Science.gov

Sample records for setting network eaprasnet

  1. Partially ordered sets in complex networks

    NASA Astrophysics Data System (ADS)

    Xuan, Qi; Du, Fang; Wu, Tie-Jun

    2010-05-01

    In this paper, a partial-order relation is defined among vertices of a network to describe which vertex is more important than another on its contribution to the connectivity of the network. A maximum linearly ordered subset of vertices is defined as a chain and the chains sharing the same end-vertex are grouped as a family. Through combining the same vertices appearing in different chains, a directed chain graph is obtained. Based on these definitions, a series of new network measurements, such as chain length distribution, family diversity distribution, as well as the centrality of families, are proposed. By studying the partially ordered sets in three kinds of real-world networks, many interesting results are revealed. For instance, the similar approximately power-law chain length distribution may be attributed to a chain-based positive feedback mechanism, i.e. new vertices prefer to participate in longer chains, which can be inferred by combining the notable preferential attachment rule with a well-ordered recommendation manner. Moreover, the relatively large average incoming degree of the chain graphs may indicate an efficient substitution mechanism in these networks. Most of the partially ordered set-based properties cannot be explained by the current well-known scale-free network models; therefore, we are required to propose more appropriate network models in the future.

  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. Edge union of networks on the same vertex set

    NASA Astrophysics Data System (ADS)

    Loe, Chuan Wen; Jeldtoft Jensen, Henrik

    2013-06-01

    Random network generators such as Erdős-Rényi, Watts-Strogatz and Barabási-Albert models are used as models to study real-world networks. Let G1(V, E1) and G2(V, E2) be two such networks on the same vertex set V. This paper studies the degree distribution and clustering coefficient of the resultant networks, G(V, E1∪E2).

  5. 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.

  6. 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.

  7. Dominating sets and ego-centered decompositions in social networks

    NASA Astrophysics Data System (ADS)

    Boudourides, M. A.; Lenis, S. T.

    2016-09-01

    Our aim here is to address the problem of decomposing a whole network into a minimal number of ego-centered subnetworks. For this purpose, the network egos are picked out as the members of a minimum dominating set of the network. However, to find such an efficient dominating ego-centered construction, we need to be able to detect all the minimum dominating sets and to compare all the corresponding dominating ego-centered decompositions of the network. To find all the minimum dominating sets of the network, we are developing a computational heuristic, which is based on the partition of the set of nodes of a graph into three subsets, the always dominant vertices, the possible dominant vertices and the never dominant vertices, when the domination number of the network is known. To compare the ensuing dominating ego-centered decompositions of the network, we are introducing a number of structural measures that count the number of nodes and links inside and across the ego-centered subnetworks. Furthermore, we are applying the techniques of graph domination and ego-centered decomposition for six empirical social networks.

  8. 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.…

  9. 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)

  10. 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.

  11. 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.

  12. Analysis of Gene Sets Based on the Underlying Regulatory Network

    PubMed Central

    Michailidis, George

    2009-01-01

    Abstract Networks are often used to represent the interactions among genes and proteins. These interactions are known to play an important role in vital cell functions and should be included in the analysis of genes that are differentially expressed. Methods of gene set analysis take advantage of external biological information and analyze a priori defined sets of genes. These methods can potentially preserve the correlation among genes; however, they do not directly incorporate the information about the gene network. In this paper, we propose a latent variable model that directly incorporates the network information. We then use the theory of mixed linear models to present a general inference framework for the problem of testing the significance of subnetworks. Several possible test procedures are introduced and a network based method for testing the changes in expression levels of genes as well as the structure of the network is presented. The performance of the proposed method is compared with methods of gene set analysis using both simulation studies, as well as real data on genes related to the galactose utilization pathway in yeast. PMID:19254181

  13. 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…

  14. Social Network Analysis in Healthcare Settings: A Systematic Scoping Review

    PubMed Central

    Chambers, Duncan; Wilson, Paul; Thompson, Carl; Harden, Melissa

    2012-01-01

    Background Social network analysis (SNA) has been widely used across a range of disciplines but is most commonly applied to help improve the effectiveness and efficiency of decision making processes in commercial organisations. We are utilising SNA to inform the development and implementation of tailored behaviour-change interventions to improve the uptake of evidence into practice in the English National Health Service. To inform this work, we conducted a systematic scoping review to identify and evaluate the use of SNA as part of an intervention to support the implementation of change in healthcare settings. Methods and Findings We searched ten bibliographic databases to October 2011. We also searched reference lists, hand searched selected journals and websites, and contacted experts in the field. To be eligible for the review, studies had to describe and report the results of an SNA performed with healthcare professionals (e.g. doctors, nurses, pharmacists, radiographers etc.) and others involved in their professional social networks. We included 52 completed studies, reported in 62 publications. Almost all of the studies were limited to cross sectional descriptions of networks; only one involved using the results of the SNA as part of an intervention to change practice. Conclusions We found very little evidence for the potential of SNA being realised in healthcare settings. However, it seems unlikely that networks are less important in healthcare than other settings. Future research should seek to go beyond the merely descriptive to implement and evaluate SNA-based interventions. PMID:22870261

  15. 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.

  16. 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.

  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.

  18. 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

  19. 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.

  20. 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

  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. 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.

  3. Permitted and forbidden sets in discrete-time linear threshold recurrent neural networks.

    PubMed

    Yi, Zhang; Zhang, Lei; Yu, Jiali; Tan, Kok Kiong

    2009-06-01

    The concepts of permitted and forbidden sets enable a new perspective of the memory in neural networks. Such concepts exhibit interesting dynamics in recurrent neural networks. This paper studies the basic theories of permitted and forbidden sets of the linear threshold discrete-time recurrent neural networks. The linear threshold transfer function has been regarded as an adequate transfer function for recurrent neural networks. Networks with this transfer function form a class of hybrid analog and digital networks which are especially useful for perceptual computations. Networks in discrete time can directly provide algorithms for efficient implementation in digital hardware. The main contribution of this paper is to establish foundations of permitted and forbidden sets. Necessary and sufficient conditions for the linear threshold discrete-time recurrent neural networks are obtained for complete convergence, existence of permitted and forbidden sets, as well as conditionally multiattractivity, respectively. Simulation studies explore some possible interesting practical applications.

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

    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.

  5. Building damage-resilient dominating sets in complex networks against random and targeted attacks.

    PubMed

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

    2015-02-09

    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.

  6. 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.

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

    PubMed

    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.

  8. Social Networking Tools in a University Setting: A Student's Perspective

    ERIC Educational Resources Information Center

    Haytko, Diana L.; Parker, R. Stephen

    2012-01-01

    As Professors, we are challenged to reach ever-changing cohorts of college students as they flow through our classes and our lives. Technological advancements happen daily and we need to decide which, if any, to incorporate into our classrooms. Our students constantly check Facebook, Twitter, MySpace and other online social networks. Should we be…

  9. 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.

  10. Functional-network-based gene set analysis using gene-ontology.

    PubMed

    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

  11. The Impact of Educational Networking in the Educational Setting

    ERIC Educational Resources Information Center

    Lozano, Melissa Nicole

    2011-01-01

    Society's reliance on technology today has created a demand for more effective ways of communication unlike any before. The need to communicate has made its way from the home to the business world and into the educational setting. This article discusses the historical journey that has landed communication in the classroom. Scholars such as Piaget…

  12. 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

  13. A New Method for Setting Calculation Sequence of Directional Relay Protection in Multi-Loop Networks

    NASA Astrophysics Data System (ADS)

    Haijun, Xiong; Qi, Zhang

    2016-08-01

    Workload of relay protection setting calculation in multi-loop networks may be reduced effectively by optimization setting calculation sequences. A new method of setting calculation sequences of directional distance relay protection in multi-loop networks based on minimum broken nodes cost vector (MBNCV) was proposed to solve the problem experienced in current methods. Existing methods based on minimum breakpoint set (MBPS) lead to more break edges when untying the loops in dependent relationships of relays leading to possibly more iterative calculation workloads in setting calculations. A model driven approach based on behavior trees (BT) was presented to improve adaptability of similar problems. After extending the BT model by adding real-time system characters, timed BT was derived and the dependency relationship in multi-loop networks was then modeled. The model was translated into communication sequence process (CSP) models and an optimization setting calculation sequence in multi-loop networks was finally calculated by tools. A 5-nodes multi-loop network was applied as an example to demonstrate effectiveness of the modeling and calculation method. Several examples were then calculated with results indicating the method effectively reduces the number of forced broken edges for protection setting calculation in multi-loop networks.

  14. An efficient graph theory based method to identify every minimal reaction set in a metabolic network

    PubMed Central

    2014-01-01

    Background Development of cells with minimal metabolic functionality is gaining importance due to their efficiency in producing chemicals and fuels. Existing computational methods to identify minimal reaction sets in metabolic networks are computationally expensive. Further, they identify only one of the several possible minimal reaction sets. Results In this paper, we propose an efficient graph theory based recursive optimization approach to identify all minimal reaction sets. Graph theoretical insights offer systematic methods to not only reduce the number of variables in math programming and increase its computational efficiency, but also provide efficient ways to find multiple optimal solutions. The efficacy of the proposed approach is demonstrated using case studies from Escherichia coli and Saccharomyces cerevisiae. In case study 1, the proposed method identified three minimal reaction sets each containing 38 reactions in Escherichia coli central metabolic network with 77 reactions. Analysis of these three minimal reaction sets revealed that one of them is more suitable for developing minimal metabolism cell compared to other two due to practically achievable internal flux distribution. In case study 2, the proposed method identified 256 minimal reaction sets from the Saccharomyces cerevisiae genome scale metabolic network with 620 reactions. The proposed method required only 4.5 hours to identify all the 256 minimal reaction sets and has shown a significant reduction (approximately 80%) in the solution time when compared to the existing methods for finding minimal reaction set. Conclusions Identification of all minimal reactions sets in metabolic networks is essential since different minimal reaction sets have different properties that effect the bioprocess development. The proposed method correctly identified all minimal reaction sets in a both the case studies. The proposed method is computationally efficient compared to other methods for finding minimal

  15. 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

  16. Sensitivity analysis of biological Boolean networks using information fusion based on nonadditive set functions

    PubMed Central

    2014-01-01

    Background An algebraic method for information fusion based on nonadditive set functions is used to assess the joint contribution of Boolean network attributes to the sensitivity of the network to individual node mutations. The node attributes or characteristics under consideration are: in-degree, out-degree, minimum and average path lengths, bias, average sensitivity of Boolean functions, and canalizing degrees. The impact of node mutations is assessed using as target measure the average Hamming distance between a non-mutated/wild-type network and a mutated network. Results We find that for a biochemical signal transduction network consisting of several main signaling pathways whose nodes represent signaling molecules (mainly proteins), the algebraic method provides a robust classification of attribute contributions. This method indicates that for the biochemical network, the most significant impact is generated mainly by the combined effects of two attributes: out-degree, and average sensitivity of nodes. Conclusions The results support the idea that both topological and dynamical properties of the nodes need to be under consideration. The algebraic method is robust against the choice of initial conditions and partition of data sets in training and testing sets for estimation of the nonadditive set functions of the information fusion procedure. PMID:25189194

  17. 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.

  18. 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.

  19. 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

  20. Balance between Noise and Information Flow Maximizes Set Complexity of Network Dynamics

    PubMed Central

    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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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…

  8. 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

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

    PubMed

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

    2016-03-17

    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.

  10. 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

  11. 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.

  12. Short-Term Electric Load Forecasting Using Neural Network with Fuzzy Set Based Classification

    NASA Astrophysics Data System (ADS)

    Bumroonggit, Gumpanart

    1995-01-01

    This research studies a short-term electric load forecasting technique using a multi-layer feedforward Artificial Neural Network with a fuzzy set-based classification algorithm. Based on the fact that the power system load strongly depends on the weather of the serving area, the hourly data is classified into different classes of weather condition using the concept of fuzzy set representation of weather variables. Then the set of artificial neural networks for these classes of weather condition is trained and used to perform the forecasting. The load forecasting index is also developed from the application of the fuzzy logic system. The presented technique is tested with the utility's data for various lead times ranging from 24 to 120 hours. The results indicate that the technique is able to forecast the system load with excellent accuracy and its performance does not deteriorate as the lead time becomes longer.

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

    PubMed

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

    2016-02-11

    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.

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. Computing minimal nutrient sets from metabolic networks via linear constraint solving

    PubMed Central

    2013-01-01

    Background As more complete genome sequences become available, bioinformatics challenges arise in how to exploit genome sequences to make phenotypic predictions. One type of phenotypic prediction is to determine sets of compounds that will support the growth of a bacterium from the metabolic network inferred from the genome sequence of that organism. Results We present a method for computationally determining alternative growth media for an organism based on its metabolic network and transporter complement. Our method predicted 787 alternative anaerobic minimal nutrient sets for Escherichia coli K–12 MG1655 from the EcoCyc database. The program automatically partitioned the nutrients within these sets into 21 equivalence classes, most of which correspond to compounds serving as sources of carbon, nitrogen, phosphorous, and sulfur, or combinations of these essential elements. The nutrient sets were predicted with 72.5% accuracy as evaluated by comparison with 91 growth experiments. Novel aspects of our approach include (a) exhaustive consideration of all combinations of nutrients rather than assuming that all element sources can substitute for one another(an assumption that can be invalid in general) (b) leveraging the notion of a machinery-duplicating constraint, namely, that all intermediate metabolites used in active reactions must be produced in increasing concentrations to prevent successive dilution from cell division, (c) the use of Satisfiability Modulo Theory solvers rather than Linear Programming solvers, because our approach cannot be formulated as linear programming, (d) the use of Binary Decision Diagrams to produce an efficient implementation. Conclusions Our method for generating minimal nutrient sets from the metabolic network and transporters of an organism combines linear constraint solving with binary decision diagrams to efficiently produce solution sets to provided growth problems. PMID:23537498

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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 1990 s 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 2010 Global 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

  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. Random set tracking and entropy based control applied to distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Stein, David; Witkoskie, James; Theophanis, Stephen; Kuklinski, Walter

    2007-04-01

    This paper describes an integrated approach to sensor fusion and resource management applicable to sensor networks. The sensor fusion and tracking algorithm is based on the theory of random sets. Tracking is herein considered to be the estimation of parameters in a state space such that for a given target certain components, e.g., position and velocity, are time varying and other components, e.g., identifying features, are stationary. The fusion algorithm provides at each time step the posterior probability density function, known as the global density, on the state space, and the control algorithm identifies the set of sensors that should be used at the next time step in order to minimize, subject to constraints, an approximation of the expected entropy of the global density. The random set approach to target tracking models association ambiguity by statistically weighing all possible hypotheses and associations. Computational complexity is managed by approximating the posterior Global Density using a Gaussian mixture density and using an approach based on the Kulbach-Leibler metric to limit the number of components in the Gaussian mixture representation. A closed form approximation of the expected entropy of the global density, expressed as a Gaussian mixture density, at the next time step for a given set of proposed measurements is developed. Optimal sensor selection involves a search over subsets of sensors, and the computational complexity of this search is managed by employing the Mobius transformation. Field and simulated data from a sensor network comprised of multiple range radars, and acoustic arrays, that measure angle of arrival, are used to demonstrate the approach to sensor fusion and resource management.

  17. 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

  18. Comparison of bladder segmentation using deep-learning convolutional neural network with and without level sets

    NASA Astrophysics Data System (ADS)

    Cha, Kenny H.; Hadjiiski, Lubomir M.; Samala, Ravi K.; Chan, Heang-Ping; Cohan, Richard H.; Caoili, Elaine M.

    2016-03-01

    We are developing a CAD system for detection of bladder cancer in CTU. In this study we investigated the application of deep-learning convolutional neural network (DL-CNN) to the segmentation of the bladder, which is a challenging problem because of the strong boundary between the non-contrast and contrast-filled regions in the bladder. We trained a DL-CNN to estimate the likelihood of a pixel being inside the bladder using neighborhood information. The segmented bladder was obtained from thresholding and hole-filling of the likelihood map. We compared the segmentation performance of the DL-CNN alone and with additional cascaded 3D and 2D level sets to refine the segmentation using 3D hand-segmented contours as reference standard. The segmentation accuracy was evaluated by five performance measures: average volume intersection %, average % volume error, average absolute % error, average minimum distance, and average Jaccard index for a data set of 81 training and 92 test cases. For the training set, DLCNN with level sets achieved performance measures of 87.2+/-6.1%, 6.0+/-9.1%, 8.7+/-6.1%, 3.0+/-1.2 mm, and 81.9+/-7.6%, respectively, while the DL-CNN alone obtained the values of 73.6+/-8.5%, 23.0+/-8.5%, 23.0+/-8.5%, 5.1+/-1.5 mm, and 71.5+/-9.2%, respectively. For the test set, the DL-CNN with level sets achieved performance measures of 81.9+/-12.1%, 10.2+/-16.2%, 14.0+/-13.0%, 3.6+/-2.0 mm, and 76.2+/-11.8%, respectively, while DL-CNN alone obtained 68.7+/-12.0%, 27.2+/-13.7%, 27.4+/-13.6%, 5.7+/-2.2 mm, and 66.2+/-11.8%, respectively. DL-CNN alone is effective in segmenting bladders but may not follow the details of the bladder wall. The combination of DL-CNN with level sets provides highly accurate bladder segmentation.

  19. 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.

  20. Hydro-Climatic Data Network (HCDN) Streamflow Data Set, 1874-1988

    USGS Publications Warehouse

    Slack, James Richard; Lumb, Alan M.; Landwehr, Jurate Maciunas

    1993-01-01

    The potential consequences of climate change to continental water resources are of great concern in the management of those resources. Critically important to society is what effect fluctuations in the prevailing climate may have on hydrologic conditions, such as the occurrence and magnitude of floods or droughts and the seasonal distribution of water supplies within a region. Records of streamflow that are unaffected by artificial diversions, storage, or other works of man in or on the natural stream channels or in the watershed can provide an account of hydrologic responses to fluctuations in climate. By examining such records given known past meteorologic conditions, we can better understand hydrologic responses to those conditions and anticipate the effects of postulated changes in current climate regimes. Furthermore, patterns in streamflow records can indicate when a change in the prevailing climate regime may have occurred in the past, even in the absence of concurrent meteorologic records. A streamflow data set, which is specifically suitable for the study of surface-water conditions throughout the United States under fluctuations in the prevailing climatic conditions, has been developed. This data set, called the Hydro-Climatic Data Network, or HCDN, consists of streamflow records for 1,659 sites throughout United States and its Territories. Records cumulatively span the period 1874 through 1988, inclusive, and represent a total of 73,231 water years of information. Development of the HCDN Data Set: Records for the HCDN were obtained through a comprehensive search of the extensive surface- water data holdings of the U.S. Geological Survey (USGS), which are contained in the USGS National Water Storage and Retrieval System (WATSTORE). All streamflow discharge records in WATSTORE through September 30, 1988, were examined for inclusion in the HCDN in accordance with strictly defined criteria of measurement accuracy and natural conditions. No reconstructed

  1. General melting point prediction based on a diverse compound data set and artificial neural networks.

    PubMed

    Karthikeyan, M; Glen, Robert C; Bender, Andreas

    2005-01-01

    We report the development of a robust and general model for the prediction of melting points. It is based on a diverse data set of 4173 compounds and employs a large number of 2D and 3D descriptors to capture molecular physicochemical and other graph-based properties. Dimensionality reduction is performed by principal component analysis, while a fully connected feed-forward back-propagation artificial neural network is employed for model generation. The melting point is a fundamental physicochemical property of a molecule that is controlled by both single-molecule properties and intermolecular interactions due to packing in the solid state. Thus, it is difficult to predict, and previously only melting point models for clearly defined and smaller compound sets have been developed. Here we derive the first general model that covers a comparatively large and relevant part of organic chemical space. The final model is based on 2D descriptors, which are found to contain more relevant information than the 3D descriptors calculated. Internal random validation of the model achieves a correlation coefficient of R(2) = 0.661 with an average absolute error of 37.6 degrees C. The model is internally consistent with a correlation coefficient of the test set of Q(2) = 0.658 (average absolute error 38.2 degrees C) and a correlation coefficient of the internal validation set of Q(2) = 0.645 (average absolute error 39.8 degrees C). Additional validation was performed on an external drug data set consisting of 277 compounds. On this external data set a correlation coefficient of Q(2) = 0.662 (average absolute error 32.6 degrees C) was achieved, showing ability of the model to generalize. Compared to an earlier model for the prediction of melting points of druglike compounds our model exhibits slightly improved performance, despite the much larger chemical space covered. The remaining model error is due to molecular properties that are not captured using single-molecule based

  2. Fast computation of minimal cut sets in metabolic networks with a Berge algorithm that utilizes binary bit pattern trees.

    PubMed

    Jungreuthmayer, Christian; Beurton-Aimar, Marie; Zanghellini, Jürgen

    2013-01-01

    Minimal cut sets are a valuable tool for analyzing metabolic networks and for identifying optimal gene intervention strategies by eliminating unwanted metabolic functions and keeping desired functionality. Minimal cut sets rely on the concept of elementary flux modes, which are sets of indivisible metabolic pathways under steady-state condition. However, the computation of minimal cut sets is nontrivial, as even medium-sized metabolic networks with just 100 reactions easily have several hundred million elementary flux modes. We developed a minimal cut set tool that implements the well-known Berge algorithm and utilizes a novel approach to significantly reduce the program run time by using binary bit pattern trees. By using the introduced tree approach, the size of metabolic models that can be analyzed and optimized by minimal cut sets is pushed to new and considerably higher limits.

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

    PubMed

    Takemoto, Kazuhiro; Akutsu, Tatsuya

    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.

  4. 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

  5. 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.

  6. 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

  7. The roles of reward, default, and executive control networks in set-shifting impairments in schizophrenia.

    PubMed

    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

  8. Patients’ experience of chronic illness care in a network of teaching settings

    PubMed Central

    Houle, Janie; Beaulieu, Marie-Dominique; Lussier, Marie-Thérèse; Del Grande, Claudio; Pellerin, Jean-Pierre; Authier, Marie; Duplain, Réjean; Tran, Tri Minh; Allison, François

    2012-01-01

    Abstract Objective To evaluate chronic illness care delivery from the patient’s perspective and to examine its main correlates. Design Cross-sectional, descriptive study using questionnaires and medical chart review. Setting Nine teaching family practices in Quebec. Participants A total of 364 patients with diabetes, hypertension, or chronic obstructive pulmonary disease. Main outcomes measures Score on the Patient Assessment of Chronic Illness Care (PACIC) questionnaire, which evaluates the patient’s perspective on the care received based on the chronic care model (CCM); patients characteristics (sex, level of education, number of chronic illnesses); patient-physician relationship (relational continuity, interpersonal communication assessed from the patient’s perspective); and interdisciplinary care and technical quality of care abstracted from patients’ medical charts. Results The mean PACIC score obtained (2.8 out of 5) indicates that, on average, CCM-concordant care “generally did not occur” or occurred only “sometimes” in this network of teaching practices. However, with a mean technical quality-of-care score of nearly 80%, physicians in this network showed a high degree of adherence to clinical guidelines for the chronic illnesses under study. Patient education level lower than high school was negatively associated with PACIC scores, while positive associations were found with male sex, number of chronic illnesses, relational continuity, interpersonal communication, interdisciplinary care, and technical quality of care. Conclusion Patients with less education reported receiving less CCM-concordant care. The patient-physician relationship was the strongest correlate of PACIC scores, while interdisciplinary care and technical quality of care had modest contributions. PMID:23242897

  9. 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.

  10. 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

  11. 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

  12. Prioritization of candidate disease genes by enlarging the seed set and fusing information of the network topology and gene expression.

    PubMed

    Zhang, Shao-Wu; Shao, Dong-Dong; Zhang, Song-Yao; Wang, Yi-Bin

    2014-06-01

    The identification of disease genes is very important not only to provide greater understanding of gene function and cellular mechanisms which drive human disease, but also to enhance human disease diagnosis and treatment. Recently, high-throughput techniques have been applied to detect dozens or even hundreds of candidate genes. However, experimental approaches to validate the many candidates are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Therefore, numerous theoretical and computational methods (e.g. network-based approaches) have been developed to prioritize candidate disease genes. Many network-based approaches implicitly utilize the observation that genes causing the same or similar diseases tend to correlate with each other in gene-protein relationship networks. Of these network approaches, the random walk with restart algorithm (RWR) is considered to be a state-of-the-art approach. To further improve the performance of RWR, we propose a novel method named ESFSC to identify disease-related genes, by enlarging the seed set according to the centrality of disease genes in a network and fusing information of the protein-protein interaction (PPI) network topological similarity and the gene expression correlation. The ESFSC algorithm restarts at all of the nodes in the seed set consisting of the known disease genes and their k-nearest neighbor nodes, then walks in the global network separately guided by the similarity transition matrix constructed with PPI network topological similarity properties and the correlational transition matrix constructed with the gene expression profiles. As a result, all the genes in the network are ranked by weighted fusing the above results of the RWR guided by two types of transition matrices. Comprehensive simulation results of the 10 diseases with 97 known disease genes collected from the Online Mendelian Inheritance in Man (OMIM) database show that ESFSC outperforms existing methods for

  13. The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.

    PubMed

    Djurfeldt, Mikael

    2012-07-01

    The connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in neuronal network models, from small-scale to large-scale structure. The algebra provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA is expressive enough to describe a wide range of connection patterns, including multiple types of random and/or geometrically dependent connectivity, and can serve as a concise notation for network structure in scientific writing. CSA implementations allow for scalable and efficient representation of connectivity in parallel neuronal network simulators and could even allow for avoiding explicit representation of connections in computer memory. The expressiveness of CSA makes prototyping of network structure easy. A C+ + version of the algebra has been implemented and used in a large-scale neuronal network simulation (Djurfeldt et al., IBM J Res Dev 52(1/2):31-42, 2008b) and an implementation in Python has been publicly released.

  14. 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.

  15. Revisiting the Rural-Urban Contrast: Personal Networks in Nonmetropolitan and Metropolitan Settings.

    ERIC Educational Resources Information Center

    Beggs, John J.; And Others

    1996-01-01

    General Social Survey data (1985) indicate that nonmetropolitan social networks were smaller and denser than urban networks; contained larger proportions of long-term ties, ties to kin and neighbors, and ties involving multiple roles; but were not more homogeneous, except with regard to religion. Data from southwestern Louisiana, however,…

  16. Primary health care service delivery networks for the prevention and management of type 2 diabetes: using social network methods to describe interorganisational collaboration in a rural setting.

    PubMed

    McDonald, Julie; Jayasuriya, Rohan; Harris, Mark Fort

    2011-01-01

    Adults with type 2 diabetes or with behavioural risk factors require comprehensive and well coordinated responses from a range of health care providers who often work in different organisational settings. This study examines three types of collaborative links between organisations involved in a rural setting. Social network methods were employed using survey data on three types of links, and data was collected from a purposive sample of 17 organisations representing the major provider types. The analysis included a mix of unconfirmed and confirmed links, and network measures. General practices were the most influential provider group in initiating referrals, and they referred to the broadest range of organisations in the network. Team care arrangements formed a small part of the general practice referral network. They were used more for access to private sector allied health care providers and less for sharing care with public sector health services. Involvement in joint programs/activities was limited to public and non-government sector services, with no participation from the private sector. The patterns of interactions suggest that informal referral networks provide access to services and coordination of care for individual patients with diabetes. Two population subgroups would benefit from more proactive approaches to ensure equitable access to services and coordination of care across organisational boundaries: people with more complex health care needs and people at risk of developing diabetes.

  17. 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

  18. 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

  19. Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation

    NASA Astrophysics Data System (ADS)

    Gaonkar, Bilwaj; Hovda, David; Martin, Neil; Macyszyn, Luke

    2016-03-01

    Deep Learning, refers to large set of neural network based algorithms, have emerged as promising machine- learning tools in the general imaging and computer vision domains. Convolutional neural networks (CNNs), a specific class of deep learning algorithms, have been extremely effective in object recognition and localization in natural images. A characteristic feature of CNNs, is the use of a locally connected multi layer topology that is inspired by the animal visual cortex (the most powerful vision system in existence). While CNNs, perform admirably in object identification and localization tasks, typically require training on extremely large datasets. Unfortunately, in medical image analysis, large datasets are either unavailable or are extremely expensive to obtain. Further, the primary tasks in medical imaging are organ identification and segmentation from 3D scans, which are different from the standard computer vision tasks of object recognition. Thus, in order to translate the advantages of deep learning to medical image analysis, there is a need to develop deep network topologies and training methodologies, that are geared towards medical imaging related tasks and can work in a setting where dataset sizes are relatively small. In this paper, we present a technique for stacked supervised training of deep feed forward neural networks for segmenting organs from medical scans. Each `neural network layer' in the stack is trained to identify a sub region of the original image, that contains the organ of interest. By layering several such stacks together a very deep neural network is constructed. Such a network can be used to identify extremely small regions of interest in extremely large images, inspite of a lack of clear contrast in the signal or easily identifiable shape characteristics. What is even more intriguing is that the network stack achieves accurate segmentation even when it is trained on a single image with manually labelled ground truth. We validate

  20. 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…

  1. 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

  2. Unions Set Sights on High-Profile Charter-Network Schools

    ERIC Educational Resources Information Center

    Sawchuk, Stephen

    2009-01-01

    What started as a ripple in the charter community shows signs of becoming a wave as major charter school networks scramble to respond to an unfamiliar phenomenon: moves by their teachers to organize unions. In the first half of this year, teachers formed collective bargaining units in schools run by several of the best-known and highest-profile…

  3. 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

  4. 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

    2016-01-11

    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.

  5. 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.

  6. 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

  7. Mitochondrial superoxide in osteocytes perturbs canalicular networks in the setting of age-related osteoporosis.

    PubMed

    Kobayashi, Keiji; Nojiri, Hidetoshi; Saita, Yoshitomo; Morikawa, Daichi; Ozawa, Yusuke; Watanabe, Kenji; Koike, Masato; Asou, Yoshinori; Shirasawa, Takuji; Yokote, Koutaro; Kaneko, Kazuo; Shimizu, Takahiko

    2015-03-16

    Osteocytes are major bone cells that play a crucial role in maintaining the quality of and healing damage to bone tissue. The number of living osteocytes and canalicular networks declines in an age-dependent manner. However, the pathological effects of mitochondrial redox imbalances on osteocytes and bone metabolism have not been fully elucidated. We generated mice lacking mitochondrial superoxide dismutase 2 (Sod2) in osteocytes. Like an aged bone, Sod2 depletion in the osteocytes positively enhanced the production of cellular superoxide in vivo. A bone morphological analysis demonstrated that the Sod2-deficient femurs showed remarkable bone loss in an age-dependent manner. Interestingly, Sod2 loss induced markedly disorganized osteocytic canalicular networks and decreased the number of live osteocytes. Furthermore, Sod2 deficiency significantly suppressed bone formation and increased bone resorption concomitant with the upregulation of sclerostin and receptor activator of NF-κB ligand (RANKL). In vitro experiments also revealed that treatment with paraquat, a superoxide inducer in mitochondria, promoted the RANKL expression via, in part, ERK phosphorylation. These findings demonstrate that the mitochondrial superoxide induced in osteocytes by Sod2 ablation causes age-related bone loss due to the impairment of canalicular networks and bone metabolism via the deregulation of the sclerostin and RANKL expression.

  8. Physical rehabilitation in post-conflict settings: analysis of public policy and stakeholder networks.

    PubMed

    Blanchet, Karl; Girois, Susan; Urseau, Isabelle; Smerdon, Christine; Drouet, Yann; Jama, Ali

    2014-01-01

    Physical rehabilitation plays a determinant role in post-conflict contexts to restore disabled citizens' mobility and independence. While the main objectives of any physical rehabilitation programme are to ensure that the services provided are accessible and of good quality to meet existing needs, it is intended that the services need to be supported over the long term by public health and social welfare authorities. This article presents the results of a study conducted in three post-conflict countries on the relationships between the level of commitment of national governments to rehabilitation services and the influence of social networks on national policy related to physical rehabilitation. From a policy and resource standpoint, the environment in Nepal is the most favourable for creating leverage at the national level to influence the commitment of ministries in the rehabilitation sector, compared with Cambodia and Somaliland. Stakeholder network analysis in Nepal, furthermore, reveals a dominant civil society and private sector supporting rehabilitation services, including intense involvement of local organisations and user groups. Implications for Rehabilitation Physical rehabilitation is not on the top of the agenda of governments in fragile states. The commitment and involvement of national authorities in the rehabilitation sector is positively influenced by civil society and international organisations. The denser the social network of the rehabilitation sector is, the more influence the actors can exert influence over national authorities. PMID:23672208

  9. Functional network construction in Arabidopsis using rule-based machine learning on large-scale data sets.

    PubMed

    Bassel, George W; Glaab, Enrico; Marquez, Julietta; Holdsworth, Michael J; Bacardit, Jaume

    2011-09-01

    The meta-analysis of large-scale postgenomics data sets within public databases promises to provide important novel biological knowledge. Statistical approaches including correlation analyses in coexpression studies of gene expression have emerged as tools to elucidate gene function using these data sets. Here, we present a powerful and novel alternative methodology to computationally identify functional relationships between genes from microarray data sets using rule-based machine learning. This approach, termed "coprediction," is based on the collective ability of groups of genes co-occurring within rules to accurately predict the developmental outcome of a biological system. We demonstrate the utility of coprediction as a powerful analytical tool using publicly available microarray data generated exclusively from Arabidopsis thaliana seeds to compute a functional gene interaction network, termed Seed Co-Prediction Network (SCoPNet). SCoPNet predicts functional associations between genes acting in the same developmental and signal transduction pathways irrespective of the similarity in their respective gene expression patterns. Using SCoPNet, we identified four novel regulators of seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8), and predicted interactions at the level of transcript abundance between these novel and previously described factors influencing Arabidopsis seed germination. An online Web tool to query SCoPNet has been developed as a community resource to dissect seed biology and is available at http://www.vseed.nottingham.ac.uk/. PMID:21896882

  10. 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

  11. A novel proposal of a simplified bacterial gene set and the neo-construction of a general minimized metabolic network

    PubMed Central

    Ye, Yuan-Nong; Ma, Bin-Guang; Dong, Chuan; Zhang, Hong; Chen, Ling-Ling; Guo, Feng-Biao

    2016-01-01

    A minimal gene set (MGS) is critical for the assembly of a minimal artificial cell. We have developed a proposal of simplifying bacterial gene set to approximate a bacterial MGS by the following procedure. First, we base our simplified bacterial gene set (SBGS) on experimentally determined essential genes to ensure that the genes included in the SBGS are critical. Second, we introduced a half-retaining strategy to extract persistent essential genes to ensure stability. Third, we constructed a viable metabolic network to supplement SBGS. The proposed SBGS includes 327 genes and required 431 reactions. This report describes an SBGS that preserves both self-replication and self-maintenance systems. In the minimized metabolic network, we identified five novel hub metabolites and confirmed 20 known hubs. Highly essential genes were found to distribute the connecting metabolites into more reactions. Based on our SBGS, we expanded the pool of targets for designing broad-spectrum antibacterial drugs to reduce pathogen resistance. We also suggested a rough semi-de novo strategy to synthesize an artificial cell, with potential applications in industry. PMID:27713529

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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.

  20. Objectives and applications of phenotyping network set-up for livestock.

    PubMed

    Hocquette, Jean-François; Capel, Carine; David, Valérie; Guémené, Daniel; Bidanel, Joël; Ponsart, Claire; Gastinel, Pierre-Louis; Bail, Pierre-Yves Le; Monget, Philippe; Mormède, Pierre; Barbezant, Maurice; Guillou, Florian; Peyraud, Jean-Louis

    2012-07-01

    Providing phenotypic information, which is accurate, reliable, repeatable and comparable across countries or laboratories, is critical to gain a better understanding of the relationship between genes and phenotypes. So far, it is indeed extremely difficult to combine different sources of phenotypic data from multiple origins, partly because of the variability in the methods of phenotyping. The phenotyping program of livestock involves the definition of complex phenotypes obtained from data integration at different levels (from molecules to herds), the implementation of the latest technologies to accurately characterize at high speed and low cost, the greatest number of animals in a better characterized environment, and the development and sharing of large databases for data analysis and modeling. Such a program also involves the construction of a coordinated network of research and professional facilities and a common language with shared definition of unambiguous animal traits and of methods to assess them. To this end, it will build on the 'Animal Trait Ontology of Livestock' (ATOL) project with the objective of defining precisely the phenotypes of interest for farm animals. Then, it will be necessary to combine an environmental information system related to animal husbandry and associated methods to capture the phenotypic differences between animals.

  1. 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.

  2. 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)

  3. 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.

  4. 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…

  5. 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

  6. 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.

  7. 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

  8. Dynamics and control at feedback vertex sets. II: a faithful monitor to determine the diversity of molecular activities in regulatory networks.

    PubMed

    Mochizuki, Atsushi; Fiedler, Bernold; Kurosawa, Gen; Saito, Daisuke

    2013-10-21

    Modern biology provides many networks describing regulations between many species of molecules. It is widely believed that the dynamics of molecular activities based on such regulatory networks are the origin of biological functions. However, we currently have a limited understanding of the relationship between the structure of a regulatory network and its dynamics. In this study we develop a new theory to provide an important aspect of dynamics from information of regulatory linkages alone. We show that the "feedback vertex set" (FVS) of a regulatory network is a set of "determining nodes" of the dynamics. The theory is powerful to study real biological systems in practice. It assures that (i) any long-term dynamical behavior of the whole system, such as steady states, periodic oscillations or quasi-periodic oscillations, can be identified by measurements of a subset of molecules in the network, and that (ii) the subset is determined from the regulatory linkage alone. For example, dynamical attractors possibly generated by a signal transduction network with 113 molecules can be identified by measurement of the activity of only 5 molecules, if the information on the network structure is correct. Our theory therefore provides a rational criterion to select key molecules to control a system. We also demonstrate that controlling the dynamics of the FVS is sufficient to switch the dynamics of the whole system from one attractor to others, distinct from the original.

  9. Single and mixed dyslipidaemia in Canadian primary care settings: findings from the Canadian primary care sentinel surveillance network database

    PubMed Central

    Asghari, Shabnam; Aref-Eshghi, Erfan; Godwin, Marshall; Duke, Pauline; Williamson, Tyler; Mahdavian, Masoud

    2015-01-01

    Objectives Dyslipidaemia is a major risk factor to cardiovascular disease (CVD)—the leading cause of death worldwide. Limited data are available about the prevalence of various dyslipidaemia in Canada. The objective of this study is to describe the prevalence of various single and mixed dyslipidaemia within the Canadian population in a primary care setting. Setting A cross-sectional study, using the Canadian Primary Care Sentinel Surveillance Network (CPCSSN), was undertaken. Participants Non-pregnant adults older than 20 years were included. Outcome measures Canadian guidelines were used to define dyslipidaemia. Descriptive statistics and multivariate regression analyses were conducted to compare the prevalence of single/mixed dyslipidaemia. Results 134 074 individuals with a mean age of 59.2 (55.8% women) were identified. 34.8% of this population had no lipid abnormality, whereas 35.8%, 17.3% and 3.2% had abnormalities in one, two and three lipid components, respectively. Approximately 86% of these patients did not receive any lipid-lowering medication. Among the medication users (14%), approximately 12% were on statin monotherapy. Statin users (n=16 036) had a lower rate of low-density lipoprotein dyslipidaemia compared to non-medication users (3% vs 17%), whereas the prevalence of high-density lipoprotein (HDL) (20% vs 12%) and triglycerides (TG) (12% vs 7%) dyslipidaemia were higher in statin users. Statin users had a greater prevalence of HDL, TG and combined HDL-TG dyslipidaemia compared to non-medication users (OR 1.44, 95% CI 1.36 to 153), (OR 1.18, 95% CI 1.10 to 1.27) and (OR 1.30, 95% CI 1.22 to 1.38), respectively, (all p values<0.0001). Conclusions One of every five patients in primary care settings in Canada is suffering from mixed dyslipidaemia. The overall prevalence of dyslipidaemia remains the same between treated and untreated groups, although the type of abnormal lipid component is considerably different. Among the CVD risk factors

  10. 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…

  11. A new 2.5D representation for lymph node detection using random sets of deep convolutional neural network observations.

    PubMed

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

    2014-01-01

    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.

  12. 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…

  13. 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...

  14. 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

  15. Time series analysis of benzo[A]pyrene-induced transcriptome changes suggests that a network of transcription factors regulates the effects on functional gene sets.

    PubMed

    van Delft, Joost H M; Mathijs, Karen; Staal, Yvonne C M; van Herwijnen, Marcel H M; Brauers, Karen J J; Boorsma, André; Kleinjans, Jos C S

    2010-10-01

    Chemical carcinogens may cause a multitude of effects inside cells, thereby affecting transcript levels of genes by direct activation of transcription factors (TF) or indirectly through the formation of DNA damage. As the temporal profiles of these responses may be profoundly different, examining time-dependent changes may provide new insights in TF networks related to cellular responses to chemical carcinogens. Therefore, we investigated in human hepatoma cells gene expression changes caused by benzo[a]pyrene at 12 time points after exposure, in relation to DNA adduct and cell cycle. Temporal profiles for functional gene sets demonstrate both early and late effects in up- and downregulation of relevant gene sets involved in cell cycle, apoptosis, DNA repair, and metabolism of amino acids and lipids. Many significant transcription regulation networks appeared to be around TF that are proto-oncogenes or tumor suppressor genes. The time series analysis tool Short Time-series Expression Miner (STEM) was used to identify time-dependent correlation of pathways, gene sets, TF networks, and biological parameters. Most correlations are with DNA adduct levels, which is an early response, and less with the later responses on G1 and S phase cells. The majority of the modulated genes in the Reactome pathways can be regulated by several of these TF, e.g., 73% by nuclear factor-kappa B and 34-42% by c-MYC, SRF, AP1, and E2F1. All these TF can also regulate one or more of the others. Our data indicate that a complex network of a few TF is responsible for the majority of the transcriptional changes induced by BaP. This network hardly changes over time, despite that the transcriptional profiles clearly alter, suggesting that also other regulatory mechanisms are involved.

  16. 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…

  17. 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

  18. A new approach to training back-propagation artificial neural networks: empirical evaluation on ten data sets from clinical studies.

    PubMed

    Ciampi, Antonio; Zhang, Fulin

    2002-05-15

    We present a new approach to training back-propagation artificial neural nets (BP-ANN) based on regularization and cross-validation and on initialization by a logistic regression (LR) model. The new approach is expected to produce a BP-ANN predictor at least as good as the LR-based one. We have applied the approach to ten data sets of biomedical interest and systematically compared BP-ANN and LR. In all data sets, taking deviance as criterion, the BP-ANN predictor outperforms the LR predictor used in the initialization, and in six cases the improvement is statistically significant. The other evaluation criteria used (C-index, MSE and error rate) yield variable results, but, on the whole, confirm that, in practical situations of clinical interest, proper training may significantly improve the predictive performance of a BP-ANN.

  19. Engaging communities to strengthen research ethics in low-income settings: selection and perceptions of members of a network of representatives in coastal Kenya.

    PubMed

    Kamuya, Dorcas M; Marsh, Vicki; Kombe, Francis K; Geissler, P Wenzel; Molyneux, Sassy C

    2013-04-01

    There is wide agreement that community engagement is important for many research types and settings, often including interaction with 'representatives' of communities. There is relatively little published experience of community engagement in international research settings, with available information focusing on Community Advisory Boards or Groups (CAB/CAGs), or variants of these, where CAB/G members often advise researchers on behalf of the communities they represent. In this paper we describe a network of community members ('KEMRI Community Representatives', or 'KCRs') linked to a large multi-disciplinary research programme on the Kenyan Coast. Unlike many CAB/Gs, the intention with the KCR network has evolved to be for members to represent the geographical areas in which a diverse range of health studies are conducted through being typical of those communities. We draw on routine reports, self-administered questionnaires and interviews to: 1) document how typical KCR members are of the local communities in terms of basic characteristics, and 2) explore KCR's perceptions of their roles, and of the benefits and challenges of undertaking these roles. We conclude that this evolving network is a potentially valuable way of strengthening interactions between a research institution and a local geographic community, through contributing to meeting intrinsic ethical values such as showing respect, and instrumental values such as improving consent processes. However, there are numerous challenges involved. Other ways of interacting with members of local communities, including community leaders, and the most vulnerable groups least likely to be vocal in representative groups, have always been, and remain, essential. PMID:23433404

  20. ENGAGING COMMUNITIES TO STRENGTHEN RESEARCH ETHICS IN LOW-INCOME SETTINGS: SELECTION AND PERCEPTIONS OF MEMBERS OF A NETWORK OF REPRESENTATIVES IN COASTAL KENYA

    PubMed Central

    Kamuya, Dorcas M; Marsh, Vicki; Kombe, Francis K; Geissler, P Wenzel; Molyneux, Sassy C

    2013-01-01

    There is wide agreement that community engagement is important for many research types and settings, often including interaction with ‘representatives’ of communities. There is relatively little published experience of community engagement in international research settings, with available information focusing on Community Advisory Boards or Groups (CAB/CAGs), or variants of these, where CAB/G members often advise researchers on behalf of the communities they represent. In this paper we describe a network of community members (‘KEMRI Community Representatives’, or ‘KCRs’) linked to a large multi-disciplinary research programme on the Kenyan Coast. Unlike many CAB/Gs, the intention with the KCR network has evolved to be for members to represent the geographical areas in which a diverse range of health studies are conducted through being typical of those communities. We draw on routine reports, self-administered questionnaires and interviews to: 1) document how typical KCR members are of the local communities in terms of basic characteristics, and 2) explore KCR's perceptions of their roles, and of the benefits and challenges of undertaking these roles. We conclude that this evolving network is a potentially valuable way of strengthening interactions between a research institution and a local geographic community, through contributing to meeting intrinsic ethical values such as showing respect, and instrumental values such as improving consent processes. However, there are numerous challenges involved. Other ways of interacting with members of local communities, including community leaders, and the most vulnerable groups least likely to be vocal in representative groups, have always been, and remain, essential. PMID:23433404

  1. Engaging communities to strengthen research ethics in low-income settings: selection and perceptions of members of a network of representatives in coastal Kenya.

    PubMed

    Kamuya, Dorcas M; Marsh, Vicki; Kombe, Francis K; Geissler, P Wenzel; Molyneux, Sassy C

    2013-04-01

    There is wide agreement that community engagement is important for many research types and settings, often including interaction with 'representatives' of communities. There is relatively little published experience of community engagement in international research settings, with available information focusing on Community Advisory Boards or Groups (CAB/CAGs), or variants of these, where CAB/G members often advise researchers on behalf of the communities they represent. In this paper we describe a network of community members ('KEMRI Community Representatives', or 'KCRs') linked to a large multi-disciplinary research programme on the Kenyan Coast. Unlike many CAB/Gs, the intention with the KCR network has evolved to be for members to represent the geographical areas in which a diverse range of health studies are conducted through being typical of those communities. We draw on routine reports, self-administered questionnaires and interviews to: 1) document how typical KCR members are of the local communities in terms of basic characteristics, and 2) explore KCR's perceptions of their roles, and of the benefits and challenges of undertaking these roles. We conclude that this evolving network is a potentially valuable way of strengthening interactions between a research institution and a local geographic community, through contributing to meeting intrinsic ethical values such as showing respect, and instrumental values such as improving consent processes. However, there are numerous challenges involved. Other ways of interacting with members of local communities, including community leaders, and the most vulnerable groups least likely to be vocal in representative groups, have always been, and remain, essential.

  2. A Systematic Review and Network Meta-Analysis of Biologic Agents in the First Line Setting for Advanced Colorectal Cancer

    PubMed Central

    Kumachev, Alexander; Yan, Marie; Berry, Scott; Ko, Yoo-Joung; Martinez, Maria C. R.; Shah, Keya; Chan, Kelvin K. W.

    2015-01-01

    Background Epithelial growth factor receptor inhibitors (EGFRis) and bevacizumab (BEV) are used in combination with chemotherapy for the treatment of metastatic colorectal cancer (mCRC). However, few randomized controlled trials (RCTs) have directly compared their relative efficacy on progression-free survival (PFS) and overall survival (OS). Methods We conducted a systematic review of first-line RCTs comparing (1) EGFRis vs. BEV, with chemotherapy in both arms (2) EGFRis + chemotherapy vs. chemotherapy alone, or (3) BEV + chemotherapy vs. chemotherapy alone, using Cochrane methodology. Data on and PFS and OS were extracted using the Parmar method. Pairwise meta-analyses and Bayesian network meta-analyses (NMA) were conducted to estimate the direct, indirect and combined PFS and OS hazard ratios (HRs) comparing EGFRis to BEV. Results Seventeen RCTs contained extractable data for quantitative analysis. Combining direct and indirect data using an NMA did not show a statistical difference between EGFRis versus BEV (PFS HR = 1.11 (95% CR: 0.92–1.36) and OS HR = 0.91 (95% CR: 0.75–1.09)). Direct meta-analysis (3 RCTs), indirect (14 RCTs) and combined (17 RCTs) NMA of PFS HRs were concordant and did not show a difference between EGFRis and BEV. Meta-analysis of OS using direct evidence, largely influenced by one trial, showed an improvement with EGFRis therapy (HR = 0.79 (95% CR: 0.65–0.98)), while indirect and combined NMA of OS did not show a difference between EGFRis and BEV Successive inclusions of trials over time in the combined NMA did not show superiority of EGFRis over BEV. Conclusions Our findings did not support OS or PFS benefits of EGFRis over BEV in first-line mCRC. PMID:26474403

  3. 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.

  4. 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.

  5. 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.

  6. Networks.

    ERIC Educational Resources Information Center

    Cerf, Vinton G.

    1991-01-01

    The demands placed on the networks transporting the information and knowledge generated by the increased diversity and sophistication of computational machinery are described. What is needed to support this increased flow, the structures already in place, and what must be built are topics of discussion. (KR)

  7. Using rough sets, neural networks, and logistic regression to predict compliance with cholesterol guidelines goals in patients with coronary artery disease.

    PubMed

    Dubey, Anil K

    2003-01-01

    Coronary artery disease is a leading cause of death and disability in the United States and throughout the developed world. Results from large randomized, blinded, placebo-controlled trials have demonstrated clearly the benefit of lowering LDL cholesterol in lowering the risk for coronary artery disease. Unfortunately, despite the quantity of evidence, and the availability of medications that can efficiently lower LDL cholesterol with few side effects, not everyone who could benefit from cholesterol lowering interventions actually receives them. Despite the dissemination of national care guidelines for the evaluation and treatment of cholesterol levels (NCEP - National Cholesterol Education Program), compliance with such guidelines is suboptimal. There clearly is room for improvement in narrowing the gap between evidence based guidelines and actual clinical practice. The ability to classify those patients who are or will likely to be noncompliant on the basis of patient data routinely collected during patient care could be potentially useful by enabling the focusing of limited health care resources to those who are or will be at high risk of being under treated. In order to explore this possibility further, we attempted to create such classifiers of cholesterol guideline compliance. To do this, we obtained data from an ambulatory electronic medical record system at use at the MGH adult primary care practices for over 20 years. We obtained the data from this hierarchically-structured EMR using its own native query language, called MQL (Medical Query Language). Next, we applied to the collected data the machine learning techniques of rough set theory, neural networks (feed forward backpropagation nets), and logistic regression. We did this by using commonly available software that for the most part is freely available via the internet. We then compared the accuracy of the classifier models using the receiver operating characteristic (ROC) area and C-index summary

  8. 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.

  9. 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

  10. Automated International Information Networks; Systems Design Concepts, Goal-Setting and Priorities. FID/TM Panel at the ASIS Meeting in San Francisco, 2 October, 1969.

    ERIC Educational Resources Information Center

    Samuelson, Kjell

    An invitation to participate in this panel discussion was sent to official representatives of organizations which had an expressed interest in information networks. Since some of the represented international bodies had started preliminary planning for network communication, the discussion was centered around systems design concepts. However, as…

  11. 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…

  12. 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)

  13. 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.

  14. Stroke management in northern Lombardy: organization of an emergency-urgency network and development of a connection between prehospital and in-hospital settings.

    PubMed

    Vidale, Simone; Verrengia, Elena; Gerardi, Francesca; Arnaboldi, Marco; Bezzi, Giacomo; Bono, Giorgio; Guidotti, Mario; Grampa, Giampiero; Perrone, Patrizia; Zarcone, Davide; Zoli, Alberto; Beghi, Ettore; Agostoni, Elio; Porazzi, Daniele; Landriscina, Mario

    2012-08-01

    Stroke is the leading cause of disability in adulthood, and the principal aim of care in cerebrovascular disease is the reduction of this negative outcome and mortality. Several studies demonstrated the efficacy of thrombolytic therapy in ischemic stroke, but up to 80% of cases could not be treated because the diagnostic workup exceeds the time limit. In this article, we described the design of a study conducted in the northern Lombardy, within the district of Sondrio, Lecco, Como, and Varese. The awaited results of this study are reduction of avoidable delay, organization of an operative stroke emergency network, and identification of highly specialized structures. The study schedules education and data registration with implementation and training of acute stroke management algorithms. The use of standardized protocols during prehospital and in-hospital phase can optimize acute stroke pathways. The results of this study could contribute to the assessment of an effective and homogeneous health system to manage acute stroke.

  15. Sequencing-based gene network analysis provides a core set of gene resource for understanding thermal adaptation in Zhikong scallop Chlamys farreri.

    PubMed

    Fu, X; Sun, Y; Wang, J; Xing, Q; Zou, J; Li, R; Wang, Z; Wang, S; Hu, X; Zhang, L; Bao, Z

    2014-01-01

    Marine organisms are commonly exposed to variable environmental conditions, and many of them are under threat from increased sea temperatures caused by global climate change. Generating transcriptomic resources under different stress conditions are crucial for understanding molecular mechanisms underlying thermal adaptation. In this study, we conducted transcriptome-wide gene expression profiling of the scallop Chlamys farreri challenged by acute and chronic heat stress. Of the 13 953 unique tags, more than 850 were significantly differentially expressed at each time point after acute heat stress, which was more than the number of tags differentially expressed (320-350) under chronic heat stress. To obtain a systemic view of gene expression alterations during thermal stress, a weighted gene coexpression network was constructed. Six modules were identified as acute heat stress-responsive modules. Among them, four modules involved in apoptosis regulation, mRNA binding, mitochondrial envelope formation and oxidation reduction were downregulated. The remaining two modules were upregulated. One was enriched with chaperone and the other with microsatellite sequences, whose coexpression may originate from a transcription factor binding site. These results indicated that C. farreri triggered several cellular processes to acclimate to elevated temperature. No modules responded to chronic heat stress, suggesting that the scallops might have acclimated to elevated temperature within 3 days. This study represents the first sequencing-based gene network analysis in a nonmodel aquatic species and provides valuable gene resources for the study of thermal adaptation, which should assist in the development of heat-tolerant scallop lines for aquaculture.

  16. Youths navigating social networks and social support systems in settings of chronic crisis: the case of youth-headed households in Rwanda.

    PubMed

    Lee, Laura May

    2012-10-01

    Youth-headed households in Rwanda live in a context of chronic crisis, where poverty, disease and uncertainty are not exceptional but characterise people's daily lived reality. Struggling under the pressures of economic deprivation, social isolation, abuse and exploitation, these youths experience social suffering and feel the impact of social forces on their everyday lives. Yet, amid constraints in the environment, youths demonstrate resilience by actively navigating their social networks and working to create opportunities for the future. The article describes qualitative research carried out in three communities in Rwanda, between 2006 and 2010, examining the support systems of Rwandan youths affected by the HIV epidemic and socio-political conflict and exploring how youth heads of households navigate social networks in order to buffer the suffering in their lives. It is argued that social support is vital for these youths as they struggle to survive, seek to gain a degree of control over their lives, and strive to have a hopeful future. Examples show the remarkable ability of such youths to confront adversity by mobilising resources and exhibiting agency, although they may continue to experience suffering when support is lacking. The article concludes that to improve wellbeing and reduce suffering for youth-headed households, it is critical to recognise the social relations that may limit or enhance these youths' ability to navigate their social environment. Youths' agency needs to be recognised as a means to reduce the detrimental impacts of their actions and instead build on positive strategies, enabling them as they navigate their life course towards future possibilities. Finally, the dual role of youth heads of households - as individuals in adult roles and as youths - should be recognised, with initiatives to build them up designed around economic strengthening and mentorship.

  17. Network of vascular diseases, death and biochemical characteristics in a set of 4,197 patients with type 1 diabetes (The FinnDiane Study)

    PubMed Central

    Mäkinen, Ville-Petteri; Forsblom, Carol; Thorn, Lena M; Wadén, Johan; Kaski, Kimmo; Ala-Korpela, Mika; Groop, Per-Henrik

    2009-01-01

    Background Cardiovascular disease is the main cause of premature death in patients with type 1 diabetes. Patients with diabetic kidney disease have an increased risk of heart attack or stroke. Accurate knowledge of the complex inter-dependencies between the risk factors is critical for pinpointing the best targets for research and treatment. Therefore, the aim of this study was to describe the association patterns between clinical and biochemical features of diabetic complications. Methods Medical records and serum and urine samples of 4,197 patients with type 1 diabetes were collected from health care centers in Finland. At baseline, the mean diabetes duration was 22 years, 52% were male, 23% had kidney disease (urine albumin excretion over 300 mg/24 h or end-stage renal disease) and 8% had a history of macrovascular events. All-cause mortality was evaluated after an average of 6.5 years of follow-up (25,714 patient years). The dataset comprised 28 clinical and 25 biochemical variables that were regarded as the nodes of a network to assess their mutual relationships. Results The networks contained cliques that were densely inter-connected (r > 0.6), including cliques for high-density lipoprotein (HDL) markers, for triglycerides and cholesterol, for urinary excretion and for indices of body mass. The links between the cliques showed biologically relevant interactions: an inverse relationship between HDL cholesterol and the triglyceride clique (r < -0.3, P < 10-16), a connection between triglycerides and body mass via C-reactive protein (r > 0.3, P < 10-16) and intermediate-density cholesterol as the connector between lipoprotein metabolism and albuminuria (r > 0.3, P < 10-16). Aging and macrovascular disease were linked to death via working ability and retinopathy. Diabetic kidney disease, serum creatinine and potassium, retinopathy and blood pressure were inter-connected. Blood pressure correlations indicated accelerated vascular aging in individuals with kidney

  18. SETS. Set Equation Transformation System

    SciTech Connect

    Worrell, 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.

  19. 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

  20. Networking computers.

    PubMed

    McBride, D C

    1997-03-01

    This decade the role of the personal computer has shifted dramatically from a desktop device designed to increase individual productivity and efficiency to an instrument of communication linking people and machines in different places with one another. A computer in one city can communicate with another that may be thousands of miles away. Networking is how this is accomplished. Just like the voice network used by the telephone, computer networks transmit data and other information via modems over these same telephone lines. A network can be created over both short and long distances. Networks can be established within a hospital or medical building or over many hospitals or buildings covering many geographic areas. Those confined to one location are called LANs, local area networks. Those that link computers in one building to those at other locations are known as WANs, or wide area networks. The ultimate wide area network is the one we've all been hearing so much about these days--the Internet, and its World Wide Web. Setting up a network is a process that requires careful planning and commitment. To avoid potential pitfalls and to make certain the network you establish meets your needs today and several years down the road, several steps need to be followed. This article reviews the initial steps involved in getting ready to network.

  1. Dissection of the oncogenic MYCN transcriptional network reveals a large set of clinically relevant cell cycle genes as drivers of neuroblastoma tumorigenesis.

    PubMed

    Murphy, Derek M; Buckley, Patrick G; Bryan, Kenneth; Watters, Karen M; Koster, Jan; van Sluis, Peter; Molenaar, Jan; Versteeg, Rogier; Stallings, Raymond L

    2011-06-01

    Amplification of the oncogenic transcription factor MYCN plays a major role in the pathogenesis of several pediatric cancers, including neuroblastoma, medulloblastoma, and rhabodomyosarcoma. For neuroblastoma, MYCN amplification is the most powerful genetic predictor of poor patient survival, yet the mechanism by which MYCN drives tumorigenesis is only partially understood. To gain an insight into the distribution of MYCN binding and to identify clinically relevant MYCN target genes, we performed an integrated analysis of MYCN ChIP-chip and mRNA expression using the MYCN repressible SHEP-21N neuroblastoma cell line. We hypothesized that genes exclusively MYCN bound in SHEP-21N cells over-expressing MYCN would be enriched for direct targets which contribute to the process of disease progression. Integrated analysis revealed that MYCN drives tumorigenesis predominantly as a positive regulator of target gene transcription. A high proportion of genes (24%) that are MYCN bound and up-regulated in the SHEP-21N model are significantly associated with poor overall patient survival (OS) in a set of 88 tumors. In contrast, the proportion of genes down-regulated when bound by MYCN in the SHEP-21N model and which are significantly associated with poor overall patient survival when under-expressed in primary tumors was significantly lower (5%). Gene ontology analysis determined a highly statistically significant enrichment for cell cycle related genes within the over-expressed MYCN target group which were also associated with poor OS. We conclude that the over-expression of MYCN leads to aberrant binding and over-expression of genes associated with cell cycle regulation which are significantly correlated with poor OS and MYCN amplification.

  2. Assisting the diagnosis of Graves' hyperthyroidism with Bayesian-type and SOM-type neural networks by making use of a set of three routine tests and their correlation with free T4.

    PubMed

    Sato, W; Hoshi, K; Kawakami, J; Sato, K; Sugawara, A; Saito, Y; Yoshida, K

    2010-01-01

    In our previous paper, we proposed a novel screening method that assists the diagnosis of Graves' hyperthyroidism via two types of neural networks by making use of routine test data. This method can be applied by non-specialists during physical check-ups at a low cost and is expected to lead to rapid referrals for examination and treatment by thyroid specialists, that is, to improve patients' QOL. In this report, the amount of female sample data was increased and routine test data (14 parameters) from 120 subjects with a known diagnosis (35 patients with Graves' hyperthyroidism and 85 healthy volunteers) were adopted as training data, before 171 individuals who had also undergone the same routine tests at the Tohoku University Hospital were screened by the network for Graves' hyperthyroidism. The present re-examination of the screening method showed its high screening ability with the set of parameters used (low serum creatinine was added to the established measures of elevated alkaline phosphatase and low total cholesterol that appear in the Graves' hyperthyroidism guidelines) and robustness due to the increase of the training sample data. It was also found that there is a strong correlation between the three parameters and serum free thyroxine (FT4) in Graves' hyperthyroidism, which supports the usefulness of our screening method.

  3. 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.

  4. 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.

  5. 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.

  6. Subgraphs and network motifs in geometric networks

    NASA Astrophysics Data System (ADS)

    Itzkovitz, Shalev; Alon, Uri

    2005-02-01

    Many real-world networks describe systems in which interactions decay with the distance between nodes. Examples include systems constrained in real space such as transportation and communication networks, as well as systems constrained in abstract spaces such as multivariate biological or economic data sets and models of social networks. These networks often display network motifs: subgraphs that recur in the network much more often than in randomized networks. To understand the origin of the network motifs in these networks, it is important to study the subgraphs and network motifs that arise solely from geometric constraints. To address this, we analyze geometric network models, in which nodes are arranged on a lattice and edges are formed with a probability that decays with the distance between nodes. We present analytical solutions for the numbers of all three- and four-node subgraphs, in both directed and nondirected geometric networks. We also analyze geometric networks with arbitrary degree sequences and models with a bias for directed edges in one direction. Scaling rules for scaling of subgraph numbers with system size, lattice dimension, and interaction range are given. Several invariant measures are found, such as the ratio of feedback and feed-forward loops, which do not depend on system size, dimension, or connectivity function. We find that network motifs in many real-world networks, including social networks and neuronal networks, are not captured solely by these geometric models. This is in line with recent evidence that biological network motifs were selected as basic circuit elements with defined information-processing functions.

  7. Unraveling the signal scenario of fruit set.

    PubMed

    Sotelo-Silveira, Mariana; Marsch-Martínez, Nayelli; de Folter, Stefan

    2014-06-01

    Long-term goals to impact or modify fruit quality and yield have been the target of researchers for many years. Different approaches such as traditional breeding,mutation breeding, and transgenic approaches have revealed a regulatory network where several hormones concur in a complex way to regulate fruit set and development,and these networks are shared in some way among species with different kinds of fruits. Understanding the molecular and biochemical networks of fruit set and development could be very useful for breeders to meet the current and future challenges of agricultural problems. PMID:24659051

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. Affinity driven social networks

    NASA Astrophysics Data System (ADS)

    Ruyú, B.; Kuperman, M. N.

    2007-04-01

    In this work we present a model for evolving networks, where the driven force is related to the social affinity between individuals of a population. In the model, a set of individuals initially arranged on a regular ordered network and thus linked with their closest neighbors are allowed to rearrange their connections according to a dynamics closely related to that of the stable marriage problem. We show that the behavior of some topological properties of the resulting networks follows a non trivial pattern.

  15. Dominating Biological Networks

    PubMed Central

    Milenković, Tijana; Memišević, Vesna; Bonato, Anthony; Pržulj, Nataša

    2011-01-01

    Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI) networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of “biologically central (BC)” genes (i.e., their protein products), such as those involved in aging, cancer, infectious diseases, or signaling and drug-targeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network. To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC) role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs) in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its “spine” that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks. PMID:21887225

  16. 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.

  17. 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

    2015-10-20

    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.

  18. 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.

  19. Spatially embedded random networks.

    PubMed

    Barnett, L; Di Paolo, E; Bullock, S

    2007-11-01

    Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the spatial element is mostly ignored and, in particular, its relation to network structure disregarded. In this paper we introduce a model framework to analyze the mediation of network structure by spatial embedding; specifically, we model connectivity as dependent on the distance between network nodes. Our spatially embedded random networks construction is not primarily intended as an accurate model of any specific class of real-world networks, but rather to gain intuition for the effects of spatial embedding on network structure; nevertheless we are able to demonstrate, in a quite general setting, some constraints of spatial embedding on connectivity such as the effects of spatial symmetry, conditions for scale free degree distributions and the existence of small-world spatial networks. We also derive some standard structural statistics for spatially embedded networks and illustrate the application of our model framework with concrete examples. PMID:18233726

  20. Spatially embedded random networks

    NASA Astrophysics Data System (ADS)

    Barnett, L.; di Paolo, E.; Bullock, S.

    2007-11-01

    Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the spatial element is mostly ignored and, in particular, its relation to network structure disregarded. In this paper we introduce a model framework to analyze the mediation of network structure by spatial embedding; specifically, we model connectivity as dependent on the distance between network nodes. Our spatially embedded random networks construction is not primarily intended as an accurate model of any specific class of real-world networks, but rather to gain intuition for the effects of spatial embedding on network structure; nevertheless we are able to demonstrate, in a quite general setting, some constraints of spatial embedding on connectivity such as the effects of spatial symmetry, conditions for scale free degree distributions and the existence of small-world spatial networks. We also derive some standard structural statistics for spatially embedded networks and illustrate the application of our model framework with concrete examples.

  1. Cross-cultural and site-based influences on demographic, well-being, and social network predictors of risk perception in hazard and disaster settings in Ecuador and Mexico: predictors of risk perception in hazard and disaster settings in Ecuador and Mexico.

    PubMed

    Jones, Eric C; Faas, Albert J; Murphy, Arthur D; Tobin, Graham A; Whiteford, Linda M; McCarty, Christopher

    2013-03-01

    Although virtually all comparative research about risk perception focuses on which hazards are of concern to people in different culture groups, much can be gained by focusing on predictors of levels of risk perception in various countries and places. In this case, we examine standard and novel predictors of risk perception in seven sites among communities affected by a flood in Mexico (one site) and volcanic eruptions in Mexico (one site) and Ecuador (five sites). We conducted more than 450 interviews with questions about how people feel at the time (after the disaster) regarding what happened in the past, their current concerns, and their expectations for the future. We explore how aspects of the context in which people live have an effect on how strongly people perceive natural hazards in relationship with demographic, well-being, and social network factors. Generally, our research indicates that levels of risk perception for past, present, and future aspects of a specific hazard are similar across these two countries and seven sites. However, these contexts produced different predictors of risk perception-in other words, there was little overlap between sites in the variables that predicted the past, present, or future aspects of risk perception in each site. Generally, current stress was related to perception of past danger of an event in the Mexican sites, but not in Ecuador; network variables were mainly important for perception of past danger (rather than future or present danger), although specific network correlates varied from site to site across the countries.

  2. A Network Primer for Educators.

    ERIC Educational Resources Information Center

    Cornish, Maria; Monahan, Brian

    1996-01-01

    Provides educators with a basic understanding of what networks are and how they can be used in educational settings. Topics include issues, policies, and equipment involved in setting up a network; software; telephone service; a computer facilitator; and the Internet and the World Wide Web for elementary and secondary education. (LRW)

  3. Motifs in brain networks.

    PubMed

    Sporns, Olaf; Kötter, Rolf

    2004-11-01

    Complex brains have evolved a highly efficient network architecture whose structural connectivity is capable of generating a large repertoire of functional states. We detect characteristic network building blocks (structural and functional motifs) in neuroanatomical data sets and identify a small set of structural motifs that occur in significantly increased numbers. Our analysis suggests the hypothesis that brain networks maximize both the number and the diversity of functional motifs, while the repertoire of structural motifs remains small. Using functional motif number as a cost function in an optimization algorithm, we obtain network topologies that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. These results are consistent with the hypothesis that highly evolved neural architectures are organized to maximize functional repertoires and to support highly efficient integration of information.

  4. Motifs in Brain Networks

    PubMed Central

    2004-01-01

    Complex brains have evolved a highly efficient network architecture whose structural connectivity is capable of generating a large repertoire of functional states. We detect characteristic network building blocks (structural and functional motifs) in neuroanatomical data sets and identify a small set of structural motifs that occur in significantly increased numbers. Our analysis suggests the hypothesis that brain networks maximize both the number and the diversity of functional motifs, while the repertoire of structural motifs remains small. Using functional motif number as a cost function in an optimization algorithm, we obtain network topologies that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. These results are consistent with the hypothesis that highly evolved neural architectures are organized to maximize functional repertoires and to support highly efficient integration of information. PMID:15510229

  5. Noncomputable Spectral Sets

    NASA Astrophysics Data System (ADS)

    Teutsch, Jason

    2007-01-01

    It is possible to enumerate all computer programs. In particular, for every partial computable function, there is a shortest program which computes that function. f-MIN is the set of indices for shortest programs. In 1972, Meyer showed that f-MIN is Turing equivalent to 0'', the halting set with halting set oracle. This paper generalizes the notion of shortest programs, and we use various measures from computability theory to describe the complexity of the resulting "spectral sets." We show that under certain Godel numberings, the spectral sets are exactly the canonical sets 0', 0'', 0''', ... up to Turing equivalence. This is probably not true in general, however we show that spectral sets always contain some useful information. We show that immunity, or "thinness" is a useful characteristic for distinguishing between spectral sets. In the final chapter, we construct a set which neither contains nor is disjoint from any infinite arithmetic set, yet it is 0-majorized and contains a natural spectral set. Thus a pathological set becomes a bit more friendly. Finally, a number of interesting open problems are left for the inspired reader.

  6. 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.

  7. 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

  8. 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.

  9. 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]).

  10. 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.…

  11. Visualizing Social Networks

    NASA Astrophysics Data System (ADS)

    Correa, Carlos D.; Ma, Kwan-Liu

    With today‘s ubiquity and popularity of social network applications, the ability to analyze and understand large networks in an efficient manner becomes critically important. However, as networks become larger and more complex, reasoning about social dynamics via simple statistics is not a feasible option. To overcome these limitations, we can rely on visual metaphors. Visualization nowadays is no longer a passive process that produces images from a set of numbers. Recent years have witnessed a convergence of social network analytics and visualization, coupled with interaction, that is changing the way analysts understand and characterize social networks. In this chapter, we discuss the main goal of visualization and how different metaphors are aimed towards elucidating different aspects of social networks, such as structure and semantics. We also describe a number of methods where analytics and visualization are interwoven towards providing a better comprehension of social structure and dynamics.

  12. National Highway Planning Network

    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

  13. 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.

  14. 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 ...

  15. Embeddings of Causal Sets

    SciTech Connect

    Reid, David D.

    2009-07-06

    A key postulate of the causal set program is that this discrete partial order offers a sufficiently rich structure to make it a viable model of spacetime for quantum gravity. If the deep structure of spacetime is that of a causal set, then the correspondence principle (with the spacetimes of general relativity) must be obeyed. Therefore, one of the requirements of this program is to establish that the causal set structure is in fact, not just in principle, fully consistent with our macroscopic notion of spacetime as a Lorentzian manifold. An important component of any such 'manifold test' is the ability to find embeddings of causal sets into Lorentzian manifolds.

  16. 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

  17. 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.

  18. 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.

  19. 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)

  20. 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.

  1. 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

  2. A security architecture for health information networks.

    PubMed

    Kailar, Rajashekar; Muralidhar, Vinod

    2007-10-11

    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.

  3. Frequency set on systems

    NASA Astrophysics Data System (ADS)

    Wilby, W. A.; Brett, A. R. H.

    Frequency set on techniques used in ECM applications include repeater jammers, frequency memory loops (RF and optical), coherent digital RF memories, and closed loop VCO set on systems. Closed loop frequency set on systems using analog phase and frequency locking are considered to have a number of cost and performance advantages. Their performance is discussed in terms of frequency accuracy, bandwidth, locking time, stability, and simultaneous signals. Some experimental results are presented which show typical locking performance. Future ECM systems might require a response to very short pulses. Acoustooptic and fiber-optic pulse stretching techniques can be used to meet such requirements.

  4. Setting standards: Legislative proposals

    SciTech Connect

    Pontius, F.W.

    1995-11-01

    This article, second of a two-part series examining the standard-setting process reviews legislative proposals that would change the way drinking water standards are set. How drinking water standards should be set and which contaminants should be regulated is a central issue for Safe Drinking Water Act (SDWA) reauthorization. Suggested amendments to the standard-setting provisions of the SDWA cover a broad spectrum of issues. In general, environmental groups argue that standards are not strict enough and that greater consideration should be given to sensitive subpopulations. Others note that the high costs associated with meeting increasingly strict standards are not justified in light of the uncertain and sometimes nonexistent incremental benefits.

  5. 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 ...

  6. 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…

  7. Controllability of complex networks.

    PubMed

    Liu, Yang-Yu; Slotine, Jean-Jacques; Barabási, Albert-László

    2011-05-12

    The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system's entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network's degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.

  8. 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.

  9. 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.

  10. Setting conservation priorities.

    PubMed

    Wilson, Kerrie A; Carwardine, Josie; Possingham, Hugh P

    2009-04-01

    A generic framework for setting conservation priorities based on the principles of classic decision theory is provided. This framework encapsulates the key elements of any problem, including the objective, the constraints, and knowledge of the system. Within the context of this framework the broad array of approaches for setting conservation priorities are reviewed. While some approaches prioritize assets or locations for conservation investment, it is concluded here that prioritization is incomplete without consideration of the conservation actions required to conserve the assets at particular locations. The challenges associated with prioritizing investments through time in the face of threats (and also spatially and temporally heterogeneous costs) can be aided by proper problem definition. Using the authors' general framework for setting conservation priorities, multiple criteria can be rationally integrated and where, how, and when to invest conservation resources can be scheduled. Trade-offs are unavoidable in priority setting when there are multiple considerations, and budgets are almost always finite. The authors discuss how trade-offs, risks, uncertainty, feedbacks, and learning can be explicitly evaluated within their generic framework for setting conservation priorities. Finally, they suggest ways that current priority-setting approaches may be improved.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. Network cosmology.

    PubMed

    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.

  16. Set Equation Transformation System.

    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

  17. 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.

  18. FTA Basic Event & Cut Set Ranking.

    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

  19. 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.

  20. 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…

  1. A Security Architecture for Health Information Networks

    PubMed Central

    Kailar, Rajashekar

    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

  2. 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…

  3. Group Goal Setting

    ERIC Educational Resources Information Center

    Sparks, Dennis C.

    1978-01-01

    Action goal setting uses power of peer influence in a healthy and constructive manner, and provides appropriate follow-up for many counseling and classroom activities. This process could help individuals of all ages to take more control over their behavior and create life-styles congruent with their abilities, interests, and values. (Author)

  4. 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…

  5. 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.

  6. 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…

  7. 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

  8. 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.

  9. 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…

  10. 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.

  11. Keyworth urges setting priorities

    NASA Astrophysics Data System (ADS)

    A strong advocate of scientists setting priorities within their disciplines, George A. Keyworth, II, President Reagan's science advisor and director of the Office of Science and Technology Policy, recently offered three possible consequences if such priorities are not set.‘I'm especially worried about the continued inability—or unwillingness—of the science community to agree among themselves about priorities—or to abide by their decisions when they can agree,’ he said [emphasis his]. ‘I wouldn't think it necessary that I remind them that these are tough times. I'll add that for anyone depending on federal funding, they're going to remain tough, times for quite a while,’ Keyworth told the American Physical Society at its mid-April meeting in Baltimore, Md.

  12. Setting mastery learning standards.

    PubMed

    Yudkowsky, Rachel; Park, Yoon Soo; Lineberry, Matthew; Knox, Aaron; Ritter, E Matthew

    2015-11-01

    Mastery learning is an instructional approach in which educational progress is based on demonstrated performance, not curricular time. Learners practice and retest repeatedly until they reach a designated mastery level; the final level of achievement is the same for all, although time to mastery may vary. Given the unique properties of mastery learning assessments, a thoughtful approach to establishing the performance levels and metrics that determine when a learner has demonstrated mastery is essential.Standard-setting procedures require modification when used for mastery learning settings in health care, particularly regarding the use of evidence-based performance data, the determination of appropriate benchmark or comparison groups, and consideration of patient safety consequences. Information about learner outcomes and past performance data of learners successful at the subsequent level of training can be more helpful than traditional information about test performance of past examinees. The marginally competent "borderline student" or "borderline group" referenced in traditional item-based and examinee-based procedures will generally need to be redefined in mastery settings. Patient safety considerations support conjunctive standards for key knowledge and skill subdomains and for items that have an impact on clinical outcomes. Finally, traditional psychometric indices used to evaluate the quality of standards do not necessarily reflect critical measurement properties of mastery assessments. Mastery learning and testing are essential to the achievement and assessment of entrustable professional activities and residency milestones. With careful attention, sound mastery standard-setting procedures can provide an essential step toward improving the effectiveness of health professions education, patient safety, and patient care. PMID:26375263

  13. 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.

  14. Gene set enrichment analysis.

    PubMed

    Tilford, Charles A; Siemers, Nathan O

    2009-01-01

    Set enrichment analytical methods have become commonplace tools applied to the analysis and interpretation of biological data. The statistical techniques are used to identify categorical biases within lists of genes, proteins, or metabolites. The goal is to discover the shared functions or properties of the biological items represented within the lists. Application of these methods can provide great biological insight, including the discovery of participation in the same biological activity or pathway, shared interacting genes or regulators, common cellular compartmentalization, or association with disease. The methods require ordered or unordered lists of biological items as input, understanding of the reference set from which the lists were selected, categorical classifiers describing the items, and a statistical algorithm to assess bias of each classifier. Due to the complexity of most algorithms and the number of calculations performed, computer software is almost always used for execution of the algorithm, as well as for presentation of the results. This chapter will provide an overview of the statistical methods used to perform an enrichment analysis. Guidelines for assembly of the requisite information will be presented, with a focus on careful definition of the sets used by the statistical algorithms. The need for multiple test correction when working with large libraries of classifiers is emphasized, and we outline several options for performing the corrections. Finally, interpreting the results of such analysis will be discussed along with examples of recent research utilizing the techniques.

  15. Observability of Neuronal Network Motifs

    PubMed Central

    Whalen, Andrew J.; Brennan, Sean N.; Sauer, Timothy D.; Schiff, Steven J.

    2014-01-01

    We quantify observability in small (3 node) neuronal networks as a function of 1) the connection topology and symmetry, 2) the measured nodes, and 3) the nodal dynamics (linear and nonlinear). We find that typical observability metrics for 3 neuron motifs range over several orders of magnitude, depending upon topology, and for motifs containing symmetry the network observability decreases when observing from particularly confounded nodes. Nonlinearities in the nodal equations generally decrease the average network observability and full network information becomes available only in limited regions of the system phase space. Our findings demonstrate that such networks are partially observable, and suggest their potential efficacy in reconstructing network dynamics from limited measurement data. How well such strategies can be used to reconstruct and control network dynamics in experimental settings is a subject for future experimental work. PMID:25909092

  16. 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.

  17. 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.

  18. Ranking Information in Networks

    NASA Astrophysics Data System (ADS)

    Eliassi-Rad, Tina; Henderson, Keith

    Given a network, we are interested in ranking sets of nodes that score highest on user-specified criteria. For instance in graphs from bibliographic data (e.g. PubMed), we would like to discover sets of authors with expertise in a wide range of disciplines. We present this ranking task as a Top-K problem; utilize fixed-memory heuristic search; and present performance of both the serial and distributed search algorithms on synthetic and real-world data sets.

  19. 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…

  20. 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

  1. 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.

  2. Telemedicine in educational settings.

    PubMed

    Newton, Heather

    The use of telemedicine to enhance patient care is well documented in the literature (Currell et al 2001); however, its use in educational settings requires further exploration. Technological advances in electronic communication have been the catalyst for enabling the transmission and storage of large volumes of data. This, in turn, has allowed still and video images to be used for clinical consultation and the advancement of healthcare professionals' knowledge and skills. This article discusses the use of telemedicine in healthcare practices and explores its value as an educational tool, particularly in the field of wound care.

  3. 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)

  4. 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.

  5. 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.

  6. Network science.

    PubMed

    Barabási, Albert-László

    2013-03-28

    Professor Barabási's talk described how the tools of network science can help understand the Web's structure, development and weaknesses. The Web is an information network, in which the nodes are documents (at the time of writing over one trillion of them), connected by links. Other well-known network structures include the Internet, a physical network where the nodes are routers and the links are physical connections, and organizations, where the nodes are people and the links represent communications.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. Integrative Network Biology: Graph Prototyping for Co-Expression Cancer Networks

    PubMed Central

    Kugler, Karl G.; Mueller, Laurin A. J.; Graber, Armin; Dehmer, Matthias

    2011-01-01

    Network-based analysis has been proven useful in biologically-oriented areas, e.g., to explore the dynamics and complexity of biological networks. Investigating a set of networks allows deriving general knowledge about the underlying topological and functional properties. The integrative analysis of networks typically combines networks from different studies that investigate the same or similar research questions. In order to perform an integrative analysis it is often necessary to compare the properties of matching edges across the data set. This identification of common edges is often burdensome and computational intensive. Here, we present an approach that is different from inferring a new network based on common features. Instead, we select one network as a graph prototype, which then represents a set of comparable network objects, as it has the least average distance to all other networks in the same set. We demonstrate the usefulness of the graph prototyping approach on a set of prostate cancer networks and a set of corresponding benign networks. We further show that the distances within the cancer group and the benign group are statistically different depending on the utilized distance measure. PMID:21829532

  12. Tool setting device

    DOEpatents

    Brown, Raymond J.

    1977-01-01

    The present invention relates to a tool setting device for use with numerically controlled machine tools, such as lathes and milling machines. A reference position of the machine tool relative to the workpiece along both the X and Y axes is utilized by the control circuit for driving the tool through its program. This reference position is determined for both axes by displacing a single linear variable displacement transducer (LVDT) with the machine tool through a T-shaped pivotal bar. The use of the T-shaped bar allows the cutting tool to be moved sequentially in the X or Y direction for indicating the actual position of the machine tool relative to the predetermined desired position in the numerical control circuit by using a single LVDT.

  13. Attractor Metabolic Networks

    PubMed Central

    De la Fuente, Ildefonso M.; Cortes, Jesus M.; Pelta, David A.; Veguillas, Juan

    2013-01-01

    Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity. Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network. Conclusions/Significance We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency

  14. Control efficacy of complex networks

    NASA Astrophysics Data System (ADS)

    Gao, Xin-Dong; Wang, Wen-Xu; Lai, Ying-Cheng

    2016-06-01

    Controlling complex networks has become a forefront research area in network science and engineering. Recent efforts have led to theoretical frameworks of controllability to fully control a network through steering a minimum set of driver nodes. However, in realistic situations not every node is accessible or can be externally driven, raising the fundamental issue of control efficacy: if driving signals are applied to an arbitrary subset of nodes, how many other nodes can be controlled? We develop a framework to determine the control efficacy for undirected networks of arbitrary topology. Mathematically, based on non-singular transformation, we prove a theorem to determine rigorously the control efficacy of the network and to identify the nodes that can be controlled for any given driver nodes. Physically, we develop the picture of diffusion that views the control process as a signal diffused from input signals to the set of controllable nodes. The combination of mathematical theory and physical reasoning allows us not only to determine the control efficacy for model complex networks and a large number of empirical networks, but also to uncover phenomena in network control, e.g., hub nodes in general possess lower control centrality than an average node in undirected networks.

  15. Control efficacy of complex networks

    PubMed Central

    Gao, Xin-Dong; Wang, Wen-Xu; Lai, Ying-Cheng

    2016-01-01

    Controlling complex networks has become a forefront research area in network science and engineering. Recent efforts have led to theoretical frameworks of controllability to fully control a network through steering a minimum set of driver nodes. However, in realistic situations not every node is accessible or can be externally driven, raising the fundamental issue of control efficacy: if driving signals are applied to an arbitrary subset of nodes, how many other nodes can be controlled? We develop a framework to determine the control efficacy for undirected networks of arbitrary topology. Mathematically, based on non-singular transformation, we prove a theorem to determine rigorously the control efficacy of the network and to identify the nodes that can be controlled for any given driver nodes. Physically, we develop the picture of diffusion that views the control process as a signal diffused from input signals to the set of controllable nodes. The combination of mathematical theory and physical reasoning allows us not only to determine the control efficacy for model complex networks and a large number of empirical networks, but also to uncover phenomena in network control, e.g., hub nodes in general possess lower control centrality than an average node in undirected networks. PMID:27324438

  16. Superelastic networks

    SciTech Connect

    Obukhov, S.P.; Rubinstein, M.; Colby, R.H.

    1993-12-31

    This paper discusses the elastic modulus, swelling, and deswelling behavior of networks as a function of their concentration and the preparation state. Based on these results, the authors expect that networks prepared by crosslinking long chains at low concentration, followed by removal of solvent, will have superelastic properties - the deswollen networks will have low modulus and will be capable of stretching by enormous amounts without breaking. This is because deswelling introduces only temporary entanglements. These temporary entanglements change the static configuration of the network strands. The authors discuss the non-Gaussian nature of these strands and the linear viscoelastic response of the superelastic networks.

  17. Vulnerability of network of networks

    NASA Astrophysics Data System (ADS)

    Havlin, S.; Kenett, D. Y.; Bashan, A.; Gao, J.; Stanley, H. E.

    2014-10-01

    Our dependence on networks - be they infrastructure, economic, social or others - leaves us prone to crises caused by the vulnerabilities of these networks. There is a great need to develop new methods to protect infrastructure networks and prevent cascade of failures (especially in cases of coupled networks). Terrorist attacks on transportation networks have traumatized modern societies. With a single blast, it has become possible to paralyze airline traffic, electric power supply, ground transportation or Internet communication. How, and at which cost can one restructure the network such that it will become more robust against malicious attacks? The gradual increase in attacks on the networks society depends on - Internet, mobile phone, transportation, air travel, banking, etc. - emphasize the need to develop new strategies to protect and defend these crucial networks of communication and infrastructure networks. One example is the threat of liquid explosives a few years ago, which completely shut down air travel for days, and has created extreme changes in regulations. Such threats and dangers warrant the need for new tools and strategies to defend critical infrastructure. In this paper we review recent advances in the theoretical understanding of the vulnerabilities of interdependent networks with and without spatial embedding, attack strategies and their affect on such networks of networks as well as recently developed strategies to optimize and repair failures caused by such attacks.

  18. Multimedia telehomecare system using standard TV set.

    PubMed

    Guillén, S; Arredondo, M T; Traver, V; García, J M; Fernández, C

    2002-12-01

    Nowadays, there are a very large number of patients that need specific health support at home. The deployment of broadband communication networks is making feasible the provision of home care services with a proper quality of service. This paper presents a telehomecare multimedia platform that runs over integrated services digital network and internet protocol using videoconferencing standards H.320 and H.323, and standard TV set for patient interaction. This platform allows online remote monitoring: ECG, heart sound, blood pressure. Usability, affordability, and interoperability were considered for the design and development of its hardware and software components. A first evaluation of technical and usability aspects were carried forward with 52 patients of a private clinic and 10 students in the University. Results show a high rate (mean = 4.33, standard deviation--SD = 1.63 in a five-points Likert scale) in the global perception of users on the quality of images, voice, and feeling of virtual presence.

  19. Multimedia telehomecare system using standard TV set.

    PubMed

    Guillén, S; Arredondo, M T; Traver, V; García, J M; Fernández, C

    2002-12-01

    Nowadays, there are a very large number of patients that need specific health support at home. The deployment of broadband communication networks is making feasible the provision of home care services with a proper quality of service. This paper presents a telehomecare multimedia platform that runs over integrated services digital network and internet protocol using videoconferencing standards H.320 and H.323, and standard TV set for patient interaction. This platform allows online remote monitoring: ECG, heart sound, blood pressure. Usability, affordability, and interoperability were considered for the design and development of its hardware and software components. A first evaluation of technical and usability aspects were carried forward with 52 patients of a private clinic and 10 students in the University. Results show a high rate (mean = 4.33, standard deviation--SD = 1.63 in a five-points Likert scale) in the global perception of users on the quality of images, voice, and feeling of virtual presence. PMID:12542238

  20. Associative memory in phasing neuron networks

    SciTech Connect

    Nair, Niketh S; Bochove, Erik J.; Braiman, Yehuda

    2014-01-01

    We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

  1. Neural-Network Object-Recognition Program

    NASA Technical Reports Server (NTRS)

    Spirkovska, L.; Reid, M. B.

    1993-01-01

    HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

  2. Optimizing Nutrient Uptake in Biological Transport Networks

    NASA Astrophysics Data System (ADS)

    Ronellenfitsch, Henrik; Katifori, Eleni

    2013-03-01

    Many biological systems employ complex networks of vascular tubes to facilitate transport of solute nutrients, examples include the vascular system of plants (phloem), some fungi, and the slime-mold Physarum. It is believed that such networks are optimized through evolution for carrying out their designated task. We propose a set of hydrodynamic governing equations for solute transport in a complex network, and obtain the optimal network architecture for various classes of optimizing functionals. We finally discuss the topological properties and statistical mechanics of the resulting complex networks, and examine correspondence of the obtained networks to those found in actual biological systems.

  3. On Tree-Based Phylogenetic Networks.

    PubMed

    Zhang, Louxin

    2016-07-01

    A large class of phylogenetic networks can be obtained from trees by the addition of horizontal edges between the tree edges. These networks are called tree-based networks. We present a simple necessary and sufficient condition for tree-based networks and prove that a universal tree-based network exists for any number of taxa that contains as its base every phylogenetic tree on the same set of taxa. This answers two problems posted by Francis and Steel recently. A byproduct is a computer program for generating random binary phylogenetic networks under the uniform distribution model.

  4. Telemedicine in clinical setting

    PubMed Central

    Zhang, Xiao-Ying; Zhang, Peiying

    2016-01-01

    The telemedicine department of a hospital is an emerging branch in upcoming hospitals and may become an essential component of every hospital. It basically utilizes the information technologies along with telecommunication systems in order to provide clinical care and assistance. Furthermore, the branch of telemedicine offers significant opportunities for the process of developmental freedom from illness, early death, and preventable diseases. It advances development by providing relevant drugs and the necessary care aimed to alleviate patient suffering. It is also beneficial for patients in rural remote areas who usually do not have adequate access to advanced hospitals. Telemedicine in these remote areas allows for timely treatment of emergency cases. Thus, it contributes towards remote emergency critical care in order to save lives in crucial cases. Additionally, the emerging advances have now enabled telemedicine to transfer large amounts of clinical informatics data including images, and test reports to the specifically specialized health professionals in some serious cases. However, as in the case of many emerging technologies, organizing information and understanding the field has significant challenges. The present review article aimed to discuss important aspects of the field with regard to the better management of patients in clinical settings. PMID:27703503

  5. Computer Networks As Social Networks

    NASA Astrophysics Data System (ADS)

    Wellman, Barry

    2001-09-01

    Computer networks are inherently social networks, linking people, organizations, and knowledge. They are social institutions that should not be studied in isolation but as integrated into everyday lives. The proliferation of computer networks has facilitated a deemphasis on group solidarities at work and in the community and afforded a turn to networked societies that are loosely bounded and sparsely knit. The Internet increases people's social capital, increasing contact with friends and relatives who live nearby and far away. New tools must be developed to help people navigate and find knowledge in complex, fragmented, networked societies.

  6. Network Monitor and Control of Disruption-Tolerant Networks

    NASA Technical Reports Server (NTRS)

    Torgerson, J. Leigh

    2014-01-01

    For nearly a decade, NASA and many researchers in the international community have been developing Internet-like protocols that allow for automated network operations in networks where the individual links between nodes are only sporadically connected. A family of Disruption-Tolerant Networking (DTN) protocols has been developed, and many are reaching CCSDS Blue Book status. A NASA version of DTN known as the Interplanetary Overlay Network (ION) has been flight-tested on the EPOXI spacecraft and ION is currently being tested on the International Space Station. Experience has shown that in order for a DTN service-provider to set up a large scale multi-node network, a number of network monitor and control technologies need to be fielded as well as the basic DTN protocols. The NASA DTN program is developing a standardized means of querying a DTN node to ascertain its operational status, known as the DTN Management Protocol (DTNMP), and the program has developed some prototypes of DTNMP software. While DTNMP is a necessary component, it is not sufficient to accomplish Network Monitor and Control of a DTN network. JPL is developing a suite of tools that provide for network visualization, performance monitoring and ION node control software. This suite of network monitor and control tools complements the GSFC and APL-developed DTN MP software, and the combined package can form the basis for flight operations using DTN.

  7. An efficient quantum scheme for Private Set Intersection

    NASA Astrophysics Data System (ADS)

    Shi, Run-hua; Mu, Yi; Zhong, Hong; Cui, Jie; Zhang, Shun

    2016-01-01

    Private Set Intersection allows a client to privately compute set intersection with the collaboration of the server, which is one of the most fundamental and key problems within the multiparty collaborative computation of protecting the privacy of the parties. In this paper, we first present a cheat-sensitive quantum scheme for Private Set Intersection. Compared with classical schemes, our scheme has lower communication complexity, which is independent of the size of the server's set. Therefore, it is very suitable for big data services in Cloud or large-scale client-server networks.

  8. Controlling synchronous patterns in complex networks.

    PubMed

    Lin, Weijie; Fan, Huawei; Wang, Ying; Ying, Heping; Wang, Xingang

    2016-04-01

    Although the set of permutation symmetries of a complex network could be very large, few of them give rise to stable synchronous patterns. Here we present a general framework and develop techniques for controlling synchronization patterns in complex network of coupled chaotic oscillators. Specifically, according to the network permutation symmetry, we design a small-size and weighted network, namely the control network, and use it to control the large-size complex network by means of pinning coupling. We argue mathematically that for any of the network symmetries, there always exists a critical pinning strength beyond which the unstable synchronous pattern associated to this symmetry can be stabilized. The feasibility of the control method is verified by numerical simulations of both artificial and real-world networks and demonstrated experimentally in systems of coupled chaotic circuits. Our studies show the controllability of synchronous patterns in complex networks of coupled chaotic oscillators.

  9. Risk and reliability assessment for telecommunications networks

    SciTech Connect

    Wyss, G.D.; Schriner, H.K.; Gaylor, T.R.

    1996-08-01

    Sandia National Laboratories has assembled an interdisciplinary team to explore the applicability of probabilistic logic modeling (PLM) techniques to model network reliability for a wide variety of communications network architectures. The authors have found that the reliability and failure modes of current generation network technologies can be effectively modeled using fault tree PLM techniques. They have developed a ``plug-and-play`` fault tree analysis methodology that can be used to model connectivity and the provision of network services in a wide variety of current generation network architectures. They have also developed an efficient search algorithm that can be used to determine the minimal cut sets of an arbitrarily-interconnected (non-hierarchical) network without the construction of a fault tree model. This paper provides an overview of these modeling techniques and describes how they are applied to networks that exhibit hybrid network structures (i.e., a network in which some areas are hierarchical and some areas are not hierarchical).

  10. Leadership in School Networks: Findings from the Networked Learning Communities Programme

    ERIC Educational Resources Information Center

    Jopling, Michael; Spender, Barbara

    2006-01-01

    The Networked Learning Community (NLC) programme has been a major research and development activity of the National College of School Leadership (NCSL). One hundred and four voluntary, funded school networks were set up following a process of bidding and selection operated by a core NCSL team, the Networked Learning Group (NLG). A second tranche…

  11. Temporal network structures controlling disease spreading.

    PubMed

    Holme, Petter

    2016-08-01

    We investigate disease spreading on eight empirical data sets of human contacts (mostly proximity networks recording who is close to whom, at what time). We compare three levels of representations of these data sets: temporal networks, static networks, and a fully connected topology. We notice that the difference between the static and fully connected networks-with respect to time to extinction and average outbreak size-is smaller than between the temporal and static topologies. This suggests that, for these data sets, temporal structures influence disease spreading more than static-network structures. To explain the details in the differences between the representations, we use 32 network measures. This study concurs that long-time temporal structures, like the turnover of nodes and links, are the most important for the spreading dynamics. PMID:27627315

  12. Temporal network structures controlling disease spreading.

    PubMed

    Holme, Petter

    2016-08-01

    We investigate disease spreading on eight empirical data sets of human contacts (mostly proximity networks recording who is close to whom, at what time). We compare three levels of representations of these data sets: temporal networks, static networks, and a fully connected topology. We notice that the difference between the static and fully connected networks-with respect to time to extinction and average outbreak size-is smaller than between the temporal and static topologies. This suggests that, for these data sets, temporal structures influence disease spreading more than static-network structures. To explain the details in the differences between the representations, we use 32 network measures. This study concurs that long-time temporal structures, like the turnover of nodes and links, are the most important for the spreading dynamics.

  13. Innovation Networks

    NASA Astrophysics Data System (ADS)

    Pyka, Andreas; Scharnhorst, Andrea

    The idea for this book started when we organized a topical workshop entitled "Innovation Networks - New Approaches in Modeling and Analyzing" (held in Augsburg, Germany in October 2005), under the auspices of Exystence, a network of excellence funded in the European Union's Fifth Framework Program. Unlike other conferences on innovation and networks, however, this workshop brought together scientists from economics, sociology, communication science, science and technology studies, and physics. With this book we aim to build further on a bridge connecting the bodies of knowledge on networks in economics, the social sciences and, more recently, statistical physics.

  14. Deploying temporary networks for upscaling of sparse network stations

    NASA Astrophysics Data System (ADS)

    Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

    2016-10-01

    Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

  15. Network-Based Identification of Biomarkers Coexpressed with Multiple Pathways

    PubMed Central

    Guo, Nancy Lan; Wan, Ying-Wooi

    2014-01-01

    Unraveling complex molecular interactions and networks and incorporating clinical information in modeling will present a paradigm shift in molecular medicine. Embedding biological relevance via modeling molecular networks and pathways has become increasingly important for biomarker identification in cancer susceptibility and metastasis studies. Here, we give a comprehensive overview of computational methods used for biomarker identification, and provide a performance comparison of several network models used in studies of cancer susceptibility, disease progression, and prognostication. Specifically, we evaluated implication networks, Boolean networks, Bayesian networks, and Pearson’s correlation networks in constructing gene coexpression networks for identifying lung cancer diagnostic and prognostic biomarkers. The results show that implication networks, implemented in Genet package, identified sets of biomarkers that generated an accurate prediction of lung cancer risk and metastases; meanwhile, implication networks revealed more biologically relevant molecular interactions than Boolean networks, Bayesian networks, and Pearson’s correlation networks when evaluated with MSigDB database. PMID:25392692

  16. A Set of Questions, A Question of Sets.

    ERIC Educational Resources Information Center

    Mathematics in School, 1985

    1985-01-01

    Two versions of a page of exercises using set ideas are presented, one in plain language and one in technical language. Some questions and answers about the appropriateness of set terminology and symbols are then given. (MNS)

  17. A neural network prototyping package within IRAF

    NASA Technical Reports Server (NTRS)

    Bazell, D.; Bankman, I.

    1992-01-01

    We outline our plans for incorporating a Neural Network Prototyping Package into the IRAF environment. The package we are developing will allow the user to choose between different types of networks and to specify the details of the particular architecture chosen. Neural networks consist of a highly interconnected set of simple processing units. The strengths of the connections between units are determined by weights which are adaptively set as the network 'learns'. In some cases, learning can be a separate phase of the user cycle of the network while in other cases the network learns continuously. Neural networks have been found to be very useful in pattern recognition and image processing applications. They can form very general 'decision boundaries' to differentiate between objects in pattern space and they can be used for associative recall of patterns based on partial cures and for adaptive filtering. We discuss the different architectures we plan to use and give examples of what they can do.

  18. The network of concepts in written texts

    NASA Astrophysics Data System (ADS)

    Caldeira, S. M. G.; Petit Lobão, T. C.; Andrade, R. F. S.; Neme, A.; Miranda, J. G. V.

    2006-02-01

    Complex network theory is used to investigate the structure of meaningful concepts in written texts of individual authors. Networks have been constructed after a two phase filtering, where words with less meaning contents are eliminated and all remaining words are set to their canonical form, without any number, gender or time flexion. Each sentence in the text is added to the network as a clique. A large number of written texts have been scrutinised, and it is found that texts have small-world as well as scale-free structures. The growth process of these networks has also been investigated, and a universal evolution of network quantifiers have been found among the set of texts written by distinct authors. Further analyses, based on shuffling procedures taken either on the texts or on the constructed networks, provide hints on the role played by the word frequency and sentence length distributions to the network structure.

  19. Re-Setting Music Education's "Default Settings"

    ERIC Educational Resources Information Center

    Regelski, Thomas A.

    2013-01-01

    This paper explores the effects and problems of one highly influential default setting of the "normal style template" of music education and proposes some alternatives. These do not require abandoning all traditional templates for school music. But re-setting the default settings does depend on reconsidering the promised function of…

  20. Spin foam models as energetic causal sets

    NASA Astrophysics Data System (ADS)

    Cortês, Marina; Smolin, Lee

    2016-04-01

    Energetic causal sets are causal sets endowed by a flow of energy-momentum between causally related events. These incorporate a novel mechanism for the emergence of space-time from causal relations [M. Cortês and L. Smolin, Phys. Rev. D 90, 084007 (2014); Phys. Rev. D 90, 044035 (2014)]. Here we construct a spin foam model which is also an energetic causal set model. This model is closely related to the model introduced in parallel by Wolfgang Wieland in [Classical Quantum Gravity 32, 015016 (2015)]. What makes a spin foam model also an energetic causal set is Wieland's identification of new degrees of freedom analogous to momenta, conserved at events (or four-simplices), whose norms are not mass, but the volume of tetrahedra. This realizes the torsion constraints, which are missing in previous spin foam models, and are needed to relate the connection dynamics to those of the metric, as in general relativity. This identification makes it possible to apply the new mechanism for the emergence of space-time to a spin foam model. Our formulation also makes use of Markopoulou's causal formulation of spin foams [arXiv:gr-qc/9704013]. These are generated by evolving spin networks with dual Pachner moves. This endows the spin foam history with causal structure given by a partial ordering of the events which are dual to four-simplices.

  1. Network Directory.

    ERIC Educational Resources Information Center

    Butler, Jocelyn A.; Batey, Anne

    This Network Directory is part of the effort by the Northwest Regional Educational Laboratory (NWREL) School Improvement Program to promote communication among educational professionals about school improvement. Specifically, the directory is designed to provide information for networking among schools involved in systematic, long-term…

  2. Diabetes network.

    PubMed

    2016-07-01

    Diabetes UK has launched a network of information and support for commissioning and improvement in diabetes care. The network is free to join and offers monthly updates on good practice from around the UK, a forum for sharing ideas and learning, and access to Diabetes UK resources. PMID:27369708

  3. Policy issues in interconnecting networks

    NASA Technical Reports Server (NTRS)

    Leiner, Barry M.

    1989-01-01

    To support the activities of the Federal Research Coordinating Committee (FRICC) in creating an interconnected set of networks to serve the research community, two workshops were held to address the technical support of policy issues that arise when interconnecting such networks. The workshops addressed the required and feasible technologies and architectures that could be used to satisfy the desired policies for interconnection. The results of the workshop are documented.

  4. Temporal networks

    NASA Astrophysics Data System (ADS)

    Holme, Petter; Saramäki, Jari

    2012-10-01

    A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via e-mail, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names-temporal graphs, evolving graphs, time-varying graphs, time-aggregated graphs, time-stamped graphs, dynamic networks, dynamic graphs, dynamical graphs, and so on. This review covers different fields where temporal graphs are considered

  5. Radial sets: interactive visual analysis of large overlapping sets.

    PubMed

    Alsallakh, Bilal; Aigner, Wolfgang; Miksch, Silvia; Hauser, Helwig

    2013-12-01

    In many applications, data tables contain multi-valued attributes that often store the memberships of the table entities to multiple sets such as which languages a person masters, which skills an applicant documents, or which features a product comes with. With a growing number of entities, the resulting element-set membership matrix becomes very rich of information about how these sets overlap. Many analysis tasks targeted at set-typed data are concerned with these overlaps as salient features of such data. This paper presents Radial Sets, a novel visual technique to analyze set memberships for a large number of elements. Our technique uses frequency-based representations to enable quickly finding and analyzing different kinds of overlaps between the sets, and relating these overlaps to other attributes of the table entities. Furthermore, it enables various interactions to select elements of interest, find out if they are over-represented in specific sets or overlaps, and if they exhibit a different distribution for a specific attribute compared to the rest of the elements. These interactions allow formulating highly-expressive visual queries on the elements in terms of their set memberships and attribute values. As we demonstrate via two usage scenarios, Radial Sets enable revealing and analyzing a multitude of overlapping patterns between large sets, beyond the limits of state-of-the-art techniques. PMID:24051816

  6. Policies for implementing network firewalls

    SciTech Connect

    Brown, C.D.

    1994-05-01

    Corporate networks are frequently protected by {open_quotes}firewalls{close_quotes} or gateway systems that control access to/from other networks, e.g., the Internet, in order to reduce the network`s vulnerability to hackers and other unauthorized access. Firewalls typically limit access to particular network nodes and application protocols, and they often perform special authentication and authorization functions. One of the difficult issues associated with network firewalls is determining which applications should be permitted through the firewall. For example, many networks permit the exchange of electronic mail with the outside but do not permit file access to be initiated by outside users, as this might allow outside users to access sensitive data or to surreptitiously modify data or programs (e.g., to intall Trojan Horse software). However, if access through firewalls is severely restricted, legitimate network users may find it difficult or impossible to collaborate with outside users and to share data. Some of the most serious issues regarding firewalls involve setting policies for firewalls with the goal of achieving an acceptable balance between the need for greater functionality and the associated risks. Two common firewall implementation techniques, screening routers and application gateways, are discussed below, followed by some common policies implemented by network firewalls.

  7. MOTIVATION: Goals and Goal Setting

    ERIC Educational Resources Information Center

    Stratton, Richard K.

    2005-01-01

    Goal setting has great impact on a team's performance. Goals enable a team to synchronize their efforts to achieve success. In this article, the author talks about goals and goal setting. This articles complements Domain 5--Teaching and Communication (p.14) and discusses one of the benchmarks listed therein: "Teach the goal setting process and…

  8. Motivating Athletes Through Goal Setting.

    ERIC Educational Resources Information Center

    Weinberg, Robert S.

    1982-01-01

    This article provides some guidelines for coaches and athletes for goal setting strategies: (1) set realistic goals; (2) write down goals, so that they are remembered and understood by all persons involved; (3) set measurable objective goals; and (4) have coach act as facilitator. (CJ)

  9. Fuzzy Sets and Mathematical Education.

    ERIC Educational Resources Information Center

    Alsina, C.; Trillas, E.

    1991-01-01

    Presents the concept of "Fuzzy Sets" and gives some ideas for its potential interest in mathematics education. Defines what a Fuzzy Set is, describes why we need to teach fuzziness, gives some examples of fuzzy questions, and offers some examples of activities related to fuzzy sets. (MDH)

  10. Control of collective network chaos

    NASA Astrophysics Data System (ADS)

    Wagemakers, Alexandre; Barreto, Ernest; Sanjuán, Miguel A. F.; So, Paul

    2014-06-01

    Under certain conditions, the collective behavior of a large globally-coupled heterogeneous network of coupled oscillators, as quantified by the macroscopic mean field or order parameter, can exhibit low-dimensional chaotic behavior. Recent advances describe how a small set of "reduced" ordinary differential equations can be derived that captures this mean field behavior. Here, we show that chaos control algorithms designed using the reduced equations can be successfully applied to imperfect realizations of the full network. To systematically study the effectiveness of this technique, we measure the quality of control as we relax conditions that are required for the strict accuracy of the reduced equations, and hence, the controller. Although the effects are network-dependent, we show that the method is effective for surprisingly small networks, for modest departures from global coupling, and even with mild inaccuracy in the estimate of network heterogeneity.

  11. Control of collective network chaos

    SciTech Connect

    Wagemakers, Alexandre Sanjuán, Miguel A. F.

    2014-06-01

    Under certain conditions, the collective behavior of a large globally-coupled heterogeneous network of coupled oscillators, as quantified by the macroscopic mean field or order parameter, can exhibit low-dimensional chaotic behavior. Recent advances describe how a small set of “reduced” ordinary differential equations can be derived that captures this mean field behavior. Here, we show that chaos control algorithms designed using the reduced equations can be successfully applied to imperfect realizations of the full network. To systematically study the effectiveness of this technique, we measure the quality of control as we relax conditions that are required for the strict accuracy of the reduced equations, and hence, the controller. Although the effects are network-dependent, we show that the method is effective for surprisingly small networks, for modest departures from global coupling, and even with mild inaccuracy in the estimate of network heterogeneity.

  12. Composing Music with Complex Networks

    NASA Astrophysics Data System (ADS)

    Liu, Xiaofan; Tse, Chi K.; Small, Michael

    In this paper we study the network structure in music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurrences. We analyze sample compositions from Bach, Mozart, Chopin, as well as other types of music including Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. Power-law exponents of degree distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be created by using a biased random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. The newly created music from complex networks will be played in the presentation.

  13. Technological Networks

    NASA Astrophysics Data System (ADS)

    Mitra, Bivas

    The study of networks in the form of mathematical graph theory is one of the fundamental pillars of discrete mathematics. However, recent years have witnessed a substantial new movement in network research. The focus of the research is shifting away from the analysis of small graphs and the properties of individual vertices or edges to consideration of statistical properties of large scale networks. This new approach has been driven largely by the availability of technological networks like the Internet [12], World Wide Web network [2], etc. that allow us to gather and analyze data on a scale far larger than previously possible. At the same time, technological networks have evolved as a socio-technological system, as the concepts of social systems that are based on self-organization theory have become unified in technological networks [13]. In today’s society, we have a simple and universal access to great amounts of information and services. These information services are based upon the infrastructure of the Internet and the World Wide Web. The Internet is the system composed of ‘computers’ connected by cables or some other form of physical connections. Over this physical network, it is possible to exchange e-mails, transfer files, etc. On the other hand, the World Wide Web (commonly shortened to the Web) is a system of interlinked hypertext documents accessed via the Internet where nodes represent web pages and links represent hyperlinks between the pages. Peer-to-peer (P2P) networks [26] also have recently become a popular medium through which huge amounts of data can be shared. P2P file sharing systems, where files are searched and downloaded among peers without the help of central servers, have emerged as a major component of Internet traffic. An important advantage in P2P networks is that all clients provide resources, including bandwidth, storage space, and computing power. In this chapter, we discuss these technological networks in detail. The review

  14. Temporal stability of network partitions.

    PubMed

    Petri, Giovanni; Expert, Paul

    2014-08-01

    We present a method to find the best temporal partition at any time scale and rank the relevance of partitions found at different time scales. This method is based on random walkers coevolving with the network and as such constitutes a generalization of partition stability to the case of temporal networks. We show that, when applied to a toy model and real data sets, temporal stability uncovers structures that are persistent over meaningful time scales as well as important isolated events, making it an effective tool to study both abrupt changes and gradual evolution of a network mesoscopic structures.

  15. Women's connectivity in extreme networks.

    PubMed

    Manrique, Pedro; Cao, Zhenfeng; Gabriel, Andrew; Horgan, John; Gill, Paul; Qi, Hong; Restrepo, Elvira M; Johnson, Daniela; Wuchty, Stefan; Song, Chaoming; Johnson, Neil

    2016-06-01

    A popular stereotype is that women will play more minor roles than men as environments become more dangerous and aggressive. Our analysis of new longitudinal data sets from offline and online operational networks [for example, ISIS (Islamic State)] shows that although men dominate numerically, women emerge with superior network connectivity that can benefit the underlying system's robustness and survival. Our observations suggest new female-centric approaches that could be used to affect such networks. They also raise questions about how individual contributions in high-pressure systems are evaluated. PMID:27386564

  16. IGS Network Coordinator Report - 2002

    NASA Technical Reports Server (NTRS)

    Moore, Angelyn

    2004-01-01

    The IGS network is a set of permanent, continuously-operating, dual-frequency GPS stations operated by over 100 worldwide agencies. The dataset is pooled at IGS Data Centers for routine use by IGS Analysis Centers in creating precise IGS products, as well as free access by other analysts around the world. The IGS Central Bureau hosts the IGS Network Coordinator, who assures adherence to standards and provides information regarding the IGS network via the Central Bureau Information System website at http://igscb.jpl.nasa.gov.

  17. Temporal stability of network partitions.

    PubMed

    Petri, Giovanni; Expert, Paul

    2014-08-01

    We present a method to find the best temporal partition at any time scale and rank the relevance of partitions found at different time scales. This method is based on random walkers coevolving with the network and as such constitutes a generalization of partition stability to the case of temporal networks. We show that, when applied to a toy model and real data sets, temporal stability uncovers structures that are persistent over meaningful time scales as well as important isolated events, making it an effective tool to study both abrupt changes and gradual evolution of a network mesoscopic structures. PMID:25215787

  18. Sampling Networks from Their Posterior Predictive Distribution.

    PubMed

    Goyal, Ravi; De Gruttola, Victor; Blitzstein, Joseph

    2014-04-01

    Recent research indicates that knowledge about social networks can be leveraged to increase efficiency of interventions (Valente, 2012). However, in many settings, there exists considerable uncertainty regarding the structure of the network. This can render the estimation of potential effects of network-based interventions difficult, as providing appropriate guidance to select interventions often requires a representation of the whole network. In order to make use of the network property estimates to simulate the effect of interventions, it may be beneficial to sample networks from an estimated posterior predictive distribution, which can be specified using a wide range of models. Sampling networks from a posterior predictive distribution of network properties ensures that the uncertainty about network property parameters is adequately captured. The tendency for relationships among network properties to exhibit sharp thresholds has important implications for understanding global network topology in the presence of uncertainty; therefore, it is essential to account for uncertainty. We provide detail needed to sample networks for the specific network properties of degree distribution, mixing frequency, and clustering. Our methods to generate networks are demonstrated using simulated data and data from the National Longitudinal Study of Adolescent Health.

  19. Network Structure and City Size

    PubMed Central

    Levinson, David

    2012-01-01

    Network structure varies across cities. This variation may yield important knowledge about how the internal structure of the city affects its performance. This paper systematically compares a set of surface transportation network structure variables (connectivity, hierarchy, circuity, treeness, entropy, accessibility) across the 50 largest metropolitan areas in the United States. A set of scaling parameters are discovered to show how network size and structure vary with city size. These results suggest that larger cities are physically more inter-connected. Hypotheses are presented as to why this might obtain. This paper then consistently measures and ranks access to jobs across 50 US metropolitan areas. It uses that accessibility measure, along with network structure variables and city size to help explain journey-to-work time and auto mode share in those cities. A 1 percent increase in accessibility reduces average metropolitan commute times by about 90 seconds each way. A 1 percent increase in network connectivity reduces commute time by 0.1 percent. A 1 percent increase in accessibility results in a 0.0575 percent drop in auto mode share, while a 1 percent increase in treeness reduces auto mode share by 0.061 percent. Use of accessibility and network structure measures is important for planning and evaluating the performance of network investments and land use changes. PMID:22253764

  20. Multiprotocol label-switching network functional description

    NASA Astrophysics Data System (ADS)

    Owens, Kenneth R.; Kroculick, Joseph

    1999-11-01

    This paper integrates a functional transport and control layer network architecture for MPLS emphasizing Traffic Engineering concepts such as the specification and provisioning of end-to-end QoS service layer agreements. MPLS transport networks are provisioned considering administrator-defined policies on bandwidth allocation, security, and accounting techniques. The MPLS architecture consists of the transport and control layer networks. The transport layer network is concerned with configuration, packet forwarding, signaling, adaptation to higher layers, and support of higher layers. The control layer network is concerned with policy configuration, management, distribution, definitions, schemas, elements, settings, and enforcement.

  1. Modularity and community structure in networks.

    PubMed

    Newman, M E J

    2006-06-01

    Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure is one of the outstanding issues in the study of networked systems. One highly effective approach is the optimization of the quality function known as "modularity" over the possible divisions of a network. Here I show that the modularity can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which I call the modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times. I illustrate the method with applications to several published network data sets.

  2. Modularity and community structure in networks

    PubMed Central

    Newman, M. E. J.

    2006-01-01

    Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure is one of the outstanding issues in the study of networked systems. One highly effective approach is the optimization of the quality function known as “modularity” over the possible divisions of a network. Here I show that the modularity can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which I call the modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times. I illustrate the method with applications to several published network data sets. PMID:16723398

  3. Innovation network

    PubMed Central

    Acemoglu, Daron; Akcigit, Ufuk; Kerr, William R.

    2016-01-01

    Technological progress builds upon itself, with the expansion of invention in one domain propelling future work in linked fields. Our analysis uses 1.8 million US patents and their citation properties to map the innovation network and its strength. Past innovation network structures are calculated using citation patterns across technology classes during 1975–1994. The interaction of this preexisting network structure with patent growth in upstream technology fields has strong predictive power on future innovation after 1995. This pattern is consistent with the idea that when there is more past upstream innovation for a particular technology class to build on, then that technology class innovates more. PMID:27681628

  4. Supporting Advice Sharing for Technical Problems in Residential Settings

    ERIC Educational Resources Information Center

    Poole, Erika Shehan

    2010-01-01

    Visions of future computing in residential settings often come with assumptions of seamless, well-functioning, properly configured devices and network connectivity. In the near term, however, processes of setup, maintenance, and troubleshooting are fraught with difficulties; householders regularly report these tasks as confusing, frustrating, and…

  5. Straight monotonic embedding of data sets in Euclidean spaces.

    PubMed

    Courrieu, Pierre

    2002-12-01

    This paper presents a fast incremental algorithm for embedding data sets belonging to various topological spaces in Euclidean spaces. This is useful for networks whose input consists of non-Euclidean (possibly non-numerical) data, for the on-line computation of spatial maps in autonomous agent navigation problems, and for building internal representations from empirical similarity data. PMID:12425437

  6. Straight monotonic embedding of data sets in Euclidean spaces.

    PubMed

    Courrieu, Pierre

    2002-12-01

    This paper presents a fast incremental algorithm for embedding data sets belonging to various topological spaces in Euclidean spaces. This is useful for networks whose input consists of non-Euclidean (possibly non-numerical) data, for the on-line computation of spatial maps in autonomous agent navigation problems, and for building internal representations from empirical similarity data.

  7. Dissociating Stimulus-Set and Response-Set in the Context of Task-Set Switching

    ERIC Educational Resources Information Center

    Kieffaber, Paul D.; Kruschke, John K.; Cho, Raymond Y.; Walker, Philip M.; Hetrick, William P.

    2013-01-01

    The primary aim of the present research was to determine how "stimulus-set" and "response-set" components of task-set contribute to switch costs and conflict processing. Three experiments are described wherein participants completed an explicitly cued task-switching procedure. Experiment 1 established that task switches requiring a reconfiguration…

  8. A comparative analysis of network robustness against different link attacks

    NASA Astrophysics Data System (ADS)

    Duan, Boping; Liu, Jing; Zhou, Mingxing; Ma, Liangliang

    2016-04-01

    Recently, the study of optimizing network robustness has attracted increasing attentions, and the constraint that every node's degree cannot be changed is considered. Although this constraint maintains the node degree distribution consistently in order to reserve the structure of networks, it makes the network structure be lack of flexibility since many network structure always transform in the modern society. Given this consideration, in this paper, we analyze the robustness of networks through setting a new constraint; that is, only the number of edges should be unchanged. Then, we use the link-robustness index (Rl) as the measure of the network robustness against either random failures or intentional attacks, and make a comparative analysis of network robustness against different types of link attacks. Moreover, we use four types of networks as initial networks, namely scale-free networks, random networks, regular networks, and small-world networks. The experimental results show that the values of robustness measures for the optimized networks starting from different initial networks are similar under different link attacks, but the network topologies may be different. That is to say, networks with different topologies may have similar robustness in terms of the robustness measures. We also find that the optimized networks obtained by one link attack may not robust against other link attacks, sometimes, even weaker than the original networks. Therefore, before building networks, it is better to study which type of link attacks may happen.

  9. Setting conservation targets for sandy beach ecosystems

    NASA Astrophysics Data System (ADS)

    Harris, Linda; Nel, Ronel; Holness, Stephen; Sink, Kerry; Schoeman, David

    2014-10-01

    Representative and adequate reserve networks are key to conserving biodiversity. This begs the question, how much of which features need to be placed in protected areas? Setting specifically-derived conservation targets for most ecosystems is common practice; however, this has never been done for sandy beaches. The aims of this paper, therefore, are to propose a methodology for setting conservation targets for sandy beach ecosystems; and to pilot the proposed method using data describing biodiversity patterns and processes from microtidal beaches in South Africa. First, a classification scheme of valued features of beaches is constructed, including: biodiversity features; unique features; and important processes. Second, methodologies for setting targets for each feature under different data-availability scenarios are described. From this framework, targets are set for features characteristic of microtidal beaches in South Africa, as follows. 1) Targets for dune vegetation types were adopted from a previous assessment, and ranged 19-100%. 2) Targets for beach morphodynamic types (habitats) were set using species-area relationships (SARs). These SARs were derived from species richness data from 142 sampling events around the South African coast (extrapolated to total theoretical species richness estimates using previously-established species-accumulation curve relationships), plotted against the area of the beach (calculated from Google Earth imagery). The species-accumulation factor (z) was 0.22, suggesting a baseline habitat target of 27% is required to protect 75% of the species. This baseline target was modified by heuristic principles, based on habitat rarity and threat status, with final values ranging 27-40%. 3) Species targets were fixed at 20%, modified using heuristic principles based on endemism, threat status, and whether or not beaches play an important role in the species' life history, with targets ranging 20-100%. 4) Targets for processes and 5

  10. Sentinel Network

    Cancer.gov

    The Sentinel Network is an integrated, electronic, national medical product safety initiative that compiles information about the safe and effective use of medical products accessible to patients and healthcare practitioners.

  11. Temporal network structures controlling disease spreading

    NASA Astrophysics Data System (ADS)

    Holme, Petter

    2016-08-01

    We investigate disease spreading on eight empirical data sets of human contacts (mostly proximity networks recording who is close to whom, at what time). We compare three levels of representations of these data sets: temporal networks, static networks, and a fully connected topology. We notice that the difference between the static and fully connected networks—with respect to time to extinction and average outbreak size—is smaller than between the temporal and static topologies. This suggests that, for these data sets, temporal structures influence disease spreading more than static-network structures. To explain the details in the differences between the representations, we use 32 network measures. This study concurs that long-time temporal structures, like the turnover of nodes and links, are the most important for the spreading dynamics.

  12. Deep Reconstruction Models for Image Set Classification.

    PubMed

    Hayat, Munawar; Bennamoun, Mohammed; An, Senjian

    2015-04-01

    Image set classification finds its applications in a number of real-life scenarios such as classification from surveillance videos, multi-view camera networks and personal albums. Compared with single image based classification, it offers more promises and has therefore attracted significant research attention in recent years. Unlike many existing methods which assume images of a set to lie on a certain geometric surface, this paper introduces a deep learning framework which makes no such prior assumptions and can automatically discover the underlying geometric structure. Specifically, a Template Deep Reconstruction Model (TDRM) is defined whose parameters are initialized by performing unsupervised pre-training in a layer-wise fashion using Gaussian Restricted Boltzmann Machines (GRBMs). The initialized TDRM is then separately trained for images of each class and class-specific DRMs are learnt. Based on the minimum reconstruction errors from the learnt class-specific models, three different voting strategies are devised for classification. Extensive experiments are performed to demonstrate the efficacy of the proposed framework for the tasks of face and object recognition from image sets. Experimental results show that the proposed method consistently outperforms the existing state of the art methods. PMID:26353289

  13. Developer Network

    SciTech Connect

    2012-08-21

    NREL's Developer Network, developer.nrel.gov, provides data that users can access to provide data to their own analyses, mobile and web applications. Developers can retrieve the data through a Web services API (application programming interface). The Developer Network handles overhead of serving up web services such as key management, authentication, analytics, reporting, documentation standards, and throttling in a common architecture, while allowing web services and APIs to be maintained and managed independently.

  14. Sentient networks

    SciTech Connect

    Chapline, G.

    1998-03-01

    The engineering problems of constructing autonomous networks of sensors and data processors that can provide alerts for dangerous situations provide a new context for debating the question whether man-made systems can emulate the cognitive capabilities of the mammalian brain. In this paper we consider the question whether a distributed network of sensors and data processors can form ``perceptions`` based on sensory data. Because sensory data can have exponentially many explanations, the use of a central data processor to analyze the outputs from a large ensemble of sensors will in general introduce unacceptable latencies for responding to dangerous situations. A better idea is to use a distributed ``Helmholtz machine`` architecture in which the sensors are connected to a network of simple processors, and the collective state of the network as a whole provides an explanation for the sensory data. In general communication within such a network will require time division multiplexing, which opens the door to the possibility that with certain refinements to the Helmholtz machine architecture it may be possible to build sensor networks that exhibit a form of artificial consciousness.

  15. PUMP SETS NO. 5 AND NO. 4. Each pump set ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    PUMP SETS NO. 5 AND NO. 4. Each pump set consists of a Worthington Pump and a General Electric motor - Edwards Air Force Base, Air Force Rocket Propulsion Laboratory, Flame Deflector Water System, Test Area 1-120, north end of Jupiter Boulevard, Boron, Kern County, CA

  16. Maximal switchability of centralized networks

    NASA Astrophysics Data System (ADS)

    Vakulenko, Sergei; Morozov, Ivan; Radulescu, Ovidiu

    2016-08-01

    We consider continuous time Hopfield-like recurrent networks as dynamical models for gene regulation and neural networks. We are interested in networks that contain n high-degree nodes preferably connected to a large number of N s weakly connected satellites, a property that we call n/N s -centrality. If the hub dynamics is slow, we obtain that the large time network dynamics is completely defined by the hub dynamics. Moreover, such networks are maximally flexible and switchable, in the sense that they can switch from a globally attractive rest state to any structurally stable dynamics when the response time of a special controller hub is changed. In particular, we show that a decrease of the controller hub response time can lead to a sharp variation in the network attractor structure: we can obtain a set of new local attractors, whose number can increase exponentially with N, the total number of nodes of the nework. These new attractors can be periodic or even chaotic. We provide an algorithm, which allows us to design networks with the desired switching properties, or to learn them from time series, by adjusting the interactions between hubs and satellites. Such switchable networks could be used as models for context dependent adaptation in functional genetics or as models for cognitive functions in neuroscience.

  17. RNEDE: Resilient Network Design Environment

    SciTech Connect

    Venkat Venkatasubramanian, Tanu Malik, Arun Giridh; Craig Rieger; Keith Daum; Miles McQueen

    2010-08-01

    Modern living is more and more dependent on the intricate web of critical infrastructure systems. The failure or damage of such systems can cause huge disruptions. Traditional design of this web of critical infrastructure systems was based on the principles of functionality and reliability. However, it is increasingly being realized that such design objectives are not sufficient. Threats, disruptions and faults often compromise the network, taking away the benefits of an efficient and reliable design. Thus, traditional network design parameters must be combined with self-healing mechanisms to obtain a resilient design of the network. In this paper, we present RNEDEa resilient network design environment that that not only optimizes the network for performance but tolerates fluctuations in its structure that result from external threats and disruptions. The environment evaluates a set of remedial actions to bring a compromised network to an optimal level of functionality. The environment includes a visualizer that enables the network administrator to be aware of the current state of the network and the suggested remedial actions at all times.

  18. Modeling Epidemics Spreading on Social Contact Networks

    PubMed Central

    ZHANG, ZHAOYANG; WANG, HONGGANG; WANG, CHONGGANG; FANG, HUA

    2016-01-01

    Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

  19. Stability indicators in network reconstruction.

    PubMed

    Filosi, Michele; Visintainer, Roberto; Riccadonna, Samantha; Jurman, Giuseppe; Furlanello, Cesare

    2014-01-01

    The number of available algorithms to infer a biological network from a dataset of high-throughput measurements is overwhelming and keeps growing. However, evaluating their performance is unfeasible unless a 'gold standard' is available to measure how close the reconstructed network is to the ground truth. One measure of this is the stability of these predictions to data resampling approaches. We introduce NetSI, a family of Network Stability Indicators, to assess quantitatively the stability of a reconstructed network in terms of inference variability due to data subsampling. In order to evaluate network stability, the main NetSI methods use a global/local network metric in combination with a resampling (bootstrap or cross-validation) procedure. In addition, we provide two normalized variability scores over data resampling to measure edge weight stability and node degree stability, and then introduce a stability ranking for edges and nodes. A complete implementation of the NetSI indicators, including the Hamming-Ipsen-Mikhailov (HIM) network distance adopted in this paper is available with the R package nettools. We demonstrate the use of the NetSI family by measuring network stability on four datasets against alternative network reconstruction methods. First, the effect of sample size on stability of inferred networks is studied in a gold standard framework on yeast-like data from the Gene Net Weaver simulator. We also consider the impact of varying modularity on a set of structurally different networks (50 nodes, from 2 to 10 modules), and then of complex feature covariance structure, showing the different behaviours of standard reconstruction methods based on Pearson correlation, Maximum Information Coefficient (MIC) and False Discovery Rate (FDR) strategy. Finally, we demonstrate a strong combined effect of different reconstruction methods and phenotype subgroups on a hepatocellular carcinoma miRNA microarray dataset (240 subjects), and we validate the

  20. BER Science Network Requirements

    SciTech Connect

    Alapaty, Kiran; Allen, Ben; Bell, Greg; Benton, David; Brettin, Tom; Canon, Shane; Dart, Eli; Cotter, Steve; Crivelli, Silvia; Carlson, Rich; Dattoria, Vince; Desai, Narayan; Egan, Richard; Tierney, Brian; Goodwin, Ken; Gregurick, Susan; Hicks, Susan; Johnston, Bill; de Jong, Bert; Kleese van Dam, Kerstin; Livny, Miron; Markowitz, Victor; McGraw, Jim; McCord, Raymond; Oehmen, Chris; Regimbal, Kevin; Shipman, Galen; Strand, Gary; Flick, Jeff; Turnbull, Susan; Williams, Dean; Zurawski, Jason

    2010-11-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In April 2010 ESnet and the Office of Biological and Environmental Research, of the DOE Office of Science, organized a workshop to characterize the networking requirements of the science programs funded by BER. The requirements identified at the workshop are summarized and described in more detail in the case studies and the Findings section. A number of common themes emerged from the case studies and workshop discussions. One is that BER science, like many other disciplines, is becoming more and more distributed and collaborative in nature. Another common theme is that data set sizes are exploding. Climate Science in particular is on the verge of needing to manage exabytes of data, and Genomics is on the verge of a huge paradigm shift in the number of sites with sequencers and the amount of sequencer data being generated.

  1. Evolving neural networks for detecting breast cancer.

    PubMed

    Fogel, D B; Wasson, E C; Boughton, E M

    1995-09-01

    Artificial neural networks are applied to the problem of detecting breast cancer from histologic data. Evolutionary programming is used to train the networks. This stochastic optimization method reduces the chance of becoming trapped in locally optimal weight sets. Preliminary results indicate that very parsimonious neural nets can outperform other methods reported in the literature on the same data. The results are statistically significant.

  2. Artificial Neural Networks and Instructional Technology.

    ERIC Educational Resources Information Center

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  3. Neural network segmentation of magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Frederick, Blaise

    1990-07-01

    Neural networks are well adapted to the task of grouping input patterns into subsets which share some similarity. Moreover once trained they can generalize their classification rules to classify new data sets. Sets of pixel intensities from magnetic resonance (MR) images provide a natural input to a neural network by varying imaging parameters MR images can reflect various independent physical parameters of tissues in their pixel intensities. A neural net can then be trained to classify physically similar tissue types based on sets of pixel intensities resulting from different imaging studies on the same subject. A neural network classifier for image segmentation was implemented on a Sun 4/60 and was tested on the task of classifying tissues of canine head MR images. Four images of a transaxial slice with different imaging sequences were taken as input to the network (three spin-echo images and an inversion recovery image). The training set consisted of 691 representative samples of gray matter white matter cerebrospinal fluid bone and muscle preclassified by a neuroscientist. The network was trained using a fast backpropagation algorithm to derive the decision criteria to classify any location in the image by its pixel intensities and the image was subsequently segmented by the classifier. The classifier''s performance was evaluated as a function of network size number of network layers and length of training. A single layer neural network performed quite well at

  4. Radiation Behavior of Analog Neural Network Chip

    NASA Technical Reports Server (NTRS)

    Langenbacher, H.; Zee, F.; Daud, T.; Thakoor, A.

    1996-01-01

    A neural network experiment conducted for the Space Technology Research Vehicle (STRV-1) 1-b launched in June 1994. Identical sets of analog feed-forward neural network chips was used to study and compare the effects of space and ground radiation on the chips. Three failure mechanisms are noted.

  5. Social Networking on the Semantic Web

    ERIC Educational Resources Information Center

    Finin, Tim; Ding, Li; Zhou, Lina; Joshi, Anupam

    2005-01-01

    Purpose: Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach: The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents with social network information that were encoded using the…

  6. Neighborhood Age Structure and Support Networks.

    ERIC Educational Resources Information Center

    Ward, Russell A.; And Others

    Studies conducted in specifically age-segregated housing for older persons suggest that such age-homogeneous settings encourage networks of friendships and mutual assistance. Since patterns of age segregation exist within communities, such segregation may result in similar social benefits. Interviews (N=1,185) assessing social networks were…

  7. Evolving Sensitivity Balances Boolean Networks

    PubMed Central

    Luo, Jamie X.; Turner, Matthew S.

    2012-01-01

    We investigate the sensitivity of Boolean Networks (BNs) to mutations. We are interested in Boolean Networks as a model of Gene Regulatory Networks (GRNs). We adopt Ribeiro and Kauffman’s Ergodic Set and use it to study the long term dynamics of a BN. We define the sensitivity of a BN to be the mean change in its Ergodic Set structure under all possible loss of interaction mutations. Insilico experiments were used to selectively evolve BNs for sensitivity to losing interactions. We find that maximum sensitivity was often achievable and resulted in the BNs becoming topologically balanced, i.e. they evolve towards network structures in which they have a similar number of inhibitory and excitatory interactions. In terms of the dynamics, the dominant sensitivity strategy that evolved was to build BNs with Ergodic Sets dominated by a single long limit cycle which is easily destabilised by mutations. We discuss the relevance of our findings in the context of Stem Cell Differentiation and propose a relationship between pluripotent stem cells and our evolved sensitive networks. PMID:22586459

  8. The Mapmark Standard Setting Method

    ERIC Educational Resources Information Center

    Schulz, E. Matthew; Mitzel, Howard C.

    2005-01-01

    A new standard setting method, Mapmark, was recently developed by ACT Inc. in the course of a contract with the National Assessment Governing Board (NAGB) to set achievement levels for the 2005 National Assessment of Educational Progress (NAEP) in Grade 12 mathematics. Mapmark includes elements of the bookmark method (Lewis, Mitzel, & Green, 1996;…

  9. Chemistry Sets Face Uncertain Future.

    ERIC Educational Resources Information Center

    Stinson, Stephen C.

    1979-01-01

    Chemistry sets, often a child's first contact with chemistry, are becoming less attractive to manufacturers as the market for these items decreases. There is a tendency for recently manufactured chemistry sets to be less adequate than those selling in the same price range in past years. Manuals vary in quality among manufacturers. (RE)

  10. Analysis of the Westland Data Set

    NASA Technical Reports Server (NTRS)

    Wen, Fang; Willett, Peter; Deb, Somnath

    2001-01-01

    The "Westland" set of empirical accelerometer helicopter data with seeded and labeled faults is analyzed with the aim of condition monitoring. The autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; and it has also been found that augmentation of these by harmonic and other parameters call improve classification significantly. Several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior oil training data and is thus able to quantify probability of error in all exact manner, such that features may be discarded or coarsened appropriately.

  11. Workshop on neural networks

    SciTech Connect

    Uhrig, R.E.; Emrich, M.L.

    1990-01-01

    The topics covered in this report are: Learning, Memory, and Artificial Neural Systems; Emerging Neural Network Technology; Neural Networks; Digital Signal Processing and Neural Networks; Application of Neural Networks to In-Core Fuel Management; Neural Networks in Process Control; Neural Network Applications in Image Processing; Neural Networks for Multi-Sensor Information Fusion; Neural Network Research in Instruments Controls Division; Neural Networks Research in the ORNL Engineering Physics and Mathematics Division; Neural Network Applications for Linear Programming; Neural Network Applications to Signal Processing and Diagnostics; Neural Networks in Filtering and Control; Neural Network Research at Tennessee Technological University; and Global Minima within the Hopfield Hypercube.

  12. Wavelet Representation of Contour Sets

    SciTech Connect

    Bertram, M; Laney, D E; Duchaineau, M A; Hansen, C D; Hamann, B; Joy, K I

    2001-07-19

    We present a new wavelet compression and multiresolution modeling approach for sets of contours (level sets). In contrast to previous wavelet schemes, our algorithm creates a parametrization of a scalar field induced by its contoum and compactly stores this parametrization rather than function values sampled on a regular grid. Our representation is based on hierarchical polygon meshes with subdivision connectivity whose vertices are transformed into wavelet coefficients. From this sparse set of coefficients, every set of contours can be efficiently reconstructed at multiple levels of resolution. When applying lossy compression, introducing high quantization errors, our method preserves contour topology, in contrast to compression methods applied to the corresponding field function. We provide numerical results for scalar fields defined on planar domains. Our approach generalizes to volumetric domains, time-varying contours, and level sets of vector fields.

  13. Breast Cancer Detection with Reduced Feature Set

    PubMed Central

    Kılıç, Niyazi; Bilgili, Erdem

    2015-01-01

    This paper explores feature reduction properties of independent component analysis (ICA) on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC) dataset is reduced to one-dimensional feature vector computing an independent component (IC). The original data with 30 features and reduced one feature (IC) are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN), artificial neural network (ANN), radial basis function neural network (RBFNN), and support vector machine (SVM). The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations) and partitioning (20%–40%) methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden's index, discriminant power, and the receiver operating characteristic (ROC) curve with its criterion values including area under curve (AUC) and 95% confidential interval (CI). This represents an improvement in diagnostic decision support system, while reducing computational complexity. PMID:26078774

  14. The neurobiology of syntax: beyond string sets.

    PubMed

    Petersson, Karl Magnus; Hagoort, Peter

    2012-07-19

    The human capacity to acquire language is an outstanding scientific challenge to understand. Somehow our language capacities arise from the way the human brain processes, develops and learns in interaction with its environment. To set the stage, we begin with a summary of what is known about the neural organization of language and what our artificial grammar learning (AGL) studies have revealed. We then review the Chomsky hierarchy in the context of the theory of computation and formal learning theory. Finally, we outline a neurobiological model of language acquisition and processing based on an adaptive, recurrent, spiking network architecture. This architecture implements an asynchronous, event-driven, parallel system for recursive processing. We conclude that the brain represents grammars (or more precisely, the parser/generator) in its connectivity, and its ability for syntax is based on neurobiological infrastructure for structured sequence processing. The acquisition of this ability is accounted for in an adaptive dynamical systems framework. Artificial language learning (ALL) paradigms might be used to study the acquisition process within such a framework, as well as the processing properties of the underlying neurobiological infrastructure. However, it is necessary to combine and constrain the interpretation of ALL results by theoretical models and empirical studies on natural language processing. Given that the faculty of language is captured by classical computational models to a significant extent, and that these can be embedded in dynamic network architectures, there is hope that significant progress can be made in understanding the neurobiology of the language faculty. PMID:22688633

  15. The neurobiology of syntax: beyond string sets.

    PubMed

    Petersson, Karl Magnus; Hagoort, Peter

    2012-07-19

    The human capacity to acquire language is an outstanding scientific challenge to understand. Somehow our language capacities arise from the way the human brain processes, develops and learns in interaction with its environment. To set the stage, we begin with a summary of what is known about the neural organization of language and what our artificial grammar learning (AGL) studies have revealed. We then review the Chomsky hierarchy in the context of the theory of computation and formal learning theory. Finally, we outline a neurobiological model of language acquisition and processing based on an adaptive, recurrent, spiking network architecture. This architecture implements an asynchronous, event-driven, parallel system for recursive processing. We conclude that the brain represents grammars (or more precisely, the parser/generator) in its connectivity, and its ability for syntax is based on neurobiological infrastructure for structured sequence processing. The acquisition of this ability is accounted for in an adaptive dynamical systems framework. Artificial language learning (ALL) paradigms might be used to study the acquisition process within such a framework, as well as the processing properties of the underlying neurobiological infrastructure. However, it is necessary to combine and constrain the interpretation of ALL results by theoretical models and empirical studies on natural language processing. Given that the faculty of language is captured by classical computational models to a significant extent, and that these can be embedded in dynamic network architectures, there is hope that significant progress can be made in understanding the neurobiology of the language faculty.

  16. Effective Teacher Professionalization in Networks?

    ERIC Educational Resources Information Center

    Hofman, Roelande H.; Dijkstra, Bernadette J.

    2010-01-01

    Teacher professionalization has been focused too strongly on external experts and a one-size-fits-all set of solutions that often fail to distinguish between the needs of different teachers. This article describes a research into teacher networks that might be more successful vehicles for professional development of teachers. The results show that…

  17. Network Policy and Economic Doctrines

    ERIC Educational Resources Information Center

    Atkinson, Robert D.

    2010-01-01

    For many years, debates over telecommunications network policy were marked by a relative lack of partisan and ideological conflict. In the last decade, this has changed markedly. Today, debates over a whole set of issues, including broadband competition, net neutrality, copyright, privacy, and others, have become more contentious. These…

  18. Bank supervision using the Threshold-Minimum Dominating Set

    NASA Astrophysics Data System (ADS)

    Gogas, Periklis; Papadimitriou, Theophilos; Matthaiou, Maria-Artemis

    2016-06-01

    An optimized, healthy and stable banking system resilient to financial crises is a prerequisite for sustainable growth. Minimization of (a) the associated systemic risk and (b) the propagation of contagion in the case of a banking crisis are necessary conditions to achieve this goal. Central Banks are in charge of this significant undertaking via a close and detailed monitoring of the banking network. In this paper, we propose the use of an auxiliary supervision/monitoring system that is both efficient with respect to the required resources and can promptly identify a set of banks that are in distress so that immediate and appropriate action can be taken by the supervising authority. We use the network defined by the interrelations between banking institutions employing tools from Complex Networks theory for an efficient management of the entire banking network. In doing so, we introduce the Threshold Minimum Dominating Set (T-MDS). The T-MDS is used to identify the smallest and most efficient subset of banks that can be used as (a) sensors of distress of a manifesting banking crisis and (b) provide a path of possible contagion. We propose the use of this method as a supplementary monitoring tool in the arsenal of a Central Bank. Our dataset includes the 122 largest American banks in terms of their interbank loans. The empirical results show that when the T-MDS methodology is applied, we can have an efficient supervision of the whole banking network, by monitoring just a subset of 47 banks.

  19. Maximum Parsimony on Phylogenetic networks

    PubMed Central

    2012-01-01

    Background Phylogenetic networks are generalizations of phylogenetic trees, that are used to model evolutionary events in various contexts. Several different methods and criteria have been introduced for reconstructing phylogenetic trees. Maximum Parsimony is a character-based approach that infers a phylogenetic tree by minimizing the total number of evolutionary steps required to explain a given set of data assigned on the leaves. Exact solutions for optimizing parsimony scores on phylogenetic trees have been introduced in the past. Results In this paper, we define the parsimony score on networks as the sum of the substitution costs along all the edges of the network; and show that certain well-known algorithms that calculate the optimum parsimony score on trees, such as Sankoff and Fitch algorithms extend naturally for networks, barring conflicting assignments at the reticulate vertices. We provide heuristics for finding the optimum parsimony scores on networks. Our algorithms can be applied for any cost matrix that may contain unequal substitution costs of transforming between different characters along different edges of the network. We analyzed this for experimental data on 10 leaves or fewer with at most 2 reticulations and found that for almost all networks, the bounds returned by the heuristics matched with the exhaustively determined optimum parsimony scores. Conclusion The parsimony score we define here does not directly reflect the cost of the best tree in the network that displays the evolution of the character. However, when searching for the most parsimonious network that describes a collection of characters, it becomes necessary to add additional cost considerations to prefer simpler structures, such as trees over networks. The parsimony score on a network that we describe here takes into account the substitution costs along the additional edges incident on each reticulate vertex, in addition to the substitution costs along the other edges which are

  20. Opening up the black box of artificial neural networks

    SciTech Connect

    Spining, M.T.; Darsey, J.A.; Sumpter, B.G.; Noid, D.W.

    1994-05-01

    In this paper, neural networks are divided according to training methods--supervised and unsupervised. Supervised training is used when a training set consisting of inputs and outputs is available. The network uses the training set to determine an error and then adjusts itself with respect to that error. Unsupervised networks are used when training sets with known outputs are not available, for example, for realtime learning. These networks use the inputs to adjust themselves so that similar input gives similar output. Another classification that will be used is feedforward and feedback networks. In a feedforward network, information is propagated through the network in one direction until it emerges as the network`s output. However, in a feedback (recurrent) network, the input information is propagated through the network but can also cycle back into the network (the signal is recurrent). In the present paper, the authors give a fundamental overview of feedforward neural networks, present some applications using them in chemical physics, and comment on the potential for future uses in chemistry. They begin by discussing some specific types of neural networks that provide the generality needed to pursue applications in the chemical sciences.

  1. Queuing theory models for computer networks

    NASA Technical Reports Server (NTRS)

    Galant, David C.

    1989-01-01

    A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

  2. Online Community Detection for Large Complex Networks

    PubMed Central

    Pan, Gang; Zhang, Wangsheng; Wu, Zhaohui; Li, Shijian

    2014-01-01

    Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information). The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance. PMID:25061683

  3. Quantifying evolvability in small biological networks

    SciTech Connect

    Nemenman, Ilya; Mugler, Andrew; Ziv, Etay; Wiggins, Chris H

    2008-01-01

    The authors introduce a quantitative measure of the capacity of a small biological network to evolve. The measure is applied to a stochastic description of the experimental setup of Guet et al. (Science 2002, 296, pp. 1466), treating chemical inducers as functional inputs to biochemical networks and the expression of a reporter gene as the functional output. The authors take an information-theoretic approach, allowing the system to set parameters that optimise signal processing ability, thus enumerating each network's highest-fidelity functions. All networks studied are highly evolvable by the measure, meaning that change in function has little dependence on change in parameters. Moreover, each network's functions are connected by paths in the parameter space along which information is not significantly lowered, meaning a network may continuously change its functionality without completely losing it along the way. This property further underscores the evolvability of the networks.

  4. Core organization of directed complex networks

    NASA Astrophysics Data System (ADS)

    Azimi-Tafreshi, N.; Dorogovtsev, S. N.; Mendes, J. F. F.

    2013-03-01

    The recursive removal of leaves (dead end vertices) and their neighbors from an undirected network results, when this pruning algorithm stops, in a so-called core of the network. This specific subgraph should be distinguished from k-cores, which are principally different subgraphs in networks. If the vertex mean degree of a network is sufficiently large, the core is a giant cluster containing a finite fraction of vertices. We find that generalization of this pruning algorithm to directed networks provides a significantly more complex picture of cores. By implementing a rate equation approach to this pruning procedure for directed uncorrelated networks, we identify a set of cores progressively embedded into each other in a network and describe their birth points and structure.

  5. Availability issues in wireless visual sensor networks.

    PubMed

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

    2014-01-01

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

  6. Structural factoring approach for analyzing stochastic networks

    NASA Technical Reports Server (NTRS)

    Hayhurst, Kelly J.; Shier, Douglas R.

    1991-01-01

    The problem of finding the distribution of the shortest path length through a stochastic network is investigated. A general algorithm for determining the exact distribution of the shortest path length is developed based on the concept of conditional factoring, in which a directed, stochastic network is decomposed into an equivalent set of smaller, generally less complex subnetworks. Several network constructs are identified and exploited to reduce significantly the computational effort required to solve a network problem relative to complete enumeration. This algorithm can be applied to two important classes of stochastic path problems: determining the critical path distribution for acyclic networks and the exact two-terminal reliability for probabilistic networks. Computational experience with the algorithm was encouraging and allowed the exact solution of networks that have been previously analyzed only by approximation techniques.

  7. Availability Issues in Wireless Visual Sensor Networks

    PubMed Central

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

    2014-01-01

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

  8. Privacy Amplification with Social Networks

    NASA Astrophysics Data System (ADS)

    Nagaraja, Shishir

    There are a number of scenarios where users wishing to communicate, share a weak secret. Often, they are also part of a common social network. Connections (edges) from the social network are represented as shared link keys between participants (vertices). We propose mechanisms that utilise the graph topology of such a network, to increase the entropy of weak pre-shared secrets. Our proposal is based on using random walks to identify a chain of common acquaintances between Alice and Bob, each of which contribute entropy to the final key. Our mechanisms exploit one-wayness and convergence properties of Markovian random walks to, firstly, maximize the set of potential entropy contributors, and second, to resist any contribution from dubious sources such as Sybill sub-networks.

  9. Penrose tilings as model sets

    NASA Astrophysics Data System (ADS)

    Shutov, A. V.; Maleev, A. V.

    2015-11-01

    The Baake construction, based on generating a set of vertices of Penrose tilings as a model set, is refined. An algorithm and a corresponding computer program for constructing an uncountable set of locally indistinguishable Penrose tilings are developed proceeding from this refined construction. Based on an analysis of the parameters of tiling vertices, 62 versions of rhomb combinations at the tiling center are determined. The combinatorial structure of Penrose tiling worms is established. A concept of flip transformations of tilings is introduced that makes it possible to construct Penrose tilings that cannot be implemented in the Baake construction.

  10. Outbreaks in Health Care Settings.

    PubMed

    Sood, Geeta; Perl, Trish M

    2016-09-01

    Outbreaks and pseudo-outbreaks in health care settings can be complex and should be evaluated systematically using epidemiologic tools. Laboratory testing is an important part of an outbreak evaluation. Health care personnel, equipment, supplies, water, ventilation systems, and the hospital environment have been associated with health care outbreaks. Settings including the neonatal intensive care unit, endoscopy, oncology, and transplant units are areas that have specific issues which impact the approach to outbreak investigation and control. Certain organisms have a predilection for health care settings because of the illnesses of patients, the procedures performed, and the care provided. PMID:27515142

  11. Alignment-free protein interaction network comparison

    PubMed Central

    Ali, Waqar; Rito, Tiago; Reinert, Gesine; Sun, Fengzhu; Deane, Charlotte M.

    2014-01-01

    Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161230

  12. Statistical Mechanics of Neural Networks

    NASA Astrophysics Data System (ADS)

    Rau, Albrecht

    1992-01-01

    Available from UMI in association with The British Library. Requires signed TDF. In this thesis we study neural networks using tools from the statistical mechanics of systems with quenched disorder. We apply these tools to two structurally different types of networks, feed-forward and feedback networks, whose properties we first review. After reviewing the use of feed-forward networks to infer unknown rules from sets of examples, we demonstrate how practical considerations can be incorporated into the analysis and how, as a consequence, existing learning theories have to be modified. To do so, we analyse the learning of rules which cannot be learnt perfectly due to constraints on the networks used. We present and analyse a model of multi-class classification and mention how it can be used. Finally we give an analytical treatment of a "learning by query" algorithm, for which the rule is extracted from queries which are not random but selected to increase the information gain. In this thesis feedback networks are used as associative memories. Our study centers on an analysis of specific features of the basins of attraction and the structure of weight space of optimized neural networks. We investigate the pattern selectivity of optimized networks, i.e. their ability to differentiate similar but distinct patterns, and show how the basins of attraction may be enlarged using external stimulus fields. Using a new method of analysis we study the weight space organization of optimized neural networks and show how the insights gained can be used to classify different groups of networks.

  13. Wave Propagation in Isotropic Media with Two Orthogonal Fracture Sets

    NASA Astrophysics Data System (ADS)

    Shao, S.; Pyrak-Nolte, L. J.

    2016-10-01

    Orthogonal intersecting fracture sets form fracture networks that affect the hydraulic and mechanical integrity of a rock mass. Interpretation of elastic waves propagated through orthogonal fracture networks is complicated by guided modes that propagate along and between fractures, by multiple internal reflections, as well as by scattering from fracture intersections. The existence of some or all of these potentially overlapping modes depends on local stress fields that can preferentially close or open either one or both sets of fractures. In this study, an acoustic wave front imaging system was used to examine the effect of bi-axial loading conditions on acoustic wave propagation in isotropic media containing two orthogonal fracture sets. From the experimental data, orthogonal intersecting fracture sets support guided waves that depend on fracture spacing and fracture-specific stiffnesses. In addition, fracture intersections have stronger effects on propagating wave fronts than merely the superposition of the effects of two independent fractures because of energy partitioning among transmitted/reflected waves, scattered waves and guided modes. Interpretation of the properties of fractures or fracture sets from seismic measurements must consider non-uniform fracture stiffnesses within and among fracture sets, as well as considering the striking effects of fracture intersections on wave propagation.

  14. New value added to network services through software-defined optical core networking

    NASA Astrophysics Data System (ADS)

    Yamada, Akiko; Nakatsugawa, Keiichi; Yamashita, Shinji; Soumiya, Toshio

    2016-02-01

    If an optical core network can be handled flexibly, it can be used not only as network infrastructure but also as a temporary broadband resource when customers have to transfer a large volume of data quickly, which will in turn lead to new WAN services. We propose "software-defined optical core networking", which achieves flexible optical network control, meaning it virtualizes optical transport network/wavelength-division multiplexing resources and controls them with resources from other layers, such as Ether/MPLS. We developed a testbed system and verified that users could request broadband resources easily, and our controller could quickly set up an optical channel data unit path for the request.

  15. Multivariate gene-set testing based on graphical models.

    PubMed

    Städler, Nicolas; Mukherjee, Sach

    2015-01-01

    The identification of predefined groups of genes ("gene-sets") which are differentially expressed between two conditions ("gene-set analysis", or GSA) is a very popular analysis in bioinformatics. GSA incorporates biological knowledge by aggregating over genes that are believed to be functionally related. This can enhance statistical power over analyses that consider only one gene at a time. However, currently available GSA approaches are based on univariate two-sample comparison of single genes. This means that they cannot test for multivariate hypotheses such as differences in covariance structure between the two conditions. Yet interplay between genes is a central aspect of biological investigation and it is likely that such interplay may differ between conditions. This paper proposes a novel approach for gene-set analysis that allows for truly multivariate hypotheses, in particular differences in gene-gene networks between conditions. Testing hypotheses concerning networks is challenging due the nature of the underlying estimation problem. Our starting point is a recent, general approach for high-dimensional two-sample testing. We refine the approach and show how it can be used to perform multivariate, network-based gene-set testing. We validate the approach in simulated examples and show results using high-throughput data from several studies in cancer biology.

  16. Biomarker Reference Sets for Cancers in Women — EDRN Public Portal

    Cancer.gov

    The purpose of this study is to develop a standard reference set of specimens for use by investigators participating in the National Cancer Institutes Early Detection Research Network (EDRN) in defining false positive rates for new cancer biomarkers in women.

  17. Bootstrap percolation on spatial networks

    NASA Astrophysics Data System (ADS)

    Gao, Jian; Zhou, Tao; Hu, Yanqing

    2015-10-01

    Bootstrap percolation is a general representation of some networked activation process, which has found applications in explaining many important social phenomena, such as the propagation of information. Inspired by some recent findings on spatial structure of online social networks, here we study bootstrap percolation on undirected spatial networks, with the probability density function of long-range links’ lengths being a power law with tunable exponent. Setting the size of the giant active component as the order parameter, we find a parameter-dependent critical value for the power-law exponent, above which there is a double phase transition, mixed of a second-order phase transition and a hybrid phase transition with two varying critical points, otherwise there is only a second-order phase transition. We further find a parameter-independent critical value around -1, about which the two critical points for the double phase transition are almost constant. To our surprise, this critical value -1 is just equal or very close to the values of many real online social networks, including LiveJournal, HP Labs email network, Belgian mobile phone network, etc. This work helps us in better understanding the self-organization of spatial structure of online social networks, in terms of the effective function for information spreading.

  18. Bootstrap percolation on spatial networks

    PubMed Central

    Gao, Jian; Zhou, Tao; Hu, Yanqing

    2015-01-01

    Bootstrap percolation is a general representation of some networked activation process, which has found applications in explaining many important social phenomena, such as the propagation of information. Inspired by some recent findings on spatial structure of online social networks, here we study bootstrap percolation on undirected spatial networks, with the probability density function of long-range links’ lengths being a power law with tunable exponent. Setting the size of the giant active component as the order parameter, we find a parameter-dependent critical value for the power-law exponent, above which there is a double phase transition, mixed of a second-order phase transition and a hybrid phase transition with two varying critical points, otherwise there is only a second-order phase transition. We further find a parameter-independent critical value around −1, about which the two critical points for the double phase transition are almost constant. To our surprise, this critical value −1 is just equal or very close to the values of many real online social networks, including LiveJournal, HP Labs email network, Belgian mobile phone network, etc. This work helps us in better understanding the self-organization of spatial structure of online social networks, in terms of the effective function for information spreading. PMID:26423347

  19. Aging and functional brain networks

    SciTech Connect

    Tomasi D.; Tomasi, D.; Volkow, N.D.

    2011-07-11

    Aging is associated with changes in human brain anatomy and function and cognitive decline. Recent studies suggest the aging decline of major functional connectivity hubs in the 'default-mode' network (DMN). Aging effects on other networks, however, are largely unknown. We hypothesized that aging would be associated with a decline of short- and long-range functional connectivity density (FCD) hubs in the DMN. To test this hypothesis, we evaluated resting-state data sets corresponding to 913 healthy subjects from a public magnetic resonance imaging database using functional connectivity density mapping (FCDM), a voxelwise and data-driven approach, together with parallel computing. Aging was associated with pronounced long-range FCD decreases in DMN and dorsal attention network (DAN) and with increases in somatosensory and subcortical networks. Aging effects in these networks were stronger for long-range than for short-range FCD and were also detected at the level of the main functional hubs. Females had higher short- and long-range FCD in DMN and lower FCD in the somatosensory network than males, but the gender by age interaction effects were not significant for any of the networks or hubs. These findings suggest that long-range connections may be more vulnerable to aging effects than short-range connections and that, in addition to the DMN, the DAN is also sensitive to aging effects, which could underlie the deterioration of attention processes that occurs with aging.

  20. Bootstrap percolation on spatial networks.

    PubMed

    Gao, Jian; Zhou, Tao; Hu, Yanqing

    2015-10-01

    Bootstrap percolation is a general representation of some networked activation process, which has found applications in explaining many important social phenomena, such as the propagation of information. Inspired by some recent findings on spatial structure of online social networks, here we study bootstrap percolation on undirected spatial networks, with the probability density function of long-range links' lengths being a power law with tunable exponent. Setting the size of the giant active component as the order parameter, we find a parameter-dependent critical value for the power-law exponent, above which there is a double phase transition, mixed of a second-order phase transition and a hybrid phase transition with two varying critical points, otherwise there is only a second-order phase transition. We further find a parameter-independent critical value around -1, about which the two critical points for the double phase transition are almost constant. To our surprise, this critical value -1 is just equal or very close to the values of many real online social networks, including LiveJournal, HP Labs email network, Belgian mobile phone network, etc. This work helps us in better understanding the self-organization of spatial structure of online social networks, in terms of the effective function for information spreading.

  1. The modularity of pollination networks

    PubMed Central

    Olesen, Jens M.; Bascompte, Jordi; Dupont, Yoko L.; Jordano, Pedro

    2007-01-01

    In natural communities, species and their interactions are often organized as nonrandom networks, showing distinct and repeated complex patterns. A prevalent, but poorly explored pattern is ecological modularity, with weakly interlinked subsets of species (modules), which, however, internally consist of strongly connected species. The importance of modularity has been discussed for a long time, but no consensus on its prevalence in ecological networks has yet been reached. Progress is hampered by inadequate methods and a lack of large datasets. We analyzed 51 pollination networks including almost 10,000 species and 20,000 links and tested for modularity by using a recently developed simulated annealing algorithm. All networks with >150 plant and pollinator species were modular, whereas networks with <50 species were never modular. Both module number and size increased with species number. Each module includes one or a few species groups with convergent trait sets that may be considered as coevolutionary units. Species played different roles with respect to modularity. However, only 15% of all species were structurally important to their network. They were either hubs (i.e., highly linked species within their own module), connectors linking different modules, or both. If these key species go extinct, modules and networks may break apart and initiate cascades of extinction. Thus, species serving as hubs and connectors should receive high conservation priorities. PMID:18056808

  2. FIRE II - Cirrus Data Sets

    Atmospheric Science Data Center

    2013-07-26

    FIRE II - Cirrus Data Sets First ISCCP Regional Experiment (FIRE) II ... stratocumulus systems, the radiative properties of these clouds and their interactions. Relevant Documents:  FIRE Project Guide FIRE II - Cirrus Home Page FIRE II - Cirrus Mission Summaries ...

  3. Comprehensive, Multi-Source Cyber-Security Data Set

    DOE Data Explorer

    Kent, Alexander D. [Los Alamos National Laboratory

    2015-05-21

    This data set represents 58 consecutive days of de-identified event data collected from five sources within Los Alamos National Laboratory’s corporate, internal computer network. The data sources include Windows-based authentication events from both individual computers and centralized Active Directory domain controller servers; process start and stop events from individual Windows computers; Domain Name Service (DNS) lookups as collected on internal DNS servers; network flow data as collected on at several key router locations; and a set of well-defined red teaming events that present bad behavior within the 58 days. In total, the data set is approximately 12 gigabytes compressed across the five data elements and presents 1,648,275,307 events in total for 12,425 users, 17,684 computers, and 62,974 processes. Specific users that are well known system related (SYSTEM, Local Service) were not de-identified though any well-known administrators account were still de-identified. In the network flow data, well-known ports (e.g. 80, 443, etc) were not de-identified. All other users, computers, process, ports, times, and other details were de-identified as a unified set across all the data elements (e.g. U1 is the same U1 in all of the data). The specific timeframe used is not disclosed for security purposes. In addition, no data that allows association outside of LANL’s network is included. All data starts with a time epoch of 1 using a time resolution of 1 second. In the authentication data, failed authentication events are only included for users that had a successful authentication event somewhere within the data set.

  4. An adaptive level set method

    SciTech Connect

    Milne, R.B.

    1995-12-01

    This thesis describes a new method for the numerical solution of partial differential equations of the parabolic type on an adaptively refined mesh in two or more spatial dimensions. The method is motivated and developed in the context of the level set formulation for the curvature dependent propagation of surfaces in three dimensions. In that setting, it realizes the multiple advantages of decreased computational effort, localized accuracy enhancement, and compatibility with problems containing a range of length scales.

  5. An inability to set independent attentional control settings by hemifield.

    PubMed

    Becker, Mark W; Ravizza, Susan M; Peltier, Chad

    2015-11-01

    Recent evidence suggests that people can simultaneously activate attentional control setting for two distinct colors. However, it is unclear whether both attentional control settings must operate globally across the visual field or whether each can be constrained to a particular spatial location. Using two different paradigms, we investigated participants' ability to apply independent color attentional control settings to distinct regions of space. In both experiments, participants were told to identify red letters in one hemifield and green letters in the opposite hemifield. Additionally, some trials used a "relevant distractor"-a letter that matched the opposite side's target color. In Experiment 1, eight letters appeared (four per hemifield) simultaneously for a brief amount of time and then were masked. Relevant distractors increased the error rate and resulted in a greater number of distractor intrusions than irrelevant distractors. Similar results were observed in Experiment 2 in which red and green targets were presented in two rapid serial visual presentation streams. Relevant distractors were found to produce an attentional blink similar in magnitude to an actual target. The results of both experiments suggest that letters matching either attentional control setting were selected by attention and were processed as if they were targets, providing strong evidence that both attentional control settings were applied globally, rather than being constrained to a particular location. PMID:26220268

  6. Equity, sustainability and governance in urban settings.

    PubMed

    Rice, Marilyn; Hancock, Trevor

    2016-03-01

    In this commentary the urban setting is explored from the perspective of ecological sustainability and social equity. Urban-related issues are highlighted related to social inequality, deficits in urban infrastructures, behavior-related illnesses and risks, global ecological changes, and urban sprawl. Approaches to addressing these issues are described from the perspective of urban governance, urban planning and design, social determinants of health, health promotion, and personal and community empowerment. Examples of successful strategies are provided from Latin America, including using participatory instruments (assessments, evaluation, participatory budgeting, etc.), establishing intersectoral committees, increasing participation of civil society organizations, and developing virtual forums and networks to channel participatory and collaborative processes. A way forward is proposed, using the urban setting to show the imperative of creating intersectoral policies and programs that produce environments that are both healthy and sustainable. It will be important to include new forms of social participation and use social media to facilitate citizen decision-making and active participation of all sectors of society, especially excluded groups.

  7. Equity, sustainability and governance in urban settings.

    PubMed

    Rice, Marilyn; Hancock, Trevor

    2016-03-01

    In this commentary the urban setting is explored from the perspective of ecological sustainability and social equity. Urban-related issues are highlighted related to social inequality, deficits in urban infrastructures, behavior-related illnesses and risks, global ecological changes, and urban sprawl. Approaches to addressing these issues are described from the perspective of urban governance, urban planning and design, social determinants of health, health promotion, and personal and community empowerment. Examples of successful strategies are provided from Latin America, including using participatory instruments (assessments, evaluation, participatory budgeting, etc.), establishing intersectoral committees, increasing participation of civil society organizations, and developing virtual forums and networks to channel participatory and collaborative processes. A way forward is proposed, using the urban setting to show the imperative of creating intersectoral policies and programs that produce environments that are both healthy and sustainable. It will be important to include new forms of social participation and use social media to facilitate citizen decision-making and active participation of all sectors of society, especially excluded groups. PMID:27199023

  8. System Administrator for LCS Development Sets

    NASA Technical Reports Server (NTRS)

    Garcia, Aaron

    2013-01-01

    The Spaceport Command and Control System Project is creating a Checkout and Control System that will eventually launch the next generation of vehicles from Kennedy Space Center. KSC has a large set of Development and Operational equipment already deployed in several facilities, including the Launch Control Center, which requires support. The position of System Administrator will complete tasks across multiple platforms (Linux/Windows), many of them virtual. The Hardware Branch of the Control and Data Systems Division at the Kennedy Space Center uses system administrators for a variety of tasks. The position of system administrator comes with many responsibilities which include maintaining computer systems, repair or set up hardware, install software, create backups and recover drive images are a sample of jobs which one must complete. Other duties may include working with clients in person or over the phone and resolving their computer system needs. Training is a major part of learning how an organization functions and operates. Taking that into consideration, NASA is no exception. Training on how to better protect the NASA computer infrastructure will be a topic to learn, followed by NASA work polices. Attending meetings and discussing progress will be expected. A system administrator will have an account with root access. Root access gives a user full access to a computer system and or network. System admins can remove critical system files and recover files using a tape backup. Problem solving will be an important skill to develop in order to complete the many tasks.

  9. Making Connections: A Network Approach to University Disaster Preparedness

    ERIC Educational Resources Information Center

    Stein, Catherine H.; Vickio, Craig J.; Fogo, Wendy R.; Abraham, Kristen M.

    2007-01-01

    A network approach to disaster preparedness in university settings is described. Basic network concepts relevant for disaster preparedness and methods for analyzing network data without complex mathematics are presented. A case study of campus mental health and academic units at a midwestern university is presented to illustrate the practical…

  10. Network Views

    ERIC Educational Resources Information Center

    Alexander, Louis

    2010-01-01

    The world changed in 2008. The financial crisis brought with it a deepening sense of insecurity, and the desire to be connected to a network increased. Throughout the summer and fall of 2008, events were unfolding with alarming rapidity. The Massachusetts Institute of Technology (MIT) Alumni Association wanted to respond to this change in the…

  11. Gradient networks

    NASA Astrophysics Data System (ADS)

    Toroczkai, Zoltán; Kozma, Balázs; Bassler, Kevin E.; Hengartner, N. W.; Korniss, G.

    2008-04-01

    Gradient networks are defined (Toroczkai and Bassler 2004 Nature 428 716) as directed graphs formed by local gradients of a scalar field distributed on the nodes of a substrate network G. We present the derivation for some of the general properties of gradient graphs and give an exact expression for the in-degree distribution R(l) of the gradient network when the substrate is a binomial (Erd{\\;\\kern -0.10em \\raise -0.35ex \\{{^{^{\\prime\\prime}}}}\\kern -0.57em \\o} s-Rényi) random graph, G_{N,p} , and the scalars are independent identically distributed (i.i.d.) random variables. We show that in the limit N \\to \\infty, p \\to 0, z = pN = \\mbox{const} \\gg 1, R(l)\\propto l^{-1} for l < l_c = z , i.e., gradient networks become scale-free graphs up to a cut-off degree. This paper presents the detailed derivation of the results announced in Toroczkai and Bassler (2004 Nature 428 716).

  12. Knowledge Networks

    ERIC Educational Resources Information Center

    McLeod, Scott

    2008-01-01

    The blogosphere and the Internet are both examples of complex, self-organizing networks. So too is the world of academic publishing. Some faculty members are prolific article and book writers. Their publications often are hubs, or even superhubs, in the scholarly literature, cited regularly by others. Some scholars might just be nodes, with…

  13. Beyond Networking.

    ERIC Educational Resources Information Center

    Carmel, Michael

    1981-01-01

    Discusses the new relationships between libraries and their users with reference to the worldwide medical information networks which have developed through the influence of the U.S. National Library of Medicine. Consideration is given to the new roles librarians will have to assume. (Author/LLS)

  14. Ada Run Time Support Environments and a common APSE Interface Set. [Ada Programming Support Environment

    NASA Technical Reports Server (NTRS)

    Mckay, C. W.; Bown, R. L.

    1985-01-01

    The paper discusses the importance of linking Ada Run Time Support Environments to the Common Ada Programming Support Environment (APSE) Interface Set (CAIS). A non-stop network operating systems scenario is presented to serve as a forum for identifying the important issues. The network operating system exemplifies the issues involved in the NASA Space Station data management system.

  15. A Measure for the Cohesion of Weighted Networks.

    ERIC Educational Resources Information Center

    Egghe, Leo; Rousseau, Ronald

    2003-01-01

    Discusses graph theory in information science, focusing on measures for the cohesion of networks. Illustrates how a set of weights between connected nodes can be transformed into a set of dissimilarity measures and presents an example of the new compactness measures for a cocitation and a bibliographic coupling network. (Author/LRW)

  16. Predicting lithologic parameters using artificial neural networks

    SciTech Connect

    Link, C.A.; Wideman, C.J.; Hanneman, D.L.

    1995-06-01

    Artificial neural networks (ANNs) are becoming increasingly popular as a method for parameter classification and as a tool for recognizing complex relationships in a variety of data types. The power of ANNs lies in their ability to {open_quotes}learn{close_quotes} from a set of training data and then being able to {open_quotes}generalize{close_quotes} to new data sets. In addition, ANNs are able to incorporate data over a large range of scales and are robust in the presence of noise. A back propagation artificial neural network has proved to be a useful tool for predicting sequence boundaries from well logs in a Cenozoic basin. The network was trained using the following log set: neutron porosity, bulk density, pef, and interpreted paleosol horizons from a well in the Deer Lodge Valley, southwestern Montana. After successful training, this network was applied to the same set of well logs from a nearby well minus the interpreted paleosol horizons. The trained neural network was able to produce reasonable predictions for paleosol sequence boundaries in the test well based on the previous training. In an ongoing oil reservoir characterization project, a back propagation neural network is being used to produce estimates of porosity and permeability for subsequent input into a reservoir simulator. A combination of core, well log, geological, and 3-D seismic data serves as input to a back propagation network which outputs estimates of the spatial distribution of porosity and permeability away from the well.

  17. ASCR Science Network Requirements

    SciTech Connect

    Dart, Eli; Tierney, Brian

    2009-08-24

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In April 2009 ESnet and the Office of Advanced Scientific Computing Research (ASCR), of the DOE Office of Science, organized a workshop to characterize the networking requirements of the programs funded by ASCR. The ASCR facilities anticipate significant increases in wide area bandwidth utilization, driven largely by the increased capabilities of computational resources and the wide scope of collaboration that is a hallmark of modern science. Many scientists move data sets between facilities for analysis, and in some cases (for example the Earth System Grid and the Open Science Grid), data distribution is an essential component of the use of ASCR facilities by scientists. Due to the projected growth in wide area data transfer needs, the ASCR supercomputer centers all expect to deploy and use 100 Gigabit per second networking technology for wide area connectivity as soon as that deployment is financially feasible. In addition to the network connectivity that ESnet provides, the ESnet Collaboration Services (ECS) are critical to several science communities. ESnet identity and trust services, such as the DOEGrids certificate authority, are widely used both by the supercomputer centers and by collaborations such as Open Science Grid (OSG) and the Earth System Grid (ESG). Ease of use is a key determinant of the scientific utility of network-based services. Therefore, a key enabling aspect for scientists beneficial use of high

  18. Whether information network supplements friendship network

    NASA Astrophysics Data System (ADS)

    Miao, Lili; Zhang, Qian-Ming; Nie, Da-Cheng; Cai, Shi-Min

    2015-02-01

    Homophily is a significant mechanism for link prediction in complex network, of which principle describes that people with similar profiles or experiences tend to tie with each other. In a multi-relationship network, friendship among people has been utilized to reinforce similarity of taste for recommendation system whose basic idea is similar to homophily, yet how the taste inversely affects friendship prediction is little discussed. This paper contributes to address the issue by analyzing two benchmark data sets both including user's behavioral information of taste and friendship based on the principle of homophily. It can be found that the creation of friendship tightly associates with personal taste. Especially, the behavioral information of taste involving with popular objects is much more effective to improve the performance of friendship prediction. However, this result seems to be contradictory to the finding in Zhang et al. (2013) that the behavior information of taste involving with popular objects is redundant in recommendation system. We thus discuss this inconformity to comprehensively understand the correlation between them.

  19. Neural network based system for equipment surveillance

    DOEpatents

    Vilim, Richard B.; Gross, Kenneth C.; Wegerich, Stephan W.

    1998-01-01

    A method and system for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process.

  20. Neural network based system for equipment surveillance

    DOEpatents

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

    1998-04-28

    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  1. Realizing actual feedback control of complex network

    NASA Astrophysics Data System (ADS)

    Tu, Chengyi; Cheng, Yuhua

    2014-06-01

    In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems.

  2. Suicide in the Medical Setting

    PubMed Central

    Ballard, Elizabeth D.; Pao, Maryland; Henderson, David; Lee, Laura M.; Bostwick, J. Michael; Rosenstein, Donald L.

    2009-01-01

    Article-at-a-Glance Background Little is known about suicide in the hospital setting. Although suicide is a major public health concern, the literature on suicide in the medical setting is limited, and accurate data on hospital-based suicides are unavailable. Consequently, the prevalence, demographic characteristics, and risk factors for suicide in this population are unknown. The literature on completed suicides in medical or surgical wards of a general hospital was summarized to generate hypotheses for further investigation regarding in-hospital suicides. Methods MEDLINE, PsycINFO, IndexCat, and Scopus were queried for English-language articles on inpatient suicides in a general hospital. These data were compared with reports of suicide by psychiatric inpatients and the annual suicide statistics from the U.S. general population. Results Twelve articles detailing 335 suicides in the medical setting were included. Published data on hospital-based suicides are limited by selection bias, incomplete reporting, and a small number of completed suicides. Consequently, no significant setting-specific findings emerge from the existing literature. Reported cases suggest that inpatients who commit suicide in the medical setting may have a different demographic profile and employ different methods of suicide in comparison with individuals who commit suicide in psychiatric settings or the general population. Discussion Given the absence of systematic data collection and the highly variable nature of reported suicides, it coult not be determined if clinically relevant distinctions exist between suicides in different health care settings. Prospective and more detailed data collection are needed because a more complete characterization of suicide in medical inpatients may be useful in both prevention approaches and institutional policies with respect to hospital-based suicides. PMID:18714750

  3. NASA Deep Space Network Operations Scheduling

    NASA Astrophysics Data System (ADS)

    Enari, D. M.

    The functioning of the Deep Space Network Operations Scheduling, Jet Propulsion Laboratory, CA is reviewed. The primary objectives of the Operations Scheduling are: to schedule the worldwide global allocation of ground communications, tracking facilities, and equipment; and to provide deep space telecommunications for command, tracking, telemetry, and control in support of flight mission operations and tests. Elements of the earth set are Deep Space Stations (DSS) which provide the telecommunications link between the earth and spacecraft; NASA Communications Network; Network Data Processing Area; Network Operations Control Area which provides operational direction to the DSS; Mission Control and Computing systems; and Mission Support areas which provide flight control of the spacecraft. Elements of the space set include mission priorities and requirements which determine the spacecraft queue for allocating network resources. Scheduling is discussed in terms of long-range (3 years), mid-range (8 weeks), and short-range (2 weeks).

  4. The network management expert system prototype for Sun Workstations

    NASA Technical Reports Server (NTRS)

    Leigh, Albert

    1990-01-01

    Networking has become one of the fastest growing areas in the computer industry. The emergence of distributed workstations make networking more popular because they need to have connectivity between themselves as well as with other computer systems to share information and system resources. Making the networks more efficient and expandable by selecting network services and devices that fit to one's need is vital to achieve reliability and fast throughput. Networks are dynamically changing and growing at a rate that outpaces the available human resources. Therefore, there is a need to multiply the expertise rapidly rather than employing more network managers. In addition, setting up and maintaining networks by following the manuals can be tedious and cumbersome even for an experienced network manager. This prototype expert system was developed to experiment on Sun Workstations to assist system and network managers in selecting and configurating network services.

  5. Social Networking Services in E-Learning

    ERIC Educational Resources Information Center

    Weber, Peter; Rothe, Hannes

    2012-01-01

    This paper is a report on the findings of a study conducted on the use of the social networking service NING in a cross-location e-learning setting named "Net Economy." We describe how we implemented NING as a fundamental part of the setting through a special phase concept and team building approach. With the help of user statistics, we examine…

  6. Social Networking Services in E-Learning

    ERIC Educational Resources Information Center

    Weber, Peter; Rothe, Hannes

    2016-01-01

    This paper is a report on the findings of a study conducted on the use of the social networking service NING in a cross-location e-learning setting named "Net Economy." We describe how we implemented NING as a fundamental part of the setting through a special phase concept and team building approach. With the help of user statistics, we…

  7. Accurate multiple network alignment through context-sensitive random walk

    PubMed Central

    2015-01-01

    Background Comparative network analysis can provide an effective means of analyzing large-scale biological networks and gaining novel insights into their structure and organization. Global network alignment aims to predict the best overall mapping between a given set of biological networks, thereby identifying important similarities as well as differences among the networks. It has been shown that network alignment methods can be used to detect pathways or network modules that are conserved across different networks. Until now, a number of network alignment algorithms have been proposed based on different formulations and approaches, many of them focusing on pairwise alignment. Results In this work, we propose a novel multiple network alignment algorithm based on a context-sensitive random walk model. The random walker employed in the proposed algorithm switches between two different modes, namely, an individual walk on a single network and a simultaneous walk on two networks. The switching decision is made in a context-sensitive manner by examining the current neighborhood, which is effective for quantitatively estimating the degree of correspondence between nodes that belong to different networks, in a manner that sensibly integrates node similarity and topological similarity. The resulting node correspondence scores are then used to predict the maximum expected accuracy (MEA) alignment of the given networks. Conclusions Performance evaluation based on synthetic networks as well as real protein-protein interaction networks shows that the proposed algorithm can construct more accurate multiple network alignments compared to other leading methods. PMID:25707987

  8. System and method for generating a relationship network

    DOEpatents

    Franks, Kasian; Myers, Cornelia A.; Podowski, Raf M.

    2011-07-26

    A computer-implemented system and process for generating a relationship network is disclosed. The system provides a set of data items to be related and generates variable length data vectors to represent the relationships between the terms within each data item. The system can be used to generate a relationship network for documents, images, or any other type of file. This relationship network can then be queried to discover the relationships between terms within the set of data items.

  9. System and method for generating a relationship network

    DOEpatents

    Franks, Kasian; Myers, Cornelia A; Podowski, Raf M

    2015-05-05

    A computer-implemented system and process for generating a relationship network is disclosed. The system provides a set of data items to be related and generates variable length data vectors to represent the relationships between the terms within each data item. The system can be used to generate a relationship network for documents, images, or any other type of file. This relationship network can then be queried to discover the relationships between terms within the set of data items.

  10. Intelligent virtual reality in the setting of fuzzy sets

    NASA Technical Reports Server (NTRS)

    Dockery, John; Littman, David

    1992-01-01

    The authors have previously introduced the concept of virtual reality worlds governed by artificial intelligence. Creation of an intelligent virtual reality was further proposed as a universal interface for the handicapped. This paper extends consideration of intelligent virtual realty to a context in which fuzzy set principles are explored as a major tool for implementing theory in the domain of applications to the disabled.

  11. Vocabulary Mining for Information Retrieval: Rough Sets and Fuzzy Sets.

    ERIC Educational Resources Information Center

    Srinivasan, Padmini; Ruiz, Miguel E.; Kraft, Donald H.; Chen, Jianhua

    2001-01-01

    Explains vocabulary mining in information retrieval and describes a framework for vocabulary mining that allows the use of rough set-based approximations even when documents and queries are described using weighted, or fuzzy, representations. Examines coordination between multiple vocabulary views and applies the framework to the Unified Medical…

  12. FRIPON, the French fireball network

    NASA Astrophysics Data System (ADS)

    Colas, F.; Zanda, B.; Bouley, S.; Vaubaillon, J.; Marmo, C.; Audureau, Y.; Kwon, M. K.; Rault, J. L.; Caminade, S.; Vernazza, P.; Gattacceca, J.; Birlan, M.; Maquet, L.; Egal, A.; Rotaru, M.; Gruson-Daniel, Y.; Birnbaum, C.; Cochard, F.; Thizy, O.

    2015-10-01

    FRIPON (Fireball Recovery and InterPlanetary Observation Network) [4](Colas et al, 2014) was recently founded by ANR (Agence Nationale de la Recherche). Its aim is to connect meteoritical science with asteroidal and cometary science in order to better understand solar system formation and evolution. The main idea is to set up an observation network covering all the French territory to collect a large number of meteorites (one or two per year) with accurate orbits, allowing us to pinpoint possible parent bodies. 100 all-sky cameras will be installed at the end of 2015 forming a dense network with an average distance of 100km between stations. To maximize the accuracy of orbit determination, we will mix our optical data with radar data from the GRAVES beacon received by 25 stations [5](Rault et al, 2015). As both the setting up of the network and the creation of search teams for meteorites will need manpower beyond our small team of professionals, we are developing a citizen science network called Vigie-Ciel [6](Zanda et al, 2015). The public at large will thus be able to simply use our data, participate in search campaigns or even setup their own cameras.

  13. CFD Data Sets on the WWW for Education and Testing

    NASA Technical Reports Server (NTRS)

    Globus, Al; Lasinski, T. A. (Technical Monitor)

    1995-01-01

    The Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Ames Research Center has begun the development of a Computational Fluid Dynamics (CFD) data set archive on the World Wide Web (WWW) at URL http://www.nas.nasa.gov/NAS/DataSets/. Data sets are integrated with related information such as research papers, metadata, visualizations, etc. In this paper, four classes of users are identified and discussed: students, visualization developers, CFD practitioners, and management. Bandwidth and security issues are briefly reviewed and the status of the archive as of May 1995 is examined. Routine network distribution of data sets is likely to have profound implications for the conduct of science. The exact nature of these changes is subject to speculation, but the ability for anyone to examine the data, in addition to the investigator's analysis, may well play an important role in the future.

  14. Assessment of protein set coherence using functional annotations

    PubMed Central

    Chagoyen, Monica; Carazo, Jose M; Pascual-Montano, Alberto

    2008-01-01

    Background Analysis of large-scale experimental datasets frequently produces one or more sets of proteins that are subsequently mined for functional interpretation and validation. To this end, a number of computational methods have been devised that rely on the analysis of functional annotations. Although current methods provide valuable information (e.g. significantly enriched annotations, pairwise functional similarities), they do not specifically measure the degree of homogeneity of a protein set. Results In this work we present a method that scores the degree of functional homogeneity, or coherence, of a set of proteins on the basis of the global similarity of their functional annotations. The method uses statistical hypothesis testing to assess the significance of the set in the context of the functional space of a reference set. As such, it can be used as a first step in the validation of sets expected to be homogeneous prior to further functional interpretation. Conclusion We evaluate our method by analysing known biologically relevant sets as well as random ones. The known relevant sets comprise macromolecular complexes, cellular components and pathways described for Saccharomyces cerevisiae, which are mostly significantly coherent. Finally, we illustrate the usefulness of our approach for validating 'functional modules' obtained from computational analysis of protein-protein interaction networks. Matlab code and supplementary data are available at PMID:18937846

  15. Rotation gene set testing for longitudinal expression data.

    PubMed

    Dørum, Guro; Snipen, Lars; Solheim, Margrete; Saebø, Solve

    2014-11-01

    Gene set analysis methods are popular tools for identifying differentially expressed gene sets in microarray data. Most existing methods use a permutation test to assess significance for each gene set. The permutation test's assumption of exchangeable samples is often not satisfied for time-series data and complex experimental designs, and in addition it requires a certain number of samples to compute p-values accurately. The method presented here uses a rotation test rather than a permutation test to assess significance. The rotation test can compute accurate p-values also for very small sample sizes. The method can handle complex designs and is particularly suited for longitudinal microarray data where the samples may have complex correlation structures. Dependencies between genes, modeled with the use of gene networks, are incorporated in the estimation of correlations between samples. In addition, the method can test for both gene sets that are differentially expressed and gene sets that show strong time trends. We show on simulated longitudinal data that the ability to identify important gene sets may be improved by taking the correlation structure between samples into account. Applied to real data, the method identifies both gene sets with constant expression and gene sets with strong time trends.

  16. Consistency analysis of metabolic correlation networks

    PubMed Central

    Müller-Linow, Mark; Weckwerth, Wolfram; Hütt, Marc-Thorsten

    2007-01-01

    Background Metabolic correlation networks are derived from the covariance of metabolites in replicates of metabolomics experiments. They constitute an interesting intermediate between topology (i.e. the system's architecture defined by the set of reactions between metabolites) and dynamics (i.e. the metabolic concentrations observed as fluctuations around steady-state values in the metabolic network). Results Here we analyze, how such a correlation network changes over time, and compare the relative positions of metabolites in the correlation networks with those in established metabolic networks derived from genome databases. We find that network similarity indeed decreases with an increasing time difference between these networks during a day/night course and, counter intuitively, that proximity of metabolites in the correlation network is no indicator of proximity of the metabolites in the metabolic network. Conclusion The organizing principles of correlation networks are distinct from those of metabolic reaction maps. Time courses of correlation networks may in the future prove an important data source for understanding these organizing principles. PMID:17892579

  17. Segmenting data sets for RIP.

    PubMed

    de Sanctis, Daniele; Nanao, Max H

    2012-09-01

    Specific radiation damage can be used for the phasing of macromolecular crystal structures. In practice, however, the optimization of the X-ray dose used to `burn' the crystal to induce specific damage can be difficult. Here, a method is presented in which a single large data set that has not been optimized in any way for radiation-damage-induced phasing (RIP) is segmented into multiple sub-data sets, which can then be used for RIP. The efficacy of this method is demonstrated using two model systems and two test systems. A method to improve the success of this type of phasing experiment by varying the composition of the two sub-data sets with respect to their separation by image number, and hence by absorbed dose, as well as their individual completeness is illustrated. PMID:22948916

  18. Segmenting data sets for RIP.

    PubMed

    de Sanctis, Daniele; Nanao, Max H

    2012-09-01

    Specific radiation damage can be used for the phasing of macromolecular crystal structures. In practice, however, the optimization of the X-ray dose used to `burn' the crystal to induce specific damage can be difficult. Here, a method is presented in which a single large data set that has not been optimized in any way for radiation-damage-induced phasing (RIP) is segmented into multiple sub-data sets, which can then be used for RIP. The efficacy of this method is demonstrated using two model systems and two test systems. A method to improve the success of this type of phasing experiment by varying the composition of the two sub-data sets with respect to their separation by image number, and hence by absorbed dose, as well as their individual completeness is illustrated.

  19. Setting standards: Risk assessment issues

    SciTech Connect

    Pontius, F.W.

    1995-07-01

    How drinking water standards are set and which contaminants should be regulated are central issues in reauthorization of the Safe Drinking Water Act (SDWA). Suggested amendments to the standard-setting provisions of the SDWA cover a broad spectrum. In general, environmental groups argue that standards are not strict enough and that greater consideration should be given to sensitive subpopulations. Other note that the high cost associated with meeting increasingly strict standards is unjustified in light of the uncertain and sometimes nonexistent incremental benefits. This article takes a look at the issues involved in developing a rational approach for establishing drinking water standards. It reviews the current approach used by the US Environmental Protection Agency (USEPA) to set standards.

  20. Insecurity of Wireless Networks

    SciTech Connect

    Sheldon, Frederick T; Weber, John Mark; Yoo, Seong-Moo; Pan, W. David

    2012-01-01

    Wireless is a powerful core technology enabling our global digital infrastructure. Wi-Fi networks are susceptible to attacks on Wired Equivalency Privacy, Wi-Fi Protected Access (WPA), and WPA2. These attack signatures can be profiled into a system that defends against such attacks on the basis of their inherent characteristics. Wi-Fi is the standard protocol for wireless networks used extensively in US critical infrastructures. Since the Wired Equivalency Privacy (WEP) security protocol was broken, the Wi-Fi Protected Access (WPA) protocol has been considered the secure alternative compatible with hardware developed for WEP. However, in November 2008, researchers developed an attack on WPA, allowing forgery of Address Resolution Protocol (ARP) packets. Subsequent enhancements have enabled ARP poisoning, cryptosystem denial of service, and man-in-the-middle attacks. Open source systems and methods (OSSM) have long been used to secure networks against such attacks. This article reviews OSSMs and the results of experimental attacks on WPA. These experiments re-created current attacks in a laboratory setting, recording both wired and wireless traffic. The article discusses methods of intrusion detection and prevention in the context of cyber physical protection of critical Internet infrastructure. The basis for this research is a specialized (and undoubtedly incomplete) taxonomy of Wi-Fi attacks and their adaptations to existing countermeasures and protocol revisions. Ultimately, this article aims to provide a clearer picture of how and why wireless protection protocols and encryption must achieve a more scientific basis for detecting and preventing such attacks.

  1. [The Pasteur network].

    PubMed

    Durosoir, J L

    1995-01-14

    Inspired by Louis Pasteur, the international network of Pasteur Institutes forms an original body of research institutes whose vitality has grown steadily since Albert Calmette first created the Saigon Institute in 1891. The dynamic development of the 23 Pasteur Institutes currently implanted throughout the world was made possible by three driving forces. First of all, Pasteur's own teaching--"Advance only what you can prove experimentally"--the founding principle of modern research. Secondly, the international missions headed by leading collaborators including Thuillier who worked on cholera in Egypt, Loir who initiated antirabies research in Australia and Russia, Calmette in Saigon, and others in Rio de Janeiro, Dalat, Tunis and Alger. And finally Pasteur's own personal renown. Today the Pasteur Institutes fill a vital need in their respective countries developing and producing vaccines locally, serving often as the only competent medical laboratory in developing countries and helping improve standards of hygiene adapted to local situations. Fundamental research has always been at the heart of Pasteur Institutes, coupled with essential training for technicians and researchers alike. Despite political incertitudes and turmoil, the international network of Pasteur Institutes has held its place as the leader in scientific progress for over a century, setting the place for modern international research. The Cantacuzene Institute in Bucarest and the Pasteur Institute in Saint-Petersburg which joined the network in 1991 and 1993 are the most recent examples of the fundamental principle of exchange and cooperation so important for further development.

  2. Neural networks and chaos: construction, evaluation of chaotic networks, and prediction of chaos with multilayer feedforward networks.

    PubMed

    Bahi, Jacques M; Couchot, Jean-François; Guyeux, Christophe; Salomon, Michel

    2012-03-01

    Many research works deal with chaotic neural networks for various fields of application. Unfortunately, up to now, these networks are usually claimed to be chaotic without any mathematical proof. The purpose of this paper is to establish, based on a rigorous theoretical framework, an equivalence between chaotic iterations according to Devaney and a particular class of neural networks. On the one hand, we show how to build such a network, on the other hand, we provide a method to check if a neural network is a chaotic one. Finally, the ability of classical feedforward multilayer perceptrons to learn sets of data obtained from a dynamical system is regarded. Various boolean functions are iterated on finite states. Iterations of some of them are proven to be chaotic as it is defined by Devaney. In that context, important differences occur in the training process, establishing with various neural networks that chaotic behaviors are far more difficult to learn.

  3. Chemical networks

    NASA Astrophysics Data System (ADS)

    Thi, Wing-Fai

    2015-09-01

    This chapter discusses the fundamental ideas of how chemical networks are build, their strengths and limitations. The chemical reactions that occur in disks combine the cold phase reactions used to model cold molecular clouds with the hot chemistry applied to planetary atmosphere models. With a general understanding of the different types of reactions that can occur, one can proceed in building a network of chemical reactions and use it to explain the abundance of species seen in disks. One on-going research subject is finding new paths to synthesize species either in the gas-phase or on grain surfaces. Specific formation routes for water or carbon monoxide are discussed in more details. 13th Lecture of the Summer School "Protoplanetary Disks: Theory and Modelling Meet Observations"

  4. Telepsychiatry in juvenile justice settings.

    PubMed

    Kaliebe, Kristopher E; Heneghan, James; Kim, Thomas J

    2011-01-01

    Telepsychiatry is emerging as a valuable means of providing mental health care in juvenile justice settings. Youth in the juvenile justice system have high levels of psychiatric morbidity. State and local juvenile justice systems frequently struggle to provide specialized psychiatric care, as these systems have limited resources and often operate in remote locations. Case studies in the use of telepsychiatry to provide improved care in juvenile corrections in 4 states are described, along with a review of advantages and disadvantages of telepsychiatry in these settings. PMID:21092916

  5. Telepsychiatry in juvenile justice settings.

    PubMed

    Kaliebe, Kristopher E; Heneghan, James; Kim, Thomas J

    2011-01-01

    Telepsychiatry is emerging as a valuable means of providing mental health care in juvenile justice settings. Youth in the juvenile justice system have high levels of psychiatric morbidity. State and local juvenile justice systems frequently struggle to provide specialized psychiatric care, as these systems have limited resources and often operate in remote locations. Case studies in the use of telepsychiatry to provide improved care in juvenile corrections in 4 states are described, along with a review of advantages and disadvantages of telepsychiatry in these settings.

  6. Retina vascular network recognition

    NASA Astrophysics Data System (ADS)

    Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

    1993-09-01

    The analysis of morphological and structural modifications of the retina vascular network is an interesting investigation method in the study of diabetes and hypertension. Normally this analysis is carried out by qualitative evaluations, according to standardized criteria, though medical research attaches great importance to quantitative analysis of vessel color, shape and dimensions. The paper describes a system which automatically segments and recognizes the ocular fundus circulation and micro circulation network, and extracts a set of features related to morphometric aspects of vessels. For this class of images the classical segmentation methods seem weak. We propose a computer vision system in which segmentation and recognition phases are strictly connected. The system is hierarchically organized in four modules. Firstly the Image Enhancement Module (IEM) operates a set of custom image enhancements to remove blur and to prepare data for subsequent segmentation and recognition processes. Secondly the Papilla Border Analysis Module (PBAM) automatically recognizes number, position and local diameter of blood vessels departing from optical papilla. Then the Vessel Tracking Module (VTM) analyses vessels comparing the results of body and edge tracking and detects branches and crossings. Finally the Feature Extraction Module evaluates PBAM and VTM output data and extracts some numerical indexes. Used algorithms appear to be robust and have been successfully tested on various ocular fundus images.

  7. Coherent spin-networks

    SciTech Connect

    Bianchi, Eugenio; Magliaro, Elena; Perini, Claudio

    2010-07-15

    In this paper we discuss a proposal of coherent states for loop quantum gravity. These states are labeled by a point in the phase space of general relativity as captured by a spin-network graph. They are defined as the gauge-invariant projection of a product over links of Hall's heat kernels for the cotangent bundle of SU(2). The labels of the state are written in terms of two unit vectors, a spin and an angle for each link of the graph. The heat-kernel time is chosen to be a function of the spin. These labels are the ones used in the spin-foam setting and admit a clear geometric interpretation. Moreover, the set of labels per link can be written as an element of SL(2,C). These states coincide with Thiemann's coherent states with the area operator as complexifier. We study the properties of semiclassicality of these states and show that, for large spins, they reproduce a superposition over spins of spin-networks with nodes labeled by Livine-Speziale coherent intertwiners. Moreover, the weight associated to spins on links turns out to be given by a Gaussian times a phase as originally proposed by Rovelli.

  8. Modeling the citation network by network cosmology.

    PubMed

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  9. NASA Network

    NASA Technical Reports Server (NTRS)

    Carter, David; Wetzel, Scott

    2000-01-01

    The NASA Network includes nine NASA operated and partner operated stations covering North America, the west coast of South America, the Pacific, and Western Australia . A new station is presently being setup in South Africa and discussions are underway to add another station in Argentina. NASA SLR operations are supported by Honeywell Technical Solutions, Inc (HTSI), formally AlliedSignal Technical Services, The University of Texas, the University of Hawaii and Universidad Nacional de San Agustin.

  10. Estimation of global network statistics from incomplete data.

    PubMed

    Bliss, Catherine A; Danforth, Christopher M; Dodds, Peter Sheridan

    2014-01-01

    Complex networks underlie an enormous variety of social, biological, physical, and virtual systems. A profound complication for the science of complex networks is that in most cases, observing all nodes and all network interactions is impossible. Previous work addressing the impacts of partial network data is surprisingly limited, focuses primarily on missing nodes, and suggests that network statistics derived from subsampled data are not suitable estimators for the same network statistics describing the overall network topology. We generate scaling methods to predict true network statistics, including the degree distribution, from only partial knowledge of nodes, links, or weights. Our methods are transparent and do not assume a known generating process for the network, thus enabling prediction of network statistics for a wide variety of applications. We validate analytical results on four simulated network classes and empirical data sets of various sizes. We perform subsampling experiments by varying proportions of sampled data and demonstrate that our scaling methods can provide very good estimates of true network statistics while acknowledging limits. Lastly, we apply our techniques to a set of rich and evolving large-scale social networks, Twitter reply networks. Based on 100 million tweets, we use our scaling techniques to propose a statistical characterization of the Twitter Interactome from September 2008 to November 2008. Our treatment allows us to find support for Dunbar's hypothesis in detecting an upper threshold for the number of active social contacts that individuals maintain over the course of one week.

  11. Interworking evolution of mobile satellite and terrestrial networks

    NASA Technical Reports Server (NTRS)

    Matyas, R.; Kelleher, P.; Moller, P.; Jones, T.

    1993-01-01

    There is considerable interest among mobile satellite service providers in interworking with terrestrial networks to provide a universal global network. With such interworking, subscribers may be provided a common set of services such as those planned for the Public Switched Telephone Network (PSTN), the Integrated Services Digital Network (ISDN), and future Intelligent Networks (IN's). This paper first reviews issues in satellite interworking. Next the status and interworking plans of terrestrial mobile communications service providers are examined with early examples of mobile satellite interworking including a discussion of the anticipated evolution towards full interworking between mobile satellite and both fixed and mobile terrestrial networks.

  12. Implementing controlled-unitary operations over the butterfly network

    SciTech Connect

    Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S.; Murao, Mio

    2014-12-04

    We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

  13. Behavior Management in Afterschool Settings

    ERIC Educational Resources Information Center

    Mahoney, Joseph L.

    2014-01-01

    Although behavioral management is one of the most challenging aspects of working in an afterschool setting, staff do not typically receive formal training in evidence-based approaches to handling children's behavior problems. Common approaches to behavioral management such as punishment or time-out are temporary solutions because they do not…

  14. Input in an Institutional Setting.

    ERIC Educational Resources Information Center

    Bardovi-Harlig, Kathleen; Hartford, Beverly S.

    1996-01-01

    Investigates the nature of input available to learners in the institutional setting of the academic advising session. Results indicate that evidence for the realization of speech acts, positive evidence from peers and status unequals, the effect of stereotypes, and limitations of a learner's pragmatic and grammatical competence are influential…

  15. Conversational Competence in Academic Settings

    ERIC Educational Resources Information Center

    Bowman, Richard F.

    2014-01-01

    Conversational competence is a process, not a state. Ithaca does not exist, only the voyage to Ithaca. Vibrant campuses are a series of productive conversations. At its core, communicative competence in academic settings mirrors a collective search for meaning regarding the purpose and direction of a campus community. Communicative competence…

  16. Ethical Issues in Clinical Settings.

    ERIC Educational Resources Information Center

    Bain, Linda L.; And Others

    1993-01-01

    Four papers on ethical issues in physical education clinical settings are presented: (1) "Ethical Issues in Teaching" (L. Bain); (2) "Ethics in Professional Advising and Academic Counseling of Graduate Students" (G. Roberts); (3) "Ethical Issues in Clinical Services" (R. Singer); and (4) a reaction to the three previous papers by Bonnie Berger.…

  17. Bullying in Early Educational Settings

    ERIC Educational Resources Information Center

    Kirves, Laura; Sajaniemi, Nina

    2012-01-01

    The aim of this research was to study the prevalence of bullying in early educational settings in Finnish kindergartens. In addition, the study investigated whether bullying in kindergartens differs from school bullying and what forms bullying takes among under-school-age children. Two kinds of data were collected for the study: data from a survey…

  18. Informal Learning in Experiential Settings.

    ERIC Educational Resources Information Center

    Neathery, Madelyn Faye

    1998-01-01

    Assesses informal learning in experiential settings. Elementary teachers (n=20) from public and private schools participated in an on-site seminar involving experiential learning in science centers, a wildlife refuge, and a zoological sanctuary. The significance of instruction provided by guides, types of exhibits, and the use of informational…

  19. Teaching Quality across School Settings

    ERIC Educational Resources Information Center

    Cohen, Julie; Brown, Michelle

    2016-01-01

    Districts are increasingly making personnel decisions based on teachers' impact on student-achievement gains and classroom observations. In some schools, however, a teacher's practices and their students' achievement may reflect not just individual but collaborative efforts. In other settings, teachers' instruction benefits less from the insights…

  20. A distributed telerobotics construction set

    NASA Technical Reports Server (NTRS)

    Wise, James D.

    1994-01-01

    During the course of our research on distributed telerobotic systems, we have assembled a collection of generic, reusable software modules and an infrastructure for connecting them to form a variety of telerobotic configurations. This paper describes the structure of this 'Telerobotics Construction Set' and lists some of the components which comprise it.

  1. Criteria for Developing Criteria Sets.

    ERIC Educational Resources Information Center

    Martin, James L.

    Criteria sets are a necessary step in the systematic development of evaluation in education. Evaluation results from the combination of criteria and evidence. There is a need to develop explicit tools for evaluating criteria, similar to those used in evaluating evidence. The formulation of such criteria depends on distinguishing between terms…

  2. "Trap Setting" in Didactic Materials.

    ERIC Educational Resources Information Center

    Urdal, Pamela

    1984-01-01

    Trap setting is a concept based on a psycholinguistic explanation of the acquisition of second language skills emphasizing cognitive and creative processes over the auditory, visual, and imitative. It proposes that opportunities for repeated attempts at solving new problems through constant testing and retesting of creative hypotheses bring the…

  3. Organizational Constraints and Goal Setting

    ERIC Educational Resources Information Center

    Putney, Frederick B.; Wotman, Stephen

    1978-01-01

    Management modeling techniques are applied to setting operational and capital goals using cost analysis techniques in this case study at the Columbia University School of Dental and Oral Surgery. The model was created as a planning tool used in developing a financially feasible operating plan and a 100 percent physical renewal plan. (LBH)

  4. Families & School. Best of "set."

    ERIC Educational Resources Information Center

    Podmore, Valerie N., Ed.; Richards, Llyn, Ed.

    Published to celebrate the United Nations' International Year of the Family, this special issue presents selected articles from "set," a twice yearly journal of research information for teachers. These articles look at the contribution of educational research on the relationships between schools and families, and families and learning in Australia…

  5. Setting Time Limits on Tests

    ERIC Educational Resources Information Center

    van der Linden, Wim J.

    2011-01-01

    It is shown how the time limit on a test can be set to control the probability of a test taker running out of time before completing it. The probability is derived from the item parameters in the lognormal model for response times. Examples of curves representing the probability of running out of time on a test with given parameters as a function…

  6. Communicable Diseases in Childhood Settings.

    ERIC Educational Resources Information Center

    Networks, 1994

    1994-01-01

    This newsletter addresses managing the spread of communicable diseases in childhood settings as well as educational program concerns for children who are HIV infected. Noting that communicable diseases are a source of concern no matter how minor they might appear, the newsletter suggests that it is important for individuals who work with the…

  7. Goal Setting to Achieve Results

    ERIC Educational Resources Information Center

    Newman, Rich

    2012-01-01

    Both districts and individual schools have a very clear set of goals and skills for their students to achieve and master. In fact, except in rare cases, districts and schools develop very detailed goals they wish to pursue. In most cases, unfortunately, only the teachers and staff at a particular school or district-level office are aware of the…

  8. Promoting Literacy in Multilingual Settings

    ERIC Educational Resources Information Center

    Kosonen, Kimmo; Young, Catherine; Malone, Susan

    2006-01-01

    This compilation of resource papers and findings is from a regional workshop on mother-tongue/bilingual literacy programmes for ethnic and linguistic minorities in multilingual settings. It was organized by Asia-Pacific Programme of Education for All (APPEAL), United Nations Educational and Cultural Organization (UNESCO) Bangkok, 6-10 December…

  9. States Set Common Standards, IF...

    ERIC Educational Resources Information Center

    Hill, Richard

    Whether differences in the standards states have set can be explained by something other than regional differences is explored. In addition, a way in which standards can be compared is defined, and the standard of proficiency that seems to be widely shared across the country is illustrated. The Trial State Assessment (TSA) data from the National…

  10. Physics, stability, and dynamics of supply networks.

    PubMed

    Helbing, Dirk; Lämmer, Stefan; Seidel, Thomas; Seba, Pétr; Płatkowski, Tadeusz

    2004-12-01

    We show how to treat supply networks as physical transport problems governed by balance equations and equations for the adaptation of production speeds. Although the nonlinear behavior is different, the linearized set of coupled differential equations is formally related to those of mechanical or electrical oscillator networks. Supply networks possess interesting features due to their complex topology and directed links. We derive analytical conditions for absolute and convective instabilities. The empirically observed "bullwhip effect" in supply chains is explained as a form of convective instability based on resonance effects. Moreover, it is generalized to arbitrary supply networks. Their related eigenvalues are usually complex, depending on the network structure (even without loops). Therefore, their generic behavior is characterized by damped or growing oscillations. We also show that regular distribution networks possess two negative eigenvalues only, but perturbations generate a spectrum of complex eigenvalues. PMID:15697443

  11. Scaling of global input-output networks

    NASA Astrophysics Data System (ADS)

    Liang, Sai; Qi, Zhengling; Qu, Shen; Zhu, Ji; Chiu, Anthony S. F.; Jia, Xiaoping; Xu, Ming

    2016-06-01

    Examining scaling patterns of networks can help understand how structural features relate to the behavior of the networks. Input-output networks consist of industries as nodes and inter-industrial exchanges of products as links. Previous studies consider limited measures for node strengths and link weights, and also ignore the impact of dataset choice. We consider a comprehensive set of indicators in this study that are important in economic analysis, and also examine the impact of dataset choice, by studying input-output networks in individual countries and the entire world. Results show that Burr, Log-Logistic, Log-normal, and Weibull distributions can better describe scaling patterns of global input-output networks. We also find that dataset choice has limited impacts on the observed scaling patterns. Our findings can help examine the quality of economic statistics, estimate missing data in economic statistics, and identify key nodes and links in input-output networks to support economic policymaking.

  12. Zone routing in a torus network

    DOEpatents

    Chen, Dong; Heidelberger, Philip; Kumar, Sameer

    2013-01-29

    A system for routing data in a network comprising a network logic device at a sending node for determining a path between the sending node and a receiving node, wherein the network logic device sets one or more selection bits and one or more hint bits within the data packet, a control register for storing one or more masks, wherein the network logic device uses the one or more selection bits to select a mask from the control register and the network logic device applies the selected mask to the hint bits to restrict routing of the data packet to one or more routing directions for the data packet within the network and selects one of the restricted routing directions from the one or more routing directions and sends the data packet along a link in the selected routing direction toward the receiving node.

  13. Congestion control and avoidance for ATM networks

    NASA Astrophysics Data System (ADS)

    Wu, Chih-Ming

    1997-10-01

    The flow of papers proposing new schemes to cope with congestion in networks continues unabated. In particular as the deployment of ATM networks advances effective congestion control is required to ensure that these networks can effectively provide the wide range of services that they promise. This paper attempts to evaluate whether recently proposed algorithms are likely to be useful in practice using performance simulation and modeling methods. However the performance is very sensitive to the flow control parameters and identifying an appropriate set of parameters is difficult since it depends heavily on the traffic conditions. The aim of this paper described is to broaden the context within which ATM performance is considered, and outline ongoing work in performance evaluation of ATM networks. This paper presents the complete picture for evaluating the properties of congestion control mechanisms including fairness, overhead, data loss and network utilization are described. It is particularly aimed at estimating the effects of recent congestion control schemes for ATM networks.

  14. Super-speed computer interfaces and networks

    SciTech Connect

    Tolmie, D.E.; St. John, W.; DuBois, D.H.

    1997-10-01

    This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Research into super-speed computer interfaces has been directed towards identifying networking requirements from compute-intensive applications that are crucial to DOE programs. In particular, both the DOE Energy Research High Performance Computing Research Centers (HPCRC) and the DOE Defense Programs Accelerated Strategic Computing Initiative (ASCI) have planned applications that will require large increases in network bandwidth. This project was set up to help network researchers identify those networking requirements and to plan the development of such networks. Based on studies, research, and LANL-sponsored workshops, this project helped forge the beginnings for multi-gigabit/sec network research and developments that today is being lead by Los Alamos in the American National Standards Institute (ANSI) 6.4 gigabit/sec specification called HIPPI-6400.

  15. Boolean networks with multiexpressions and parameters.

    PubMed

    Zou, Yi Ming

    2013-01-01

    To model biological systems using networks, it is desirable to allow more than two levels of expression for the nodes and to allow the introduction of parameters. Various modeling and simulation methods addressing these needs using Boolean models, both synchronous and asynchronous, have been proposed in the literature. However, analytical study of these more general Boolean networks models is lagging. This paper aims to develop a concise theory for these different Boolean logic-based modeling methods. Boolean models for networks where each node can have more than two levels of expression and Boolean models with parameters are defined algebraically with examples provided. Certain classes of random asynchronous Boolean networks and deterministic moduli asynchronous Boolean networks are investigated in detail using the setting introduced in this paper. The derived theorems provide a clear picture for the attractor structures of these asynchronous Boolean networks.

  16. The Sun Sets on Mars

    NASA Technical Reports Server (NTRS)

    2004-01-01

    On Sol 20 of its journey, Mars Exploration Rover Opportunity woke up around 5:30 in the martian afternoon to watch the sunset. A series of five sets of three-color images from the rover's panoramic camera was acquired looking toward the southwest. Each set used an infrared, green and violet filter, rather than the human red-green-blue, so that the maximum panoramic camera wavelength range could be covered by the observations, enhancing the scientific value of the measurements.

    A color image was made from the first post-sunset sequence of calibrated color images, with the color balance set to approximate what the sunset color would have looked like to the human eye. The color seen in this first post-sunset image was then used to colorize each image in the sequence. Approximately one-minute gaps between consecutive color images meant the Sun's position changed within each color set, so the images had to be manually shifted to compensate for this motion. In this fashion, the position and brightness of the Sun are taken from each individual image, but the color is taken from a single set of images. The images were then combined into a movie where one color set fades gracefully into the next. Analysis of the five color sets shows that there were only small color variations during the sunset, so most of the real variations are captured in the movie.

    The rapid dimming of the Sun near the horizon is due to the dust in the sky. There is nearly twice as much dust as there was when the Mars Pathfinder spacecraft, which landed on Mars in 1997, imaged the sunset. This causes the Sun to be many times fainter. The sky above the Sun has the same blue tint observed by Pathfinder and also by Viking, which landed on Mars in 1976. This is because dust in the martian atmosphere scatters blue light forward toward the observer much more efficiently than it scatters red light forward. Therefore, a 'halo' of blueish sky color is always observed close to the Sun. We're only seeing

  17. Building a Smartphone Seismic Network

    NASA Astrophysics Data System (ADS)

    Kong, Q.; Allen, R. M.

    2013-12-01

    We are exploring to build a new type of seismic network by using the smartphones. The accelerometers in smartphones can be used to record earthquakes, the GPS unit can give an accurate location, and the built-in communication unit makes the communication easier for this network. In the future, these smartphones may work as a supplement network to the current traditional network for scientific research and real-time applications. In order to build this network, we developed an application for android phones and server to record the acceleration in real time. These records can be sent back to a server in real time, and analyzed at the server. We evaluated the performance of the smartphone as a seismic recording instrument by comparing them with high quality accelerometer while located on controlled shake tables for a variety of tests, and also the noise floor test. Based on the daily human activity data recorded by the volunteers and the shake table tests data, we also developed algorithm for the smartphones to detect earthquakes from daily human activities. These all form the basis of setting up a new prototype smartphone seismic network in the near future.

  18. Bond Percolation on Multiplex Networks

    NASA Astrophysics Data System (ADS)

    Hackett, A.; Cellai, D.; Gómez, S.; Arenas, A.; Gleeson, J. P.

    2016-04-01

    We present an analytical approach for bond percolation on multiplex networks and use it to determine the expected size of the giant connected component and the value of the critical bond occupation probability in these networks. We advocate the relevance of these tools to the modeling of multilayer robustness and contribute to the debate on whether any benefit is to be yielded from studying a full multiplex structure as opposed to its monoplex projection, especially in the seemingly irrelevant case of a bond occupation probability that does not depend on the layer. Although we find that in many cases the predictions of our theory for multiplex networks coincide with previously derived results for monoplex networks, we also uncover the remarkable result that for a certain class of multiplex networks, well described by our theory, new critical phenomena occur as multiple percolation phase transitions are present. We provide an instance of this phenomenon in a multiplex network constructed from London rail and European air transportation data sets.

  19. Hypothesis generation in signaling networks.

    PubMed

    Ruths, Derek A; Nakhleh, Luay; Iyengar, M Sriram; Reddy, Shrikanth A G; Ram, Prahlad T

    2006-11-01

    Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.

  20. Lagged correlation networks

    NASA Astrophysics Data System (ADS)

    Curme, Chester

    Technological advances have provided scientists with large high-dimensional datasets that describe the behaviors of complex systems: from the statistics of energy levels in complex quantum systems, to the time-dependent transcription of genes, to price fluctuations among assets in a financial market. In this environment, where it may be difficult to infer the joint distribution of the data, network science has flourished as a way to gain insight into the structure and organization of such systems by focusing on pairwise interactions. This work focuses on a particular setting, in which a system is described by multivariate time series data. We consider time-lagged correlations among elements in this system, in such a way that the measured interactions among elements are asymmetric. Finally, we allow these interactions to be characteristically weak, so that statistical uncertainties may be important to consider when inferring the structure of the system. We introduce a methodology for constructing statistically validated networks to describe such a system, extend the methodology to accommodate interactions with a periodic component, and show how consideration of bipartite community structures in these networks can aid in the construction of robust statistical models. An example of such a system is a financial market, in which high frequency returns data may be used to describe contagion, or the spreading of shocks in price among assets. These data provide the experimental testing ground for our methodology. We study NYSE data from both the present day and one decade ago, examine the time scales over which the validated lagged correlation networks exist, and relate differences in the topological properties of the networks to an increasing economic efficiency. We uncover daily periodicities in the validated interactions, and relate our findings to explanations of the Epps Effect, an empirical phenomenon of financial time series. We also study bipartite community

  1. Network device interface for digitally interfacing data channels to a controller via a network

    NASA Technical Reports Server (NTRS)

    Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor)

    2004-01-01

    The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

  2. Network device interface for digitally interfacing data channels to a controller via a network

    NASA Technical Reports Server (NTRS)

    Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor)

    2005-01-01

    The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

  3. Why Network? Theoretical Perspectives on Networking

    ERIC Educational Resources Information Center

    Muijs, Daniel; West, Mel; Ainscow, Mel

    2010-01-01

    In recent years, networking and collaboration have become increasingly popular in education. However, there is at present a lack of attention to the theoretical basis of networking, which could illuminate when and when not to network and under what conditions networks are likely to be successful. In this paper, we will attempt to sketch the…

  4. P-hub protection models for survivable hub network design

    NASA Astrophysics Data System (ADS)

    Kim, Hyun

    2012-10-01

    The design of survivable networks has been a significant issue in network-based infrastructure in transportation, electric power systems, and telecommunications. In telecommunications networks, hubs and backbones are the most critical assets to be protected from any network failure because many network flows use these facilities, resulting in an intensive concentration of flows at these facilities. This paper addresses a series of new hub and spoke network models as survivable network designs, which are termed p- hub protection models (PHPRO). The PHPRO aim to build networks that maximize the total potential interacting traffic over a set of origin-destination nodes based on different routing assumptions, including multiple assignments and back-up hub routes with distance restrictions. Empirical analyses are presented using telecommunication networks in the United States, and the vulnerabilities of networks based on possible disruption scenarios are examined. The results reveal that PROBA, the model with a back-up routing scheme, considerably enhances the network resilience and even the network performance, indicating that the model is a candidate for a strong survivable hub network design. An extension, PROBA-D, also shows that applying a distance restriction can be strategically used for designing back-up hub routes if a network can trade off between network performance and network cost, which results from the reduced length of back-up routings.

  5. A new formulation for feedforward neural networks.

    PubMed

    Razavi, Saman; Tolson, Bryan A

    2011-10-01

    Feedforward neural network is one of the most commonly used function approximation techniques and has been applied to a wide variety of problems arising from various disciplines. However, neural networks are black-box models having multiple challenges/difficulties associated with training and generalization. This paper initially looks into the internal behavior of neural networks and develops a detailed interpretation of the neural network functional geometry. Based on this geometrical interpretation, a new set of variables describing neural networks is proposed as a more effective and geometrically interpretable alternative to the traditional set of network weights and biases. Then, this paper develops a new formulation for neural networks with respect to the newly defined variables; this reformulated neural network (ReNN) is equivalent to the common feedforward neural network but has a less complex error response surface. To demonstrate the learning ability of ReNN, in this paper, two training methods involving a derivative-based (a variation of backpropagation) and a derivative-free optimization algorithms are employed. Moreover, a new measure of regularization on the basis of the developed geometrical interpretation is proposed to evaluate and improve the generalization ability of neural networks. The value of the proposed geometrical interpretation, the ReNN approach, and the new regularization measure are demonstrated across multiple test problems. Results show that ReNN can be trained more effectively and efficiently compared to the common neural networks and the proposed regularization measure is an effective indicator of how a network would perform in terms of generalization.

  6. Statistical physics of complex networks

    NASA Astrophysics Data System (ADS)

    Xie, Huafeng

    Rank algorithm to a new ranking method, CiteRank, in which the starting point of random surfers is exponentially biased towards more recent publications. The ranking results are compared for two rather different citation networks: all American Physical Society publications between 1893 and 2003 and the set of high energy physics theory (hep-th) preprints. Despite major differences between these two networks, we find that their optimal parameters of the CiteRank algorithm are remarkably similar.

  7. Minimum network constraint on reverse engineering to develop biological regulatory networks.

    PubMed

    Shao, Bin; Wu, Jiayi; Tian, Binghui; Ouyang, Qi

    2015-09-01

    Reconstructing the topological structure of biological regulatory networks from microarray expression data or data of protein expression profiles is one of major tasks in systems biology. In recent years, various mathematical methods have been developed to meet this task. Here, based on our previously reported reverse engineering method, we propose a new constraint, i.e., the minimum network constraint, to facilitate the reconstruction of biological networks. Three well studied regulatory networks (the budding yeast cell cycle network, the fission yeast cell cycle network, and the SOS network of Escherichia coli) were used as the test sets to verify the performance of this method. Numerical results show that the biological networks prefer to use the minimal networks to fulfill their functional tasks, making it possible to apply minimal network criteria in the network reconstruction process. Two scenarios were considered in the reconstruction process: generating data using different initial conditions; and generating data from knock out and over-expression experiments. In both cases, network structures are revealed faithfully in a few steps using our approach.

  8. Cross-Species Network Analysis Uncovers Conserved Nitrogen-Regulated Network Modules in Rice1[OPEN

    PubMed Central

    Obertello, Mariana; Shrivastava, Stuti; Katari, Manpreet S.; Coruzzi, Gloria M.

    2015-01-01

    In this study, we used a cross-species network approach to uncover nitrogen (N)-regulated network modules conserved across a model and a crop species. By translating gene network knowledge from the data-rich model Arabidopsis (Arabidopsis thaliana) to a crop, rice (Oryza sativa), we identified evolutionarily conserved N-regulatory modules as targets for translational studies to improve N use efficiency in transgenic plants. To uncover such conserved N-regulatory network modules, we first generated an N-regulatory network based solely on rice transcriptome and gene interaction data. Next, we enhanced the network knowledge in the rice N-regulatory network using transcriptome and gene interaction data from Arabidopsis and new data from Arabidopsis and rice plants exposed to the same N treatment conditions. This cross-species network analysis uncovered a set of N-regulated transcription factors (TFs) predicted to target the same genes and network modules in both species. Supernode analysis of the TFs and their targets in these conserved network modules uncovered genes directly related to N use (e.g. N assimilation) and to other shared biological processes indirectly related to N. This cross-species network approach was validated with members of two TF families in the supernode network, BASIC-LEUCINE ZIPPER TRANSCRIPTION FACTOR1-TGA and HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY ROOT SHORTENING1 (HRS1)/HRS1 Homolog family, which have recently been experimentally validated to mediate the N response in Arabidopsis. PMID:26045464

  9. Integrated network design and scheduling problems :

    SciTech Connect

    Nurre, Sarah G.; Carlson, Jeffrey J.

    2014-01-01

    We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

  10. NASA Ocean Altimeter Pathfinder Project. Report 2; Data Set Validation

    NASA Technical Reports Server (NTRS)

    Koblinsky, C. J.; Ray, Richard D.; Beckley, Brian D.; Bremmer, Anita; Tsaoussi, Lucia S.; Wang, Yan-Ming

    1999-01-01

    The NOAA/NASA Pathfinder program was created by the Earth Observing System (EOS) Program Office to determine how existing satellite-based data sets can be processed and used to study global change. The data sets are designed to be long time-series data processed with stable calibration and community consensus algorithms to better assist the research community. The Ocean Altimeter Pathfinder Project involves the reprocessing of all altimeter observations with a consistent set of improved algorithms, based on the results from TOPEX/POSEIDON (T/P), into easy-to-use data sets for the oceanographic community for climate research. Details are currently presented in two technical reports: Report# 1: Data Processing Handbook Report #2: Data Set Validation This report describes the validation of the data sets against a global network of high quality tide gauge measurements and provides an estimate of the error budget. The first report describes the processing schemes used to produce the geodetic consistent data set comprised of SEASAT, GEOSAT, ERS-1, TOPEX/ POSEIDON, and ERS-2 satellite observations.

  11. Design principles in biological networks

    NASA Astrophysics Data System (ADS)

    Goyal, Sidhartha

    Much of biology emerges from networks of interactions. Even in a single bacterium such as Escherichia coli, there are hundreds of coexisting gene and protein networks. Although biological networks are the outcome of evolution, various physical and biological constraints limit their functional capacity. The focus of this thesis is to understand how functional constraints such as optimal growth in mircoorganisms and information flow in signaling pathways shape the metabolic network of bacterium E. coli and the quorum sensing network of marine bacterium Vibrio harveyi, respectively. Metabolic networks convert basic elemental sources into complex building-blocks eventually leading to cell's growth. Therefore, typically, metabolic pathways are often coupled both by the use of a common substrate and by stoichiometric utilization of their products for cell growth. We showed that such a coupled network with product-feedback inhibition may exhibit limit-cycle oscillations which arise via a Hopf bifurcation. Furthermore, we analyzed several representative metabolic modules and find that, in all cases, simple product-feedback inhibition allows nearly optimal growth, in agreement with the predicted growth-rate by the flux-balance analysis (FBA). Bacteria have fascinating and diverse social lives. They display coordinated group behaviors regulated by quorum sensing (QS) systems. The QS circuit of V. harveyi integrates and funnels different ecological information through a common phosphorelay cascade to a set of small regulatory RNAs (sRNAs) that enables collective behavior. We analyzed the signaling properties and information flow in the QS circuit, which provides a model for information flow in signaling networks more generally. A comparative study of post-transcriptional and conventional transcriptional regulation suggest a niche for sRNAs in allowing cells to transition quickly yet reliably between distinct states. Furthermore, we develop a new framework for analyzing signal

  12. Coordinating Networks of Robotic Observatories

    NASA Astrophysics Data System (ADS)

    Mason, C. L.

    1993-12-01

    This abstract describes our project on scheduling for networks of remote robotic telescopes. The project is being developed as part of our larger goal to build automated tools to address the complete life-cycle of an observation request, from electronic transmission of the observation request to the return of raw and reduced data, using the Automatic Telescope Instruction Set, or ATIS. With distributed artificial intelligence (DAI) software techniques, we have designed a network scheduling system as a collection of distributed, cooperating scheduling agents. Each agent is responsible for the scheduling of observation requests for one robotic telescope. This perspective allows the network scheduling system to preserve the individualized priorities and policies that may exist for any one telescope while promoting the collaborative behavior required for acquiring and providing telescope time in a network. We are interested in heterogeneous networks that are made by connecting pre-existing fully automated remote telescopes. Providers of telescopes are anyone with a fully automated telescope and telecommunication capabilities. In essence, the network system is created by interconnecting multiple stand-alone systems. The scheduling software for each stand-alone system (or agent) is based on two primary components: an advanced scheduling system, CERES, that employs look-ahead contingent scheduling methods, and a collaborator, that communicates with other agents in the network, both written in C and Lisp. Cooperation among agents is based on the premise that astronomers at one telescope are often willing to trade for time on another telescope. In general, agents are autonomous but may react cooperatively to observational requests communicated by other scheduling agents. Our work involves engineering the protocols for cooperation, and the development of a programming language and agent architecture to express such protocols. The system is being constructed with the help of

  13. Diagnosing Anomalous Network Performance with Confidence

    SciTech Connect

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

    2011-04-01

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

  14. Measuring and modeling correlations in multiplex networks.

    PubMed

    Nicosia, Vincenzo; Latora, Vito

    2015-09-01

    The interactions among the elementary components of many complex systems can be qualitatively different. Such systems are therefore naturally described in terms of multiplex or multilayer networks, i.e., networks where each layer stands for a different type of interaction between the same set of nodes. There is today a growing interest in understanding when and why a description in terms of a multiplex network is necessary and more informative than a single-layer projection. Here we contribute to this debate by presenting a comprehensive study of correlations in multiplex networks. Correlations in node properties, especially degree-degree correlations, have been thoroughly studied in single-layer networks. Here we extend this idea to investigate and characterize correlations between the different layers of a multiplex network. Such correlations are intrinsically multiplex, and we first study them empirically by constructing and analyzing several multiplex networks from the real world. In particular, we introduce various measures to characterize correlations in the activity of the nodes and in their degree at the different layers and between activities and degrees. We show that real-world networks exhibit indeed nontrivial multiplex correlations. For instance, we find cases where two layers of the same multiplex network are positively correlated in terms of node degrees, while other two layers are negatively correlated. We then focus on constructing synthetic multiplex networks, proposing a series of models to reproduce the correlations observed empirically and/or to assess their relevance. PMID:26465526

  15. Cross-linked structure of network evolution

    SciTech Connect

    Bassett, Danielle S.; Wymbs, Nicholas F.; Grafton, Scott T.; Porter, Mason A.; Mucha, Peter J.

    2014-03-15

    We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks.

  16. Measuring and modeling correlations in multiplex networks

    NASA Astrophysics Data System (ADS)

    Nicosia, Vincenzo; Latora, Vito

    2015-09-01

    The interactions among the elementary components of many complex systems can be qualitatively different. Such systems are therefore naturally described in terms of multiplex or multilayer networks, i.e., networks where each layer stands for a different type of interaction between the same set of nodes. There is today a growing interest in understanding when and why a description in terms of a multiplex network is necessary and more informative than a single-layer projection. Here we contribute to this debate by presenting a comprehensive study of correlations in multiplex networks. Correlations in node properties, especially degree-degree correlations, have been thoroughly studied in single-layer networks. Here we extend this idea to investigate and characterize correlations between the different layers of a multiplex network. Such correlations are intrinsically multiplex, and we first study them empirically by constructing and analyzing several multiplex networks from the real world. In particular, we introduce various measures to characterize correlations in the activity of the nodes and in their degree at the different layers and between activities and degrees. We show that real-world networks exhibit indeed nontrivial multiplex correlations. For instance, we find cases where two layers of the same multiplex network are positively correlated in terms of node degrees, while other two layers are negatively correlated. We then focus on constructing synthetic multiplex networks, proposing a series of models to reproduce the correlations observed empirically and/or to assess their relevance.

  17. Caseview: building the reference set.

    PubMed

    Lévy, Pierre P

    2004-01-01

    There is a worldwide consensus for using the diagnosis related groups (DRG) when considering hospital activity. This tool leads to the production of tables of numbers (case mix), the interpretation of which is difficult. Therefore, methods aimed at facilitating this interpretation are needed. One of such methods is the case view, i.e. a graphical representation of the case mix. It reduces, in a way, each DRG to a "pixel", the set of the DRGs being an image (the case view). The reference set should be organized according to three criteria: medical/surgical, nosological and economic. This method can be used to answer theoretical questions or to visualize activity at the level of a hospital or at the level of a department. The purpose of this paper is to present important principles inherent in this graphic representation, both at the level of the method and at the level of the user.

  18. Optical set-reset latch

    DOEpatents

    Skogen, Erik J.

    2013-01-29

    An optical set-reset (SR) latch is formed from a first electroabsorption modulator (EAM), a second EAM and a waveguide photodetector (PD) which are arranged in an optical and electrical feedback loop which controls the transmission of light through the first EAM to latch the first EAM in a light-transmissive state in response to a Set light input. A second waveguide PD controls the transmission of light through the second EAM and is used to switch the first EAM to a light-absorptive state in response to a Reset light input provided to the second waveguide PD. The optical SR latch, which may be formed on a III-V compound semiconductor substrate (e.g. an InP or a GaAs substrate) as a photonic integrated circuit (PIC), stores a bit of optical information and has an optical output for the logic state of that bit of information.

  19. Communications Network

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The Multi-Compatible Network Interface Unit (MCNIU) is intended to connect the space station's communications and tracking, guidance and navigation, life support, electric power, payload data, hand controls, display consoles and other systems, and also communicate with diverse processors. Honeywell is now marketing MCNIU commercially. It has applicability in certain military operations or civil control centers. It has nongovernment utility among large companies, universities and research organizations that transfer large amounts of data among workstations and computers. *This product is no longer commercially available.

  20. Less than a Class Set

    ERIC Educational Resources Information Center

    Bennett, Kristin Redington

    2012-01-01

    The iPad holds amazing potential for classroom use. Just a few--or even only one--is enough to get results. Having a class set promotes traditional, whole-class instruction, but fewer iPads facilitate individualized and tailored instruction. In this article, the author discusses the potential of the iPad and suggests ways to put the iPad to use in…

  1. [Networks in cognitive research].

    PubMed

    Pléh, Csaba

    2012-01-01

    This review paper starts from discussing two models of network research: one starting from general networks, the other starting from the Ego. Ego based researches are characterized starting form the model of Dunbar as presenting networks of different size and intimacy, both in real and virtual networks. Researches into the personality determinants of networks mainly shows the effects of extroversion. The future of network research indicates a trend towards relating personal, conceptual, and neural networks.

  2. Electrical contact tool set station

    DOEpatents

    Byers, M.E.

    1988-02-22

    An apparatus is provided for the precise setting to zero of electrically conductive cutting tools used in the machining of work pieces. An electrically conductive cylindrical pin, tapered at one end to a small flat, rests in a vee-shaped channel in a base so that its longitudinal axis is parallel to the longitudinal axis of the machine's spindle. Electronic apparatus is connected between the cylindrical pin and the electrically conductive cutting tool to produce a detectable signal when contact between tool and pin is made. The axes of the machine are set to zero by contact between the cutting tool and the sides, end or top of the cylindrical pin. Upon contact, an electrical circuit is completed, and the detectable signal is produced. The tool can then be set to zero for that axis. Should the tool contact the cylindrical pin with too much force, the cylindrical pin would be harmlessly dislodged from the vee-shaped channel, preventing damage either to the cutting tool or the cylindrical pin. 5 figs.

  3. Examining the amenability of urban street networks for locating facilities

    NASA Astrophysics Data System (ADS)

    Zhang, Tong; Zeng, Zhe; Jia, Tao; Li, Jing

    2016-09-01

    This paper aims to characterize urban street networks from the perspective of facility location that is widely used for siting public or private services. Both topological and geometrical features of urban street networks are investigated to examine their impacts on the performance of facility location. We propose a set of efficiency and centrality measures to evaluate the amenability of street networks for locating facilities. The evaluation of 15 large cities in the U.S. reveals that facility locations are strongly affected by road network structures. For realistic street networks, grid planned road network are more amenable to locating facilities than irregular networks. The analyses on idealized network offer further evidence of the correlations between network properties and service provision efficiencies.

  4. Multi-scale modularity and motif distributional effect in metabolic networks.

    PubMed

    Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

    2016-01-01

    Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks.

  5. Simple models of human brain functional networks.

    PubMed

    Vértes, Petra E; Alexander-Bloch, Aaron F; Gogtay, Nitin; Giedd, Jay N; Rapoport, Judith L; Bullmore, Edward T

    2012-04-10

    Human brain functional networks are embedded in anatomical space and have topological properties--small-worldness, modularity, fat-tailed degree distributions--that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.

  6. Community Seismic Network (CSN)

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    We report on developments in sensor connectivity, architecture, and data fusion algorithms executed in Cloud computing systems in the Community Seismic Network (CSN), a network of low-cost sensors housed in homes and offices by volunteers in the Pasadena, CA area. The network has over 200 sensors continuously reporting anomalies in local acceleration through the Internet to a Cloud computing service (the Google App Engine) that continually fuses sensor data to rapidly detect shaking from earthquakes. The Cloud computing system consists of data centers geographically distributed across the continent and is likely to be resilient even during earthquakes and other local disasters. The region of Southern California is partitioned in a multi-grid style into sets of telescoping cells called geocells. Data streams from sensors within a geocell are fused to detect anomalous shaking across the geocell. Temporal spatial patterns across geocells are used to detect anomalies across regions. The challenge is to detect earthquakes rapidly with an extremely low false positive rate. We report on two data fusion algorithms, one that tessellates the surface so as to fuse data from a large region around Pasadena and the other, which uses a standard tessellation of equal-sized cells. Since September 2011, the network has successfully detected earthquakes of magnitude 2.5 or higher within 40 Km of Pasadena. In addition to the standard USB device, which connects to the host's computer, we have developed a stand-alone sensor that directly connects to the internet via Ethernet or wifi. This bypasses security concerns that some companies have with the USB-connected devices, and allows for 24/7 monitoring at sites that would otherwise shut down their computers after working hours. In buildings we use the sensors to model the behavior of the structures during weak events in order to understand how they will perform during strong events. Visualization models of instrumented buildings ranging

  7. On the design of artificial auto-associative neuronal networks.

    PubMed

    Reimann, Stefan

    1998-06-01

    In this paper, we consider the problem of how to construct an artificial neuronal network such that it reproduces a given set of patterns in an exact manner. It turns out that the structure of the weight matrix of the network represents the structure of the set of patterns it is acting on, not the patterns themselves. Conditions are discussed under which the associative network memorizes a certain subset of these patterns. Our formal approach is based on the simple observation that neural networks are structured sets of neurons. By regarding recurrent neural networks as dynamical systems with symmetry, the category of G-sets and G-morphisms appears as a natural framework for evaluating their structure and functioning analytically.

  8. Standardization for Body Area Networks

    NASA Astrophysics Data System (ADS)

    Astrin, Arthur W.; Li, Huan-Bang; Kohno, Ryuji

    Body Area Networks (BAN) can provide a wide range of applications including medical support, healthcare monitoring, and consumer electronics with increased convenience or comfort. To harmonize with the strong demands from both medical and healthcare societies, and information and communications technology (ICT) industries, IEEE 802.15.6 task group (TG6) was set up to develop an IEEE wireless standard on BAN. This paper presents a general guidance to TG6. Some pre-works to set up TG6 are reviewed. The objectives, main topics, current status are described in details.

  9. Insufficient depression treatment in outpatient settings

    PubMed Central

    Schneider, Frank; Kratz, Sandra; Bermejo, Isaac; Menke, Ralph; Mulert, Christoph; Hegerl, Ulrich; Berger, Mathias; Gaebel, Wolfgang; Härter, Martin

    2004-01-01

    Background: The present status of outpatient treatment of depression in Germany was evaluated with respect to the adherence of general practitioners (GPs) and specialists of psychiatry to clinical practice guidelines. Methods: In total, 488 depressed patients' psychopathology, diagnostic assessment, therapeutic measures and referral frequency were documented at inclusion into study by 43 general practitioners and 23 specialists of psychiatry in three regions of Germany. The investigation of change in depressive symptoms after six to eight weeks by means of self-assessment could be evaluated for 165 patients. Results: The results of diagnostic assessment demonstrated that diagnoses of depression were not always based on the diagnostic criteria for depression (ICD-10): 33% of GPs' and 17% of specialists' patients were included as depressed patients into the study despite not fulfilling the ICD-10 criteria in the standardized documentation. Therapeutic undertreatment was more often found in the group of GPs. Referrals were found not to be oriented towards guidelines. After six to eight weeks, one half of patients reported a reduction in depressed symptoms, the other half of patients reported a stagnation or even a progression. Conclusions: The study has shown that physicians in outpatient settings still fail to orient themselves towards guideline recommendations. This reflects the need for physicians to receive guideline training, with the aim of improving the quality of care for depression. A quality management intervention program consisting of guideline training and an interdisciplinary quality circle to improve depression treatment and networking was supported by the authors and is currently being evaluated. PMID:19675684

  10. Robustness of a Network of Networks

    NASA Astrophysics Data System (ADS)

    Gao, Jianxi; Buldyrev, Sergey V.; Stanley, H. Eugene; Havlin, Shlomo

    2012-02-01

    Network research has been focused on studying the properties of a single isolated network, which rarely exists. We develop a general analytical framework for studying percolation of n interdependent networks. We illustrate our analytical solutions for three examples: (i) For any tree of n fully dependent Erdos-R'enyi (ER) networks, each of average degree k, we find that the giant component P∞=p[1-(-kP∞)]^n where 1 - p is the initial fraction of removed nodes. This general result coincides for n = 1 with the known second-order phase transition for a single network. For any n>1 cascading failures occur and the percolation becomes an abrupt first-order transition. (ii) For a starlike network of n partially interdependent ER networks, P∞ depends also on the topology--in contrast to case (i). (iii) For a looplike network formed by n partially dependent ER networks, P∞ is independent of n.

  11. Fuzzy associative conjuncted maps network.

    PubMed

    Goh, Hanlin; Lim, Joo-Hwee; Quek, Chai

    2009-08-01

    The fuzzy associative conjuncted maps (FASCOM) is a fuzzy neural network that associates data of nonlinearly related inputs and outputs. In the network, each input or output dimension is represented by a feature map that is partitioned into fuzzy or crisp sets. These fuzzy sets are then conjuncted to form antecedents and consequences, which are subsequently associated to form if-then rules. The associative memory is encoded through an offline batch mode learning process consisting of three consecutive phases. The initial unsupervised membership function initialization phase takes inspiration from the organization of sensory maps in our brains by allocating membership functions based on uniform information density. Next, supervised Hebbian learning encodes synaptic weights between input and output nodes. Finally, a supervised error reduction phase fine-tunes the network, which allows for the discovery of the varying levels of influence of each input dimension across an output feature space in the encoded memory. In the series of experiments, we show that each phase in the learning process contributes significantly to the final accuracy of prediction. Further experiments using both toy problems and real-world data demonstrate significant superiority in terms of accuracy of nonlinear estimation when benchmarked against other prominent architectures and exhibit the network's suitability to perform analysis and prediction on real-world applications, such as traffic density prediction as shown in this paper.

  12. Technologies for Networked Enabled Operations

    NASA Technical Reports Server (NTRS)

    Glass, B.; Levine, J.

    2005-01-01

    Current point-to-point data links will not scale to support future integration of surveillance, security, and globally-distributed air traffic data, and already hinders efficiency and capacity. While the FAA and industry focus on a transition to initial system-wide information management (SWIM) capabilities, this paper describes a set of initial studies of NAS network-enabled operations technology gaps targeted for maturity in later SWIM spirals (201 5-2020 timeframe).

  13. Extraction of Martian valley networks from digital topography

    NASA Technical Reports Server (NTRS)

    Stepinski, T. F.; Collier, M. L.

    2004-01-01

    We have developed a novel method for delineating valley networks on Mars. The valleys are inferred from digital topography by an autonomous computer algorithm as drainage networks, instead of being manually mapped from images. Individual drainage basins are precisely defined and reconstructed to restore flow continuity disrupted by craters. Drainage networks are extracted from their underlying basins using the contributing area threshold method. We demonstrate that such drainage networks coincide with mapped valley networks verifying that valley networks are indeed drainage systems. Our procedure is capable of delineating and analyzing valley networks with unparalleled speed and consistency. We have applied this method to 28 Noachian locations on Mars exhibiting prominent valley networks. All extracted networks have a planar morphology similar to that of terrestrial river networks. They are characterized by a drainage density of approx.0.1/km, low in comparison to the drainage density of terrestrial river networks. Slopes of "streams" in Martian valley networks decrease downstream at a slower rate than slopes of streams in terrestrial river networks. This analysis, based on a sizable data set of valley networks, reveals that although valley networks have some features pointing to their origin by precipitation-fed runoff erosion, their quantitative characteristics suggest that precipitation intensity and/or longevity of past pluvial climate were inadequate to develop mature drainage basins on Mars.

  14. Minimal test set for stuck-at faults in VLSI

    NASA Technical Reports Server (NTRS)

    Shamanna, M.; Whitaker, S.

    1990-01-01

    Minimal test sets have the property that each input vector simultaneously tests several faults in a network. Existing techniques to determine a minimal set of detection tests rely heavily on complicated algebraic techniques. In this paper, two new methods are presented which do not require Boolean algebra or Karnaugh maps. The first is a graphical approach using fault folding graphs. The second is a design by inspection technique. This work follows the unique approach of first finding all the faults that can be detected by a single test. This tremendously reduces the work required to determine a minimal test set. The design by inspection method could be automated for programmatic generation of minimal stuck-at fault tests.

  15. A network dynamics approach to chemical reaction networks

    NASA Astrophysics Data System (ADS)

    van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

    2016-04-01

    A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

  16. Nested Neural Networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1992-01-01

    Report presents analysis of nested neural networks, consisting of interconnected subnetworks. Analysis based on simplified mathematical models more appropriate for artificial electronic neural networks, partly applicable to biological neural networks. Nested structure allows for retrieval of individual subpatterns. Requires fewer wires and connection devices than fully connected networks, and allows for local reconstruction of damaged subnetworks without rewiring entire network.

  17. Quantum gate-set tomography

    NASA Astrophysics Data System (ADS)

    Blume-Kohout, Robin

    2014-03-01

    Quantum information technology is built on (1) physical qubits and (2) precise, accurate quantum logic gates that transform their states. Developing quantum logic gates requires good characterization - both in the development phase, where we need to identify a device's flaws so as to fix them, and in the production phase, where we need to make sure that the device works within specs and predict residual error rates and types. This task falls to quantum state and process tomography. But until recently, protocols for tomography relied on a pre-existing and perfectly calibrated reference frame comprising the measurements (and, for process tomography, input states) used to characterize the device. In practice, these measurements are neither independent nor perfectly known - they are usually implemented via exactly the same gates that we are trying to characterize! In the past year, several partial solutions to this self-consistency problem have been proposed. I will present a framework (gate set tomography, or GST) that addresses and resolves this problem, by self-consistently characterizing an entire set of quantum logic gates on a black-box quantum device. In particular, it contains an explicit closed-form protocol for linear-inversion gate set tomography (LGST), which is immune to both calibration error and technical pathologies like local maxima of the likelihood (which plagued earlier methods). GST also demonstrates significant (multiple orders of magnitude) improvements in efficiency over standard tomography by using data derived from long sequences of gates (much like randomized benchmarking). GST has now been applied to qubit devices in multiple technologies. I will present and discuss results of GST experiments in technologies including a single trapped-ion qubit and a silicon quantum dot qubit. Sandia National Laboratories is a multiprogram laboratory operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U

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

    SciTech Connect

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

    2012-09-11

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

  19. Constellations and Networks

    NASA Astrophysics Data System (ADS)

    Greenwald, R. A.

    2013-12-01

    Constellations and Networks Prior to the late 1970's, most satellites probing the Earth's upper atmosphere, ionosphere, and magnetosphere and most ground-based experiments measuring the upper atmosphere and ionosphere provided uncoordinated, localized measurements of different regions of the Earth's near-space environment with the objective of determining their basic properties. These measurements showed that the magnetosphere was divided into a number of regions, each containing plasmas with different properties and varying concentrations of energetic particles. By the mid 1970's, this discovery phase of the various regions of the Earth's magnetosphere had essentially been completed. The next step was to understand how the various plasma domains of the magnetosphere and ionosphere were coupled into a complex plasma system and how energy flowed through this system from the solar wind to the upper atmosphere. To achieve this goal, satellite missions sponsored by NASA, ESA, and ISAS became more complex beginning with ISEE and extending to ISTP, Cluster, and many others. Specifically, the research effort evolved into coordinated multipoint measurements provided by constellations of spacecraft, all with on-board propulsion and station-keeping capability. During the same period, other scientific funding agencies in many countries supplemented the satellite-based research effort with the development of ground-based instrumentation networks capable of remote sensing the ionosphere and upper atmosphere. These networks provide measurements that complement the satellite data sets by providing large-scale contextual views of the state of the ionosphere and magnetically conjugate determinations of important physical parameters such as ionospheric electric fields and current systems. In this paper I discuss several of these ground-based networks and highlight research areas where they have made important contributions to satellite constellation missions as well as other topic

  20. MAXIMUM LIKELIHOOD ESTIMATION FOR SOCIAL NETWORK DYNAMICS

    PubMed Central

    Snijders, Tom A.B.; Koskinen, Johan; Schweinberger, Michael

    2014-01-01

    A model for network panel data is discussed, based on the assumption that the observed data are discrete observations of a continuous-time Markov process on the space of all directed graphs on a given node set, in which changes in tie variables are independent conditional on the current graph. The model for tie changes is parametric and designed for applications to social network analysis, where the network dynamics can be interpreted as being generated by choices made by the social actors represented by the nodes of the graph. An algorithm for calculating the Maximum Likelihood estimator is presented, based on data augmentation and stochastic approximation. An application to an evolving friendship network is given and a small simulation study is presented which suggests that for small data sets the Maximum Likelihood estimator is more efficient than the earlier proposed Method of Moments estimator. PMID:25419259

  1. Setting yourself up for success

    NASA Astrophysics Data System (ADS)

    2016-04-01

    So, as the school year is ending, are you just trying to survive your "season" or are you thinking ahead and preparing yourself for a great next season? I want to encourage you to consider the steps you should take now to set yourself up for success next year and beyond. By establishing a few timely habits, you can come into the next school year in a much better position. Some habits are simply keeping track of what happens this year so you can repeat the good and toss the bad. Others involve maintaining a dedication to lifelong learning.

  2. Consecutive projections onto convex sets.

    PubMed

    Degenhard, A; Hayes, C; Leach, M O

    2002-03-21

    In this note we describe and evaluate the performance of a novel approach to information recovery that involves consecutive projection onto convex sets (POCS). The method is applied to a time series of medical image data and the results are compared to images reconstructed using the standard POCS reconstruction method. The consecutive POCS method converges in a desired step-wise manner producing reconstructed images of superior quality compared to the standard scheme and can speed up the reconstruction process. The proposed method is of value for many finite sampling imaging problems including, in particular, fast-scan magnetic resonance imaging applications.

  3. Phase transitions in complex network dynamics

    NASA Astrophysics Data System (ADS)

    Squires, Shane

    Two phase transitions in complex networks are analyzed. The first of these is a percolation transition, in which the network develops a macroscopic connected component as edges are added to it. Recent work has shown that if edges are added "competitively" to an undirected network, the onset of percolation is abrupt or "explosive." A new variant of explosive percolation is introduced here for directed networks, whose critical behavior is explored using numerical simulations and finite-size scaling theory. This process is also characterized by a very rapid percolation transition, but it is not as sudden as in undirected networks. The second phase transition considered here is the emergence of instability in Boolean networks, a class of dynamical systems that are widely used to model gene regulation. The dynamics, which are determined by the network topology and a set of update rules, may be either stable or unstable, meaning that small perturbations to the state of the network either die out or grow to become macroscopic. Here, this transition is analytically mapped onto a well-studied percolation problem, which can be used to predict the average steady-state distance between perturbed and unperturbed trajectories. This map applies to specific Boolean networks with few restrictions on network topology, but can only be applied to two commonly used types of update rules. Finally, a method is introduced for predicting the stability of Boolean networks with a much broader range of update rules. The network is assumed to have a given complex topology, subject only to a locally tree-like condition, and the update rules may be correlated with topological features of the network. While past work has addressed the separate effects of topology and update rules on stability, the present results are the first widely applicable approach to studying how these effects interact. Numerical simulations agree with the theory and show that such correlations between topology and update

  4. Structural measures for multiplex networks

    NASA Astrophysics Data System (ADS)

    Battiston, Federico; Nicosia, Vincenzo; Latora, Vito

    2014-03-01

    Many real-world complex systems consist of a set of elementary units connected by relationships of different kinds. All such systems are better described in terms of multiplex networks, where the links at each layer represent a different type of interaction between the same set of nodes rather than in terms of (single-layer) networks. In this paper we present a general framework to describe and study multiplex networks, whose links are either unweighted or weighted. In particular, we propose a series of measures to characterize the multiplexicity of the systems in terms of (i) basic node and link properties such as the node degree, and the edge overlap and reinforcement, (ii) local properties such as the clustering coefficient and the transitivity, and (iii) global properties related to the navigability of the multiplex across the different layers. The measures we introduce are validated on a genuinely multiplex data set of Indonesian terrorists, where information among 78 individuals are recorded with respect to mutual trust, common operations, exchanged communications, and business relationships.

  5. Structural measures for multiplex networks.

    PubMed

    Battiston, Federico; Nicosia, Vincenzo; Latora, Vito

    2014-03-01

    Many real-world complex systems consist of a set of elementary units connected by relationships of different kinds. All such systems are better described in terms of multiplex networks, where the links at each layer represent a different type of interaction between the same set of nodes rather than in terms of (single-layer) networks. In this paper we present a general framework to describe and study multiplex networks, whose links are either unweighted or weighted. In particular, we propose a series of measures to characterize the multiplexicity of the systems in terms of (i) basic node and link properties such as the node degree, and the edge overlap and reinforcement, (ii) local properties such as the clustering coefficient and the transitivity, and (iii) global properties related to the navigability of the multiplex across the different layers. The measures we introduce are validated on a genuinely multiplex data set of Indonesian terrorists, where information among 78 individuals are recorded with respect to mutual trust, common operations, exchanged communications, and business relationships.

  6. Cluster modified projective synchronization between networks with distinct topologies

    NASA Astrophysics Data System (ADS)

    Vahedi, Shahed; Noorani, Mohd Salmi Md

    2016-02-01

    Cluster modified projective synchronization (CMPS) between two topologically distinct community networks is studied in this paper. Each cluster here has a unique dynamics at least with respect to the parameter sets. Using an adaptive feedback control gain and a matrix scaling factor, we show that CMPS between two community networks can be realized with considering minimum assumptions and imposing just few restrictions on the configuration set. We use Lyapunov stability theory for the proof and employ computer simulation to confirm our result on randomly generated community networks. Simulations also show the possibility of having hybrid synchronization between the two networks.

  7. Early hydration and setting of oil well cement

    SciTech Connect

    Zhang Jie; Weissinger, Emily A.; Peethamparan, Sulapha; Scherer, George W.

    2010-07-15

    A broad experimental study has been performed to characterize the early hydration and setting of cement pastes prepared with Class H oil well cement at water-to-cement ratios (w/c) from 0.25 to 0.40, cured at temperatures from 10 to 60 {sup o}C, and mixed with chemical additives. Chemical shrinkage during hydration was measured by a newly developed system, degree of hydration was determined by thermogravimetric analysis, and setting time was tested by Vicat and ultrasonic velocity measurements. A Boundary Nucleation and Growth model provides a good fit to the chemical shrinkage data. Temperature increase and accelerator additions expedite the rate of cement hydration by causing more rapid nucleation of hydration products, leading to earlier setting; conversely, retarder and viscosity modifying agents delay cement nucleation, causing later setting times. Lower w/c paste needs less hydration product to form a percolating solid network (i.e., to reach the initial setting point). However, for the systems evaluated, at a given w/c, the degree of hydration at setting is a constant, regardless of the effects of ambient temperature or the presence of additives.

  8. Interconnection networks

    DOEpatents

    Faber, V.; Moore, J.W.

    1988-06-20

    A network of interconnected processors is formed from a vertex symmetric graph selected from graphs GAMMA/sub d/(k) with degree d, diameter k, and (d + 1)exclamation/ (d /minus/ k + 1)exclamation processors for each d greater than or equal to k and GAMMA/sub d/(k, /minus/1) with degree d /minus/ 1, diameter k + 1, and (d + 1)exclamation/(d /minus/ k + 1)exclamation processors for each d greater than or equal to k greater than or equal to 4. Each processor has an address formed by one of the permutations from a predetermined sequence of letters chosen a selected number of letters at a time, and an extended address formed by appending to the address the remaining ones of the predetermined sequence of letters. A plurality of transmission channels is provided from each of the processors, where each processor has one less channel than the selected number of letters forming the sequence. Where a network GAMMA/sub d/(k, /minus/1) is provided, no processor has a channel connected to form an edge in a direction delta/sub 1/. Each of the channels has an identification number selected from the sequence of letters and connected from a first processor having a first extended address to a second processor having a second address formed from a second extended address defined by moving to the front of the first extended address the letter found in the position within the first extended address defined by the channel identification number. The second address is then formed by selecting the first elements of the second extended address corresponding to the selected number used to form the address permutations. 9 figs.

  9. Network traffic analysis using dispersion patterns

    SciTech Connect

    Khan, F. N.

    2010-03-15

    The Verilog code us used to map a measurement solution on FPGA to analyze network traffic. It realizes a set of Bloom filters and counters, besides associated control logic that can quickly measure statistics like InDegree, OutDegree, Depth, in the context of Traffic Dispersion Graphs. Such patterns are helpful in classification of network activity, like Peer to Peer and Port-Scanning, in the traffic.

  10. International Lunar Network (ILN) Anchor Nodes

    NASA Technical Reports Server (NTRS)

    Cohen, Barbara A.

    2008-01-01

    This slide presentation reviews what we know about the interior and surface of the moon and the need to establish a robotic set of geophysical monitoring stations on the surface of the Moon for the purpose of providing significant scientific value to the exploration of the Moon. The ILN Anchor Nodes will provide the backbone of the network in a way that accomplishes new science and allows other nodes to be flexible contributors to the network.

  11. Optical Omega network: a compact implementation technique

    NASA Astrophysics Data System (ADS)

    Wong, K. W.; Cheng, L. M.

    1995-10-01

    We propose a technique for the compact implementation of an optical Omega network. This technique utilizes the concept that both the perfect-shuffle interconnection and the switching stages can be realized by the same procedures, i.e., duplicate, shift, superimpose, and mask. As a result, a single set of optics is sufficient to realize the whole Omega network in a time-multiplexed recursive manner. Optical setups were designed and a proof-of-principle experiment was performed.

  12. Auto-associative nanoelectronic neural network

    SciTech Connect

    Nogueira, C. P. S. M.; Guimarães, J. G.

    2014-05-15

    In this paper, an auto-associative neural network using single-electron tunneling (SET) devices is proposed and simulated at low temperature. The nanoelectronic auto-associative network is able to converge to a stable state, previously stored during training. The recognition of the pattern involves decreasing the energy of the input state until it achieves a point of local minimum energy, which corresponds to one of the stored patterns.

  13. Challenges Associated With Using Large Data Sets for Quality Assessment and Research in Clinical Settings.

    PubMed

    Cohen, Bevin; Vawdrey, David K; Liu, Jianfang; Caplan, David; Furuya, E Yoko; Mis, Frederick W; Larson, Elaine

    2015-08-01

    The rapidly expanding use of electronic records in health-care settings is generating unprecedented quantities of data available for clinical, epidemiological, and cost-effectiveness research. Several challenges are associated with using these data for clinical research, including issues surrounding access and information security, poor data quality, inconsistency of data within and across institutions, and a paucity of staff with expertise to manage and manipulate large clinical data sets. In this article, we describe our experience with assembling a data-mart and conducting clinical research using electronic data from four facilities within a single hospital network in New York City. We culled data from several electronic sources, including the institution's admission-discharge-transfer system, cost accounting system, electronic health record, clinical data warehouse, and departmental records. The final data-mart contained information for more than 760,000 discharges occurring from 2006 through 2012. Using categories identified by the National Institutes of Health Big Data to Knowledge initiative as a framework, we outlined challenges encountered during the development and use of a domain-specific data-mart and recommend approaches to overcome these challenges.

  14. Challenges Associated With Using Large Data Sets for Quality Assessment and Research in Clinical Settings

    PubMed Central

    Cohen, Bevin; Vawdrey, David K.; Liu, Jianfang; Caplan, David; Furuya, E. Yoko; Mis, Frederick W.; Larson, Elaine

    2015-01-01

    The rapidly expanding use of electronic records in health-care settings is generating unprecedented quantities of data available for clinical, epidemiological, and cost-effectiveness research. Several challenges are associated with using these data for clinical research, including issues surrounding access and information security, poor data quality, inconsistency of data within and across institutions, and a paucity of staff with expertise to manage and manipulate large clinical data sets. In this article, we describe our experience with assembling a data-mart and conducting clinical research using electronic data from four facilities within a single hospital network in New York City. We culled data from several electronic sources, including the institution’s admission-discharge-transfer system, cost accounting system, electronic health record, clinical data warehouse, and departmental records. The final data-mart contained information for more than 760,000 discharges occurring from 2006 through 2012. Using categories identified by the National Institutes of Health Big Data to Knowledge initiative as a framework, we outlined challenges encountered during the development and use of a domain-specific data-mart and recommend approaches to overcome these challenges. PMID:26351216

  15. Challenges Associated With Using Large Data Sets for Quality Assessment and Research in Clinical Settings.

    PubMed

    Cohen, Bevin; Vawdrey, David K; Liu, Jianfang; Caplan, David; Furuya, E Yoko; Mis, Frederick W; Larson, Elaine

    2015-08-01

    The rapidly expanding use of electronic records in health-care settings is generating unprecedented quantities of data available for clinical, epidemiological, and cost-effectiveness research. Several challenges are associated with using these data for clinical research, including issues surrounding access and information security, poor data quality, inconsistency of data within and across institutions, and a paucity of staff with expertise to manage and manipulate large clinical data sets. In this article, we describe our experience with assembling a data-mart and conducting clinical research using electronic data from four facilities within a single hospital network in New York City. We culled data from several electronic sources, including the institution's admission-discharge-transfer system, cost accounting system, electronic health record, clinical data warehouse, and departmental records. The final data-mart contained information for more than 760,000 discharges occurring from 2006 through 2012. Using categories identified by the National Institutes of Health Big Data to Knowledge initiative as a framework, we outlined challenges encountered during the development and use of a domain-specific data-mart and recommend approaches to overcome these challenges. PMID:26351216

  16. Robustness of networks of networks with degree-degree correlation

    NASA Astrophysics Data System (ADS)

    Min, Byungjoon; Canals, Santiago; Makse, Hernan

    Many real-world complex systems ranging from critical infrastructure and transportation networks to living systems including brain and cellular networks are not formed by an isolated network but by a network of networks. Randomly coupled networks with interdependency between different networks may easily result in abrupt collapse. Here, we seek a possible explanation of stable functioning in natural networks of networks including functional brain networks. Specifically, we analyze the robustness of networks of networks focused on one-to-many interconnections between different networks and degree-degree correlation. Implication of the network robustness on functional brain networks of rats is also discussed.

  17. Statistical Design of Electric Power Transmission Networks.

    NASA Astrophysics Data System (ADS)

    Guvenis, Albert

    This thesis presents a statistical planning method for expanding electric power transmission networks in the presence of load/generation and network uncertainties. The objective of the proposed algorithm is to obtain a set of alternative network expansion plans which have optimum reliability and expansion cost. Present methods optimize the existing network based on a deterministic performance index. Therefore, they are limited to a nominal design and cannot minimize the loss of load probability due to random fluctuations in the power system parameters. This thesis addresses this problem of designing a power transmission network that minimizes the loss-of-load probability (or equivalently maximizes the reliability) under random load/generation and network fluctuations. Two probabilistic indices, reliability and adequacy, are defined in order to quantify the transmission network performance under uncertainties. Reliability is defined as the probability of supplying the random substation load demands under random circuit outages, whereas adequacy is the same index computed under the non-outage condition. The effectiveness of the proposed statistical planning method is its ability to optimize these two indices by using efficient gradient methods. The approach taken is to first optimize the adequacy using a set-imbedding technique. Then the adequate network obtained in the first design stage is reoptimized with respect to reliability using a modified Parametric Sampling technique. The reliability optimization method developed in this thesis optimizes the discrete reliability of the network by successively optimizing approximate continuous functions. It is shown that the solution of the continuous optimization problems converge to the solution of the discrete reliability optimization problem. Two objectives, reliability and expansion cost, are optimized simultaneously. By weighting these objectives differently a set of alternative expansion plans are obtained, which

  18. Animal transportation networks.

    PubMed

    Perna, Andrea; Latty, Tanya

    2014-11-01

    Many group-living animals construct transportation networks of trails, galleries and burrows by modifying the environment to facilitate faster, safer or more efficient movement. Animal transportation networks can have direct influences on the fitness of individuals, whereas the shape and structure of transportation networks can influence community dynamics by facilitating contacts between different individuals and species. In this review, we discuss three key areas in the study of animal transportation networks: the topological properties of networks, network morphogenesis and growth, and the behaviour of network users. We present a brief primer on elements of network theory, and then discuss the different ways in which animal groups deal with the fundamental trade-off between the competing network properties of travel efficiency, robustness and infrastructure cost. We consider how the behaviour of network users can impact network efficiency, and call for studies that integrate both network topology and user behaviour. We finish with a prospectus for future research.

  19. Animal transportation networks

    PubMed Central

    Perna, Andrea; Latty, Tanya

    2014-01-01

    Many group-living animals construct transportation networks of trails, galleries and burrows by modifying the environment to facilitate faster, safer or more efficient movement. Animal transportation networks can have direct influences on the fitness of individuals, whereas the shape and structure of transportation networks can influence community dynamics by facilitating contacts between different individuals and species. In this review, we discuss three key areas in the study of animal transportation networks: the topological properties of networks, network morphogenesis and growth, and the behaviour of network users. We present a brief primer on elements of network theory, and then discuss the different ways in which animal groups deal with the fundamental trade-off between the competing network properties of travel efficiency, robustness and infrastructure cost. We consider how the behaviour of network users can impact network efficiency, and call for studies that integrate both network topology and user behaviour. We finish with a prospectus for future research. PMID:25165598

  20. Scale-Aware Pixelwise Object Proposal Networks

    NASA Astrophysics Data System (ADS)

    Jie, Zequn; Liang, Xiaodan; Feng, Jiashi; Lu, Wen Feng; Tay, Eng Hock Francis; Yan, Shuicheng

    2016-10-01

    Object proposal is essential for current state-of-the-art object detection pipelines. However, the existing proposal methods generally fail in producing results with satisfying localization accuracy. The case is even worse for small objects which however are quite common in practice. In this paper we propose a novel Scale-aware Pixel-wise Object Proposal (SPOP) network to tackle the challenges. The SPOP network can generate proposals with high recall rate and average best overlap (ABO), even for small objects. In particular, in order to improve the localization accuracy, a fully convolutional network is employed which predicts locations of object proposals for each pixel. The produced ensemble of pixel-wise object proposals enhances the chance of hitting the object significantly without incurring heavy extra computational cost. To solve the challenge of localizing objects at small scale, two localization networks which are specialized for localizing objects with different scales are introduced, following the divide-and-conquer philosophy. Location outputs of these two networks are then adaptively combined to generate the final proposals by a large-/small-size weighting network. Extensive evaluations on PASCAL VOC 2007 show the SPOP network is superior over the state-of-the-art models. The high-quality proposals from SPOP network also significantly improve the mean average precision (mAP) of object detection with Fast-RCNN framework. Finally, the SPOP network (trained on PASCAL VOC) shows great generalization performance when testing it on ILSVRC 2013 validation set.