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  1. Statistical network analysis for analyzing policy networks

    DEFF Research Database (Denmark)

    Robins, Garry; Lewis, Jenny; Wang, Peng

    2012-01-01

    and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs......To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social......), and stochastic actor-oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach...

  2. Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

    Directory of Open Access Journals (Sweden)

    Xi Jin

    2015-01-01

    Full Text Available The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the method A-MM is tighter than or equal to that computed by the method N-MM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the large-scale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.

  3. Analyzing negative ties in social networks

    Directory of Open Access Journals (Sweden)

    Mankirat Kaur

    2016-03-01

    Full Text Available Online social networks are a source of sharing information and maintaining personal contacts with other people through social interactions and thus forming virtual communities online. Social networks are crowded with positive and negative relations. Positive relations are formed by support, endorsement and friendship and thus, create a network of well-connected users whereas negative relations are a result of opposition, distrust and avoidance creating disconnected networks. Due to increase in illegal activities such as masquerading, conspiring and creating fake profiles on online social networks, exploring and analyzing these negative activities becomes the need of hour. Usually negative ties are treated in same way as positive ties in many theories such as balance theory and blockmodeling analysis. But the standard concepts of social network analysis do not yield same results in respect of each tie. This paper presents a survey on analyzing negative ties in social networks through various types of network analysis techniques that are used for examining ties such as status, centrality and power measures. Due to the difference in characteristics of flow in positive and negative tie networks some of these measures are not applicable on negative ties. This paper also discusses new methods that have been developed specifically for analyzing negative ties such as negative degree, and h∗ measure along with the measures based on mixture of positive and negative ties. The different types of social network analysis approaches have been reviewed and compared to determine the best approach that can appropriately identify the negative ties in online networks. It has been analyzed that only few measures such as Degree and PN centrality are applicable for identifying outsiders in network. For applicability in online networks, the performance of PN measure needs to be verified and further, new measures should be developed based upon negative clique concept.

  4. Structural factoring approach for analyzing stochastic networks

    Science.gov (United States)

    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.

  5. How to Analyze Company Using Social Network?

    Science.gov (United States)

    Palus, Sebastian; Bródka, Piotr; Kazienko, Przemysław

    Every single company or institution wants to utilize its resources in the most efficient way. In order to do so they have to be have good structure. The new way to analyze company structure by utilizing existing within company natural social network and example of its usage on Enron company are presented in this paper.

  6. Novel topological descriptors for analyzing biological networks

    Directory of Open Access Journals (Sweden)

    Varmuza Kurt K

    2010-06-01

    Full Text Available Abstract Background Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information. Results In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem. Conclusions Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.

  7. Can recurrence networks show small-world property?

    International Nuclear Information System (INIS)

    Jacob, Rinku; Harikrishnan, K.P.; Misra, R.; Ambika, G.

    2016-01-01

    Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value ϵ chosen at or just above the percolation threshold of the network are quite well understood, what happens as the threshold increases beyond the usual operational window is still not clear from a complex network perspective. The present Letter is focused mainly on the network properties at intermediate-to-large values of the recurrence threshold, for which no systematic study has been performed so far. We argue, with numerical support, that recurrence networks constructed from chaotic attractors with ϵ equal to the usual recurrence threshold or slightly above cannot, in general, show small-world property. However, if the threshold is further increased, the recurrence network topology initially changes to a small-world structure and finally to that of a classical random graph as the threshold approaches the size of the strange attractor. - Highlights: • Properties of recurrence networks at intermediate-to-large values of recurrence threshold are analyzed from a complex network perspective. • Using a combined plot of characteristic path length and clustering coefficient, it is shown that the recurrence network constructed with recurrence threshold equal to or just above the percolation threshold cannot, in general, display small-world property. • As the recurrence threshold is increased from its usual operational window, the resulting network makes a smooth transition initially to a small-world network for an intermediate range of thresholds and finally to the classical random graph as the threshold becomes comparable to the size of the attractor.

  8. Can recurrence networks show small-world property?

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, Rinku, E-mail: rinku.jacob.vallanat@gmail.com [Department of Physics, The Cochin College, Cochin, 682002 (India); Harikrishnan, K.P., E-mail: kp_hk2002@yahoo.co.in [Department of Physics, The Cochin College, Cochin, 682002 (India); Misra, R., E-mail: rmisra@iucaa.in [Inter University Centre for Astronomy and Astrophysics, Pune, 411007 (India); Ambika, G., E-mail: g.ambika@iiserpune.ac.in [Indian Institute of Science Education and Research, Pune, 411008 (India)

    2016-08-12

    Recurrence networks are complex networks, constructed from time series data, having several practical applications. Though their properties when constructed with the threshold value ϵ chosen at or just above the percolation threshold of the network are quite well understood, what happens as the threshold increases beyond the usual operational window is still not clear from a complex network perspective. The present Letter is focused mainly on the network properties at intermediate-to-large values of the recurrence threshold, for which no systematic study has been performed so far. We argue, with numerical support, that recurrence networks constructed from chaotic attractors with ϵ equal to the usual recurrence threshold or slightly above cannot, in general, show small-world property. However, if the threshold is further increased, the recurrence network topology initially changes to a small-world structure and finally to that of a classical random graph as the threshold approaches the size of the strange attractor. - Highlights: • Properties of recurrence networks at intermediate-to-large values of recurrence threshold are analyzed from a complex network perspective. • Using a combined plot of characteristic path length and clustering coefficient, it is shown that the recurrence network constructed with recurrence threshold equal to or just above the percolation threshold cannot, in general, display small-world property. • As the recurrence threshold is increased from its usual operational window, the resulting network makes a smooth transition initially to a small-world network for an intermediate range of thresholds and finally to the classical random graph as the threshold becomes comparable to the size of the attractor.

  9. Revealing and analyzing networks of environmental systems

    Science.gov (United States)

    Eveillard, D.; Bittner, L.; Chaffron, S.; Guidi, L.; Raes, J.; Karsenti, E.; Bowler, C.; Gorsky, G.

    2015-12-01

    Understanding the interactions between microbial communities and their environment well enough to be able to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is a complicated task, because (i) communities are complex, (ii) most are described qualitatively, and (iii) quantitative understanding of the way communities interacts with their surroundings remains incomplete. Within this seminar, we will illustrate two complementary approaches that aim to overcome these points in different manners. First, we will present a network analysis that focus on the biological carbon pump in the global ocean. The biological carbon pump is the process by which photosynthesis transforms CO2 to organic carbon sinking to the deep-ocean as particles where it is sequestered. While the intensity of the pump correlate to plankton community composition, the underlying ecosystem structure and interactions driving this process remain largely uncharacterized Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve understanding of these drivers. We show that specific plankton communities correlate with carbon export and highlight unexpected and overlooked taxa such as Radiolaria, alveolate parasites and bacterial pathogens, as well as Synechococcus and their phages, as key players in the biological pump. Additionally, we show that the abundances of just a few bacterial and viral genes predict most of the global ocean carbon export's variability. Together these findings help elucidate ecosystem drivers of the biological carbon pump and present a case study for scaling from genes-to-ecosystems. Second, we will show preliminary results on a probabilistic modeling that predicts microbial community structure across observed physicochemical data, from a putative network and partial quantitative knowledge. This modeling shows that, despite

  10. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  11. Analyzing the Bitcoin Network: The First Four Years

    Directory of Open Access Journals (Sweden)

    Matthias Lischke

    2016-03-01

    Full Text Available In this explorative study, we examine the economy and transaction network of the decentralized digital currency Bitcoin during the first four years of its existence. The objective is to develop insights into the evolution of the Bitcoin economy during this period. For this, we establish and analyze a novel integrated dataset that enriches data from the Bitcoin blockchain with off-network data such as business categories and geo-locations. Our analyses reveal the major Bitcoin businesses and markets. Our results also give insights on the business distribution by countries and how businesses evolve over time. We also show that there is a gambling network that features many very small transactions. Furthermore, regional differences in the adoption and business distribution could be found. In the network analysis, the small world phenomenon is investigated and confirmed for several subgraphs of the Bitcoin network.

  12. Analyzing Evolving Social Network 2 (EVOLVE2)

    Science.gov (United States)

    2015-04-01

    WORK UNIT NUMBER N2 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of Southern California 3720 S. Flower Street, Third Floor Los...score, and resource allocation. Below the double line are link prediction heuristics introduced in this paper. name symbol definition common neighbors...LIST OF SYMBOLS , ABBREVIATIONS AND ACRONYMS A adjacency matrix of a network D diagonal out-degree matrix DW out-degree matrix of the reweighted network

  13. Analyzing complex networks through correlations in centrality measurements

    International Nuclear Information System (INIS)

    Ricardo Furlan Ronqui, José; Travieso, Gonzalo

    2015-01-01

    Many real world systems can be expressed as complex networks of interconnected nodes. It is frequently important to be able to quantify the relative importance of the various nodes in the network, a task accomplished by defining some centrality measures, with different centrality definitions stressing different aspects of the network. It is interesting to know to what extent these different centrality definitions are related for different networks. In this work, we study the correlation between pairs of a set of centrality measures for different real world networks and two network models. We show that the centralities are in general correlated, but with stronger correlations for network models than for real networks. We also show that the strength of the correlation of each pair of centralities varies from network to network. Taking this fact into account, we propose the use of a centrality correlation profile, consisting of the values of the correlation coefficients between all pairs of centralities of interest, as a way to characterize networks. Using the yeast protein interaction network as an example we show also that the centrality correlation profile can be used to assess the adequacy of a network model as a representation of a given real network. (paper)

  14. Analyzing Bullwhip Effect in Supply Networks under Exogenous Uncertainty

    Directory of Open Access Journals (Sweden)

    Mitra Darvish

    2014-05-01

    Full Text Available This paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. The stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. In fact, we propose an exact formula in order to measure the bullwhip effect in the addressed supply network topology considering the system in Markovian chain framework and presenting a matrix of network member relationships and relevant order sequences. The formula turns out using a mathematical method called frequency domain analysis. The major contribution of this paper is analyzing the bullwhip effect considering exogenous uncertainty in supply networks and using the Fourier transform in order to simplify the relevant calculations. We present a number of numerical examples to assess the analytical results accuracy in quantifying the bullwhip effect.

  15. A Network Approach to Analyzing Highly Recombinant Malaria Parasite Genes

    Science.gov (United States)

    Larremore, Daniel B.; Clauset, Aaron; Buckee, Caroline O.

    2013-01-01

    The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences. PMID:24130474

  16. A network approach to analyzing highly recombinant malaria parasite genes.

    Science.gov (United States)

    Larremore, Daniel B; Clauset, Aaron; Buckee, Caroline O

    2013-01-01

    The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

  17. A network approach to analyzing highly recombinant malaria parasite genes.

    Directory of Open Access Journals (Sweden)

    Daniel B Larremore

    Full Text Available The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs, and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

  18. Characterization of leadership styles by analyzing social networks

    Directory of Open Access Journals (Sweden)

    Enrique Saravia Vergara

    2015-12-01

    Full Text Available The study presents an analysis of networks to characterize the leadership styles in an institution volunteer, complementary or alternative to classic questionnaires to measure leadership. The study raises test questions to identify friendly relations and prominent leaders in the leadership dimensions of transformational, transactional and passive / avoidant and analyzes, for each of them, the metrics of the network structure as a whole and the role each individual actor. The study exploratory level, based on the opinion of 9 members of a specific project, allowed to show the benefits of network analysis applied to the subject of leadership: (i identified that the climate of "respect and trust", "enthusiasm" and "concern for the welfare of the people" dominate the organization; and (ii the individual role of each leader was identified. Three leaders who are considered as the best friends and care about the welfare of others were identified, but one of them stands for broadcasting "greater respect and trust" and is "an example to follow"; while the other two leaders stand out as being more "enthusiastic and optimistic" and "promote innovation and creativity," among other findings.

  19. Analyzing complex networks evolution through Information Theory quantifiers

    International Nuclear Information System (INIS)

    Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martin Gomez

    2011-01-01

    A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

  20. Analyzing complex networks evolution through Information Theory quantifiers

    Energy Technology Data Exchange (ETDEWEB)

    Carpi, Laura C., E-mail: Laura.Carpi@studentmail.newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Rosso, Osvaldo A., E-mail: rosso@fisica.ufmg.b [Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina); Saco, Patricia M., E-mail: Patricia.Saco@newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Hidraulica, Facultad de Ciencias Exactas, Ingenieria y Agrimensura, Universidad Nacional de Rosario, Avenida Pellegrini 250, Rosario (Argentina); Ravetti, Martin Gomez, E-mail: martin.ravetti@dep.ufmg.b [Departamento de Engenharia de Producao, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, Belo Horizonte (31270-901), MG (Brazil)

    2011-01-24

    A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

  1. Vector network analyzer (VNA) measurements and uncertainty assessment

    CERN Document Server

    Shoaib, Nosherwan

    2017-01-01

    This book describes vector network analyzer measurements and uncertainty assessments, particularly in waveguide test-set environments, in order to establish their compatibility to the International System of Units (SI) for accurate and reliable characterization of communication networks. It proposes a fully analytical approach to measurement uncertainty evaluation, while also highlighting the interaction and the linear propagation of different uncertainty sources to compute the final uncertainties associated with the measurements. The book subsequently discusses the dimensional characterization of waveguide standards and the quality of the vector network analyzer (VNA) calibration techniques. The book concludes with an in-depth description of the novel verification artefacts used to assess the performance of the VNAs. It offers a comprehensive reference guide for beginners to experts, in both academia and industry, whose work involves the field of network analysis, instrumentation and measurements.

  2. Systems and methods for modeling and analyzing networks

    Science.gov (United States)

    Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

    2013-10-29

    The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

  3. The wireshark field guide analyzing and troubleshooting network traffic

    CERN Document Server

    Shimonski, Robert

    2013-01-01

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

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

    Science.gov (United States)

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

    2018-05-01

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

  5. Analyzing Enterprise Networks Needs: Action Research from the Mechatronics Sector

    Science.gov (United States)

    Cagnazzo, Luca; Taticchi, Paolo; Bidini, Gianni; Baglieri, Enzo

    New business models and theories are developing nowadays towards collaborative environments direction, and many new tools in sustaining companies involved in these organizations are emerging. Among them, a plethora of methodologies to analyze their needs are already developed for single companies. Few academic works are available about Enterprise Networks (ENs) need analysis. This paper presents the learning from an action research (AR) in the mechatronics sector: AR has been used in order to experience the issue of evaluating network needs and therefore define, develop, and test a complete framework for network evaluation. Reflection on the story in the light of the experience and the theory is presented, as well as extrapolation to a broader context and articulation of usable knowledge.

  6. Analyzing the multilevel structure of the European airport network

    Directory of Open Access Journals (Sweden)

    Oriol Lordan

    2017-04-01

    Full Text Available The multilayered structure of the European airport network (EAN, composed of connections and flights between European cities, is analyzed through the k-core decomposition of the connections network. This decomposition allows to identify the core, bridge and periphery layers of the EAN. The core layer includes the best-connected cities, which include important business air traffic destinations. The periphery layer includes cities with lesser connections, which serve low populated areas where air travel is an economic alternative. The remaining cities form the bridge of the EAN, including important leisure travel origins and destinations. The multilayered structure of the EAN affects network robustness, as the EAN is more robust to isolation of nodes of the core, than to the isolation of a combination of core and bridge nodes.

  7. Innovation Networks New Approaches in Modelling and Analyzing

    CERN Document Server

    Pyka, Andreas

    2009-01-01

    The science of graphs and networks has become by now a well-established tool for modelling and analyzing a variety of systems with a large number of interacting components. Starting from the physical sciences, applications have spread rapidly to the natural and social sciences, as well as to economics, and are now further extended, in this volume, to the concept of innovations, viewed broadly. In an abstract, systems-theoretical approach, innovation can be understood as a critical event which destabilizes the current state of the system, and results in a new process of self-organization leading to a new stable state. The contributions to this anthology address different aspects of the relationship between innovation and networks. The various chapters incorporate approaches in evolutionary economics, agent-based modeling, social network analysis and econophysics and explore the epistemic tension between insights into economics and society-related processes, and the insights into new forms of complex dynamics.

  8. Analyzing phase diagrams and phase transitions in networked competing populations

    Science.gov (United States)

    Ni, Y.-C.; Yin, H. P.; Xu, C.; Hui, P. M.

    2011-03-01

    Phase diagrams exhibiting the extent of cooperation in an evolutionary snowdrift game implemented in different networks are studied in detail. We invoke two independent payoff parameters, unlike a single payoff often used in most previous works that restricts the two payoffs to vary in a correlated way. In addition to the phase transition points when a single payoff parameter is used, phase boundaries separating homogeneous phases consisting of agents using the same strategy and a mixed phase consisting of agents using different strategies are found. Analytic expressions of the phase boundaries are obtained by invoking the ideas of the last surviving patterns and the relative alignments of the spectra of payoff values to agents using different strategies. In a Watts-Strogatz regular network, there exists a re-entrant phenomenon in which the system goes from a homogeneous phase into a mixed phase and re-enters the homogeneous phase as one of the two payoff parameters is varied. The non-trivial phase diagram accompanying this re-entrant phenomenon is quantitatively analyzed. The effects of noise and cooperation in randomly rewired Watts-Strogatz networks are also studied. The transition between a mixed phase and a homogeneous phase is identify to belong to the directed percolation universality class. The methods used in the present work are applicable to a wide range of problems in competing populations of networked agents.

  9. Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

    Directory of Open Access Journals (Sweden)

    Yunpeng Xiao

    2012-01-01

    Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

  10. Program for Analyzing Flows in a Complex Network

    Science.gov (United States)

    Majumdar, Alok Kumar

    2006-01-01

    Generalized Fluid System Simulation Program (GFSSP) version 4 is a general-purpose computer program for analyzing steady-state and transient flows in a complex fluid network. The program is capable of modeling compressibility, fluid transients (e.g., water hammers), phase changes, mixtures of chemical species, and such externally applied body forces as gravitational and centrifugal ones. A graphical user interface enables the user to interactively develop a simulation of a fluid network consisting of nodes and branches. The user can also run the simulation and view the results in the interface. The system of equations for conservation of mass, energy, chemical species, and momentum is solved numerically by a combination of the Newton-Raphson and successive-substitution methods.

  11. A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

    Science.gov (United States)

    Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

    2005-01-01

    This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

  12. Droplet networks with incorporated protein diodes show collective properties

    Science.gov (United States)

    Maglia, Giovanni; Heron, Andrew J.; Hwang, William L.; Holden, Matthew A.; Mikhailova, Ellina; Li, Qiuhong; Cheley, Stephen; Bayley, Hagan

    2009-07-01

    Recently, we demonstrated that submicrolitre aqueous droplets submerged in an apolar liquid containing lipid can be tightly connected by means of lipid bilayers to form networks. Droplet interface bilayers have been used for rapid screening of membrane proteins and to form asymmetric bilayers with which to examine the fundamental properties of channels and pores. Networks, meanwhile, have been used to form microscale batteries and to detect light. Here, we develop an engineered protein pore with diode-like properties that can be incorporated into droplet interface bilayers in droplet networks to form devices with electrical properties including those of a current limiter, a half-wave rectifier and a full-wave rectifier. The droplet approach, which uses unsophisticated components (oil, lipid, salt water and a simple pore), can therefore be used to create multidroplet networks with collective properties that cannot be produced by droplet pairs.

  13. Optical vector network analyzer based on double-sideband modulation.

    Science.gov (United States)

    Jun, Wen; Wang, Ling; Yang, Chengwu; Li, Ming; Zhu, Ning Hua; Guo, Jinjin; Xiong, Liangming; Li, Wei

    2017-11-01

    We report an optical vector network analyzer (OVNA) based on double-sideband (DSB) modulation using a dual-parallel Mach-Zehnder modulator. The device under test (DUT) is measured twice with different modulation schemes. By post-processing the measurement results, the response of the DUT can be obtained accurately. Since DSB modulation is used in our approach, the measurement range is doubled compared with conventional single-sideband (SSB) modulation-based OVNA. Moreover, the measurement accuracy is improved by eliminating the even-order sidebands. The key advantage of the proposed scheme is that the measurement of a DUT with bandpass response can also be simply realized, which is a big challenge for the SSB-based OVNA. The proposed method is theoretically and experimentally demonstrated.

  14. Biasing vector network analyzers using variable frequency and amplitude signals

    Science.gov (United States)

    Nobles, J. E.; Zagorodnii, V.; Hutchison, A.; Celinski, Z.

    2016-08-01

    We report the development of a test setup designed to provide a variable frequency biasing signal to a vector network analyzer (VNA). The test setup is currently used for the testing of liquid crystal (LC) based devices in the microwave region. The use of an AC bias for LC based devices minimizes the negative effects associated with ionic impurities in the media encountered with DC biasing. The test setup utilizes bias tees on the VNA test station to inject the bias signal. The square wave biasing signal is variable from 0.5 to 36.0 V peak-to-peak (VPP) with a frequency range of DC to 10 kHz. The test setup protects the VNA from transient processes, voltage spikes, and high-frequency leakage. Additionally, the signals to the VNA are fused to ½ amp and clipped to a maximum of 36 VPP based on bias tee limitations. This setup allows us to measure S-parameters as a function of both the voltage and the frequency of the applied bias signal.

  15. Network public opinion space sentiment tendency analyze based on recurrent convolution neural network

    Science.gov (United States)

    Zhang, Gaowei; Xu, Lingyu; Wang, Lei

    2018-04-01

    The purpose of this chapter is to analyze the investor's psychological characteristics and investment decision-making behavior characteristics, to study the investor sentiment under the network public opinion, and then analyze from three aspects: First, investor sentiment analysis and how to spread in the online media; The influence mechanism of investor's emotion on the stock market and its effect; the third one is to measure the investor's emotion based on the degree of attention, trying hard to sort out the internal relations between the investor's sentiment and the network public opinion and the stock market, in order to lay the theoretical foundation of this article.

  16. Towards a theoretical framework for analyzing complex linguistic networks

    CERN Document Server

    Lücking, Andy; Banisch, Sven; Blanchard, Philippe; Job, Barbara

    2016-01-01

    The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities.This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statisticalmodels of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information scien...

  17. Social network analyzer on the example of Twitter

    Science.gov (United States)

    Gorodetskaia, Mariia; Khruslova, Diana

    2017-09-01

    Social networks are powerful sources of data due to their popularity. Twitter is one of the networks providing a lot of data. There is need to collect this data for future usage from linguistics to SMM and marketing. The report examines the existing software solutions and provides new ones. The study includes information about the software developed. Some future features are listed.

  18. Comparing Models GRM, Refraction Tomography and Neural Network to Analyze Shallow Landslide

    Directory of Open Access Journals (Sweden)

    Armstrong F. Sompotan

    2011-11-01

    Full Text Available Detailed investigations of landslides are essential to understand fundamental landslide mechanisms. Seismic refraction method has been proven as a useful geophysical tool for investigating shallow landslides. The objective of this study is to introduce a new workflow using neural network in analyzing seismic refraction data and to compare the result with some methods; that are general reciprocal method (GRM and refraction tomography. The GRM is effective when the velocity structure is relatively simple and refractors are gently dipping. Refraction tomography is capable of modeling the complex velocity structures of landslides. Neural network is found to be more potential in application especially in time consuming and complicated numerical methods. Neural network seem to have the ability to establish a relationship between an input and output space for mapping seismic velocity. Therefore, we made a preliminary attempt to evaluate the applicability of neural network to determine velocity and elevation of subsurface synthetic models corresponding to arrival times. The training and testing process of the neural network is successfully accomplished using the synthetic data. Furthermore, we evaluated the neural network using observed data. The result of the evaluation indicates that the neural network can compute velocity and elevation corresponding to arrival times. The similarity of those models shows the success of neural network as a new alternative in seismic refraction data interpretation.

  19. Optimization of the kernel functions in a probabilistic neural network analyzing the local pattern distribution.

    Science.gov (United States)

    Galleske, I; Castellanos, J

    2002-05-01

    This article proposes a procedure for the automatic determination of the elements of the covariance matrix of the gaussian kernel function of probabilistic neural networks. Two matrices, a rotation matrix and a matrix of variances, can be calculated by analyzing the local environment of each training pattern. The combination of them will form the covariance matrix of each training pattern. This automation has two advantages: First, it will free the neural network designer from indicating the complete covariance matrix, and second, it will result in a network with better generalization ability than the original model. A variation of the famous two-spiral problem and real-world examples from the UCI Machine Learning Repository will show a classification rate not only better than the original probabilistic neural network but also that this model can outperform other well-known classification techniques.

  20. Analyzing Human Communication Networks in Organizations: Applications to Management Problems.

    Science.gov (United States)

    Farace, Richard V.; Danowski, James A.

    Investigating the networks of communication in organizations leads to an understanding of efficient and inefficient information dissemination as practiced in large systems. Most important in organizational communication is the role of the "liaison person"--the coordinator of intercommunication. When functioning efficiently, coordinators maintain…

  1. Analyzing Spread of Influence in Social Networks for Transportation Applications

    Science.gov (United States)

    2016-09-02

    This project analyzed the spread of influence in social media, in particular, the Twitter social media site, and identified the individuals who exert the most influence to those they interact with. There are published studies that use social media to...

  2. Analyzing Spread of Influence in Social Networks for Transportation Application.

    Science.gov (United States)

    2016-09-02

    This project analyzed the spread of influence in social media, in particular, the Twitter social media site, and identified the individuals who exert the most influence to those they interact with. There are published studies that use social media to...

  3. Analyzing the Social Networks of High- and Low-Performing Students in Online Discussion Forums

    Science.gov (United States)

    Ghadirian, Hajar; Salehi, Keyvan; Ayub, Ahmad Fauzi Mohd

    2018-01-01

    An ego network is an individual's social network relationships with core members. In this study, the ego network parameters in online discussion spaces of high- and low-performing students were compared. The extent to which students' ego networks changed over the course were also analyzed. Participation in 7 weeks of online discussions were…

  4. Look Together: Analyzing Gaze Coordination with Epistemic Network Analysis

    Directory of Open Access Journals (Sweden)

    Sean eAndrist

    2015-07-01

    Full Text Available When conversing and collaborating in everyday situations, people naturally and interactively align their behaviors with each other across various communication channels, including speech, gesture, posture, and gaze. Having access to a partner's referential gaze behavior has been shown to be particularly important in achieving collaborative outcomes, but the process in which people's gaze behaviors unfold over the course of an interaction and become tightly coordinated is not well understood. In this paper, we present work to develop a deeper and more nuanced understanding of coordinated referential gaze in collaborating dyads. We recruited 13 dyads to participate in a collaborative sandwich-making task and used dual mobile eye tracking to synchronously record each participant's gaze behavior. We used a relatively new analysis technique—epistemic network analysis—to jointly model the gaze behaviors of both conversational participants. In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice. We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows. We conducted three separate analyses of the data to reveal (1 properties and patterns of how gaze coordination unfolds throughout an interaction sequence, (2 optimal time lags of gaze alignment within a dyad at different phases of the interaction, and (3 differences in gaze coordination patterns for interaction sequences that lead to breakdowns and repairs. In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users.

  5. Analyzing the Dynamics of Communication in Online Social Networks

    Science.gov (United States)

    de Choudhury, Munmun; Sundaram, Hari; John, Ajita; Seligmann, Doree Duncan

    This chapter deals with the analysis of interpersonal communication dynamics in online social networks and social media. Communication is central to the evolution of social systems. Today, the different online social sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements (i.e., image, video) as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information or concepts, and how the media channels impact our online interactional behavior. Our central hypothesis is that such communication dynamics between individuals manifest themselves via two key aspects: the information or concept that is the content of communication, and the channel i.e., the media via which communication takes place. We present computational models and discuss large-scale quantitative observational studies for both these organizing ideas. First, we develop a computational framework to determine the "interestingness" property of conversations cented around rich media. Second, we present user models of diffusion of social actions and study the impact of homophily on the diffusion process. The outcome of this research is twofold. First, extensive empirical studies on datasets from YouTube have indicated that on rich media sites, the conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Second, observational and computational studies on large social media datasets such as Twitter have indicated that diffusion of social actions in a network can be indicative of future information cascades. Besides, given a topic, these cascades are often a

  6. Optical vector network analyzer with improved accuracy based on polarization modulation and polarization pulling.

    Science.gov (United States)

    Li, Wei; Liu, Jian Guo; Zhu, Ning Hua

    2015-04-15

    We report a novel optical vector network analyzer (OVNA) with improved accuracy based on polarization modulation and stimulated Brillouin scattering (SBS) assisted polarization pulling. The beating between adjacent higher-order optical sidebands which are generated because of the nonlinearity of an electro-optic modulator (EOM) introduces considerable error to the OVNA. In our scheme, the measurement error is significantly reduced by removing the even-order optical sidebands using polarization discrimination. The proposed approach is theoretically analyzed and experimentally verified. The experimental results show that the accuracy of the OVNA is greatly improved compared to a conventional OVNA.

  7. ANALYZING SOCIAL NETWORKS FROM THE PERSPECTIVE OF MARKETING DECISIONS

    Directory of Open Access Journals (Sweden)

    Logica BANICA

    2015-12-01

    Full Text Available Nowadays, the Web became more than a space for product presentation, but also a capitalization market (e-commerce and an efficient way to know the customer preferences and to meet their requirements. Large companies have the financial potential to use various marketing strategies and, in particular, digital-marketing. Instead, small businesses are looking for lower cost or no cost methods (also called guerrilla marketing. A small company can compete with a large company by approaching a particular range of products that excel in quality, and also by inventiveness in the marketing strategy. During 2010-2015 the potential of Information Technology and Communications (IT&C sector was proved for the companies which aimed towards modernization of technologies and introduced new strategies in order to commercialize new products. An important challenge for companies was to be aware of the changes in customer behaviour, using social networks software. Finally, research centers have set up new IT&C services and improved marketing and communications following the crisis. More and more companies invest in analytic tools to monitor their marketing strategies and Big Data becomes extremely useful for this purpose, using information like customer demographics and spending habits, oscillation between simplicity, comfort and glamour. There are various tools that can transform in a very short time, massive amounts of data into real business value in a very short time, helping companies and retailers to understand, at any point in the product lifecycle, which trends are gaining and which are losing ground. These insights give them the possibility to reduce the risk of not selling their products by making adjustments to the design, production or promotional strategies, before putting the goods on the market. In this paper we aim to present the advantages of exploring customer requirements from social media for marketing strategy of an enterprise, by using SNA

  8. Analyzing the causation of a railway accident based on a complex network

    Science.gov (United States)

    Ma, Xin; Li, Ke-Ping; Luo, Zi-Yan; Zhou, Jin

    2014-02-01

    In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. By employing the complex network theory, especially its statistical indicators, the railway accident as well as its key causations can be analyzed from the overall perspective. As a case, the “7.23” China—Yongwen railway accident is illustrated based on this model. The results show that the inspection of signals and the checking of line conditions before trains run played an important role in this railway accident. In conclusion, the constructed model gives a theoretical clue for railway accident prediction and, hence, greatly reduces the occurrence of railway accidents.

  9. Analyzing the causation of a railway accident based on a complex network

    International Nuclear Information System (INIS)

    Ma Xin; Li Ke-Ping; Luo Zi-Yan; Zhou Jin

    2014-01-01

    In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. By employing the complex network theory, especially its statistical indicators, the railway accident as well as its key causations can be analyzed from the overall perspective. As a case, the “7.23” China—Yongwen railway accident is illustrated based on this model. The results show that the inspection of signals and the checking of line conditions before trains run played an important role in this railway accident. In conclusion, the constructed model gives a theoretical clue for railway accident prediction and, hence, greatly reduces the occurrence of railway accidents. (interdisciplinary physics and related areas of science and technology)

  10. A network centrality measure framework for analyzing urban traffic flow: A case study of Wuhan, China

    Science.gov (United States)

    Zhao, Shuangming; Zhao, Pengxiang; Cui, Yunfan

    2017-07-01

    In this paper, we propose an improved network centrality measure framework that takes into account both the topological characteristics and the geometric properties of a road network in order to analyze urban traffic flow in relation to different modes: intersection, road, and community, which correspond to point mode, line mode, and area mode respectively. Degree, betweenness, and PageRank centralities are selected as the analysis measures, and GPS-enabled taxi trajectory data is used to evaluate urban traffic flow. The results show that the mean value of the correlation coefficients between the modified degree, the betweenness, and the PageRank centralities and the traffic flow in all periods are higher than the mean value of the correlation coefficients between the conventional degree, the betweenness, the PageRank centralities and the traffic flow at different modes; this indicates that the modified measurements, for analyzing traffic flow, are superior to conventional centrality measurements. This study helps to shed light into the understanding of urban traffic flow in relation to different modes from the perspective of complex networks.

  11. Construction and comparison of gene co-expression networks shows complex plant immune responses

    Directory of Open Access Journals (Sweden)

    Luis Guillermo Leal

    2014-10-01

    Full Text Available Gene co-expression networks (GCNs are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species. In this work, a methodology for the reconstruction and comparison of GCNs is presented. This approach was applied using gene expression data that were obtained from immunity experiments in Arabidopsis thaliana, rice, soybean, tomato and cassava. After the evaluation of diverse similarity metrics for the GCN reconstruction, we recommended the mutual information coefficient measurement and a clustering coefficient-based method for similarity threshold selection. To compare GCNs, we proposed a multivariate approach based on the Principal Component Analysis (PCA. Branches of plant immunity that were exemplified by each experiment were analyzed in conjunction with the PCA results, suggesting both the robustness and the dynamic nature of the cellular responses. The dynamic of molecular plant responses produced networks with different characteristics that are differentiable using our methodology. The comparison of GCNs from plant pathosystems, showed that in response to similar pathogens plants could activate conserved signaling pathways. The results confirmed that the closeness of GCNs projected on the principal component space is an indicative of similarity among GCNs. This also can be used to understand global patterns of events triggered during plant immune responses.

  12. Analyzing the factors affecting network lifetime cluster-based wireless sensor network

    International Nuclear Information System (INIS)

    Malik, A.S.; Qureshi, A.

    2010-01-01

    Cluster-based wireless sensor networks enable the efficient utilization of the limited energy resources of the deployed sensor nodes and hence prolong the node as well as network lifetime. Low Energy Adaptive Clustering Hierarchy (Leach) is one of the most promising clustering protocol proposed for wireless sensor networks. This paper provides the energy utilization and lifetime analysis for cluster-based wireless sensor networks based upon LEACH protocol. Simulation results identify some important factors that induce unbalanced energy utilization between the sensor nodes and hence affect the network lifetime in these types of networks. These results highlight the need for a standardized, adaptive and distributed clustering technique that can increase the network lifetime by further balancing the energy utilization among sensor nodes. (author)

  13. Analysis of Few-Mode Multi-Core Fiber Splice Behavior Using an Optical Vector Network Analyzer

    DEFF Research Database (Denmark)

    Rommel, Simon; Mendinueta, Jose Manuel Delgado; Klaus, Werner

    2017-01-01

    The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively and negativ......The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively...

  14. Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks.

    Directory of Open Access Journals (Sweden)

    Xiaoke Ma

    2015-06-01

    Full Text Available Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules. We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression.

  15. Accuracy assessment of the scalar network analyzer using sliding termination techniques

    DEFF Research Database (Denmark)

    Knudsen, Bent; Engen, Glenn F.; Guldbrandsen, Birthe

    1989-01-01

    In the absence of phase response the major, if not the primary, sources of error in the scalar network analyzer are the imperfect directivity, etc., associated with its internal and frequently inaccessible test set or measurement network. An explicit expression is obtained for this error in terms...

  16. Software network analyzer for computer network performance measurement planning over heterogeneous services in higher educational institutes

    OpenAIRE

    Ismail, Mohd Nazri

    2009-01-01

    In 21st century, convergences of technologies and services in heterogeneous environment have contributed multi-traffic. This scenario will affect computer network on learning system in higher educational Institutes. Implementation of various services can produce different types of content and quality. Higher educational institutes should have a good computer network infrastructure to support usage of various services. The ability of computer network should consist of i) higher bandwidth; ii) ...

  17. A human protein interaction network shows conservation of aging processes between human and invertebrate species.

    Directory of Open Access Journals (Sweden)

    Russell Bell

    2009-03-01

    Full Text Available We have mapped a protein interaction network of human homologs of proteins that modify longevity in invertebrate species. This network is derived from a proteome-scale human protein interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity network is composed of 175 human homologs of proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human proteins that interact with these homologs. Overall, the network consists of 3,271 binary interactions among 2,338 unique proteins. A comparison of the average node degree of the human longevity homologs with random sets of proteins in the Core Network indicates that human homologs of longevity proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that proteins in this network are significantly more connected than would be expected by chance. To examine the relationship of this network to human aging phenotypes, we compared the genes encoding longevity network proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity protein homologs and their interactors, we observed enrichments for differentially expressed genes in the network. To determine whether homologs of human longevity interacting proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity protein interaction network presented here is enriched for novel conserved longevity proteins.

  18. Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease

    Science.gov (United States)

    Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M.; Leonardo, Cassandra D.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matthew A.; Thompson, Paul M.

    2015-01-01

    Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. PMID:26640830

  19. Building and analyzing protein interactome networks by cross-species comparisons

    Directory of Open Access Journals (Sweden)

    Blackman Barron

    2010-03-01

    Full Text Available Abstract Background A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. Results The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. Conclusions Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

  20. System, apparatus and methods to implement high-speed network analyzers

    Science.gov (United States)

    Ezick, James; Lethin, Richard; Ros-Giralt, Jordi; Szilagyi, Peter; Wohlford, David E

    2015-11-10

    Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

  1. Analyzing Comprehensive QoS with Security Constraints for Services Composition Applications in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Naixue Xiong

    2014-12-01

    Full Text Available Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs. The quality of service (QoS of services composition applications (SCAs are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique—vector universal generating function (VUGF—which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

  2. Analyzing comprehensive QoS with security constraints for services composition applications in wireless sensor networks.

    Science.gov (United States)

    Xiong, Naixue; Wu, Zhao; Huang, Yannong; Xu, Degang

    2014-12-01

    Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs). The quality of service (QoS) of services composition applications (SCAs) are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF) shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique-vector universal generating function (VUGF)-which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

  3. Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability

    International Nuclear Information System (INIS)

    Ouyang, Min; Zhao, Lijing; Hong, Liu; Pan, Zhezhe

    2014-01-01

    Recently numerous studies have applied complex network based models to study the performance and vulnerability of infrastructure systems under various types of attacks and hazards. But how effective are these models to capture their real performance response is still a question worthy of research. Taking the Chinese railway system as an example, this paper selects three typical complex network based models, including purely topological model (PTM), purely shortest path model (PSPM), and weight (link length) based shortest path model (WBSPM), to analyze railway accessibility and flow-based vulnerability and compare their results with those from the real train flow model (RTFM). The results show that the WBSPM can produce the train routines with 83% stations and 77% railway links identical to the real routines and can approach the RTFM the best for railway vulnerability under both single and multiple component failures. The correlation coefficient for accessibility vulnerability from WBSPM and RTFM under single station failures is 0.96 while it is 0.92 for flow-based vulnerability; under multiple station failures, where each station has the same failure probability fp, the WBSPM can produce almost identical vulnerability results with those from the RTFM under almost all failures scenarios when fp is larger than 0.62 for accessibility vulnerability and 0.86 for flow-based vulnerability

  4. PerturbationAnalyzer: a tool for investigating the effects of concentration perturbation on protein interaction networks.

    Science.gov (United States)

    Li, Fei; Li, Peng; Xu, Wenjian; Peng, Yuxing; Bo, Xiaochen; Wang, Shengqi

    2010-01-15

    The propagation of perturbations in protein concentration through a protein interaction network (PIN) can shed light on network dynamics and function. In order to facilitate this type of study, PerturbationAnalyzer, which is an open source plugin for Cytoscape, has been developed. PerturbationAnalyzer can be used in manual mode for simulating user-defined perturbations, as well as in batch mode for evaluating network robustness and identifying significant proteins that cause large propagation effects in the PINs when their concentrations are perturbed. Results from PerturbationAnalyzer can be represented in an intuitive and customizable way and can also be exported for further exploration. PerturbationAnalyzer has great potential in mining the design principles of protein networks, and may be a useful tool for identifying drug targets. PerturbationAnalyzer can be accessed from the Cytoscape web site http://www.cytoscape.org/plugins/index.php or http://biotech.bmi.ac.cn/PerturbationAnalyzer. Supplementary data are available at Bioinformatics online.

  5. Limitation of degree information for analyzing the interaction evolution in online social networks

    Science.gov (United States)

    Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

    2014-04-01

    Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

  6. Analyzing the reliability of shuffle-exchange networks using reliability block diagrams

    International Nuclear Information System (INIS)

    Bistouni, Fathollah; Jahanshahi, Mohsen

    2014-01-01

    Supercomputers and multi-processor systems are comprised of thousands of processors that need to communicate in an efficient way. One reasonable solution would be the utilization of multistage interconnection networks (MINs), where the challenge is to analyze the reliability of such networks. One of the methods to increase the reliability and fault-tolerance of the MINs is use of various switching stages. Therefore, recently, the reliability of one of the most common MINs namely shuffle-exchange network (SEN) has been evaluated through the investigation on the impact of increasing the number of switching stage. Also, it is concluded that the reliability of SEN with one additional stage (SEN+) is better than SEN or SEN with two additional stages (SEN+2), even so, the reliability of SEN is better compared to SEN with two additional stages (SEN+2). Here we re-evaluate the reliability of these networks where the results of the terminal, broadcast, and network reliability analysis demonstrate that SEN+ and SEN+2 continuously outperform SEN and are very alike in terms of reliability. - Highlights: • The impact of increasing the number of stages on reliability of MINs is investigated. • The RBD method as an accurate method is used for the reliability analysis of MINs. • Complex series–parallel RBDs are used to determine the reliability of the MINs. • All measures of the reliability (i.e. terminal, broadcast, and network reliability) are analyzed. • All reliability equations will be calculated for different size N×N

  7. Tiny Integrated Network Analyzer for Noninvasive Measurements of Electrically Small Antennas

    DEFF Research Database (Denmark)

    Buskgaard, Emil Feldborg; Krøyer, Ben; Tatomirescu, Alexandru

    2016-01-01

    the system. The tiny integrated network analyzer is a stand-alone Arduino-based measurement system that utilizes the transmit signal of the system under test as its reference. It features a power meter with triggering ability, on-board memory, universal serial bus, and easy extendibility with general...

  8. When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks.

    Science.gov (United States)

    Iván, Gábor; Grolmusz, Vince

    2011-02-01

    Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today. Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients. The Perl script for computing the personalized PageRank in protein networks is available for non-profit research applications (together with sample input files) at the address: http://uratim.com/pp.zip.

  9. A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns.

    Science.gov (United States)

    Xu, W; LeBeau, J M

    2018-05-01

    We establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk size, center position, and rotation without the need for pretreating the data. With the aligned data, additional networks then measure the sample thickness and tilt. The performance of the network is explored as a function of a variety of variables including thickness, tilt, and dose. A methodology to explore the response of the neural network to various pattern features is also presented. Processing patterns at a rate of  ∼ 0.1 s/pattern, the network is shown to be orders of magnitude faster than a brute force method while maintaining accuracy. The approach is thus suitable for automatically processing big, 4D STEM data. We also discuss the generality of the method to other materials/orientations as well as a hybrid approach that combines the features of the neural network with least squares fitting for even more robust analysis. The source code is available at https://github.com/subangstrom/DeepDiffraction. Copyright © 2018 Elsevier B.V. All rights reserved.

  10. Analyzing energy consumption of wireless networks. A model-based approach

    Energy Technology Data Exchange (ETDEWEB)

    Yue, Haidi

    2013-03-04

    During the last decades, wireless networking has been continuously a hot topic both in academy and in industry. Many different wireless networks have been introduced like wireless local area networks, wireless personal networks, wireless ad hoc networks, and wireless sensor networks. If these networks want to have a long term usability, the power consumed by the wireless devices in each of these networks needs to be managed efficiently. Hence, a lot of effort has been carried out for the analysis and improvement of energy efficiency, either for a specific network layer (protocol), or new cross-layer designs. In this thesis, we apply model-based approach for the analysis of energy consumption of different wireless protocols. The protocols under consideration are: one leader election protocol, one routing protocol, and two medium access control protocols. By model-based approach we mean that all these four protocols are formalized as some formal models, more precisely, as discrete-time Markov chains (DTMCs), Markov decision processes (MDPs), or stochastic timed automata (STA). For the first two models, DTMCs and MDPs, we model them in PRISM, a prominent model checker for probabilistic model checking, and apply model checking technique to analyze them. Model checking belongs to the family of formal methods. It discovers exhaustively all possible (reachable) states of the models, and checks whether these models meet a given specification. Specifications are system properties that we want to study, usually expressed by some logics, for instance, probabilistic computer tree logic (PCTL). However, while model checking relies on rigorous mathematical foundations and automatically explores the entire state space of a model, its applicability is also limited by the so-called state space explosion problem -- even systems of moderate size often yield models with an exponentially larger state space that thwart their analysis. Hence for the STA models in this thesis, since there

  11. Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

    Science.gov (United States)

    Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

    2016-11-01

    Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

  12. Accurate optical vector network analyzer based on optical single-sideband modulation and balanced photodetection.

    Science.gov (United States)

    Xue, Min; Pan, Shilong; Zhao, Yongjiu

    2015-02-15

    A novel optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation and balanced photodetection is proposed and experimentally demonstrated, which can eliminate the measurement error induced by the high-order sidebands in the OSSB signal. According to the analytical model of the conventional OSSB-based OVNA, if the optical carrier in the OSSB signal is fully suppressed, the measurement result is exactly the high-order-sideband-induced measurement error. By splitting the OSSB signal after the optical device-under-test (ODUT) into two paths, removing the optical carrier in one path, and then detecting the two signals in the two paths using a balanced photodetector (BPD), high-order-sideband-induced measurement error can be ideally eliminated. As a result, accurate responses of the ODUT can be achieved without complex post-signal processing. A proof-of-concept experiment is carried out. The magnitude and phase responses of a fiber Bragg grating (FBG) measured by the proposed OVNA with different modulation indices are superimposed, showing that the high-order-sideband-induced measurement error is effectively removed.

  13. Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms.

    Directory of Open Access Journals (Sweden)

    J Matthew Mahoney

    2015-01-01

    Full Text Available Systemic sclerosis (SSc is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6-12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected

  14. Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

    Directory of Open Access Journals (Sweden)

    Kirouac Daniel C

    2012-05-01

    Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

  15. Development of a new software for analyzing 3-D fracture network

    Science.gov (United States)

    Um, Jeong-Gi; Noh, Young-Hwan; Choi, Yosoon

    2014-05-01

    A new software is presented to analyze fracture network in 3-D. Recently, we completed the software package based on information given in EGU2013. The software consists of several modules that play roles in management of borehole data, stochastic modelling of fracture network, construction of analysis domain, visualization of fracture geometry in 3-D, calculation of equivalent pipes and production of cross-section diagrams. Intel Parallel Studio XE 2013, Visual Studio.NET 2010 and the open source VTK library were utilized as development tools to efficiently implement the modules and the graphical user interface of the software. A case study was performed to analyze 3-D fracture network system at the Upper Devonian Grosmont Formation in Alberta, Canada. The results have suggested that the developed software is effective in modelling and visualizing 3-D fracture network system, and can provide useful information to tackle the geomechanical problems related to strength, deformability and hydraulic behaviours of the fractured rock masses. This presentation describes the concept and details of the development and implementation of the software.

  16. New Theoretical Analysis of the LRRM Calibration Technique for Vector Network Analyzers

    OpenAIRE

    Purroy Martín, Francesc; Pradell i Cara, Lluís

    2001-01-01

    In this paper, a new theoretical analysis of the four-standards line-reflect-reflect-match (LRRM) vector network-analyzer (VNA) calibration technique is presented. As a result, it is shown that the reference-impedance (to which the LRRM calibration is referred) cannot generally be defined whenever nonideal standards are used. Based on this consideration, a new algorithm to determine the on-wafer match standard is proposed that improves the LRRM calibration accuracy. Experimental verification ...

  17. Analyzing topological characteristics of neuronal functional networks in the rat brain

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Hu [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); School of Computer Science, Fudan University, Shanghai 200433 (China); Yang, Shengtao [Institutes of Brain Science, Fudan University, Shanghai 200433 (China); Song, Yuqing [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); Wei, Hui [School of Computer Science, Fudan University, Shanghai 200433 (China)

    2014-08-28

    In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats. - Highlights: • We constructed the neuronal function networks based on the recorded neurons. • We analyzed the two main complex network characteristics, namely, small-world structure and community structure. • NFNs which were constructed based on the recorded neurons in this study exhibit small-world properties. • Some NFNs have community structure characteristics.

  18. Analyzing topological characteristics of neuronal functional networks in the rat brain

    International Nuclear Information System (INIS)

    Lu, Hu; Yang, Shengtao; Song, Yuqing; Wei, Hui

    2014-01-01

    In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats. - Highlights: • We constructed the neuronal function networks based on the recorded neurons. • We analyzed the two main complex network characteristics, namely, small-world structure and community structure. • NFNs which were constructed based on the recorded neurons in this study exhibit small-world properties. • Some NFNs have community structure characteristics

  19. Identify and analyze the opportunities and threats of social networks for shahid Beheshti University students

    Directory of Open Access Journals (Sweden)

    R. Tavalaee

    2017-09-01

    Full Text Available Due to the growth of information and communication technology in societies Especially among students, the use of these technologies has become as part of regular working people. Social networks as one of the most important and widely in cyberspace which is Used by many people in various fields. application of social network by students as young and educated population is important.In this regard, this study aimed to investigate and identify the opportunities and threats for shahid Beheshti University students in social network. This study aims to develop a practical and descriptive methodology. Information obtained from the questionnaires using SPSS statistical analysis software in two parts: descriptive and inferential statistics were analyzed.The results indicate that five variables related to social networking opportunities, including e-learning, leisure, organized social groups, the possibility of dialogue and culture, as well as five variables related to social networking threats, including transfer value unethical, abusive, spreading false information, internet & Communications destructive addiction, has a significant positive effect on students.

  20. Analyzing self-similar and fractal properties of the C. elegans neural network.

    Directory of Open Access Journals (Sweden)

    Tyler M Reese

    Full Text Available The brain is one of the most studied and highly complex systems in the biological world. While much research has concentrated on studying the brain directly, our focus is the structure of the brain itself: at its core an interconnected network of nodes (neurons. A better understanding of the structural connectivity of the brain should elucidate some of its functional properties. In this paper we analyze the connectome of the nematode Caenorhabditis elegans. Consisting of only 302 neurons, it is one of the better-understood neural networks. Using a Laplacian Matrix of the 279-neuron "giant component" of the network, we use an eigenvalue counting function to look for fractal-like self similarity. This matrix representation is also used to plot visualizations of the neural network in eigenfunction coordinates. Small-world properties of the system are examined, including average path length and clustering coefficient. We test for localization of eigenfunctions, using graph energy and spacial variance on these functions. To better understand results, all calculations are also performed on random networks, branching trees, and known fractals, as well as fractals which have been "rewired" to have small-world properties. We propose algorithms for generating Laplacian matrices of each of these graphs.

  1. How Unstable Are Complex Financial Systems? Analyzing an Inter-bank Network of Credit Relations

    Science.gov (United States)

    Sinha, Sitabhra; Thess, Maximilian; Markose, Sheri

    The recent worldwide economic crisis of 2007-09 has focused attention on the need to analyze systemic risk in complex financial networks. We investigate the problem of robustness of such systems in the context of the general theory of dynamical stability in complex networks and, in particular, how the topology of connections influence the risk of the failure of a single institution triggering a cascade of successive collapses propagating through the network. We use data on bilateral liabilities (or exposure) in the derivatives market between 202 financial intermediaries based in USA and Europe in the last quarter of 2009 to empirically investigate the network structure of the over-the-counter (OTC) derivatives market. We observe that the network exhibits both heterogeneity in node properties and the existence of communities. It also has a prominent core-periphery organization and can resist large-scale collapse when subjected to individual bank defaults (however, failure of any bank in the core may result in localized collapse of the innermost core with substantial loss of capital) but is vulnerable to system-wide breakdown as a result of an accompanying liquidity crisis.

  2. Identifying and Analyzing Strong Components of an Industrial Network Based on Cycle Degree

    Directory of Open Access Journals (Sweden)

    Zhiying Zhang

    2016-01-01

    Full Text Available In the era of big data and cloud computing, data research focuses not only on describing the individual characteristics but also on depicting the relationships among individuals. Studying dependence and constraint relationships among industries has aroused significant interest in the academic field. From the network perspective, this paper tries to analyze industrial relational structures based on cycle degree. The cycle degree of a vertex, that is, the number of cycles through a vertex in an industrial network, can describe the roles of the vertices of strong components in industrial circulation. In most cases, different vertices in a strong component have different cycle degrees, and the one with a larger cycle degree plays more important roles. However, the concept of cycle degree does not involve the lengths of the cycles, which are also important for circulations. The more indirect the relationship between two industries is, the weaker it is. In order to analyze strong components thoroughly, this paper proposes the concept of circular centrality taking into consideration the influence by two factors: the lengths and the numbers of cycles through a vertex. Exemplification indicates that a profound analysis of strong components in an industrial network can reveal the features of an economy.

  3. Improved equivalent magnetic network modeling for analyzing working points of PMs in interior permanent magnet machine

    Science.gov (United States)

    Guo, Liyan; Xia, Changliang; Wang, Huimin; Wang, Zhiqiang; Shi, Tingna

    2018-05-01

    As is well known, the armature current will be ahead of the back electromotive force (back-EMF) under load condition of the interior permanent magnet (PM) machine. This kind of advanced armature current will produce a demagnetizing field, which may make irreversible demagnetization appeared in PMs easily. To estimate the working points of PMs more accurately and take demagnetization under consideration in the early design stage of a machine, an improved equivalent magnetic network model is established in this paper. Each PM under each magnetic pole is segmented, and the networks in the rotor pole shoe are refined, which makes a more precise model of the flux path in the rotor pole shoe possible. The working point of each PM under each magnetic pole can be calculated accurately by the established improved equivalent magnetic network model. Meanwhile, the calculated results are compared with those calculated by FEM. And the effects of d-axis component and q-axis component of armature current, air-gap length and flux barrier size on working points of PMs are analyzed by the improved equivalent magnetic network model.

  4. ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation

    Science.gov (United States)

    Matsuyama, Shinako; Terano, Takao

    This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.

  5. Calibration-measurement unit for the automation of vector network analyzer measurements

    Directory of Open Access Journals (Sweden)

    I. Rolfes

    2008-05-01

    Full Text Available With the availability of multi-port vector network analyzers, the need for automated, calibrated measurement facilities increases. In this contribution, a calibration-measurement unit is presented which realizes a repeatable automated calibration of the measurement setup as well as a user-friendly measurement of the device under test (DUT. In difference to commercially available calibration units, which are connected to the ports of the vector network analyzer preceding a measurement and which are then removed so that the DUT can be connected, the presented calibration-measurement unit is permanently connected to the ports of the VNA for the calibration as well as for the measurement of the DUT. This helps to simplify the calibrated measurement of complex scattering parameters. Moreover, a full integration of the calibration unit into the analyzer setup becomes possible. The calibration-measurement unit is based on a multiport switch setup of e.g. electromechanical relays. Under the assumption of symmetry of a switch, on the one hand the unit realizes the connection of calibration standards like one-port reflection standards and two-port through connections between different ports and on the other hand it enables the connection of the DUT. The calibration-measurement unit is applicable for two-port VNAs as well as for multiport VNAs. For the calibration of the unit, methods with completely known calibration standards like SOLT (short, open, load, through as well as self-calibration procedures like TMR or TLR can be applied.

  6. A queueing network model to analyze the impact of parallelization of care on patient cycle time.

    Science.gov (United States)

    Jiang, Lixiang; Giachetti, Ronald E

    2008-09-01

    The total time a patient spends in an outpatient facility, called the patient cycle time, is a major contributor to overall patient satisfaction. A frequently recommended strategy to reduce the total time is to perform some activities in parallel thereby shortening patient cycle time. To analyze patient cycle time this paper extends and improves upon existing multi-class open queueing network model (MOQN) so that the patient flow in an urgent care center can be modeled. Results of the model are analyzed using data from an urgent care center contemplating greater parallelization of patient care activities. The results indicate that parallelization can reduce the cycle time for those patient classes which require more than one diagnostic and/ or treatment intervention. However, for many patient classes there would be little if any improvement, indicating the importance of tools to analyze business process reengineering rules. The paper makes contributions by implementing an approximation for fork/join queues in the network and by improving the approximation for multiple server queues in both low traffic and high traffic conditions. We demonstrate the accuracy of the MOQN results through comparisons to simulation results.

  7. Evaluation of axial pile bearing capacity based on pile driving analyzer (PDA) test using Neural Network

    Science.gov (United States)

    Maizir, H.; Suryanita, R.

    2018-01-01

    A few decades, many methods have been developed to predict and evaluate the bearing capacity of driven piles. The problem of the predicting and assessing the bearing capacity of the pile is very complicated and not yet established, different soil testing and evaluation produce a widely different solution. However, the most important thing is to determine methods used to predict and evaluate the bearing capacity of the pile to the required degree of accuracy and consistency value. Accurate prediction and evaluation of axial bearing capacity depend on some variables, such as the type of soil, diameter, and length of pile, etc. The aims of the study of Artificial Neural Networks (ANNs) are utilized to obtain more accurate and consistent axial bearing capacity of a driven pile. ANNs can be described as mapping an input to the target output data. The method using the ANN model developed to predict and evaluate the axial bearing capacity of the pile based on the pile driving analyzer (PDA) test data for more than 200 selected data. The results of the predictions obtained by the ANN model and the PDA test were then compared. This research as the neural network models give a right prediction and evaluation of the axial bearing capacity of piles using neural networks.

  8. Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

    International Nuclear Information System (INIS)

    Main, P.; Navarro, H.

    2009-01-01

    Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distribution of some unknown variables of interest given a set of evidential nodes whose values are known. The problem of uncertainty about the assumption of normality is very common in applications. Thus a sensitivity analysis of the non-normality effect in our conclusions could be necessary. The aspect of non-normality to be considered is the tail behavior. In this line, the multivariate exponential power distribution is a family depending on a kurtosis parameter that goes from a leptokurtic to a platykurtic distribution with the normal as a mesokurtic distribution. Therefore a more general model can be considered using the multivariate exponential power distribution to describe the joint distribution of a Bayesian network, with a kurtosis parameter reflecting deviations from the normal distribution. The sensitivity of the conclusions to this perturbation is analyzed using the Kullback-Leibler divergence measure that provides an interesting formula to evaluate the effect

  9. Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

    Energy Technology Data Exchange (ETDEWEB)

    Main, P. [Dpto. Estadistica e I.O., Fac. Ciencias Matematicas, Univ. Complutense de Madrid, 28040 Madrid (Spain)], E-mail: pmain@mat.ucm.es; Navarro, H. [Dpto. de Estadistica, I.O. y Calc. Numerico, Fac. Ciencias, UNED, 28040 Madrid (Spain)

    2009-05-15

    Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distribution of some unknown variables of interest given a set of evidential nodes whose values are known. The problem of uncertainty about the assumption of normality is very common in applications. Thus a sensitivity analysis of the non-normality effect in our conclusions could be necessary. The aspect of non-normality to be considered is the tail behavior. In this line, the multivariate exponential power distribution is a family depending on a kurtosis parameter that goes from a leptokurtic to a platykurtic distribution with the normal as a mesokurtic distribution. Therefore a more general model can be considered using the multivariate exponential power distribution to describe the joint distribution of a Bayesian network, with a kurtosis parameter reflecting deviations from the normal distribution. The sensitivity of the conclusions to this perturbation is analyzed using the Kullback-Leibler divergence measure that provides an interesting formula to evaluate the effect.

  10. Using Individualized Brain Network for Analyzing Structural Covariance of the Cerebral Cortex in Alzheimer's Patients.

    Science.gov (United States)

    Kim, Hee-Jong; Shin, Jeong-Hyeon; Han, Cheol E; Kim, Hee Jin; Na, Duk L; Seo, Sang Won; Seong, Joon-Kyung

    2016-01-01

    Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC

  11. Analyzing the effect of routing protocols on media access control protocols in radio networks

    Energy Technology Data Exchange (ETDEWEB)

    Barrett, C. L. (Christopher L.); Drozda, M. (Martin); Marathe, A. (Achla); Marathe, M. V. (Madhav V.)

    2002-01-01

    We study the effect of routing protocols on the performance of media access control (MAC) protocols in wireless radio networks. Three well known MAC protocols: 802.11, CSMA, and MACA are considered. Similarly three recently proposed routing protocols: AODV, DSR and LAR scheme 1 are considered. The experimental analysis was carried out using GloMoSim: a tool for simulating wireless networks. The main focus of our experiments was to study how the routing protocols affect the performance of the MAC protocols when the underlying network and traffic parameters are varied. The performance of the protocols was measured w.r.t. five important parameters: (i) number of received packets, (ii) average latency of each packet, (iii) throughput (iv) long term fairness and (v) number of control packets at the MAC layer level. Our results show that combinations of routing and MAC protocols yield varying performance under varying network topology and traffic situations. The result has an important implication; no combination of routing protocol and MAC protocol is the best over all situations. Also, the performance analysis of protocols at a given level in the protocol stack needs to be studied not locally in isolation but as a part of the complete protocol stack. A novel aspect of our work is the use of statistical technique, ANOVA (Analysis of Variance) to characterize the effect of routing protocols on MAC protocols. This technique is of independent interest and can be utilized in several other simulation and empirical studies.

  12. Resting-state networks associated with cognitive processing show more age-related decline than those associated with emotional processing.

    Science.gov (United States)

    Nashiro, Kaoru; Sakaki, Michiko; Braskie, Meredith N; Mather, Mara

    2017-06-01

    Correlations in activity across disparate brain regions during rest reveal functional networks in the brain. Although previous studies largely agree that there is an age-related decline in the "default mode network," how age affects other resting-state networks, such as emotion-related networks, is still controversial. Here we used a dual-regression approach to investigate age-related alterations in resting-state networks. The results revealed age-related disruptions in functional connectivity in all 5 identified cognitive networks, namely the default mode network, cognitive-auditory, cognitive-speech (or speech-related somatosensory), and right and left frontoparietal networks, whereas such age effects were not observed in the 3 identified emotion networks. In addition, we observed age-related decline in functional connectivity in 3 visual and 3 motor/visuospatial networks. Older adults showed greater functional connectivity in regions outside 4 out of the 5 identified cognitive networks, consistent with the dedifferentiation effect previously observed in task-based functional magnetic resonance imaging studies. Both reduced within-network connectivity and increased out-of-network connectivity were correlated with poor cognitive performance, providing potential biomarkers for cognitive aging. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

    Science.gov (United States)

    Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

    2017-04-27

    Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By

  14. Combining evolutionary game theory and network theory to analyze human cooperation patterns

    International Nuclear Information System (INIS)

    Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro; Catania, Emanuele; Guardo, Ermanno; Pagano, Salvatore

    2016-01-01

    Highlights: • We investigate the evolutionary dynamics of human cooperation in a social network. • We introduce the concepts of “Critical Mass”, centrality measure and homophily. • The emergence of cooperation is affected by the spatial choice of the “Critical Mass”. • Our findings show that homophily speeds up the convergence towards cooperation. • Centrality and “Critical Mass” spatial choice partially offset the impact of homophily. - Abstract: As natural systems continuously evolve, the human cooperation dilemma represents an increasingly more challenging question. Humans cooperate in natural and social systems, but how it happens and what are the mechanisms which rule the emergence of cooperation, represent an open and fascinating issue. In this work, we investigate the evolution of cooperation through the analysis of the evolutionary dynamics of behaviours within the social network, where nodes can choose to cooperate or defect following the classical social dilemmas represented by Prisoner’s Dilemma and Snowdrift games. To this aim, we introduce a sociological concept and statistical estimator, “Critical Mass”, to detect the minimum initial seed of cooperators able to trigger the diffusion process, and the centrality measure to select within the social network. Selecting different spatial configurations of the Critical Mass nodes, we highlight how the emergence of cooperation can be influenced by this spatial choice of the initial core in the network. Moreover, we target to shed light how the concept of homophily, a social shaping factor for which “birds of a feather flock together”, can affect the evolutionary process. Our findings show that homophily allows speeding up the diffusion process and make quicker the convergence towards human cooperation, while centrality measure and thus the Critical Mass selection, play a key role in the evolution showing how the spatial configurations can create some hidden patterns, partially

  15. Livelihood diversification in tropical coastal communities: a network-based approach to analyzing 'livelihood landscapes'.

    Directory of Open Access Journals (Sweden)

    Joshua E Cinner

    Full Text Available BACKGROUND: Diverse livelihood portfolios are frequently viewed as a critical component of household economies in developing countries. Within the context of natural resources governance in particular, the capacity of individual households to engage in multiple occupations has been shown to influence important issues such as whether fishers would exit a declining fishery, how people react to policy, the types of resource management systems that may be applicable, and other decisions about natural resource use. METHODOLOGY/PRINCIPAL FINDINGS: This paper uses network analysis to provide a novel methodological framework for detailed systemic analysis of household livelihood portfolios. Paying particular attention to the role of natural resource-based occupations such as fisheries, we use network analyses to map occupations and their interrelationships- what we refer to as 'livelihood landscapes'. This network approach allows for the visualization of complex information about dependence on natural resources that can be aggregated at different scales. We then examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities in 5 western Indian Ocean countries. Network statistics, including in- and out-degree centrality, the density of the network, and the level of network centralization are compared along a multivariate index of community-level socioeconomic development and a gradient of human population density. The combination of network analyses suggests an increase in household-level specialization with development for most occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified. CONCLUSIONS/SIGNIFICANCE: The novel modeling approach introduced here provides for various types of livelihood portfolio analyses at different scales of social aggregation. Our livelihood landscapes approach provides insights

  16. Quasi-Optical Network Analyzers and High-Reliability RF MEMS Switched Capacitors

    Science.gov (United States)

    Grichener, Alexander

    The thesis first presents a 2-port quasi-optical scalar network analyzer consisting of a transmitter and receiver both built in planar technology. The network analyzer is based on a Schottky-diode mixer integrated inside a planar antenna and fed differentially by a CPW transmission line. The antenna is placed on an extended hemispherical high-resistivity silicon substrate lens. The LO signal is swept from 3-5 GHz and high-order harmonic mixing in both up- and down- conversion mode is used to realize the 15-50 GHz RF bandwidth. The network analyzer resulted in a dynamic range of greater than 40 dB and was successfully used to measure a frequency selective surface with a second-order bandpass response. Furthermore, the system was built with circuits and components for easy scaling to millimeter-wave frequencies which is the primary motivation for this work. The application areas for a millimeter and submillimeter-wave network analyzer include material characterization and art diagnostics. The second project presents several RF MEMS switched capacitors designed for high-reliability operation and suitable for tunable filters and reconfigurable networks. The first switched-capacitor resulted in a digital capacitance ratio of 5 and an analog capacitance ratio of 5-9. The analog tuning of the down-state capacitance is enhanced by a positive vertical stress gradient in the the beam, making it ideal for applications that require precision tuning. A thick electroplated beam resulted in Q greater than 100 at C to X-band frequencies, and power handling of 0.6-1.1 W. The design also minimized charging in the dielectric, resulting in excellent reliability performance even under hot-switched and high power (1 W) conditions. The second switched-capacitor was designed without any dielectric to minimize charging. The device was hot-switched at 1 W of RF power for greater than 11 billion cycles with virtually no change in the C-V curve. The final project presents a 7-channel

  17. Biana: a software framework for compiling biological interactions and analyzing networks.

    Science.gov (United States)

    Garcia-Garcia, Javier; Guney, Emre; Aragues, Ramon; Planas-Iglesias, Joan; Oliva, Baldo

    2010-01-27

    The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

  18. ATHENA [Advanced Thermal Hydraulic Energy Network Analyzer] solutions to developmental assessment problems

    International Nuclear Information System (INIS)

    Carlson, K.E.; Ransom, V.H.; Roth, P.A.

    1987-03-01

    The ATHENA (Advanced Thermal Hydraulic Energy Network Analyzer) code has been developed to perform transient simulation of the thermal hydraulic systems that may be found in fusion reactors, space reactors, and other advanced systems. As an assessment of current capability the code was applied to a number of physical problems, both conceptual and actual experiments. Results indicate that the numerical solution to the basic conservation equations is technically sound, and that generally good agreement can be obtained when modeling relevant hydrodynamic experiments. The assessment also demonstrates basic fusion system modeling capability and verifies compatibility of the code with both CDC and CRAY mainframes. Areas where improvements could be made include constitutive modeling, which describes the interfacial exchange term. 13 refs., 84 figs

  19. Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD for brain cancer

    Directory of Open Access Journals (Sweden)

    Ying Huang

    2015-07-01

    Full Text Available The rapid development of new and emerging science & technologies (NESTs brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area – nano-enabled drug delivery (NEDD. NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1 international cooperation is increasing, but networking characteristics change over time; (2 highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3 research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

  20. Singular value decomposition and artificial neutral network for analyzing bonner sphere data

    International Nuclear Information System (INIS)

    Zhu, Qingjun; Song, Gang; Song, Fengquan; Guo, Qian; Wu, Yican

    2012-01-01

    The objective of this study was to build an effective and reliable method based on the artificial neural network (ANN) model for unfolding neutron spectrum. The number of counts measured by 15 Bonner spheres and 281 neutron spectra were selected as the database. After singular value decomposition was used to determine the relationship between Bonner spheres, 11 Bonner spheres were chosen as input descriptors. The three-layer feedforward neural networks (11-5-1) were employed to predict the spectrum in each energy bin. Using information entropy theory and the results of the ANN calculations, the sensitivity of each sphere to the entropy of the spectrum was quantitatively analyzed. The spectra results were compared with the results obtained using the maximum entropy method (MEM). The averaged root mean-square-error (MSE) of the MEM output and the desired spectra was 0.012; the averaged MSE of the ANN calculations was 0.006. The MSE results indicate that the 11-5-1 ANN models are able to accurately and reliably predict neutron spectra. The ANN model developed in this study to unfold neutron spectra from the counts measured by 11 Bonner spheres provides an alternative method for unfolding spectrum. The singular value decomposition is an effective method for the analysis of data obtained from Bonner spheres and the neutron spectra.

  1. An Artificial Neural Network for Analyzing Overall Uniformity in Outdoor Lighting Systems

    Directory of Open Access Journals (Sweden)

    Antonio del Corte-Valiente

    2017-02-01

    Full Text Available Street lighting installations are an essential service for modern life due to their capability of creating a welcoming feeling at nighttime. Nevertheless, several studies have highlighted that it is possible to improve the quality of the light significantly improving the uniformity of the illuminance. The main difficulty arises when trying to improve some of the installation’s characteristics based only on statistical analysis of the light distribution. This paper presents a new algorithm that is able to obtain the overall illuminance uniformity in order to improve this sort of installations. To develop this algorithm it was necessary to perform a detailed study of all the elements which are part of street lighting installations. Because classification is one of the most important tasks in the application areas of artificial neural networks, we compared the performances of six types of training algorithms in a feed forward neural network for analyzing the overall uniformity in outdoor lighting systems. We found that the best algorithm that minimizes the error is “Levenberg-Marquardt back-propagation”, which approximates the desired output of the training pattern. By means of this kind of algorithm, it is possible to help to lighting professionals optimize the quality of street lighting installations.

  2. 77 FR 29637 - Game Show Network, LLC v. Cablevision Systems Corp.

    Science.gov (United States)

    2012-05-18

    ... Affairs Bureau at (202) 418-0530 (voice), (202) 418-0432 (TTY). Synopsis of the Order I. Introduction 1... its affiliated cable networks (American Movie Classics (AMC), Fuse, Independent Film Channel, WE tv...

  3. Using an agent-based model to analyze the dynamic communication network of the immune response

    Directory of Open Access Journals (Sweden)

    Doolittle John

    2011-01-01

    Full Text Available Abstract Background The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines. While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines, chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics, ultimately for the design of therapeutic interventions. Results Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations ending in viral elimination (win versus persistent infection (loss, due to the removal of infected agents. However, early cellular interactions preceded successful clearance of infection. Specifically, more Dendritic Agent interactions with TCell and BCell Agents, and more BCell Agent interactions with TCell Agents early in the simulation were associated with the immune win outcome. The Dendritic Agents greatly influenced the outcome, confirming them as hub agents of the immune network. In addition, unexpectedly high frequencies of Dendritic Agent-self interactions occurred in the lymphoid compartment late in the

  4. Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

    Science.gov (United States)

    Rap, Shelley; Blonder, Ron

    2016-02-01

    We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse events were tallied in the different groups. We analyzed the different events that were found in chemistry learning Facebook groups (CLFGs). The analysis revealed that seven types of interactions were observed in the CLFGs: The most common interaction (47 %) dealt with organizing learning (e.g., announcements regarding homework, the location of the next class); learning interactions were observed in 22 % of the posts, and links to learning materials and social interactions constituted about 20 % each. The learning events that were ascertained underwent a deeper examination and three different types of chemistry learning interactions were identified. This examination was based on the theoretical framework of the commognitive approach to learning (Sfard in Thinking as communicating. Cambridge University Press, Cambridge, 2008), which will be explained. The identified learning interactions that were observed in the Facebook groups illustrate the potential of SNs to serve as an additional tool for teachers to advance their students' learning of chemistry.

  5. Radar cross-section measurements of ice particles using vector network analyzer

    Directory of Open Access Journals (Sweden)

    Jinhu Wang

    2016-09-01

    Full Text Available We carried out radar cross-section (RSC measurements of ice particles in a microwave anechoic chamber at Nanjing University of Information Science and Technology. We used microwave similarity theory to enlarge the size of particle from the micrometer to millimeter scale and to reduce the testing frequency from 94 GHz to 10 GHz. The microwave similarity theory was validated using the method of moments for single metal sphere, single dielectric sphere, and spherical and non-spherical dielectric particle swarms. The differences between the retrieved and theoretical results at 94 GHz were 0.016117%, 0.0023029%, 0.027627%, and 0.0046053%, respectively. We proposed a device that can measure the RCS of ice particles in the chamber based on the S21 parameter obtained from vector network analyzer. On the basis of the measured S21 parameter of the calibration material (metal plates and their corresponding theoretical RCS values, the RCS values of a spherical Teflon particle swarm and cuboid candle particle swarm was retrieved at 10 GHz. In this case, the differences between the retrieved and theoretical results were 12.72% and 24.49% for the Teflon particle swarm and cuboid candle swarm, respectively.

  6. Wideband optical vector network analyzer based on optical single-sideband modulation and optical frequency comb.

    Science.gov (United States)

    Xue, Min; Pan, Shilong; He, Chao; Guo, Ronghui; Zhao, Yongjiu

    2013-11-15

    A novel approach to increase the measurement range of the optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation is proposed and experimentally demonstrated. In the proposed system, each comb line in an optical frequency comb (OFC) is selected by an optical filter and used as the optical carrier for the OSSB-based OVNA. The frequency responses of an optical device-under-test (ODUT) are thus measured channel by channel. Because the comb lines in the OFC have fixed frequency spacing, by fitting the responses measured in all channels together, the magnitude and phase responses of the ODUT can be accurately achieved in a large range. A proof-of-concept experiment is performed. A measurement range of 105 GHz and a resolution of 1 MHz is achieved when a five-comb-line OFC with a frequency spacing of 20 GHz is applied to measure the magnitude and phase responses of a fiber Bragg grating.

  7. Measurements by a Vector Network Analyzer at 325 to 508 GHz

    Science.gov (United States)

    Fung, King Man; Samoska, Lorene; Chattopadhyay, Goutam; Gaier, Todd; Kangaslahti, Pekka; Pukala, David; Lau, Yuenie; Oleson, Charles; Denning, Anthony

    2008-01-01

    Recent experiments were performed in which return loss and insertion loss of waveguide test assemblies in the frequency range from 325 to 508 GHz were measured by use of a swept-frequency two-port vector network analyzer (VNA) test set. The experiments were part of a continuing effort to develop means of characterizing passive and active electronic components and systems operating at ever increasing frequencies. The waveguide test assemblies comprised WR-2.2 end sections collinear with WR-3.3 middle sections. The test set, assembled from commercially available components, included a 50-GHz VNA scattering- parameter test set and external signal synthesizers, augmented with recently developed frequency extenders, and further augmented with attenuators and amplifiers as needed to adjust radiofrequency and intermediate-frequency power levels between the aforementioned components. The tests included line-reflect-line calibration procedures, using WR-2.2 waveguide shims as the "line" standards and waveguide flange short circuits as the "reflect" standards. Calibrated dynamic ranges somewhat greater than about 20 dB for return loss and 35 dB for insertion loss were achieved. The measurement data of the test assemblies were found to substantially agree with results of computational simulations.

  8. Cisco Router and Switch Forensics Investigating and Analyzing Malicious Network Activity

    CERN Document Server

    Liu, Dale

    2009-01-01

    Cisco IOS (the software that runs the vast majority of Cisco routers and all Cisco network switches) is the dominant routing platform on the Internet and corporate networks. This widespread distribution, as well as its architectural deficiencies, makes it a valuable target for hackers looking to attack a corporate or private network infrastructure. Compromised devices can disrupt stability, introduce malicious modification, and endanger all communication on the network. For security of the network and investigation of attacks, in-depth analysis and diagnostics are critical, but no book current

  9. Framework based on communicability and flow to analyze complex network dynamics

    Science.gov (United States)

    Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.

    2018-05-01

    Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.

  10. Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees.

    Directory of Open Access Journals (Sweden)

    Catherine Hobaiter

    2014-09-01

    Full Text Available Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition--that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, "moss-sponging" and "leaf-sponge re-use," in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most "cultural" of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.

  11. Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees.

    Science.gov (United States)

    Hobaiter, Catherine; Poisot, Timothée; Zuberbühler, Klaus; Hoppitt, William; Gruber, Thibaud

    2014-09-01

    Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition--that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, "moss-sponging" and "leaf-sponge re-use," in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most "cultural" of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.

  12. Functional coupling networks inferred from prefrontal cortex activity show experience-related effective plasticity

    Directory of Open Access Journals (Sweden)

    Gaia Tavoni

    2017-10-01

    Full Text Available Functional coupling networks are widely used to characterize collective patterns of activity in neural populations. Here, we ask whether functional couplings reflect the subtle changes, such as in physiological interactions, believed to take place during learning. We infer functional network models reproducing the spiking activity of simultaneously recorded neurons in prefrontal cortex (PFC of rats, during the performance of a cross-modal rule shift task (task epoch, and during preceding and following sleep epochs. A large-scale study of the 96 recorded sessions allows us to detect, in about 20% of sessions, effective plasticity between the sleep epochs. These coupling modifications are correlated with the coupling values in the task epoch, and are supported by a small subset of the recorded neurons, which we identify by means of an automatized procedure. These potentiated groups increase their coativation frequency in the spiking data between the two sleep epochs, and, hence, participate to putative experience-related cell assemblies. Study of the reactivation dynamics of the potentiated groups suggests a possible connection with behavioral learning. Reactivation is largely driven by hippocampal ripple events when the rule is not yet learned, and may be much more autonomous, and presumably sustained by the potentiated PFC network, when learning is consolidated. Cell assemblies coding for memories are widely believed to emerge through synaptic modification resulting from learning, yet their identification from activity is very arduous. We propose a functional-connectivity-based approach to identify experience-related cell assemblies from multielectrode recordings in vivo, and apply it to the prefrontal cortex activity of rats recorded during a task epoch and the preceding and following sleep epochs. We infer functional couplings between the recorded cells in each epoch. Comparisons of the functional coupling networks across the epochs allow us

  13. [Macromolecular aromatic network characteristics of Chinese power coal analyzed by synchronous fluorescence and X-ray diffraction].

    Science.gov (United States)

    Ye, Cui-Ping; Feng, Jie; Li, Wen-Ying

    2012-07-01

    Coal structure, especially the macromolecular aromatic skeleton structure, has a strong influence on coke reactivity and coal gasification, so it is the key to grasp the macromolecular aromatic skeleton coal structure for getting the reasonable high efficiency utilization of coal. However, it is difficult to acquire their information due to the complex compositions and structure of coal. It has been found that the macromolecular aromatic network coal structure would be most isolated if small molecular of coal was first extracted. Then the macromolecular aromatic skeleton coal structure would be clearly analyzed by instruments, such as X-ray diffraction (XRD), fluorescence spectroscopy with synchronous mode (Syn-F), Gel permeation chromatography (GPC) etc. Based on the previous results, according to the stepwise fractional liquid extraction, two Chinese typical power coals, PS and HDG, were extracted by silica gel as stationary phase and acetonitrile, tetrahydrofuran (THF), pyridine and 1-methyl-2-pyrollidinone (NMP) as a solvent group for sequential elution. GPC, Syn-F and XRD were applied to investigate molecular mass distribution, condensed aromatic structure and crystal characteristics. The results showed that the size of aromatic layers (La) is small (3-3.95 nm) and the stacking heights (Lc) are 0.8-1.2 nm. The molecular mass distribution of the macromolecular aromatic network structure is between 400 and 1 130 amu, with condensed aromatic numbers of 3-7 in the structure units.

  14. Analyzing 3D xylem networks in Vitis vinifera using High Resolution Computed Tomography (HRCT)

    Science.gov (United States)

    Recent developments in High Resolution Computed Tomography (HRCT) have made it possible to visualize three dimensional (3D) xylem networks without time consuming, labor intensive physical sectioning. Here we describe a new method to visualize complex vessel networks in plants and produce a quantitat...

  15. Analyzing on Reality TV Show in the Perspective of Performance Study%电视真人秀节目的表演学解读

    Institute of Scientific and Technical Information of China (English)

    李绍元

    2012-01-01

    表演学为电视真人秀提供了一种新的研究视野和研究路径。在真人秀节目的表演学解读中,可以将自我呈现作为逻辑前设,把自我实现作为目标诉求,考察节目选手、主持、评委、观众、电视媒体乃至政府等主体的行为。分析真人秀表演的自我呈现、规范向度、审美旨趣和中介化问题。在这个意义上说,电视真人秀其实是一种表演范式,它既是一种审美表演(舞台表演),也是一种社会表演,还是一种媒介表演。%Performance study provides a new research field of vision and research path to the reality TV show. If we discuss reality TV show according to performance study,we will acquire the presentation of self as the logical presupposition,will set self-fulfillment as a target appeal,analyze the behavior of the players, the judges, the audience, the TV media and the government officials etc.,and research the presentation of self presentation, the standard dimension, the aesthetic objective and the mediated problems. In this sense, the reality TV show is actually a kind of performance model, which is not only a kind of aesthetic performance (stage performance), but also a kind social performance and media performance.

  16. Protracted abstinence from distinct drugs of abuse shows regulation of a common gene network.

    Science.gov (United States)

    Le Merrer, Julie; Befort, Katia; Gardon, Olivier; Filliol, Dominique; Darcq, Emmanuel; Dembele, Doulaye; Becker, Jerome A J; Kieffer, Brigitte L

    2012-01-01

    Addiction is a chronic brain disorder. Prolonged abstinence from drugs of abuse involves dysphoria, high stress responsiveness and craving. The neurobiology of drug abstinence, however, is poorly understood. We previously identified a unique set of hundred mu-opioid receptor-dependent genes in the extended amygdala, a key site for hedonic and stress processing in the brain. Here we examined these candidate genes either immediately after chronic morphine, nicotine, Δ9-tetrahydrocannabinol or alcohol, or following 4 weeks of abstinence. Regulation patterns strongly differed among chronic groups. In contrast, gene regulations strikingly converged in the abstinent groups and revealed unforeseen common adaptations within a novel huntingtin-centered molecular network previously unreported in addiction research. This study demonstrates that, regardless the drug, a specific set of transcriptional regulations develops in the abstinent brain, which possibly contributes to the negative affect characterizing protracted abstinence. This transcriptional signature may represent a hallmark of drug abstinence and a unitary adaptive molecular mechanism in substance abuse disorders. © 2011 The Authors, Addiction Biology © 2011 Society for the Study of Addiction.

  17. Analyzing the role of networks in Middle East and North African ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2013-11-18

    Nov 18, 2013 ... ... and the role it played in entrepreneurs' success were supported by IDRC. ... entrepreneurs depend mainly on close connections, such as family and ... of the benefits of networking, particularly women entrepreneurs who ...

  18. Modeling and Analyzing Intrusion Attempts to a Computer Network Operating in a Defense in Depth Posture

    National Research Council Canada - National Science Library

    Givens, Mark

    2004-01-01

    In order to ensure the confidentially, integrity, and availability of networked resources operating on the Global Information Grid, the Department of Defense has incorporated a "Defense-in-Depth" posture...

  19. Integrated Autonomous Network Management (IANM) Multi-Topology Route Manager and Analyzer

    National Research Council Canada - National Science Library

    Henderson, Thomas R; Bae, Kyle; Fang, Jin; Kushi, David M

    2008-01-01

    .... In a previous ONR research effort, Boeing and Cisco Systems had studied the applicability of MTR in the context of Navy network scenarios, and Boeing had produced a Linux-based prototype of MTR...

  20. A conceptual framework for analyzing sustainability strategies in industrial supply networks from an innovation perspective.

    NARCIS (Netherlands)

    van Bommel, H.W.M.; van Bommel, Harrie W.M.

    2011-01-01

    This article proposes a new conceptual framework concerning the implementation of sustainability in supply networks from an innovation perspective. Based upon a recent qualitative literature review in environmental, social/ethical and logistics/operations management journals, this article summarizes

  1. A Complex Network Model for Analyzing Railway Accidents Based on the Maximal Information Coefficient

    International Nuclear Information System (INIS)

    Shao Fu-Bo; Li Ke-Ping

    2016-01-01

    It is an important issue to identify important influencing factors in railway accident analysis. In this paper, employing the good measure of dependence for two-variable relationships, the maximal information coefficient (MIC), which can capture a wide range of associations, a complex network model for railway accident analysis is designed in which nodes denote factors of railway accidents and edges are generated between two factors of which MIC values are larger than or equal to the dependent criterion. The variety of network structure is studied. As the increasing of the dependent criterion, the network becomes to an approximate scale-free network. Moreover, employing the proposed network, important influencing factors are identified. And we find that the annual track density-gross tonnage factor is an important factor which is a cut vertex when the dependent criterion is equal to 0.3. From the network, it is found that the railway development is unbalanced for different states which is consistent with the fact. (paper)

  2. Combining many interaction networks to predict gene function and analyze gene lists.

    Science.gov (United States)

    Mostafavi, Sara; Morris, Quaid

    2012-05-01

    In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Analyzing Social Media Networks with NodeXL Insights from a Connected World

    CERN Document Server

    Hansen, Derek; Smith, Marc A

    2010-01-01

    Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

  4. Theoretical Neuroanatomy:Analyzing the Structure, Dynamics,and Function of Neuronal Networks

    Science.gov (United States)

    Seth, Anil K.; Edelman, Gerald M.

    The mammalian brain is an extraordinary object: its networks give rise to our conscious experiences as well as to the generation of adaptive behavior for the organism within its environment. Progress in understanding the structure, dynamics and function of the brain faces many challenges. Biological neural networks change over time, their detailed structure is difficult to elucidate, and they are highly heterogeneous both in their neuronal units and synaptic connections. In facing these challenges, graph-theoretic and information-theoretic approaches have yielded a number of useful insights and promise many more.

  5. Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

    Science.gov (United States)

    Rap, Shelley; Blonder, Ron

    2016-01-01

    We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse…

  6. Analyzing Networked Learning Practices in HigherEducation and Continuing Professional Development

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone

    Deliverable 28.5.4 reports on the preparation of the book "Analysing Networked Learning Practices in Higher Education and Continuing Professional Development", which consists of an Introduction, case studies and a concluding section, which presents the theoretical work and empirical work conducte...

  7. Analyzing the impact of relay station characteristics on uplink performance in cellular network

    NARCIS (Netherlands)

    Dimitrova, D.C.; van den Berg, Hans Leo; Heijenk, Geert

    2009-01-01

    Uplink users in cellular networks, such as UMTS/ HSPA, located at the edge of the cell generally suffer from poor channel conditions. Deploying intermediate relay nodes is seen as a promising approach towards extending cell coverage. This paper focuses on the role of packet scheduling in cellular

  8. Analyzing big data in social media: Text and network analyses of an eating disorder forum.

    Science.gov (United States)

    Moessner, Markus; Feldhege, Johannes; Wolf, Markus; Bauer, Stephanie

    2018-05-10

    Social media plays an important role in everyday life of young people. Numerous studies claim negative effects of social media and media in general on eating disorder risk factors. Despite the availability of big data, only few studies have exploited the possibilities so far in the field of eating disorders. Methods for data extraction, computerized content analysis, and network analysis will be introduced. Strategies and methods will be exemplified for an ad-hoc dataset of 4,247 posts and 34,118 comments by 3,029 users of the proed forum on Reddit. Text analysis with latent Dirichlet allocation identified nine topics related to social support and eating disorder specific content. Social network analysis describes the overall communication patterns, and could identify community structures and most influential users. A linear network autocorrelation model was applied to estimate associations in language among network neighbors. The supplement contains R code for data extraction and analyses. This paper provides an introduction to investigating social media data, and will hopefully stimulate big data social media research in eating disorders. When applied in real-time, the methods presented in this manuscript could contribute to improving the safety of ED-related online communication. © 2018 Wiley Periodicals, Inc.

  9. Social network analysis as a method for analyzing interaction in collaborative online learning environments

    Directory of Open Access Journals (Sweden)

    Patricia Rice Doran

    2011-12-01

    Full Text Available Social network analysis software such as NodeXL has been used to describe participation and interaction in numerous social networks, but it has not yet been widely used to examine dynamics in online classes, where participation is frequently required rather than optional and participation patterns may be impacted by the requirements of the class, the instructor’s activities, or participants’ intrinsic engagement with the subject matter. Such social network analysis, which examines the dynamics and interactions among groups of participants in a social network or learning group, can be valuable in programs focused on teaching collaborative and communicative skills, including teacher preparation programs. Applied to these programs, social network analysis can provide information about instructional practices likely to facilitate student interaction and collaboration across diverse student populations. This exploratory study used NodeXL to visualize students’ participation in an online course, with the goal of identifying (1 ways in which NodeXL could be used to describe patterns in participant interaction within an instructional setting and (2 identifying specific patterns in participant interaction among students in this particular course. In this sample, general education teachers demonstrated higher measures of connection and interaction with other participants than did those from specialist (ESOL or special education backgrounds, and tended to interact more frequently with all participants than the majority of participants from specialist backgrounds. We recommend further research to delineate specific applications of NodeXL within an instructional context, particularly to identify potential patterns in student participation based on variables such as gender, background, cultural and linguistic heritage, prior training and education, and prior experience so that instructors can ensure their practice helps to facilitate student interaction

  10. TROVE: A User-friendly Tool for Visualizing and Analyzing Cancer Hallmarks in Signaling Networks.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Zheng, Jie

    2017-09-22

    Cancer hallmarks, a concept that seeks to explain the complexity of cancer initiation and development, provide a new perspective of studying cancer signaling which could lead to a greater understanding of this complex disease. However, to the best of our knowledge, there is currently a lack of tools that support such hallmark-based study of the cancer signaling network, thereby impeding the gain of knowledge in this area. We present TROVE, a user-friendly software that facilitates hallmark annotation, visualization and analysis in cancer signaling networks. In particular, TROVE facilitates hallmark analysis specific to particular cancer types. Available under the Eclipse Public License from: https://sites.google.com/site/cosbyntu/softwares/trove and https://github.com/trove2017/Trove. hechua@ntu.edu.sg or assourav@ntu.edu.sg. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  11. Close encounters: Analyzing how social similarity and propinquity contribute to strong network connections.

    OpenAIRE

    Reagans, Ray Eugene

    2010-01-01

    Models of network formation emphasize the importance of social similarity and propinquity in producing strong interpersonal connections. The positive effect each factor can have on tie strength has been documented across a number of studies, and yet we know surprisingly very little about how the two factors combine to produce strong ties. Being in close proximity could either amplify or dampen the positive effect that social similarity can have on tie strength. Data on tie strength among teac...

  12. ARTIFICIAL NEURAL-NETWORK PREDICTIONS OF URINARY CALCULUS COMPOSITIONS ANALYZED WITH INFRARED-SPECTROSCOPY

    NARCIS (Netherlands)

    VOLMER, M; WOLTHERS, BG; METTING, HJ; DEHAAN, THY; COENEGRACHT, PMJ; VANDERSLIK, W

    Infrared (IR) spectroscopy is used to analyze urinary calculus (renal stone) constituents. However, interpretation of IR spectra for quantifying urinary calculus constituents in mixtures is difficult, requiring expert knowledge by trained technicians. In our laboratory IR spectra of unknown calculi

  13. Anatomical Network Analysis Shows Decoupling of Modular Lability and Complexity in the Evolution of the Primate Skull

    Science.gov (United States)

    Esteve-Altava, Borja; Boughner, Julia C.; Diogo, Rui; Villmoare, Brian A.; Rasskin-Gutman, Diego

    2015-01-01

    Modularity and complexity go hand in hand in the evolution of the skull of primates. Because analyses of these two parameters often use different approaches, we do not know yet how modularity evolves within, or as a consequence of, an also-evolving complex organization. Here we use a novel network theory-based approach (Anatomical Network Analysis) to assess how the organization of skull bones constrains the co-evolution of modularity and complexity among primates. We used the pattern of bone contacts modeled as networks to identify connectivity modules and quantify morphological complexity. We analyzed whether modularity and complexity evolved coordinately in the skull of primates. Specifically, we tested Herbert Simon’s general theory of near-decomposability, which states that modularity promotes the evolution of complexity. We found that the skulls of extant primates divide into one conserved cranial module and up to three labile facial modules, whose composition varies among primates. Despite changes in modularity, statistical analyses reject a positive feedback between modularity and complexity. Our results suggest a decoupling of complexity and modularity that translates to varying levels of constraint on the morphological evolvability of the primate skull. This study has methodological and conceptual implications for grasping the constraints that underlie the developmental and functional integration of the skull of humans and other primates. PMID:25992690

  14. Analyzing the Impact of Storage Shortage on Data Availability in Decentralized Online Social Networks

    Directory of Open Access Journals (Sweden)

    Songling Fu

    2014-01-01

    Full Text Available Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs. The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today’s online social networks (OSNs due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction.

  15. The Unfolding MD Simulations of Cyclophilin: Analyzed by Surface Contact Networks and Their Associated Metrics

    Science.gov (United States)

    Roy, Sourav; Basu, Sankar; Dasgupta, Dipak; Bhattacharyya, Dhananjay; Banerjee, Rahul

    2015-01-01

    Currently, considerable interest exists with regard to the dissociation of close packed aminoacids within proteins, in the course of unfolding, which could result in either wet or dry moltenglobules. The progressive disjuncture of residues constituting the hydrophobic core ofcyclophilin from L. donovani (LdCyp) has been studied during the thermal unfolding of the molecule, by molecular dynamics simulations. LdCyp has been represented as a surface contactnetwork (SCN) based on the surface complementarity (Sm) of interacting residues within themolecular interior. The application of Sm to side chain packing within proteins make it a very sensitive indicator of subtle perturbations in packing, in the thermal unfolding of the protein. Network based metrics have been defined to track the sequential changes in the disintegration ofthe SCN spanning the hydrophobic core of LdCyp and these metrics prove to be highly sensitive compared to traditional metrics in indicating the increased conformational (and dynamical) flexibility in the network. These metrics have been applied to suggest criteria distinguishing DMG, WMG and transition state ensembles and to identify key residues involved in crucial conformational/topological events during the unfolding process. PMID:26545107

  16. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Science.gov (United States)

    Park, Chihyun; Ahn, Jaegyoon; Kim, Hyunjin; Park, Sanghyun

    2014-01-01

    The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  17. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Directory of Open Access Journals (Sweden)

    Chihyun Park

    Full Text Available BACKGROUND: The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. RESULTS: In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. CONCLUSIONS: The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  18. Analyzing the determinants of the UK consumer's engagement in Viral Marketing on Social Networking Sites : A university Student's perspective

    OpenAIRE

    Alkhateeb, Ali; Alli, Zahir; Moussa, Wissam

    2012-01-01

    Social media, especially the social networking sites (SNS) like Facebook.com, has experienced exponential growth all across the globe in the last decade. It is rapidly attracting the consumers and replacing the traditional media. Electronic word of mouth (eWOM) through social media has acquired substantial position in the marketing mix as well as integrated marketing communication of the business organizations. This research aimed at analyzing different social relationship factors or determin...

  19. Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

    Science.gov (United States)

    Kotegawa, Tatsuya

    Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high

  20. A UV-Induced Genetic Network Links the RSC Complex to Nucleotide Excision Repair and Shows Dose-Dependent Rewiring

    Directory of Open Access Journals (Sweden)

    Rohith Srivas

    2013-12-01

    Full Text Available Efficient repair of UV-induced DNA damage requires the precise coordination of nucleotide excision repair (NER with numerous other biological processes. To map this crosstalk, we generated a differential genetic interaction map centered on quantitative growth measurements of >45,000 double mutants before and after different doses of UV radiation. Integration of genetic data with physical interaction networks identified a global map of 89 UV-induced functional interactions among 62 protein complexes, including a number of links between the RSC complex and several NER factors. We show that RSC is recruited to both silenced and transcribed loci following UV damage where it facilitates efficient repair by promoting nucleosome remodeling. Finally, a comparison of the response to high versus low levels of UV shows that the degree of genetic rewiring correlates with dose of UV and reveals a network of dose-specific interactions. This study makes available a large resource of UV-induced interactions, and it illustrates a methodology for identifying dose-dependent interactions based on quantitative shifts in genetic networks.

  1. Software ecosystems analyzing and managing business networks in the software industry

    CERN Document Server

    Jansen, S; Cusumano, MA

    2013-01-01

    This book describes the state-of-the-art of software ecosystems. It constitutes a fundamental step towards an empirically based, nuanced understanding of the implications for management, governance, and control of software ecosystems. This is the first book of its kind dedicated to this emerging field and offers guidelines on how to analyze software ecosystems; methods for managing and growing; methods on transitioning from a closed software organization to an open one; and instruments for dealing with open source, licensing issues, product management and app stores. It is unique in bringing t

  2. Enzyme-Based Logic Gates and Networks with Output Signals Analyzed by Various Methods.

    Science.gov (United States)

    Katz, Evgeny

    2017-07-05

    The paper overviews various methods that are used for the analysis of output signals generated by enzyme-based logic systems. The considered methods include optical techniques (optical absorbance, fluorescence spectroscopy, surface plasmon resonance), electrochemical techniques (cyclic voltammetry, potentiometry, impedance spectroscopy, conductivity measurements, use of field effect transistor devices, pH measurements), and various mechanoelectronic methods (using atomic force microscope, quartz crystal microbalance). Although each of the methods is well known for various bioanalytical applications, their use in combination with the biomolecular logic systems is rather new and sometimes not trivial. Many of the discussed methods have been combined with the use of signal-responsive materials to transduce and amplify biomolecular signals generated by the logic operations. Interfacing of biocomputing logic systems with electronics and "smart" signal-responsive materials allows logic operations be extended to actuation functions; for example, stimulating molecular release and switchable features of bioelectronic devices, such as biofuel cells. The purpose of this review article is to emphasize the broad variability of the bioanalytical systems applied for signal transduction in biocomputing processes. All bioanalytical systems discussed in the article are exemplified with specific logic gates and multi-gate networks realized with enzyme-based biocatalytic cascades. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Time Analyzer for Time Synchronization and Monitor of the Deep Space Network

    Science.gov (United States)

    Cole, Steven; Gonzalez, Jorge, Jr.; Calhoun, Malcolm; Tjoelker, Robert

    2003-01-01

    A software package has been developed to measure, monitor, and archive the performance of timing signals distributed in the NASA Deep Space Network. Timing signals are generated from a central master clock and distributed to over 100 users at distances up to 30 kilometers. The time offset due to internal distribution delays and time jitter with respect to the central master clock are critical for successful spacecraft navigation, radio science, and very long baseline interferometry (VLBI) applications. The instrument controller and operator interface software is written in LabView and runs on the Linux operating system. The software controls a commercial multiplexer to switch 120 separate timing signals to measure offset and jitter with a time-interval counter referenced to the master clock. The offset of each channel is displayed in histogram form, and "out of specification" alarms are sent to a central complex monitor and control system. At any time, the measurement cycle of 120 signals can be interrupted for diagnostic tests on an individual channel. The instrument also routinely monitors and archives the long-term stability of all frequency standards or any other 1-pps source compared against the master clock. All data is stored and made available for

  4. Investigations on the sensitivity of a stepped-frequency radar utilizing a vector network analyzer for Ground Penetrating Radar

    Science.gov (United States)

    Seyfried, Daniel; Schubert, Karsten; Schoebel, Joerg

    2014-12-01

    Employing a continuous-wave radar system, with the stepped-frequency radar being one type of this class, all reflections from the environment are present continuously and simultaneously at the receiver. Utilizing such a radar system for Ground Penetrating Radar purposes, antenna cross-talk and ground bounce reflection form an overall dominant signal contribution while reflections from objects buried in the ground are of quite weak amplitude due to attenuation in the ground. This requires a large dynamic range of the receiver which in turn requires high sensitivity of the radar system. In this paper we analyze the sensitivity of our vector network analyzer utilized as stepped-frequency radar system for GPR pipe detection. We furthermore investigate the performance of increasing the sensitivity of the radar by means of appropriate averaging and low-noise pre-amplification of the received signal. It turns out that the improvement in sensitivity actually achievable may differ significantly from theoretical expectations. In addition, we give a descriptive explanation why our appropriate experiments demonstrate that the sensitivity of the receiver is independent of the distance between the target object and the source of dominant signal contribution. Finally, our investigations presented in this paper lead to a preferred setting of operation for our vector network analyzer in order to achieve best detection capability for weak reflection amplitudes, hence making the radar system applicable for Ground Penetrating Radar purposes.

  5. Analyzing Collaborative Governance Through Social Network Analysis: A Case Study of River Management Along the Waal River in The Netherlands.

    Science.gov (United States)

    Fliervoet, J M; Geerling, G W; Mostert, E; Smits, A J M

    2016-02-01

    Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.

  6. A simple method for analyzing exome sequencing data shows distinct levels of nonsynonymous variation for human immune and nervous system genes.

    Directory of Open Access Journals (Sweden)

    Jan Freudenberg

    Full Text Available To measure the strength of natural selection that acts upon single nucleotide variants (SNVs in a set of human genes, we calculate the ratio between nonsynonymous SNVs (nsSNVs per nonsynonymous site and synonymous SNVs (sSNVs per synonymous site. We transform this ratio with a respective factor f that corrects for the bias of synonymous sites towards transitions in the genetic code and different mutation rates for transitions and transversions. This method approximates the relative density of nsSNVs (rdnsv in comparison with the neutral expectation as inferred from the density of sSNVs. Using SNVs from a diploid genome and 200 exomes, we apply our method to immune system genes (ISGs, nervous system genes (NSGs, randomly sampled genes (RSGs, and gene ontology annotated genes. The estimate of rdnsv in an individual exome is around 20% for NSGs and 30-40% for ISGs and RSGs. This smaller rdnsv of NSGs indicates overall stronger purifying selection. To quantify the relative shift of nsSNVs towards rare variants, we next fit a linear regression model to the estimates of rdnsv over different SNV allele frequency bins. The obtained regression models show a negative slope for NSGs, ISGs and RSGs, supporting an influence of purifying selection on the frequency spectrum of segregating nsSNVs. The y-intercept of the model predicts rdnsv for an allele frequency close to 0. This parameter can be interpreted as the proportion of nonsynonymous sites where mutations are tolerated to segregate with an allele frequency notably greater than 0 in the population, given the performed normalization of the observed nsSNV to sSNV ratio. A smaller y-intercept is displayed by NSGs, indicating more nonsynonymous sites under strong negative selection. This predicts more monogenically inherited or de-novo mutation diseases that affect the nervous system.

  7. Measurement of Dielectric Properties at 75 - 325 GHz using a Vector Network Analyzer and Full Wave Simulator

    Directory of Open Access Journals (Sweden)

    S.Khanal

    2012-06-01

    Full Text Available This paper presents a fast and easy to use method to determine permittivity and loss tangent in the frequency range of 75 to 325 GHz. To obtain the permittivity and the loss tangent of the test material, the reflection and transmission S-parameters of a waveguide section filled with the test material are measured using a vector network analyzer and then compared with the simulated plots from a full wave simulator (HFSS, or alternatively the measurement results are used in mathematical formulas. The results are coherent over multiple waveguide bands.

  8. Multi-site cholera surveillance within the African Cholera Surveillance Network shows endemicity in Mozambique, 2011–2015

    Science.gov (United States)

    Langa, José Paulo; Dengo Baloi, Liliana; Wood, Richard; Ouedraogo, Issaka; Njanpop-Lafourcade, Berthe-Marie; Inguane, Dorteia; Elias Chitio, Jucunu; Mhlanga, Themba; Gujral, Lorna; D. Gessner, Bradford; Munier, Aline; A. Mengel, Martin

    2017-01-01

    Background Mozambique suffers recurrent annual cholera outbreaks especially during the rainy season between October to March. The African Cholera Surveillance Network (Africhol) was implemented in Mozambique in 2011 to generate accurate detailed surveillance data to support appropriate interventions for cholera control and prevention in the country. Methodology/Principal findings Africhol was implemented in enhanced surveillance zones located in the provinces of Sofala (Beira), Zambézia (District Mocuba), and Cabo Delgado (Pemba City). Data were also analyzed from the three outbreak areas that experienced the greatest number of cases during the time period under observation (in the districts of Cuamba, Montepuez, and Nampula). Rectal swabs were collected from suspected cases for identification of Vibrio cholerae, as well as clinical, behavioral, and socio-demographic variables. We analyzed factors associated with confirmed, hospitalized, and fatal cholera using multivariate logistic regression models. A total of 1,863 suspected cases and 23 deaths (case fatality ratio (CFR), 1.2%) were reported from October 2011 to December 2015. Among these suspected cases, 52.2% were tested of which 23.5% were positive for Vibrio cholerae O1 Ogawa. Risk factors independently associated with the occurrence of confirmed cholera were living in Nampula city district, the year 2014, human immunodeficiency virus infection, and the primary water source for drinking. Conclusions/Significance Cholera was endemic in Mozambique during the study period with a high CFR and identifiable risk factors. The study reinforces the importance of continued cholera surveillance, including a strong laboratory component. The results enhanced our understanding of the need to target priority areas and at-risk populations for interventions including oral cholera vaccine (OCV) use, and assess the impact of prevention and control strategies. Our data were instrumental in informing integrated prevention and

  9. Multi-site cholera surveillance within the African Cholera Surveillance Network shows endemicity in Mozambique, 2011-2015.

    Science.gov (United States)

    Semá Baltazar, Cynthia; Langa, José Paulo; Dengo Baloi, Liliana; Wood, Richard; Ouedraogo, Issaka; Njanpop-Lafourcade, Berthe-Marie; Inguane, Dorteia; Elias Chitio, Jucunu; Mhlanga, Themba; Gujral, Lorna; D Gessner, Bradford; Munier, Aline; A Mengel, Martin

    2017-10-01

    Mozambique suffers recurrent annual cholera outbreaks especially during the rainy season between October to March. The African Cholera Surveillance Network (Africhol) was implemented in Mozambique in 2011 to generate accurate detailed surveillance data to support appropriate interventions for cholera control and prevention in the country. Africhol was implemented in enhanced surveillance zones located in the provinces of Sofala (Beira), Zambézia (District Mocuba), and Cabo Delgado (Pemba City). Data were also analyzed from the three outbreak areas that experienced the greatest number of cases during the time period under observation (in the districts of Cuamba, Montepuez, and Nampula). Rectal swabs were collected from suspected cases for identification of Vibrio cholerae, as well as clinical, behavioral, and socio-demographic variables. We analyzed factors associated with confirmed, hospitalized, and fatal cholera using multivariate logistic regression models. A total of 1,863 suspected cases and 23 deaths (case fatality ratio (CFR), 1.2%) were reported from October 2011 to December 2015. Among these suspected cases, 52.2% were tested of which 23.5% were positive for Vibrio cholerae O1 Ogawa. Risk factors independently associated with the occurrence of confirmed cholera were living in Nampula city district, the year 2014, human immunodeficiency virus infection, and the primary water source for drinking. Cholera was endemic in Mozambique during the study period with a high CFR and identifiable risk factors. The study reinforces the importance of continued cholera surveillance, including a strong laboratory component. The results enhanced our understanding of the need to target priority areas and at-risk populations for interventions including oral cholera vaccine (OCV) use, and assess the impact of prevention and control strategies. Our data were instrumental in informing integrated prevention and control efforts during major cholera outbreaks in recent years.

  10. Comparison of Control Approaches in Genetic Regulatory Networks by Using Stochastic Master Equation Models, Probabilistic Boolean Network Models and Differential Equation Models and Estimated Error Analyzes

    Science.gov (United States)

    Caglar, Mehmet Umut; Pal, Ranadip

    2011-03-01

    Central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid''. However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of cell level data and probabilistic - nonlinear nature of interactions. Several models widely used to analyze and simulate these types of nonlinear interactions. Stochastic Master Equation (SME) models give probabilistic nature of the interactions in a detailed manner, with a high calculation cost. On the other hand Probabilistic Boolean Network (PBN) models give a coarse scale picture of the stochastic processes, with a less calculation cost. Differential Equation (DE) models give the time evolution of mean values of processes in a highly cost effective way. The understanding of the relations between the predictions of these models is important to understand the reliability of the simulations of genetic regulatory networks. In this work the success of the mapping between SME, PBN and DE models is analyzed and the accuracy and affectivity of the control policies generated by using PBN and DE models is compared.

  11. Use of Bayesian Networks to Analyze Port Variables in Order to Make Sustainable Planning and Management Decision

    Directory of Open Access Journals (Sweden)

    Beatriz Molina Serrano

    2018-01-01

    Full Text Available In the current economic, social and political environment, society demands a greater variety of outcomes from the public logistics sector, such as efficiency, efficiency of managed resources, greater transparency and business performance. All of them are an indispensable counterpart for its recognition and support. In case of port planning and management, many variables are included. Use of Bayesian Networks allows to classify, predict and diagnose these variables and even to estimate the subsequent probability of unknown variables, basing on the known ones. Research includes a data base with more than 40 variables, which have been classified as smart port studies in Spain. Then a network was generated using a non-cyclic conducted grafo, which shows port variable relationships. As conclusion, economic variables are cause of the rest of categories and they represent a parent role in the most of cases. Furthermore, if environmental variables are known, subsequent probability of social variables can be estimated.

  12. Plasmid Flux in Escherichia coli ST131 Sublineages, Analyzed by Plasmid Constellation Network (PLACNET), a New Method for Plasmid Reconstruction from Whole Genome Sequences

    Science.gov (United States)

    Garcillán-Barcia, M. Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M.; de la Cruz, Fernando

    2014-01-01

    Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ–proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages. PMID:25522143

  13. Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences.

    Science.gov (United States)

    Lanza, Val F; de Toro, María; Garcillán-Barcia, M Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M; de la Cruz, Fernando

    2014-12-01

    Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

  14. Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET, a new method for plasmid reconstruction from whole genome sequences.

    Directory of Open Access Journals (Sweden)

    Val F Lanza

    2014-12-01

    Full Text Available Bacterial whole genome sequence (WGS methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage, comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC, comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

  15. GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

    Science.gov (United States)

    Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

    2012-01-01

    In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

  16. GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

    Directory of Open Access Journals (Sweden)

    S M Hadi Hosseini

    Full Text Available In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC and functional data analyses (FDA, in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL and healthy matched Controls (CON. The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

  17. Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network.

    Directory of Open Access Journals (Sweden)

    Seung Seog Han

    Full Text Available Although there have been reports of the successful diagnosis of skin disorders using deep learning, unrealistically large clinical image datasets are required for artificial intelligence (AI training. We created datasets of standardized nail images using a region-based convolutional neural network (R-CNN trained to distinguish the nail from the background. We used R-CNN to generate training datasets of 49,567 images, which we then used to fine-tune the ResNet-152 and VGG-19 models. The validation datasets comprised 100 and 194 images from Inje University (B1 and B2 datasets, respectively, 125 images from Hallym University (C dataset, and 939 images from Seoul National University (D dataset. The AI (ensemble model; ResNet-152 + VGG-19 + feedforward neural networks results showed test sensitivity/specificity/ area under the curve values of (96.0 / 94.7 / 0.98, (82.7 / 96.7 / 0.95, (92.3 / 79.3 / 0.93, (87.7 / 69.3 / 0.82 for the B1, B2, C, and D datasets. With a combination of the B1 and C datasets, the AI Youden index was significantly (p = 0.01 higher than that of 42 dermatologists doing the same assessment manually. For B1+C and B2+ D dataset combinations, almost none of the dermatologists performed as well as the AI. By training with a dataset comprising 49,567 images, we achieved a diagnostic accuracy for onychomycosis using deep learning that was superior to that of most of the dermatologists who participated in this study.

  18. Deep neural networks show an equivalent and often superior performance to dermatologists in onychomycosis diagnosis: Automatic construction of onychomycosis datasets by region-based convolutional deep neural network.

    Science.gov (United States)

    Han, Seung Seog; Park, Gyeong Hun; Lim, Woohyung; Kim, Myoung Shin; Na, Jung Im; Park, Ilwoo; Chang, Sung Eun

    2018-01-01

    Although there have been reports of the successful diagnosis of skin disorders using deep learning, unrealistically large clinical image datasets are required for artificial intelligence (AI) training. We created datasets of standardized nail images using a region-based convolutional neural network (R-CNN) trained to distinguish the nail from the background. We used R-CNN to generate training datasets of 49,567 images, which we then used to fine-tune the ResNet-152 and VGG-19 models. The validation datasets comprised 100 and 194 images from Inje University (B1 and B2 datasets, respectively), 125 images from Hallym University (C dataset), and 939 images from Seoul National University (D dataset). The AI (ensemble model; ResNet-152 + VGG-19 + feedforward neural networks) results showed test sensitivity/specificity/ area under the curve values of (96.0 / 94.7 / 0.98), (82.7 / 96.7 / 0.95), (92.3 / 79.3 / 0.93), (87.7 / 69.3 / 0.82) for the B1, B2, C, and D datasets. With a combination of the B1 and C datasets, the AI Youden index was significantly (p = 0.01) higher than that of 42 dermatologists doing the same assessment manually. For B1+C and B2+ D dataset combinations, almost none of the dermatologists performed as well as the AI. By training with a dataset comprising 49,567 images, we achieved a diagnostic accuracy for onychomycosis using deep learning that was superior to that of most of the dermatologists who participated in this study.

  19. Analyzing subsurface drain network performance in an agricultural monitoring site with a three-dimensional hydrological model

    Science.gov (United States)

    Nousiainen, Riikka; Warsta, Lassi; Turunen, Mika; Huitu, Hanna; Koivusalo, Harri; Pesonen, Liisa

    2015-10-01

    Effectiveness of a subsurface drainage system decreases with time, leading to a need to restore the drainage efficiency by installing new drain pipes in problem areas. The drainage performance of the resulting system varies spatially and complicates runoff and nutrient load generation within the fields. We presented a method to estimate the drainage performance of a heterogeneous subsurface drainage system by simulating the area with the three-dimensional hydrological FLUSH model. A GIS analysis was used to delineate the surface runoff contributing area in the field. We applied the method to reproduce the water balance and to investigate the effectiveness of a subsurface drainage network of a clayey field located in southern Finland. The subsurface drainage system was originally installed in the area in 1971 and the drainage efficiency was improved in 1995 and 2005 by installing new drains. FLUSH was calibrated against total runoff and drain discharge data from 2010 to 2011 and validated against total runoff in 2012. The model supported quantification of runoff fractions via the three installed drainage networks. Model realisations were produced to investigate the extent of the runoff contributing areas and the effect of the drainage parameters on subsurface drain discharge. The analysis showed that better model performance was achieved when the efficiency of the oldest drainage network (installed in 1971) was decreased. Our analysis method can reveal the drainage system performance but not the reason for the deterioration of the drainage performance. Tillage layer runoff from the field was originally computed by subtracting drain discharge from the total runoff. The drains installed in 1995 bypass the measurement system, which renders the tillage layer runoff calculation procedure invalid after 1995. Therefore, this article suggests use of a local correction coefficient based on the simulations for further research utilizing data from the study area.

  20. Based on records of Three Gorge Telemetric Seismic Network to analyze Vibration process of micro fracture of rock landslide

    Science.gov (United States)

    WANG, Q.

    2017-12-01

    Used the finite element analysis software GeoStudio to establish vibration analysis model of Qianjiangping landslide, which locates at the Three Gorges Reservoir area. In QUAKE/W module, we chosen proper Dynamic elasticity modulus and Poisson's ratio of soil layer and rock stratum. When loading, we selected the waveform data record of Three Gorge Telemetric Seismic Network as input ground motion, which includes five rupture events recorded of Lujiashan seismic station. In dynamic simulating, we mainly focused on sliding process when the earthquake date record was applied. The simulation result shows that Qianjiangping landslide wasn't not only affected by its own static force, but also experienced the dynamic process of micro fracture-creep-slip rupture-creep-slip.it provides a new approach for the early warning feasibility of rock landslide in future research.

  1. A General Bayesian Network Approach to Analyzing Online Game Item Values and Its Influence on Consumer Satisfaction and Purchase Intention

    Science.gov (United States)

    Lee, Kun Chang; Park, Bong-Won

    Many online game users purchase game items with which to play free-to-play games. Because of a lack of research into which there is no specified framework for categorizing the values of game items, this study proposes four types of online game item values based on an analysis of literature regarding online game characteristics. It then proposes to investigate how online game users perceive satisfaction and purchase intention from the proposed four types of online game item values. Though regression analysis has been used frequently to answer this kind of research question, we propose a new approach, a General Bayesian Network (GBN), which can be performed in an understandable way without sacrificing predictive accuracy. Conventional techniques, such as regression analysis, do not provide significant explanation for this kind of problem because they are fixed to a linear structure and are limited in explaining why customers are likely to purchase game items and if they are satisfied with their purchases. In contrast, the proposed GBN provides a flexible underlying structure based on questionnaire survey data and offers robust decision support on this kind of research question by identifying its causal relationships. To illustrate the validity of GBN in solving the research question in this study, 327 valid questionnaires were analyzed using GBN with what-if and goal-seeking approaches. The experimental results were promising and meaningful in comparison with regression analysis results.

  2. A network model shows the importance of coupled processes in the microbial N cycle in the Cape Fear River Estuary

    Science.gov (United States)

    Hines, David E.; Lisa, Jessica A.; Song, Bongkeun; Tobias, Craig R.; Borrett, Stuart R.

    2012-06-01

    Estuaries serve important ecological and economic functions including habitat provision and the removal of nutrients. Eutrophication can overwhelm the nutrient removal capacity of estuaries and poses a widely recognized threat to the health and function of these ecosystems. Denitrification and anaerobic ammonium oxidation (anammox) are microbial processes responsible for the removal of fixed nitrogen and diminish the effects of eutrophication. Both of these microbial removal processes can be influenced by direct inputs of dissolved inorganic nitrogen substrates or supported by microbial interactions with other nitrogen transforming pathways such as nitrification and dissimilatory nitrate reduction to ammonium (DNRA). The coupling of nitrogen removal pathways to other transformation pathways facilitates the removal of some forms of inorganic nitrogen; however, differentiating between direct and coupled nitrogen removal is difficult. Network modeling provides a tool to examine interactions among microbial nitrogen cycling processes and to determine the within-system history of nitrogen involved in denitrification and anammox. To examine the coupling of nitrogen cycling processes, we built a nitrogen budget mass balance network model in two adjacent 1 cm3 sections of bottom water and sediment in the oligohaline portion of the Cape Fear River Estuary, NC, USA. Pathway, flow, and environ ecological network analyses were conducted to characterize the organization of nitrogen flow in the estuary and to estimate the coupling of nitrification to denitrification and of nitrification and DNRA to anammox. Centrality analysis indicated NH4+ is the most important form of nitrogen involved in removal processes. The model analysis further suggested that direct denitrification and coupled nitrification-denitrification had similar contributions to nitrogen removal while direct anammox was dominant to coupled forms of anammox. Finally, results also indicated that partial

  3. Using Modeling and Simulation to Analyze Application and Network Performance at the Radioactive Waste and Nuclear Material Disposition Facility

    International Nuclear Information System (INIS)

    LIFE, ROY A.; MAESTAS, JOSEPH H.; BATEMAN, DENNIS B.

    2003-01-01

    Telecommunication services customers at the Radioactive Waste and Nuclear Material Disposition Facility (RWNMDF) have endured regular service outages that seem to be associated with a custom Microsoft Access Database. In addition, the same customers have noticed periods when application response times are noticeably worse than at others. To the customers, the two events appear to be correlated. Although many network design activities can be accomplished using trial-and-error methods, there are as many, if not more occasions where computerized analysis is necessary to verify the benefits of implementing one design alternative versus another. This is particularly true when network design is performed with application flows and response times in mind. More times than not, it is unclear whether upgrading certain aspects of the network will provide sufficient benefit to justify the corresponding costs, and network modeling tools can be used to help staff make these decisions. This report summarizes our analysis of the situation at the RWNMDF, in which computerized analysis was used to accomplish four objectives: (1) identify the source of the problem; (2) identify areas where improvements make the most sense; (3) evaluate various scenarios ranging from upgrading the network infrastructure, installing an additional fiber trunk as a way to improve local network performance, and re-locating the RWNMDF database onto corporate servers; and (4) demonstrate a methodology for network design using actual application response times to predict, select, and implement the design alternatives that provide the best performance and cost benefits

  4. Analyzing the impact of global financial crisis on the interconnectedness of Asian stock markets using network science

    OpenAIRE

    Jitendra Aswani

    2015-01-01

    As importance of Asian Stock Markets (ASM) has increased after the globalization, it is become significant to know how this network of ASM behaves on the onset of financial crises. For this study, the Global Financial Crisis is considered whose origin was in the developed country, US, unlike the Asian crisis of 1997. To evaluate the impact of financial crisis on the ASM, network theory is used as a tool here. Network modeling of stock markets is useful as it can help to avert the spillover of...

  5. Magnetostatics and dynamics of ion irradiatied NiFe/Ta multilayer films studied by vector network analyzer ferromagnetic resonance

    International Nuclear Information System (INIS)

    Marko, Daniel

    2010-01-01

    In the present work, the implications of ion irradiation on the magnetostatic and dynamic properties of soft magnetic Py/Ta (Py=Permalloy: Ni 80 Fe 20 ) single and multilayer films have been investigated with the main objective of finding a way to determine their saturation magnetization. Both polar magneto-optical Kerr effect (MOKE) and vector network analyzer ferromagnetic resonance (VNA-FMR) measurements have proven to be suitable methods to determine μ 0 M S , circumventing the problem of the unknown effective magnetic volume that causes conventional techniques such as SQUID or VSM to fail. Provided there is no perpendicular anisotropy contribution in the samples, the saturation magnetization can be determined even in the case of strong interfacial mixing due to an inherently high number of Py/Ta interfaces and/or ion irradiation with high fluences. Another integral part of this work has been to construct a VNA-FMR spectrometer capable of performing both azimuthal and polar angle-dependent measurements using a magnet strong enough to saturate samples containing iron. Starting from scratch, this comprised numerous steps such as developing a suitable coplanar waveguide design, and writing the control, evaluation, and fitting software. With both increasing ion fluence and number of Py/Ta interfaces, a decrease of saturation magnetization has been observed. In the case of the 10 x Py samples, an immediate decrease of μ 0 M S already sets in at small ion fluences. However, for the 1 x Py and 5 x Py samples, the saturation magnetization remains constant up to a certain ion fluence, but then starts to rapidly decrease. Ne ion irradiation causes a mixing and broadening of the interfaces. Thus, the Py/Ta stacks undergo a transition from being polycrystalline to amorphous at a critical fluence depending on the number of interfaces. The saturation magnetization is found to vanish at a Ta concentration of about 10-15 at.% in the Py layers. The samples possess a small

  6. Letting the managers manage: analyzing capacity to conserve biodiversity in a cross-border protected area network

    Directory of Open Access Journals (Sweden)

    Sarah Clement

    2016-09-01

    Full Text Available Biodiversity loss is one of the most significant drivers of ecosystem change and is projected to continue at a rapid rate. While protected areas, such as national parks, are seen as important refuges for biodiversity, their effectiveness in stemming biodiversity decline has been questioned. Public agencies have a critical role in the governance of many such areas, but there are tensions between the need for these agencies to be more "adaptive" and their current operating environment. Our aim is to analyze how institutions enable or constrain capacity to conserve biodiversity in a globally significant cross-border network of protected areas, the Australian Alps. Using a novel conceptual framework for diagnosing biodiversity institutions, our research examined institutional adaptive capacity and more general capacity for conserving biodiversity. Several intertwined issues limit public agencies' capacity to fulfill their conservation responsibilities. Narrowly defined accountability measures constrain adaptive capacity and divert attention away from addressing key biodiversity outcomes. Implications for learning were also evident, with protected area agencies demonstrating successful learning for on-ground issues but less success in applying this learning to deeper policy change. Poor capacity to buffer political and community influences in managing significant cross-border drivers of biodiversity decline signals poor fit with the institutional context and has implications for functional fit. While cooperative federalism provides potential benefits for buffering through diversity, it also means protected area agencies have restricted authority to address cross-border threats. Restrictions on staff authority and discretion, as public servants, have further implications for deploying capacity. This analysis, particularly the possibility of fostering "ambidexterity" - creatively responding to political pressures in a way that also achieves a desirable

  7. Magnetostatics and dynamics of ion irradiatied NiFe/Ta multilayer films studied by vector network analyzer ferromagnetic resonance

    Energy Technology Data Exchange (ETDEWEB)

    Marko, Daniel

    2010-11-25

    In the present work, the implications of ion irradiation on the magnetostatic and dynamic properties of soft magnetic Py/Ta (Py=Permalloy: Ni{sub 80}Fe{sub 20}) single and multilayer films have been investigated with the main objective of finding a way to determine their saturation magnetization. Both polar magneto-optical Kerr effect (MOKE) and vector network analyzer ferromagnetic resonance (VNA-FMR) measurements have proven to be suitable methods to determine {mu}{sub 0}M{sub S}, circumventing the problem of the unknown effective magnetic volume that causes conventional techniques such as SQUID or VSM to fail. Provided there is no perpendicular anisotropy contribution in the samples, the saturation magnetization can be determined even in the case of strong interfacial mixing due to an inherently high number of Py/Ta interfaces and/or ion irradiation with high fluences. Another integral part of this work has been to construct a VNA-FMR spectrometer capable of performing both azimuthal and polar angle-dependent measurements using a magnet strong enough to saturate samples containing iron. Starting from scratch, this comprised numerous steps such as developing a suitable coplanar waveguide design, and writing the control, evaluation, and fitting software. With both increasing ion fluence and number of Py/Ta interfaces, a decrease of saturation magnetization has been observed. In the case of the 10 x Py samples, an immediate decrease of {mu}{sub 0}M{sub S} already sets in at small ion fluences. However, for the 1 x Py and 5 x Py samples, the saturation magnetization remains constant up to a certain ion fluence, but then starts to rapidly decrease. Ne ion irradiation causes a mixing and broadening of the interfaces. Thus, the Py/Ta stacks undergo a transition from being polycrystalline to amorphous at a critical fluence depending on the number of interfaces. The saturation magnetization is found to vanish at a Ta concentration of about 10-15 at.% in the Py layers

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

    Directory of Open Access Journals (Sweden)

    V. Murale

    2014-03-01

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

  9. Using Exponential Random Graph Models to Analyze the Character of Peer Relationship Networks and Their Effects on the Subjective Well-being of Adolescents.

    Science.gov (United States)

    Jiao, Can; Wang, Ting; Liu, Jianxin; Wu, Huanjie; Cui, Fang; Peng, Xiaozhe

    2017-01-01

    The influences of peer relationships on adolescent subjective well-being were investigated within the framework of social network analysis, using exponential random graph models as a methodological tool. The participants in the study were 1,279 students (678 boys and 601 girls) from nine junior middle schools in Shenzhen, China. The initial stage of the research used a peer nomination questionnaire and a subjective well-being scale (used in previous studies) to collect data on the peer relationship networks and the subjective well-being of the students. Exponential random graph models were then used to explore the relationships between students with the aim of clarifying the character of the peer relationship networks and the influence of peer relationships on subjective well being. The results showed that all the adolescent peer relationship networks in our investigation had positive reciprocal effects, positive transitivity effects and negative expansiveness effects. However, none of the relationship networks had obvious receiver effects or leaders. The adolescents in partial peer relationship networks presented similar levels of subjective well-being on three dimensions (satisfaction with life, positive affects and negative affects) though not all network friends presented these similarities. The study shows that peer networks can affect an individual's subjective well-being. However, whether similarities among adolescents are the result of social influences or social choices needs further exploration, including longitudinal studies that investigate the potential processes of subjective well-being similarities among adolescents.

  10. Development of new process network for gas chromatograph and analyzers connected with SCADA system and Digital Control Computers at Cernavoda NPP Unit 1

    International Nuclear Information System (INIS)

    Deneanu, Cornel; Popa Nemoiu, Dragos; Nica, Dana; Bucur, Cosmin

    2007-01-01

    The continuous monitoring of gas mixture concentrations (deuterium/ hydrogen/oxygen/nitrogen) accumulated in 'Moderator Cover Gas', 'Liquid Control Zone' and 'Heat Transport D 2 O Storage Tank Cover Gas', as well as the continuous monitoring of Heavy Water into Light Water concentration in 'Boilers Steam', 'Boilers Blown Down', 'Moderator heat exchangers', and 'Recirculated Water System', sensing any leaks of Cernavoda NPP U1 led to requirement of developing a new process network for gas chromatograph and analyzers connected to the SCADA system and Digital Control Computers of Cernavoda NPP Unit 1. In 2005 it was designed and implemented the process network for gas chromatograph which connected the gas chromatograph equipment to the SCADA system and Digital Control Computers of the Cernavoda NPP Unit 1. Later this process network for gas chromatograph has been extended to connect the AE13 and AE14 Fourier Transform Infrared (FTIR) analyzers with either. The Gas Chromatograph equipment measures with best accuracy the mixture gases (deuterium/ hydrogen/oxygen/nitrogen) concentration. The Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers measure the Heavy Water into Light Water concentration in Boilers Steam, Boilers BlownDown, Moderator heat exchangers, and Recirculated Water System, monitoring and signaling any leaks. The Gas Chromatograph equipment and Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers use the new OPC (Object Link Embedded for Process Control) technologies available in ABB's VistaNet network for interoperability with automation equipment. This new process network has interconnected the ABB chromatograph and Fourier Transform Infrared analyzers with plant Digital Control Computers using new technology. The result was an increased reliability and capability for inspection and improved system safety

  11. Fracture network evaluation program (FraNEP): A software for analyzing 2D fracture trace-line maps

    Science.gov (United States)

    Zeeb, Conny; Gomez-Rivas, Enrique; Bons, Paul D.; Virgo, Simon; Blum, Philipp

    2013-10-01

    Fractures, such as joints, faults and veins, strongly influence the transport of fluids through rocks by either enhancing or inhibiting flow. Techniques used for the automatic detection of lineaments from satellite images and aerial photographs, LIDAR technologies and borehole televiewers significantly enhanced data acquisition. The analysis of such data is often performed manually or with different analysis software. Here we present a novel program for the analysis of 2D fracture networks called FraNEP (Fracture Network Evaluation Program). The program was developed using Visual Basic for Applications in Microsoft Excel™ and combines features from different existing software and characterization techniques. The main novelty of FraNEP is the possibility to analyse trace-line maps of fracture networks applying the (1) scanline sampling, (2) window sampling or (3) circular scanline and window method, without the need of switching programs. Additionally, binning problems are avoided by using cumulative distributions, rather than probability density functions. FraNEP is a time-efficient tool for the characterisation of fracture network parameters, such as density, intensity and mean length. Furthermore, fracture strikes can be visualized using rose diagrams and a fitting routine evaluates the distribution of fracture lengths. As an example of its application, we use FraNEP to analyse a case study of lineament data from a satellite image of the Oman Mountains.

  12. Engagement and Knowledge Building in an Afterschool STEM Club: Analyzing Youth and Facilitator Posting Behavior on a Social Networking Site

    Science.gov (United States)

    Won, Samantha G. L.; Evans, Michael A.; Huang, Lixiao

    2017-01-01

    Social networking sites (SNSs) are popular technologies used frequently among youth for recreational purposes. Increasing attention has been paid to the use of SNSs in educational settings as a way to engage youth interest and encourage academically productive discussion. Potential affordances of using SNSs for education include knowledge…

  13. Who do you know? Developing and Analyzing Entrepreneur Networks: An Analysis of the Tech Entrepreneurial Environment of Six African Cities

    Science.gov (United States)

    2015-01-01

    2013, 2014, 2015) Greve, A. and Salaff, J. W. (2003), Social Networks and Entrepreneurship . Entrepreneurship Theory and Practice , 28: 1–22. doi...Social Capital: A Theory of Structure and Action. Cambridge University Press, New York 2001. Liu, Y., Slotine, J., and Barabasi, A. (2011...success of start-ups. Entrepreneurship and Regional Development. 16:391–412.

  14. Who do you know? Developing and Analyzing Entrepreneur Networks: An Analysis of the Entrepreneurial Environment of Kampala, Uganda

    Science.gov (United States)

    2013-11-04

    and Samsung . Outbox markets itself not just as an incubator, but also as a place for the tech community to meet with potential mentors and access...different membership focus. Their members are 4 | P a g e Network Science Center, West Point www.netscience.usma.edu 845.938.0804 more diverse . There...Internet connection, lounge area, and conference room. The businesses under incubation at Mara LaunchPad are more diverse than those at the other

  15. Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction.

    Science.gov (United States)

    Reyes-Gibby, Cielito C; Yuan, Christine; Wang, Jian; Yeung, Sai-Ching J; Shete, Sanjay

    2015-06-05

    Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

  16. Analyzing Brain Functions by Subject Classification of Functional Near-Infrared Spectroscopy Data Using Convolutional Neural Networks Analysis

    Directory of Open Access Journals (Sweden)

    Satoru Hiwa

    2016-01-01

    Full Text Available Functional near-infrared spectroscopy (fNIRS is suitable for noninvasive mapping of relative changes in regional cortical activity but is limited for quantitative comparisons among cortical sites, subjects, and populations. We have developed a convolutional neural network (CNN analysis method that learns feature vectors for accurate identification of group differences in fNIRS responses. In this study, subject gender was classified using CNN analysis of fNIRS data. fNIRS data were acquired from male and female subjects during a visual number memory task performed in a white noise environment because previous studies had revealed that the pattern of cortical blood flow during the task differed between males and females. A learned classifier accurately distinguished males from females based on distinct fNIRS signals from regions of interest (ROI including the inferior frontal gyrus and premotor areas that were identified by the learning algorithm. These cortical regions are associated with memory storage, attention, and task motor response. The accuracy of the classifier suggests stable gender-based differences in cerebral blood flow during this task. The proposed CNN analysis method can objectively identify ROIs using fNIRS time series data for machine learning to distinguish features between groups.

  17. Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.

    Science.gov (United States)

    Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars

    2018-01-01

    Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.

  18. Methods for Analyzing Pipe Networks

    DEFF Research Database (Denmark)

    Nielsen, Hans Bruun

    1989-01-01

    to formulate the flow equations in terms of pipe discharges than in terms of energy heads. The behavior of some iterative methods is compared in the initial phase with large errors. It is explained why the linear theory method oscillates when the iteration gets close to the solution, and it is further...... demonstrated that this method offers good starting values for a Newton-Raphson iteration....

  19. Analyzing Peace Pedagogies

    Science.gov (United States)

    Haavelsrud, Magnus; Stenberg, Oddbjorn

    2012-01-01

    Eleven articles on peace education published in the first volume of the Journal of Peace Education are analyzed. This selection comprises peace education programs that have been planned or carried out in different contexts. In analyzing peace pedagogies as proposed in the 11 contributions, we have chosen network analysis as our method--enabling…

  20. Retinal Capillary Network and Foveal Avascular Zone in Eyes with Vein Occlusion and Fellow Eyes Analyzed With Optical Coherence Tomography Angiography.

    Science.gov (United States)

    Adhi, Mehreen; Filho, Marco A Bonini; Louzada, Ricardo N; Kuehlewein, Laura; de Carlo, Talisa E; Baumal, Caroline R; Witkin, Andre J; Sadda, Srinivas R; Sarraf, David; Reichel, Elias; Duker, Jay S; Waheed, Nadia K

    2016-07-01

    To evaluate the perifoveolar retinal capillary network at different depths and to quantify the foveal avascular zone (FAZ) in eyes with retinal vein occlusion (RVO) compared with their fellow eyes and healthy controls using spectral-domain optical coherence tomography angiography (SD-OCTA). We prospectively recruited 23 patients with RVO including 15 eyes with central RVO (CRVO) and 8 eyes with branch RVO (BRVO), their fellow eyes, and 8 age-matched healthy controls (8 eyes) for imaging on prototype OCTA software within RTVue-XR Avanti. The 3 × 3 mm and 6 × 6 mm en face angiograms of superficial and deep retinal capillary plexuses were segmented. Perifoveolar retinal capillary network was analyzed and FAZ was quantified. Decrease in vascular perfusion at the deep plexus was observed in all eyes with CRVO (8/8, 100%) and BRVO (6/6, 100%) without cystoid macular edema, and in 8 of 15 (53%) and 2 of 8 (25%) of the fellow eyes, respectively. Vascular tortuosity was observed in 13 of 15 (87%) CRVO and 5 of 8 (63%) BRVO eyes. Collaterals were seen in 10 of 15 (67%) CRVO and 5 of 8 (63%) BRVO eyes. Mean FAZ area was larger in eyes with RVO than their fellow eyes (1.13 ± 0.25 mm2 versus 0.58 ± 0.28 mm2; P = 0.007) and controls (1.13 ± 0.25 mm2 versus 0.30 ± 0.09 mm2; P network and is able to quantify the FAZ in RVO. Longitudinal studies may be considered to evaluate the clinical utility of OCTA in RVO and other retinal vascular diseases.

  1. Transient analyzer

    International Nuclear Information System (INIS)

    Muir, M.D.

    1975-01-01

    The design and design philosophy of a high performance, extremely versatile transient analyzer is described. This sub-system was designed to be controlled through the data acquisition computer system which allows hands off operation. Thus it may be placed on the experiment side of the high voltage safety break between the experimental device and the control room. This analyzer provides control features which are extremely useful for data acquisition from PPPL diagnostics. These include dynamic sample rate changing, which may be intermixed with multiple post trigger operations with variable length blocks using normal, peak to peak or integrate modes. Included in the discussion are general remarks on the advantages of adding intelligence to transient analyzers, a detailed description of the characteristics of the PPPL transient analyzer, a description of the hardware, firmware, control language and operation of the PPPL transient analyzer, and general remarks on future trends in this type of instrumentation both at PPPL and in general

  2. A comparative study of artificial neural network and multivariate regression analysis to analyze optimum renal stone fragmentation by extracorporeal shock wave lithotripsy

    Directory of Open Access Journals (Sweden)

    Goyal Neeraj

    2010-01-01

    Full Text Available To compare the accuracy of artificial neural network (ANN analysis and multi-variate regression analysis (MVRA for renal stone fragmentation by extracorporeal shock wave lithotripsy (ESWL. A total of 276 patients with renal calculus were treated by ESWL during December 2001 to December 2006. Of them, the data of 196 patients were used for training the ANN. The predictability of trained ANN was tested on 80 subsequent patients. The input data include age of patient, stone size, stone burden, number of sittings and urinary pH. The output values (predicted values were number of shocks and shock power. Of these 80 patients, the input was analyzed and output was also calculated by MVRA. The output values (predicted values from both the methods were compared and the results were drawn. The predicted and observed values of shock power and number of shocks were compared using 1:1 slope line. The results were calculated as coefficient of correlation (COC (r2 . For prediction of power, the MVRA COC was 0.0195 and ANN COC was 0.8343. For prediction of number of shocks, the MVRA COC was 0.5726 and ANN COC was 0.9329. In conclusion, ANN gives better COC than MVRA, hence could be a better tool to analyze the optimum renal stone fragmentation by ESWL.

  3. A comparative study of artificial neural network and multivariate regression analysis to analyze optimum renal stone fragmentation by extracorporeal shock wave lithotripsy

    International Nuclear Information System (INIS)

    Neeraj K Goyal, Abhay Kumar; Sameer Trivedi

    2010-01-01

    To compare the accuracy of artificial neural network (ANN) analysis and multivariate regression analysis (MVRA) for renal stone fragmentation by extracorporeal shock wave lithotripsy (ESWL). A total of 276 patients with renal calculus were treated by ESWL during December 2001 to December 2006. Of them, the data of 196 patients were used for training the ANN. The predictability of trained ANN was tested on 80 subsequent patients. The input data include age of patient, stone size, stone burden, number of sittings and urinary pH. The output values (predicted values) were number of shocks and shock power. Of these 80 patients, the input was analyzed and output was also calculated by MVRA. The output values (predicted values) from both the methods were compared and the results were drawn. The predicted and observed values of shock power and number of shocks were compared using 1:1 slope line. The results were calculated as coefficient of correlation (COC) (r2 ). For prediction of power, the MVRA COC was 0.0195 and ANN COC was 0.8343. For prediction of number of shocks, the MVRA COC was 0.5726 and ANN COC was 0.9329. In conclusion, ANN gives better COC than MVRA, hence could be a better tool to analyze the optimum renal stone fragmentation by ESWL (Author).

  4. Radiometric analyzer

    International Nuclear Information System (INIS)

    Arima, S.; Oda, M.; Miyashita, K.; Takada, M.

    1977-01-01

    A radiometric analyzer for measuring the characteristic values of a sample by radiation includes a humer of radiation measuring subsystems having different ratios of sensitivities to the elements of the sample and linearizing circuits having inverse function characteristics of calibration functions which correspond to the radiation measuring subsystems. A weighing adder operates a desirable linear combination of the outputs of the linearizing circuits. Operators for operating between two or more different linear combinations are included

  5. A method for analyzing the business case for provider participation in the National Cancer Institute's Community Clinical Oncology Program and similar federally funded, provider-based research networks.

    Science.gov (United States)

    Reiter, Kristin L; Song, Paula H; Minasian, Lori; Good, Marjorie; Weiner, Bryan J; McAlearney, Ann Scheck

    2012-09-01

    The Community Clinical Oncology Program (CCOP) plays an essential role in the efforts of the National Cancer Institute (NCI) to increase enrollment in clinical trials. Currently, there is little practical guidance in the literature to assist provider organizations in analyzing the return on investment (ROI), or business case, for establishing and operating a provider-based research network (PBRN) such as the CCOP. In this article, the authors present a conceptual model of the business case for PBRN participation, a spreadsheet-based tool and advice for evaluating the business case for provider participation in a CCOP organization. A comparative, case-study approach was used to identify key components of the business case for hospitals attempting to support a CCOP research infrastructure. Semistructured interviews were conducted with providers and administrators. Key themes were identified and used to develop the financial analysis tool. Key components of the business case included CCOP start-up costs, direct revenue from the NCI CCOP grant, direct expenses required to maintain the CCOP research infrastructure, and incidental benefits, most notably downstream revenues from CCOP patients. The authors recognized the value of incidental benefits as an important contributor to the business case for CCOP participation; however, currently, this component is not calculated. The current results indicated that providing a method for documenting the business case for CCOP or other PBRN involvement will contribute to the long-term sustainability and expansion of these programs by improving providers' understanding of the financial implications of participation. Copyright © 2011 American Cancer Society.

  6. Contamination Analyzer

    Science.gov (United States)

    1994-01-01

    Measurement of the total organic carbon content in water is important in assessing contamination levels in high purity water for power generation, pharmaceutical production and electronics manufacture. Even trace levels of organic compounds can cause defects in manufactured products. The Sievers Model 800 Total Organic Carbon (TOC) Analyzer, based on technology developed for the Space Station, uses a strong chemical oxidizing agent and ultraviolet light to convert organic compounds in water to carbon dioxide. After ionizing the carbon dioxide, the amount of ions is determined by measuring the conductivity of the deionized water. The new technique is highly sensitive, does not require compressed gas, and maintenance is minimal.

  7. Metal and physico-chemical variations at a hydroelectric reservoir analyzed by Multivariate Analyses and Artificial Neural Networks: environmental management and policy/decision-making tools.

    Science.gov (United States)

    Cavalcante, Y L; Hauser-Davis, R A; Saraiva, A C F; Brandão, I L S; Oliveira, T F; Silveira, A M

    2013-01-01

    This paper compared and evaluated seasonal variations in physico-chemical parameters and metals at a hydroelectric power station reservoir by applying Multivariate Analyses and Artificial Neural Networks (ANN) statistical techniques. A Factor Analysis was used to reduce the number of variables: the first factor was composed of elements Ca, K, Mg and Na, and the second by Chemical Oxygen Demand. The ANN showed 100% correct classifications in training and validation samples. Physico-chemical analyses showed that water pH values were not statistically different between the dry and rainy seasons, while temperature, conductivity, alkalinity, ammonia and DO were higher in the dry period. TSS, hardness and COD, on the other hand, were higher during the rainy season. The statistical analyses showed that Ca, K, Mg and Na are directly connected to the Chemical Oxygen Demand, which indicates a possibility of their input into the reservoir system by domestic sewage and agricultural run-offs. These statistical applications, thus, are also relevant in cases of environmental management and policy decision-making processes, to identify which factors should be further studied and/or modified to recover degraded or contaminated water bodies. Copyright © 2012 Elsevier B.V. All rights reserved.

  8. Redes em subsidiárias de multinacionais: um estudo de caso com análise de redes sociais de inventores e patentes Networks in multinational subsidiaries: a case study analyzing social networks of inventors and patents

    Directory of Open Access Journals (Sweden)

    Belmiro do Nascimento João

    2009-10-01

    Full Text Available Este artigo mostra a relevância estratégica de uma subsidiária do grupo multinacional Sabó, do setor de autopeças. Foi realizado um estudo de caso com análise de redes sociais e entrevistas com executivos para examinar uma rede de inventores e patentes depositadas entre 1978 e 2008 para esse grupo. Há uma breve revisão da literatura de negócios internacionais e da relevância estratégica de subsidiárias de multinacionais, do papel das redes, complementada pela questão das competências e do conhecimento em subsidiárias. O artigo parte do mapeamento total da rede (matriz e subsidiárias, de patentes e inventores (atores para a Sabó, com suas relações investigadas por meio da análise de redes sociais (ARS. A relevância estratégica da subsidiária é enfatizada na estratégia global da empresa. Este artigo analisa as competências essenciais desenvolvidas pela subsidiária, bem como as métricas de rede, destacando a atuação dos principais atores (centrais e seus papéis na rede como brokers.This article shows the strategic relevance of a multinational group subsidiary in the auto parts industry. The research included a single case study, social network analysis and interviews with managers in order to examine a network of inventors and patents for the Sabó Group in the period between 1978 and 2008. The article presents a brief review of the literature concerning international business and the strategic relevance of multinational subsidiaries, the role of networks, and the issue of competencies and knowledge in subsidiaries. The study starts by mapping the whole network (headquarters and subsidiaries - from patents and inventors (actors towards the Sabó Group -, investigating the relationships through social network analysis (SNA. The strategic relevance of the subsidiary is emphasized by the company's overall strategy. This article examines the core competencies developed by the subsidiary and the network metrics

  9. A π-π 3D network of tetranuclear μ2/μ3-carbonato Dy(III) bis-pyrazolylpyridine clusters showing single molecule magnetism features.

    Science.gov (United States)

    Gass, Ian A; Moubaraki, Boujemaa; Langley, Stuart K; Batten, Stuart R; Murray, Keith S

    2012-02-18

    2,6-Di(pyrazole-3-yl)pyridine, 3-bpp, forms a porous (4(9)·6(6)) π-π mediated 3D network of trigonal pyramidal [Dy(III)(4)] carbonato-bridged complexes, with hexagonal channels comprising 54% of the unit cell volume, the material displaying slow magnetisation reversal. This journal is © The Royal Society of Chemistry 2012

  10. Analyzing Snowpack Metrics Over Large Spatial Extents Using Calibrated, Enhanced-Resolution Brightness Temperature Data and Long Short Term Memory Artificial Neural Networks

    Science.gov (United States)

    Norris, W.; J Q Farmer, C.

    2017-12-01

    Snow water equivalence (SWE) is a difficult metric to measure accurately over large spatial extents; snow-tell sites are too localized, and traditional remotely sensed brightness temperature data is at too coarse of a resolution to capture variation. The new Calibrated Enhanced-Resolution Brightness Temperature (CETB) data from the National Snow and Ice Data Center (NSIDC) offers remotely sensed brightness temperature data at an enhanced resolution of 3.125 km versus the original 25 km, which allows for large spatial extents to be analyzed with reduced uncertainty compared to the 25km product. While the 25km brightness temperature data has proved useful in past research — one group found decreasing trends in SWE outweighed increasing trends three to one in North America; other researchers used the data to incorporate winter conditions, like snow cover, into ecological zoning criterion — with the new 3.125 km data, it is possible to derive more accurate metrics for SWE, since we have far more spatial variability in measurements. Even with higher resolution data, using the 37 - 19 GHz frequencies to estimate SWE distorts the data during times of melt onset and accumulation onset. Past researchers employed statistical splines, while other successful attempts utilized non-parametric curve fitting to smooth out spikes distorting metrics. In this work, rather than using legacy curve fitting techniques, a Long Short Term Memory (LSTM) Artificial Neural Network (ANN) was trained to perform curve fitting on the data. LSTM ANN have shown great promise in modeling time series data, and with almost 40 years of data available — 14,235 days — there is plenty of training data for the ANN. LSTM's are ideal for this type of time series analysis because they allow important trends to persist for long periods of time, but ignore short term fluctuations; since LSTM's have poor mid- to short-term memory, they are ideal for smoothing out the large spikes generated in the melt

  11. Analyzing the Impact of Different Pcv Calibration Models on Height Determination Using Gps/Glonass Observations from Asg-Eupos Network

    Science.gov (United States)

    Dawidowicz, Karol

    2014-12-01

    The integration of GPS with GLONASS is very important in satellite-based positioning because it can clearly improve reliability and availability. However, unlike GPS, GLONASS satellites transmit signals at different frequencies. This results in significant difficulties in modeling and ambiguity resolution for integrated GNSS positioning. There are also some difficulties related to the antenna Phase Center Variations (PCV) problem because, as is well known, the PCV is dependent on the received signal frequency dependent. Thus, processing simultaneous observations from different positioning systems, e.g. GPS and GLONASS, we can expect complications resulting from the different structure of signals and differences in satellite constellations. The ASG-EUPOS multifunctional system for precise satellite positioning is a part of the EUPOS project involving countries of Central and Eastern Europe. The number of its users is increasing rapidly. Currently 31 of 101 reference stations are equipped with GPS/GLONASS receivers and the number is still increasing. The aim of this paper is to study the height solution differences caused by using different PCV calibration models in integrated GPS/GLONASS observation processing. Studies were conducted based on the datasets from the ASG-EUPOS network. Since the study was intended to evaluate the impact on height determination from the users' point of view, a so-called "commercial" software was chosen for post-processing. The analysis was done in a baseline mode: 3 days of GNSS data collected with three different receivers and antennas were used. For the purposes of research the daily observations were divided into different sessions with a session length of one hour. The results show that switching between relative and absolute PCV models may cause an obvious effect on height determination. This issue is particularly important when mixed GPS/GLONASS observations are post-processed.

  12. FMG, RENUM, LINEL, ELLFMG, ELLP, and DIMES: Chain of programs for calculating and analyzing fluid flow through two-dimensional fracture networks -- theory and design

    International Nuclear Information System (INIS)

    Billaux, D.; Bodea, S.; Long, J.

    1988-02-01

    This report describes some of the programs developed at Lawrence Berkeley Laboratory for network modelling. By themselves, these programs form a complete chain for the study of the equivalent permeability of two-dimensional fracture networks. FMG generates the fractures considered as line discontinuities, with any desired distribution of aperture, length, and orientation. The locations of these fractures on a plane can be either specified or generated randomly. The intersections of these fractures with each other, and with the boundaries of a specified flow region, are determined, and a finite element line network is output. RENUM is a line network optimizer. Nodes very close to each other are merged, dead-ends are removed, and the nodes are then renumbered in order to minimize the bandwidth of the corresponding linear system of equations. LINEL computes the steady state flux through a mesh of line elements previously processed by program RENUM. Equivalent directional permeabilities are output. ELLFMG determines the three components of the permeability tensor which best fits the directional permeabilities output by LINEL. A measure of the goodness fit is also computed. Two plotting programs, DIMES and ELLP, help visualize the outputs of these programs. DIMES plots the line network at various stages of the process. ELLP plots the equivalent permeability results. 14 refs., 25 figs

  13. The Avian Knowledge Network : A partnership to organize, analyze, and visualize bird observation data for education, conservation, research, and land management

    Science.gov (United States)

    Marshall Iliff; Leo Salas; Ernesto Ruelas Inzunza; Grant Ballard; Denis Lepage; Steve Kelling

    2009-01-01

    The Avian Knowledge Network (AKN) is an international collaboration of academic, nongovernment, and government institutions with the goal of organizing observations of birds into an interoperable format to enhance access, data visualization and exploration, and scientifi c analyses. The AKN uses proven cyberinfrastructure and informatics techniques as the foundation of...

  14. A Network Traffic Control Enhancement Approach over Bluetooth Networks

    DEFF Research Database (Denmark)

    Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun

    2003-01-01

    This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated solu...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well......This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...

  15. Multichannel Mars Organic Analyzer (McMOA): Microfluidic Networks for the Automated In Situ Microchip Electrophoretic Analysis of Organic Biomarkers on Mars

    Science.gov (United States)

    Chiesl, T. N.; Benhabib, M.; Stockton, A. M.; Mathies, R. A.

    2010-04-01

    We present the Multichannel Mars Organic Analyzer (McMOA) for the analysis of Amino Acids, PAHs, and Oxidized Carbon. Microfluidic architecures integrating automated metering, mixing, on chip reactions, and serial dilutions are also discussed.

  16. Cocaine users with comorbid Cluster B personality disorders show dysfunctional brain activation and connectivity in the emotional regulation networks during negative emotion maintenance and reappraisal.

    Science.gov (United States)

    Albein-Urios, Natalia; Verdejo-Román, Juan; Soriano-Mas, Carles; Asensio, Samuel; Martínez-González, José Miguel; Verdejo-García, Antonio

    2013-12-01

    Cocaine dependence often co-occurs with Cluster B personality disorders. Since both disorders are characterized by emotion regulation deficits, we predicted that cocaine comorbid patients would exhibit dysfunctional patterns of brain activation and connectivity during reappraisal of negative emotions. We recruited 18 cocaine users with comorbid Cluster B personality disorders, 17 cocaine users without comorbidities and 21 controls to be scanned using functional magnetic resonance imaging (fMRI) during performance on a reappraisal task in which they had to maintain or suppress the emotions induced by negative affective stimuli. We followed region of interest (ROI) and whole-brain approaches to investigate brain activations and connectivity associated with negative emotion experience and reappraisal. Results showed that cocaine users with comorbid personality disorders had reduced activation of the subgenual anterior cingulate cortex during negative emotion maintenance and increased activation of the lateral orbitofrontal cortex and the amygdala during reappraisal. Amygdala activation correlated with impulsivity and antisocial beliefs in the comorbid group. Connectivity analyses showed that in the cocaine comorbid group the subgenual cingulate was less efficiently connected with the amygdala and the fusiform gyri and more efficiently connected with the anterior insula during maintenance, whereas during reappraisal the left orbitofrontal cortex was more efficiently connected with the amygdala and the right orbitofrontal cortex was less efficiently connected with the dorsal striatum. We conclude that cocaine users with comorbid Cluster B personality disorders have distinctive patterns of brain activation and connectivity during maintenance and reappraisal of negative emotions, which correlate with impulsivity and dysfunctional beliefs. Copyright © 2013 Elsevier B.V. and ECNP. All rights reserved.

  17. Analyzing the interactions of mRNAs, miRNAs, lncRNAs and circRNAs to predict competing endogenous RNA networks in glioblastoma.

    Science.gov (United States)

    Yuan, Yang; Jiaoming, Li; Xiang, Wang; Yanhui, Liu; Shu, Jiang; Maling, Gou; Qing, Mao

    2018-05-01

    Cross-talk between competitive endogenous RNAs (ceRNAs) may play a critical role in revealing potential mechanisms of tumor development and physiology. Glioblastoma is the most common type of malignant primary brain tumor, and the mechanisms of tumor genesis and development in glioblastoma are unclear. Here, to investigate the role of non-coding RNAs and the ceRNA network in glioblastoma, we performed paired-end RNA sequencing and microarray analyses to obtain the expression profiles of mRNAs, lncRNAs, circRNAs and miRNAs. We identified that the expression of 501 lncRNAs, 1999 mRNAs, 2038 circRNAs and 143 miRNAs were often altered between glioblastoma and matched normal brain tissue. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed on these differentially expressed mRNAs and miRNA-mediated target genes of lncRNAs and circRNAs. Furthermore, we used a multi-step computational framework and several bioinformatics methods to construct a ceRNA network combining mRNAs, miRNAs, lncRNAs and circRNA, based on co-expression analysis between the differentially expressed RNAs. We identified that plenty of lncRNAs, CircRNAs and their downstream target genes in the ceRNA network are related to glutamatergic synapse, suggesting that glutamate metabolism is involved in glioma biological functions. Our results will accelerate the understanding of tumorigenesis, cancer progression and even therapeutic targeting in glioblastoma.

  18. The Contribution of GIS to Display and Analyze the Water Quality Data Collected by a Wireless Sensor Network: Case of Bouregreg Catchment, Morocco

    Science.gov (United States)

    Boubakri, S.; Rhinane, H.

    2017-11-01

    The monitoring of water quality is, in most cases, managed in the laboratory and not on real time bases. Besides this process being lengthy, it doesn't provide the required specifications to describe the evolution of the quality parameters that are of interest. This study presents the integration of Geographic Information Systems (GIS) with wireless sensor networks (WSN) aiming to create a system able to detect the parameters like temperature, salinity and conductivity in a Moroccan catchment scale and transmit information to the support station. This Information is displayed and evaluated in a GIS using maps and spatial dashboard to monitor the water quality in real time.

  19. THE CONTRIBUTION OF GIS TO DISPLAY AND ANALYZE THE WATER QUALITY DATA COLLECTED BY A WIRELESS SENSOR NETWORK: CASE OF BOUREGREG CATCHMENT, MOROCCO

    Directory of Open Access Journals (Sweden)

    S. Boubakri

    2017-11-01

    Full Text Available The monitoring of water quality is, in most cases, managed in the laboratory and not on real time bases. Besides this process being lengthy, it doesn’t provide the required specifications to describe the evolution of the quality parameters that are of interest. This study presents the integration of Geographic Information Systems (GIS with wireless sensor networks (WSN aiming to create a system able to detect the parameters like temperature, salinity and conductivity in a Moroccan catchment scale and transmit information to the support station. This Information is displayed and evaluated in a GIS using maps and spatial dashboard to monitor the water quality in real time.

  20. Robustness of airline route networks

    Science.gov (United States)

    Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

    2016-03-01

    Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

  1. Networking for the Environment

    DEFF Research Database (Denmark)

    Dickel, Petra; Hörisch, Jacob; Ritter, Thomas

    2018-01-01

    Although the public debate on the environmental orientation of firms has intensified, there is a lack of understanding about the consequences of that orientation, especially in terms of its impact on firms' networking behavior. In order to fill this gap, this paper analyzes the impact of external...... and internal environmental orientation on start-ups’ network characteristics, because networks are both vital for the success of start-ups and resource demanding. More specifically, the effects of environmental orientation on networking frequency and network size among start-ups are analyzed. Empirical data...... from 248 technology-based start-ups shows that those firms with a strong external environmental orientation have significantly higher networking frequencies and build larger networks. Conversely, a strong internal environmental orientation is linked to smaller networks. Thus, the results highlight...

  2. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  3. Cascading Failures and Recovery in Networks of Networks

    Science.gov (United States)

    Havlin, Shlomo

    Network science have been focused on the properties of a single isolated network that does not interact or depends on other networks. In reality, many real-networks, such as power grids, transportation and communication infrastructures interact and depend on other networks. I will present a framework for studying the vulnerability and the recovery of networks of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes like certain locations play a role in two networks -multiplex. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. I will present analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. I will show, that the general theory has many novel features that are not present in the classical network theory. When recovery of components is possible global spontaneous recovery of the networks and hysteresis phenomena occur and the theory suggests an optimal repairing strategy of system of systems. I will also show that interdependent networks embedded in space are significantly more vulnerable compared to non embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences.Thus, analyzing data of real network of networks is highly required to understand the system vulnerability. DTRA, ONR, Israel Science Foundation.

  4. Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory

    Directory of Open Access Journals (Sweden)

    Nai-Ru Xu

    2016-01-01

    Full Text Available The paper establishes the evolutionary mechanism model of agile supply chain network by means of complex network theory which can be used to describe the growth process of the agile supply chain network and analyze the complexity of the agile supply chain network. After introducing the process and the suitability of taking complex network theory into supply chain network research, the paper applies complex network theory into the agile supply chain network research, analyzes the complexity of agile supply chain network, presents the evolutionary mechanism of agile supply chain network based on complex network theory, and uses Matlab to simulate degree distribution, average path length, clustering coefficient, and node betweenness. Simulation results show that the evolution result displays the scale-free property. It lays the foundations of further research on agile supply chain network based on complex network theory.

  5. Vulnerability and controllability of networks of networks

    International Nuclear Information System (INIS)

    Liu, Xueming; Peng, Hao; Gao, Jianxi

    2015-01-01

    Network science is a highly interdisciplinary field ranging from natural science to engineering technology and it has been applied to model complex systems and used to explain their behaviors. Most previous studies have been focus on isolated networks, but many real-world networks do in fact interact with and depend on other networks via dependency connectivities, forming “networks of networks” (NON). The interdependence between networks has been found to largely increase the vulnerability of interacting systems, when a node in one network fails, it usually causes dependent nodes in other networks to fail, which, in turn, may cause further damage on the first network and result in a cascade of failures with sometimes catastrophic consequences, e.g., electrical blackouts caused by the interdependence of power grids and communication networks. The vulnerability of a NON can be analyzed by percolation theory that can be used to predict the critical threshold where a NON collapses. We review here the analytic framework for analyzing the vulnerability of NON, which yields novel percolation laws for n-interdependent networks and also shows that percolation theory of a single network studied extensively in physics and mathematics in the last 50 years is a specific limited case of the more general case of n interacting networks. Understanding the mechanism behind the cascading failure in NON enables us finding methods to decrease the vulnerability of the natural systems and design of more robust infrastructure systems. By examining the vulnerability of NON under targeted attack and studying the real interdependent systems, we find two methods to decrease the systems vulnerability: (1) protect the high-degree nodes, and (2) increase the degree correlation between networks. Furthermore, the ultimate proof of our understanding of natural and technological systems is reflected in our ability to control them. We also review the recent studies and challenges on the

  6. Analyzing competition in intermodal freight transport networks

    NARCIS (Netherlands)

    Saeedi, Hamid; Wiegmans, Bart; Behdani, Behzad; Zuidwijk, Rob

    2017-01-01

    To cope with an intense and competitive environment, intermodal freight transport operators have increasingly adopted business practices —like horizontal and vertical business integration—which aim to reduce the operational costs, increase the profit margins, and improve their competitive position

  7. Analyzing Earth Science Research Networking through Visualizations

    Science.gov (United States)

    Hasnain, S.; Stephan, R.; Narock, T.

    2017-12-01

    Using D3.js we visualize collaboration amongst several geophysical science organizations, such as the American Geophysical Union (AGU) and the Federation of Earth Science Information Partners (ESIP). We look at historical trends in Earth Science research topics, cross-domain collaboration, and topics of interest to the general population. The visualization techniques used provide an effective way for non-experts to easily explore distributed and heterogeneous Big Data. Analysis of these visualizations provides stakeholders with insights into optimizing meetings, performing impact evaluation, structuring outreach efforts, and identifying new opportunities for collaboration.

  8. Soft Decision Analyzer

    Science.gov (United States)

    Lansdowne, Chatwin; Steele, Glen; Zucha, Joan; Schlesinger, Adam

    2013-01-01

    We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

  9. A 40 GHz fully integrated circuit with a vector network analyzer and a coplanar-line-based detection area for circulating tumor cell analysis using 65 nm CMOS technology

    Science.gov (United States)

    Nakanishi, Taiki; Matsunaga, Maya; Kobayashi, Atsuki; Nakazato, Kazuo; Niitsu, Kiichi

    2018-03-01

    A 40-GHz fully integrated CMOS-based circuit for circulating tumor cells (CTC) analysis, consisting of an on-chip vector network analyzer (VNA) and a highly sensitive coplanar-line-based detection area is presented in this paper. In this work, we introduce a fully integrated architecture that eliminates unwanted parasitic effects. The proposed analyzer was designed using 65 nm CMOS technology, and SPICE and MWS simulations were used to validate its operation. The simulation confirmed that the proposed circuit can measure S-parameter shifts resulting from the addition of various types of tumor cells to the detection area, the data of which are provided in a previous study: the |S 21| values for HepG2, A549, and HEC-1-A cells are -0.683, -0.580, and -0.623 dB, respectively. Additionally, the measurement demonstrated an S-parameters reduction of -25.7% when a silicone resin was put on the circuit. Hence, the proposed system is expected to contribute to cancer diagnosis.

  10. Symmetry in Complex Networks

    Directory of Open Access Journals (Sweden)

    Angel Garrido

    2011-01-01

    Full Text Available In this paper, we analyze a few interrelated concepts about graphs, such as their degree, entropy, or their symmetry/asymmetry levels. These concepts prove useful in the study of different types of Systems, and particularly, in the analysis of Complex Networks. A System can be defined as any set of components functioning together as a whole. A systemic point of view allows us to isolate a part of the world, and so, we can focus on those aspects that interact more closely than others. Network Science analyzes the interconnections among diverse networks from different domains: physics, engineering, biology, semantics, and so on. Current developments in the quantitative analysis of Complex Networks, based on graph theory, have been rapidly translated to studies of brain network organization. The brain's systems have complex network features—such as the small-world topology, highly connected hubs and modularity. These networks are not random. The topology of many different networks shows striking similarities, such as the scale-free structure, with the degree distribution following a Power Law. How can very different systems have the same underlying topological features? Modeling and characterizing these networks, looking for their governing laws, are the current lines of research. So, we will dedicate this Special Issue paper to show measures of symmetry in Complex Networks, and highlight their close relation with measures of information and entropy.

  11. Analyzing the Facebook Friendship Graph

    OpenAIRE

    Catanese, Salvatore; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo

    2010-01-01

    Online Social Networks (OSN) during last years acquired a huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, our purpose is to analyze Facebook, considering a significant sample of data reflecting relationships among subscribed users. Our goal is to extract, from this platform, relevant ...

  12. Show-Bix &

    DEFF Research Database (Denmark)

    2014-01-01

    The anti-reenactment 'Show-Bix &' consists of 5 dias projectors, a dial phone, quintophonic sound, and interactive elements. A responsive interface will enable the Dias projectors to show copies of original dias slides from the Show-Bix piece ”March på Stedet”, 265 images in total. The copies are...

  13. Hardware Realization of an Ethernet Packet Analyzer Search Engine

    Science.gov (United States)

    2000-06-30

    specific for the home automation industry. This analyzer will be at the gateway of a network and analyze Ethernet packets as they go by. It will keep... home automation and not the computer network. This system is a stand-alone real-time network analyzer capable of decoding Ethernet protocols. The

  14. Comparison analysis on vulnerability of metro networks based on complex network

    Science.gov (United States)

    Zhang, Jianhua; Wang, Shuliang; Wang, Xiaoyuan

    2018-04-01

    This paper analyzes the networked characteristics of three metro networks, and two malicious attacks are employed to investigate the vulnerability of metro networks based on connectivity vulnerability and functionality vulnerability. Meanwhile, the networked characteristics and vulnerability of three metro networks are compared with each other. The results show that Shanghai metro network has the largest transport capacity, Beijing metro network has the best local connectivity and Guangzhou metro network has the best global connectivity, moreover Beijing metro network has the best homogeneous degree distribution. Furthermore, we find that metro networks are very vulnerable subjected to malicious attacks, and Guangzhou metro network has the best topological structure and reliability among three metro networks. The results indicate that the proposed methodology is feasible and effective to investigate the vulnerability and to explore better topological structure of metro networks.

  15. Robustness of weighted networks

    Science.gov (United States)

    Bellingeri, Michele; Cassi, Davide

    2018-01-01

    Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

  16. Maximum entropy networks are more controllable than preferential attachment networks

    International Nuclear Information System (INIS)

    Hou, Lvlin; Small, Michael; Lao, Songyang

    2014-01-01

    A maximum entropy (ME) method to generate typical scale-free networks has been recently introduced. We investigate the controllability of ME networks and Barabási–Albert preferential attachment networks. Our experimental results show that ME networks are significantly more easily controlled than BA networks of the same size and the same degree distribution. Moreover, the control profiles are used to provide insight into control properties of both classes of network. We identify and classify the driver nodes and analyze the connectivity of their neighbors. We find that driver nodes in ME networks have fewer mutual neighbors and that their neighbors have lower average degree. We conclude that the properties of the neighbors of driver node sensitively affect the network controllability. Hence, subtle and important structural differences exist between BA networks and typical scale-free networks of the same degree distribution. - Highlights: • The controllability of maximum entropy (ME) and Barabási–Albert (BA) networks is investigated. • ME networks are significantly more easily controlled than BA networks of the same degree distribution. • The properties of the neighbors of driver node sensitively affect the network controllability. • Subtle and important structural differences exist between BA networks and typical scale-free networks

  17. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago Vanderlei; Giannitsarou, Chrysi; Johnson, CR

    2017-01-01

    We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and define a network aggregator that preserves network cohesion.

  18. Latent geometry of bipartite networks

    Science.gov (United States)

    Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

    2017-03-01

    Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

  19. ORA: Organization Risk Analyzer

    National Research Council Canada - National Science Library

    Carley, Kathleen M; Reminga, Jeff

    2004-01-01

    .... Measures are also organized by input requirements and by output. ORA generates formatted reports viewable on screen or in log files, and reads and writes networks in multiple data formats to be interoperable...

  20. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  1. Talking with TV shows

    DEFF Research Database (Denmark)

    Sandvik, Kjetil; Laursen, Ditte

    2014-01-01

    User interaction with radio and television programmes is not a new thing. However, with new cross-media production concepts such as X Factor and Voice, this is changing dramatically. The second-screen logic of these productions encourages viewers, along with TV’s traditional one-way communication...... mode, to communicate on interactive (dialogue-enabling) devices such as laptops, smartphones and tablets. Using the TV show Voice as our example, this article shows how the technological and situational set-up of the production invites viewers to engage in new ways of interaction and communication...

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

    Science.gov (United States)

    Yoshihara, Chika; Shimizu, Shinji

    2005-10-01

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

  3. Talk Show Science.

    Science.gov (United States)

    Moore, Mitzi Ruth

    1992-01-01

    Proposes having students perform skits in which they play the roles of the science concepts they are trying to understand. Provides the dialog for a skit in which hot and cold gas molecules are interviewed on a talk show to study how these properties affect wind, rain, and other weather phenomena. (MDH)

  4. Obesity in show cats.

    Science.gov (United States)

    Corbee, R J

    2014-12-01

    Obesity is an important disease with a high prevalence in cats. Because obesity is related to several other diseases, it is important to identify the population at risk. Several risk factors for obesity have been described in the literature. A higher incidence of obesity in certain cat breeds has been suggested. The aim of this study was to determine whether obesity occurs more often in certain breeds. The second aim was to relate the increased prevalence of obesity in certain breeds to the official standards of that breed. To this end, 268 cats of 22 different breeds investigated by determining their body condition score (BCS) on a nine-point scale by inspection and palpation, at two different cat shows. Overall, 45.5% of the show cats had a BCS > 5, and 4.5% of the show cats had a BCS > 7. There were significant differences between breeds, which could be related to the breed standards. Most overweight and obese cats were in the neutered group. It warrants firm discussions with breeders and cat show judges to come to different interpretations of the standards in order to prevent overweight conditions in certain breeds from being the standard of beauty. Neutering predisposes for obesity and requires early nutritional intervention to prevent obese conditions. Journal of Animal Physiology and Animal Nutrition © 2014 Blackwell Verlag GmbH.

  5. Honored Teacher Shows Commitment.

    Science.gov (United States)

    Ratte, Kathy

    1987-01-01

    Part of the acceptance speech of the 1985 National Council for the Social Studies Teacher of the Year, this article describes the censorship experience of this honored social studies teacher. The incident involved the showing of a videotape version of the feature film entitled "The Seduction of Joe Tynan." (JDH)

  6. The energy show

    International Nuclear Information System (INIS)

    1988-01-01

    The Energy Show is a new look at the problems of world energy, where our supplies come from, now and in the future. The programme looks at how we need energy to maintain our standards of living. Energy supply is shown as the complicated set of problems it is - that Fossil Fuels are both raw materials and energy sources, that some 'alternatives' so readily suggested as practical options are in reality a long way from being effective. (author)

  7. Analyzing Visibility Configurations.

    Science.gov (United States)

    Dachsbacher, C

    2011-04-01

    Many algorithms, such as level of detail rendering and occlusion culling methods, make decisions based on the degree of visibility of an object, but do not analyze the distribution, or structure, of the visible and occluded regions across surfaces. We present an efficient method to classify different visibility configurations and show how this can be used on top of existing methods based on visibility determination. We adapt co-occurrence matrices for visibility analysis and generalize them to operate on clusters of triangular surfaces instead of pixels. We employ machine learning techniques to reliably classify the thus extracted feature vectors. Our method allows perceptually motivated level of detail methods for real-time rendering applications by detecting configurations with expected visual masking. We exemplify the versatility of our method with an analysis of area light visibility configurations in ray tracing and an area-to-area visibility analysis suitable for hierarchical radiosity refinement. Initial results demonstrate the robustness, simplicity, and performance of our method in synthetic scenes, as well as real applications.

  8. Web server attack analyzer

    OpenAIRE

    Mižišin, Michal

    2013-01-01

    Web server attack analyzer - Abstract The goal of this work was to create prototype of analyzer of injection flaws attacks on web server. Proposed solution combines capabilities of web application firewall and web server log analyzer. Analysis is based on configurable signatures defined by regular expressions. This paper begins with summary of web attacks, followed by detection techniques analysis on web servers, description and justification of selected implementation. In the end are charact...

  9. Electron attachment analyzer

    International Nuclear Information System (INIS)

    Popp, P.; Grosse, H.J.; Leonhardt, J.; Mothes, S.; Oppermann, G.

    1984-01-01

    The invention concerns an electron attachment analyzer for detecting traces of electroaffine substances in electronegative gases, especially in air. The analyzer can be used for monitoring working places, e. g., in operating theatres. The analyzer consists of two electrodes inserted in a base frame of insulating material (quartz or ceramics) and a high-temperature resistant radiation source ( 85 Kr, 3 H, or 63 Ni)

  10. Nuclear power plant analyzer

    International Nuclear Information System (INIS)

    Stritar, A.

    1986-01-01

    The development of Nuclear Power Plant Analyzers in USA is described. There are two different types of Analyzers under development in USA, the forst in Idaho and Los Alamos national Lab, the second in brookhaven National lab. That one is described in detail. The computer hardware and the mathematical models of the reactor vessel thermalhydraulics are described. (author)

  11. Analyzing in the present

    DEFF Research Database (Denmark)

    Revsbæk, Line; Tanggaard, Lene

    2015-01-01

    The article presents a notion of “analyzing in the present” as a source of inspiration in analyzing qualitative research materials. The term emerged from extensive listening to interview recordings during everyday commuting to university campus. Paying attention to the way different parts of vari...

  12. Gearbox vibration diagnostic analyzer

    Science.gov (United States)

    1992-01-01

    This report describes the Gearbox Vibration Diagnostic Analyzer installed in the NASA Lewis Research Center's 500 HP Helicopter Transmission Test Stand to monitor gearbox testing. The vibration of the gearbox is analyzed using diagnostic algorithms to calculate a parameter indicating damaged components.

  13. Showing Value (Editorial

    Directory of Open Access Journals (Sweden)

    Denise Koufogiannakis

    2009-06-01

    Full Text Available When Su Cleyle and I first decided to start Evidence Based Library and Information Practice, one of the things we agreed upon immediately was that the journal be open access. We knew that a major obstacle to librarians using the research literature was that they did not have access to the research literature. Although Su and I are both academic librarians who can access a wide variety of library and information literature from our institutions, we belong to a profession where not everyone has equal access to the research in our field. Without such access to our own body of literature, how can we ever hope for practitioners to use research evidence in their decision making? It would have been contradictory to the principles of evidence based library and information practice to do otherwise.One of the specific groups we thought could use such an open access venue for discovering research literature was school librarians. School librarians are often isolated and lacking access to the research literature that may help them prove to stakeholders the importance of their libraries and their role within schools. Certainly, school libraries have been in decline and the use of evidence to show value is needed. As Ken Haycock noted in his 2003 report, The Crisis in Canada’s School Libraries: The Case for Reform and Reinvestment, “Across the country, teacher-librarians are losing their jobs or being reassigned. Collections are becoming depleted owing to budget cuts. Some principals believe that in the age of the Internet and the classroom workstation, the school library is an artifact” (9. Within this context, school librarians are looking to our research literature for evidence of the impact that school library programs have on learning outcomes and student success. They are integrating that evidence into their practice, and reflecting upon what can be improved locally. They are focusing on students and showing the impact of school libraries and

  14. Secure positioning in wireless networks

    DEFF Research Database (Denmark)

    Capkun, Srdjan; Hubaux, Jean-Pierre

    2006-01-01

    So far, the problem of positioning in wireless networks has been studied mainly in a non-adversarial settings. In this work, we analyze the resistance of positioning techniques to position and distance spoofing attacks. We propose a mechanism for secure positioning of wireless devices, that we call...... Verifiable Multilateration. We then show how this mechanism can be used to secure positioning in sensor networks. We analyze our system through simulations....

  15. Emission pathway modeling to analyze national ambition levels of decarbonization

    International Nuclear Information System (INIS)

    Kainuma, Mikiko; Waisman, Henri

    2015-01-01

    The Deep Decarbonization Pathways Project (DDPP) is a knowledge network comprising 15 Country Research Teams and several Partner Organizations which develop and share methods, assumptions, and findings related to deep decarbonization. It analyzes the technical decarbonization potential, exploring options for deep decarbonization, but also better taking into account existing infrastructure stocks. It shows the possibility to reduce total CO 2 -energy emissions by 45% by 2050, with bottom-up analyses by 15 Country Research Teams

  16. Self-Interested Routing in Queueing Networks

    OpenAIRE

    Ali K. Parlaktürk; Sunil Kumar

    2004-01-01

    We study self-interested routing in stochastic networks, taking into account the discrete stochastic dynamics of such networks. We analyze a two-station multiclass queueing network in which the system manager chooses the scheduling rule and individual customers choose routes in a self-interested manner. We show that this network can be unstable in Nash equilibrium under some scheduling rules. We also design a nontrivial scheduling rule that negates the performance degradation resulting from s...

  17. Miniature mass analyzer

    CERN Document Server

    Cuna, C; Lupsa, N; Cuna, S; Tuzson, B

    2003-01-01

    The paper presents the concept of different mass analyzers that were specifically designed as small dimension instruments able to detect with great sensitivity and accuracy the main environmental pollutants. The mass spectrometers are very suited instrument for chemical and isotopic analysis, needed in environmental surveillance. Usually, this is done by sampling the soil, air or water followed by laboratory analysis. To avoid drawbacks caused by sample alteration during the sampling process and transport, the 'in situ' analysis is preferred. Theoretically, any type of mass analyzer can be miniaturized, but some are more appropriate than others. Quadrupole mass filter and trap, magnetic sector, time-of-flight and ion cyclotron mass analyzers can be successfully shrunk, for each of them some performances being sacrificed but we must know which parameters are necessary to be kept unchanged. To satisfy the miniaturization criteria of the analyzer, it is necessary to use asymmetrical geometries, with ion beam obl...

  18. Local dependency in networks

    Directory of Open Access Journals (Sweden)

    Kudĕlka Miloš

    2015-06-01

    Full Text Available Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. We introduce a method for measuring the strength of the relationship between two nodes of a network and for their ranking. This method is applicable to all kinds of networks, including directed and weighted networks. The approach extracts dependency relations among the network’s nodes from the structure in local surroundings of individual nodes. For the tasks we deal with in this article, the key technical parameter is locality. Since only the surroundings of the examined nodes are used in computations, there is no need to analyze the entire network. This allows the application of our approach in the area of large-scale networks. We present several experiments using small networks as well as large-scale artificial and real world networks. The results of the experiments show high effectiveness due to the locality of our approach and also high quality node ranking comparable to PageRank.

  19. Extraction spectrophotometric analyzer

    International Nuclear Information System (INIS)

    Batik, J.; Vitha, F.

    1985-01-01

    Automation is discussed of extraction spectrophotometric determination of uranium in a solution. Uranium is extracted from accompanying elements in an HCl medium with a solution of tributyl phosphate in benzene. The determination is performed by measuring absorbance at 655 nm in a single-phase ethanol-water-benzene-tributyl phosphate medium. The design is described of an analyzer consisting of an analytical unit and a control unit. The analyzer performance promises increased productivity of labour, improved operating and hygiene conditions, and mainly more accurate results of analyses. (J.C.)

  20. Data Auditor: Analyzing Data Quality Using Pattern Tableaux

    Science.gov (United States)

    Srivastava, Divesh

    Monitoring databases maintain configuration and measurement tables about computer systems, such as networks and computing clusters, and serve important business functions, such as troubleshooting customer problems, analyzing equipment failures, planning system upgrades, etc. These databases are prone to many data quality issues: configuration tables may be incorrect due to data entry errors, while measurement tables may be affected by incorrect, missing, duplicate and delayed polls. We describe Data Auditor, a tool for analyzing data quality and exploring data semantics of monitoring databases. Given a user-supplied constraint, such as a boolean predicate expected to be satisfied by every tuple, a functional dependency, or an inclusion dependency, Data Auditor computes "pattern tableaux", which are concise summaries of subsets of the data that satisfy or fail the constraint. We discuss the architecture of Data Auditor, including the supported types of constraints and the tableau generation mechanism. We also show the utility of our approach on an operational network monitoring database.

  1. Network cosmology.

    Science.gov (United States)

    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.

  2. Sulfur Dioxide Analyzer Instrument Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Springston, Stephen R. [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2016-05-01

    The Sulfur Dioxide Analyzer measures sulfur dioxide based on absorbance of UV light at one wavelength by SO2 molecules which then decay to a lower energy state by emitting UV light at a longer wavelength. Specifically, SO2 + hυ1 →SO2 *→SO2 + hυ2 The emitted light is proportional to the concentration of SO2 in the optical cell. External communication with the analyzer is available through an Ethernet port configured through the instrument network of the AOS systems. The Model 43i-TLE is part of the i-series of Thermo Scientific instruments. The i-series instruments are designed to interface with external computers through the proprietary Thermo Scientific iPort Software. However, this software is somewhat cumbersome and inflexible. Brookhaven National Laboratory (BNL) has written an interface program in National Instruments LabView that both controls the Model 43i-TLE Analyzer AND queries the unit for all measurement and housekeeping data. The LabView vi (the software program written by BNL) ingests all raw data from the instrument and outputs raw data files in a uniform data format similar to other instruments in the AOS and described more fully in Section 6.0 below.

  3. Americal options analyzed differently

    NARCIS (Netherlands)

    Nieuwenhuis, J.W.

    2003-01-01

    In this note we analyze in a discrete-time context and with a finite outcome space American options starting with the idea that every tradable should be a martingale under a certain measure. We believe that in this way American options become more understandable to people with a good working

  4. Analyzing Political Television Advertisements.

    Science.gov (United States)

    Burson, George

    1992-01-01

    Presents a lesson plan to help students understand that political advertisements often mislead, lie, or appeal to emotion. Suggests that the lesson will enable students to examine political advertisements analytically. Includes a worksheet to be used by students to analyze individual political advertisements. (DK)

  5. Centrifugal analyzer development

    International Nuclear Information System (INIS)

    Burtis, C.A.; Bauer, M.L.; Bostick, W.D.

    1976-01-01

    The development of the centrifuge fast analyzer (CFA) is reviewed. The development of a miniature CFA with computer data analysis is reported and applications for automated diagnostic chemical and hematological assays are discussed. A portable CFA system with microprocessor was adapted for field assays of air and water samples for environmental pollutants, including ammonia, nitrates, nitrites, phosphates, sulfates, and silica. 83 references

  6. KWU Nuclear Plant Analyzer

    International Nuclear Information System (INIS)

    Bennewitz, F.; Hummel, R.; Oelmann, K.

    1986-01-01

    The KWU Nuclear Plant Analyzer is a real time engineering simulator based on the KWU computer programs used in plant transient analysis and licensing. The primary goal is to promote the understanding of the technical and physical processes of a nuclear power plant at an on-site training facility. Thus the KWU Nuclear Plant Analyzer is available with comparable low costs right at the time when technical questions or training needs arise. This has been achieved by (1) application of the transient code NLOOP; (2) unrestricted operator interaction including all simulator functions; (3) using the mainframe computer Control Data Cyber 176 in the KWU computing center; (4) four color graphic displays controlled by a dedicated graphic computer, no control room equipment; and (5) coupling of computers by telecommunication via telephone

  7. Analyzed Using Statistical Moments

    International Nuclear Information System (INIS)

    Oltulu, O.

    2004-01-01

    Diffraction enhanced imaging (DEl) technique is a new x-ray imaging method derived from radiography. The method uses a monorheumetten x-ray beam and introduces an analyzer crystal between an object and a detector Narrow angular acceptance of the analyzer crystal generates an improved contrast over the evaluation radiography. While standart radiography can produce an 'absorption image', DEl produces 'apparent absorption' and 'apparent refraction' images with superior quality. Objects with similar absorption properties may not be distinguished with conventional techniques due to close absorption coefficients. This problem becomes more dominant when an object has scattering properties. A simple approach is introduced to utilize scattered radiation to obtain 'pure absorption' and 'pure refraction' images

  8. Emission spectrometric isotope analyzer

    International Nuclear Information System (INIS)

    Mauersberger, K.; Meier, G.; Nitschke, W.; Rose, W.; Schmidt, G.; Rahm, N.; Andrae, G.; Krieg, D.; Kuefner, W.; Tamme, G.; Wichlacz, D.

    1982-01-01

    An emission spectrometric isotope analyzer has been designed for determining relative abundances of stable isotopes in gaseous samples in discharge tubes, in liquid samples, and in flowing gaseous samples. It consists of a high-frequency generator, a device for defined positioning of discharge tubes, a grating monochromator with oscillating slit and signal converter, signal generator, window discriminator, AND connection, read-out display, oscillograph, gas dosing device and chemical conversion system with carrier gas source and vacuum pump

  9. Influence of degree correlations on network structure and stability in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2007-08-01

    Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

  10. PhosphoSiteAnalyzer

    DEFF Research Database (Denmark)

    Bennetzen, Martin V; Cox, Jürgen; Mann, Matthias

    2012-01-01

    an algorithm to retrieve kinase predictions from the public NetworKIN webpage in a semiautomated way and applies hereafter advanced statistics to facilitate a user-tailored in-depth analysis of the phosphoproteomic data sets. The interface of the software provides a high degree of analytical flexibility......Phosphoproteomic experiments are routinely conducted in laboratories worldwide, and because of the fast development of mass spectrometric techniques and efficient phosphopeptide enrichment methods, researchers frequently end up having lists with tens of thousands of phosphorylation sites...... and is designed to be intuitive for most users. PhosphoSiteAnalyzer is a freeware program available at http://phosphosite.sourceforge.net ....

  11. Electrodynamic thermogravimetric analyzer

    International Nuclear Information System (INIS)

    Spjut, R.E.; Bar-Ziv, E.; Sarofim, A.F.; Longwell, J.P.

    1986-01-01

    The design and operation of a new device for studying single-aerosol-particle kinetics at elevated temperatures, the electrodynamic thermogravimetric analyzer (EDTGA), was examined theoretically and experimentally. The completed device consists of an electrodynamic balance modified to permit particle heating by a CO 2 laser, temperature measurement by a three-color infrared-pyrometry system, and continuous weighing by a position-control system. In this paper, the position-control, particle-weight-measurement, heating, and temperature-measurement systems are described and their limitations examined

  12. Analyzing Chinese Financial Reporting

    Institute of Scientific and Technical Information of China (English)

    SABRINA; ZHANG

    2008-01-01

    If the world’s capital markets could use a harmonized accounting framework it would not be necessary for a comparison between two or more sets of accounting standards. However,there is much to do before this becomes reality.This article aims to pres- ent a general overview of China’s General Accepted Accounting Principles(GAAP), U.S.General Accepted Accounting Principles and International Financial Reporting Standards(IFRS),and to analyze the differ- ences among IFRS,U.S.GAAP and China GAAP using fixed assets as an example.

  13. Inductive dielectric analyzer

    International Nuclear Information System (INIS)

    Agranovich, Daniel; Popov, Ivan; Ben Ishai, Paul; Feldman, Yuri; Polygalov, Eugene

    2017-01-01

    One of the approaches to bypass the problem of electrode polarization in dielectric measurements is the free electrode method. The advantage of this technique is that, the probing electric field in the material is not supplied by contact electrodes, but rather by electromagnetic induction. We have designed an inductive dielectric analyzer based on a sensor comprising two concentric toroidal coils. In this work, we present an analytic derivation of the relationship between the impedance measured by the sensor and the complex dielectric permittivity of the sample. The obtained relationship was successfully employed to measure the dielectric permittivity and conductivity of various alcohols and aqueous salt solutions. (paper)

  14. Thermodynamics of random reaction networks.

    Directory of Open Access Journals (Sweden)

    Jakob Fischer

    Full Text Available Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with Watts-Strogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa -1.5 for linear and -1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks.

  15. Thermodynamics of random reaction networks.

    Science.gov (United States)

    Fischer, Jakob; Kleidon, Axel; Dittrich, Peter

    2015-01-01

    Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha) and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with Watts-Strogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa -1.5 for linear and -1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks.

  16. Plutonium solution analyzer

    International Nuclear Information System (INIS)

    Burns, D.A.

    1994-09-01

    A fully automated analyzer has been developed for plutonium solutions. It was assembled from several commercially available modules, is based upon segmented flow analysis, and exhibits precision about an order of magnitude better than commercial units (0.5%-O.05% RSD). The system was designed to accept unmeasured, untreated liquid samples in the concentration range 40-240 g/L and produce a report with sample identification, sample concentrations, and an abundance of statistics. Optional hydraulics can accommodate samples in the concentration range 0.4-4.0 g/L. Operating at a typical rate of 30 to 40 samples per hour, it consumes only 0.074 mL of each sample and standard, and generates waste at the rate of about 1.5 mL per minute. No radioactive material passes through its multichannel peristaltic pump (which remains outside the glovebox, uncontaminated) but rather is handled by a 6-port, 2-position chromatography-type loop valve. An accompanying computer is programmed in QuickBASIC 4.5 to provide both instrument control and data reduction. The program is truly user-friendly and communication between operator and instrument is via computer screen displays and keyboard. Two important issues which have been addressed are waste minimization and operator safety (the analyzer can run in the absence of an operator, once its autosampler has been loaded)

  17. Multiple capillary biochemical analyzer

    Science.gov (United States)

    Dovichi, N.J.; Zhang, J.Z.

    1995-08-08

    A multiple capillary analyzer allows detection of light from multiple capillaries with a reduced number of interfaces through which light must pass in detecting light emitted from a sample being analyzed, using a modified sheath flow cuvette. A linear or rectangular array of capillaries is introduced into a rectangular flow chamber. Sheath fluid draws individual sample streams through the cuvette. The capillaries are closely and evenly spaced and held by a transparent retainer in a fixed position in relation to an optical detection system. Collimated sample excitation radiation is applied simultaneously across the ends of the capillaries in the retainer. Light emitted from the excited sample is detected by the optical detection system. The retainer is provided by a transparent chamber having inward slanting end walls. The capillaries are wedged into the chamber. One sideways dimension of the chamber is equal to the diameter of the capillaries and one end to end dimension varies from, at the top of the chamber, slightly greater than the sum of the diameters of the capillaries to, at the bottom of the chamber, slightly smaller than the sum of the diameters of the capillaries. The optical system utilizes optic fibers to deliver light to individual photodetectors, one for each capillary tube. A filter or wavelength division demultiplexer may be used for isolating fluorescence at particular bands. 21 figs.

  18. Plutonium solution analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Burns, D.A.

    1994-09-01

    A fully automated analyzer has been developed for plutonium solutions. It was assembled from several commercially available modules, is based upon segmented flow analysis, and exhibits precision about an order of magnitude better than commercial units (0.5%-O.05% RSD). The system was designed to accept unmeasured, untreated liquid samples in the concentration range 40-240 g/L and produce a report with sample identification, sample concentrations, and an abundance of statistics. Optional hydraulics can accommodate samples in the concentration range 0.4-4.0 g/L. Operating at a typical rate of 30 to 40 samples per hour, it consumes only 0.074 mL of each sample and standard, and generates waste at the rate of about 1.5 mL per minute. No radioactive material passes through its multichannel peristaltic pump (which remains outside the glovebox, uncontaminated) but rather is handled by a 6-port, 2-position chromatography-type loop valve. An accompanying computer is programmed in QuickBASIC 4.5 to provide both instrument control and data reduction. The program is truly user-friendly and communication between operator and instrument is via computer screen displays and keyboard. Two important issues which have been addressed are waste minimization and operator safety (the analyzer can run in the absence of an operator, once its autosampler has been loaded).

  19. Molecular ecological network analyses.

    Science.gov (United States)

    Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong

    2012-05-30

    Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open

  20. Analyzing Pseudophosphatase Function.

    Science.gov (United States)

    Hinton, Shantá D

    2016-01-01

    Pseudophosphatases regulate signal transduction cascades, but their mechanisms of action remain enigmatic. Reflecting this mystery, the prototypical pseudophosphatase STYX (phospho-serine-threonine/tyrosine-binding protein) was named with allusion to the river of the dead in Greek mythology to emphasize that these molecules are "dead" phosphatases. Although proteins with STYX domains do not catalyze dephosphorylation, this in no way precludes their having other functions as integral elements of signaling networks. Thus, understanding their roles in signaling pathways may mark them as potential novel drug targets. This chapter outlines common strategies used to characterize the functions of pseudophosphatases, using as an example MK-STYX [mitogen-activated protein kinase (MAPK) phospho-serine-threonine/tyrosine binding], which has been linked to tumorigenesis, apoptosis, and neuronal differentiation. We start with the importance of "restoring" (when possible) phosphatase activity in a pseudophosphatase so that the active mutant may be used as a comparison control throughout immunoprecipitation and mass spectrometry analyses. To this end, we provide protocols for site-directed mutagenesis, mammalian cell transfection, co-immunoprecipitation, phosphatase activity assays, and immunoblotting that we have used to investigate MK-STYX and the active mutant MK-STYXactive. We also highlight the importance of utilizing RNA interference (RNAi) "knockdown" technology to determine a cellular phenotype in various cell lines. Therefore, we outline our protocols for introducing short hairpin RNA (shRNA) expression plasmids into mammalians cells and quantifying knockdown of gene expression with real-time quantitative PCR (qPCR). A combination of cellular, molecular, biochemical, and proteomic techniques has served as powerful tools in identifying novel functions of the pseudophosphatase MK-STYX. Likewise, the information provided here should be a helpful guide to elucidating the

  1. Trace impurity analyzer

    International Nuclear Information System (INIS)

    Schneider, W.J.; Edwards, D. Jr.

    1979-01-01

    The desirability for long-term reliability of large scale helium refrigerator systems used on superconducting accelerator magnets has necessitated detection of impurities to levels of a few ppM. An analyzer that measures trace impurity levels of condensable contaminants in concentrations of less than a ppM in 15 atm of He is described. The instrument makes use of the desorption temperature at an indicated pressure of the various impurities to determine the type of contaminant. The pressure rise at that temperature yields a measure of the contaminant level of the impurity. A LN 2 cryogenic charcoal trap is also employed to measure air impurities (nitrogen and oxygen) to obtain the full range of contaminant possibilities. The results of this detector which will be in use on the research and development helium refrigerator of the ISABELLE First-Cell is described

  2. Analyzing Water's Optical Absorption

    Science.gov (United States)

    2002-01-01

    A cooperative agreement between World Precision Instruments (WPI), Inc., and Stennis Space Center has led the UltraPath(TM) device, which provides a more efficient method for analyzing the optical absorption of water samples at sea. UltraPath is a unique, high-performance absorbance spectrophotometer with user-selectable light path lengths. It is an ideal tool for any study requiring precise and highly sensitive spectroscopic determination of analytes, either in the laboratory or the field. As a low-cost, rugged, and portable system capable of high- sensitivity measurements in widely divergent waters, UltraPath will help scientists examine the role that coastal ocean environments play in the global carbon cycle. UltraPath(TM) is a trademark of World Precision Instruments, Inc. LWCC(TM) is a trademark of World Precision Instruments, Inc.

  3. PDA: Pooled DNA analyzer

    Directory of Open Access Journals (Sweden)

    Lin Chin-Yu

    2006-04-01

    Full Text Available Abstract Background Association mapping using abundant single nucleotide polymorphisms is a powerful tool for identifying disease susceptibility genes for complex traits and exploring possible genetic diversity. Genotyping large numbers of SNPs individually is performed routinely but is cost prohibitive for large-scale genetic studies. DNA pooling is a reliable and cost-saving alternative genotyping method. However, no software has been developed for complete pooled-DNA analyses, including data standardization, allele frequency estimation, and single/multipoint DNA pooling association tests. This motivated the development of the software, 'PDA' (Pooled DNA Analyzer, to analyze pooled DNA data. Results We develop the software, PDA, for the analysis of pooled-DNA data. PDA is originally implemented with the MATLAB® language, but it can also be executed on a Windows system without installing the MATLAB®. PDA provides estimates of the coefficient of preferential amplification and allele frequency. PDA considers an extended single-point association test, which can compare allele frequencies between two DNA pools constructed under different experimental conditions. Moreover, PDA also provides novel chromosome-wide multipoint association tests based on p-value combinations and a sliding-window concept. This new multipoint testing procedure overcomes a computational bottleneck of conventional haplotype-oriented multipoint methods in DNA pooling analyses and can handle data sets having a large pool size and/or large numbers of polymorphic markers. All of the PDA functions are illustrated in the four bona fide examples. Conclusion PDA is simple to operate and does not require that users have a strong statistical background. The software is available at http://www.ibms.sinica.edu.tw/%7Ecsjfann/first%20flow/pda.htm.

  4. SINDA, Systems Improved Numerical Differencing Analyzer

    Science.gov (United States)

    Fink, L. C.; Pan, H. M. Y.; Ishimoto, T.

    1972-01-01

    Computer program has been written to analyze group of 100-node areas and then provide for summation of any number of 100-node areas to obtain temperature profile. SINDA program options offer user variety of methods for solution of thermal analog modes presented in network format.

  5. A neutron activation analyzer

    International Nuclear Information System (INIS)

    Westphal, G.P.; Lemmel, H.; Grass, F.; De Regge, P.P.; Burns, K.; Markowicz, A.

    2005-01-01

    Dubbed 'Analyzer' because of its simplicity, a neutron activation analysis facility for short-lived isomeric transitions is based on a low-cost rabbit system and an adaptive digital filter which are controlled by a software performing irradiation control, loss-free gamma-spectrometry, spectra evaluation, nuclide identification and calculation of concentrations in a fully automatic flow of operations. Designed for TRIGA reactors and constructed from inexpensive plastic tubing and an aluminum in-core part, the rabbit system features samples of 5 ml and 10 ml with sample separation at 150 ms and 200 ms transport time or 25 ml samples without separation at a transport time of 300 ms. By automatically adapting shaping times to pulse intervals the preloaded digital filter gives best throughput at best resolution up to input counting rates of 10 6 cps. Loss-free counting enables quantitative correction of counting losses of up to 99%. As a test of system reproducibility in sample separation geometry, K, Cl, Mn, Mg, Ca, Sc, and V have been determined in various reference materials at excellent agreement with consensus values. (author)

  6. Downhole Fluid Analyzer Development

    Energy Technology Data Exchange (ETDEWEB)

    Bill Turner

    2006-11-28

    A novel fiber optic downhole fluid analyzer has been developed for operation in production wells. This device will allow real-time determination of the oil, gas and water fractions of fluids from different zones in a multizone or multilateral completion environment. The device uses near infrared spectroscopy and induced fluorescence measurement to unambiguously determine the oil, water and gas concentrations at all but the highest water cuts. The only downhole components of the system are the fiber optic cable and windows. All of the active components--light sources, sensors, detection electronics and software--will be located at the surface, and will be able to operate multiple downhole probes. Laboratory testing has demonstrated that the sensor can accurately determine oil, water and gas fractions with a less than 5 percent standard error. Once installed in an intelligent completion, this sensor will give the operating company timely information about the fluids arising from various zones or multilaterals in a complex completion pattern, allowing informed decisions to be made on controlling production. The research and development tasks are discussed along with a market analysis.

  7. Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, Seungwon; Pan, Lei; Zhai, Chengxing; Tang, Benyang; Kubar, Terry; Zhang, Zia; Wang, Wei

    2015-01-01

    The comprehensive and innovative evaluation of climate models with newly available global observations is critically needed for the improvement of climate model current-state representation and future-state predictability. A climate model diagnostic evaluation process requires physics-based multi-variable analyses that typically involve large-volume and heterogeneous datasets, making them both computation- and data-intensive. With an exploratory nature of climate data analyses and an explosive growth of datasets and service tools, scientists are struggling to keep track of their datasets, tools, and execution/study history, let alone sharing them with others. In response, we have developed a cloud-enabled, provenance-supported, web-service system called Climate Model Diagnostic Analyzer (CMDA). CMDA enables the physics-based, multivariable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. At the same time, CMDA provides a crowd-sourcing space where scientists can organize their work efficiently and share their work with others. CMDA is empowered by many current state-of-the-art software packages in web service, provenance, and semantic search.

  8. Percolation of interdependent network of networks

    International Nuclear Information System (INIS)

    Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

    2015-01-01

    Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

  9. Mining social networks and security informatics

    CERN Document Server

    Özyer, Tansel; Rokne, Jon; Khoury, Suheil

    2013-01-01

    Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for soci

  10. Multichannel analyzer embedded in FPGA

    International Nuclear Information System (INIS)

    Garcia D, A.; Hernandez D, V. M.; Vega C, H. R.; Ordaz G, O. O.; Bravo M, I.

    2017-10-01

    Ionizing radiation has different applications, so it is a very significant and useful tool, which in turn can be dangerous for living beings if they are exposed to uncontrolled doses. However, due to its characteristics, it cannot be perceived by any of the senses of the human being, so that in order to know the presence of it, radiation detectors and additional devices are required to quantify and classify it. A multichannel analyzer is responsible for separating the different pulse heights that are generated in the detectors, in a certain number of channels; according to the number of bits of the analog to digital converter. The objective of the work was to design and implement a multichannel analyzer and its associated virtual instrument, for nuclear spectrometry. The components of the multichannel analyzer were created in VHDL hardware description language and packaged in the Xilinx Vivado design suite, making use of resources such as the ARM processing core that the System on Chip Zynq contains and the virtual instrument was developed on the LabView programming graphics platform. The first phase was to design the hardware architecture to be embedded in the FPGA and for the internal control of the multichannel analyzer the application was generated for the ARM processor in C language. For the second phase, the virtual instrument was developed for the management, control and visualization of the results. The data obtained as a result of the development of the system were observed graphically in a histogram showing the spectrum measured. The design of the multichannel analyzer embedded in FPGA was tested with two different radiation detection systems (hyper-pure germanium and scintillation) which allowed determining that the spectra obtained are similar in comparison with the commercial multichannel analyzers. (Author)

  11. Digital Microfluidics Sample Analyzer

    Science.gov (United States)

    Pollack, Michael G.; Srinivasan, Vijay; Eckhardt, Allen; Paik, Philip Y.; Sudarsan, Arjun; Shenderov, Alex; Hua, Zhishan; Pamula, Vamsee K.

    2010-01-01

    Three innovations address the needs of the medical world with regard to microfluidic manipulation and testing of physiological samples in ways that can benefit point-of-care needs for patients such as premature infants, for which drawing of blood for continuous tests can be life-threatening in their own right, and for expedited results. A chip with sample injection elements, reservoirs (and waste), droplet formation structures, fluidic pathways, mixing areas, and optical detection sites, was fabricated to test the various components of the microfluidic platform, both individually and in integrated fashion. The droplet control system permits a user to control droplet microactuator system functions, such as droplet operations and detector operations. Also, the programming system allows a user to develop software routines for controlling droplet microactuator system functions, such as droplet operations and detector operations. A chip is incorporated into the system with a controller, a detector, input and output devices, and software. A novel filler fluid formulation is used for the transport of droplets with high protein concentrations. Novel assemblies for detection of photons from an on-chip droplet are present, as well as novel systems for conducting various assays, such as immunoassays and PCR (polymerase chain reaction). The lab-on-a-chip (a.k.a., lab-on-a-printed-circuit board) processes physiological samples and comprises a system for automated, multi-analyte measurements using sub-microliter samples of human serum. The invention also relates to a diagnostic chip and system including the chip that performs many of the routine operations of a central labbased chemistry analyzer, integrating, for example, colorimetric assays (e.g., for proteins), chemiluminescence/fluorescence assays (e.g., for enzymes, electrolytes, and gases), and/or conductometric assays (e.g., for hematocrit on plasma and whole blood) on a single chip platform.

  12. Gossip algorithms in quantum networks

    International Nuclear Information System (INIS)

    Siomau, Michael

    2017-01-01

    Gossip algorithms is a common term to describe protocols for unreliable information dissemination in natural networks, which are not optimally designed for efficient communication between network entities. We consider application of gossip algorithms to quantum networks and show that any quantum network can be updated to optimal configuration with local operations and classical communication. This allows to speed-up – in the best case exponentially – the quantum information dissemination. Irrespective of the initial configuration of the quantum network, the update requiters at most polynomial number of local operations and classical communication. - Highlights: • We analyze the performance of gossip algorithms in quantum networks. • Local operations and classical communication (LOCC) can speed the performance up. • The speed-up is exponential in the best case; the number of LOCC is polynomial.

  13. Gossip algorithms in quantum networks

    Energy Technology Data Exchange (ETDEWEB)

    Siomau, Michael, E-mail: siomau@nld.ds.mpg.de [Physics Department, Jazan University, P.O. Box 114, 45142 Jazan (Saudi Arabia); Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen (Germany)

    2017-01-23

    Gossip algorithms is a common term to describe protocols for unreliable information dissemination in natural networks, which are not optimally designed for efficient communication between network entities. We consider application of gossip algorithms to quantum networks and show that any quantum network can be updated to optimal configuration with local operations and classical communication. This allows to speed-up – in the best case exponentially – the quantum information dissemination. Irrespective of the initial configuration of the quantum network, the update requiters at most polynomial number of local operations and classical communication. - Highlights: • We analyze the performance of gossip algorithms in quantum networks. • Local operations and classical communication (LOCC) can speed the performance up. • The speed-up is exponential in the best case; the number of LOCC is polynomial.

  14. Robot task space analyzer

    International Nuclear Information System (INIS)

    Hamel, W.R.; Osborn, J.

    1997-01-01

    Many nuclear projects such as environmental restoration and waste management challenges involve radiation or other hazards that will necessitate the use of remote operations that protect human workers from dangerous exposures. Remote work is far more costly to execute than what workers could accomplish directly with conventional tools and practices because task operations are slow and tedious due to difficulties of remote manipulation and viewing. Decades of experience within the nuclear remote operations community show that remote tasks may take hundreds of times longer than hands-on work; even with state-of-the-art force- reflecting manipulators and television viewing, remote task performance execution is five to ten times slower than equivalent direct contact work. Thus the requirement to work remotely is a major cost driver in many projects. Modest improvements in the work efficiency of remote systems can have high payoffs by reducing the completion time of projects. Additional benefits will accrue from improved work quality and enhanced safety

  15. Design of multi-channel amplitude analyzer base on LonWorks

    International Nuclear Information System (INIS)

    Zhang Ying; Zhao Lihong; Chen Aihua

    2008-01-01

    The paper introduces the multi-channel analyzer which adopts LonWorks technology. The system detects the pulse peak by hardware circuits and controls data acquisition and network communication by Micro Controller and Unit and Neuron chip. SCM is programmed by Keil C51; the communication between SCM and nerve cell is realized by Neron C language, and the computer program is written by VB language. Test results show that this analyzer is with fast conversion speed and low power consumption. (authors)

  16. Grid and Data Analyzing and Security

    Directory of Open Access Journals (Sweden)

    Fatemeh SHOKRI

    2012-12-01

    Full Text Available This paper examines the importance of secure structures in the process of analyzing and distributing information with aid of Grid-based technologies. The advent of distributed network has provided many practical opportunities for detecting and recording the time of events, and made efforts to identify the events and solve problems of storing information such as being up-to-date and documented. In this regard, the data distribution systems in a network environment should be accurate. As a consequence, a series of continuous and updated data must be at hand. In this case, Grid is the best answer to use data and resource of organizations by common processing.

  17. Surname complex network for Brazil and Portugal

    Science.gov (United States)

    Ferreira, G. D.; Viswanathan, G. M.; da Silva, L. R.; Herrmann, H. J.

    2018-06-01

    We present a study of social networks based on the analysis of Brazilian and Portuguese family names (surnames). We construct networks whose nodes are names of families and whose edges represent parental relations between two families. From these networks we extract the connectivity distribution, clustering coefficient, shortest path and centrality. We find that the connectivity distribution follows an approximate power law. We associate the number of hubs, centrality and entropy to the degree of miscegenation in the societies in both countries. Our results show that Portuguese society has a higher miscegenation degree than Brazilian society. All networks analyzed lead to approximate inverse square power laws in the degree distribution. We conclude that the thermodynamic limit is reached for small networks (3 or 4 thousand nodes). The assortative mixing of all networks is negative, showing that the more connected vertices are connected to vertices with lower connectivity. Finally, the network of surnames presents some small world characteristics.

  18. Measuring the evolutionary rewiring of biological networks.

    Directory of Open Access Journals (Sweden)

    Chong Shou

    Full Text Available We have accumulated a large amount of biological network data and expect even more to come. Soon, we anticipate being able to compare many different biological networks as we commonly do for molecular sequences. It has long been believed that many of these networks change, or "rewire", at different rates. It is therefore important to develop a framework to quantify the differences between networks in a unified fashion. We developed such a formalism based on analogy to simple models of sequence evolution, and used it to conduct a systematic study of network rewiring on all the currently available biological networks. We found that, similar to sequences, biological networks show a decreased rate of change at large time divergences, because of saturation in potential substitutions. However, different types of biological networks consistently rewire at different rates. Using comparative genomics and proteomics data, we found a consistent ordering of the rewiring rates: transcription regulatory, phosphorylation regulatory, genetic interaction, miRNA regulatory, protein interaction, and metabolic pathway network, from fast to slow. This ordering was found in all comparisons we did of matched networks between organisms. To gain further intuition on network rewiring, we compared our observed rewirings with those obtained from simulation. We also investigated how readily our formalism could be mapped to other network contexts; in particular, we showed how it could be applied to analyze changes in a range of "commonplace" networks such as family trees, co-authorships and linux-kernel function dependencies.

  19. 浅探网络时代的高职“思想导师制”%Analyze the“Thought Tutorial System”of Network Era in Higher Vocational School

    Institute of Scientific and Technical Information of China (English)

    马莹

    2016-01-01

    In this paper,the characteristics of in view of the present higher vocational education and the characteris-tics of vocational college students of the new mode of Ideological and political education in Higher Vocational Colleges in Network Era—“ideological tutorial system”,by constructing the interactive and harmonious relationship between teachers and students to achieve on the current vocational college students ideological and political education system to supplement and improve,improve the effectiveness of Ideological and political education in higher vocational colleges,promote the deepening of the implementation of the“full education”.%针对现阶段高职教育的特色和高职院校学生的特点,探讨网络时代高职院校思想政治教育新模式———“思想导师制”,通过构建互动、和谐的师生关系,以实现对现阶段高职生思想政治教育体系的补充和完善,提升高职思想政治工作的有效性,推进“全员育人”的深入落实。

  20. PageRank model of opinion formation on Ulam networks

    Science.gov (United States)

    Chakhmakhchyan, L.; Shepelyansky, D.

    2013-12-01

    We consider a PageRank model of opinion formation on Ulam networks, generated by the intermittency map and the typical Chirikov map. The Ulam networks generated by these maps have certain similarities with such scale-free networks as the World Wide Web (WWW), showing an algebraic decay of the PageRank probability. We find that the opinion formation process on Ulam networks has certain similarities but also distinct features comparing to the WWW. We attribute these distinctions to internal differences in network structure of the Ulam and WWW networks. We also analyze the process of opinion formation in the frame of generalized Sznajd model which protects opinion of small communities.

  1. Detecting P2P Botnet in Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Shang-Chiuan Su

    2018-01-01

    Full Text Available Software Defined Network separates the control plane from network equipment and has great advantage in network management as compared with traditional approaches. With this paradigm, the security issues persist to exist and could become even worse because of the flexibility on handling the packets. In this paper we propose an effective framework by integrating SDN and machine learning to detect and categorize P2P network traffics. This work provides experimental evidence showing that our approach can automatically analyze network traffic and flexibly change flow entries in OpenFlow switches through the SDN controller. This can effectively help the network administrators manage related security problems.

  2. Breakdown of interdependent directed networks.

    Science.gov (United States)

    Liu, Xueming; Stanley, H Eugene; Gao, Jianxi

    2016-02-02

    Increasing evidence shows that real-world systems interact with one another via dependency connectivities. Failing connectivities are the mechanism behind the breakdown of interacting complex systems, e.g., blackouts caused by the interdependence of power grids and communication networks. Previous research analyzing the robustness of interdependent networks has been limited to undirected networks. However, most real-world networks are directed, their in-degrees and out-degrees may be correlated, and they are often coupled to one another as interdependent directed networks. To understand the breakdown and robustness of interdependent directed networks, we develop a theoretical framework based on generating functions and percolation theory. We find that for interdependent Erdős-Rényi networks the directionality within each network increases their vulnerability and exhibits hybrid phase transitions. We also find that the percolation behavior of interdependent directed scale-free networks with and without degree correlations is so complex that two criteria are needed to quantify and compare their robustness: the percolation threshold and the integrated size of the giant component during an entire attack process. Interestingly, we find that the in-degree and out-degree correlations in each network layer increase the robustness of interdependent degree heterogeneous networks that most real networks are, but decrease the robustness of interdependent networks with homogeneous degree distribution and with strong coupling strengths. Moreover, by applying our theoretical analysis to real interdependent international trade networks, we find that the robustness of these real-world systems increases with the in-degree and out-degree correlations, confirming our theoretical analysis.

  3. Dynamic and interacting complex networks

    Science.gov (United States)

    Dickison, Mark E.

    This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

  4. Implementability of two-qubit unitary operations over the butterfly network and the ladder network with free classical communication

    Energy Technology Data Exchange (ETDEWEB)

    Akibue, Seiseki [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo (Japan); Murao, Mio [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan and NanoQuine, The University of Tokyo, Tokyo (Japan)

    2014-12-04

    We investigate distributed implementation of two-qubit unitary operations over two primitive networks, the butterfly network and the ladder network, as a first step to apply network coding for quantum computation. By classifying two-qubit unitary operations in terms of the Kraus-Cirac number, the number of non-zero parameters describing the global part of two-qubit unitary operations, we analyze which class of two-qubit unitary operations is implementable over these networks with free classical communication. For the butterfly network, we show that two classes of two-qubit unitary operations, which contain all Clifford, controlled-unitary and matchgate operations, are implementable over the network. For the ladder network, we show that two-qubit unitary operations are implementable over the network if and only if their Kraus-Cirac number do not exceed the number of the bridges of the ladder.

  5. Implementability of two-qubit unitary operations over the butterfly network and the ladder network with free classical communication

    International Nuclear Information System (INIS)

    Akibue, Seiseki; Murao, Mio

    2014-01-01

    We investigate distributed implementation of two-qubit unitary operations over two primitive networks, the butterfly network and the ladder network, as a first step to apply network coding for quantum computation. By classifying two-qubit unitary operations in terms of the Kraus-Cirac number, the number of non-zero parameters describing the global part of two-qubit unitary operations, we analyze which class of two-qubit unitary operations is implementable over these networks with free classical communication. For the butterfly network, we show that two classes of two-qubit unitary operations, which contain all Clifford, controlled-unitary and matchgate operations, are implementable over the network. For the ladder network, we show that two-qubit unitary operations are implementable over the network if and only if their Kraus-Cirac number do not exceed the number of the bridges of the ladder

  6. Competing intramolecular N-H⋯O=C hydrogen bonds and extended intermolecular network in 1-(4-chlorobenzoyl)-3-(2-methyl-4-oxopentan-2-yl) thiourea analyzed by experimental and theoretical methods

    Energy Technology Data Exchange (ETDEWEB)

    Saeed, Aamer, E-mail: aamersaeed@yahoo.com [Department of Chemistry, Quaid-I-Azam University, Islamabad 45320 (Pakistan); Khurshid, Asma [Department of Chemistry, Quaid-I-Azam University, Islamabad 45320 (Pakistan); Jasinski, Jerry P. [Department of Chemistry, Keene State College, 229 Main Street Keene, NH 03435-2001 (United States); Pozzi, C. Gustavo; Fantoni, Adolfo C. [Instituto de Física La Plata, Departamento de Física, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 49 y 115, La Plata, Buenos Aires (Argentina); Erben, Mauricio F., E-mail: erben@quimica.unlp.edu.ar [CEQUINOR (UNLP, CONICET-CCT La Plata), Departamento de Química, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, C.C. 962, (1900) La Plata, Buenos Aires (Argentina)

    2014-03-18

    Highlights: • Two distinct N-H⋯O=C intramolecular competing hydrogen bonds are feasible in the title molecule. • Crystal structures and vibrational properties were determined. • The C=O and C=S double bonds of the acyl-thiourea group are mutually oriented in opposite directions. • A strong hyperconjugative lpO1 → σ{sup ∗}(N2-H) remote interaction was detected. • Topological analysis reveals a Cl⋯N interaction playing a relevant role in crystal packing. - Abstract: The synthesis of a novel 1-acyl-thiourea species (C{sub 14}H{sub 17}N{sub 2}O{sub 2}SCl), has been tailored in such a way that two distinct N-H⋯O=C intramolecular competing hydrogen bonds are feasible. The X-ray structure analysis as well as the vibrational (FT-IR and FT-Raman) data reveal that the S conformation is preferred, with the C=O and C=S bonds of the acyl-thiourea group pointing in opposite directions. The preference for the intramolecular N-H⋯O=C hydrogen bond within the -C(O)NHC(S)NH- core is confirmed. The Natural Bond Orbital and the Atom in Molecule approaches demonstrate that a strong hyperconjugative lpO → σ{sup ∗}(N-H) remote interaction between the acyl and the thioamide N-H groups is responsible for the stabilization of the S conformation. Intermolecular interactions have been characterized in the periodic system electron density and the topological analysis reveals the presence of an extended intermolecular network in the crystal, including a Cl⋯N interaction playing a relevant role in crystal packing.

  7. Optical network control plane for multi-domain networking

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva

    This thesis focuses on multi-domain routing for traffice engineering and survivability support in optical transport networks under the Generalized Multi-Protocol Label Switching (GMPLS) control framework. First, different extensions to the Border Gateway Protocol for multi-domain Traffic...... process are not enough for efficient TE in mesh multi-domain networks. Enhancing the protocol with multi-path dissemination capability, combined with the employment of an end-to-end TE metric proves to be a highly efficient solution. Simulation results show good performance characteristics of the proposed...... is not as essential for improved network performance as the length of the provided paths. Second, the issue of multi-domain survivability support is analyzed. An AS-disjoint paths is beneficial not only for resilience support, but also for facilitating adequate network reactions to changes in the network, which...

  8. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago V. V.; Giannitsarou, Chryssi; Johnson, Charles R.

    2016-01-01

    This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00199-016-0992-1 We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and d...

  9. The modularity of pollination networks

    DEFF Research Database (Denmark)

    Olesen, Jens Mogens; Bascompte, J.; Dupont, Yoko

    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

  10. Multichannel analyzer development in CAMAC

    International Nuclear Information System (INIS)

    Nagy, J.Z.; Zarandy, A.

    1988-01-01

    The data acquisition in TOKAMAK experiments some CAMAC modules have been developed. The modules are the following: 64 K analyzer memory, 32 K analyzer memory, 6-channel pulse peak analyzer memory which contains the 32 K analyzer memory and eight AD-converters

  11. The Aqueduct Global Flood Analyzer

    Science.gov (United States)

    Iceland, Charles

    2015-04-01

    As population growth and economic growth take place, and as climate change accelerates, many regions across the globe are finding themselves increasingly vulnerable to flooding. A recent OECD study of the exposure of the world's large port cities to coastal flooding found that 40 million people were exposed to a 1 in 100 year coastal flood event in 2005, and the total value of exposed assets was about US 3,000 billion, or 5% of global GDP. By the 2070s, those numbers were estimated to increase to 150 million people and US 35,000 billion, or roughly 9% of projected global GDP. Impoverished people in developing countries are particularly at risk because they often live in flood-prone areas and lack the resources to respond. WRI and its Dutch partners - Deltares, IVM-VU University Amsterdam, Utrecht University, and PBL Netherlands Environmental Assessment Agency - are in the initial stages of developing a robust set of river flood and coastal storm surge risk measures that show the extent of flooding under a variety of scenarios (both current and future), together with the projected human and economic impacts of these flood scenarios. These flood risk data and information will be accessible via an online, easy-to-use Aqueduct Global Flood Analyzer. We will also investigate the viability, benefits, and costs of a wide array of flood risk reduction measures that could be implemented in a variety of geographic and socio-economic settings. Together, the activities we propose have the potential for saving hundreds of thousands of lives and strengthening the resiliency and security of many millions more, especially those who are most vulnerable. Mr. Iceland will present Version 1.0 of the Aqueduct Global Flood Analyzer and provide a preview of additional elements of the Analyzer to be released in the coming years.

  12. Open innovation in networks

    DEFF Research Database (Denmark)

    Hu, Yimei

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

  13. Spectral properties of Google matrix of Wikipedia and other networks

    Science.gov (United States)

    Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

    2013-05-01

    We study the properties of eigenvalues and eigenvectors of the Google matrix of the Wikipedia articles hyperlink network and other real networks. With the help of the Arnoldi method, we analyze the distribution of eigenvalues in the complex plane and show that eigenstates with significant eigenvalue modulus are located on well defined network communities. We also show that the correlator between PageRank and CheiRank vectors distinguishes different organizations of information flow on BBC and Le Monde web sites.

  14. Basketball Teams as Strategic Networks

    Science.gov (United States)

    Fewell, Jennifer H.; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S.

    2012-01-01

    We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness. PMID:23139744

  15. Basketball teams as strategic networks.

    Science.gov (United States)

    Fewell, Jennifer H; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S

    2012-01-01

    We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as "uphill/downhill" flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.

  16. Basketball teams as strategic networks.

    Directory of Open Access Journals (Sweden)

    Jennifer H Fewell

    Full Text Available We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1 whether teams consistently moved the ball towards their shooting specialists, measured as "uphill/downhill" flux, and (2 whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players and network entropy (unpredictability of ball movement had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.

  17. Integrating Networking into ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2018-01-01

    Networking is foundational to the ATLAS distributed infrastructure and there are many ongoing activities related to networking both within and outside of ATLAS. We will report on the progress in a number of areas exploring ATLAS's use of networking and our ability to monitor the network, analyze metrics from the network, and tune and optimize application and end-host parameters to make the most effective use of the network. Specific topics will include work on Open vSwitch for production systems, network analytics, FTS testing and tuning, and network problem alerting and alarming.

  18. Entropy of dynamical social networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

    2012-02-01

    Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

  19. Export policies for multi-domain WDM networks

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva; Ruepp, Sarah Renée

    2010-01-01

    We analyze the performance of six export policies for a multi-domain routing protocol in WDM networks. We show that providing many AS-disjoint paths for survivability and load-balancing does not necessarily guarantee the lowest connection blocking......We analyze the performance of six export policies for a multi-domain routing protocol in WDM networks. We show that providing many AS-disjoint paths for survivability and load-balancing does not necessarily guarantee the lowest connection blocking...

  20. Effects of network node consolidation in optical access and aggregation networks on costs and power consumption

    Science.gov (United States)

    Lange, Christoph; Hülsermann, Ralf; Kosiankowski, Dirk; Geilhardt, Frank; Gladisch, Andreas

    2010-01-01

    The increasing demand for higher bit rates in access networks requires fiber deployment closer to the subscriber resulting in fiber-to-the-home (FTTH) access networks. Besides higher access bit rates optical access network infrastructure and related technologies enable the network operator to establish larger service areas resulting in a simplified network structure with a lower number of network nodes. By changing the network structure network operators want to benefit from a changed network cost structure by decreasing in short and mid term the upfront investments for network equipment due to concentration effects as well as by reducing the energy costs due to a higher energy efficiency of large network sites housing a high amount of network equipment. In long term also savings in operational expenditures (OpEx) due to the closing of central office (CO) sites are expected. In this paper different architectures for optical access networks basing on state-of-the-art technology are analyzed with respect to network installation costs and power consumption in the context of access node consolidation. Network planning and dimensioning results are calculated for a realistic network scenario of Germany. All node consolidation scenarios are compared against a gigabit capable passive optical network (GPON) based FTTH access network operated from the conventional CO sites. The results show that a moderate reduction of the number of access nodes may be beneficial since in that case the capital expenditures (CapEx) do not rise extraordinarily and savings in OpEx related to the access nodes are expected. The total power consumption does not change significantly with decreasing number of access nodes but clustering effects enable a more energyefficient network operation and optimized power purchase order quantities leading to benefits in energy costs.

  1. Hyperbolicity measures democracy in real-world networks

    Science.gov (United States)

    Borassi, Michele; Chessa, Alessandro; Caldarelli, Guido

    2015-09-01

    In this work, we analyze the hyperbolicity of real-world networks, a geometric quantity that measures if a space is negatively curved. We provide two improvements in our understanding of this quantity: first of all, in our interpretation, a hyperbolic network is "aristocratic", since few elements "connect" the system, while a non-hyperbolic network has a more "democratic" structure with a larger number of crucial elements. The second contribution is the introduction of the average hyperbolicity of the neighbors of a given node. Through this definition, we outline an "influence area" for the vertices in the graph. We show that in real networks the influence area of the highest degree vertex is small in what we define "local" networks (i.e., social or peer-to-peer networks), and large in "global" networks (i.e., power grid, metabolic networks, or autonomous system networks).

  2. Design principles in biological networks

    Science.gov (United States)

    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

  3. A tandem parallel plate analyzer

    International Nuclear Information System (INIS)

    Hamada, Y.; Fujisawa, A.; Iguchi, H.; Nishizawa, A.; Kawasumi, Y.

    1996-11-01

    By a new modification of a parallel plate analyzer the second-order focus is obtained in an arbitrary injection angle. This kind of an analyzer with a small injection angle will have an advantage of small operational voltage, compared to the Proca and Green analyzer where the injection angle is 30 degrees. Thus, the newly proposed analyzer will be very useful for the precise energy measurement of high energy particles in MeV range. (author)

  4. NASA GIBS Use in Live Planetarium Shows

    Science.gov (United States)

    Emmart, C. B.

    2015-12-01

    The American Museum of Natural History's Hayden Planetarium was rebuilt in year 2000 as an immersive theater for scientific data visualization to show the universe in context to our planet. Specific astrophysical movie productions provide the main daily programming, but interactive control software, developed at AMNH allows immersive presentation within a data aggregation of astronomical catalogs called the Digital Universe 3D Atlas. Since 2006, WMS globe browsing capabilities have been built into a software development collaboration with Sweden's Linkoping University (LiU). The resulting Uniview software, now a product of the company SCISS, is operated by about fifty planetariums around that world with ability to network amongst the sites for global presentations. Public presentation of NASA GIBS has allowed authoritative narratives to be presented within the range of data available in context to other sources such as Science on a Sphere, NASA Earth Observatory and Google Earth KML resources. Specifically, the NOAA supported World Views Network conducted a series of presentations across the US that focused on local ecological issues that could then be expanded in the course of presentation to national and global scales of examination. NASA support of for GIBS resources in an easy access multi scale streaming format like WMS has tremendously enabled particularly facile presentations of global monitoring like never before. Global networking of theaters for distributed presentations broadens out the potential for impact of this medium. Archiving and refinement of these presentations has already begun to inform new types of documentary productions that examine pertinent, global interdependency topics.

  5. Layer 2 and 3 contention resolution and radio-over-fiber in OCDMA PON for transparent optical access in personal networks

    NARCIS (Netherlands)

    Huiszoon, B.; Hartog, F.T.H. den; Larrodé, M.G.; Koonen, A.M.J.

    2008-01-01

    In this paper, we analyze, for the first time, the eminent role of optical transparent networking in personal networks. We show how an optical access network mitigates many issues with respect to connectivity and mobility management. A concrete personal network user-scenario deduces requirements for

  6. Risk Aversion in Game Shows

    DEFF Research Database (Denmark)

    Andersen, Steffen; Harrison, Glenn W.; Lau, Morten I.

    2008-01-01

    We review the use of behavior from television game shows to infer risk attitudes. These shows provide evidence when contestants are making decisions over very large stakes, and in a replicated, structured way. Inferences are generally confounded by the subjective assessment of skill in some games......, and the dynamic nature of the task in most games. We consider the game shows Card Sharks, Jeopardy!, Lingo, and finally Deal Or No Deal. We provide a detailed case study of the analyses of Deal Or No Deal, since it is suitable for inference about risk attitudes and has attracted considerable attention....

  7. Measuring performance at trade shows

    DEFF Research Database (Denmark)

    Hansen, Kåre

    2004-01-01

    Trade shows is an increasingly important marketing activity to many companies, but current measures of trade show performance do not adequately capture dimensions important to exhibitors. Based on the marketing literature's outcome and behavior-based control system taxonomy, a model is built...... that captures a outcome-based sales dimension and four behavior-based dimensions (i.e. information-gathering, relationship building, image building, and motivation activities). A 16-item instrument is developed for assessing exhibitors perceptions of their trade show performance. The paper presents evidence...

  8. Pinning Control Strategy of Multicommunity Structure Networks

    Directory of Open Access Journals (Sweden)

    Chao Ding

    2017-01-01

    Full Text Available In order to investigate the effects of community structure on synchronization, a pinning control strategy is researched in a class of complex networks with community structure in this paper. A feedback control law is designed based on the network community structure information. The stability condition is given and proved by using Lyapunov stability theory. Our research shows that as to community structure networks, there being a threshold hT≈5, when coupling strength bellows this threshold, the stronger coupling strength corresponds to higher synchronizability; vice versa, the stronger coupling strength brings lower synchronizability. In addition the synchronizability of overlapping and nonoverlapping community structure networks was simulated and analyzed; while the nodes were controlled randomly and intensively, the results show that intensive control strategy is better than the random one. The network will reach synchronization easily when the node with largest betweenness was controlled. Furthermore, four difference networks’ synchronizability, such as Barabási-Albert network, Watts-Strogatz network, Erdös-Rényi network, and community structure network, are simulated; the research shows that the community structure network is more easily synchronized under the same control strength.

  9. Tokyo Motor Show 2003; Tokyo Motor Show 2003

    Energy Technology Data Exchange (ETDEWEB)

    Joly, E.

    2004-01-01

    The text which follows present the different techniques exposed during the 37. Tokyo Motor Show. The report points out the great tendencies of developments of the Japanese automobile industry. The hybrid electric-powered vehicles or those equipped with fuel cells have been highlighted by the Japanese manufacturers which allow considerable budgets in the research of less polluting vehicles. The exposed models, although being all different according to the manufacturer, use always a hybrid system: fuel cell/battery. The manufacturers have stressed too on the intelligent systems for navigation and safety as well as on the design and comfort. (O.M.)

  10. Network Affordances

    DEFF Research Database (Denmark)

    Samson, Audrey; Soon, Winnie

    2015-01-01

    This paper examines the notion of network affordance within the context of network art. Building on Gibson's theory (Gibson, 1979) we understand affordance as the perceived and actual parameters of a thing. We expand on Gaver's affordance of predictability (Gaver, 1996) to include ecological...... and computational parameters of unpredictability. We illustrate the notion of unpredictability by considering four specific works that were included in a network art exhibiton, SPEED SHOW [2.0] Hong Kong. The paper discusses how the artworks are contingent upon the parameteric relations (Parisi, 2013......), of the network. We introduce network affordance as a dynamic framework that could articulate the experienced tension arising from the (visible) symbolic representation of computational processes and its hidden occurrences. We base our proposal on the experience of both organising the SPEED SHOW and participating...

  11. Digital Multi Channel Analyzer Enhancement

    International Nuclear Information System (INIS)

    Gonen, E.; Marcus, E.; Wengrowicz, U.; Beck, A.; Nir, J.; Sheinfeld, M.; Broide, A.; Tirosh, D.

    2002-01-01

    A cement analyzing system based on radiation spectroscopy had been developed [1], using novel digital approach for real-time, high-throughput and low-cost Multi Channel Analyzer. The performance of the developed system had a severe problem: the resulted spectrum suffered from lack of smoothness, it was very noisy and full of spikes and surges, therefore it was impossible to use this spectrum for analyzing the cement substance. This paper describes the work carried out to improve the system performance

  12. PM 3655 PHILIPS Logic analyzer

    CERN Multimedia

    A logic analyzer is an electronic instrument that captures and displays multiple signals from a digital system or digital circuit. A logic analyzer may convert the captured data into timing diagrams, protocol decodes, state machine traces, assembly language, or may correlate assembly with source-level software. Logic Analyzers have advanced triggering capabilities, and are useful when a user needs to see the timing relationships between many signals in a digital system.

  13. Network analysis reveals multiscale controls on streamwater chemistry

    Science.gov (United States)

    Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey

    2014-01-01

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...

  14. The Homogeneity Research of Urban Rail Transit Network Performance

    Directory of Open Access Journals (Sweden)

    Wang Fu-jian

    2016-01-01

    Full Text Available Urban Rail Transit is an important part of the public transit, it is necessary to carry out the corresponding network function analysis. Previous studies mainly about network performance analysis of a single city rail transit, lacking of horizontal comparison between the multi-city, it is difficult to find inner unity of different Urban Rail Transit network functions. Taking into account the Urban Rail Transit network is a typical complex networks, so this paper proposes the application of complex network theory to research the homogeneity of Urban Rail Transit network performance. This paper selects rail networks of Beijing, Shanghai, Guangzhou as calculation case, gave them a complex network mapping through the L, P Space method and had a static topological analysis using complex network theory, Network characteristics in three cities were calculated and analyzed form node degree distribution and node connection preference. Finally, this paper studied the network efficiency changes of Urban Rail Transit system under different attack mode. The results showed that, although rail transport network size, model construction and construction planning of the three cities are different, but their network performance in many aspects showed high homogeneity.

  15. Analyzing traffic layout using dynamic social network analysis.

    Science.gov (United States)

    2014-07-12

    it is essential to build, maintain, and use our transportation systems in a manner that meets our current : needs while addressing the social and economic needs of future generations. In todays world, : transportation congestion causes serious neg...

  16. Analyzing Divisia Rules Extracted from a Feedforward Neural Network

    National Research Council Canada - National Science Library

    Schmidt, Vincent A; Binner, Jane M

    2006-01-01

    This paper introduces a mechanism for generating a series of rules that characterize the money-price relationship, defined as the relationship between the rate of growth of the money supply and inflation...

  17. Analyzing GAIAN Database (GaianDB) on a Tactical Network

    Science.gov (United States)

    2015-11-30

    databases, and other files, and exposes them as 1 unified structured query language ( SQL )-compliant data source. This “store locally query anywhere...UDP server that could communicate directly with the CSRs via the CSR’s serial port. However, GAIAN has over 800,000 lines of source code. It...management, by which all would have to be modified to communicate with our server and maintain utility. Not only did we quickly realize that this

  18. ANALYZING SOCIAL NETWORKS FROM THE PERSPECTIVE OF MARKETING DECISIONS

    OpenAIRE

    Logica BANICA; Victoria-Mihaela BRINZEA; Magdalena RADULESCU

    2015-01-01

    Nowadays, the Web became more than a space for product presentation, but also a capitalization market (e-commerce) and an efficient way to know the customer preferences and to meet their requirements. Large companies have the financial potential to use various marketing strategies and, in particular, digital-marketing. Instead, small businesses are looking for lower cost or no cost methods (also called guerrilla marketing). A small company can compete with a large company by approaching a par...

  19. Charge Analyzer Responsive Local Oscillations

    Science.gov (United States)

    Krause, Linda Habash; Thornton, Gary

    2015-01-01

    The first transatlantic radio transmission, demonstrated by Marconi in December of 1901, revealed the essential role of the ionosphere for radio communications. This ionized layer of the upper atmosphere controls the amount of radio power transmitted through, reflected off of, and absorbed by the atmospheric medium. Low-frequency radio signals can propagate long distances around the globe via repeated reflections off of the ionosphere and the Earth's surface. Higher frequency radio signals can punch through the ionosphere to be received at orbiting satellites. However, any turbulence in the ionosphere can distort these signals, compromising the performance or even availability of space-based communication and navigations systems. The physics associated with this distortion effect is analogous to the situation when underwater images are distorted by convecting air bubbles. In fact, these ionospheric features are often called 'plasma bubbles' since they exhibit some of the similar behavior as underwater air bubbles. These events, instigated by solar and geomagnetic storms, can cause communication and navigation outages that last for hours. To help understand and predict these outages, a world-wide community of space scientists and technologists are devoted to researching this topic. One aspect of this research is to develop instruments capable of measuring the ionospheric plasma bubbles. Figure 1 shows a photo of the Charge Analyzer Responsive to Local Oscillations (CARLO), a new instrument under development at NASA Marshall Space Flight Center (MSFC). It is a frequency-domain ion spectrum analyzer designed to measure the distributions of ionospheric turbulence from 1 Hz to 10 kHz (i.e., spatial scales from a few kilometers down to a few centimeters). This frequency range is important since it focuses on turbulence scales that affect VHF/UHF satellite communications, GPS systems, and over-the-horizon radar systems. CARLO is based on the flight-proven Plasma Local

  20. Reality show: um paradoxo nietzschiano

    Directory of Open Access Journals (Sweden)

    Ilana Feldman

    2011-01-01

    Full Text Available

    O fenômeno dos reality shows - e a subseqüente relação entre imagem e verdade - assenta-se sobre uma série de paradoxos. Tais paradoxos podem ser compreendidos à luz do pensamento do filósofo alemão Friedrich Nietzsche, que, através dos usos de formulações paradoxais, concebia a realidade como um mundo de pura aparência e a verdade como um acréscimo ficcional, como um efeito. A ficção é então tomada, na filosofia de Nietzsche, não em seu aspecto falsificante e desrealizador - como sempre pleiteou nossa tradição metafísica -, mas como condição necessária para que certa espécie de invenção possa operar como verdade. Sendo assim, a própria expressão reality show, através de sua formulação paradoxal, engendra explicitamente um mundo de pura aparência, em que a verdade, a parte reality da proposição, é da ordem do suplemento, daquilo que se acrescenta ficcionalmente - como um adjetivo - a show. O ornamento, nesse caso, passa a ocupar o lugar central, apontando para o efeito produzido: o efeito-de-verdade. Seguindo, então, o pensamento nietzschiano e sua atualização na contemporaneidade, investigaremos de que forma os televisivos “shows de realidade” operam paradoxalmente, em consonância com nossas paradoxais práticas culturais.

  1. A random network based, node attraction facilitated network evolution method

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-03-01

    Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

  2. Multichannel analyzer type CMA-3

    International Nuclear Information System (INIS)

    Czermak, A.; Jablonski, J.; Ostrowicz, A.

    1978-01-01

    Multichannel analyzer CMA-3 is designed for two-parametric analysis with operator controlled logical windows. It is implemented in CAMAC standard. A single crate contains all required modules and is controlled by the PDP-11/10 minicomputer. Configuration of CMA-3 is shown. CMA-3 is the next version of the multichannel analyzer described in report No 958/E-8. (author)

  3. Analyzing data files in SWAN

    CERN Document Server

    Gajam, Niharika

    2016-01-01

    Traditionally analyzing data happens via batch-processing and interactive work on the terminal. The project aims to provide another way of analyzing data files: A cloud-based approach. It aims to make it a productive and interactive environment through the combination of FCC and SWAN software.

  4. Statistical mechanics of the international trade network.

    Science.gov (United States)

    Fronczak, Agata; Fronczak, Piotr

    2012-05-01

    Analyzing real data on international trade covering the time interval 1950-2000, we show that in each year over the analyzed period the network is a typical representative of the ensemble of maximally random weighted networks, whose directed connections (bilateral trade volumes) are only characterized by the product of the trading countries' GDPs. It means that time evolution of this network may be considered as a continuous sequence of equilibrium states, i.e., a quasistatic process. This, in turn, allows one to apply the linear response theory to make (and also verify) simple predictions about the network. In particular, we show that bilateral trade fulfills a fluctuation-response theorem, which states that the average relative change in imports (exports) between two countries is a sum of the relative changes in their GDPs. Yearly changes in trade volumes prove that the theorem is valid.

  5. Nestedness of ectoparasite-vertebrate host networks.

    Directory of Open Access Journals (Sweden)

    Sean P Graham

    2009-11-01

    Full Text Available Determining the structure of ectoparasite-host networks will enable disease ecologists to better understand and predict the spread of vector-borne diseases. If these networks have consistent properties, then studying the structure of well-understood networks could lead to extrapolation of these properties to others, including those that support emerging pathogens. Borrowing a quantitative measure of network structure from studies of mutualistic relationships between plants and their pollinators, we analyzed 29 ectoparasite-vertebrate host networks--including three derived from molecular bloodmeal analysis of mosquito feeding patterns--using measures of nestedness to identify non-random interactions among species. We found significant nestedness in ectoparasite-vertebrate host lists for habitats ranging from tropical rainforests to polar environments. These networks showed non-random patterns of nesting, and did not differ significantly from published estimates of nestedness from mutualistic networks. Mutualistic and antagonistic networks appear to be organized similarly, with generalized ectoparasites interacting with hosts that attract many ectoparasites and more specialized ectoparasites usually interacting with these same "generalized" hosts. This finding has implications for understanding the network dynamics of vector-born pathogens. We suggest that nestedness (rather than random ectoparasite-host associations can allow rapid transfer of pathogens throughout a network, and expand upon such concepts as the dilution effect, bridge vectors, and host switching in the context of nested ectoparasite-vertebrate host networks.

  6. Extending the Lifetime of Sensor Networks through Adaptive Reclustering

    Directory of Open Access Journals (Sweden)

    Gianluigi Ferrari

    2007-06-01

    Full Text Available We analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality-of-service (QoS constraint, given by the maximum tolerable probability of decision error at the access point (AP. In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal for the lifetime of a single sensor. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. We also derive an analytical framework for the computation of the network lifetime and the penalty, in terms of time delay and energy consumption, brought by adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime. Moreover, the observation of the phenomenon should be frequent in order to limit the penalties associated with the reclustering procedure. We also apply the developed framework to analyze the energy consumption associated with the proposed reclustering protocol, obtaining results in good agreement with the performance of realistic wireless sensor networks. Finally, we present simulation results on the lifetime of IEEE 802.15.4 wireless sensor networks, which enrich the proposed analytical framework and show that typical networking performance metrics (such as throughput and delay are influenced by the sensor network lifetime.

  7. Extending the Lifetime of Sensor Networks through Adaptive Reclustering

    Directory of Open Access Journals (Sweden)

    Ferrari Gianluigi

    2007-01-01

    Full Text Available We analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality-of-service (QoS constraint, given by the maximum tolerable probability of decision error at the access point (AP. In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal for the lifetime of a single sensor. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. We also derive an analytical framework for the computation of the network lifetime and the penalty, in terms of time delay and energy consumption, brought by adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime. Moreover, the observation of the phenomenon should be frequent in order to limit the penalties associated with the reclustering procedure. We also apply the developed framework to analyze the energy consumption associated with the proposed reclustering protocol, obtaining results in good agreement with the performance of realistic wireless sensor networks. Finally, we present simulation results on the lifetime of IEEE 802.15.4 wireless sensor networks, which enrich the proposed analytical framework and show that typical networking performance metrics (such as throughput and delay are influenced by the sensor network lifetime.

  8. Temporal networks

    Science.gov (United States)

    Holme, Petter; Saramäki, Jari

    2012-10-01

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

  9. Ecological network analysis: network construction

    NARCIS (Netherlands)

    Fath, B.D.; Scharler, U.M.; Ulanowicz, R.E.; Hannon, B.

    2007-01-01

    Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but

  10. Robustness of airline alliance route networks

    Science.gov (United States)

    Lordan, Oriol; Sallan, Jose M.; Simo, Pep; Gonzalez-Prieto, David

    2015-05-01

    The aim of this study is to analyze the robustness of the three major airline alliances' (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure - the inverted adaptive strategy - is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion - inverted efficiency - shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results.

  11. [Automated analyzer of enzyme immunoassay].

    Science.gov (United States)

    Osawa, S

    1995-09-01

    Automated analyzers for enzyme immunoassay can be classified by several points of view: the kind of labeled antibodies or enzymes, detection methods, the number of tests per unit time, analytical time and speed per run. In practice, it is important for us consider the several points such as detection limits, the number of tests per unit time, analytical range, and precision. Most of the automated analyzers on the market can randomly access and measure samples. I will describe the recent advance of automated analyzers reviewing their labeling antibodies and enzymes, the detection methods, the number of test per unit time and analytical time and speed per test.

  12. Network-based functional enrichment

    Directory of Open Access Journals (Sweden)

    Poirel Christopher L

    2011-11-01

    Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are

  13. Energy Efficient Evolution of Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Mogensen, Preben

    2011-01-01

    options for how to evolve their networks, allowing them to carry the expected increase in traffic. The best solution is generally selected based on two main criteria, performance and cost. However, pushed by a variety of environmental and energy challenges, MNOs are now also showing interest...... in understanding the impact that different options can have on the energy consumption of their networks. This paper investigates the possible energy gains of evolving a mobile network through a joint pico deployment and macro upgrade solution over a period of 8 years. Besides the network energy consumption, energy...... efficiency in Mbps/kWh is also analyzed. Furthermore, a cost analysis is carried out, to give a more complete picture of the different options being considered. Focusing on the last year of the evolution analysis, results show that deploying more pico sites reduces the energy consumption of the network...

  14. An Analysis of Construction Accident Factors Based on Bayesian Network

    OpenAIRE

    Yunsheng Zhao; Jinyong Pei

    2013-01-01

    In this study, we have an analysis of construction accident factors based on bayesian network. Firstly, accidents cases are analyzed to build Fault Tree method, which is available to find all the factors causing the accidents, then qualitatively and quantitatively analyzes the factors with Bayesian network method, finally determines the safety management program to guide the safety operations. The results of this study show that bad condition of geological environment has the largest posterio...

  15. DEMorphy, German Language Morphological Analyzer

    OpenAIRE

    Altinok, Duygu

    2018-01-01

    DEMorphy is a morphological analyzer for German. It is built onto large, compactified lexicons from German Morphological Dictionary. A guesser based on German declension suffixed is also provided. For German, we provided a state-of-art morphological analyzer. DEMorphy is implemented in Python with ease of usability and accompanying documentation. The package is suitable for both academic and commercial purposes wit a permissive licence.

  16. A Categorization of Dynamic Analyzers

    Science.gov (United States)

    Lujan, Michelle R.

    1997-01-01

    Program analysis techniques and tools are essential to the development process because of the support they provide in detecting errors and deficiencies at different phases of development. The types of information rendered through analysis includes the following: statistical measurements of code, type checks, dataflow analysis, consistency checks, test data,verification of code, and debugging information. Analyzers can be broken into two major categories: dynamic and static. Static analyzers examine programs with respect to syntax errors and structural properties., This includes gathering statistical information on program content, such as the number of lines of executable code, source lines. and cyclomatic complexity. In addition, static analyzers provide the ability to check for the consistency of programs with respect to variables. Dynamic analyzers in contrast are dependent on input and the execution of a program providing the ability to find errors that cannot be detected through the use of static analysis alone. Dynamic analysis provides information on the behavior of a program rather than on the syntax. Both types of analysis detect errors in a program, but dynamic analyzers accomplish this through run-time behavior. This paper focuses on the following broad classification of dynamic analyzers: 1) Metrics; 2) Models; and 3) Monitors. Metrics are those analyzers that provide measurement. The next category, models, captures those analyzers that present the state of the program to the user at specified points in time. The last category, monitors, checks specified code based on some criteria. The paper discusses each classification and the techniques that are included under them. In addition, the role of each technique in the software life cycle is discussed. Familiarization with the tools that measure, model and monitor programs provides a framework for understanding the program's dynamic behavior from different, perspectives through analysis of the input

  17. CSTT Update: Fuel Quality Analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Brosha, Eric L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Lujan, Roger W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Mukundan, Rangachary [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rockward, Tommy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Romero, Christopher J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Williams, Stefan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Wilson, Mahlon S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2018-02-06

    These are slides from a presentation. The following topics are covered: project background (scope and approach), developing the prototype (timeline), update on intellectual property, analyzer comparisons (improving humidification, stabilizing the baseline, applying clean-up strategy, impact of ionomer content and improving clean-up), proposed operating mode, considerations for testing in real-world conditions (Gen 1 analyzer electronics development, testing partner identified, field trial planning), summary, and future work.

  18. Bowling alone but tweeting together: the evolution of human interaction in the social networking era

    OpenAIRE

    Antoci, Angelo; Sabatini, Fabio; Sodini, Mauro

    2011-01-01

    The objective of this paper is to theoretically analyze how human interaction may evolve in a world characterized by the explosion of online networking and other Web-mediated ways of building and nurturing relationships. The analysis shows that online networking yields a storage mechanism through which any individual contribution - e.g. a blog post, a comment, or a photo - is stored within a particular network and ready for virtual access by each member who connects to the network. When someo...

  19. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    OpenAIRE

    Chih-Yu Wen; Ying-Chih Chen

    2009-01-01

    This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show t...

  20. Spreading in online social networks: the role of social reinforcement.

    Science.gov (United States)

    Zheng, Muhua; Lü, Linyuan; Zhao, Ming

    2013-07-01

    Some epidemic spreading models are usually applied to analyze the propagation of opinions or news. However, the dynamics of epidemic spreading and information or behavior spreading are essentially different in many aspects. Centola's experiments [Science 329, 1194 (2010)] on behavior spreading in online social networks showed that the spreading is faster and broader in regular networks than in random networks. This result contradicts with the former understanding that random networks are preferable for spreading than regular networks. To describe the spreading in online social networks, a unknown-known-approved-exhausted four-status model was proposed, which emphasizes the effect of social reinforcement and assumes that the redundant signals can improve the probability of approval (i.e., the spreading rate). Performing the model on regular and random networks, it is found that our model can well explain the results of Centola's experiments on behavior spreading and some former studies on information spreading in different parameter space. The effects of average degree and network size on behavior spreading process are further analyzed. The results again show the importance of social reinforcement and are accordant with Centola's anticipation that increasing the network size or decreasing the average degree will enlarge the difference of the density of final approved nodes between regular and random networks. Our work complements the former studies on spreading dynamics, especially the spreading in online social networks where the information usually requires individuals' confirmations before being transmitted to others.

  1. Graphs, Ideal Flow, and the Transportation Network

    OpenAIRE

    Teknomo, Kardi

    2016-01-01

    This lecture discusses the mathematical relationship between network structure and network utilization of transportation network. Network structure means the graph itself. Network utilization represent the aggregation of trajectories of agents in using the network graph. I show the similarity and relationship between the structural pattern of the network and network utilization.

  2. Stable configurations in social networks

    Science.gov (United States)

    Bronski, Jared C.; DeVille, Lee; Ferguson, Timothy; Livesay, Michael

    2018-06-01

    We present and analyze a model of opinion formation on an arbitrary network whose dynamics comes from a global energy function. We study the global and local minimizers of this energy, which we call stable opinion configurations, and describe the global minimizers under certain assumptions on the friendship graph. We show a surprising result that the number of stable configurations is not necessarily monotone in the strength of connection in the social network, i.e. the model sometimes supports more stable configurations when the interpersonal connections are made stronger.

  3. Maximum Parsimony on Phylogenetic networks

    Science.gov (United States)

    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

  4. On-Demand Urine Analyzer

    Science.gov (United States)

    Farquharson, Stuart; Inscore, Frank; Shende, Chetan

    2010-01-01

    A lab-on-a-chip was developed that is capable of extracting biochemical indicators from urine samples and generating their surface-enhanced Raman spectra (SERS) so that the indicators can be quantified and identified. The development was motivated by the need to monitor and assess the effects of extended weightlessness, which include space motion sickness and loss of bone and muscle mass. The results may lead to developments of effective exercise programs and drug regimes that would maintain astronaut health. The analyzer containing the lab-on-a- chip includes materials to extract 3- methylhistidine (a muscle-loss indicator) and Risedronate (a bone-loss indicator) from the urine sample and detect them at the required concentrations using a Raman analyzer. The lab-on- a-chip has both an extractive material and a SERS-active material. The analyzer could be used to monitor the onset of diseases, such as osteoporosis.

  5. Device for analyzing a solution

    International Nuclear Information System (INIS)

    Marchand, Joseph.

    1978-01-01

    The device enables a solution containing an antigen to be analyzed by the radio-immunology technique without coming up against the problems of antigen-antibody complex and free antigen separation. This device, for analyzing a solution containing a biological compound capable of reacting with an antagonistic compound specific of the biological compound, features a tube closed at its bottom end and a component set and immobilized in the bottom of the tube so as to leave a capacity between the bottom of the tube and its lower end. The component has a large developed surface and is so shaped that it allows the solution to be analyzed to have access to the bottom of the tube; it is made of a material having some elastic deformation and able to take up a given quantity of the biological compound or of the antagonistic compound specific of the biological compound [fr

  6. Shapley ratings in brain networks

    Directory of Open Access Journals (Sweden)

    Rolf Kötter

    2007-11-01

    Full Text Available Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale connectivity networks. In this paper, we explore the application of concepts from graph and game theory toward this end. Specifically, we utilize the Shapley value principle, which assigns a rank to players in a coalition based upon their individual contributions to the collective profit of that coalition, to assess the contributions of individual brain structures to the graph derived from the global connectivity network. We report Shapley values for variations of a prefrontal network, as well as for a visual cortical network, which had both been extensively investigated previously. This analysis highlights particular nodes as strong or weak contributors to global connectivity. To understand the nature of their contribution, we compare the Shapley values obtained from these networks and appropriate controls to other previously described nodal measures of structural connectivity. We find a strong correlation between Shapley values and both betweenness centrality and connection density. Moreover, a stepwise multiple linear regression analysis indicates that approximately 79% of the variance in Shapley values obtained from random networks can be explained by betweenness centrality alone. Finally, we investigate the effects of local lesions on the Shapley ratings, showing that the present networks have an immense structural resistance to degradation. We discuss our results highlighting the use of such measures for characterizing the organization and functional role of brain networks.

  7. Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

    Directory of Open Access Journals (Sweden)

    Firoozeh Zare-Farashbandi

    2014-01-01

    Full Text Available Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true.

  8. Information theory perspective on network robustness

    International Nuclear Information System (INIS)

    Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.

    2016-01-01

    A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology. - Highlights: • A novel methodology to measure the robustness of a network to component failure or targeted attacks is proposed. • The use of the network's distance PDF allows a precise analysis. • The method provides a dynamic robustness profile showing the response of the topology to each failure event. • The measure is capable to detect network's critical elements.

  9. Loviisa nuclear power plant analyzer

    International Nuclear Information System (INIS)

    Porkholm, K.; Nurmilaukas, P.; Tiihonen, O.; Haenninen, M.; Puska, E.

    1992-12-01

    The APROS Simulation Environment has been developed since 1986 by Imatran Voima Oy (IVO) and the Technical Research Centre of Finland (VTT). It provides tools, solution algorithms and process components for use in different simulation systems for design, analysis and training purposes. One of its main nuclear applications is the Loviisa Nuclear Power Plant Analyzer (LPA). The Loviisa Plant Analyzer includes all the important plant components both in the primary and in the secondary circuits. In addition, all the main control systems, the protection system and the high voltage electrical systems are included. (orig.)

  10. Simulating activation propagation in social networks using the graph theory

    Directory of Open Access Journals (Sweden)

    František Dařena

    2010-01-01

    Full Text Available The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the network-like structures and to study spreading activation algorithm for reasons of analyzing these structures. The paper presents the process of modeling multidimensional networks by means of directed graphs with several characteristics. The paper also demonstrates using Spreading Activation algorithm as a good method for analyzing multidimensional network with the main focus on recommender systems. The experiments showed that the choice of parameters of the algorithm is crucial, that some kind of constraint should be included and that the algorithm is able to provide a stable environment for simulations with networks.

  11. Networks as integrated in research methodologies in PER

    DEFF Research Database (Denmark)

    Bruun, Jesper

    2016-01-01

    of using networks to create insightful maps of learning discussions. To conclude, I argue that conceptual blending is a powerful framework for constructing "mixed methods" methodologies that may integrate diverse theories and other methodologies with network methodologies.......In recent years a number of researchers within the PER community have started using network analysis as a new methodology to extend our understanding of teaching and learning physics by viewing these as complex systems. In this paper, I give examples of social, cognitive, and action mapping...... networks and how they can be analyzed. In so doing I show how a network can be methodologically described as a set of relations between a set of entities, and how a network can be characterized and analyzed as a mathematical object. Then, as an illustrative example, I discuss a relatively new example...

  12. Network Transformations in Economy

    Directory of Open Access Journals (Sweden)

    Bolychev O.

    2014-09-01

    Full Text Available In the context of ever-increasing market competition, networked interactions play a special role in the economy. The network form of entrepreneurship is increasingly viewed as an effective organizational structure to create a market value embedded in innovative business solutions. The authors study the characteristics of a network as an economic category and emphasize certain similarities between Rus sian and international approaches to identifying interactions of economic systems based on the network principle. The paper focuses on the types of networks widely used in the economy. The authors analyze the transformation of business networks along two lines: from an intra- to an inter-firm network and from an inter-firm to an inter-organizational network. The possible forms of network formation are described depending on the strength of connections and the type of integration. The drivers and reasons behind process of transition from a hierarchical model of the organizational structure to a network type are identified. The authors analyze the advantages of creating inter-firm networks and discuss the features of inter-organizational networks as compares to inter-firm ones. The article summarizes the reasons for and advantages of participation in inter-rganizational networks and identifies the main barriers to the formation of inter-organizational network.

  13. The security analyzer: A security analyzer program written in Prolog

    International Nuclear Information System (INIS)

    Zimmerman, B.D.; Densley, P.J.

    1986-09-01

    The Security Analyzer is a software tool capable of analyzing the effectiveness of a facility's security system. It is written in the Prolog logic programming computer language, using entity-relationship data modeling techniques. The program performs the following functions: (1) provides descriptive, locational and operational status information about intrusion detectors and assessment devices (i.e., ''sensors'' and ''cameras'') upon request; (2) provides for storage and retrieval of maintenance history information for various components of the security system (including intrusion detectors), and allows for changing that information as desired; (3) provides a ''search'' mode, wherein all paths are found from any specified physical location to another specified location which satisfy user chosen ''intruder detection'' probability and elapsed time criteria (i.e., the program finds the ''weakest paths'' from a security point of view). The first two of these functions can be provided fairly easily with a conventional database program; the third function could be provided using Fortran or some similar language, though with substantial difficulty. In the Security Analyzer program, all these functions are provided in a simple and straight-forward manner. This simplicity is possible because the program is written in the symbolic (as opposed to numeric) processing language Prolog, and because the knowledge base is structured according to entity-relationship modeling principles. Also, the use of Prolog and the entity-relationship modeling technique allows the capabilities of the Security analyzer program, both for knowledge base interrogation and for searching-type operations, to be easily expanded in ways that would be very difficult for a numeric and more algorithmically deterministic language such as Fortran to duplicate. 4 refs

  14. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chih-Yu Wen

    2009-05-01

    Full Text Available This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

  15. Dynamic hierarchical sleep scheduling for wireless ad-hoc sensor networks.

    Science.gov (United States)

    Wen, Chih-Yu; Chen, Ying-Chih

    2009-01-01

    This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

  16. Methods of analyzing crude oil

    Science.gov (United States)

    Cooks, Robert Graham; Jjunju, Fred Paul Mark; Li, Anyin; Rogan, Iman S.

    2017-08-15

    The invention generally relates to methods of analyzing crude oil. In certain embodiments, methods of the invention involve obtaining a crude oil sample, and subjecting the crude oil sample to mass spectrometry analysis. In certain embodiments, the method is performed without any sample pre-purification steps.

  17. Therapy Talk: Analyzing Therapeutic Discourse

    Science.gov (United States)

    Leahy, Margaret M.

    2004-01-01

    Therapeutic discourse is the talk-in-interaction that represents the social practice between clinician and client. This article invites speech-language pathologists to apply their knowledge of language to analyzing therapy talk and to learn how talking practices shape clinical roles and identities. A range of qualitative research approaches,…

  18. The Convertible Arbitrage Strategy Analyzed

    NARCIS (Netherlands)

    Loncarski, I.; Ter Horst, J.R.; Veld, C.H.

    2006-01-01

    This paper analyzes convertible bond arbitrage on the Canadian market for the period 1998 to 2004.Convertible bond arbitrage is the combination of a long position in convertible bonds and a short position in the underlying stocks. Convertible arbitrage has been one of the most successful strategies

  19. Analyzing the complexity of nanotechnology

    NARCIS (Netherlands)

    Vries, de M.J.; Schummer, J.; Baird, D.

    2006-01-01

    Nanotechnology is a highly complex technological development due to many uncertainties in our knowledge about it. The Dutch philosopher Herman Dooyeweerd has developed a conceptual framework that can be used (1) to analyze the complexity of technological developments and (2) to see how priorities

  20. Proton-beam energy analyzer

    International Nuclear Information System (INIS)

    Belan, V.N.; Bolotin, L.I.; Kiselev, V.A.; Linnik, A.F.; Uskov, V.V.

    1989-01-01

    The authors describe a magnetic analyzer for measurement of proton-beam energy in the range from 100 keV to 25 MeV. The beam is deflected in a uniform transverse magnetic field and is registered by photographing a scintillation screen. The energy spectrum of the beam is constructed by microphotometry of the photographic film

  1. Malware Propagation and Prevention Model for Time-Varying Community Networks within Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Lan Liu

    2017-01-01

    Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when qshowed that our model is effective, and the results may help to decide the SDN control strategy to defend against network malware and provide a theoretical basis to reduce and prevent network security incidents.

  2. The genre tutorial and social networks terminology

    Directory of Open Access Journals (Sweden)

    Márcio Sales Santiago

    2014-02-01

    Full Text Available This paper analyzes the terminology in the Internet social networks tutorials. A tutorial is a specialized text, full of terms, aiming to teach an individual or group of individuals who need some guidelines to operationalize a computerized tool, such as a social network. It is necessary to identify linguistic and terminological characteristics from the specialized lexical units in this digital genre. Social networks terminology is described and exemplified here. The results show that it is possible to refer to two specific terminologies in tutorials which help to determine the terminological profile of the thematic area, specifically from the point of view of denomination.

  3. Nuclear plant analyzer development at INEL

    International Nuclear Information System (INIS)

    Laats, E.T.; Russell, K.D.; Stewart, H.D.

    1983-01-01

    The Office of Nuclear Regulatory Research of the US Nuclear Regulatory Commission (NRC) has sponsored development of a software-hardware system called the Nuclear Plant Analyzer (NPA). This paper describes the status of the NPA project at the INEL after one year of development. When completed, the NPA will be an integrated network of analytical tools for performing reactor plant analyses. Development of the NPA in FY-1983 progressed along two parallel pathways; namely, conceptual planning and software development. Regarding NPA planning, and extensive effort was conducted to define the function requirements of the NPA, conceptual design, and hardware needs. Regarding software development conducted in FY-1983, all development was aimed toward demonstrating the basic concept and feasibility of the NPA. Nearly all software was developed and resides on the INEL twin Control Data Corporation 176 mainframe computers

  4. Analyzing, Modelling, and Designing Software Ecosystems

    DEFF Research Database (Denmark)

    Manikas, Konstantinos

    as the software development and distribution by a set of actors dependent on each other and the ecosystem. We commence on the hypothesis that the establishment of a software ecosystem on the telemedicine services of Denmark would address these issues and investigate how a software ecosystem can foster...... the development, implementation, and use of telemedicine services. We initially expand the theory of software ecosystems by contributing to the definition and understanding of software ecosystems, providing means of analyzing existing and designing new ecosystems, and defining and measuring the qualities...... of software ecosystems. We use these contributions to design a software ecosystem in the telemedicine services of Denmark with (i) a common platform that supports and promotes development from different actors, (ii) high software interaction, (iii) strong social network of actors, (iv) robust business...

  5. Using networking and communications software in business

    CERN Document Server

    McBride, PK

    2014-01-01

    Using Networking and Communications Software in Business covers the importance of networks in a business firm, the benefits of computer communications within a firm, and the cost-benefit in putting up networks in businesses. The book is divided into six parts. Part I looks into the nature and varieties of networks, networking standards, and network software. Part II discusses the planning of a networked system, which includes analyzing the requirements for the network system, the hardware for the network, and network management. The installation of the network system and the network managemen

  6. Intelligentization: an efficient means to get more from optical networking

    Science.gov (United States)

    Chen, Zhi Yun

    2001-10-01

    Infocom is a term used to describe the merger of Information and Communications and is used to show the radical changes in today's network traffic. The continuous growth of Infocom traffic, especially that of Internet, is driving Infocom networks to expand rapidly. To service providers, the traffic is consuming the bandwidth of their network. Simultaneously, users are complaining too slow, the net never stopped in China. It is the reality faced by both the service providers and equipment vendors. Demands from both the customers and competition in market call for an efficient network infrastructure. What should a Service Provider do? This paper will first analyze the development trends of optical networking and the formation of the concepts of Intelligent Optical Network (ION) and Automatic Switched Optical Network (ASON) as a solution to this problem. Next it will look at the ways to bring intelligence into optical networks, discussing the benefits to service providers by showing some application examples. Finally, it concludes that the development of optical networking has arrived at a point of introducing intelligence into optical networks. The intelligent optical networks and Automatic Switched Optical Networks will immediately bring a wide range of benefit to service providers, equipment vendors, and, of course, the end users.

  7. Weighted Complex Network Analysis of Shanghai Rail Transit System

    Directory of Open Access Journals (Sweden)

    Yingying Xing

    2016-01-01

    Full Text Available With increasing passenger flows and construction scale, Shanghai rail transit system (RTS has entered a new era of networking operation. In addition, the structure and properties of the RTS network have great implications for urban traffic planning, design, and management. Thus, it is necessary to acquire their network properties and impacts. In this paper, the Shanghai RTS, as well as passenger flows, will be investigated by using complex network theory. Both the topological and dynamic properties of the RTS network are analyzed and the largest connected cluster is introduced to assess the reliability and robustness of the RTS network. Simulation results show that the distribution of nodes strength exhibits a power-law behavior and Shanghai RTS network shows a strong weighted rich-club effect. This study also indicates that the intentional attacks are more detrimental to the RTS network than to the random weighted network, but the random attacks can cause slightly more damage to the random weighted network than to the RTS network. Our results provide a richer view of complex weighted networks in real world and possibilities of risk analysis and policy decisions for the RTS operation department.

  8. An Efficient Hierarchy Algorithm for Community Detection in Complex Networks

    Directory of Open Access Journals (Sweden)

    Lili Zhang

    2014-01-01

    Full Text Available Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time-varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine-grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too.

  9. Analyzer for gamma cameras diagnostic

    International Nuclear Information System (INIS)

    Oramas Polo, I.; Osorio Deliz, J. F.; Diaz Garcia, A.

    2013-01-01

    This research work was carried out to develop an analyzer for gamma cameras diagnostic. It is composed of an electronic system that includes hardware and software capabilities, and operates from the acquisition of the 4 head position signals of a gamma camera detector. The result is the spectrum of the energy delivered by nuclear radiation coming from the camera detector head. This system includes analog processing of position signals from the camera, digitization and the subsequent processing of the energy signal in a multichannel analyzer, sending data to a computer via a standard USB port and processing of data in a personal computer to obtain the final histogram. The circuits are composed of an analog processing board and a universal kit with micro controller and programmable gate array. (Author)

  10. Methods for Analyzing Social Media

    DEFF Research Database (Denmark)

    Jensen, Jakob Linaa

    2013-01-01

    Social media is becoming increasingly attractive for users. It is a fast way to communicate ideas and a key source of information. It is therefore one of the most influential mediums of communication of our time and an important area for audience research. The growth of social media invites many...... new questions such as: How can we analyze social media? Can we use traditional audience research methods and apply them to online content? Which new research strategies have been developed? Which ethical research issues and controversies do we have to pay attention to? This book focuses on research...... strategies and methods for analyzing social media and will be of interest to researchers and practitioners using social media, as well as those wanting to keep up to date with the subject....

  11. New approach to analyzing vulnerability

    International Nuclear Information System (INIS)

    O'Callaghan, P.B.; Carlson, R.L.; Riedeman, G.W.

    1986-01-01

    The Westinghouse Hanford Company (WHC) has recently completed construction of the Fuel Cycle Plant (FCP) at Richland, Washington. At start-up the facility will fabricate driver fuel for the Fast Flux Test Facility in the Secure Automated Fabrication line. After construction completion, but before facility certification, the Department of Energy (DOE) Richland Operation Office requested that a vulnerability analysis be performed which assumed multiple insiders as a threat to the security system. A unique method of analyzing facility vulnerabilities was developed at the Security Applications Center (SAC), which is managed by WHC for DOE. The method that was developed verifies a previous vulnerability assessment, as well as introducing a modeling technique which analyzes security alarms in relation to delaying factors and possible insider activities. With this information it is possible to assess the relative strength or weakness of various possible routes to and from a target within a facility

  12. Remote Laser Diffraction PSD Analyzer

    International Nuclear Information System (INIS)

    Batcheller, T.A.; Huestis, G.M.; Bolton, S.M.

    2000-01-01

    Particle size distribution (PSD) analysis of radioactive slurry samples were obtained using a modified off-the-shelf classical laser light scattering particle size analyzer. A Horiba Instruments Inc. Model La-300 PSD analyzer, which has a 0.1 to 600 micron measurement range, was modified for remote application in a hot cell (gamma radiation) environment. The general details of the modifications to this analyzer are presented in this paper. This technology provides rapid and simple PSD analysis, especially down in the fine and microscopic particle size regime. Particle size analysis of these radioactive slurries down in this smaller range was not achievable - making this technology far superior than the traditional methods used previously. Remote deployment and utilization of this technology is in an exploratory stage. The risk of malfunction in this radiation environment is countered by gaining of this tremendously useful fundamental engineering data. Successful acquisition of this data, in conjunction with other characterization analyses, provides important information that can be used in the myriad of potential radioactive waste management alternatives

  13. A new uranium automatic analyzer

    International Nuclear Information System (INIS)

    Xia Buyun; Zhu Yaokun; Wang Bin; Cong Peiyuan; Zhang Lan

    1993-01-01

    A new uranium automatic analyzer based on the flow injection analysis (FIA) principle has been developed. It consists of a multichannel peristaltic pump, an injection valve, a photometric detector, a single-chip microprocessor system and electronic circuit. The new designed multifunctional auto-injection valve can automatically change the injection volume of the sample and the channels so that the determination ranges and items can easily be changed. It also can make the instrument vary the FIA operation modes that it has functions of a universal instrument. A chromatographic column with extractant-containing resin was installed in the manifold of the analyzer for the concentration and separation of trace uranium. The 2-(5-bromo-2-pyridylazo)-5-diethyl-aminophenol (Br-PADAP) was used as colour reagent. Uranium was determined in the aqueous solution by adding cetyl-pyridium bromide (CPB). The uranium in the solution in the range 0.02-500 mg · L -1 can be directly determined without any pretreatment. A sample throughput rate of 30-90 h -1 and reproducibility of 1-2% were obtained. The analyzer has been satisfactorily applied to the laboratory and the plant

  14. Remote Laser Diffraction PSD Analyzer

    International Nuclear Information System (INIS)

    Batcheller, Thomas Aquinas; Huestis, Gary Michael; Bolton, Steven Michael

    2000-01-01

    Particle size distribution (PSD) analysis of radioactive slurry samples were obtained using a modified ''off-the-shelf'' classical laser light scattering particle size analyzer. A Horiba Instruments Inc. Model La-300 PSD analyzer, which has a 0.1 to 600 micron measurement range, was modified for remote application in a ''hot cell'' (gamma radiation) environment. The general details of the modifications to this analyzer are presented in this paper. This technology provides rapid and simple PSD analysis, especially down in the fine and microscopic particle size regime. Particle size analysis of these radioactive slurries down in this smaller range was not achievable--making this technology far superior than the traditional methods used previously. Remote deployment and utilization of this technology is in an exploratory stage. The risk of malfunction in this radiation environment is countered by gaining of this tremendously useful fundamental engineering data. Successful acquisition of this data, in conjunction with other characterization analyses, provides important information that can be used in the myriad of potential radioactive waste management alternatives

  15. Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity

    Science.gov (United States)

    Liu, Sijia; Chen, Pin-Yu; Hero, Alfred O.

    2018-04-01

    We consider the problem of accelerating distributed optimization in multi-agent networks by sequentially adding edges. Specifically, we extend the distributed dual averaging (DDA) subgradient algorithm to evolving networks of growing connectivity and analyze the corresponding improvement in convergence rate. It is known that the convergence rate of DDA is influenced by the algebraic connectivity of the underlying network, where better connectivity leads to faster convergence. However, the impact of network topology design on the convergence rate of DDA has not been fully understood. In this paper, we begin by designing network topologies via edge selection and scheduling. For edge selection, we determine the best set of candidate edges that achieves the optimal tradeoff between the growth of network connectivity and the usage of network resources. The dynamics of network evolution is then incurred by edge scheduling. Further, we provide a tractable approach to analyze the improvement in the convergence rate of DDA induced by the growth of network connectivity. Our analysis reveals the connection between network topology design and the convergence rate of DDA, and provides quantitative evaluation of DDA acceleration for distributed optimization that is absent in the existing analysis. Lastly, numerical experiments show that DDA can be significantly accelerated using a sequence of well-designed networks, and our theoretical predictions are well matched to its empirical convergence behavior.

  16. Network Anomaly Detection Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Ali A. Ghorbani

    2008-11-01

    Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  17. Network Anomaly Detection Based on Wavelet Analysis

    Science.gov (United States)

    Lu, Wei; Ghorbani, Ali A.

    2008-12-01

    Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  18. Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach

    Directory of Open Access Journals (Sweden)

    Mike W.-L. Cheung

    2016-05-01

    Full Text Available Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists – and probably the most crucial one – is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study.

  19. Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach.

    Science.gov (United States)

    Cheung, Mike W-L; Jak, Suzanne

    2016-01-01

    Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists-and probably the most crucial one-is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study.

  20. Growth strategies and governance of horizontal business networks: the case of the biggest German cooperative food retail network

    Directory of Open Access Journals (Sweden)

    Douglas Wegner

    2011-08-01

    Full Text Available Several growth strategies may be adopted by cooperative retail networks, but these strategies create dilemmas about how to organize business networks with a large number of participants and the adjustments in the governance system that are necessary to facilitate growth. The article examines the relations between the growth strategies adopted by a horizontal business network and its governance system. We analyze the case of Edeka, a centennial cooperative network, leader in food retail in Germany, showing its growth strategies and implications for the network structure. The case study was based on various secondary data sources and focuses the whole network – and not the networked firms – as the unit of analysis. Results indicate that, in order to grow, the network changed its governance structure and the process of participation of members in decision making, creating a hierarchical structure with professional management. The paper contributes to the discussions on cooperative governance and demonstrates that governance systems are transient and adapt to the network strategies. From a management viewpoint, the results show the effects of the growth strategies adopted by business networks, regarding the role of network managers and entrepreneurs in network management.

  1. Sensor Network Disposition Facing the Task of Multisensor Cross Cueing

    Directory of Open Access Journals (Sweden)

    Ce Pang

    2017-01-01

    Full Text Available In order to build the sensor network facing the task of multisensor crossing cueing, the requirements of initiating cueing and being cued are analyzed. Probability theory is used when building models, then probability of sensor cueing in the case of target moving is given, and, after that, the best distance between two sensors is calculated. The operational environment is described by normal distribution function. In the process of distributing sensor network, their elements, operational environment demand of cueing, and the probability of sensor network coverage are considered; then the optimization algorithm of sensor network based on hypothesis testing theory is made. The simulation result indicates that the algorithm can make sensor network which is required. On the basis of that, the two cases, including targets that make linear motion and orbit motion, are used to test the performance of the sensor network, which show that the sensor network can make uninterrupted detection on targets through multisensor cross cuing.

  2. Cytoskeletal actin dynamics shape a ramifying actin network underpinning immunological synapse formation

    DEFF Research Database (Denmark)

    Fritzsche, Marco; Fernandes, Ricardo A.; Chang, Veronica T.

    2017-01-01

    optical microscopes to analyze resting and activated T cells, we show that, following contact formation with activating surfaces, these cells sequentially rearrange their cortical actin across the entire cell, creating a previously unreported ramifying actin network above the immunological synapse...

  3. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    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

  4. Characterizing the topology of probabilistic biological networks.

    Science.gov (United States)

    Todor, Andrei; Dobra, Alin; Kahveci, Tamer

    2013-01-01

    Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software

  5. The security analyzer, a security analyzer program written in Prolog

    International Nuclear Information System (INIS)

    Zimmerman, B.D.; Densley, P.J.; Carlson, R.L.

    1987-01-01

    A technique has been developed to characterize a nuclear facility and measure the strengths and weaknesses of the physical protection system. It utilizes the artificial intelligence capabilities available in the prolog programming language to probe a facility's defenses and find potential attack paths that meet designated search criteria. As sensors or barriers become inactive due to maintenance, failure, or inclement weather conditions, the protection system can rapidly be reanalyzed to discover weaknesses that would need to be strengthened by alternative means. Conversely, proposed upgrades and enhancements can be easily entered into the database and their effect measured against a variety of potential adversary attacks. Thus the security analyzer is a tool that aids the protection planner as well as the protection operations staff

  6. Characterizing time series: when Granger causality triggers complex networks

    International Nuclear Information System (INIS)

    Ge Tian; Cui Yindong; Lin Wei; Liu Chong; Kurths, Jürgen

    2012-01-01

    In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length. (paper)

  7. Characterizing time series: when Granger causality triggers complex networks

    Science.gov (United States)

    Ge, Tian; Cui, Yindong; Lin, Wei; Kurths, Jürgen; Liu, Chong

    2012-08-01

    In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIHMassachusetts Institute of Technology-Beth Israel Hospital. human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.

  8. Network evolution of body plans.

    Directory of Open Access Journals (Sweden)

    Koichi Fujimoto

    Full Text Available One of the major goals in evolutionary developmental biology is to understand the relationship between gene regulatory networks and the diverse morphologies and their functionalities. Are the diversities solely triggered by random events, or are they inevitable outcomes of an interplay between evolving gene networks and natural selection? Segmentation in arthropod embryogenesis represents a well-known example of body plan diversity. Striped patterns of gene expression that lead to the future body segments appear simultaneously or sequentially in long and short germ-band development, respectively. Moreover, a combination of both is found in intermediate germ-band development. Regulatory genes relevant for stripe formation are evolutionarily conserved among arthropods, therefore the differences in the observed traits are thought to have originated from how the genes are wired. To reveal the basic differences in the network structure, we have numerically evolved hundreds of gene regulatory networks that produce striped patterns of gene expression. By analyzing the topologies of the generated networks, we show that the characteristics of stripe formation in long and short germ-band development are determined by Feed-Forward Loops (FFLs and negative Feed-Back Loops (FBLs respectively, and those of intermediate germ-band development are determined by the interconnections between FFL and negative FBL. Network architectures, gene expression patterns and knockout responses exhibited by the artificially evolved networks agree with those reported in the fly Drosophila melanogaster and the beetle Tribolium castaneum. For other arthropod species, principal network architectures that remain largely unknown are predicted. Our results suggest that the emergence of the three modes of body segmentation in arthropods is an inherent property of the evolving networks.

  9. The kpx, a program analyzer for parallelization

    International Nuclear Information System (INIS)

    Matsuyama, Yuji; Orii, Shigeo; Ota, Toshiro; Kume, Etsuo; Aikawa, Hiroshi.

    1997-03-01

    The kpx is a program analyzer, developed as a common technological basis for promoting parallel processing. The kpx consists of three tools. The first is ktool, that shows how much execution time is spent in program segments. The second is ptool, that shows parallelization overhead on the Paragon system. The last is xtool, that shows parallelization overhead on the VPP system. The kpx, designed to work for any FORTRAN cord on any UNIX computer, is confirmed to work well after testing on Paragon, SP2, SR2201, VPP500, VPP300, Monte-4, SX-4 and T90. (author)

  10. Fuel analyzer; Analisador de combustiveis

    Energy Technology Data Exchange (ETDEWEB)

    Cozzolino, Roberval [RS Motors, Indaiatuba, SP (Brazil)

    2008-07-01

    The current technology 'COMBUSTIMETRO' aims to examine the fuel through performance of the engine, as the role of the fuel is to produce energy for the combustion engine in the form of which is directly proportional to the quality and type of fuel. The 'COMBUSTIMETRO' has an engine that always keeps the same entry of air, fuel and fixed point of ignition. His operation is monitored by sensors (Sonda Lambda, RPM and Gases Analyzer) connected to a processor that performs calculations and records the information, generate reports and graphs. (author)

  11. Clusters in nonsmooth oscillator networks

    Science.gov (United States)

    Nicks, Rachel; Chambon, Lucie; Coombes, Stephen

    2018-03-01

    For coupled oscillator networks with Laplacian coupling, the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory, this approach has recently been extended to treat more general cluster states. However, the MSF and its generalizations require the determination of a set of Floquet multipliers from variational equations obtained by linearization around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by, the framework is often explored using numerical techniques. Here, we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of saltation matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration, we analyze an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris-Lecar neuron model. We use these examples to emphasize that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly, the procedure that we present here, for understanding cluster synchronization in networks, is valid for a wide variety of systems in

  12. Measuring Asymmetry in Insect-Plant Networks

    Energy Technology Data Exchange (ETDEWEB)

    Cruz, Claudia P T [Programa de Pos-Graduacao em Fisica, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); De Almeida, Adriana M [Departamento de Botanica, Ecologia e Zoologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil); Corso, Gilberto, E-mail: claudia@dfte.ufrn.br, E-mail: adrianam@ufrn.br, E-mail: corso@cb.ufrn.br [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, UFRN - Campus Universitario, Lagoa Nova, CEP 59078 972, Natal, RN (Brazil)

    2011-03-01

    In this work we focus on interaction networks between insects and plants and in the characterization of insect plant asymmetry, an important issue in coevolution and evolutionary biology. We analyze in particular the asymmetry in the interaction matrix of animals (herbivorous insects) and plants (food resource for the insects). Instead of driving our attention to the interaction matrix itself we derive two networks associated to the bipartite network: the animal network, D{sub 1}, and the plant network, D{sub 2}. These networks are constructed according to the following recipe: two animal species are linked once if they interact with the same plant. In a similar way, in the plant network, two plants are linked if they interact with the same animal. To explore the asymmetry between D{sub 2} and D{sub 1} we test for a set of 23 networks from the ecologic literature networks: the difference in size, {Delta}L, clustering coefficient difference, {Delta}C, and mean connectivity difference, {Delta}. We used a nonparametric statistical test to check the differences in {Delta}L, {Delta}C and {Delta}. Our results indicate that {Delta}L and {Delta} show a significative asymmetry.

  13. Approaching human language with complex networks

    Science.gov (United States)

    Cong, Jin; Liu, Haitao

    2014-12-01

    The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).

  14. Chaotic diagonal recurrent neural network

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Zhang Yi

    2012-01-01

    We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

  15. Online Advertising in Social Networks

    Science.gov (United States)

    Bagherjeiran, Abraham; Bhatt, Rushi P.; Parekh, Rajesh; Chaoji, Vineet

    Online social networks offer opportunities to analyze user behavior and social connectivity and leverage resulting insights for effective online advertising. This chapter focuses on the role of social network information in online display advertising.

  16. Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

    Directory of Open Access Journals (Sweden)

    Rui Ding

    Full Text Available Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

  17. Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

    Science.gov (United States)

    Ding, Rui; Ujang, Norsidah; Hamid, Hussain Bin; Wu, Jianjun

    2015-01-01

    Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

  18. Towards Effective Intra-flow Network Coding in Software Defined Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Donghai Zhu

    2016-01-01

    Full Text Available Wireless Mesh Networks (WMNs have potential to provide convenient broadband wireless Internet access to mobile users.With the support of Software-Defined Networking (SDN paradigm that separates control plane and data plane, WMNs can be easily deployed and managed. In addition, by exploiting the broadcast nature of the wireless medium and the spatial diversity of multi-hop wireless networks, intra-flow network coding has shown a greater benefit in comparison with traditional routing paradigms in data transmission for WMNs. In this paper, we develop a novel OpenCoding protocol, which combines the SDN technique with intra-flow network coding for WMNs. Our developed protocol can simplify the deployment and management of the network and improve network performance. In OpenCoding, a controller that works on the control plane makes routing decisions for mesh routers and the hop-by-hop forwarding function is replaced by network coding functions in data plane. We analyze the overhead of OpenCoding. Through a simulation study, we show the effectiveness of the OpenCoding protocol in comparison with existing schemes. Our data shows that OpenCoding outperforms both traditional routing and intra-flow network coding schemes.

  19. Network Compression as a Quality Measure for Protein Interaction Networks

    Science.gov (United States)

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

    2012-01-01

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

  20. Compact Microwave Fourier Spectrum Analyzer

    Science.gov (United States)

    Savchenkov, Anatoliy; Matsko, Andrey; Strekalov, Dmitry

    2009-01-01

    A compact photonic microwave Fourier spectrum analyzer [a Fourier-transform microwave spectrometer, (FTMWS)] with no moving parts has been proposed for use in remote sensing of weak, natural microwave emissions from the surfaces and atmospheres of planets to enable remote analysis and determination of chemical composition and abundances of critical molecular constituents in space. The instrument is based on a Bessel beam (light modes with non-zero angular momenta) fiber-optic elements. It features low power consumption, low mass, and high resolution, without a need for any cryogenics, beyond what is achievable by the current state-of-the-art in space instruments. The instrument can also be used in a wide-band scatterometer mode in active radar systems.

  1. Patterned basal seismicity shows sub-ice stream bedforms

    Science.gov (United States)

    Barcheck, C. G.; Tulaczyk, S. M.; Schwartz, S. Y.

    2017-12-01

    Patterns in seismicity emanating from the bottom of fast-moving ice streams and glaciers may indicate localized patches of higher basal resistance— sometimes called 'sticky spots', or otherwise varying basal properties. These seismogenic basal areas resist an unknown portion of the total driving stress of the Whillans Ice Plain (WIP), in West Antarctica, but may play an important role in the WIP stick-slip cycle and ice stream slowdown. To better understand the mechanism and importance of basal seismicity beneath the WIP, we analyze seismic data collected by a small aperture (micro-earthquakes in Dec 2014, and we compare the resulting map of seismicity to ice bottom depth measured by airborne radar. The number of basal earthquakes per area within the network is spatially heterogeneous, but a pattern of two 400m wide streaks of high seismicity rates is evident, with >50-500 earthquakes detected per 50x50m grid cell in 2 weeks. These seismically active streaks are elongated approximately in the ice flow direction with a spacing of 750m. Independent airborne radar measurements of ice bottom depth from Jan 2013 show a low-amplitude ( 5m) undulation in the basal topography superposed on a regional gradient in ice bottom depth. The flow-perpendicular wavelength of these low-amplitude undulations is comparable to the spacing of the high seismicity bands, and the streaks of high seismicity intersect local lows in the undulating basal topography. We interpret these seismic and radar observations as showing seismically active sub-ice stream bedforms that are low amplitude and elongated in the direction of ice flow, comparable to the morphology of mega scale glacial lineations (MSGLs), with high basal seismicity rates observed in the MSGL troughs. These results have implications for understanding the formation mechanism of MSGLS and well as understanding the interplay between basal topographic roughness, spatially varying basal till and hydrologic properties, basal

  2. Application of Game Theory Approaches in Routing Protocols for Wireless Networks

    Science.gov (United States)

    Javidi, Mohammad M.; Aliahmadipour, Laya

    2011-09-01

    An important and essential issue for wireless networks is routing protocol design that is a major technical challenge due to the function of the network. Game theory is a powerful mathematical tool that analyzes the strategic interactions among multiple decision makers and the results of researches show that applied game theory in routing protocol lead to improvement the network performance through reduce overhead and motivates selfish nodes to collaborate in the network. This paper presents a review and comparison for typical representatives of routing protocols designed that applied game theory approaches for various wireless networks such as ad hoc networks, mobile ad hoc networks and sensor networks that all of them lead to improve the network performance.

  3. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  4. Formulation and applications of complex network theory

    Science.gov (United States)

    Park, Juyong

    In recent years, there has been a great surge of interest among physicists in modeling social, technological, or biological systems as networks. Analyses of large-scale networks such as the Internet have led to discoveries of many unexpected network properties, including power-law degree distributions. These discoveries have prompted physicists to devise novel ways to model networks, both computational and theoretical. In this dissertation, we present several network models and their applications. First, we study the theory of Exponential Random Graphs. We derive it from the principle of maximum entropy, thereby showing that it is the equivalent of the Gibbs ensemble for networks. Using tools of statistical physics, we solve well-known and new examples that include power-law networks and the two-star model. Our solutions confirm the existence of a first-order phase transition for the latter whose exact behavior has not been presented previously. We also study degree correlations and clustering in networks. Degrees of adjacent vertices are positively correlated in social networks, whereas they are negatively correlated in other types of networks. We demonstrate that a negative degree correlation is a more natural state of a network, and therefore that social networks are an exception. We argue that variations in the number of vertices in social groups cause positive degree correlations, and analyze a model that incorporates such a mechanism. The model indeed shows a high level of degree correlation and clustering that is similar in value to those of real networks. Finally, we develop algorithms for ranking vertices in networks that represent pairwise comparisons. The first algorithm is based on the familiar concept of indirect wins and losses. The second algorithm is based on the concept of retrodictive accuracy, which is maximized by positioning as many winners above the losers as possible. We compare the rankings of American college football teams generated by our

  5. Multiplicative Attribute Graph Model of Real-World Networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

    2010-10-20

    Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

  6. Extracting information from multiplex networks

    Science.gov (United States)

    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.

  7. Analyzing Gender Stereotyping in Bollywood Movies

    OpenAIRE

    Madaan, Nishtha; Mehta, Sameep; Agrawaal, Taneea S; Malhotra, Vrinda; Aggarwal, Aditi; Saxena, Mayank

    2017-01-01

    The presence of gender stereotypes in many aspects of society is a well-known phenomenon. In this paper, we focus on studying such stereotypes and bias in Hindi movie industry (Bollywood). We analyze movie plots and posters for all movies released since 1970. The gender bias is detected by semantic modeling of plots at inter-sentence and intra-sentence level. Different features like occupation, introduction of cast in text, associated actions and descriptions are captured to show the pervasiv...

  8. Controllability of Train Service Network

    Directory of Open Access Journals (Sweden)

    Xuelei Meng

    2015-01-01

    Full Text Available Train service network is a network form of train service plan. The controllability of the train service plan determines the recovery possibility of the train service plan in emergencies. We first build the small-world model for train service network and analyze the scale-free character of it. Then based on the linear network controllability theory, we discuss the LB model adaptability in train service network controllability analysis. The LB model is improved and we construct the train service network and define the connotation of the driver nodes based on the immune propagation and cascading failure in the train service network. An algorithm to search for the driver nodes, turning the train service network into a bipartite graph, is proposed and applied in the train service network. We analyze the controllability of the train service network of China with the method and the results of the computing case prove the feasibility of it.

  9. Relativistic effects in the calibration of electrostatic electron analyzers. I. Toroidal analyzers

    Energy Technology Data Exchange (ETDEWEB)

    Keski Rahkonen, O [Helsinki University of Technology, Espoo (Finland). Laboratory of Physics; Krause, M O [Oak Ridge National Lab., Tenn. (USA)

    1978-02-01

    Relativistic correction terms up to the second order are derived for the kinetic energy of an electron travelling along the circular central trajectory of a toroidal analyzer. Furthermore, a practical energy calibration equation of the spherical sector plate analyzer is written for the variable-plate-voltage recording mode. Accurate measurements with a spherical analyzer performed using kinetic energies from 600 to 2100 eV are in good agreement with this theory showing our approximation (neglect of fringing fields, and source and detector geometry) is realistic enough for actual calibration purposes.

  10. Radiation energy detector and analyzer

    International Nuclear Information System (INIS)

    Roberts, T.G.

    1981-01-01

    A radiation detector array and a method for measuring the spectral content of radiation. The radiation sensor or detector is an array or stack of thin solid-electrolyte batteries. The batteries, arranged in a stack, may be composed of independent battery cells or may be arranged so that adjacent cells share a common terminal surface. This common surface is possible since the polarity of the batteries with respect to an adjacent battery is unrestricted, allowing a reduction in component parts of the assembly and reducing the overall stack length. Additionally, a test jig or chamber for allowing rapid measurement of the voltage across each battery is disclosed. A multichannel recorder and display may be used to indicate the voltage gradient change across the cells, or a small computer may be used for rapidly converting these voltage readings to a graph of radiation intensity versus wavelength or energy. The behavior of the batteries when used as a radiation detector and analyzer are such that the voltage measurements can be made at leisure after the detector array has been exposed to the radiation, and it is not necessary to make rapid measurements as is now done

  11. Nuclear plant analyzer desktop workstation

    International Nuclear Information System (INIS)

    Beelman, R.J.

    1990-01-01

    In 1983 the U.S. Nuclear Regulatory Commission (USNRC) commissioned the Idaho National Engineering Laboratory (INEL) to develop a Nuclear Plant Analyzer (NPA). The NPA was envisioned as a graphical aid to assist reactor safety analysts in comprehending the results of thermal-hydraulic code calculations. The development was to proceed in three distinct phases culminating in a desktop reactor safety workstation. The desktop NPA is now complete. The desktop NPA is a microcomputer based reactor transient simulation, visualization and analysis tool developed at INEL to assist an analyst in evaluating the transient behavior of nuclear power plants by means of graphic displays. The NPA desktop workstation integrates advanced reactor simulation codes with online computer graphics allowing reactor plant transient simulation and graphical presentation of results. The graphics software, written exclusively in ANSI standard C and FORTRAN 77 and implemented over the UNIX/X-windows operating environment, is modular and is designed to interface to the NRC's suite of advanced thermal-hydraulic codes to the extent allowed by that code. Currently, full, interactive, desktop NPA capabilities are realized only with RELAP5

  12. Pelvimetry revisited: Analyzing cephalopelvic disproportion

    Energy Technology Data Exchange (ETDEWEB)

    Lenhard, Miriam S. [Department of Obstetrics and Gynecology, Ludwig-Maximilians-University of Munich, 81377 Munich (Germany); Johnson, Thorsten R.C., E-mail: thorsten.johnson@med.uni-muenchen.d [Department of Radiology, Ludwig-Maximilians-University of Munich, Marchioninistrasse 15, 81377 Munich (Germany); Weckbach, Sabine; Nikolaou, Konstantin [Department of Radiology, Ludwig-Maximilians-University of Munich, Marchioninistrasse 15, 81377 Munich (Germany); Friese, Klaus; Hasbargen, Uwe [Department of Obstetrics and Gynecology, Ludwig-Maximilians-University of Munich, 81377 Munich (Germany)

    2010-06-15

    The objective of this study was to assess the clinical value of pelvimetry to predict dystocia due to cephalopelvic disproportion. 63 patients who had received an abdominal CT scan postpartum were included. Pelvimetry was performed retrospectively with these datasets on a 3D workstation; there were no CT examinations performed solely for pelvimetry, and there was no radiation exposure for study purposes. Patients were divided into three groups by the course of birth, i.e. normal vaginal delivery (A), dystocia due to cephalopelvic disproportion (B) and other patients (C). Previously described methods were evaluated for their accuracy in diagnosing cephalopelvic disproportion. The pelvimetric parameters did not show significant differences between groups A (n = 20) and B (n = 20) except for the sagittal mid-pelvic diameter (q) with 12.7 {+-} 0.6 cm vs. 11.9 {+-} 0.6 cm (p = 0.0001). The ROC analysis of the previously described methods showed areas under the curve between 0.50 and 0.67. The ROC curves for q had an area of 0.88, providing 85% sensitivity with 85% specificity. In conclusion, the sagittal mid-pelvic diameter shows potential to detect cephalopelvic disproportion with acceptable accuracy. With the information gained on the CT data, a prospective trial based on MR imaging can be set up to validate the diagnostic accuracy.

  13. Pelvimetry revisited: Analyzing cephalopelvic disproportion

    International Nuclear Information System (INIS)

    Lenhard, Miriam S.; Johnson, Thorsten R.C.; Weckbach, Sabine; Nikolaou, Konstantin; Friese, Klaus; Hasbargen, Uwe

    2010-01-01

    The objective of this study was to assess the clinical value of pelvimetry to predict dystocia due to cephalopelvic disproportion. 63 patients who had received an abdominal CT scan postpartum were included. Pelvimetry was performed retrospectively with these datasets on a 3D workstation; there were no CT examinations performed solely for pelvimetry, and there was no radiation exposure for study purposes. Patients were divided into three groups by the course of birth, i.e. normal vaginal delivery (A), dystocia due to cephalopelvic disproportion (B) and other patients (C). Previously described methods were evaluated for their accuracy in diagnosing cephalopelvic disproportion. The pelvimetric parameters did not show significant differences between groups A (n = 20) and B (n = 20) except for the sagittal mid-pelvic diameter (q) with 12.7 ± 0.6 cm vs. 11.9 ± 0.6 cm (p = 0.0001). The ROC analysis of the previously described methods showed areas under the curve between 0.50 and 0.67. The ROC curves for q had an area of 0.88, providing 85% sensitivity with 85% specificity. In conclusion, the sagittal mid-pelvic diameter shows potential to detect cephalopelvic disproportion with acceptable accuracy. With the information gained on the CT data, a prospective trial based on MR imaging can be set up to validate the diagnostic accuracy.

  14. Community structures and role detection in music networks

    Science.gov (United States)

    Teitelbaum, T.; Balenzuela, P.; Cano, P.; Buldú, Javier M.

    2008-12-01

    We analyze the existence of community structures in two different social networks using data obtained from similarity and collaborative features between musical artists. Our analysis reveals some characteristic organizational patterns and provides information about the driving forces behind the growth of the networks. In the similarity network, we find a strong correlation between clusters of artists and musical genres. On the other hand, the collaboration network shows two different kinds of communities: rather small structures related to music bands and geographic zones, and much bigger communities built upon collaborative clusters with a high number of participants related through the period the artists were active. Finally, we detect the leading artists inside their corresponding communities and analyze their roles in the network by looking at a few topological properties of the nodes.

  15. Regional modeling approach for analyzing harmonic stability in radial power electronics based power system

    DEFF Research Database (Denmark)

    Yoon, Changwoo; Bai, Haofeng; Wang, Xiongfei

    2015-01-01

    Stability analysis of distributed power generation system becomes complex when there are many numbers of grid inverters in the system. In order to analyze system stability, the overall network impedance will be lumped and needs to be analyzed one by one. However, using a unified bulky transfer-fu...... and then it is expanded for generalizing its concept to an overall radial structured network....

  16. Analyzing Cyber-Physical Threats on Robotic Platforms.

    Science.gov (United States)

    Ahmad Yousef, Khalil M; AlMajali, Anas; Ghalyon, Salah Abu; Dweik, Waleed; Mohd, Bassam J

    2018-05-21

    Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBot TM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications.

  17. Analyzing Cyber-Physical Threats on Robotic Platforms †

    Science.gov (United States)

    2018-01-01

    Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream) and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT) was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBotTM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS) and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications. PMID:29883403

  18. Analyzing Cyber-Physical Threats on Robotic Platforms

    Directory of Open Access Journals (Sweden)

    Khalil M. Ahmad Yousef

    2018-05-01

    Full Text Available Robots are increasingly involved in our daily lives. Fundamental to robots are the communication link (or stream and the applications that connect the robots to their clients or users. Such communication link and applications are usually supported through client/server network connection. This networking system is amenable of being attacked and vulnerable to the security threats. Ensuring security and privacy for robotic platforms is thus critical, as failures and attacks could have devastating consequences. In this paper, we examine several cyber-physical security threats that are unique to the robotic platforms; specifically the communication link and the applications. Threats target integrity, availability and confidential security requirements of the robotic platforms, which use MobileEyes/arnlServer client/server applications. A robot attack tool (RAT was developed to perform specific security attacks. An impact-oriented approach was adopted to analyze the assessment results of the attacks. Tests and experiments of attacks were conducted in simulation environment and physically on the robot. The simulation environment was based on MobileSim; a software tool for simulating, debugging and experimenting on MobileRobots/ActivMedia platforms and their environments. The robot platform PeopleBotTM was used for physical experiments. The analysis and testing results show that certain attacks were successful at breaching the robot security. Integrity attacks modified commands and manipulated the robot behavior. Availability attacks were able to cause Denial-of-Service (DoS and the robot was not responsive to MobileEyes commands. Integrity and availability attacks caused sensitive information on the robot to be hijacked. To mitigate security threats, we provide possible mitigation techniques and suggestions to raise awareness of threats on the robotic platforms, especially when the robots are involved in critical missions or applications.

  19. Soil Bacterial and Fungal Communities Show Distinct Recovery Patterns during Forest Ecosystem Restoration.

    Science.gov (United States)

    Sun, Shan; Li, Song; Avera, Bethany N; Strahm, Brian D; Badgley, Brian D

    2017-07-15

    Bacteria and fungi are important mediators of biogeochemical processes and play essential roles in the establishment of plant communities, which makes knowledge about their recovery after extreme disturbances valuable for understanding ecosystem development. However, broad ecological differences between bacterial and fungal organisms, such as growth rates, stress tolerance, and substrate utilization, suggest they could follow distinct trajectories and show contrasting dynamics during recovery. In this study, we analyzed both the intra-annual variability and decade-scale recovery of bacterial and fungal communities in a chronosequence of reclaimed mined soils using next-generation sequencing to quantify their abundance, richness, β-diversity, taxonomic composition, and cooccurrence network properties. Bacterial communities shifted gradually, with overlapping β-diversity patterns across chronosequence ages, while shifts in fungal communities were more distinct among different ages. In addition, the magnitude of intra-annual variability in bacterial β-diversity was comparable to the changes across decades of chronosequence age, while fungal communities changed minimally across months. Finally, the complexity of bacterial cooccurrence networks increased with chronosequence age, while fungal networks did not show clear age-related trends. We hypothesize that these contrasting dynamics of bacteria and fungi in the chronosequence result from (i) higher growth rates for bacteria, leading to higher intra-annual variability; (ii) higher tolerance to environmental changes for fungi; and (iii) stronger influence of vegetation on fungal communities. IMPORTANCE Both bacteria and fungi play essential roles in ecosystem functions, and information about their recovery after extreme disturbances is important for understanding whole-ecosystem development. Given their many differences in phenotype, phylogeny, and life history, a comparison of different bacterial and fungal recovery

  20. Molecular network topology and reliability for multipurpose diagnosis

    Directory of Open Access Journals (Sweden)

    Jalil MA

    2011-10-01

    Full Text Available MA Jalil1, N Moongfangklang2,3, K Innate4, S Mitatha3, J Ali5, PP Yupapin41Ibnu Sina Institute of Fundamental Science Studies, Nanotechnology Research Alliance, University of Technology Malaysia, Johor Bahru, Malaysia; 2School of Information and Communication Technology, Phayao University, Phayao, Thailand; 3Hybrid Computing Research Laboratory, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 4Nanoscale Science and Engineering Research Alliance, Advanced Research Center for Photonics, Faculty of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand; 5Institute of Advanced Photonics Science, Nanotechnology Research Alliance, University of Technology Malaysia, Johor Bahru, MalaysiaAbstract: This investigation proposes the use of molecular network topology for drug delivery and diagnosis network design. Three modules of molecular network topologies, such as bus, star, and ring networks, are designed and manipulated based on a micro- and nanoring resonator system. The transportation of the trapping molecules by light in the network is described and the theoretical background is reviewed. The quality of the network is analyzed and calculated in terms of signal transmission (ie, signal to noise ratio and crosstalk effects. Results obtained show that a bus network has advantages over star and ring networks, where the use of mesh networks is possible. In application, a thin film network can be fabricated in the form of a waveguide and embedded in artificial bone, which can be connected to the required drug targets. The particular drug/nutrient can be transported to the required targets via the particular network used.Keywords: molecular network, network reliability, network topology, drug network, multi-access network

  1. A Complex Network Approach to Distributional Semantic Models.

    Directory of Open Access Journals (Sweden)

    Akira Utsumi

    Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.

  2. Cost and Availability Analysis of 2- and 3-Connected WDM Networks Physical Interconnection

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Pedersen, Jens Myrup

    2012-01-01

    for the best trade-off among the relevant parameters for the network. In this paper we analyze this trade-off by studying 2-and 3-connected graphs to be used as WDM (Wavelength Division Multiplexing) networks physical infrastructure. The experiments show how the way links are distributed to interconnect...

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

    Science.gov (United States)

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

    2015-05-01

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

  4. Resting-state functional connectivity of orthographic networks in acquired dysgraphia

    Directory of Open Access Journals (Sweden)

    Gali Ellenblum

    2015-05-01

    The NTA findings indicate that the relationship between orthographic and default-mode networks is characterized by greater within- vs. across-network connectivity. Furthermore, we show for the first time a pattern of increasing within/across network “coherence normalization” following spelling rehabilitation. Additional dysgraphic participants and other networks (language, sensory-motor, etc. will be analyzed to develop a better understanding of the RS orthographic network and its response to damage and recovery. Acknowledgements. The work is part of a multi-site, NIDCD-supported project examining language recovery neurobiology in aphasia (DC006740. We thank Melissa Greenberger and Xiao-Wei Song.

  5. Assessing the implications of cellular network performance on mobile content access

    DEFF Research Database (Denmark)

    Kaup, Fabian; Michelinakis, Foivos; Bui, Nicola

    2016-01-01

    Mobile applications such as VoIP, (live) gaming, or video streaming have diverse QoS requirements ranging from low delay to high throughput. The optimization of the network quality experienced by end-users requires detailed knowledge of the expected network performance. Also, the achieved service...... of cellular network measurements, focused on analyzing root causes of mobile network performance variability. Measurements conducted on a 4G cellular network in Germany show that management and configuration decisions have a substantial impact on the performance. Specifically, it is observed...

  6. Validation of network communicability metrics for the analysis of brain structural networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Andreotti

    Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

  7. Network connectivity value.

    Science.gov (United States)

    Dragicevic, Arnaud; Boulanger, Vincent; Bruciamacchie, Max; Chauchard, Sandrine; Dupouey, Jean-Luc; Stenger, Anne

    2017-04-21

    In order to unveil the value of network connectivity, we formalize the construction of ecological networks in forest environments as an optimal control dynamic graph-theoretic problem. The network is based on a set of bioreserves and patches linked by ecological corridors. The node dynamics, built upon the consensus protocol, form a time evolutive Mahalanobis distance weighted by the opportunity costs of timber production. We consider a case of complete graph, where the ecological network is fully connected, and a case of incomplete graph, where the ecological network is partially connected. The results show that the network equilibrium depends on the size of the reception zone, while the network connectivity depends on the environmental compatibility between the ecological areas. Through shadow prices, we find that securing connectivity in partially connected networks is more expensive than in fully connected networks, but should be undertaken when the opportunity costs are significant. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  9. Heterogeneity and Networks

    OpenAIRE

    Goyal, S.

    2018-01-01

    This chapter shows that networks can have large and differentiated effects on behavior and then argues that social and economic pressures facilitate the formation of heterogenous networks. Thus networks can play an important role in understanding the wide diversity in human behaviour and in economic outcomes.

  10. Network protocols and sockets

    OpenAIRE

    BALEJ, Marek

    2010-01-01

    My work will deal with network protocols and sockets and their use in programming language C#. It will therefore deal programming network applications on the platform .NET from Microsoft and instruments, which C# provides to us. There will describe the tools and methods for programming network applications, and shows a description and sample applications that work with sockets and application protocols.

  11. Integrating networks with Mathematica

    NARCIS (Netherlands)

    Strijkers, R.J.; Meijer, R.J.

    2008-01-01

    We have developed a concept that considers network behavior as a collection of software objects, which can be used or modified in computer programs. The interfaces of these software objects are exposed as web services and enable applications to analyze and manipulate networks, e.g. to find

  12. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Hong Kezhu

    2007-01-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  13. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Kezhu Hong

    2007-04-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  14. Autonomous Distributed Self-Organization for Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chih-Yu Wen

    2009-11-01

    Full Text Available This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently. A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

  15. Autonomous distributed self-organization for mobile wireless sensor networks.

    Science.gov (United States)

    Wen, Chih-Yu; Tang, Hung-Kai

    2009-01-01

    This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

  16. An information spreading model based on online social networks

    Science.gov (United States)

    Wang, Tao; He, Juanjuan; Wang, Xiaoxia

    2018-01-01

    Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

  17. Violence on canadian television networks.

    Science.gov (United States)

    Paquette, Guy

    2004-02-01

    Over the past twenty years, the question of the effects of violence on television has figured prominently in public opinion and hundreds of studies have been devoted to this subject. Many researchers have determined that violence has a negative impact on behavior. The public, broadcasters and political figures all support the idea of reducing the total amount of violence on television - in particular in shows for children. A thousand programs aired between 1993 and 2001 on major non-specialty television networks in Canada were analyzed: TVA, TQS, as well as CTV and Global, private French and English networks, as well as the English CBC Radio and French Radio-Canada for the public networks. The methodology consists of a classic analysis of content where an act of violence constitutes a unit of analysis. The data collected revealed that the amount of violence has increased regularly since 1993 despite the stated willingness on the part of broadcasters to produce programs with less violence. The total number of violent acts, as well as the number of violent acts per hour, is increasing. Private networks deliver three times more violence than public networks. Researchers have also noted that a high proportion of violence occurs in programs airing before 21:00 hours, thereby exposing a large number of children to this violence. Psychological violence is taking on a more significant role in Canadian Television.

  18. A Morphology Study of Nanofiller Networks in Polymer Nanocomposites: Improving Their Electrical Conductivity through Better Doping Strategies

    KAUST Repository

    Mora Cordova, Angel

    2018-01-01

    to systematically analyze conductive networks and show how particles are arranged. A definition of loading efficiency is provided based on the results obtained from this morphology analysis. This study provides useful guidelines for designing these types

  19. Multidimensional Risk Management for Underground Electricity Networks

    Directory of Open Access Journals (Sweden)

    Garcez Thalles V.

    2014-08-01

    Full Text Available In the paper we consider an electricity provider company that makes decision on allocating resources on electric network maintenance. The investments decrease malfunction rate of network nodes. An accidental event (explosion, fire, etc. or a malfunctioning on underground system can have various consequences and in different perspectives, such as deaths and injuries of pedestrians, fires in nearby locations, disturbances in the flow of vehicular traffic, loss to the company image, operating and financial losses, etc. For this reason it is necessary to apply an approach of the risk management that considers the multidimensional view of the consequences. Furthermore an analysis of decision making should consider network dependencies between the nodes of the electricity distribution system. In the paper we propose the use of the simulation to assess the network effects (such as the increase of the probability of other accidental event and the occurrence of blackouts of the dependent nodes in the multidimensional risk assessment in electricity grid. The analyzed effects include node overloading due to malfunction of adjacent nodes and blackouts that take place where there is temporarily no path in the grid between the power plant and a node. The simulation results show that network effects have crucial role for decisions in the network maintenance – outcomes of decisions to repair a particular node in the network can have significant influence on performance of other nodes. However, those dependencies are non-linear. The effects of network connectivity (number of connections between nodes on its multidimensional performance assessment depend heavily on the overloading effect level. The simulation results do not depend on network type structure (random or small world – however simulation outcomes for random networks have shown higher variance compared to small-world networks.

  20. A Comparison of Online Social Networks and Real-Life Social Networks: A Study of Sina Microblogging

    Directory of Open Access Journals (Sweden)

    Dayong Zhang

    2014-01-01

    Full Text Available Online social networks appear to enrich our social life, which raises the question whether they remove cognitive constraints on human communication and improve human social capabilities. In this paper, we analyze the users' following and followed relationships based on the data of Sina Microblogging and reveal several structural properties of Sina Microblogging. Compared with real-life social networks, our results confirm some similar features. However, Sina Microblogging also shows its own specialties, such as hierarchical structure and degree disassortativity, which all mark a deviation from real-life social networks. The low cost of the online network forms a broader perspective, and the one-way link relationships make it easy to spread information, but the online social network does not make too much difference in the creation of strong interpersonal relationships. Finally, we describe the mechanisms for the formation of these characteristics and discuss the implications of these structural properties for the real-life social networks.

  1. Data reliability in complex directed networks

    Science.gov (United States)

    Sanz, Joaquín; Cozzo, Emanuele; Moreno, Yamir

    2013-12-01

    The availability of data from many different sources and fields of science has made it possible to map out an increasing number of networks of contacts and interactions. However, quantifying how reliable these data are remains an open problem. From Biology to Sociology and Economics, the identification of false and missing positives has become a problem that calls for a solution. In this work we extend one of the newest, best performing models—due to Guimerá and Sales-Pardo in 2009—to directed networks. The new methodology is able to identify missing and spurious directed interactions with more precision than previous approaches, which renders it particularly useful for analyzing data reliability in systems like trophic webs, gene regulatory networks, communication patterns and several social systems. We also show, using real-world networks, how the method can be employed to help search for new interactions in an efficient way.

  2. Data reliability in complex directed networks

    International Nuclear Information System (INIS)

    Sanz, Joaquín; Cozzo, Emanuele; Moreno, Yamir

    2013-01-01

    The availability of data from many different sources and fields of science has made it possible to map out an increasing number of networks of contacts and interactions. However, quantifying how reliable these data are remains an open problem. From Biology to Sociology and Economics, the identification of false and missing positives has become a problem that calls for a solution. In this work we extend one of the newest, best performing models—due to Guimerá and Sales-Pardo in 2009—to directed networks. The new methodology is able to identify missing and spurious directed interactions with more precision than previous approaches, which renders it particularly useful for analyzing data reliability in systems like trophic webs, gene regulatory networks, communication patterns and several social systems. We also show, using real-world networks, how the method can be employed to help search for new interactions in an efficient way. (paper)

  3. E-commerce System Security Assessment based on Bayesian Network Algorithm Research

    OpenAIRE

    Ting Li; Xin Li

    2013-01-01

    Evaluation of e-commerce network security is based on assessment method Bayesian networks, and it first defines the vulnerability status of e-commerce system evaluation index and the vulnerability of the state model of e-commerce systems, and after the principle of the Bayesian network reliability of e-commerce system and the criticality of the vulnerabilities were analyzed, experiments show that the change method is a good evaluation of the security of e-commerce systems.

  4. AN ANALYZING OF SOCIAL TRUST IN THE TABRIZ METROPOLITAN AREAS

    Directory of Open Access Journals (Sweden)

    Nader Zali

    2012-12-01

    Full Text Available The social capital consists of two fundamental components. Relations and links, norms and trust that facilitate group activities, relations and social networks as components of social capital has been evaluated in Tabriz city. This research has been conducted with descriptive and analytical approach in survey. The statistical society of this research was citizens of Tabriz city and the information has been gathered via face to face referring to homes by cluster sampling. In this research four components like accumulating social relations, symmetrical relations, supporting relations and mediation relations as main components of quality of social relations and structure of relations has been analyzed. The results of this study show that the relational stable degree is low in Tabriz city and accumulating the social relation as one of indices of relational stability has got better status in comparison to other indices. Also based on results of this research the social relations in Tabriz city have got very low adaptability degree. At the end of article according to importance of social capital in social development it has been referred to its role in advancement of programs of social development.

  5. AN ANALYZING OF SOCIAL TRUST IN THE TABRIZ METROPOLITAN AREAS

    Directory of Open Access Journals (Sweden)

    Nader Zali

    2012-01-01

    Full Text Available The social capital consists of two fundamental components. Relations and links, norms and trust that facilitate group activities, relations and social networks as components of social capital has been evaluated in Tabriz city. This research has been conducted with descriptive and analytical approach in survey. The statistical society of this research was citizens of Tabriz city and the information has been gathered via face to face referring to homes by cluster sampling. In this research four components like accumulating social relations, symmetrical relations, supporting relations and mediation relations as main components of quality of social relations and structure of relations has been analyzed. The results of this study show that the relational stable degree is low in Tabriz city and accumulating the social relation as one of indices of relational stability has got better status in comparison to other indices. Also based on results of this research the social relations in Tabriz city have got very low adaptability degree. At the end of article according to importance of social capital in social development it has been referred to its role in advancement of programs of social development.

  6. Increasing Scalability of Researcher Network Extraction from the Web

    Science.gov (United States)

    Asada, Yohei; Matsuo, Yutaka; Ishizuka, Mitsuru

    Social networks, which describe relations among people or organizations as a network, have recently attracted attention. With the help of a social network, we can analyze the structure of a community and thereby promote efficient communications within it. We investigate the problem of extracting a network of researchers from the Web, to assist efficient cooperation among researchers. Our method uses a search engine to get the cooccurences of names of two researchers and calculates the streangth of the relation between them. Then we label the relation by analyzing the Web pages in which these two names cooccur. Research on social network extraction using search engines as ours, is attracting attention in Japan as well as abroad. However, the former approaches issue too many queries to search engines to extract a large-scale network. In this paper, we propose a method to filter superfluous queries and facilitates the extraction of large-scale networks. By this method we are able to extract a network of around 3000-nodes. Our experimental results show that the proposed method reduces the number of queries significantly while preserving the quality of the network as compared to former methods.

  7. Nonlinear single-spin spectrum analyzer.

    Science.gov (United States)

    Kotler, Shlomi; Akerman, Nitzan; Glickman, Yinnon; Ozeri, Roee

    2013-03-15

    Qubits have been used as linear spectrum analyzers of their environments. Here we solve the problem of nonlinear spectral analysis, required for discrete noise induced by a strongly coupled environment. Our nonperturbative analytical model shows a nonlinear signal dependence on noise power, resulting in a spectral resolution beyond the Fourier limit as well as frequency mixing. We develop a noise characterization scheme adapted to this nonlinearity. We then apply it using a single trapped ion as a sensitive probe of strong, non-Gaussian, discrete magnetic field noise. Finally, we experimentally compared the performance of equidistant vs Uhrig modulation schemes for spectral analysis.

  8. Do Policy Networks lead to Network Governing?

    DEFF Research Database (Denmark)

    Damgaard, Bodil

    This paper challenges the notion that creation of local policy networks necessarily leads to network governing. Through actor-centred case studies in the area of municipally implemented employment policy in Denmark it was found that the local governing mode is determined mainly by the municipality......’s approach to local co-governing as well as by the capacity and interest of key private actors. It is argued that national legislation requesting the creation of local policy networks was not enough to assure network governing and the case studies show that local policy networks may subsist also under...... hierarchical governing modes. Reasons why hierarchical governing modes prevail over network governing in some settings are identified pointing to both actor borne and structural factors. Output indicators of the four cases do not show that a particular governing mode is more efficient in its employment policy...

  9. Specifying Orchestrating Capability in Network Organization and Interfirm Innovation Networks

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    -tech industry. Besides interfirm networks, some organizational researchers are interested in the internal network organizational design. Prospector firms putting innovation on top of the agenda usually has a network organization which is more flexible. This paper analyzes how an SME from a traditional industry...

  10. Packets Distributing Evolutionary Algorithm Based on PSO for Ad Hoc Network

    Science.gov (United States)

    Xu, Xiao-Feng

    2018-03-01

    Wireless communication network has such features as limited bandwidth, changeful channel and dynamic topology, etc. Ad hoc network has lots of difficulties in accessing control, bandwidth distribution, resource assign and congestion control. Therefore, a wireless packets distributing Evolutionary algorithm based on PSO (DPSO)for Ad Hoc Network is proposed. Firstly, parameters impact on performance of network are analyzed and researched to obtain network performance effective function. Secondly, the improved PSO Evolutionary Algorithm is used to solve the optimization problem from local to global in the process of network packets distributing. The simulation results show that the algorithm can ensure fairness and timeliness of network transmission, as well as improve ad hoc network resource integrated utilization efficiency.

  11. Will electrical cyber-physical interdependent networks undergo first-order transition under random attacks?

    Science.gov (United States)

    Ji, Xingpei; Wang, Bo; Liu, Dichen; Dong, Zhaoyang; Chen, Guo; Zhu, Zhenshan; Zhu, Xuedong; Wang, Xunting

    2016-10-01

    Whether the realistic electrical cyber-physical interdependent networks will undergo first-order transition under random failures still remains a question. To reflect the reality of Chinese electrical cyber-physical system, the "partial one-to-one correspondence" interdependent networks model is proposed and the connectivity vulnerabilities of three realistic electrical cyber-physical interdependent networks are analyzed. The simulation results show that due to the service demands of power system the topologies of power grid and its cyber network are highly inter-similar which can effectively avoid the first-order transition. By comparing the vulnerability curves between electrical cyber-physical interdependent networks and its single-layer network, we find that complex network theory is still useful in the vulnerability analysis of electrical cyber-physical interdependent networks.

  12. The Albuquerque Seismological Laboratory Data Quality Analyzer

    Science.gov (United States)

    Ringler, A. T.; Hagerty, M.; Holland, J.; Gee, L. S.; Wilson, D.

    2013-12-01

    The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several efforts underway to improve data quality at its stations. The Data Quality Analyzer (DQA) is one such development. The DQA is designed to characterize station data quality in a quantitative and automated manner. Station quality is based on the evaluation of various metrics, such as timing quality, noise levels, sensor coherence, and so on. These metrics are aggregated into a measurable grade for each station. The DQA consists of a website, a metric calculator (Seedscan), and a PostgreSQL database. The website allows the user to make requests for various time periods, review specific networks and stations, adjust weighting of the station's grade, and plot metrics as a function of time. The website dynamically loads all station data from a PostgreSQL database. The database is central to the application; it acts as a hub where metric values and limited station descriptions are stored. Data is stored at the level of one sensor's channel per day. The database is populated by Seedscan. Seedscan reads and processes miniSEED data, to generate metric values. Seedscan, written in Java, compares hashes of metadata and data to detect changes and perform subsequent recalculations. This ensures that the metric values are up to date and accurate. Seedscan can be run in a scheduled task or on demand by way of a config file. It will compute metrics specified in its configuration file. While many metrics are currently in development, some are completed and being actively used. These include: availability, timing quality, gap count, deviation from the New Low Noise Model, deviation from a station's noise baseline, inter-sensor coherence, and data-synthetic fits. In all, 20 metrics are planned, but any number could be added. ASL is actively using the DQA on a daily basis for station diagnostics and evaluation. As Seedscan is scheduled to run every night, data quality analysts are able to then use the

  13. Semantic analyzability in children's understanding of idioms.

    Science.gov (United States)

    Gibbs, R W

    1991-06-01

    This study investigated the role of semantic analyzability in children's understanding of idioms. Kindergartners and first, third, and fourth graders listened to idiomatic expressions either alone or at the end of short story contexts. Their task was to explain verbally the intended meanings of these phrases and then to choose their correct idiomatic interpretations. The idioms presented to the children differed in their degree of analyzability. Some idioms were highly analyzable or decomposable, with the meanings of their parts contributing independently to their overall figurative meanings. Other idioms were nondecomposable because it was difficult to see any relation between a phrase's individual components and the idiom's figurative meaning. The results showed that younger children (kindergartners and first graders) understood decomposable idioms better than they did nondecomposable phrases. Older children (third and fourth graders) understood both kinds of idioms equally well in supporting contexts, but were better at interpreting decomposable idioms than they were at understanding nondecomposable idioms without contextual information. These findings demonstrate that young children better understand idiomatic phrases whose individual parts independently contribute to their overall figurative meanings.

  14. Handheld Fluorescence Microscopy based Flow Analyzer.

    Science.gov (United States)

    Saxena, Manish; Jayakumar, Nitin; Gorthi, Sai Siva

    2016-03-01

    Fluorescence microscopy has the intrinsic advantages of favourable contrast characteristics and high degree of specificity. Consequently, it has been a mainstay in modern biological inquiry and clinical diagnostics. Despite its reliable nature, fluorescence based clinical microscopy and diagnostics is a manual, labour intensive and time consuming procedure. The article outlines a cost-effective, high throughput alternative to conventional fluorescence imaging techniques. With system level integration of custom-designed microfluidics and optics, we demonstrate fluorescence microscopy based imaging flow analyzer. Using this system we have imaged more than 2900 FITC labeled fluorescent beads per minute. This demonstrates high-throughput characteristics of our flow analyzer in comparison to conventional fluorescence microscopy. The issue of motion blur at high flow rates limits the achievable throughput in image based flow analyzers. Here we address the issue by computationally deblurring the images and show that this restores the morphological features otherwise affected by motion blur. By further optimizing concentration of the sample solution and flow speeds, along with imaging multiple channels simultaneously, the system is capable of providing throughput of about 480 beads per second.

  15. Effects of Neuromodulation on Excitatory-Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

    Science.gov (United States)

    Rich, Scott; Zochowski, Michal; Booth, Victoria

    2018-01-01

    Acetylcholine (ACh), one of the brain's most potent neuromodulators, can affect intrinsic neuron properties through blockade of an M-type potassium current. The effect of ACh on excitatory and inhibitory cells with this potassium channel modulates their membrane excitability, which in turn affects their tendency to synchronize in networks. Here, we study the resulting changes in dynamics in networks with inter-connected excitatory and inhibitory populations (E-I networks), which are ubiquitous in the brain. Utilizing biophysical models of E-I networks, we analyze how the network connectivity structure in terms of synaptic connectivity alters the influence of ACh on the generation of synchronous excitatory bursting. We investigate networks containing all combinations of excitatory and inhibitory cells with high (Type I properties) or low (Type II properties) modulatory tone. To vary network connectivity structure, we focus on the effects of the strengths of inter-connections between excitatory and inhibitory cells (E-I synapses and I-E synapses), and the strengths of intra-connections among excitatory cells (E-E synapses) and among inhibitory cells (I-I synapses). We show that the presence of ACh may or may not affect the generation of network synchrony depending on the network connectivity. Specifically, strong network inter-connectivity induces synchronous excitatory bursting regardless of the cellular propensity for synchronization, which aligns with predictions of the PING model. However, when a network's intra-connectivity dominates its inter-connectivity, the propensity for synchrony of either inhibitory or excitatory cells can determine the generation of network-wide bursting.

  16. University of Tennessee deploys force10 C-series to analyze data from CERN's Large Hadron Collider

    CERN Multimedia

    2007-01-01

    "Force20 networks, the pioneer in building and securing reliable networks, today announced that the University of Tennessee physics department has deployed the C300 resilient switch to analyze data form CERN's Large Hadron Collider." (1 page)

  17. Evolution of regulatory networks towards adaptability and stability in a changing environment

    Science.gov (United States)

    Lee, Deok-Sun

    2014-11-01

    Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.

  18. Social Networks and Technology Adoption

    OpenAIRE

    Hogset, Heidi

    2005-01-01

    This study analyzes social network effects on Kenyan smallholders' decision to adopt improved natural resource management techniques. These effects are decomposed into effects from social influence and learning through networks (strong ties), group effects, weak ties effects, informal finance, and conflicts arising from technological externalities, controlling for non-network effects.

  19. Tribological properties and morphology of bimodal elastomeric nitrile butadiene rubber networks

    International Nuclear Information System (INIS)

    Guo, Yin; Wang, Jiaxu; Li, Kang; Ding, Xingwu

    2013-01-01

    Highlights: • Bimodal elastomeric NBR as a new material was developed. • The structure of bimodal elastomeric NBR networks was determined. • The relationship between structure and mechanical properties was investigated. • The tribological properties and mechanisms of bimodal NBR were analyzed. • The benefits of bimodal NBR in the field of tribology were discussed. - Abstract: Bimodal nitrile butadiene rubber (NBR) was examined in this study. The molecular structure was determined by dynamic mechanical analysis and transmission electron microscopy. The relationship between the structure and the mechanical properties related to elastomeric tribological properties was investigated. The properties and the mechanisms of friction and wear of bimodal elastomeric NBR networks were also analyzed. The lubricating characteristics of bimodal NBR networks were revealed based on the mechanisms of friction and wear. Results show that bimodal NBR networks are similar to bimodal polydimethylsiloxane networks. The form and density of the network structure can be controlled from elastomeric networks to thermosetting resin networks. The mechanical properties of bimodal NBR networks, such as elasticity, elongation at break, fatigue characteristic, tensile strength, elastic modulus, and thermal stability can be precisely controlled following the variation in network structure. The friction, wear, and lubrication of bimodal NBR networks can be clearly described according to the principles of tribology. Common elastomers cannot simultaneously reduce friction and wear because of the different mechanisms of friction and wear; however, bimodal elastomer networks can efficiently address this problem

  20. What Hold us Together? Analyzing Biotech Field Formation

    Directory of Open Access Journals (Sweden)

    Jackeline Amantino de Andrade

    2011-03-01

    Full Text Available This article proposes to analyze the formation of biotechnological field bringing actor-network theory’s lens as contribution. Based on conclusions of studies developed by Walter Powell and colleagues it was held a research to analyze the diversity of institutional relations that are active by hemophilia therapies, the principle of generalized symmetry adopted for actor-network theory is highlight to identify how socio-technical associations are assembled. Besides the interorganizational relations, research’s findings indicate the scientific and technological contents have a significant mediating role to create and sustain those connections of knowledge. So, it is emphasized the need of a boarder theoretical discussion to enlarge explanations about the dynamics of organizational fields as well as innovation processes.

  1. Determinants of Network Outcomes

    DEFF Research Database (Denmark)

    Ysa, Tamyko; Sierra, Vicenta; Esteve, Marc

    2014-01-01

    The literature on network management is extensive. However, it generally explores network structures, neglecting the impact of management strategies. In this article we assess the effect of management strategies on network outcomes, providing empirical evidence from 119 urban revitalization...... networks. We go beyond current work by testing a path model for the determinants of network outcomes and considering the interactions between the constructs: management strategies, trust, complexity, and facilitative leadership. Our results suggest that management strategies have a strong effect on network...... outcomes and that they enhance the level of trust. We also found that facilitative leadership has a positive impact on network management as well as on trust in the network. Our findings also show that complexity has a negative impact on trust. A key finding of our research is that managers may wield more...

  2. Reciprocity of weighted networks.

    Science.gov (United States)

    Squartini, Tiziano; Picciolo, Francesco; Ruzzenenti, Franco; Garlaschelli, Diego

    2013-01-01

    In directed networks, reciprocal links have dramatic effects on dynamical processes, network growth, and higher-order structures such as motifs and communities. While the reciprocity of binary networks has been extensively studied, that of weighted networks is still poorly understood, implying an ever-increasing gap between the availability of weighted network data and our understanding of their dyadic properties. Here we introduce a general approach to the reciprocity of weighted networks, and define quantities and null models that consistently capture empirical reciprocity patterns at different structural levels. We show that, counter-intuitively, previous reciprocity measures based on the similarity of mutual weights are uninformative. By contrast, our measures allow to consistently classify different weighted networks according to their reciprocity, track the evolution of a network's reciprocity over time, identify patterns at the level of dyads and vertices, and distinguish the effects of flux (im)balances or other (a)symmetries from a true tendency towards (anti-)reciprocation.

  3. Organization of complex networks

    Science.gov (United States)

    Kitsak, Maksim

    Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how

  4. QLab 3 show control projects for live performances & installations

    CERN Document Server

    Hopgood, Jeromy

    2013-01-01

    Used from Broadway to Britain's West End, QLab software is the tool of choice for many of the world's most prominent sound, projection, and integrated media designers. QLab 3 Show Control: Projects for Live Performances & Installations is a project-based book on QLab software covering sound, video, and show control. With information on both sound and video system basics and the more advanced functions of QLab such as MIDI show control, new OSC capabilities, networking, video effects, and microphone integration, each chapter's specific projects will allow you to learn the software's capabilitie

  5. Optimal transport on supply-demand networks.

    Science.gov (United States)

    Chen, Yu-Han; Wang, Bing-Hong; Zhao, Li-Chao; Zhou, Changsong; Zhou, Tao

    2010-06-01

    In the literature, transport networks are usually treated as homogeneous networks, that is, every node has the same function, simultaneously providing and requiring resources. However, some real networks, such as power grids and supply chain networks, show a far different scenario in which nodes are classified into two categories: supply nodes provide some kinds of services, while demand nodes require them. In this paper, we propose a general transport model for these supply-demand networks, associated with a criterion to quantify their transport capacities. In a supply-demand network with heterogeneous degree distribution, its transport capacity strongly depends on the locations of supply nodes. We therefore design a simulated annealing algorithm to find the near optimal configuration of supply nodes, which remarkably enhances the transport capacity compared with a random configuration and outperforms the degree target algorithm, the betweenness target algorithm, and the greedy method. This work provides a start point for systematically analyzing and optimizing transport dynamics on supply-demand networks.

  6. Disease network of mental disorders in Korea.

    Science.gov (United States)

    Choi, Myoungje; Lee, Dong-Woo; Cho, Maeng Je; Park, Jee Eun; Gim, Minsook

    2015-12-01

    Network medicine considers networks among genes, diseases, and individuals. Networks of mental disorders remain poorly understood, despite their high comorbidity. In this study, a network of mental disorders in Korea was constructed to offer a complementary approach to treatment. Data on the prevalence and morbidity of mental disorders were obtained from the 2006 and 2011 Korean Epidemiologic Catchment Area Study, including 22 psychiatric disorders. Nodes in the network were disease phenotypes identified by Diagnostic and Statistical Manual of Mental Disorders-IV, and the links connected phenotypes showing significant comorbidity. Odds ratios were used to quantify the distance between disease pairs. Network centrality was analyzed with and without weighting of the links between disorders. Degree centrality was correlated with suicidal behaviors and use of mental health services. In 2011 and 2006, degree centrality was highest for major depressive disorder, followed by nicotine dependence and generalized anxiety disorder (2011) or alcohol dependence (2006). Weighted degree centrality was highest in conversion disorder in both years. Therefore, major depressive disorder and nicotine dependence are highly connected to other mental disorders in Korea, indicating their comorbidity and possibility of shared biological mechanisms. The use of networks could enhance the understanding of mental disorders to provide effective mental health services.

  7. Complex interdependent supply chain networks: Cascading failure and robustness

    Science.gov (United States)

    Tang, Liang; Jing, Ke; He, Jie; Stanley, H. Eugene

    2016-02-01

    A supply chain network is a typical interdependent network composed of an undirected cyber-layer network and a directed physical-layer network. To analyze the robustness of this complex interdependent supply chain network when it suffers from disruption events that can cause nodes to fail, we use a cascading failure process that focuses on load propagation. We consider load propagation via connectivity links as node failure spreads through one layer of an interdependent network, and we develop a priority redistribution strategy for failed loads subject to flow constraint. Using a giant component function and a one-to-one directed interdependence relation between nodes in a cyber-layer network and physical-layer network, we construct time-varied functional equations to quantify the dynamic process of failed loads propagation in an interdependent network. Finally, we conduct a numerical simulation for two cases, i.e., single node removal and multiple node removal at the initial disruption. The simulation results show that when we increase the number of removed nodes in an interdependent supply chain network its robustness undergoes a first-order discontinuous phase transition, and that even removing a small number of nodes will cause it to crash.

  8. Investigation of road network features and safety performance.

    Science.gov (United States)

    Wang, Xuesong; Wu, Xingwei; Abdel-Aty, Mohamed; Tremont, Paul J

    2013-07-01

    The analysis of road network designs can provide useful information to transportation planners as they seek to improve the safety of road networks. The objectives of this study were to compare and define the effective road network indices and to analyze the relationship between road network structure and traffic safety at the level of the Traffic Analysis Zone (TAZ). One problem in comparing different road networks is establishing criteria that can be used to scale networks in terms of their structures. Based on data from Orange and Hillsborough Counties in Florida, road network structural properties within TAZs were scaled using 3 indices: Closeness Centrality, Betweenness Centrality, and Meshedness Coefficient. The Meshedness Coefficient performed best in capturing the structural features of the road network. Bayesian Conditional Autoregressive (CAR) models were developed to assess the safety of various network configurations as measured by total crashes, crashes on state roads, and crashes on local roads. The models' results showed that crash frequencies on local roads were closely related to factors within the TAZs (e.g., zonal network structure, TAZ population), while crash frequencies on state roads were closely related to the road and traffic features of state roads. For the safety effects of different networks, the Grid type was associated with the highest frequency of crashes, followed by the Mixed type, the Loops & Lollipops type, and the Sparse type. This study shows that it is possible to develop a quantitative scale for structural properties of a road network, and to use that scale to calculate the relationships between network structural properties and safety. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. RMOD: a tool for regulatory motif detection in signaling network.

    Directory of Open Access Journals (Sweden)

    Jinki Kim

    Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  10. Controlling the dynamics of multi-state neural networks

    International Nuclear Information System (INIS)

    Jin, Tao; Zhao, Hong

    2008-01-01

    In this paper, we first analyze the distribution of local fields (DLF) which is induced by the memory patterns in the Q-Ising model. It is found that the structure of the DLF is closely correlated with the network dynamics and the system performance. However, the design rule adopted in the Q-Ising model, like the other rules adopted for multi-state neural networks with associative memories, cannot be applied to directly control the DLF for a given set of memory patterns, and thus cannot be applied to further study the relationships between the structure of the DLF and the dynamics of the network. We then extend a design rule, which was presented recently for designing binary-state neural networks, to make it suitable for designing general multi-state neural networks. This rule is able to control the structure of the DLF as expected. We show that controlling the DLF not only can affect the dynamic behaviors of the multi-state neural networks for a given set of memory patterns, but also can improve the storage capacity. With the change of the DLF, the network shows very rich dynamic behaviors, such as the 'chaos phase', the 'memory phase', and the 'mixture phase'. These dynamic behaviors are also observed in the binary-state neural networks; therefore, our results imply that they may be the universal behaviors of feedback neural networks

  11. Artificial intelligence for analyzing orthopedic trauma radiographs.

    Science.gov (United States)

    Olczak, Jakub; Fahlberg, Niklas; Maki, Atsuto; Razavian, Ali Sharif; Jilert, Anthony; Stark, André; Sköldenberg, Olof; Gordon, Max

    2017-12-01

    Background and purpose - Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never been applied in an orthopedic setting, and in this study we sought to determine the feasibility of using deep learning for skeletal radiographs. Methods - We extracted 256,000 wrist, hand, and ankle radiographs from Danderyd's Hospital and identified 4 classes: fracture, laterality, body part, and exam view. We then selected 5 openly available deep learning networks that were adapted for these images. The most accurate network was benchmarked against a gold standard for fractures. We furthermore compared the network's performance with 2 senior orthopedic surgeons who reviewed images at the same resolution as the network. Results - All networks exhibited an accuracy of at least 90% when identifying laterality, body part, and exam view. The final accuracy for fractures was estimated at 83% for the best performing network. The network performed similarly to senior orthopedic surgeons when presented with images at the same resolution as the network. The 2 reviewer Cohen's kappa under these conditions was 0.76. Interpretation - This study supports the use for orthopedic radiographs of artificial intelligence, which can perform at a human level. While current implementation lacks important features that surgeons require, e.g. risk of dislocation, classifications, measurements, and combining multiple exam views, these problems have technical solutions that are waiting to be implemented for orthopedics.

  12. Microsoft Windows networking essentials

    CERN Document Server

    Gibson, Darril

    2011-01-01

    The core concepts and technologies of Windows networking Networking can be a complex topic, especially for those new to the field of IT. This focused, full-color book takes a unique approach to teaching Windows networking to beginners by stripping down a network to its bare basics, thereby making each topic clear and easy to understand. Focusing on the new Microsoft Technology Associate (MTA) program, this book pares down to just the essentials, showing beginners how to gain a solid foundation for understanding networking concepts upon which more advanced topics and technologies can be built.

  13. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  14. Bayesian Networks and Influence Diagrams

    DEFF Research Database (Denmark)

    Kjærulff, Uffe Bro; Madsen, Anders Læsø

     Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...

  15. Optimization of robustness of interdependent network controllability by redundant design.

    Directory of Open Access Journals (Sweden)

    Zenghu Zhang

    Full Text Available Controllability of complex networks has been a hot topic in recent years. Real networks regarded as interdependent networks are always coupled together by multiple networks. The cascading process of interdependent networks including interdependent failure and overload failure will destroy the robustness of controllability for the whole network. Therefore, the optimization of the robustness of interdependent network controllability is of great importance in the research area of complex networks. In this paper, based on the model of interdependent networks constructed first, we determine the cascading process under different proportions of node attacks. Then, the structural controllability of interdependent networks is measured by the minimum driver nodes. Furthermore, we propose a parameter which can be obtained by the structure and minimum driver set of interdependent networks under different proportions of node attacks and analyze the robustness for interdependent network controllability. Finally, we optimize the robustness of interdependent network controllability by redundant design including node backup and redundancy edge backup and improve the redundant design by proposing different strategies according to their cost. Comparative strategies of redundant design are conducted to find the best strategy. Results shows that node backup and redundancy edge backup can indeed decrease those nodes suffering from failure and improve the robustness of controllability. Considering the cost of redundant design, we should choose BBS (betweenness-based strategy or DBS (degree based strategy for node backup and HDF(high degree first for redundancy edge backup. Above all, our proposed strategies are feasible and effective at improving the robustness of interdependent network controllability.

  16. Information theoretic description of networks

    Science.gov (United States)

    Wilhelm, Thomas; Hollunder, Jens

    2007-11-01

    We present a new information theoretic approach for network characterizations. It is developed to describe the general type of networks with n nodes and L directed and weighted links, i.e., it also works for the simpler undirected and unweighted networks. The new information theoretic measures for network characterizations are based on a transmitter-receiver analogy of effluxes and influxes. Based on these measures, we classify networks as either complex or non-complex and as either democracy or dictatorship networks. Directed networks, in particular, are furthermore classified as either information spreading and information collecting networks. The complexity classification is based on the information theoretic network complexity measure medium articulation (MA). It is proven that special networks with a medium number of links ( L∼n1.5) show the theoretical maximum complexity MA=(log n)2/2. A network is complex if its MA is larger than the average MA of appropriately randomized networks: MA>MAr. A network is of the democracy type if its redundancy Rdictatorship network. In democracy networks all nodes are, on average, of similar importance, whereas in dictatorship networks some nodes play distinguished roles in network functioning. In other words, democracy networks are characterized by cycling of information (or mass, or energy), while in dictatorship networks there is a straight through-flow from sources to sinks. The classification of directed networks into information spreading and information collecting networks is based on the conditional entropies of the considered networks ( H(A/B)=uncertainty of sender node if receiver node is known, H(B/A)=uncertainty of receiver node if sender node is known): if H(A/B)>H(B/A), it is an information collecting network, otherwise an information spreading network. Finally, different real networks (directed and undirected, weighted and unweighted) are classified according to our general scheme.

  17. SOCIAL KNOWLEDGE MANAGEMENT, RESEARCH AND INNOVATION NETWORKS FOR INCLUSION

    Directory of Open Access Journals (Sweden)

    Sandra Ace vedo Zapata

    2017-09-01

    Full Text Available The objective is to describe the social management of knowledge through research and innovation networks to promote social inclusion. The reflection of the exploratory stage is presented within the doctoral thesis analyzing the challenges of the universities in the achievement of social inclusion with networks of research and innovation. A descriptive work was done, with documentary tracking, systematization and analysis. The findings show that it is necessary to articulate efforts in interdisciplinary and transdisciplinary networks with different actors: state, company, education, scientists, technologists and vulnerable, excluded populations, to build policies and strategies for social inclusion.

  18. Throughput Capacity of Ad Hoc Networks with Route Discovery

    Directory of Open Access Journals (Sweden)

    Blum Rick S

    2007-01-01

    Full Text Available Throughput capacity of large ad hoc networks has been shown to scale adversely with the size of network . However the need for the nodes to find or repair routes has not been analyzed in this context. In this paper, we explicitly take route discovery into account and obtain the scaling law for the throughput capacity under general assumptions on the network environment, node behavior, and the quality of route discovery algorithms. We also discuss a number of possible scenarios and show that the need for route discovery may change the scaling for the throughput capacity.

  19. Characteristics of group networks in the KOSPI and the KOSDAQ

    Science.gov (United States)

    Kim, Kyungsik; Ko, Jeung-Su; Yi, Myunggi

    2012-02-01

    We investigate the main feature of group networks in the KOSPI and KOSDAQ of Korean financial markets and analyze daily cross-correlations between price fluctuations for the 5-year time period from 2006 to 2010. We discuss the stabilities by undressing the market-wide effect using the Markowitz multi-factor model and the network-based approach. In particular we ascertain the explicit list of significant firms in the few largest eigenvectors from the undressed correlation matrix. Finally, we show the structure of group correlation by applying a network-based approach. In addition, the relation between market capitalizations and businesses is examined.

  20. 802.11s Wireless Mesh Network Visualization Application

    Science.gov (United States)

    Mauldin, James Alexander

    2014-01-01

    Results of past experimentation at NASA Johnson Space Center showed that the IEEE 802.11s standard has better performance than the widely implemented alternative protocol B.A.T.M.A.N (Better Approach to Mobile Ad hoc Networking). 802.11s is now formally incorporated into the Wi- Fi 802.11-2012 standard, which specifies a hybrid wireless mesh networking protocol (HWMP). In order to quickly analyze changes to the routing algorithm and to support optimizing the mesh network behavior for our intended application a visualization tool was developed by modifying and integrating open source tools.

  1. Improving respiration measurements with gas exchange analyzers.

    Science.gov (United States)

    Montero, R; Ribas-Carbó, M; Del Saz, N F; El Aou-Ouad, H; Berry, J A; Flexas, J; Bota, J

    2016-12-01

    Dark respiration measurements with open-flow gas exchange analyzers are often questioned for their low accuracy as their low values often reach the precision limit of the instrument. Respiration was measured in five species, two hypostomatous (Vitis Vinifera L. and Acanthus mollis) and three amphistomatous, one with similar amount of stomata in both sides (Eucalyptus citriodora) and two with different stomata density (Brassica oleracea and Vicia faba). CO 2 differential (ΔCO 2 ) increased two-fold with no change in apparent R d , when the two leaves with higher stomatal density faced outside. These results showed a clear effect of the position of stomata on ΔCO 2 . Therefore, it can be concluded that leaf position is important to guarantee the improvement of respiration measurements increasing ΔCO 2 without affecting the respiration results by leaf or mass units. This method will help to increase the accuracy of leaf respiration measurements using gas exchange analyzers. Copyright © 2016 Elsevier GmbH. All rights reserved.

  2. Solar Probe ANalyzer for Ions - Laboratory Performance

    Science.gov (United States)

    Livi, R.; Larson, D. E.; Kasper, J. C.; Korreck, K. E.; Whittlesey, P. L.

    2017-12-01

    The Parker Solar Probe (PSP) mission is a heliospheric satellite that will orbit the Sun closer than any prior mission to date with a perihelion of 35 solar radii (RS) and an aphelion of 10 RS. PSP includes the Solar Wind Electrons Alphas and Protons (SWEAP) instrument suite, which in turn consists of four instruments: the Solar Probe Cup (SPC) and three Solar Probe ANalyzers (SPAN) for ions and electrons. Together, this suite will take local measurements of particles and electromagnetic fields within the Sun's corona. SPAN-Ai has completed flight calibration and spacecraft integration and is set to be launched in July of 2018. The main mode of operation consists of an electrostatic analyzer (ESA) at its aperture followed by a Time-of-Flight section to measure the energy and mass per charge (m/q) of the ambient ions. SPAN-Ai's main objective is to measure solar wind ions within an energy range of 5 eV - 20 keV, a mass/q between 1-60 [amu/q] and a field of view of 2400x1200. Here we will show flight calibration results and performance.

  3. Analyzing rare diseases terms in biomedical terminologies

    Directory of Open Access Journals (Sweden)

    Erika Pasceri

    2012-03-01

    Full Text Available Rare disease patients too often face common problems, including the lack of access to correct diagnosis, lack of quality information on the disease, lack of scientific knowledge of the disease, inequities and difficulties in access to treatment and care. These things could be changed by implementing a comprehensive approach to rare diseases, increasing international cooperation in scientific research, by gaining and sharing scientific knowledge about and by developing tools for extracting and sharing knowledge. A significant aspect to analyze is the organization of knowledge in the biomedical field for the proper management and recovery of health information. For these purposes, the sources needed have been acquired from the Office of Rare Diseases Research, the National Organization of Rare Disorders and Orphanet, organizations that provide information to patients and physicians and facilitate the exchange of information among different actors involved in this field. The present paper shows the representation of rare diseases terms in biomedical terminologies such as MeSH, ICD-10, SNOMED CT and OMIM, leveraging the fact that these terminologies are integrated in the UMLS. At the first level, it was analyzed the overlap among sources and at a second level, the presence of rare diseases terms in target sources included in UMLS, working at the term and concept level. We found that MeSH has the best representation of rare diseases terms.

  4. Analyzing Demand: Hegemonic Masculinity and Feminine Prostitution

    Directory of Open Access Journals (Sweden)

    Beatriz Ranea Triviño

    2016-12-01

    Full Text Available In this article, it is presented an exploratory research in which we analyzed the relationship between the construction of hegemonic masculinity and consumption of female prostitution. We have focused our attention on the experiences, attitudes and perceptions of young heterosexual men who have ever paid for sex. Following with a quantitative method of analysis, we conducted six semi-structured interviews with men between 18 to 35 years old. The analysis of the interviews shows the different demographic characteristics, such as, frequency of payment for sexual services, diversity of motivations, spaces where prostitutes are searched, opinions on prostitution and prostitutes. The main conclusions of this study are that the discourses of the interviewees reproduce gender stereotypes and gender sexual roles. And it is suggested that prostitution can be interpreted as a scenario where these men performance their hegemonic masculinity.

  5. Using wavelet features for analyzing gamma lines

    International Nuclear Information System (INIS)

    Medhat, M.E.; Abdel-hafiez, A.; Hassan, M.F.; Ali, M.A.; Uzhinskii, V.V.

    2004-01-01

    Data processing methods for analyzing gamma ray spectra with symmetric bell-shaped peaks form are considered. In many cases the peak form is symmetrical bell shaped in particular a Gaussian case is the most often used due to many physical reasons. The problem is how to evaluate parameters of such peaks, i.e. their positions, amplitudes and also their half-widths, that is for a single peak and overlapped peaks. Through wavelet features by using Marr wavelet (Mexican Hat) as a correlation method, it could be to estimate the optimal wavelet parameters and to locate peaks in the spectrum. The performance of the proposed method and others shows a better quality of wavelet transform method

  6. Network Fault Diagnosis Using DSM

    Institute of Scientific and Technical Information of China (English)

    Jiang Hao; Yan Pu-liu; Chen Xiao; Wu Jing

    2004-01-01

    Difference similitude matrix (DSM) is effective in reducing information system with its higher reduction rate and higher validity. We use DSM method to analyze the fault data of computer networks and obtain the fault diagnosis rules. Through discretizing the relative value of fault data, we get the information system of the fault data. DSM method reduces the information system and gets the diagnosis rules. The simulation with the actual scenario shows that the fault diagnosis based on DSM can obtain few and effective rules.

  7. Serial Network Flow Monitor

    Science.gov (United States)

    Robinson, Julie A.; Tate-Brown, Judy M.

    2009-01-01

    Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

  8. Synchronization on effective networks

    International Nuclear Information System (INIS)

    Zhou Tao; Zhao Ming; Zhou Changsong

    2010-01-01

    The study of network synchronization has attracted increasing attentionrecently. In this paper, we strictly define a class of networks, namely effective networks, which are synchronizable and orientable networks. We can prove that all the effective networks with the same size have the same spectra, and are of the best synchronizability according to the master stability analysis. However, it is found that the synchronization time for different effective networks can be quite different. Further analysis shows that the key ingredient affecting the synchronization time is the maximal depth of an effective network: the larger depth results in a longer synchronization time. The secondary factor is the number of links. The increasing number of links connecting nodes in the same layer (horizontal links) will lead to longer synchronization time, whereas the increasing number of links connecting nodes in neighboring layers (vertical links) will accelerate the synchronization. Our analysis of the relationship between the structure and synchronization properties of the original and effective networks shows that the purely directed effective network can provide an approximation of the original weighted network with normalized input strength. Our findings provide insights into the roles of depth, horizontal and vertical links in the synchronizing process, and suggest that the spectral analysis is helpful yet insufficient for the comprehensive understanding of network synchronization.

  9. Synchronization on effective networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhou Tao [Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 610054 (China); Zhao Ming [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Zhou Changsong, E-mail: cszhou@hkbu.edu.h [Department of Physics, Hong Kong Baptist University, Kowloon Tong (Hong Kong)

    2010-04-15

    The study of network synchronization has attracted increasing attentionrecently. In this paper, we strictly define a class of networks, namely effective networks, which are synchronizable and orientable networks. We can prove that all the effective networks with the same size have the same spectra, and are of the best synchronizability according to the master stability analysis. However, it is found that the synchronization time for different effective networks can be quite different. Further analysis shows that the key ingredient affecting the synchronization time is the maximal depth of an effective network: the larger depth results in a longer synchronization time. The secondary factor is the number of links. The increasing number of links connecting nodes in the same layer (horizontal links) will lead to longer synchronization time, whereas the increasing number of links connecting nodes in neighboring layers (vertical links) will accelerate the synchronization. Our analysis of the relationship between the structure and synchronization properties of the original and effective networks shows that the purely directed effective network can provide an approximation of the original weighted network with normalized input strength. Our findings provide insights into the roles of depth, horizontal and vertical links in the synchronizing process, and suggest that the spectral analysis is helpful yet insufficient for the comprehensive understanding of network synchronization.

  10. CRISP90 - SOFTWARE DESIGN ANALYZER SYSTEM

    Science.gov (United States)

    Tausworthe, R. C.

    1994-01-01

    The CRISP90 Software Design Analyzer System, an update of CRISP-80, is a set of programs forming a software design and documentation tool which supports top-down, hierarchic, modular, structured design and programming methodologies. The quality of a computer program can often be significantly influenced by the design medium in which the program is developed. The medium must foster the expression of the programmer's ideas easily and quickly, and it must permit flexible and facile alterations, additions, and deletions to these ideas as the design evolves. The CRISP90 software design analyzer system was developed to provide the PDL (Programmer Design Language) programmer with such a design medium. A program design using CRISP90 consists of short, English-like textual descriptions of data, interfaces, and procedures that are imbedded in a simple, structured, modular syntax. The display is formatted into two-dimensional, flowchart-like segments for a graphic presentation of the design. Together with a good interactive full-screen editor or word processor, the CRISP90 design analyzer becomes a powerful tool for the programmer. In addition to being a text formatter, the CRISP90 system prepares material that would be tedious and error prone to extract manually, such as a table of contents, module directory, structure (tier) chart, cross-references, and a statistics report on the characteristics of the design. Referenced modules are marked by schematic logic symbols to show conditional, iterative, and/or concurrent invocation in the program. A keyword usage profile can be generated automatically and glossary definitions inserted into the output documentation. Another feature is the capability to detect changes that were made between versions. Thus, "change-bars" can be placed in the output document along with a list of changed pages and a version history report. Also, items may be marked as "to be determined" and each will appear on a special table until the item is

  11. Networks around entrepreneurs

    DEFF Research Database (Denmark)

    Bertelsen, Rasmus Gjedssø; Ashourizadeh, Shayegheh; Jensen, Kent Wickstrøm

    2017-01-01

    Purpose: Entrepreneurs are networking with others to get advice for their businesses. The networking differs between men and women; notably, men are more often networking in the public sphere and women are more often networking in the private sphere. The aim here is to account for how such gender......Purpose: Entrepreneurs are networking with others to get advice for their businesses. The networking differs between men and women; notably, men are more often networking in the public sphere and women are more often networking in the private sphere. The aim here is to account for how...... such gendering of entrepreneurs’ networks differ between societies and cultures. Research Design: Based on survey data from the Global Entrepreneurships Monitor, a sample of 16,365 entrepreneurs is used to compare the gendering of entrepreneurs’ networks in China, and five countries largely located around...... the Persian Gulf, namely Yemen, Iran, Saudi Arabia, Qatar and United Arab Emirates. Findings: Analyses show that female entrepreneurs tend to have slightly larger private sphere networks than male entrepreneurs. The differences between male and female entrepreneurs’ networking in the public sphere...

  12. How People Interact in Evolving Online Affiliation Networks

    Science.gov (United States)

    Gallos, Lazaros K.; Rybski, Diego; Liljeros, Fredrik; Havlin, Shlomo; Makse, Hernán A.

    2012-07-01

    The study of human interactions is of central importance for understanding the behavior of individuals, groups, and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links, and we analyze quantitatively the tendencies used to create ties in these evolving online affiliation networks. We show that an accurate estimation of these probabilistic tendencies can be achieved only by following the time evolution of the network. Inferences about the reason for the existence of links using statistical analysis of network snapshots must therefore be made with great caution. Here, we start by characterizing every single link when the tie was established in the network. This information allows us to describe the probabilistic tendencies of tie formation and extract meaningful sociological conclusions. We also find significant differences in behavioral traits in the social tendencies among individuals according to their degree of activity, gender, age, popularity, and other attributes. For instance, in the particular data sets analyzed here, we find that women reciprocate connections 3 times as much as men and that this difference increases with age. Men tend to connect with the most popular people more often than women do, across all ages. On the other hand, triangular tie tendencies are similar, independent of gender, and show an increase with age. These results require further validation in other social settings. Our findings can be useful to build models of realistic social network structures and to discover the underlying laws that govern establishment of ties in evolving social networks.

  13. A research on the application of software defined networking in satellite network architecture

    Science.gov (United States)

    Song, Huan; Chen, Jinqiang; Cao, Suzhi; Cui, Dandan; Li, Tong; Su, Yuxing

    2017-10-01

    Software defined network is a new type of network architecture, which decouples control plane and data plane of traditional network, has the feature of flexible configurations and is a direction of the next generation terrestrial Internet development. Satellite network is an important part of the space-ground integrated information network, while the traditional satellite network has the disadvantages of difficult network topology maintenance and slow configuration. The application of SDN technology in satellite network can solve these problems that traditional satellite network faces. At present, the research on the application of SDN technology in satellite network is still in the stage of preliminary study. In this paper, we start with introducing the SDN technology and satellite network architecture. Then we mainly introduce software defined satellite network architecture, as well as the comparison of different software defined satellite network architecture and satellite network virtualization. Finally, the present research status and development trend of SDN technology in satellite network are analyzed.

  14. Automated Root Tracking with "Root System Analyzer"

    Science.gov (United States)

    Schnepf, Andrea; Jin, Meina; Ockert, Charlotte; Bol, Roland; Leitner, Daniel

    2015-04-01

    Crucial factors for plant development are water and nutrient availability in soils. Thus, root architecture is a main aspect of plant productivity and needs to be accurately considered when describing root processes. Images of root architecture contain a huge amount of information, and image analysis helps to recover parameters describing certain root architectural and morphological traits. The majority of imaging systems for root systems are designed for two-dimensional images, such as RootReader2, GiA Roots, SmartRoot, EZ-Rhizo, and Growscreen, but most of them are semi-automated and involve mouse-clicks in each root by the user. "Root System Analyzer" is a new, fully automated approach for recovering root architectural parameters from two-dimensional images of root systems. Individual roots can still be corrected manually in a user interface if required. The algorithm starts with a sequence of segmented two-dimensional images showing the dynamic development of a root system. For each image, morphological operators are used for skeletonization. Based on this, a graph representation of the root system is created. A dynamic root architecture model helps to determine which edges of the graph belong to an individual root. The algorithm elongates each root at the root tip and simulates growth confined within the already existing graph representation. The increment of root elongation is calculated assuming constant growth. For each root, the algorithm finds all possible paths and elongates the root in the direction of the optimal path. In this way, each edge of the graph is assigned to one or more coherent roots. Image sequences of root systems are handled in such a way that the previous image is used as a starting point for the current image. The algorithm is implemented in a set of Matlab m-files. Output of Root System Analyzer is a data structure that includes for each root an identification number, the branching order, the time of emergence, the parent

  15. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

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

    Science.gov (United States)

    Schmitt, Michael

    2004-09-01

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

  17. Recommending Learning Activities in Social Network Using Data Mining Algorithms

    Science.gov (United States)

    Mahnane, Lamia

    2017-01-01

    In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

  18. Minimal-delay traffic grooming for WDM star networks

    Science.gov (United States)

    Choi, Hongsik; Garg, Nikhil; Choi, Hyeong-Ah

    2003-10-01

    All-optical networks face the challenge of reducing slower opto-electronic conversions by managing assignment of traffic streams to wavelengths in an intelligent manner, while at the same time utilizing bandwidth resources to the maximum. This challenge becomes harder in networks closer to the end users that have insufficient data to saturate single wavelengths as well as traffic streams outnumbering the usable wavelengths, resulting in traffic grooming which requires costly traffic analysis at access nodes. We study the problem of traffic grooming that reduces the need to analyze traffic, for a class of network architecture most used by Metropolitan Area Networks; the star network. The problem being NP-complete, we provide an efficient twice-optimal-bound greedy heuristic for the same, that can be used to intelligently groom traffic at the LANs to reduce latency at the access nodes. Simulation results show that our greedy heuristic achieves a near-optimal solution.

  19. GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

    Directory of Open Access Journals (Sweden)

    Ashish Jain

    2012-07-01

    Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.

  20. Modeling the propagation of mobile malware on complex networks

    Science.gov (United States)

    Liu, Wanping; Liu, Chao; Yang, Zheng; Liu, Xiaoyang; Zhang, Yihao; Wei, Zuxue

    2016-08-01

    In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.