    NASA Astrophysics Data System (ADS)

    Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-10-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

  10. Quantifying randomness in real networks.

    PubMed

    Orsini, Chiara; Dankulov, Marija M; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-01-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs. PMID:26482121

  11. Celestial data routing network

    NASA Astrophysics Data System (ADS)

    Bordetsky, Alex

    2000-11-01

    Imagine that information processing human-machine network is threatened in a particular part of the world. Suppose that an anticipated threat of physical attacks could lead to disruption of telecommunications network management infrastructure and access capabilities for small geographically distributed groups engaged in collaborative operations. Suppose that small group of astronauts are exploring the solar planet and need to quickly configure orbital information network to support their collaborative work and local communications. The critical need in both scenarios would be a set of low-cost means of small team celestial networking. To the geographically distributed mobile collaborating groups such means would allow to maintain collaborative multipoint work, set up orbital local area network, and provide orbital intranet communications. This would be accomplished by dynamically assembling the network enabling infrastructure of the small satellite based router, satellite based Codec, and set of satellite based intelligent management agents. Cooperating single function pico satellites, acting as agents and personal switching devices together would represent self-organizing intelligent orbital network of cooperating mobile management nodes. Cooperative behavior of the pico satellite based agents would be achieved by comprising a small orbital artificial neural network capable of learning and restructing the networking resources in response to the anticipated threat.

  12. Management of coalition sensor networks

    NASA Astrophysics Data System (ADS)

    Verma, Dinesh Chandra; Brown, Theodore; Ortega, Carolyn

    2010-04-01

    The management of sensor networks in coalition settings has been treated in a piecemeal fashion in the current literature without taking a comprehensive look at the complete life cycle of coalition networks, and determining the different aspects of network management that need to be taken into account for the management of sensor networks in those contexts. In this paper, we provide a holistic approach towards managing sensor networks encountered in the context of coalition operations. We describe how the sensor networks in a coalition ought to be managed at various stages of the life cycle, and the different operations that need to be taken into account for managing various aspects of the networks. In particular, we look at the FCAPS model for network management, and assess the applicability of the FCAPS model to the different aspects of sensor network management in a coalition setting.

  13. SETS reference manual

    SciTech Connect

    Worrell, R.B.

    1985-05-01

    The Set Equation Transformation System (SETS) is used to achieve the symbolic manipulation of Boolean equations. Symbolic manipulation involves changing equations from their original forms into more useful forms - particularly by applying Boolean identities. The SETS program is an interpreter which reads, interprets, and executes SETS user programs. The user writes a SETS user program specifying the processing to be achieved and submits it, along with the required data, for execution by SETS. Because of the general nature of SETS, i.e., the capability to manipulate Boolean equations regardless of their origin, the program has been used for many different kinds of analysis.

  14. Competing edge networks

    NASA Astrophysics Data System (ADS)

    Parsons, Mark; Grindrod, Peter

    2012-06-01

    We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, subject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other's growth and encourage the other's demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails.

  15. Quantifying randomness in real networks

    PubMed Central

    Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-01-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks—the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain—and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs. PMID:26482121

  16. WATERSHED INFORMATION NETWORK

    EPA Science Inventory

    Resource Purpose:The Watershed Information Network is a set of about 30 web pages that are organized by topic. These pages access existing databases like the American Heritage Rivers Services database and Surf Your Watershed. WIN in itself has no data or data sets.
    L...

  17. Emergent Complex Network Geometry

    NASA Astrophysics Data System (ADS)

    Wu, Zhihao; Menichetti, Giulia; Rahmede, Christoph; Bianconi, Ginestra

    2015-05-01

    Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant for routing problems, inference and data mining. In real growing networks, topological, structural and geometrical properties emerge spontaneously from their dynamical rules. Nevertheless we still miss a model in which networks develop an emergent complex geometry. Here we show that a single two parameter network model, the growing geometrical network, can generate complex network geometries with non-trivial distribution of curvatures, combining exponential growth and small-world properties with finite spectral dimensionality. In one limit, the non-equilibrium dynamical rules of these networks can generate scale-free networks with clustering and communities, in another limit planar random geometries with non-trivial modularity. Finally we find that these properties of the geometrical growing networks are present in a large set of real networks describing biological, social and technological systems.

  18. Emergent Complex Network Geometry

    PubMed Central

    Wu, Zhihao; Menichetti, Giulia; Rahmede, Christoph; Bianconi, Ginestra

    2015-01-01

    Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant for routing problems, inference and data mining. In real growing networks, topological, structural and geometrical properties emerge spontaneously from their dynamical rules. Nevertheless we still miss a model in which networks develop an emergent complex geometry. Here we show that a single two parameter network model, the growing geometrical network, can generate complex network geometries with non-trivial distribution of curvatures, combining exponential growth and small-world properties with finite spectral dimensionality. In one limit, the non-equilibrium dynamical rules of these networks can generate scale-free networks with clustering and communities, in another limit planar random geometries with non-trivial modularity. Finally we find that these properties of the geometrical growing networks are present in a large set of real networks describing biological, social and technological systems. PMID:25985280

  19. Sets, Planets, and Comets

    ERIC Educational Resources Information Center

    Baker, Mark; Beltran, Jane; Buell, Jason; Conrey, Brian; Davis, Tom; Donaldson, Brianna; Detorre-Ozeki, Jeanne; Dibble, Leila; Freeman, Tom; Hammie, Robert; Montgomery, Julie; Pickford, Avery; Wong, Justine

    2013-01-01

    Sets in the game "Set" are lines in a certain four-dimensional space. Here we introduce planes into the game, leading to interesting mathematical questions, some of which we solve, and to a wonderful variation on the game "Set," in which every tableau of nine cards must contain at least one configuration for a player to pick up.

  20. Data in support of a central role of plasminogen activator inhibitor-2 polymorphism in recurrent cardiovascular disease risk in the setting of high HDL cholesterol and C-reactive protein using Bayesian network modeling.

    PubMed

    Corsetti, James P; Salzman, Peter; Ryan, Dan; Moss, Arthur J; Zareba, Wojciech; Sparks, Charles E

    2016-09-01

    Data is presented that was utilized as the basis for Bayesian network modeling of influence pathways focusing on the central role of a polymorphism of plasminogen activator inhibitor-2 (PAI-2) on recurrent cardiovascular disease risk in patients with high levels of HDL cholesterol and C-reactive protein (CRP) as a marker of inflammation, "Influences on Plasminogen Activator Inhibitor-2 Polymorphism-Associated Recurrent Cardiovascular Disease Risk in Patients with High HDL Cholesterol and Inflammation" (Corsetti et al., 2016; [1]). The data consist of occurrence of recurrent coronary events in 166 post myocardial infarction patients along with 1. clinical data on gender, race, age, and body mass index; 2. blood level data on 17 biomarkers; and 3. genotype data on 53 presumptive CVD-related single nucleotide polymorphisms. Additionally, a flow diagram of the Bayesian modeling procedure is presented along with Bayesian network subgraphs (root nodes to outcome events) utilized as the data from which PAI-2 associated influence pathways were derived (Corsetti et al., 2016; [1]). PMID:27284570

  1. Bridging: Locating Critical Connectors in a Network

    PubMed Central

    Valente, Thomas W.; Fujimoto, Kayo

    2010-01-01

    This paper proposes several measures for bridging in networks derived from Granovetter's (1973) insight that links which reduce distances in a network are important structural bridges. Bridging is calculated by systematically deleting links and calculating the resultant changes in network cohesion (measured as the inverse average path length). The average change for each node's links provides an individual level measure of bridging. We also present a normalized version which controls for network size and a network level bridging index. Bridging properties are demonstrated on hypothetical networks, empirical networks, and a set of 100 randomly generated networks to show how the bridging measure correlates with existing network measures such as degree, personal network density, constraint, closeness centrality, betweenness centrality, and vitality. Bridging and the accompanying methodology provide a family of new network measures useful for studying network structure, network dynamics, and network effects on substantive behavioral phenomenon. PMID:20582157

  2. Statistical mechanics of maximal independent sets

    NASA Astrophysics Data System (ADS)

    Dall'Asta, Luca; Pin, Paolo; Ramezanpour, Abolfazl

    2009-12-01

    The graph theoretic concept of maximal independent set arises in several practical problems in computer science as well as in game theory. A maximal independent set is defined by the set of occupied nodes that satisfy some packing and covering constraints. It is known that finding minimum and maximum-density maximal independent sets are hard optimization problems. In this paper, we use cavity method of statistical physics and Monte Carlo simulations to study the corresponding constraint satisfaction problem on random graphs. We obtain the entropy of maximal independent sets within the replica symmetric and one-step replica symmetry breaking frameworks, shedding light on the metric structure of the landscape of solutions and suggesting a class of possible algorithms. This is of particular relevance for the application to the study of strategic interactions in social and economic networks, where maximal independent sets correspond to pure Nash equilibria of a graphical game of public goods allocation.

  3. Multidimensional set switching.

    PubMed

    Hahn, Sowon; Andersen, George J; Kramer, Arthur F

    2003-06-01

    The present study examined the organization of preparatory processes that underlie set switching and, more specifically, switch costs. On each trial, subjects performed one of two perceptual judgment tasks, color or shape discrimination. Subjects also responded with one of two different response sets. The task set and/or the response set switched from one to the other after 2-6 repeated trials. Response set, task set, and double set switches were performed in both blocked and randomized conditions. Subjects performed with short (100-msec) and long (800-msec) preparatory intervals. Task and response set switches had an additive effect on reaction times (RTs) in the blocked condition. Such a pattern of results suggests a serial organization of preparatory processes when the nature of switches is predictable. However, task and response set switches had an underadditive effect on RTs in the random condition when subjects performed with a brief cue-to-target interval. This pattern of results suggests overlapping task and response set preparation. These findings are discussed in terms of strategic control of preparatory processes in set switching. PMID:12921431

  4. National Highway Planning Network

    Energy Science and Technology Software Center (ESTSC)

    1992-02-02

    NHPN, the National Highway Planning Network, is a database of major highways in the continental United States that is used for national-level analyses of highway transportation issues that require use of a network, such as studies of highway performance, network design, social and environmental impacts of transportation, vehicle routing and scheduling, and mapping. The network is based on a set of roadways digitized by the U. S. Geological Survey (USGS) from the 1980 National Atlasmore » and has been enhanced with additional roads, attribute detail, and topological error corrections to produce a true analytic network. All data have been derived from or checked against information obtained from state and Federal governmental agencies. Two files comprise this network: one describing links and the other nodes. This release, NHPN1.0, contains 44,960 links and 28,512 nodes representing approximately 380,000 miles of roadway.« less

  5. Technology Integration in a Seminary Setting.

    ERIC Educational Resources Information Center

    Lee, HeeKap; Baek, Eun-Ok; Spinner, Denny

    2002-01-01

    Discussion of technology integration in higher education focuses on an information technology project in a seminary setting that created a campus computer network, trained faculty and library staff in computer technology use and provided appropriate hardware and software, and created an endowment to support technology maintenance and updating.…

  6. Acronical Risings and Settings

    NASA Astrophysics Data System (ADS)

    Hockey, Thomas A.

    2012-01-01

    A concept found in historical primary sources, and useful in contemporary historiography, is the acronical rising and setting of stars (or planets). Topocentric terms, they provide information about a star's relationship to the Sun and thus its visibility in the sky. Yet there remains ambiguity as to what these two phrases actually mean. "Acronical” is said to have come from the Greek akros ("point,” "summit,” or "extremity") and nux ("night"). While all sources agree that the word is originally Greek, there are alternate etymologies for it. A more serious difficulty with acronical rising and setting is that there are two competing definitions. One I call the Poetical Definition. Acronical rising (or setting) is one of the three Poetical Risings (or Settings) known to classicists. (The other two are cosmical rising/setting, discussed below, and the more familiar helical rising/setting.) The term "poetical" refers to these words use in classical poetry, e. g., that of Columella, Hesiod, Ovid, Pliny the Younger, and Virgil. The Poetical Definition of "acronical” usually is meant in this context. The Poetical Definition of "acronical” is as follows: When a star rises as the Sun sets, it rises acronically. When a star sets as the Sun sets, it sets acronically. In contrast with the Poetical Definition, there also is what I call the Astronomical Definition. The Astronomical Definition is somewhat more likely to appear in astronomical, mathematical, or navigational works. When the Astronomical Definition is recorded in dictionaries, it is often with the protasis "In astronomy, . . . ." The Astronomical Definition of "acronical” is as follows: When a star rises as the Sun sets, it rises acronically. When a star sets as the Sun rises, it sets acronically. I will attempt to sort this all out in my talk.

  7. Improved Autoassociative Neural Networks

    NASA Technical Reports Server (NTRS)

    Hand, Charles

    2003-01-01

    Improved autoassociative neural networks, denoted nexi, have been proposed for use in controlling autonomous robots, including mobile exploratory robots of the biomorphic type. In comparison with conventional autoassociative neural networks, nexi would be more complex but more capable in that they could be trained to do more complex tasks. A nexus would use bit weights and simple arithmetic in a manner that would enable training and operation without a central processing unit, programs, weight registers, or large amounts of memory. Only a relatively small amount of memory (to hold the bit weights) and a simple logic application- specific integrated circuit would be needed. A description of autoassociative neural networks is prerequisite to a meaningful description of a nexus. An autoassociative network is a set of neurons that are completely connected in the sense that each neuron receives input from, and sends output to, all the other neurons. (In some instantiations, a neuron could also send output back to its own input terminal.) The state of a neuron is completely determined by the inner product of its inputs with weights associated with its input channel. Setting the weights sets the behavior of the network. The neurons of an autoassociative network are usually regarded as comprising a row or vector. Time is a quantized phenomenon for most autoassociative networks in the sense that time proceeds in discrete steps. At each time step, the row of neurons forms a pattern: some neurons are firing, some are not. Hence, the current state of an autoassociative network can be described with a single binary vector. As time goes by, the network changes the vector. Autoassociative networks move vectors over hyperspace landscapes of possibilities.

  8. From network structure to network reorganization: implications for adult neurogenesis

    NASA Astrophysics Data System (ADS)

    Schneider-Mizell, Casey M.; Parent, Jack M.; Ben-Jacob, Eshel; Zochowski, Michal R.; Sander, Leonard M.

    2010-12-01

    Networks can be dynamical systems that undergo functional and structural reorganization. One example of such a process is adult hippocampal neurogenesis, in which new cells are continuously born and incorporate into the existing network of the dentate gyrus region of the hippocampus. Many of these introduced cells mature and become indistinguishable from established neurons, joining the existing network. Activity in the network environment is known to promote birth, survival and incorporation of new cells. However, after epileptogenic injury, changes to the connectivity structure around the neurogenic niche are known to correlate with aberrant neurogenesis. The possible role of network-level changes in the development of epilepsy is not well understood. In this paper, we use a computational model to investigate how the structural and functional outcomes of network reorganization, driven by addition of new cells during neurogenesis, depend on the original network structure. We find that there is a stable network topology that allows the network to incorporate new neurons in a manner that enhances activity of the persistently active region, but maintains global network properties. In networks having other connectivity structures, new cells can greatly alter the distribution of firing activity and destroy the initial activity patterns. We thus find that new cells are able to provide focused enhancement of network only for small-world networks with sufficient inhibition. Network-level deviations from this topology, such as those caused by epileptogenic injury, can set the network down a path that develops toward pathological dynamics and aberrant structural integration of new cells.

  9. Norovirus in Healthcare Settings

    MedlinePlus

    ... Guideline for Isolation Precautions: Preventing Transmission of Infectious Agents in Healthcare Settings Occupational Safety and Health Administration (OSHA) Fact Sheet on Noroviruses [PDF - 61 ...

  10. PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: principal component analysis and absolute principal component scores on a two years and half data set

    PubMed Central

    2014-01-01

    Background The chemical composition of aerosols and particle size distributions are the most significant factors affecting air quality. In particular, the exposure to finer particles can cause short and long-term effects on human health. In the present paper PM10 (particulate matter with aerodynamic diameter lower than 10 μm), CO, NOx (NO and NO2), Benzene and Toluene trends monitored in six monitoring stations of Bari province are shown. The data set used was composed by bi-hourly means for all parameters (12 bi-hourly means per day for each parameter) and it’s referred to the period of time from January 2005 and May 2007. The main aim of the paper is to provide a clear illustration of how large data sets from monitoring stations can give information about the number and nature of the pollutant sources, and mainly to assess the contribution of the traffic source to PM10 concentration level by using multivariate statistical techniques such as Principal Component Analysis (PCA) and Absolute Principal Component Scores (APCS). Results Comparing the night and day mean concentrations (per day) for each parameter it has been pointed out that there is a different night and day behavior for some parameters such as CO, Benzene and Toluene than PM10. This suggests that CO, Benzene and Toluene concentrations are mainly connected with transport systems, whereas PM10 is mostly influenced by different factors. The statistical techniques identified three recurrent sources, associated with vehicular traffic and particulate transport, covering over 90% of variance. The contemporaneous analysis of gas and PM10 has allowed underlining the differences between the sources of these pollutants. Conclusions The analysis of the pollutant trends from large data set and the application of multivariate statistical techniques such as PCA and APCS can give useful information about air quality and pollutant’s sources. These knowledge can provide useful advices to environmental policies in

  11. Effective Goal-Setting.

    ERIC Educational Resources Information Center

    West, Michael

    1993-01-01

    Setting organizational or program objectives is seen as requiring three steps (brainstorming goals for the year, prioritizing them, and visualizing them as smaller, discrete tasks) and six principles (making goals group-specific, setting deadlines, being realistic and explicit, writing down goals, defining measurable steps, and creating…

  12. Ready, Set, Integrate!

    ERIC Educational Resources Information Center

    McCombs, John

    2003-01-01

    Describes how the American Embassy School (AES) in New Delhi, India achieved school-wide technology integration. Discusses development of a new network; beginning to mentor; organizing the Technology Integration Plan (TIP) by software application; implementing the plan; assessing progress; and results, which overall, were positive. (AEF)

  13. Enabling network-aware applications

    SciTech Connect

    Tierney, Brian L.; Gunter, Dan; Lee, Jason; Stouffer, Martin

    2001-08-01

    Many high performance distributed applications use only a small fraction of their available bandwidth. A common cause of this problem is not a flaw in the application design, but rather improperly tuned network settings. Proper tuning techniques, such as setting the correct TCP buffers and using parallel streams, are well known in the networking community, but outside the networking community they are infrequently applied. In this paper, we describe a service that makes the task of network tuning trivial for application developers and users. Widespread use of this service should virtually eliminate a common stumbling block for high performance distributed applications.

  14. A security architecture for health information networks.

    PubMed

    Kailar, Rajashekar; Muralidhar, Vinod

    2007-01-01

    Health information network security needs to balance exacting security controls with practicality, and ease of implementation in today's healthcare enterprise. Recent work on 'nationwide health information network' architectures has sought to share highly confidential data over insecure networks such as the Internet. Using basic patterns of health network data flow and trust models to support secure communication between network nodes, we abstract network security requirements to a core set to enable secure inter-network data sharing. We propose a minimum set of security controls that can be implemented without needing major new technologies, but yet realize network security and privacy goals of confidentiality, integrity and availability. This framework combines a set of technology mechanisms with environmental controls, and is shown to be sufficient to counter commonly encountered network security threats adequately. PMID:18693862

  15. The development of the International Network for Frontier Research on Earthquake Precursors (INFREP) by designing new analysing software and by setting up new recording locations of radio VLF/LF signals in Romania

    NASA Astrophysics Data System (ADS)

    Moldovan, Iren-Adelina; Petruta Constantin, Angela; Emilian Toader, Victorin; Toma-Danila, Dragos; Biagi, Pier Francesco; Maggipinto, Tommaso; Dolea, Paul; Septimiu Moldovan, Adrian

    2014-05-01

    Based on scientific evidences supporting the causality between earthquake preparatory stages, space weather and solar activity and different types of electromagnetic (EM) disturbances together with the benefit of having full access at ground and space based EM data, INFREP proposes a complex and cross correlated investigation of phenomena that occur in the coupled system Lithosphere-Atmosphere-Ionsophere in order to identify possible causes responsible for anomalous effects observed in the propagation characteristics of radio waves, especially at low (LF) and very low frequency (VLF). INFREP, a network of VLF (20-60 kHz) and LF (150-300 kHz) radio receivers, was put into operation in Europe in 2009, having as principal goal, the study of disturbances produced by the earthquakes on the propagation properties of these signals. The Romanian NIEP VLF / LF monitoring system consisting in a radio receiver -made by Elettronika S.R.L. (Italy) and provided by the Bari University- and the infrastructure that is necessary to record and transmit the collected data, is a part of the international initiative INFREP. The NIEP VLF / LF receiver installed in Romania was put into operation in February 2009 in Bucharest and relocated to the Black-Sea shore (Dobruja Seismologic Observatory) in December 2009. The first development of the Romanian EM monitoring system was needed because after changing the receiving site from Bucharest to Eforie we obtained unsatisfactory monitoring data, characterized by large fluctuations of the received signals' intensities. Trying to understand this behavior has led to the conclusion that the electric component of the electromagnetic field was possibly influenced by the local conditions. Starting from this observation we have run some tests and changed the vertical antenna with a loop-type antenna that is more appropriate in highly electric-field polluted environments. Since the amount of recorded data is huge, for streamlining the research process

  16. Self Evolving Modular Network

    NASA Astrophysics Data System (ADS)

    Tokunaga, Kazuhiro; Kawabata, Nobuyuki; Furukawa, Tetsuo

    We propose a novel modular network called the Self-Evolving Modular Network (SEEM). The SEEM has a modular network architecture with a graph structure and these following advantages: (1) new modules are added incrementally to allow the network to adapt in a self-organizing manner, and (2) graph's paths are formed based on the relationships between the models represented by modules. The SEEM is expected to be applicable to evolving functions of an autonomous robot in a self-organizing manner through interaction with the robot's environment and categorizing large-scale information. This paper presents the architecture and an algorithm for the SEEM. Moreover, performance characteristic and effectiveness of the network are shown by simulations using cubic functions and a set of 3D-objects.

  17. Network planning under uncertainties

    NASA Astrophysics Data System (ADS)

    Ho, Kwok Shing; Cheung, Kwok Wai

    2008-11-01

    generic framework for solving the network planning problem under uncertainties. In addition to reviewing the various network planning problems involving uncertainties, we also propose that a unified framework based on robust optimization can be used to solve a rather large segment of network planning problem under uncertainties. Robust optimization is first introduced in the operations research literature and is a framework that incorporates information about the uncertainty sets for the parameters in the optimization model. Even though robust optimization is originated from tackling the uncertainty in the optimization process, it can serve as a comprehensive and suitable framework for tackling generic network planning problems under uncertainties. In this paper, we begin by explaining the main ideas behind the robust optimization approach. Then we demonstrate the capabilities of the proposed framework by giving out some examples of how the robust optimization framework can be applied to the current common network planning problems under uncertain environments. Next, we list some practical considerations for solving the network planning problem under uncertainties with the proposed framework. Finally, we conclude this article with some thoughts on the future directions for applying this framework to solve other network planning problems.

  18. Network Consistent Data Association.

    PubMed

    Chakraborty, Anirban; Das, Abir; Roy-Chowdhury, Amit K

    2016-09-01

    Existing data association techniques mostly focus on matching pairs of data-point sets and then repeating this process along space-time to achieve long term correspondences. However, in many problems such as person re-identification, a set of data-points may be observed at multiple spatio-temporal locations and/or by multiple agents in a network and simply combining the local pairwise association results between sets of data-points often leads to inconsistencies over the global space-time horizons. In this paper, we propose a Novel Network Consistent Data Association (NCDA) framework formulated as an optimization problem that not only maintains consistency in association results across the network, but also improves the pairwise data association accuracies. The proposed NCDA can be solved as a binary integer program leading to a globally optimal solution and is capable of handling the challenging data-association scenario where the number of data-points varies across different sets of instances in the network. We also present an online implementation of NCDA method that can dynamically associate new observations to already observed data-points in an iterative fashion, while maintaining network consistency. We have tested both the batch and the online NCDA in two application areas-person re-identification and spatio-temporal cell tracking and observed consistent and highly accurate data association results in all the cases. PMID:26485472

  19. Settings for Suicide Prevention

    MedlinePlus

    ... Sexual Minority" Youth Finds Them at Risk of Violence September 02, 2016 The Weekly Spark Stay Connected! Subscribe Settings Schools, workplaces, hospitals, nursing homes—every place where people ...

  20. Artist Place Settings

    ERIC Educational Resources Information Center

    Pellegrino, Linda

    2009-01-01

    Art history can be a little dry at times, but the author is always trying to incorporate new ways of teaching it. In this article, she describes a project in which students were to create a place setting out of clay that had to be unified through a famous artist's style. This place setting had to consist of at least five pieces (dinner plate, cup…

  1. Set theory and physics

    SciTech Connect

    Svozil, K.

    1995-11-01

    Inasmuch as physical theories are formalizable, set theory provides a framework for theoretical physics. Four speculations about the relevance of set theoretical modeling for physics are presented: the role of transcendental set theory (i) in chaos theory, (ii) for paradoxical decompositions of solid three-dimensional objects, (iii) in the theory of effective computability (Church-Turing thesis) related to the possible {open_quotes}solution of supertasks,{close_quotes} and (iv) for weak solutions. Several approaches to set theory and their advantages and disadvantages for physical applications are discussed: Cantorian {open_quotes}naive{close_quotes} (i.e., nonaxiomatic) set theory, contructivism, and operationalism. In the author`s opinion, an attitude, of {open_quotes}suspended attention{close_quotes} (a term borrowed from psychoanalysis) seems most promising for progress. Physical and set theoretical entities must be operationalized wherever possible. At the same time, physicists should be open to {open_quotes}bizarre{close_quotes} or {open_quotes}mindboggling{close_quotes} new formalisms, which need not be operationalizable or testable at the time of their creation, but which may successfully lead to novel fields of phenomenology and technology.

  2. Set theory and physics

    NASA Astrophysics Data System (ADS)

    Svozil, K.

    1995-11-01

    Inasmuch as physical theories are formalizable, set theory provides a framework for theoretical physics. Four speculations about the relevance of set theoretical modeling for physics are presented: the role of transcendental set theory (i) in chaos theory, (ii) for paradoxical decompositions of solid three-dimensional objects, (iii) in the theory of effective computability (Church-Turing thesis) related to the possible “solution of supertasks,” and (iv) for weak solutions. Several approaches to set theory and their advantages and disadvatages for physical applications are discussed: Canlorian “naive” (i.e., nonaxiomatic) set theory, contructivism, and operationalism. In the author's opinion, an attitude of “suspended attention” (a term borrowed from psychoanalysis) seems most promising for progress. Physical and set theoretical entities must be operationalized wherever possible. At the same time, physicists should be open to “bizarre” or “mindboggling” new formalisms, which need not be operationalizable or testable at the lime of their creation, but which may successfully lead to novel fields of phenomenology and technology.

  3. Network Cosmology

    PubMed Central

    Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

    2012-01-01

    Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

  4. Wide Range SET Pulse Measurement

    NASA Technical Reports Server (NTRS)

    Shuler, Robert L.; Chen, Li

    2012-01-01

    small number of SETs were not significantly higher in the test over the control circuits. At higher LET the test circuit SETs are one or two orders of magnitude greater than for the control circuit. The NFET circuit produces more and slightly longer SETs as expected. But the differences do not appear to be significant enough to modify strategies now used to avoid capture of SETs in chips such as FPGAs. Complete data and graphs will be in the full paper / presentation. In the summary figure below left, NOCL is the reference circuit without any input, and number of stages triggered is plotted. Simulation at right shows the smallest pulse captured (stage 2) at about 300 ps. Our conclusion is that the method is promising, but that improvements in the merge network are desirable before applying in a deep submicron process

  5. Aggregating Hydrometeorological Data from International Monitoring Networks Across Earth's Largest Lake System to Quantify Uncertainty in Historical Water Budget Records, Improve Regional Water Budget Projections, and Differentiate Drivers Behind a Recent Record-Setting Surge in Water Levels

    NASA Astrophysics Data System (ADS)

    Gronewold, A.; Bruxer, J.; Smith, J.; Hunter, T.; Fortin, V.; Clites, A. H.; Durnford, D.; Qian, S.; Seglenieks, F.

    2015-12-01

    Resolving and projecting the water budget of the North American Great Lakes basin (Earth's largest lake system) requires aggregation of data from a complex array of in situ monitoring and remote sensing products that cross an international border (leading to potential sources of bias and other inconsistencies), and are relatively sparse over the surfaces of the lakes themselves. Data scarcity over the surfaces of the lakes is a particularly significant problem because, unlike Earth's other large freshwater basins, the Great Lakes basin water budget is (on annual scales) comprised of relatively equal contributions from runoff, over-lake precipitation, and over-lake evaporation. Consequently, understanding drivers behind changes in regional water storage and water levels requires a data management framework that can reconcile uncertainties associated with data scarcity and bias, and propagate those uncertainties into regional water budget projections and historical records. Here, we assess the development of a historical hydrometeorological database for the entire Great Lakes basin with records dating back to the late 1800s, and describe improvements that are specifically intended to differentiate hydrological, climatological, and anthropogenic drivers behind recent extreme changes in Great Lakes water levels. Our assessment includes a detailed analysis of the extent to which extreme cold winters in central North America in 2013-2014 (caused by the anomalous meridional upper air flow - commonly referred to in the public media as the "polar vortex" phenomenon) altered the thermal and hydrologic regimes of the Great Lakes and led to a record setting surge in water levels between January 2014 and December 2015.

  6. Weighted network analysis of earthquake seismic data

    NASA Astrophysics Data System (ADS)

    Chakraborty, Abhijit; Mukherjee, G.; Manna, S. S.

    2015-09-01

    Three different earthquake seismic data sets are used to construct the earthquake networks following the prescriptions of Abe and Suzuki (2004). It has been observed that different links of this network appear with highly different strengths. This prompted us to extend the study of earthquake networks by considering it as the weighted network. Different properties of such weighted network have been found to be quite different from those of their un-weighted counterparts.

  7. Set Equation Transformation System.

    Energy Science and Technology Software Center (ESTSC)

    2002-03-22

    Version 00 SETS is used for symbolic manipulation of Boolean equations, particularly the reduction of equations by the application of Boolean identities. It is a flexible and efficient tool for performing probabilistic risk analysis (PRA), vital area analysis, and common cause analysis. The equation manipulation capabilities of SETS can also be used to analyze noncoherent fault trees and determine prime implicants of Boolean functions, to verify circuit design implementation, to determine minimum cost fire protectionmore » requirements for nuclear reactor plants, to obtain solutions to combinatorial optimization problems with Boolean constraints, and to determine the susceptibility of a facility to unauthorized access through nullification of sensors in its protection system. Two auxiliary programs, SEP and FTD, are included. SEP performs the quantitative analysis of reduced Boolean equations (minimal cut sets) produced by SETS. The user can manipulate and evaluate the equations to find the probability of occurrence of any desired event and to produce an importance ranking of the terms and events in an equation. FTD is a fault tree drawing program which uses the proprietary ISSCO DISSPLA graphics software to produce an annotated drawing of a fault tree processed by SETS. The DISSPLA routines are not included.« less

  8. Quantum mechanics over sets

    NASA Astrophysics Data System (ADS)

    Ellerman, David

    2014-03-01

    In models of QM over finite fields (e.g., Schumacher's ``modal quantum theory'' MQT), one finite field stands out, Z2, since Z2 vectors represent sets. QM (finite-dimensional) mathematics can be transported to sets resulting in quantum mechanics over sets or QM/sets. This gives a full probability calculus (unlike MQT with only zero-one modalities) that leads to a fulsome theory of QM/sets including ``logical'' models of the double-slit experiment, Bell's Theorem, QIT, and QC. In QC over Z2 (where gates are non-singular matrices as in MQT), a simple quantum algorithm (one gate plus one function evaluation) solves the Parity SAT problem (finding the parity of the sum of all values of an n-ary Boolean function). Classically, the Parity SAT problem requires 2n function evaluations in contrast to the one function evaluation required in the quantum algorithm. This is quantum speedup but with all the calculations over Z2 just like classical computing. This shows definitively that the source of quantum speedup is not in the greater power of computing over the complex numbers, and confirms the idea that the source is in superposition.

  9. OPTIMAL NETWORK TOPOLOGY DESIGN

    NASA Technical Reports Server (NTRS)

    Yuen, J. H.

    1994-01-01

    This program was developed as part of a research study on the topology design and performance analysis for the Space Station Information System (SSIS) network. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. It is intended that this new design technique consider all important performance measures explicitly and take into account the constraints due to various technical feasibilities. In the current program, technical constraints are taken care of by the user properly forming the starting set of candidate components (e.g. nonfeasible links are not included). As subsets are generated, they are tested to see if they form an acceptable network by checking that all requirements are satisfied. Thus the first acceptable subset encountered gives the cost-optimal topology satisfying all given constraints. The user must sort the set of "feasible" link elements in increasing order of their costs. The program prompts the user for the following information for each link: 1) cost, 2) connectivity (number of stations connected by the link), and 3) the stations connected by that link. Unless instructed to stop, the program generates all possible acceptable networks in increasing order of their total costs. The program is written only to generate topologies that are simply connected. Tests on reliability, delay, and other performance measures are discussed in the documentation, but have not been incorporated into the program. This program is written in PASCAL for interactive execution and has been implemented on an IBM PC series computer operating under PC DOS. The disk contains source code only. This program was developed in 1985.

  10. Network Solutions.

    ERIC Educational Resources Information Center

    Vietzke, Robert; And Others

    1996-01-01

    This special section explains the latest developments in networking technologies, profiles school districts benefiting from successful implementations, and reviews new products for building networks. Highlights include ATM (asynchronous transfer mode), cable modems, networking switches, Internet screening software, file servers, network management…

  11. FTA Basic Event & Cut Set Ranking.

    Energy Science and Technology Software Center (ESTSC)

    1999-05-04

    Version 00 IMPORTANCE computes various measures of probabilistic importance of basic events and minimal cut sets to a fault tree or reliability network diagram. The minimal cut sets, the failure rates and the fault duration times (i.e., the repair times) of all basic events contained in the minimal cut sets are supplied as input data. The failure and repair distributions are assumed to be exponential. IMPORTANCE, a quantitative evaluation code, then determines the probability ofmore » the top event and computes the importance of minimal cut sets and basic events by a numerical ranking. Two measures are computed. The first describes system behavior at one point in time; the second describes sequences of failures that cause the system to fail in time. All measures are computed assuming statistical independence of basic events. In addition, system unavailability and expected number of system failures are computed by the code.« less

  12. Instruction set commutivity

    NASA Technical Reports Server (NTRS)

    Windley, P.

    1992-01-01

    We present a state property called congruence and show how it can be used to demonstrate commutivity of instructions in a modern load-store architecture. Our analysis is particularly important in pipelined microprocessors where instructions are frequently reordered to avoid costly delays in execution caused by hazards. Our work has significant implications to safety and security critical applications since reordering can easily change the meaning and an instruction sequence and current techniques are largely ad hoc. Our work is done in a mechanical theorem prover and results in a set of trustworthy rules for instruction reordering. The mechanization makes it practical to analyze the entire instruction set.

  13. Complex intuitionistic fuzzy sets

    NASA Astrophysics Data System (ADS)

    Alkouri, Abdulazeez (Moh'd. Jumah) S.; Salleh, Abdul Razak

    2012-09-01

    This paper presents a new concept of complex intuitionistic fuzzy set (CIFS) which is generalized from the innovative concept of a complex fuzzy set (CFS) by adding the non-membership term to the definition of CFS. The novelty of CIFS lies in its ability for membership and non-membership functions to achieve more range of values. The ranges of values are extended to the unit circle in complex plane for both membership and non-membership functions instead of [0, 1] as in the conventional intuitionistic fuzzy functions. We define basic operations namely complement, union, and intersection on CIFSs. Properties of these operations are derived.

  14. Networking standards

    NASA Technical Reports Server (NTRS)

    Davies, Mark

    1991-01-01

    The enterprise network is currently a multivendor environment consisting of many defacto and proprietary standards. During the 1990s, these networks will evolve towards networks which are based on international standards in both Local Area Network (LAN) and Wide Area Network (WAN) space. Also, you can expect to see the higher level functions and applications begin the same transition. Additional information is given in viewgraph form.

  15. Semantic Networks and Social Networks

    ERIC Educational Resources Information Center

    Downes, Stephen

    2005-01-01

    Purpose: To illustrate the need for social network metadata within semantic metadata. Design/methodology/approach: Surveys properties of social networks and the semantic web, suggests that social network analysis applies to semantic content, argues that semantic content is more searchable if social network metadata is merged with semantic web…

  16. Coaching in Community Settings.

    ERIC Educational Resources Information Center

    Nettles, Saundra Murray

    1993-01-01

    Develops a framework for promoting effective coaching, in the sense of encouraging children's achievement, in community settings for children of different ages. Effective coaches perform the following tasks: (1) teach; (2) assess performance; (3) structure the learning environment; and (4) provide social support. (SLD)

  17. The Crystal Set

    ERIC Educational Resources Information Center

    Greenslade, Thomas B., Jr.

    2014-01-01

    In past issues of this journal, the late H. R. Crane wrote a long series of articles under the running title of "How Things Work." In them, Dick dealt with many questions that physics teachers asked themselves, but did not have the time to answer. This article is my attempt to work through the physics of the crystal set, which I thought…

  18. Therapists in Oncology Settings

    ERIC Educational Resources Information Center

    Hendrick, Susan S.

    2013-01-01

    This article describes the author's experiences of working with cancer patients/survivors both individually and in support groups for many years, across several settings. It also documents current best-practice guidelines for the psychosocial treatment of cancer patients/survivors and their families. The author's view of the important qualities…

  19. Best of SET Mathematics.

    ERIC Educational Resources Information Center

    Livingstone, Ian, Ed.; Izard, John, Ed.

    1993-01-01

    Set: Research Information for Teachers, is published twice a year by the New Zealand Council for Educational Research and the Australian Council for Educational Research. This document draws together 16 articles on mathematics from previous issues grouped into three categories: general, primary, and secondary. The titles are: (1) "Contents and…

  20. Goal Setting and Hope

    ERIC Educational Resources Information Center

    Curran, Katie; Reivich, Karen

    2011-01-01

    The science behind the mechanisms and mediators that lead to successful goal accomplishment has been a focus of research since the 1970s. When an individual desires to make a change or accomplish an outcome, research shows that he or she will be more successful if he or she attends to a number of variables that are key in goal setting.…

  1. TRACKING ACCELERATOR SETTINGS.

    SciTech Connect

    D OTTAVIO,T.; FU, W.; OTTAVIO, D.P.

    2007-10-15

    Recording setting changes within an accelerator facility provides information that can be used to answer questions about when, why, and how changes were made to some accelerator system. This can be very useful during normal operations, but can also aid with security concerns and in detecting unusual software behavior. The Set History System (SHS) is a new client-server system developed at the Collider-Accelerator Department of Brookhaven National Laboratory to provide these capabilities. The SHS has been operational for over two years and currently stores about IOOK settings per day into a commercial database management system. The SHS system consists of a server written in Java, client tools written in both Java and C++, and a web interface for querying the database of setting changes. The design of the SHS focuses on performance, portability, and a minimal impact on database resources. In this paper, we present an overview of the system design along with benchmark results showing the performance and reliability of the SHS over the last year.

  2. Setting Environmental Standards

    ERIC Educational Resources Information Center

    Fishbein, Gershon

    1975-01-01

    Recent court decisions have pointed out the complexities involved in setting environmental standards. Environmental health is composed of multiple causative agents, most of which work over long periods of time. This makes the cause-and-effect relationship between health statistics and environmental contaminant exposures difficult to prove in…

  3. Setting and Achieving Objectives.

    ERIC Educational Resources Information Center

    Knoop, Robert

    1986-01-01

    Provides basic guidelines which school officials and school boards may find helpful in negotiating, establishing, and managing objectives. Discusses characteristics of good objectives, specific and directional objectives, multiple objectives, participation in setting objectives, feedback on goal process and achievement, and managing a school…

  4. Probabilistic Open Set Recognition

    NASA Astrophysics Data System (ADS)

    Jain, Lalit Prithviraj

    Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

  5. Introduction to Network Analysis in Systems Biology

    PubMed Central

    Ma’ayan, Avi

    2011-01-01

    This Teaching Resource provides lecture notes, slides, and a problem set for a set of three lectures from a course entitled “Systems Biology: Biomedical Modeling.” The materials are from three separate lectures introducing applications of graph theory and network analysis in systems biology. The first lecture describes different types of intracellular networks, methods for constructing biological networks, and different types of graphs used to represent regulatory intracellular networks. The second lecture surveys milestones and key concepts in network analysis by introducing topological measures, random networks, growing network models, and topological observations from molecular biological systems abstracted to networks. The third lecture discusses methods for analyzing lists of genes and experimental data in the context of prior knowledge networks to make predictions. PMID:21917719

  6. Topological entropy of catalytic sets: Hypercycles revisited

    NASA Astrophysics Data System (ADS)

    Sardanyés, Josep; Duarte, Jorge; Januário, Cristina; Martins, Nuno

    2012-02-01

    The dynamics of catalytic networks have been widely studied over the last decades because of their implications in several fields like prebiotic evolution, virology, neural networks, immunology or ecology. One of the most studied mathematical bodies for catalytic networks was initially formulated in the context of prebiotic evolution, by means of the hypercycle theory. The hypercycle is a set of self-replicating species able to catalyze other replicator species within a cyclic architecture. Hypercyclic organization might arise from a quasispecies as a way to increase the informational containt surpassing the so-called error threshold. The catalytic coupling between replicators makes all the species to behave like a single and coherent evolutionary multimolecular unit. The inherent nonlinearities of catalytic interactions are responsible for the emergence of several types of dynamics, among them, chaos. In this article we begin with a brief review of the hypercycle theory focusing on its evolutionary implications as well as on different dynamics associated to different types of small catalytic networks. Then we study the properties of chaotic hypercycles with error-prone replication with symbolic dynamics theory, characterizing, by means of the theory of topological Markov chains, the topological entropy and the periods of the orbits of unimodal-like iterated maps obtained from the strange attractor. We will focus our study on some key parameters responsible for the structure of the catalytic network: mutation rates, autocatalytic and cross-catalytic interactions.

  7. Communicability across evolving networks

    NASA Astrophysics Data System (ADS)

    Grindrod, Peter; Parsons, Mark C.; Higham, Desmond J.; Estrada, Ernesto

    2011-04-01

    Many natural and technological applications generate time-ordered sequences of networks, defined over a fixed set of nodes; for example, time-stamped information about “who phoned who” or “who came into contact with who” arise naturally in studies of communication and the spread of disease. Concepts and algorithms for static networks do not immediately carry through to this dynamic setting. For example, suppose A and B interact in the morning, and then B and C interact in the afternoon. Information, or disease, may then pass from A to C, but not vice versa. This subtlety is lost if we simply summarize using the daily aggregate network given by the chain A-B-C. However, using a natural definition of a walk on an evolving network, we show that classic centrality measures from the static setting can be extended in a computationally convenient manner. In particular, communicability indices can be computed to summarize the ability of each node to broadcast and receive information. The computations involve basic operations in linear algebra, and the asymmetry caused by time’s arrow is captured naturally through the noncommutativity of matrix-matrix multiplication. Illustrative examples are given for both synthetic and real-world communication data sets. We also discuss the use of the new centrality measures for real-time monitoring and prediction.

  8. SCFβ-TRCP promotes cell growth by targeting PR-Set7/Set8 for degradation

    PubMed Central

    Wang, Zhiwei; Dai, Xiangpeng; Zhong, Jiateng; Inuzuka, Hiroyuki; Wan, Lixin; Li, Xiaoning; Wang, Lixia; Ye, Xiantao; Sun, Liankun; Gao, Daming; Zou, Lee; Wei, Wenyi

    2015-01-01

    The Set8/PR-Set7/KMT5a methyltransferase plays critical roles in governing transcriptional regulation, cell cycle progression and tumorigenesis. Although CRL4Cdt2 was reported to regulate Set8 stability, deleting the PIP motif only led to partial resistance to ultraviolet-induced degradation of Set8, indicating the existence of additional E3 ligase(s) controlling Set8 stability. Furthermore, it remains largely undefined how DNA damage-induced kinase cascades trigger the timely destruction of Set8 to govern tumorigenesis. Here, we report that SCFβ-TRCP earmarks Set8 for ubiquitination and degradation in a casein kinase I-dependent manner, which is activated by DNA-damaging agents. Biologically, both CRL4Cdt2 and SCFβ-TRCP-mediated pathways contribute to ultraviolet-induced Set8 degradation to control cell cycle progression, governing the onset of DNA damage-induced checkpoints. Therefore, like many critical cell cycle regulators including p21 and Cdt1, we uncover a tight regulatory network to accurately control Set8 abundance. Our studies further suggest that aberrancies in this delicate degradation pathway might contribute to aberrant elevation of Set8 in human tumours. PMID:26666832

  9. ESNET (Energy Sciences Network)

    SciTech Connect

    Not Available

    1987-06-01

    This document describes the Energy Sciences Network (ESNET) project which was undertaken by the Scientific Computing Staff during fiscal year (FY) 1986 at the direction of the Director, Office of Energy Research (ER). This document serves as the program plan for the ESNET project and is the result of the effort of the cross program Energy Sciences Network Steering Committee. The ESNET Steering Committee has been charged to codify the overall ER computer network requirements, to document and set priorities for computer networking requirements including performance objectives. Further, this committee has been asked to identify future ESNET functional characteristics, to identify research and development needs for the ESNET, to establish ESNET performance objectives and to define the intrastructure necessary to manage and operate the ESNET facilities.

  10. The Dynamics of Network Topology

    NASA Astrophysics Data System (ADS)

    Voicu, Ramiro; Legrand, Iosif; Newman, Harvey; Barczyk, Artur; Grigoras, Costin; Dobre, Ciprian

    2011-12-01

    Network monitoring is vital to ensure proper network operation over time, and is tightly integrated with all the data intensive processing tasks used by the LHC experiments. In order to build a coherent set of network management services it is very important to collect in near real-time information about the network topology, the main data flows, traffic volume and the quality of connectivity. A set of dedicated modules were developed in the MonALISA framework to periodically perform network measurements tests between all sites. We developed global services to present in near real-time the entire network topology used by a community. For any LHC experiment such a network topology includes several hundred of routers and tens of Autonomous Systems. Any changes in the global topology are recorded and this information is can be easily correlated with traffic patterns. The evolution in time of global network topology is shown a dedicated GUI. Changes in the global topology at this level occur quite frequently and even small modifications in the connectivity map may significantly affect the network performance. The global topology graphs are correlated with active end to end network performance measurements, done with the Fast Data Transfer application, between all sites. Access to both real-time and historical data, as provided by MonALISA, is also important for developing services able to predict the usage pattern, to aid in efficiently allocating resources globally.

  11. The Crystal Set

    NASA Astrophysics Data System (ADS)

    Greenslade, Thomas B.

    2014-04-01

    In past issues of this journal, the late H. R. Crane wrote a long series of articles under the running title of "How Things Work." In them, Dick dealt with many questions that physics teachers asked themselves, but did not have the time to answer. This article is my attempt to work through the physics of the crystal set, which I thought I knew, but actually did not.

  12. NASA Integrated Space Communications Network

    NASA Technical Reports Server (NTRS)

    Tai, Wallace; Wright, Nate; Prior, Mike; Bhasin, Kul

    2012-01-01

    The NASA Integrated Network for Space Communications and Navigation (SCaN) has been in the definition phase since 2010. It is intended to integrate NASA s three existing network elements, i.e., the Space Network, Near Earth Network, and Deep Space Network, into a single network. In addition to the technical merits, the primary purpose of the Integrated Network is to achieve a level of operating cost efficiency significantly higher than it is today. Salient features of the Integrated Network include (a) a central system element that performs service management functions and user mission interfaces for service requests; (b) a set of common service execution equipment deployed at the all stations that provides return, forward, and radiometric data processing and delivery capabilities; (c) the network monitor and control operations for the entire integrated network are conducted remotely and centrally at a prime-shift site and rotating among three sites globally (a follow-the-sun approach); (d) the common network monitor and control software deployed at all three network elements that supports the follow-the-sun operations.

  13. Distributed instruction set computer

    SciTech Connect

    Wang, L.

    1989-01-01

    The Distributed Instruction Set Computer, or DISC for short, is an experimental computer system for fine-grained parallel processing. DISC employs a new parallel instruction set, an Early Binding and Scheduling data tagging scheme, and a distributed control mechanism to explore a software dataflow control method in a multiple-functional unit system. With zero system control overhead, multiple instructions are executed in parallel and/or out of order at the highest speed of n instructions/cycle, where n is the number of functional units. The quantitative simulation result indicates that a DISC system with 16 functional units can deliverer a maximal 7.7X performance speedup over a single functional-unit system at the same clock speed. Exploring a new parallel instruction set and distributed control mechanism, DISC represents three major breakthroughs in the domain of fine-grained parallel processing: (1) Fast multiple instruction issuing mechanism; (2) Parallel and/or out-of-order execution; (3) Software dataflow control scheme.

  14. Airport Surface Network Architecture Definition

    NASA Technical Reports Server (NTRS)

    Nguyen, Thanh C.; Eddy, Wesley M.; Bretmersky, Steven C.; Lawas-Grodek, Fran; Ellis, Brenda L.

    2006-01-01

    Currently, airport surface communications are fragmented across multiple types of systems. These communication systems for airport operations at most airports today are based dedicated and separate architectures that cannot support system-wide interoperability and information sharing. The requirements placed upon the Communications, Navigation, and Surveillance (CNS) systems in airports are rapidly growing and integration is urgently needed if the future vision of the National Airspace System (NAS) and the Next Generation Air Transportation System (NGATS) 2025 concept are to be realized. To address this and other problems such as airport surface congestion, the Space Based Technologies Project s Surface ICNS Network Architecture team at NASA Glenn Research Center has assessed airport surface communications requirements, analyzed existing and future surface applications, and defined a set of architecture functions that will help design a scalable, reliable and flexible surface network architecture to meet the current and future needs of airport operations. This paper describes the systems approach or methodology to networking that was employed to assess airport surface communications requirements, analyze applications, and to define the surface network architecture functions as the building blocks or components of the network. The systems approach used for defining these functions is relatively new to networking. It is viewing the surface network, along with its environment (everything that the surface network interacts with or impacts), as a system. Associated with this system are sets of services that are offered by the network to the rest of the system. Therefore, the surface network is considered as part of the larger system (such as the NAS), with interactions and dependencies between the surface network and its users, applications, and devices. The surface network architecture includes components such as addressing/routing, network management, network

  15. Fermionic networks

    NASA Astrophysics Data System (ADS)

    Javarone, Marco Alberto

    2016-08-01

    We study the structure of fermionic networks, i.e. a model of networks based on the behavior of fermionic gases, and we analyze dynamical processes over them. In this model, particle dynamics have been mapped to the domain of networks, hence a parameter representing the temperature controls the evolution of the system. In doing so, it is possible to generate adaptive networks, i.e. networks whose structure varies over time. As shown in previous works, networks generated by quantum statistics can undergo critical phenomena as phase transitions and, moreover, they can be considered as thermodynamic systems. In this study, we analyze fermionic networks and opinion dynamics processes over them, framing this network model as a computational model useful to represent complex and adaptive systems. Results highlight that a strong relation holds between the gas temperature and the structure of the achieved networks. Notably, both the degree distribution and the assortativity vary as the temperature varies, hence we can state that fermionic networks behave as adaptive networks. On the other hand, it is worth to highlight that we did not finding relation between outcomes of opinion dynamics processes and the gas temperature. Therefore, although the latter plays a fundamental role in gas dynamics, on the network domain, its importance is related only to structural properties of fermionic networks.

  16. Setting Goals for Achievement in Physical Education Settings

    ERIC Educational Resources Information Center

    Baghurst, Timothy; Tapps, Tyler; Kensinger, Weston

    2015-01-01

    Goal setting has been shown to improve student performance, motivation, and task completion in academic settings. Although goal setting is utilized by many education professionals to help students set realistic and proper goals, physical educators may not be using goal setting effectively. Without incorporating all three types of goals and…

  17. Network Basics.

    ERIC Educational Resources Information Center

    Tennant, Roy

    1992-01-01

    Explains how users can find and access information resources available on the Internet. Highlights include network information centers (NICs); lists, both formal and informal; computer networking protocols, including international standards; electronic mail; remote log-in; and file transfer. (LRW)

  18. The Lockheed Martin Network: An Intranet Analysis.

    ERIC Educational Resources Information Center

    Okey, Robert M.

    Lockheed Martin Corporation, which is comprised of approximately 72 operating units (some 200,000 employees) worldwide, has set up an intranet called the Lockheed Martin Network. On the network, the corporation released a set of corporate policies via web pages which must be implemented by each of its companies. Because each company varied on what…

  19. TARA diagnostic set

    SciTech Connect

    Sevillano, E.; Brau, K.; Goodrich, P.; Irby, J.; Mauel, M.; Post, R.S.; Smith, D.K.; Sullivan, J.

    1985-05-01

    The TARA Tandem Mirror Experiment has recently begun operation. The set of diagnostics available at this time is discussed. The following diagnostics are now in use: diamagnetic loops, a multichord microwave interferometer, Langmuir and emissive probes, pick-up loops, and secondary-emission detectors. End-loss diagnostics include net current detector arrays, Faraday cup arrays, swept particle analyzer arrays, and calorimetry. Light-emission measurements are made in the visible and VUV regions. A multichord fiber-optic array for plasma position detection is also used. In addition, a three-channel charge exchange analyzer, a hard x-ray system, and fast pressure gauges are available.

  20. A new class of rearrangeable interconnection networks

    SciTech Connect

    Douglass, B.G.

    1989-01-01

    With the current interest in general purpose multiprocessing systems and distributed processing networks, a need exists for rearrangeable interconnection networks. These networks can simultaneously transmit information from all sources to all destinations, for all possible combinations of destinations. Such networks exist, and among these the Benes network is of asymptotically optimal hardware complexity. However, this network requires excessive time to recompute the switch settings each time a new set of transmissions is requested by the source processors. Some algorithms exist to reduce this time overhead but they require excessive hardware to compute the settings. This thesis introduces a new class of rearrangeable networks, called reduced networks, based on an extension of Clos three-stage networks. It is shown that the switches in the first and third stages of Clos networks can be constructed as unique path logarithmic networks. Only the center-stage switches must be rearrangeable. This fact is then used to develop a compact network structure. The routing properties of this structure are defined, and it is shown that there is a connectivity in the setting of the switches for any Clos network. An upper and lower bound on this connectivity are established, leading to a fast routing algorithm, with a trade off between the routing time and the network hardware complexity. This can be exploited by the network designer to achieve the best combination of hardware cost and data transfer rate for the particular application. For network sizes contemplated within the foreseeable future, the resulting design will in most cases be closer to the ideal combination than any other network.

  1. Centroid calculation using neural networks

    NASA Astrophysics Data System (ADS)

    Himes, Glenn S.; Inigo, Rafael M.

    1992-01-01

    Centroid calculation provides a means of eliminating translation problems, which is useful for automatic target recognition. a neural network implementation of centroid calculation is described that used a spatial filter and a Hopfield network to determine the centroid location of an object. spatial filtering of a segmented window creates a result whose peak vale occurs at the centroid of the input data set. A Hopfield network then finds the location of this peak and hence gives the location of the centroid. Hardware implementations of the networks are described and simulation results are provided.

  2. Probabilistic framework for network partition

    NASA Astrophysics Data System (ADS)

    Li, Tiejun; Liu, Jian; E, Weinan

    2009-08-01

    Given a large and complex network, we would like to find the partition of this network into a small number of clusters. This question has been addressed in many different ways. In a previous paper, we proposed a deterministic framework for an optimal partition of a network as well as the associated algorithms. In this paper, we extend this framework to a probabilistic setting, in which each node has a certain probability of belonging to a certain cluster. Two classes of numerical algorithms for such a probabilistic network partition are presented and tested. Application to three representative examples is discussed.

  3. Characterizing Network Services through Cluster-Set Variations

    SciTech Connect

    Bartoletti, A; Tang, N

    2005-03-23

    Common Internet services can be reliably distinguished based solely upon the locations of clusters in traffic-based features (ratios of inbound to outbound packets, ratios of packets to payloads, etc.) This capability has value in revealing the nature of ''hidden'' (tunneled) services and in detecting anomalous changes to known services. We provide measures of session capture volumes sufficient to make confidence-level assertions regarding ''unknown'' services, and outline a throughput system for providing alarms for service anomalies.

  4. Controlling centrality in complex networks

    PubMed Central

    Nicosia, V.; Criado, R.; Romance, M.; Russo, G.; Latora, V.

    2012-01-01

    Spectral centrality measures allow to identify influential individuals in social groups, to rank Web pages by popularity, and even to determine the impact of scientific researches. The centrality score of a node within a network crucially depends on the entire pattern of connections, so that the usual approach is to compute node centralities once the network structure is assigned. We face here with the inverse problem, that is, we study how to modify the centrality scores of the nodes by acting on the structure of a given network. We show that there exist particular subsets of nodes, called controlling sets, which can assign any prescribed set of centrality values to all the nodes of a graph, by cooperatively tuning the weights of their out-going links. We found that many large networks from the real world have surprisingly small controlling sets, containing even less than 5 – 10% of the nodes. PMID:22355732

  5. Technologies for convergence in the metro network

    NASA Astrophysics Data System (ADS)

    Frankel, Michael Y.

    2005-02-01

    Traditional metro network architectures comprise multiple layers of networking equipment supporting a wide array of services and packet-oriented applications. Among others, these include WDM, SDH, ATM, Ethernet and IP, each requiring its own network elements and associated management solutions to perform its own independent networking functions. While these work well individually, the combined network is cumbersome and inefficient. Recent advancements in network technologies are now changing the way metro networks are designed. Multi-functional consolidation through technology integration and the standardization of protocol inter-networking methods are leading to a converged network solution in support of a diverse set of packet-aware service offerings. This presentation will explore new technologies that are enabling convergence in the metro network, both across layers and across services.

  6. Index Sets and Vectorization

    SciTech Connect

    Keasler, J A

    2012-03-27

    Vectorization is data parallelism (SIMD, SIMT, etc.) - extension of ISA enabling the same instruction to be performed on multiple data items simultaeously. Many/most CPUs support vectorization in some form. Vectorization is difficult to enable, but can yield large efficiency gains. Extra programmer effort is required because: (1) not all algorithms can be vectorized (regular algorithm structure and fine-grain parallelism must be used); (2) most CPUs have data alignment restrictions for load/store operations (obey or risk incorrect code); (3) special directives are often needed to enable vectorization; and (4) vector instructions are architecture-specific. Vectorization is the best way to optimize for power and performance due to reduced clock cycles. When data is organized properly, a vector load instruction (i.e. movaps) can replace 'normal' load instructions (i.e. movsd). Vector operations can potentially have a smaller footprint in the instruction cache when fewer instructions need to be executed. Hybrid index sets insulate users from architecture specific details. We have applied hybrid index sets to achieve optimal vectorization. We can extend this concept to handle other programming models.

  7. Communications, Navigation, and Network Reconfigurable Test-bed Flight Hardware Compatibility Test S

    NASA Technical Reports Server (NTRS)

    2010-01-01

    Communications, Navigation, and Network Reconfigurable Test-bed Flight Hardware Compatibility Test Sets and Networks Integration Management Office Testing for the Tracking and Data Relay Satellite System

  8. Controllability of the better chosen partial networks

    NASA Astrophysics Data System (ADS)

    Liu, Xueming; Pan, Linqiang

    2016-08-01

    How to control large complex networks is a great challenge. Recent studies have proved that the whole network can be sufficiently steered by injecting control signals into a minimum set of driver nodes, and the minimum numbers of driver nodes for many real networks are high, indicating that it is difficult to control them. For some large natural and technological networks, it is impossible and not feasible to control the full network. For example, in biological networks like large-scale gene regulatory networks it is impossible to control all the genes. This prompts us to explore the question how to choose partial networks that are easy for controlling and important in networked systems. In this work, we propose a method to achieve this goal. By computing the minimum driver nodes densities of the partial networks of Erdös-Rényi (ER) networks, scale-free (SF) networks and 23 real networks, we find that our method performs better than random method that chooses nodes randomly. Moreover, we find that the nodes chosen by our method tend to be the essential elements of the whole systems, via studying the nodes chosen by our method of a real human signaling network and a human protein interaction network and discovering that the chosen nodes from these networks tend to be cancer-associated genes. The implementation of our method shows some interesting connections between the structure and the controllability of networks, improving our understanding of the control principles of complex systems.

  9. A neural computation approach to the set covering problem

    SciTech Connect

    Grossman, T.

    1995-07-01

    This paper presents a neural network algorithm which is capable of finding approximate solutions for unicost set covering problems. The network has two types of units (neurons), with different dynamics and activation functions. One type represents the objects to be covered (the rows in the matrix representation of the problem) and another represents the ``covering`` sets (the 0,1 variables). They are connected as a bipartite graph which represents the incidence relations between objects and sets (i.e the 0,1 adjacency matrix). When the parameters of the units are correctly tuned, the stable states of the system correspond to the minimal covers. I show that in its basic mode of operation, descent dynamics, when the network is set in an arbitrary initial state it converges in less than 2n steps (where n is the number of variables), to a stable state which represents a valid solution. In this mode, the network implements a greedy heuristic in which the choice function is based on the unit inputs (which are determined by the activation functions and the network state). On top of the basic network dynamics, the algorithm applies an adaptive restart procedure which helps to search more effectively for ``good`` initial states and results in better performance.

  10. Small-world networks

    NASA Astrophysics Data System (ADS)

    Strogatz, Steven

    Everyone is familiar with the small-world phenomenon: soon after meeting a stranger, we are often suprised to discover that we have a mutual friend, or that we are somehow linked by a short chain of friends. In this talk, I'll present evidence that the small-world phenomenon is more than a curiosity of social networks — it is actually a general property of large, sparse networks whose topology is neither completely regular nor completely random. To check this idea, Duncan Watts and I have analyzed three networks of scientific interest: the neural network of the nematode worm C. elegans, the electrical power grid of the western United States, and the collaboration graph of actors in feature films. All three are small worlds, in the sense that the average number of "handshakes" separating any two members is extremely small (close to the theoretical lower limit set by a random graph). Yet at the same time, all three networks exhibit much more local clustering than a random net, demonstrating that they are not random. I'll also discuss a class of model networks that interpolate between regular lattices and random graphs. Previous theoretical research on complex systems in a wide range of disciplines has focused almost exclusively on networks that are either regular or random. Real networks often lie somewhere in between. Our mathematical model shows that networks in this middle ground tend to exhibit the small-world phenomenon, thanks to the presence of a few long-range edges that link parts of the graph that would otherwise be far apart. Furthermore, we find that when various dynamical systems are coupled in a small-world fashion, they exhibit much greater propagation speed, computational power, and synchronizability than their locally connected, regular counterparts. We explore the implications of these results for simple models of disease spreading, global computation in cellular automata, and collective locking of biological oscillators.