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Sample records for network analyzer showing

  1. Statistical network analysis for analyzing policy networks

    DEFF Research Database (Denmark)

    Robins, Garry; Lewis, Jenny; Wang, Peng

    2012-01-01

    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 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...

  2. Methods for Analyzing Pipe Networks

    DEFF Research Database (Denmark)

    Nielsen, Hans Bruun

    1989-01-01

    The governing equations for a general network are first set up and then reformulated in terms of matrices. This is developed to show that the choice of model for the flow equations is essential for the behavior of the iterative method used to solve the problem. It is shown that it is better to fo...... demonstrated that this method offers good starting values for a Newton-Raphson iteration.......The governing equations for a general network are first set up and then reformulated in terms of matrices. This is developed to show that the choice of model for the flow equations is essential for the behavior of the iterative method used to solve the problem. It is shown that it is better...... 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...

  3. Analyzing Worms and Network Traffic using Compression

    OpenAIRE

    Wehner, Stephanie

    2005-01-01

    Internet worms have become a widespread threat to system and network operations. In order to fight them more efficiently, it is necessary to analyze newly discovered worms and attack patterns. This paper shows how techniques based on Kolmogorov Complexity can help in the analysis of internet worms and network traffic. Using compression, different species of worms can be clustered by type. This allows us to determine whether an unknown worm binary could in fact be a later version of an existin...

  4. 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.

  5. Electrical spectrum & network analyzers a practical approach

    CERN Document Server

    Helfrick, Albert D

    1991-01-01

    This book presents fundamentals and the latest techniques of electrical spectrum analysis. It focuses on instruments and techniques used on spectrum and network analysis, rather than theory. The book covers the use of spectrum analyzers, tracking generators, and network analyzers. Filled with practical examples, the book presents techniques that are widely used in signal processing and communications applications, yet are difficult to find in most literature.Key Features* Presents numerous practical examples, including actual spectrum analyzer circuits* Instruction on how to us

  6. 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.

  7. 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.

  8. 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.

  9. CALIBRATION OF ONLINE ANALYZERS USING NEURAL NETWORKS

    Energy Technology Data Exchange (ETDEWEB)

    Rajive Ganguli; Daniel E. Walsh; Shaohai Yu

    2003-12-05

    Neural networks were used to calibrate an online ash analyzer at the Usibelli Coal Mine, Healy, Alaska, by relating the Americium and Cesium counts to the ash content. A total of 104 samples were collected from the mine, with 47 being from screened coal, and the rest being from unscreened coal. Each sample corresponded to 20 seconds of coal on the running conveyor belt. Neural network modeling used the quick stop training procedure. Therefore, the samples were split into training, calibration and prediction subsets. Special techniques, using genetic algorithms, were developed to representatively split the sample into the three subsets. Two separate approaches were tried. In one approach, the screened and unscreened coal was modeled separately. In another, a single model was developed for the entire dataset. No advantage was seen from modeling the two subsets separately. The neural network method performed very well on average but not individually, i.e. though each prediction was unreliable, the average of a few predictions was close to the true average. Thus, the method demonstrated that the analyzers were accurate at 2-3 minutes intervals (average of 6-9 samples), but not at 20 seconds (each prediction).

  10. 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.

  11. 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.

  12. Qualitative networks: a symbolic approach to analyze biological signaling networks

    Directory of Open Access Journals (Sweden)

    Henzinger Thomas A

    2007-01-01

    Full Text Available Abstract Background A central goal of Systems Biology is to model and analyze biological signaling pathways that interact with one another to form complex networks. Here we introduce Qualitative networks, an extension of Boolean networks. With this framework, we use formal verification methods to check whether a model is consistent with the laboratory experimental observations on which it is based. If the model does not conform to the data, we suggest a revised model and the new hypotheses are tested in-silico. Results We consider networks in which elements range over a small finite domain allowing more flexibility than Boolean values, and add target functions that allow to model a rich set of behaviors. We propose a symbolic algorithm for analyzing the steady state of these networks, allowing us to scale up to a system consisting of 144 elements and state spaces of approximately 1086 states. We illustrate the usefulness of this approach through a model of the interaction between the Notch and the Wnt signaling pathways in mammalian skin, and its extensive analysis. Conclusion We introduce an approach for constructing computational models of biological systems that extends the framework of Boolean networks and uses formal verification methods for the analysis of the model. This approach can scale to multicellular models of complex pathways, and is therefore a useful tool for the analysis of complex biological systems. The hypotheses formulated during in-silico testing suggest new avenues to explore experimentally. Hence, this approach has the potential to efficiently complement experimental studies in biology.

  13. 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...

  14. 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.

  15. Analyzing Evolving Social Network 2 (EVOLVE2)

    Science.gov (United States)

    2015-04-01

    social media. We have demonstrated recently that information spread cannot be modeled as an epidemic diffusion. Instead, cognitive constraints, such as...respond to any one stimulus. Cognitive constraints the nature of social interactions and therefore, how central nodes are identified. Now a node’s...link prediction task and their properties. network nodes edges missing density social networks dolphins 62 159 16 0.084 email 1133 5452 545 0.0085

  16. Using graph theory to analyze biological networks

    Science.gov (United States)

    2011-01-01

    Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. PMID:21527005

  17. A framework for analyzing contagion in assortative banking networks.

    Science.gov (United States)

    Hurd, Thomas R; Gleeson, James P; Melnik, Sergey

    2017-01-01

    We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk.

  18. Detecting and analyzing research communities in longitudinal scientific networks.

    Science.gov (United States)

    Leone Sciabolazza, Valerio; Vacca, Raffaele; Kennelly Okraku, Therese; McCarty, Christopher

    2017-01-01

    A growing body of evidence shows that collaborative teams and communities tend to produce the highest-impact scientific work. This paper proposes a new method to (1) Identify collaborative communities in longitudinal scientific networks, and (2) Evaluate the impact of specific research institutes, services or policies on the interdisciplinary collaboration between these communities. First, we apply community-detection algorithms to cross-sectional scientific collaboration networks and analyze different types of co-membership in the resulting subgroups over time. This analysis summarizes large amounts of longitudinal network data to extract sets of research communities whose members have consistently collaborated or shared collaborators over time. Second, we construct networks of cross-community interactions and estimate Exponential Random Graph Models to predict the formation of interdisciplinary collaborations between different communities. The method is applied to longitudinal data on publication and grant collaborations at the University of Florida. Results show that similar institutional affiliation, spatial proximity, transitivity effects, and use of the same research services predict higher degree of interdisciplinary collaboration between research communities. Our application also illustrates how the identification of research communities in longitudinal data and the analysis of cross-community network formation can be used to measure the growth of interdisciplinary team science at a research university, and to evaluate its association with research policies, services or institutes.

  19. Detecting and analyzing research communities in longitudinal scientific networks.

    Directory of Open Access Journals (Sweden)

    Valerio Leone Sciabolazza

    Full Text Available A growing body of evidence shows that collaborative teams and communities tend to produce the highest-impact scientific work. This paper proposes a new method to (1 Identify collaborative communities in longitudinal scientific networks, and (2 Evaluate the impact of specific research institutes, services or policies on the interdisciplinary collaboration between these communities. First, we apply community-detection algorithms to cross-sectional scientific collaboration networks and analyze different types of co-membership in the resulting subgroups over time. This analysis summarizes large amounts of longitudinal network data to extract sets of research communities whose members have consistently collaborated or shared collaborators over time. Second, we construct networks of cross-community interactions and estimate Exponential Random Graph Models to predict the formation of interdisciplinary collaborations between different communities. The method is applied to longitudinal data on publication and grant collaborations at the University of Florida. Results show that similar institutional affiliation, spatial proximity, transitivity effects, and use of the same research services predict higher degree of interdisciplinary collaboration between research communities. Our application also illustrates how the identification of research communities in longitudinal data and the analysis of cross-community network formation can be used to measure the growth of interdisciplinary team science at a research university, and to evaluate its association with research policies, services or institutes.

  20. 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.

  1. 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.

  2. 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.

  3. Constructing and Analyzing Uncertain Social Networks from Unstructured Textual Data

    Science.gov (United States)

    Johansson, Fredrik; Svenson, Pontus

    Social network analysis and link diagrams are popular tools among intelligence analysts for analyzing and understanding criminal and terrorist organizations. A bottleneck in the use of such techniques is the manual effort needed to create the network to analyze from available source information. We describe how text mining techniques can be used for extraction of named entities and the relations among them, in order to enable automatic construction of networks from unstructured text. Since the text mining techniques used, viz. algorithms for named entity recognition and relation extraction, are not perfect, we also describe a method for incorporating information about uncertainty when constructing the networks and when doing the social network analysis. The presented approach is applied on text documents describing terrorist activities in Indonesia.

  4. 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.

  5. 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.

  6. Analyzing Nonblocking Switching Networks using Linear Programming (Duality)

    CERN Document Server

    Ngo, Hung Q; Le, Anh N; Nguyen, Thanh-Nhan

    2012-01-01

    The main task in analyzing a switching network design (including circuit-, multirate-, and photonic-switching) is to determine the minimum number of some switching components so that the design is non-blocking in some sense (e.g., strict- or wide-sense). We show that, in many cases, this task can be accomplished with a simple two-step strategy: (1) formulate a linear program whose optimum value is a bound for the minimum number we are seeking, and (2) specify a solution to the dual program, whose objective value by weak duality immediately yields a sufficient condition for the design to be non-blocking. We illustrate this technique through a variety of examples, ranging from circuit to multirate to photonic switching, from unicast to $f$-cast and multicast, and from strict- to wide-sense non-blocking. The switching architectures in the examples are of Clos-type and Banyan-type, which are the two most popular architectural choices for designing non-blocking switching networks. To prove the result in the multir...

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. Design and Research on Automotive Controller Area Network Bus Analyzer

    Directory of Open Access Journals (Sweden)

    Hongwei CUI

    2014-03-01

    Full Text Available The detection method of automotive controller area network bus is researched in this paper. Failure identifying of CAN bus under different working conditions has been realized. In order to realizing intelligent failure diagnosis, data fusion means has been put forward in this paper. The composition of analysis and detection system is introduced. By analyzing and processing the data of CAN bus and sensors, work condition of automotive is achieved. Multi-pattern data fusion model and algorithm for failure diagnosis are researched. The analyzer and detection system designed in this paper can be applied to automotive fault analysis, troubleshooting and maintenance.

  12. 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.

  13. Quantifying and analyzing the network basis of genetic complexity.

    Directory of Open Access Journals (Sweden)

    Ethan G Thompson

    Full Text Available Genotype-to-phenotype maps exhibit complexity. This genetic complexity is mentioned frequently in the literature, but a consistent and quantitative definition is lacking. Here, we derive such a definition and investigate its consequences for model genetic systems. The definition equates genetic complexity with a surplus of genotypic diversity over phenotypic diversity. Applying this definition to ensembles of Boolean network models, we found that the in-degree distribution and the number of periodic attractors produced determine the relative complexity of different topology classes. We found evidence that networks that are difficult to control, or that exhibit a hierarchical structure, are genetically complex. We analyzed the complexity of the cell cycle network of Sacchoromyces cerevisiae and pinpointed genes and interactions that are most important for its high genetic complexity. The rigorous definition of genetic complexity is a tool for unraveling the structure and properties of genotype-to-phenotype maps by enabling the quantitative comparison of the relative complexities of different genetic systems. The definition also allows the identification of specific network elements and subnetworks that have the greatest effects on genetic complexity. Moreover, it suggests ways to engineer biological systems with desired genetic properties.

  14. 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.

  15. Strategizing through analyzing and influencing the network horizon

    NARCIS (Netherlands)

    Holmen, Elsebeth; Pedersen, Ann-Charlott

    2003-01-01

    How does a firm keep on being valuable in a network? One requirement is that the firm has a sufficient overview of the network and its dynamics. In other words, a firm's strategy depends on the firm's overview of the network—its network horizon. How comprehensive or limited should its network

  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. Hydrogen Bond Nanoscale Networks Showing Switchable Transport Performance

    Science.gov (United States)

    Long, Yong; Hui, Jun-Feng; Wang, Peng-Peng; Xiang, Guo-Lei; Xu, Biao; Hu, Shi; Zhu, Wan-Cheng; Lü, Xing-Qiang; Zhuang, Jing; Wang, Xun

    2012-08-01

    Hydrogen bond is a typical noncovalent bond with its strength only one-tenth of a general covalent bond. Because of its easiness to fracture and re-formation, materials based on hydrogen bonds can enable a reversible behavior in their assembly and other properties, which supplies advantages in fabrication and recyclability. In this paper, hydrogen bond nanoscale networks have been utilized to separate water and oil in macroscale. This is realized upon using nanowire macro-membranes with pore sizes ~tens of nanometers, which can form hydrogen bonds with the water molecules on the surfaces. It is also found that the gradual replacement of the water by ethanol molecules can endow this film tunable transport properties. It is proposed that a hydrogen bond network in the membrane is responsible for this switching effect. Significant application potential is demonstrated by the successful separation of oil and water, especially in the emulsion forms.

  19. 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.

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

    Science.gov (United States)

    2015-11-30

    we connected 3 Raspberry Pi’s running GaianDB and our augmented version of splatform to a network of 3 CSRs. The Raspberry Pi is a low power, low...based on Debian from a connected secure digital high capacity (SDHC) card or a universal serial bus (USB) device. The Raspberry Pi comes equipped with...requirements, capabilities, and cost make the Raspberry Pi a useful device for sensor experimentation. From there, we performed 3 types of benchmarks

  1. Analyzing the international exergy flow network of ferrous metal ores.

    Science.gov (United States)

    Qi, Hai; An, Haizhong; Hao, Xiaoqing; Zhong, Weiqiong; Zhang, Yanbing

    2014-01-01

    This paper employs an un-weighted and weighted exergy network to study the properties of ferrous metal ores in countries worldwide and their evolution from 2002 to 2012. We find that there are few countries controlling most of the ferrous metal ore exports in terms of exergy and that the entire exergy flow network is becoming more heterogeneous though the addition of new nodes. The increasing of the average clustering coefficient indicates that the formation of an international exergy flow system and regional integration is improving. When we contrast the average out strength of exergy and the average out strength of currency, we find both similarities and differences. Prices are affected largely by human factors; thus, the growth rate of the average out strength of currency has fluctuated acutely in the eleven years from 2002 to 2012. Exergy is defined as the maximum work that can be extracted from a system and can reflect the true cost in the world, and this parameter fluctuates much less. Performing an analysis based on the two aspects of exergy and currency, we find that the network is becoming uneven.

  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 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...

  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. 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

  7. Synthesize, optimize, analyze, repeat (SOAR): Application of neural network tools to ECG patient monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Watrous, R.; Towell, G.; Glassman, M.S. [Siemens Corporate Research, Princeton, NJ (United States)

    1995-12-31

    Results are reported from the application of tools for synthesizing, optimizing and analyzing neural networks to an ECG Patient Monitoring task. A neural network was synthesized from a rule-based classifier and optimized over a set of normal and abnormal heartbeats. The classification error rate on a separate and larger test set was reduced by a factor of 2. When the network was analyzed and reduced in size by a factor of 40%, the same level of performance was maintained.

  8. Analyzing the dynamics of emotional scene sequence using recurrent neuro-fuzzy network.

    Science.gov (United States)

    Zhang, Qing; Lee, Minho

    2013-02-01

    In this paper, we propose a new framework to analyze the temporal dynamics of the emotional stimuli. For this framework, both electroencephalography signal and visual information are of great importance. The fusion of visual information with brain signals allows us to capture the users' emotional state. Thus we adopt previously proposed fuzzy-GIST as emotional feature to summarize the emotional feedback. In order to model the dynamics of the emotional stimuli sequence, we develop a recurrent neuro-fuzzy network for modeling the dynamic events of emotional dimensions including valence and arousal. It can incorporate human expertise by IF-THEN fuzzy rule while recurrent connections allow the fuzzy rules of network to see its own previous output. The results show that such a framework can interact with human subjects and generate arbitrary emotional sequences after learning the dynamics of an emotional sequence with enough number of samples.

  9. 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.

  10. FCJ-178 Network Affordances: The unpredictable parameters of a Hong Kong SPEED SHOW

    Directory of Open Access Journals (Sweden)

    Audrey Samson

    2015-06-01

    Full Text Available This paper examines the notion of network affordance within the context of network art. We expand on the notion of affordances, (Gibson, 1977; 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 exhibition, SPEED SHOW [2.0] Hong Kong (2013. The paper discusses how the artworks are contingent upon the parametric relations (Parisi, 2013 of the network. We introduce network affordance as a dynamic framework that could articulate the experience of tension arising from the (visible symbolic representation of computational processes and its hidden occurrences.

  11. 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...

  12. 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.

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

    Science.gov (United States)

    Leal, Luis Guillermo; López, Camilo; López-Kleine, Liliana

    2014-01-01

    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.

  14. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  16. 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...

  17. [Using the Tabu-search-algorithm-based Bayesian network to analyze the risk factors of coronary heart diseases].

    Science.gov (United States)

    Wei, Z; Zhang, X L; Rao, H X; Wang, H F; Wang, X; Qiu, L X

    2016-06-01

    Under the available data gathered from a coronary study questionnaires with 10 792 cases, this article constructs a Bayesian network model based on the tabu search algorithm and calculates the conditional probability of each node, using the Maximum-likelihood. Pros and cons of the Bayesian network model are evaluated to compare against the logistic regression model in the analysis of coronary factors. Applicability of this network model in clinical study is also investigated. Results show that Bayesian network model can reveal the complex correlations among influencing factors on the coronary and the relationship with coronary heart diseases. Bayesian network model seems promising and more practical than the logistic regression model in analyzing the influencing factors of coronary heart disease.

  18. Software-based microwave CT system consisting of antennas and vector network analyzer.

    Science.gov (United States)

    Ogawa, Takahiro; Miyakawa, Michio

    2011-01-01

    We have developed a software-based microwave CT (SMCT) that consists of antennas and a vector network analyzer. Regardless of the scanner type, SMCT collects the S-parameters at each measurement position in the frequency range of interest. After collecting all the S-parameters, it calculates the shortest path to obtain the projection data for CPMCT. Because of the redundant data in SMCT, the calculation of the projection is easily optimized. Therefore, the system can improve the accuracy and stability of the measurement. Furthermore, the experimental system is constructed at a reasonable cost. Hence, SMCT is useful for imaging experiments for CP-MCT and particularly for basic studies. This paper describes the software-based microwave imaging system, and experimental results show the usefulness of the system.

  19. 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.

  20. 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.

  1. 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.

  2. Analyzing animal behavior via classifying each video frame using convolutional neural networks

    Science.gov (United States)

    Stern, Ulrich; He, Ruo; Yang, Chung-Hui

    2015-01-01

    High-throughput analysis of animal behavior requires software to analyze videos. Such software analyzes each frame individually, detecting animals’ body parts. But the image analysis rarely attempts to recognize “behavioral states”—e.g., actions or facial expressions—directly from the image instead of using the detected body parts. Here, we show that convolutional neural networks (CNNs)—a machine learning approach that recently became the leading technique for object recognition, human pose estimation, and human action recognition—were able to recognize directly from images whether Drosophila were “on” (standing or walking) or “off” (not in physical contact with) egg-laying substrates for each frame of our videos. We used multiple nets and image transformations to optimize accuracy for our classification task, achieving a surprisingly low error rate of just 0.072%. Classifying one of our 8 h videos took less than 3 h using a fast GPU. The approach enabled uncovering a novel egg-laying-induced behavior modification in Drosophila. Furthermore, it should be readily applicable to other behavior analysis tasks. PMID:26394695

  3. 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...

  4. ATHENA (Advanced Thermal-Hydraulic Energy Network Analyzer) transient analysis of a fusion engineering test reactor

    Energy Technology Data Exchange (ETDEWEB)

    Wareing, T.A.

    1988-02-01

    Two potential undercooling transients are of concern in the design of TIBER-II (Tokamak Ignition/Burn Experimental Reactor), namely loss of coolant and loss of flow accidents. The major area of concern for TIBER-II is the inboard shield, where, due to tungsten material, the decay heat is extremely high. The purpose of this study was to analyze these transients using the thermal-hydraulic code ATHENA (Advanced Thermal-Hydraulic Energy Network Analyzer). The most comprehensive portion of this project involved creating a simple, yet complete, ATHENA model representative of TIBER-II. The completed model represents the case when the plasma is off and contains the inboard shield, the outboard shield, the divertor shields, and the primary loop. The primary loop contains the piping, pump, pressurizer, and heat exchanger. The heat exchanger is at the same elevation as the reactor, the least favorable to establishing natural circulation. The only transient analyzed so far, however, is a loss of flow accident. Results from the loss of flow analysis show that there is sufficient natural circulation in the inboard, outboard, and lower divertor shield to remove the decay heat, assuming that the secondary side flow is at full capacity. Although the upper divertor shield does not have sufficient natural circulation, cooling is provided due to vaporization and re-flood oscillations. However, one must recognize that there may be some local hot sport where the flow geometry inhibits cooling in a LOFA; the ATHENA model would not detect any localized problem. 9 refs., 18 figs., 4 tabs.

  5. 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.

  6. 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

  7. Social Network Analysis as a tool to analyze interaction of Batsmen and Bowlers in Cricket

    CERN Document Server

    Mukherjee, Satyam

    2012-01-01

    This paper describes the far reaching applications of network methods for understanding interaction within members of sport teams. Although a popular sport in the erstwhile English colonies, cricket has not received much attention from scientific community even though there is no dearth of statistics. This paper presents a network based approach to analyze the interaction of batsmen and bowlers in International cricket matches. First we consider the network of interaction between bowlers and batsmen. If two batsmen faced the same bowler they are connected by an unweighted link. Similarly if two bowlers bowled to the same batsman, they are connected. In this way a network of batsmen and bowlers is generated. We determine the exact values of clustering coefficient, average degree, average shortest path length of the networks and compare them with the Erd\\text{\\"{o}}s-R\\text{\\'{e}}nyi model and the configuration model. We also study an alternate version of the network in which two batsmen are connected if they a...

  8. 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.

  9. Using Bayesian networks to analyze occupational stress caused by work demands: preventing stress through social support.

    Science.gov (United States)

    García-Herrero, Susana; Mariscal, M A; Gutiérrez, J M; Ritzel, Dale O

    2013-08-01

    Occupational stress is a major health hazard and a serious challenge to the effective operation of any company and represents a major problem for both individuals and organizations. Previous researches have shown that high demands (e.g. workload, emotional) combined with low resources (e.g. support, control, rewards) are associated with adverse health (e.g. psychological, physical) and organizational impacts (e.g. reduced job satisfaction, sickness absence). The objective of the present work is to create a model to analyze how social support reduces the occupational stress caused by work demands. This study used existing Spanish national data on working conditions collected by the Spanish Ministry of Labour and Immigration in 2007, where 11,054 workers were interviewed by questionnaire. A probabilistic model was built using Bayesian networks to explain the relationships between work demands and occupational stress. The model also explains how social support contributes positively to reducing stress levels. The variables studied were intellectually demanding work, overwork, workday, stress, and social support. The results show the importance of social support and of receiving help from supervisors and co-workers in preventing occupational stress. The study provides a new methodology that explains and quantifies the effects of intellectually demanding work, overwork, and workday in occupational stress. Also, the study quantifies the importance of social support to reduce occupational stress. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Analyzing fixed points of intracellular regulation networks with interrelated feedback topology

    Directory of Open Access Journals (Sweden)

    Radde Nicole

    2012-06-01

    Full Text Available Abstract Background Modeling the dynamics of intracellular regulation networks by systems of ordinary differential equations has become a standard method in systems biology, and it has been shown that the behavior of these networks is often tightly connected to the network topology. We have recently introduced the circuit-breaking algorithm, a method that uses the network topology to construct a one-dimensional circuit-characteristic of the system. It was shown that this characteristic can be used for an efficient calculation of the system’s fixed points. Results Here we extend previous work and show several connections between the circuit-characteristic and the stability of fixed points. In particular, we derive a sufficient condition on the characteristic for a fixed point to be unstable for certain graph structures and demonstrate that the characteristic does not contain the information to decide whether a fixed point is asymptotically stable. All statements are illustrated on biological network models. Conclusions Single feedback circuits and their role for complex dynamic behavior of biological networks have extensively been investigated, but a transfer of most of these concepts to more complex topologies is difficult. In this context, our algorithm is a powerful new approach for the analysis of regulation networks that goes beyond single isolated feedback circuits.

  11. 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

  12. Analyzing resilience of urban networks: a preliminary step towards more flood resilient cities

    Science.gov (United States)

    Lhomme, S.; Serre, D.; Diab, Y.; Laganier, R.

    2013-02-01

    In Europe, river floods have been increasing in frequency and severity. These circumstances require the management of flood risk by integrating new concepts like urban resilience. Nevertheless, urban resilience seems to have no accurate meanings. That is why researchers are primarily concerned with defining resilience. Nevertheless, focus on research object seems to be more important than focus on conceptual debate (Resilience of what? Rather than what is resilience?). Thus the methodology designed here is focused on urban considerations. In fact, a system approach emphasizes technical networks' importance concerning urban resilience. Principles and assumptions applied in this research finally lead to the analysis of how urban networks are able to face natural hazards. In this context, a Web-GIS has been developed for analyzing resistance capacity, absorption capacity and recovery capacity of different technical networks. A first application has been carried out on a French agglomeration in order to analyze road network absorption capacity. This application is very specific but, thanks to this example, it is already possible to highlight the methodology's usefulness.

  13. Analyzing Distributed Generation Impact on the Reliability of Electric Distribution Network

    OpenAIRE

    Sanaullah Ahmad; Sana Sardar; Babar Noor; Azzam ul Asar

    2016-01-01

    With proliferation of Distribution Generation (DG) and renewable energy technologies the power system is becoming more complex, with passage of time the development of distributed generation technologies is becoming diverse and broad. Power system reliability is one of most vital area in electric power system which deals with continuous supply of power and customer satisfaction. Distribution network in power system contributed up to 80% of reliability problems. This paper analyzes the impact ...

  14. Patterns of human gene expression variance show strong associations with signaling network hierarchy.

    Science.gov (United States)

    Komurov, Kakajan; Ram, Prahlad T

    2010-11-12

    Understanding organizational principles of cellular networks is one of the central goals of systems biology. Although much has been learnt about gene expression programs under specific conditions, global patterns of expressional variation (EV) of genes and their relationship to cellular functions and physiological responses is poorly understood. To understand global principles of relationship between transcriptional regulation of human genes and their functions, we have leveraged large-scale datasets of human gene expression measurements across a wide spectrum of cell conditions. We report that human genes are highly diverse in terms of their EV; while some genes have highly variable expression pattern, some seem to be relatively ubiquitously expressed across a wide range of conditions. The wide spectrum of gene EV strongly correlates with the positioning of proteins within the signaling network hierarchy, such that, secreted extracellular receptor ligands and membrane receptors have the highest EV, and intracellular signaling proteins have the lowest EV in the genome. Our analysis shows that this pattern of EV reflects functional centrality: proteins with highly specific signaling functions are modulated more frequently than those with highly central functions in the network, which is also consistent with previous studies on tissue-specific gene expression. Interestingly, these patterns of EV along the signaling network hierarchy have significant correlations with promoter architectures of respective genes. Our analyses suggest a generic systems level mechanism of regulation of the cellular signaling network at the transcriptional level.

  15. Patterns of human gene expression variance show strong associations with signaling network hierarchy

    Directory of Open Access Journals (Sweden)

    Ram Prahlad T

    2010-11-01

    Full Text Available Abstract Background Understanding organizational principles of cellular networks is one of the central goals of systems biology. Although much has been learnt about gene expression programs under specific conditions, global patterns of expressional variation (EV of genes and their relationship to cellular functions and physiological responses is poorly understood. Results To understand global principles of relationship between transcriptional regulation of human genes and their functions, we have leveraged large-scale datasets of human gene expression measurements across a wide spectrum of cell conditions. We report that human genes are highly diverse in terms of their EV; while some genes have highly variable expression pattern, some seem to be relatively ubiquitously expressed across a wide range of conditions. The wide spectrum of gene EV strongly correlates with the positioning of proteins within the signaling network hierarchy, such that, secreted extracellular receptor ligands and membrane receptors have the highest EV, and intracellular signaling proteins have the lowest EV in the genome. Our analysis shows that this pattern of EV reflects functional centrality: proteins with highly specific signaling functions are modulated more frequently than those with highly central functions in the network, which is also consistent with previous studies on tissue-specific gene expression. Interestingly, these patterns of EV along the signaling network hierarchy have significant correlations with promoter architectures of respective genes. Conclusion Our analyses suggest a generic systems level mechanism of regulation of the cellular signaling network at the transcriptional level.

  16. 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.

  17. 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.

  18. 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.

  19. Analyzing psychotherapy process as intersubjective sensemaking: an approach based on discourse analysis and neural networks.

    Science.gov (United States)

    Nitti, Mariangela; Ciavolino, Enrico; Salvatore, Sergio; Gennaro, Alessandro

    2010-09-01

    The authors propose a method for analyzing the psychotherapy process: discourse flow analysis (DFA). DFA is a technique representing the verbal interaction between therapist and patient as a discourse network, aimed at measuring the therapist-patient discourse ability to generate new meanings through time. DFA assumes that the main function of psychotherapy is to produce semiotic novelty. DFA is applied to the verbatim transcript of the psychotherapy. It defines the main meanings active within the therapeutic discourse by means of the combined use of text analysis and statistical techniques. Subsequently, it represents the dynamic interconnections among these meanings in terms of a "discursive network." The dynamic and structural indexes of the discursive network have been shown to provide a valid representation of the patient-therapist communicative flow as well as an estimation of its clinical quality. Finally, a neural network is designed specifically to identify patterns of functioning of the discursive network and to verify the clinical validity of these patterns in terms of their association with specific phases of the psychotherapy process. An application of the DFA to a case of psychotherapy is provided to illustrate the method and the kinds of results it produces.

  20. A New Training Method for Analyzable Structured Neural Network and Application of Daily Peak Load Forecasting

    Science.gov (United States)

    Iizaka, Tatsuya; Matsui, Tetsuro; Fukuyama, Yoshikazu

    This paper presents a daily peak load forecasting method using an analyzable structured neural network (ASNN) in order to explain forecasting reasons. In this paper, we propose a new training method for ASNN in order to explain forecasting reason more properly than the conventional training method. ASNN consists of two types of hidden units. One type of hidden units has connecting weights between the hidden units and only one group of related input units. Another one has connecting weights between the hidden units and all input units. The former type of hidden units allows to explain forecasting reasons. The latter type of hidden units ensures the forecasting performance. The proposed training method make the former type of hidden units train only independent relations between the input factors and output, and make the latter type of hidden units train only complicated interactions between input factors. The effectiveness of the proposed neural network is shown using actual daily peak load. ASNN trained by the proposed method can explain forecasting reasons more properly than ASNN trained by the conventional method. Moreover, the proposed neural network can forecast daily peak load more accurately than conventional neural network trained by the back propagation algorithm.

  1. 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

  2. Logistic growth for the Nuzi cuneiform tablets: Analyzing family networks in ancient Mesopotamia

    Science.gov (United States)

    Ueda, Sumie; Makino, Kumi; Itoh, Yoshiaki; Tsuchiya, Takashi

    2015-03-01

    We reconstruct the published year of each cuneiform tablet of the Nuzi society in ancient Mesopotamia. The tablets are on land transaction, marriage, loan, slavery contracts, etc. The number of tablets seems to increase by logistic growth. It may show the dynamics of concentration of lands or other properties into few powerful families in a period of about sixty years and most of them are in about thirty years. We reconstruct family trees and social networks of Nuzi and estimate the published years of cuneiform tablets consistently with the trees and networks, formulating least squares problems with linear inequality constraints.

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

    Science.gov (United States)

    Cinner, Joshua E; Bodin, Orjan

    2010-08-11

    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. 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. 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 into communities' dependencies and usages of natural resources, and shows how patterns of

  4. 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.

  5. Resting-state functional magnetic resonance imaging shows altered brain network topology in Type 2 diabetic patients without cognitive impairment.

    Science.gov (United States)

    Chen, Guan-Qun; Zhang, Xin; Xing, Yue; Wen, Dong; Cui, Guang-Bin; Han, Ying

    2017-11-28

    We analyzed topology of brain functional networks in type 2 diabetes mellitus (T2DM) patients without mild cognitive impairment. We recruited T2DM patients without mild cognitive impairment (4 males and 8 females) and healthy control subjects (8 males and 16 females) to undergo cognitive testing and resting-state functional magnetic resonance imaging. Graph theoretical analysis of functional brain networks revealed abnormal small-world architecture in T2DM patients as compared to control subjects. The functional brain networks of T2DM patients showed increased path length, decreased global efficiency and disrupted long-distance connections. Moreover, reduced nodal characteristics were distributed in the frontal, parietal and temporal lobes, while increased nodal characteristics were distributed in the frontal, occipital lobes, and basal ganglia in the T2DM patients. The disrupted topological properties correlated with cognitive performance of T2DM patients. These findings demonstrate altered topological organization of functional brain networks in T2DM patients without mild cognitive impairment.

  6. Using a modified Hewlett Packard 8410 network analyzer as an automated farfield antenna range receiver

    Science.gov (United States)

    Terry, John D.; Kunath, Richard R.

    1990-01-01

    A Hewlett Packard 8410 Network Analyzer was modified to be used as an automated far-field antenna range receiver. By using external mixers, analog to digital signal conversion, and an external computer/controller, the HP8410 is capable of measuring signals as low as -110 dBm. The modified receiver is an integral part of an automated far-field range which features computer controlled test antenna positioning, system measurement parameters, and data acquisition, as well as customized measurement file management. The system described was assembled and made operational, taking advantage of off-the-shelf hardware available at minimal cost.

  7. Near-field antenna testing using the Hewlett Packard 8510 automated network analyzer

    Science.gov (United States)

    Kunath, Richard R.; Garrett, Michael J.

    1990-01-01

    Near-field antenna measurements were made using a Hewlett-Packard 8510 automated network analyzer. This system features measurement sensitivity better than -90 dBm, at measurement speeds of one data point per millisecond in the fast data acquisition mode. The system was configured using external, even harmonic mixers and a fiber optic distributed local oscillator signal. Additionally, the time domain capability of the HP8510, made it possible to generate far-field diagnostic results immediately after data acquisition without the use of an external computer.

  8. 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.

  9. ezBioNet: A modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2012-10-01

    To achieve robustness against living environments, a living organism is composed of complicated regulatory mechanisms ranging from gene regulations to signal transduction. If such life phenomena are to be understand, an integrated analysis tool that should have modeling and simulation functions for biological reactions, as well as new experimental methods for measuring biological phenomena, is fundamentally required. We have designed and implemented modeling and simulation software (ezBioNet) for analyzing biological reaction networks. The software can simultaneously perform an integrated modeling of various responses occurring in cells, ranging from gene expressions to signaling processes. To support massive analysis of biological networks, we have constructed a server-side simulation system (VCellSim) that can perform ordinary differential equations (ODE) analysis, sensitivity analysis, and parameter estimates. ezBioNet integrates the BioModel database by connecting the european bioinformatics institute (EBI) servers through Web services APIs and supports the handling of systems biology markup language (SBML) files. In addition, we employed eclipse RCP (rich client platform) which is a powerful modularity framework allowing various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool, as well as a simulation system, to understand the control mechanism by monitoring the change of each component in a biological network. A researcher may perform the kinetic modeling and execute the simulation. The simulation result can be managed and visualized on ezBioNet, which is freely available at http://ezbionet.cbnu.ac.kr.

  10. 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.

  11. Logistic Growth for the Nuzi Cuneiform Tablets: Analyzing Family Networks in Ancient Mesopotamia

    OpenAIRE

    Ueda, Sumie; Makino, Kumi; Itoh, Yoshiaki; Tsuchiya, Takashi

    2013-01-01

    We reconstruct the year of publication of each cuneiform tablet of the Nuzi society in ancient Mesopotamia. The tablets, are on land transaction, marriage, loan, slavery contracts etc. The number of tablets seem to increase by logistic growth until saturation. It may show the dynamics of concentration of lands or other properties into few powerful families in a period of about twenty years. We reconstruct family trees and social networks of Nuzi and estimate the publication years of cuneiform...

  12. 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

  13. Young adolescents with autism show abnormal joint attention network: A gaze contingent fMRI study.

    Science.gov (United States)

    Oberwelland, E; Schilbach, L; Barisic, I; Krall, S C; Vogeley, K; Fink, G R; Herpertz-Dahlmann, B; Konrad, K; Schulte-Rüther, M

    2017-01-01

    Behavioral research has revealed deficits in the development of joint attention (JA) as one of the earliest signs of autism. While the neural basis of JA has been studied predominantly in adults, we recently demonstrated a protracted development of the brain networks supporting JA in typically developing children and adolescents. The present eye-tracking/fMRI study now extends these findings to adolescents with autism. Our results show that in adolescents with autism JA is subserved by abnormal activation patterns in brain areas related to social cognition abnormalities which are at the core of ASD including the STS and TPJ, despite behavioral maturation with no behavioral differences. Furthermore, in the autism group we observed increased neural activity in a network of social and emotional processing areas during interactions with their mother. Moreover, data indicated that less severely affected individuals with autism showed higher frontal activation associated with self-initiated interactions. Taken together, this study provides first-time data of JA in children/adolescents with autism incorporating the interactive character of JA, its reciprocity and motivational aspects. The observed functional differences in adolescents ASD suggest that persistent developmental differences in the neural processes underlying JA contribute to social interaction difficulties in ASD.

  14. Young adolescents with autism show abnormal joint attention network: A gaze contingent fMRI study

    Directory of Open Access Journals (Sweden)

    E. Oberwelland

    2017-01-01

    Full Text Available Behavioral research has revealed deficits in the development of joint attention (JA as one of the earliest signs of autism. While the neural basis of JA has been studied predominantly in adults, we recently demonstrated a protracted development of the brain networks supporting JA in typically developing children and adolescents. The present eye-tracking/fMRI study now extends these findings to adolescents with autism. Our results show that in adolescents with autism JA is subserved by abnormal activation patterns in brain areas related to social cognition abnormalities which are at the core of ASD including the STS and TPJ, despite behavioral maturation with no behavioral differences. Furthermore, in the autism group we observed increased neural activity in a network of social and emotional processing areas during interactions with their mother. Moreover, data indicated that less severely affected individuals with autism showed higher frontal activation associated with self-initiated interactions. Taken together, this study provides first-time data of JA in children/adolescents with autism incorporating the interactive character of JA, its reciprocity and motivational aspects. The observed functional differences in adolescents ASD suggest that persistent developmental differences in the neural processes underlying JA contribute to social interaction difficulties in ASD.

  15. 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

  16. Identifying and analyzing the most important factors in universities scientific output using neural network

    Directory of Open Access Journals (Sweden)

    Sajjad Mohammadian

    2016-12-01

    Full Text Available For achieving to ideal research system is necessary to have policy and plan. The main aims of this research are knowledge extracted from the existing data gathered by the country research system. This Knowledge is prerequisite for science and technology policy. Population of the present descriptive research includes Universities of the Ministry of Science, Research & Technology. Data is extracted from database of monitoring of science and technology system. Classification algorithms Multilayer Preceptor neural network and neural network-based radius are used for data analysis. This research results showed that among the 15 indicators studied in this research, full-time faculty members, the number of theses, research funding and number of scholarships have more importance than other indicators. Among the four factors studied, the human resource factor is in the first place and has most importance in the scholarly productions. The education factor, financial factor and Structural factor is in the second to fourth rate.

  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

    Energy Technology Data Exchange (ETDEWEB)

    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 the Effects of Gap Junction Blockade on Neural Synchrony via a Motoneuron Network Computational Model

    Directory of Open Access Journals (Sweden)

    Heraldo Memelli

    2012-01-01

    Full Text Available In specific regions of the central nervous system (CNS, gap junctions have been shown to participate in neuronal synchrony. Amongst the CNS regions identified, some populations of brainstem motoneurons are known to be coupled by gap junctions. The application of various gap junction blockers to these motoneuron populations, however, has led to mixed results regarding their synchronous firing behavior, with some studies reporting a decrease in synchrony while others surprisingly find an increase in synchrony. To address this discrepancy, we employ a neuronal network model of Hodgkin-Huxley-style motoneurons connected by gap junctions. Using this model, we implement a series of simulations and rigorously analyze their outcome, including the calculation of a measure of neuronal synchrony. Our simulations demonstrate that under specific conditions, uncoupling of gap junctions is capable of producing either a decrease or an increase in neuronal synchrony. Subsequently, these simulations provide mechanistic insight into these different outcomes.

  20. 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.

  1. Analyzing long-term correlated stochastic processes by means of recurrence networks: potentials and pitfalls.

    Science.gov (United States)

    Zou, Yong; Donner, Reik V; Kurths, Jürgen

    2015-02-01

    Long-range correlated processes are ubiquitous, ranging from climate variables to financial time series. One paradigmatic example for such processes is fractional Brownian motion (fBm). In this work, we highlight the potentials and conceptual as well as practical limitations when applying the recently proposed recurrence network (RN) approach to fBm and related stochastic processes. In particular, we demonstrate that the results of a previous application of RN analysis to fBm [Liu et al. Phys. Rev. E 89, 032814 (2014)] are mainly due to an inappropriate treatment disregarding the intrinsic nonstationarity of such processes. Complementarily, we analyze some RN properties of the closely related stationary fractional Gaussian noise (fGn) processes and find that the resulting network properties are well-defined and behave as one would expect from basic conceptual considerations. Our results demonstrate that RN analysis can indeed provide meaningful results for stationary stochastic processes, given a proper selection of its intrinsic methodological parameters, whereas it is prone to fail to uniquely retrieve RN properties for nonstationary stochastic processes like fBm.

  2. 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.

  3. S-Parameter Uncertainties in Network Analyzer Measurements with Application to Antenna Patterns

    Directory of Open Access Journals (Sweden)

    N. Yannopoulou

    2008-04-01

    Full Text Available An analytical method was developed to estimate uncertainties in full two-port Vector Network Analyzer measurements, using total differentials of S-parameters. System error uncertainties were also estimated from total differentials involving two triples of standards, in the Direct Through connection case. Standard load uncertainties and measurement inaccuracies were represented by independent differentials. Complex uncertainty in any quantity, differentiably dependent on S-parameters, is estimated by the corresponding Differential Error Region. Real uncertainties, rectangular and polar, are estimated by the orthogonal parallelogram and annular sector circumscribed about the Differential Error Region, respectively. From the user's point of view, manufactures' data may be used to set the independent differentials and apply the method. Demonstration results include: (1 System error differentials for Short, matching Load and Open pairs of opposite sex standards; (2 System error uncertainties for VNA extended by two lengthy transmission lines of opposite sex end-connectors; (3 High uncertainties in Z-parameters against frequency of an appropriately designed, DC resistive, T-Network; (4 Moderate uncertainties in amplitude and phase patterns of a designed UHF radial discone antenna (azimuthally rotated by a built positioner, under developed software control of a built hardware controller polarization coupled with a constructed gain standard antenna (stationary into an anechoic chamber.

  4. Beyond the Player: A User-Centered Approach to Analyzing Digital Games and Players Using Actor-Network Theory

    Science.gov (United States)

    Hung, Aaron Chia Yuan

    2016-01-01

    The paper uses actor-network theory (ANT) to analyze the sociotechnical networks of three groups of adolescents who played online games in different physical and social contexts. These include: an internet café, which allowed the players to be co-present; a personal laptop, which gave the player more control over how he played; and at home through…

  5. 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

  6. Modeling and Analyzing the Interaction between Network Rumors and Authoritative Information

    Directory of Open Access Journals (Sweden)

    Lingling Xia

    2015-01-01

    Full Text Available In this paper, we propose a novel two-stage rumor spreading Susceptible-Infected-Authoritative-Removed (SIAR model for complex homogeneous and heterogeneous networks. The interaction Markov chains (IMC mean-field equations based on the SIAR model are derived to describe the dynamic interaction between the rumors and authoritative information. We use a Monte Carlo simulation method to characterize the dynamics of the Susceptible-Infected-Removed (SIR and SIAR models, showing that the SIAR model with consideration of authoritative information gives a more realistic description of propagation features of rumors than the SIR model. The simulation results demonstrate that the critical threshold λc of the SIAR model has the tiniest increase than the threshold of SIR model. The sooner the authoritative information is introduced, the less negative impact the rumors will bring. We also get the result that heterogeneous networks are more prone to the spreading of rumors. Additionally, the inhibition of rumor spreading, as one of the characteristics of the new SIAR model itself, is instructive for later studies on the rumor spreading models and the controlling strategies.

  7. 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.

  8. Total Differential Errors in One-Port Network Analyzer Measurements with Application to Antenna Impedance

    Directory of Open Access Journals (Sweden)

    P. Zimourtopoulos

    2007-06-01

    Full Text Available The objective was to study uncertainty in antenna input impedance resulting from full one-port Vector Network Analyzer (VNA measurements. The VNA process equation in the reflection coefficient ρ of a load, its measurement m and three errors Es, determinable from three standard loads and their measurements, was considered. Differentials were selected to represent measurement inaccuracies and load uncertainties (Differential Errors. The differential operator was applied on the process equation and the total differential error dρ for any unknown load (Device Under Test DUT was expressed in terms of dEs and dm, without any simplification. Consequently, the differential error of input impedance Z -or any other physical quantity differentiably dependent on ρ- is expressible. Furthermore, to express precisely a comparison relation between complex differential errors, the geometric Differential Error Region and its Differential Error Intervals were defined. Practical results are presented for an indoor UHF ground-plane antenna in contrast with a common 50 Ω DC resistor inside an aluminum box. These two built, unshielded and shielded, DUTs were tested against frequency under different system configurations and measurement considerations. Intermediate results for Es and dEs characterize the measurement system itself. A number of calculations and illustrations demonstrate the application of the method.

  9. 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

  10. Self-organized annealing in laterally inhibited neural networks shows power law decay

    OpenAIRE

    Emmert-Streib, Frank

    2004-01-01

    In this paper we present a method which assigns to each layer of a multilayer neural network, whose network dynamics is governed by a noisy winner-take-all mechanism, a neural temperature. This neural temperature is obtained by a least mean square fit of the probability distribution of the noisy winner-take-all mechanism to the distribution of a softmax mechanism, which has a well defined temperature as free parameter. We call this approximated temperature resulting from the optimization step...

  11. Discriminating different classes of biological networks by analyzing the graphs spectra distribution

    CERN Document Server

    Takahashi, Daniel Yasumasa; Ferreira, Carlos Eduardo; Fujita, André

    2012-01-01

    The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibl...

  12. Analyzing the relationship between social networking addiction, interaction anxiousness and levels of loneliness of pre-service teachers

    OpenAIRE

    Hasan Özgür

    2013-01-01

    In this research, it was aimed to analyze the social networking addiction of pre-service teachers in terms of various variables and evaluate the relationship between social networking addiction and loneliness and interaction anxiousness. The research was designed according to the relational screening model. The study sample included 349 pre-service teachers studying at Trakya University Faculty of Education in 2012-2013 academic year fall term. The data were obtained using Facebook Addiction ...

  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

    administered to almost 300 entrepreneurs in 6 African economic capitals. The survey captured the roles in the local ecosystem that the entrepreneurs ...local entrepreneurs . The methodology described in “‘Who do you know?’ A Methodology to Develop Entrepreneurial Networks: The Tech Ecosystem of Six...Technical Report 15-007 “Who do you know?” Developing and Analyzing Entrepreneur Networks: An Analysis of the Tech Entrepreneurial

  14. For showing to U.S. and Brazilian people: a memory of bilateral relations through the social network Flickr

    Directory of Open Access Journals (Sweden)

    João Gilberto Neves Saraiva

    2014-09-01

    Full Text Available This paper investigates the memory of bilateral relations produced by the U.S. Embassy in Brazil on the social network Flickr in the early months of the administration of the Democrat President Barack Obama. The set of images and texts in 19 posts made by the Embassy’s profile on the network in the first half of 2009 is analyzed here. It establishes connections between the production of memory, the U.S. political conjuncture, and U.S. political myths, such as Abraham Lincoln and John Kennedy. It also discusses ways of remembering and forgetting several events in bilateral relations throughout the 20th and 21st centuries, besides the positions published on the social network regarding Brazilian politics and history. Keywords: Social Networks; Flickr; President – United States.

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. Beyond the Myth of Nationality: Analyzing Networks within the European Commission

    NARCIS (Netherlands)

    S. Suvarierol (Semin)

    2009-01-01

    textabstractThe current literature on the European Commission refers to the influence of nationality in the functioning of the Commission and in particular to the reliance on networks based on nationality, failing to give much evidence apart from anecdotes. This empirical study takes a systematic

  20. 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

  1. Investigative Data Mining Toolkit: A Software Prototype for Visualizing, Analyzing and Destabilizing Terrorist Networks

    Science.gov (United States)

    2006-12-01

    Community Structure in Very Large Networks, Physical Review E70, 066111 (2004) [25] M. Newman. A Measure of Betweenness Centrality based on Random...Fayz Ahmed, M. Alshehi, Hamza alghamdi and Ahmed alghamdi UA Flight 93: Zaid Jarrah, Ahmed alhaznawi, Saeed Alghmdi and Ahmed alnami Structural

  2. 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 conducted...

  3. 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

  4. Network meta-analysis shows commercialized subcutaneous and sublingual grass products have comparable efficacy.

    Science.gov (United States)

    Nelson, Harold; Cartier, Shannon; Allen-Ramey, Felicia; Lawton, Simon; Calderon, Moises A

    2015-01-01

    Subcutaneous immunotherapy (SCIT) and sublingual immunotherapy (SLIT) have been shown to effectively treat grass pollen allergies, although direct comparisons are sparse. To estimate the relative efficacy of SLIT tablets compared with SCIT and SLIT drops in commercially available products though network meta-analysis. A literature search of MEDLINE, Embase, and Cochrane Library publications. Randomized, double-blind clinical trials of SCIT, SLIT drops, and SLIT tablets for grass pollen were included. Bayesian network meta-analyses estimated the standardized mean difference (SMD) across 3 immunotherapy modalities on allergic rhinoconjunctivitis symptom and medication score data from publications or received from authors. Both fixed and random effects models were investigated. Thirty-seven studies were included in meta-analyses for symptom scores and 31 studies for medication scores. In the random effects model, SCIT and SLIT tablets were significantly different from placebo for symptom scores: SMDs (95% CI) of -0.32 (-0.45 to -0.18) and -0.32 (-0.41 to -0.23), respectively. No significant difference was identified for SLIT drops compared with placebo (SMD, -0.17; -0.37 to 0.04). For medication scores, significant differences compared with placebo were observed for SCIT (SMD, -0.33; 95% CI, -0.52 to -0.13), SLIT tablets (SMD, -0.23; 95% CI, -0.29 to -0.17), and SLIT drops (SMD, -0.44; 95% CI, -0.83 to -0.06). Network meta-analysis revealed no significant differences in SMDs (95% credible interval) for symptom scores (0.0145 [-0.19 to 0.23]) or medication scores (0.133 [-0.31 to 0.57]) between SLIT tablets and SCIT, or for symptom scores (-0.175 [-0.37 to 0.02]) and medication scores (0.188 [-0.18 to 0.56]) between SLIT tablets and SLIT drops. The comparisons for grass pollen immunotherapy products commercialized in at least 1 country indicate comparable reductions in allergic rhinoconjunctivitis symptoms and supplemental medication use for SLIT tablets

  5. 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.

  6. A neural network based model to analyze rice parboiling process with small dataset.

    Science.gov (United States)

    Behroozi-Khazaei, Nasser; Nasirahmadi, Abozar

    2017-07-01

    In this study, milling recovery, head rice yield, degree of milling and whiteness were utilized to characterize the milling quality of Tarom parboiled rice variety. The parboiled rice was prepared with three soaking temperatures and steaming times. Then the samples were dried to three levels of final moisture contents [8, 10 and 12% (w.b)]. Modeling of process and validating of the results with small dataset are always challenging. So, the aim of this study was to develop models based on the milling quality data in parboiling process by means of multivariate regression and artificial neural network. In order to validate the neural network model with a little dataset, K-fold cross validation method was applied. The ANN structure with one hidden layer and Tansig transfer function by 18 neurons in the hidden layer was selected as the best model in this study. The results indicated that the neural network could model the parboiling process with higher degree of accuracy. This method was a promising procedure to create accuracy and can be used as a reliable model to select the best parameters for the parboiling process with little experiment dataset.

  7. 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

  8. Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sarmad Rashed

    2017-02-01

    Full Text Available Sensor nodes in a Wireless Sensor Network (WSN can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings. In such kinds of networks, datacollectionbecomesoneofthemajorissues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage—especially Unmanned Aerial Vehicles (UAVs—is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern.

  9. Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks.

    Science.gov (United States)

    Rashed, Sarmad; Soyturk, Mujdat

    2017-02-20

    Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, datacollectionbecomesoneofthemajorissues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage-especially Unmanned Aerial Vehicles (UAVs)-is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern.

  10. A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases.

    Science.gov (United States)

    Scott-Boyer, Marie Pier; Lacroix, Sébastien; Scotti, Marco; Morine, Melissa J; Kaput, Jim; Priami, Corrado

    2016-01-18

    The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900's at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stages. Current daily recommended intakes were usually established on the basis of the association of a single nutrient to a single, most sensitive adverse effect and thus neglect interdependent and pleiotropic effects of micronutrients on biological systems. Hence, the understanding of the impact of overt or sub-clinical nutrient deficiencies on biological processes remains incomplete. Developing a more complete view of the role of micronutrients and their metabolic products in protein-mediated reactions is of importance. We thus integrated and represented cofactor-protein interaction data from multiple and diverse sources into a multi-layer network representation that links cofactors, cofactor-interacting proteins, biological processes, and diseases. Network representation of this information is a key feature of the present analysis and enables the integration of data from individual biochemical reactions and protein-protein interactions into a systems view, which may guide strategies for targeted nutritional interventions aimed at improving health and preventing diseases.

  11. Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks

    Science.gov (United States)

    Rashed, Sarmad; Soyturk, Mujdat

    2017-01-01

    Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, data collection becomes one of the major issues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage—especially Unmanned Aerial Vehicles (UAVs)—is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern. PMID:28230727

  12. 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.

  13. Analyzing the impact of storage shortage on data availability in decentralized online social networks.

    Science.gov (United States)

    Fu, Songling; He, Ligang; Liao, Xiangke; Li, Kenli; Huang, Chenlin

    2014-01-01

    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.

  14. Analyzing the network readiness of countries of the world from 2009 ...

    African Journals Online (AJOL)

    Information Technology (IT) is now globally recognized as a very strong tool for economic development and is being used by many countries to spur economic growth and to create jobs. In an attempt to objectively measure the progress of Africa in IT development over the last decade, this paper critically analyzes the Global ...

  15. 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

  16. Analyzing the Potential of Full Duplex in 5G Ultra-Dense Small Cell Networks

    DEFF Research Database (Denmark)

    Gatnau, Marta; Berardinelli, Gilberto; Mahmood, Nurul Huda

    2016-01-01

    Full duplex technology has become an attractive solution for future 5th Generation (5G) systems for accommodating the exponentially growing mobile traffic demand. Full duplex allows a node to transmit and receive simultaneously in the same frequency band, thus, theoretically, doubling the system......-interference cancellation are demonstrated using our own developed test bed. Secondly, a detailed evaluation of full duplex communication in 5G ultra-dense small cell networks via system level simulations is provided. The results are presented in terms of throughput and delay. Two types of full duplex are studied: when...... in the self-interference cancellation technology. However, there are other limitations in achieving the theoretical full duplex gain: residual self-interference, traffic constraints and inter-cell and intra-cell interference. The contribution of this article is twofold. Firstly, achievable levels of self...

  17. 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

  18. An Experiment to Analyze Performance of Virtual Private Network Approach to Information Exchange between Health Facilities

    Directory of Open Access Journals (Sweden)

    Siphael BETUEL

    2017-06-01

    Full Text Available In developing countries, Tanzania in particular, studies and reports have depicted that there is a strong desire and need for seamless information exchange across health care providing facilities. A limited study conducted in few public and private hospitals has also revealed the same. On the other hand, the eHealth community has failed to effectively take advantage of the advances in technologies to make that desire come true. One potential technology is Virtual Private Network (VPN for which it has been noticed that there is a misconception and lack of innovative initiatives that slow down its uptake in eHealth. This article presents a technical assessment of the VPN technology in Tanzanian context. Primarily, the assessment focused on practicability of the best VPN practices and the perceived user experience performance when VPN is in use. It was observed that the response time dropped significantly as expected. The increase in response time and computer memory utilization is due to security mechanisms that are involved in VPN, the stronger security is used the more performance decreases. However, the increase in response time and computer memory utilization is very small in such a way that users will not be able to notice.

  19. Anatomical network analysis shows decoupling of modular lability and complexity in the evolution of the primate skull.

    Directory of Open Access Journals (Sweden)

    Borja Esteve-Altava

    Full Text Available 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.

  20. 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.

  1. Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels

    Science.gov (United States)

    Bhardwaj, Nitin; Yan, Koon-Kiu; Gerstein, Mark B.

    2010-01-01

    Gene regulatory networks have been shown to share some common aspects with commonplace social governance structures. Thus, we can get some intuition into their organization by arranging them into well-known hierarchical layouts. These hierarchies, in turn, can be placed between the extremes of autocracies, with well-defined levels and clear chains of command, and democracies, without such defined levels and with more co-regulatory partnerships between regulators. In general, the presence of partnerships decreases the variation in information flow amongst nodes within a level, more evenly distributing stress. Here we study various regulatory networks (transcriptional, modification, and phosphorylation) for five diverse species, Escherichia coli to human. We specify three levels of regulators—top, middle, and bottom—which collectively govern the non-regulator targets lying in the lowest fourth level. We define quantities for nodes, levels, and entire networks that measure their degree of collaboration and autocratic vs. democratic character. We show individual regulators have a range of partnership tendencies: Some regulate their targets in combination with other regulators in local instantiations of democratic structure, whereas others regulate mostly in isolation, in more autocratic fashion. Overall, we show that in all networks studied the middle level has the highest collaborative propensity and coregulatory partnerships occur most frequently amongst midlevel regulators, an observation that has parallels in corporate settings where middle managers must interact most to ensure organizational effectiveness. There is, however, one notable difference between networks in different species: The amount of collaborative regulation and democratic character increases markedly with overall genomic complexity. PMID:20351254

  2. Network models of TEM β-lactamase mutations coevolving under antibiotic selection show modular structure and anticipate evolutionary trajectories.

    Science.gov (United States)

    Guthrie, Violeta Beleva; Allen, Jennifer; Camps, Manel; Karchin, Rachel

    2011-09-01

    Understanding how novel functions evolve (genetic adaptation) is a critical goal of evolutionary biology. Among asexual organisms, genetic adaptation involves multiple mutations that frequently interact in a non-linear fashion (epistasis). Non-linear interactions pose a formidable challenge for the computational prediction of mutation effects. Here we use the recent evolution of β-lactamase under antibiotic selection as a model for genetic adaptation. We build a network of coevolving residues (possible functional interactions), in which nodes are mutant residue positions and links represent two positions found mutated together in the same sequence. Most often these pairs occur in the setting of more complex mutants. Focusing on extended-spectrum resistant sequences, we use network-theoretical tools to identify triple mutant trajectories of likely special significance for adaptation. We extrapolate evolutionary paths (n = 3) that increase resistance and that are longer than the units used to build the network (n = 2). These paths consist of a limited number of residue positions and are enriched for known triple mutant combinations that increase cefotaxime resistance. We find that the pairs of residues used to build the network frequently decrease resistance compared to their corresponding singlets. This is a surprising result, given that their coevolution suggests a selective advantage. Thus, β-lactamase adaptation is highly epistatic. Our method can identify triplets that increase resistance despite the underlying rugged fitness landscape and has the unique ability to make predictions by placing each mutant residue position in its functional context. Our approach requires only sequence information, sufficient genetic diversity, and discrete selective pressures. Thus, it can be used to analyze recent evolutionary events, where coevolution analysis methods that use phylogeny or statistical coupling are not possible. Improving our ability to assess

  3. 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.

  4. 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.

  5. 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.

  6. Analyzing hidden populations online: topic, emotion, and social network of HIV-related users in the largest Chinese online community.

    Science.gov (United States)

    Liu, Chuchu; Lu, Xin

    2018-01-05

    Traditional survey methods are limited in the study of hidden populations due to the hard to access properties, including lack of a sampling frame, sensitivity issue, reporting error, small sample size, etc. The rapid increase of online communities, of which members interact with others via the Internet, have generated large amounts of data, offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. In this study, we try to understand the multidimensional characteristics of a hidden population by analyzing the massive data generated in the online community. By elaborately designing crawlers, we retrieved a complete dataset from the "HIV bar," the largest bar related to HIV on the Baidu Tieba platform, for all records from January 2005 to August 2016. Through natural language processing and social network analysis, we explored the psychology, behavior and demand of online HIV population and examined the network community structure. In HIV communities, the average topic similarity among members is positively correlated to network efficiency (r = 0.70, p online services for HIV/AIDS consultation and diagnosis be improved to avoid privacy concerns and social discrimination in China.

  7. Using individualized brain network for analyzing structural covariance of the cerebral cortex in Alzheimer’s patients

    Directory of Open Access Journals (Sweden)

    Hee-Jong Kim

    2016-09-01

    Full Text Available 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

  8. 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.

  9. Livelihood Diversification in Tropical Coastal Communities: A Network-Based Approach to Analyzing ‘Livelihood Landscapes’

    Science.gov (United States)

    Cinner, Joshua E.; Bodin, Örjan

    2010-01-01

    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 into communities

  10. 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.

  11. ATHENA (Advanced Thermal Hydraulic Energy Network Analyzer) simulation of a loss of coolant accident in a space reactor

    Energy Technology Data Exchange (ETDEWEB)

    Roth, P.A.; Shumway, R.W.

    1988-01-01

    The Advanced Thermal Hydraulic Energy Network Analyzer (ATHENA) code was used to simulate a loss-of-coolant accident (LOCA) in a conceptual space reactor design. ATHENA provides the capability of simulating the thermal-hydraulic behavior of the wide variety of systems which are being considered for use in space reactors. Flow loops containing any one of several available working fluids may interact through thermal connections with other loops containing the same or a different working fluid. The code can be used to model special systems such as: heat pipes, point reactor kinetics, plant control systems, turbines, valves, and pumps. This work demonstrates the application of the thermal radiation model which has been recently incorporated into ATHENA and verifies the need for supplemental reactor cooling to prevent reactor fuel damage in the event of a LOCA.

  12. 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.

  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)

    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

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

    Directory of Open Access Journals (Sweden)

    Cynthia Semá Baltazar

    2017-10-01

    Full Text Available 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

  15. 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.

  16. 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

  17. Analyzing heterogeneity in the effects of physical activity in children on social network structure and peer selection dynamics.

    Science.gov (United States)

    Henry, Teague; Gesell, Sabina B; Ip, Edward H

    2016-09-01

    Social networks influence children and adolescents' physical activity. The focus of this paper is to examine the differences in the effects of physical activity on friendship selection, with eye to the implications on physical activity interventions for young children. Network interventions to increase physical activity are warranted but have not been conducted. Prior to implementing a network intervention in the field, it is important to understand potential heterogeneities in the effects that activity level have on network structure. In this study, the associations between activity level and cross sectional network structure, and activity level and change in network structure are assessed. We studied a real-world friendship network among 81 children (average age 7.96 years) who lived in low SES neighborhoods, attended public schools, and attended one of two structured aftercare programs, of which one has existed and the other was new. We used the exponential random graph model (ERGMs) and its longitudinal extension to evaluate the association between activity level and various demographic factors in having, forming, and dissolving friendship. Due to heterogeneity between the friendship networks within the aftercare programs, separate analyses were conducted for each network. There was heterogeneity in the effect of physical activity on both cross sectional network structure and the formation and dissolution processes, both across time and between networks. Network analysis could be used to assess the unique structure and dynamics of a social network before an intervention is implemented, so as to optimize the effects of the network intervention for increasing childhood physical activity. Additionally, if peer selection processes are changing within a network, a static network intervention strategy for childhood physical activity could become inefficient as the network evolves.

  18. 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

    entrepreneur’s social network and utilizes the Name Generator approach to develop the social network model. This method maps an ego - centered network and...connection and a back-up power supply. • @TheHub Kampala- @TheHub is located in two renovated Kampala City Council flats on a quiet street and has a

  19. 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.

  20. Effects of specimen preparation on the electromagnetic property measurements of solid materials with an automatic network analyzer

    Science.gov (United States)

    Long, E. R., Jr.

    1986-01-01

    Effects of specimen preparation on measured values of an acrylic's electomagnetic properties at X-band microwave frequencies, TE sub 1,0 mode, utilizing an automatic network analyzer have been studied. For 1 percent or less error, a gap between the specimen edge and the 0.901-in. wall of the specimen holder was the most significant parameter. The gap had to be less than 0.002 in. The thickness variation and alignment errors in the direction parallel to the 0.901-in. wall were equally second most significant and had to be less than 1 degree. Errors in the measurement f the thickness were third most significant. They had to be less than 3 percent. The following parameters caused errors of 1 percent or less: ratios of specimen-holder thicknesses of more than 15 percent, gaps between the specimen edge and the 0.401-in. wall less than 0.045 in., position errors less than 15 percent, surface roughness, hickness variation in the direction parallel to the 0.401-in. wall less than 35 percent, and specimen alignment in the direction parallel to the 0.401-in. wall mass than 5 degrees.

  1. COLLABORATIVE PROBLEM SOLVING USING PUBLIC SOCIAL NETWORK MEDIA: ANALYZING STUDENT INTERACTION AND ITS IMPACT TO LEARNING PROCESS

    OpenAIRE

    Melvin Ballera; Ismail Ateya Lukandu; Abdalla Radwan

    2013-01-01

    This paper examines the use of social network media at three aspects in African and Libyan perspective. Firstly, to use social network media as an open network learning environment that provide service for interaction necessary for learners to support socialization and collaboration during problem solving. Secondly, to use social media as a tool to support blended learning in e-learning system and encourage non-native English students to express their ideas and fill the gap of communication p...

  2. 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)

    Lim, Woohyung; Kim, Myoung Shin; Na, Jung Im; Park, Ilwoo

    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. PMID:29352285

  3. Properties of grain boundary networks in the NEEM ice core analyzed by combined transmission and reflection optical microscopy

    Science.gov (United States)

    Binder, Tobias; Weikusat, Ilka; Garbe, Christoph; Svensson, Anders; Kipfstuhl, Sepp

    2014-05-01

    Microstructure analysis of ice cores is vital to understand the processes controlling the flow of ice on the microscale. To quantify the microstructural variability (and thus occurring processes) on centimeter, meter and kilometer scale along deep polar ice cores, a large number of sections has to be analyzed. In the last decade, two different methods have been applied: On the one hand, transmission optical microscopy of thin sections between crossed polarizers yields information on the distribution of crystal c-axes. On the other hand, reflection optical microscopy of polished and controlled sublimated section surfaces allows to characterize the high resolution properties of a single grain boundary, e.g. its length, shape or curvature (further developed by [1]). Along the entire NEEM ice core (North-West Greenland, 2537 m length) drilled in 2008-2011 we applied both methods to the same set of vertical sections. The data set comprises series of six consecutive 6 x 9 cm2 sections in steps of 20 m - in total about 800 images. A dedicated method for automatic processing and matching both image types has recently been developed [2]. The high resolution properties of the grain boundary network are analyzed. Furthermore, the automatic assignment of c-axis misorientations to visible sublimation grooves enables us to quantify the degree of similarity between the microstructure revealed by both analysis techniques. The reliability to extract grain boundaries from both image types as well as the appearance of sublimation groove patterns exhibiting low misorientations is investigated. X-ray Laue diffraction measurements (yielding full crystallographic orientation) have validated the sensitivity of the surface sublimation method for sub-grain boundaries [3]. We introduce an approach for automatic extraction of sub-grain structures from sublimation grooves. A systematic analysis of sub-grain boundary densities indicates a possible influence of high impurity contents (amongst

  4. Utilizing Social Networks in Times of Crisis: Understanding, Exploring and Analyzing Critical Incident Management at Institutions of Higher Education

    Science.gov (United States)

    Asselin, Martha Jo

    2012-01-01

    With the rising number of major crises on college campuses today (Security on Campus Inc., 2009), institutions of higher education can benefit from understanding of how social networks may be used in times of emergency. What is currently known about the usage of social networks is not integral to the current practices of crisis management that are…

  5. Taking Their Show on the Road: Becky Hebert & Siobhan Champ-Blackwell--National Network of Libraries of Medicine

    Science.gov (United States)

    Library Journal, 2005

    2005-01-01

    They're two very different women with the same mission: outreach to medically underserved populations. Both work for the National Network of Libraries of Medicine. Becky Hebert (left) covers the Southeast/Atlantic region, and Siobhan Champ-Blackwell, the mid-continental region. They spend much of their lives on the road, exhibiting at minority…

  6. 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

  7. 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.

  8. 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.

  9. Two isostructural 3D lanthanide coordination networks (Ln = Gd(3+), Dy(3+)) with squashed cuboid-type nanoscopic cages showing significant cryogenic magnetic refrigeration and slow magnetic relaxation.

    Science.gov (United States)

    Biswas, Soumava; Jena, Himanshu Sekhar; Adhikary, Amit; Konar, Sanjit

    2014-04-21

    Two isostructural lanthanide-based 3D coordination networks [Ln = Gd(3+) (1), Dy(3+)(2)] with densely packed distorted cuboid nanoscopic cages are reported for the first time. Magnetic characterization reveals that complex 1 shows a significant cryogenic magnetocaloric effect (-ΔSm = 44 J kg(-1) K(-1)), whereas 2 shows slow relaxation of magnetization.

  10. 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.

  11. Crystal structure of a partly self-complementary peptide nucleic acid (PNA) oligomer showing a duplex-triplex network

    DEFF Research Database (Denmark)

    Petersson, Britt; Nielsen, Bettina Bryde; Rasmussen, Hanne

    2005-01-01

    of the decamer (G(4)A(5)T(6)C(7)). One right- and one left-handed Watson-Crick duplex are formed. The two PNA units C(9)T(10) change helical handedness, so that each PNA strand contains both a right- and a left-handed section. The changed handedness in C(9)T(10) allows formation of Hoogsteen hydrogen bonding...... Hoogsteen type. The structural diversity of this PNA demonstrates how the PNA backbone is able to adapt to structures governed by the stacking and hydrogen-bonding interactions between the nucleobases. The crystal structure further shows how PNA oligomers containing limited sequence complementarity may form......The X-ray structure of a partly self-complementary peptide nucleic acid (PNA) decamer (H-GTAGATCACT-l-Lys-NH(2)) to 2.60 A resolution is reported. The structure is mainly controlled by the canonical Watson-Crick base pairs formed by the self-complementary stretch of four bases in the middle...

  12. Disease-associated pathophysiologic structures in pediatric rheumatic diseases show characteristics of scale-free networks seen in physiologic systems: implications for pathogenesis and treatment

    Directory of Open Access Journals (Sweden)

    McGhee Timothy

    2009-02-01

    Full Text Available Abstract Background While standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete. Gene expression profiling provides an unprecedented opportunity to understand complex human diseases by providing a global view of the multiple interactions across the genome that are likely to contribute to disease pathogenesis. Thus, the goal of gene expression profiling is not to generate lists of differentially expressed genes, but to identify the physiologic or pathogenic processes and structures represented in the expression profile. Methods RNA was separately extracted from peripheral blood neutrophils and mononuclear leukocytes, labeled, and hybridized to genome level microarrays to generate expression profiles of children with polyarticular juvenile idiopathic arthritis, juvenile dermatomyositis relative to childhood controls. Statistically significantly differentially expressed genes were identified from samples of each disease relative to controls. Functional network analysis identified interactions between products of these differentially expressed genes. Results In silico models of both diseases demonstrated similar features with properties of scale-free networks previously described in physiologic systems. These networks were observable in both cells of the innate immune system (neutrophils and cells of the adaptive immune system (peripheral blood mononuclear cells. Conclusion Genome-level transcriptional profiling from childhood onset rheumatic diseases suggested complex interactions in two arms of the immune system in both diseases. The disease associated networks showed scale-free network patterns similar to those reported in normal physiology. We postulate that these features have important implications for therapy as such networks are relatively resistant

  13. The gene expression profiling of hepatocellular carcinoma by a network analysis approach shows a dominance of intrinsically disordered proteins (IDPs) between hub nodes.

    Science.gov (United States)

    Singh, Sakshi; Colonna, Giovanni; Di Bernardo, Giovanni; Bergantino, Francesca; Cammarota, Marcella; Castello, Giuseppe; Costantini, Susan

    2015-11-01

    We have analyzed the transcriptomic data from patients with hepatocellular carcinoma (HCC) after viral HCV infection at the various stages of the disease by means of a networking analysis using the publicly available E-MTAB-950 dataset. The data was compared with those obtained in our group from HepG2 cells, a cancer cell line that lacks the viral infection. By sequential pruning of data, and also taking into account the data from cells of healthy patients as blanks, we were able to obtain a distribution of hub genes for the various stages that characterize the disease and finally, we isolated a metabolic sub-net specific to HCC alone. The general picture is that the basic organization to energetically and metabolically sustain the cells in both the normal and diseased conditions is the same, but a complex cluster of sub-networks controlled by hub genes drives the HCC progression with high metabolic flexibility and plasticity. In particular, we have extracted a sub-net of genes strictly correlated to other hub genes of the network from HepG2 cells, but specific for the HCC and mainly devoted to: (i) control at chromatin levels of cell division; (ii) control of ergastoplasmatic stress through protein degradation and misfolding; (iii) control of the immune response also through an increase of mature T-cells in the thymus. This sub-net is characterized by 26 hub genes coding for intrinsically disordered proteins with a high ability to interact with numerous molecular partners. Moreover, we have also noted that periphery molecules, that is, with one or very few interactions (e.g., cytokines or post-translational enzymes), which do not have a central role in the clusters that make up the global metabolic network, essentially have roles as information transporters. The results evidence a strong presence of intrinsically disordered proteins with key roles as hubs in the sub-networks that characterize the various stages of the disease, conferring a structural plasticity to

  14. 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.

  15. Adopting European Network for Health Technology Assessments (EunetHTA) core model for diagnostic technologies for improving the accuracy and appropriateness of blood gas analyzers' assessment.

    Science.gov (United States)

    Franchin, Tiziana; Faggiano, Francesco; Plebani, Mario; Muraca, Maurizio; De Vivo, Liliana; Derrico, Pietro; Ritrovato, Matteo

    2014-11-01

    Point-of-care testing (POCT) is a successful methodology for meeting clinical expectations of rapid and accurate results. Scientific literature has moreover highlighted and confirmed the necessity of individuating the best technological solution, in accordance with clinical requirements and contextualized to the whole health organization, where it will be implemented. Health Technology Assessment (HTA) can assist in reaching an appropriate and contextualized decision on a health technology. The aim of this study is to adapt a HTA core model for improving the evaluation of a POCT technology: blood gas analyzers. The European Network for Health Technology Assessment (EUnetHTA) core model for diagnostic technologies was applied for evaluating globally marketed blood gas analyzers. Evaluation elements were defined according to available literature and validated using the Delphi method. A HTA model of 71 issues, subdivided into 26 topics and 10 domains, was obtained by interviewing 11 healthcare experts over two rounds of Delphi questionnaires. Ten context parameters were identified in order to define the initial scenario from which the technology assessment was to begin. The model presented offers a systematic and objective structure for the evaluation of blood gas analyzers, which may play a guidance role for healthcare operators approaching the evaluation of such technologies thus improving, in a contextualized fashion, the appropriateness of purchasing.

  16. 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…

  17. A combined finite element-Langevin dynamics (FEM-LD) approach for analyzing the mechanical response of bio-polymer networks

    Science.gov (United States)

    Lin, Yuan; Wei, X.; Qian, J.; Sze, K. Y.; Shenoy, V. B.

    2014-01-01

    A Langevin dynamics based formulation is proposed to describe the shape fluctuations of biopolymer filaments. We derive a set of stochastic partial differential equations (SPDEs) to describe the temporal evolution of the shape of semiflexible filaments and show that the solutions of these equations reduce to predictions from classical modal analysis. A finite element formulation to solve these SPDEs is also developed where, besides entropy, the finite deformation of the filaments has been taken into account. The validity of the proposed finite element-Langevin dynamics (FEM-LD) approach is verified by comparing the simulation results with a variety of theoretical predictions. The method is then applied to study the mechanical behavior of randomly cross-linked F-actin networks. We find that as deformation progresses, the response of such networks undergoes transitions from being entropy dominated to being governed by filament bending and then, eventually, to being dictated by filament stretching. The levels of macroscopic stress at which these transitions take place were found to be around 1% and 10%, respectively, of the initial bulk modulus of the network, in agreement with recent experimental observations.

  18. 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.

  19. Targeting PI3K, mTOR, ERK, and Bcl-2 signaling network shows superior antileukemic activity against AML ex vivo.

    Science.gov (United States)

    Su, Yongwei; Li, Xinyu; Ma, Jun; Zhao, Jianyun; Liu, Shuang; Wang, Guan; Edwards, Holly; Taub, Jeffrey W; Lin, Hai; Ge, Yubin

    2017-12-05

    Acute myeloid leukemia (AML) remains challenging to treat and needs more effective treatments. The PI3K/mTOR pathway is involved in cell survival and has been shown to be constitutively active in 50-80% of AML patients. However, targeting the PI3K/mTOR pathway results in activation of the ERK pathway, which also plays an important role in cell survival. In addition, AML cells often overexpress antiapoptotic Bcl-2 family proteins (e.g., Bcl-2), preventing cell death. Thus, our strategy here is to target the PI3K, mTOR (by VS-5584, a PI3K and mTOR dual inhibitor), ERK (by SCH772984, an ERK-selective inhibitor), and Bcl-2 (by ABT-199, a Bcl-2-selective inhibitor) signaling network to kill AML cells. In this study, we show that while inhibition of PI3K, mTOR, and ERK showed superior induction of cell death compared to inhibition of PI3K and mTOR, the levels of cell death were modest in some AML cell lines and primary patient samples tested. Although simultaneous inhibition of PI3K, mTOR, and ERK caused downregulation of Mcl-1 and upregulation of Bim, immunoprecipitation of Bcl-2 revealed increased binding of Bim to Bcl-2, which was abolished by the addition of ABT-199, suggesting that Bim was bound to Bcl-2 which prevented cell death. Treatment with combined VS-5584, SCH772984, and ABT-199 showed significant increase in cell death in AML cell lines and primary patient samples and significant reduction in AML colony formation in primary patient samples, while there was no significant effect on colony formation of normal human CD34+ hematopoietic progenitor cells. Taken together, our findings show that inhibition of PI3K, mTOR, and ERK synergistically induces cell death in AML cells, and addition of ABT-199 enhances cell death further. Thus, our data support targeting the PI3K, mTOR, ERK, and Bcl-2 signaling network for the treatment of AML. Copyright © 2017. Published by Elsevier Inc.

  20. Analyzing Thiol-Dependent Redox Networks in the Presence of Methylene Blue and Other Antimalarial Agents with RT-PCR-Supported in silico Modeling

    Science.gov (United States)

    Zirkel, J.; Cecil, A.; Schäfer, F.; Rahlfs, S.; Ouedraogo, A.; Xiao, K.; Sawadogo, S.; Coulibaly, B.; Becker, K.; Dandekar, T.

    2012-01-01

    Background In the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data. Results We built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs for redox enzymes) as constraints and results from the YANA software package for metabolic pathway calculations. Several different lines of MB attack on Plasmodium redox defense were identified by analysis of the network effects. Next, chloroquine resistance based on pfmdr/and pfcrt transporters, as well as pyrimethamine/sulfadoxine resistance (by mutations in DHF/DHPS), were modeled in silico. Further modeling shows that MB has a favorable synergism on antimalarial network effects with these commonly used antimalarial drugs. Conclusions Theoretical and experimental results support that methylene blue should, because of its resistance-breaking potential, be further tested as a key component in drug combination therapy efforts in holoendemic areas. PMID:23236254

  1. Comparison of Free Space Measurement Using a Vector Network Analyzer and Low-Cost-Type THz-TDS Measurement Methods Between 75 and 325 GHz

    Science.gov (United States)

    Ozturk, Turgut; Morikawa, Osamu; Ünal, İlhami; Uluer, İhsan

    2017-10-01

    Specifications of two measurement systems, free space measurement using a vector network analyzer and low-cost-type terahertz time-domain spectroscopy using a multimode laser diode, have been compared in the frequency region of millimeter/sub-THz waves. In the comparison, accuracy, cost, measurement time, calculation time, etc. were considered. Four samples (Rexolite, RO3003, Ultralam 3850HT-design, and L1000HF) were selected for the comparison of the specifications of the two methods. The acquired data was used to compute the complex permittivity of measured materials. The extracted results by free space measurement agreed well to the ones obtained by low-cost-type terahertz time-domain spectroscopy. This result proves free space measurement that can be assessed as a new method of material characterization in the sub-THz region successfully worked. Furthermore, free space measurement was proved to be suitable for a measurement in a narrow frequency range. On the other hand, low-cost-type terahertz time-domain spectroscopy has features not only low cost but also measurement capability in wide frequency range.

  2. 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.

  3. 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

  4. Clustering signatures classify directed networks

    Science.gov (United States)

    Ahnert, S. E.; Fink, T. M. A.

    2008-09-01

    We use a clustering signature, based on a recently introduced generalization of the clustering coefficient to directed networks, to analyze 16 directed real-world networks of five different types: social networks, genetic transcription networks, word adjacency networks, food webs, and electric circuits. We show that these five classes of networks are cleanly separated in the space of clustering signatures due to the statistical properties of their local neighborhoods, demonstrating the usefulness of clustering signatures as a classifier of directed networks.

  5. Linking concepts in the ecology and evolution of invasive plants: network analysis shows what has been most studied and identifies knowledge gaps.

    Science.gov (United States)

    Vanderhoeven, Sonia; Brown, Cynthia S; Tepolt, Carolyn K; Tsutsui, Neil D; Vanparys, Valérie; Atkinson, Sheryl; Mahy, Grégory; Monty, Arnaud

    2010-03-01

    In recent decades, a growing number of studies have addressed connections between ecological and evolutionary concepts in biologic invasions. These connections may be crucial for understanding the processes underlying invaders' success. However, the extent to which scientists have worked on the integration of the ecology and evolution of invasive plants is poorly documented, as few attempts have been made to evaluate these efforts in invasion biology research. Such analysis can facilitate recognize well-documented relationships and identify gaps in our knowledge. In this study, we used a network-based method for visualizing the connections between major aspects of ecology and evolution in the primary research literature. Using the family Poaceae as an example, we show that ecological concepts were more studied and better interconnected than were evolutionary concepts. Several possible connections were not documented at all, representing knowledge gaps between ecology and evolution of invaders. Among knowledge gaps, the concepts of plasticity, gene flow, epigenetics and human influence were particularly under-connected. We discuss five possible research avenues to better understand the relationships between ecology and evolution in the success of Poaceae, and of alien plants in general.

  6. 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...

  7. DOG optical gas analyzers

    Energy Technology Data Exchange (ETDEWEB)

    Azbukin, A.A.; Buldakov, M.A.; Korolev, B.V.; Korolo' kov, V.A.; Matrosov, I.I. [Siberian Branch of the Russian Academy of Sciences, Tomsk (Russian Federation). Inst. of Optical Monitoring

    2002-01-01

    Stationary gas analyzers for continuous monitoring of sulfur and nitrogen oxides in exhaust gases of electric power plants burning fossil fuels have been developed. The DOG series of gas-analyzers use non-laser UV radiation sources and the differential absorption lidar (DIAL) measurement technique. Operation of the gas-analyzers at Russian electric power plants showed their high efficiency, reliability, and easiness in operation at lower cost as compared to similar foreign devices. 8 refs., 3 figs., 1 tab.

  8. ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems.

    Science.gov (United States)

    Kaimal, Vivek; Bardes, Eric E; Tabar, Scott C; Jegga, Anil G; Aronow, Bruce J

    2010-07-01

    ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3'UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster's functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org.

  9. Lanthanide-organic coordination frameworks showing new 5-connected network topology and 3D ordered array of single-molecular magnet behavior in the Dy case.

    Science.gov (United States)

    Chen, Min; Sañudo, E Carolina; Jiménez, Erika; Fang, Shao-Ming; Liu, Chun-Sen; Du, Miao

    2014-07-07

    Five isostructural lanthanide-organic coordination frameworks with a unique 3-D 5-connected (4(7).6(3))(4(3).6(5).8(2)) network, namely, [Ln(phen)(L)]n (Ln = Dy for 1, Gd for 2, Ho for 3, Er for 4, and Tb for 5), have been prepared based on bridging 5-hydroxyisophthalic acid (H3L) and chelating 1,10-phenanthroline (phen) coligand. Significantly, the Dy(III) complex 1 is an organized array of single-molecular magnets (SMMs), with frequency-dependent out-of-phase ac susceptibility signals and magnetization hysteresis at 4 K. Further analysis of the magnetic results can reveal that the SMM behavior of 1 should arise from the smaller ferromagnetic interaction between the Dy(III) ions. Complex 1 was also characterized by X-ray absorption spectra, which give the clear X-ray magnetic circular dichroism signal.

  10. 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.

  11. 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...... 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...... 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...

  12. 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.

  13. Networking for the Environment

    DEFF Research Database (Denmark)

    Dickel, Petra; Hörisch, Jacob; Ritter, Thomas

    2018-01-01

    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......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...

  14. 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.

  15. A system for measuring complex dielectric properties of thin films at submillimeter wavelengths using an open hemispherical cavity and a vector network analyzer

    Science.gov (United States)

    Rahman, Rezwanur; Taylor, P. C.; Scales, John A.

    2013-08-01

    Quasi-optical (QO) methods of dielectric spectroscopy are well established in the millimeter and submillimeter frequency bands. These methods exploit standing wave structure in the sample produced by a transmitted Gaussian beam to achieve accurate, low-noise measurement of the complex permittivity of the sample [e.g., J. A. Scales and M. Batzle, Appl. Phys. Lett. 88, 062906 (2006);, 10.1063/1.2172403 R. N. Clarke and C. B. Rosenberg, J. Phys. E 15, 9 (1982);, 10.1088/0022-3735/15/1/002 T. M. Hirovnen, P. Vainikainen, A. Lozowski, and A. V. Raisanen, IEEE Trans. Instrum. Meas. 45, 780 (1996)], 10.1109/19.516996. In effect the sample itself becomes a low-Q cavity. On the other hand, for optically thin samples (films of thickness much less than a wavelength) or extremely low loss samples (loss tangents below 10-5) the QO approach tends to break down due to loss of signal. In such a case it is useful to put the sample in a high-Q cavity and measure the perturbation of the cavity modes. Provided that the average mode frequency divided by the shift in mode frequency is less than the Q (quality factor) of the mode, then the perturbation should be resolvable. Cavity perturbation techniques are not new, but there are technological difficulties in working in the millimeter/submillimeter wave region. In this paper we will show applications of cavity perturbation to the dielectric characterization of semi-conductor thin films of the type used in the manufacture of photovoltaics in the 100 and 350 GHz range. We measured the complex optical constants of hot-wire chemical deposition grown 1-μm thick amorphous silicon (a-Si:H) film on borosilicate glass substrate. The real part of the refractive index and dielectric constant of the glass-substrate varies from frequency-independent to linearly frequency-dependent. We also see power-law behavior of the frequency-dependent optical conductivity from 316 GHz (9.48 cm-1) down to 104 GHz (3.12 cm-1).

  16. 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.

  17. Inferring Social Relations from Online and Communication Networks

    OpenAIRE

    Nasim, Mehwish

    2016-01-01

    In this work analyzed the interplay between social relations in the form of friendship ties, attributes and interaction in online social networks. In this context we analyzed composition of social circles in online social networks and showed that social circles are homophilious with respect to at least one node attribute. We showed that using the right combination of network and interaction features, links can be inferred in online covert networks. We also analyzed longitudinal dyadic interac...

  18. 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

  19. Timed Automata Semantics for Analyzing Creol

    Directory of Open Access Journals (Sweden)

    Mohammad Mahdi Jaghoori

    2010-07-01

    Full Text Available We give a real-time semantics for the concurrent, object-oriented modeling language Creol, by mapping Creol processes to a network of timed automata. We can use our semantics to verify real time properties of Creol objects, in particular to see whether processes can be scheduled correctly and meet their end-to-end deadlines. Real-time Creol can be useful for analyzing, for instance, abstract models of multi-core embedded systems. We show how analysis can be done in Uppaal.

  20. An integrated systems calculation of a steam generator tube rupture in a modular prismatic HTGR (high-temperature gas-cooled reactor) conceptual design using ATHENA (Advanced Thermal-Hydraulic Energy Network Analyzer)

    Energy Technology Data Exchange (ETDEWEB)

    Beelman, R.J. (Idaho National Engineering Laboratory, Idaho Falls (USA))

    1989-11-01

    The capability to perform integrated systems calculations of modular high-temperature gas-cooled reactor (MHTGR) transients has been developed at the Idaho National Engineering Laboratory (INEL) using the Advanced Thermal-Hydraulic Energy Network Analyzer (ATHENA) computer code. A scoping calculation of a steam generator tube rupture (SGTR) water ingress event in a prismatic 2 {times} 350-MW(thermal) MHTGR conceptual design has been completed at INEL using ATHENA. The proposed MHTGR design incorporates dual, graphite-moderated, helium-cooled, 350-MW(thermal), annular prismatic core concept reactor plants, each configured with an individual helical once-through steam generator steaming a common 280-MW(electric) turbine generator set.

  1. 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.

  2. 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.

  3. 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.

  4. Analyzing complicity in risk.

    Science.gov (United States)

    Busby, Jerry

    2008-12-01

    When risks generate anger rather than fear, there is at least someone who regards the imposition of those risks as wrongdoing; and it then makes sense to speak of the involvement in producing those risks as complicity. It is particularly relevant to examine the complicity of risk bearers, because this is likely to have a strong influence on how far other actors should go in providing them with protection. This article makes a case for analyzing complicity explicitly, in parallel with normal processes of risk assessment, and proposes a framework for this analysis. It shows how it can be applied in a case study of maritime transportation, and examines the practical and theoretical difficulties of this kind of analysis. The conclusion is that the analysis has to be formative rather than summative, but that it could provide a useful way of exposing differences in the assumptions of different actors about agency and responsibility.

  5. 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.

  6. 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

    2011-01-01

    Background The Community Clinical Oncology Program (CCOP) plays an essential role in the National Cancer Institute’s (NCI) efforts to increase enrollment in clinical trials. There is currently 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. This paper presents a conceptual model of the business case for PBRN participation and provides a spreadsheet-based tool and advice for evaluating the business case for provider participation in a CCOP organization. Methods A comparative, case-study approach was used to identify key components of the business case for hospitals attempting to support a CCOP research infrastructure. Semi-structured interviews were conducted with providers and administrators. Key themes were identified and used to develop the financial analysis tool. Results Key components of the business case include 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 value of incidental benefits is recognized as an important contributor to the business case for CCOP participation, but is not currently calculated. Conclusions 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. PMID:22213241

  7. 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

  8. Bios data analyzer.

    Science.gov (United States)

    Sabelli, H; Sugerman, A; Kovacevic, L; Kauffman, L; Carlson-Sabelli, L; Patel, M; Konecki, J

    2005-10-01

    The Bios Data Analyzer (BDA) is a set of computer programs (CD-ROM, in Sabelli et al., Bios. A Study of Creation, 2005) for new time series analyses that detects and measures creative phenomena, namely diversification, novelty, complexes, nonrandom complexity. We define a process as creative when its time series displays these properties. They are found in heartbeat interval series, the exemplar of bios .just as turbulence is the exemplar of chaos, in many other empirical series (galactic distributions, meteorological, economic and physiological series), in biotic series generated mathematically by the bipolar feedback, and in stochastic noise, but not in chaotic attractors. Differencing, consecutive recurrence and partial autocorrelation indicate nonrandom causation, thereby distinguishing chaos and bios from random and random walk. Embedding plots distinguish causal creative processes (e.g. bios) that include both simple and complex components of variation from stochastic processes (e.g. Brownian noise) that include only complex components, and from chaotic processes that decay from order to randomness as the number of dimensions is increased. Varying bin and dimensionality show that entropy measures symmetry and variety, and that complexity is associated with asymmetry. Trigonometric transformations measure coexisting opposites in time series and demonstrate bipolar, partial, and uncorrelated opposites in empirical processes and bios, supporting the hypothesis that bios is generated by bipolar feedback, a concept which is at variance with standard concepts of polar and complementary opposites.

  9. Universal MOSFET parameter analyzer

    Science.gov (United States)

    Klekachev, A. V.; Kuznetsov, S. N.; Pikulev, V. B.; Gurtov, V. A.

    2006-05-01

    MOSFET analyzer is developed to extract most important parameters of transistors. Instead of routine DC transfer and output characteristics, analyzer provides an evaluation of interface states density by applying charge pumping technique. There are two features that outperform the analyzer among similar products of other vendors. It is compact (100 × 80 × 50 mm 3 in dimensions) and lightweight (instrument with ultra low power supply (instrument was designed on the base of component parts from CYPRESS and ANALOG DEVICES (USA).

  10. 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.

  11. 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....

  12. 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 various interviews conveyed diverse significance to the listening researcher at different times became a method of continuously opening up the empirical material in a reflexive, breakdown-oriented process of analysis. We argue that situating analysis in the present of analyzing emphasizes and acknowledges...

  13. Software Design Analyzer System

    Science.gov (United States)

    Tausworthe, R. C.

    1985-01-01

    CRISP80 software design analyzer system a set of programs that supports top-down, hierarchic, modular structured design, and programing methodologies. CRISP80 allows for expression of design as picture of program.

  14. 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...

  15. Los programas radiofónicos españoles de prime time en Facebook y Twitter: Sinergias entre la radio convencional y las redes sociales/Spanish primetime radio shows in Facebook and Twitter: Synergies between on-air radio broadcasting and social networks

    National Research Council Canada - National Science Library

    M Gutiérrez; J M Martí; I Ferrer; B Monclús; X Ribes

    2014-01-01

    ...: To define the synergies between conventional radio broadcasting and social networks in Spanish talk radio based on the analysis of four primetime radio shows, which are the flagship programmes of their radio stations. Method...

  16. 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.

  17. 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 made from digital scans of the original dias slides located in the collection of the Museum of Contemporary Art in Roskilde. In front of the audience entering the space and placed on it’s own stand, is an original 60s style telephone with turning dial. Action begins when the audience lift the phone...... and dial a number. Any number will make the Dias change. All numbers are also assigned to specific sound documents: clips form rare interviews and the complete sound-re-enactment of the Show-Bix piece ‘Omringning’ (‘Surrounding’) in five channels (a quintophonie). This was originally produced...

  18. Show and Tell

    DEFF Research Database (Denmark)

    2013-01-01

    Fredag d. 1 november blev Kunsthal Charlottenborg indtaget af performanceprogrammet Show & Tell med et bredspektret program af danske og internationale kunstnere indenfor performance-, lyd- og installationskunst. Programmet præsenterer værker, der undersøger kroppens stadig mere symbiotiske forhold...... og studienævnet på Performance-design. Show & Tell - Performance program: kl. 16.30-19 Adresse: Kunsthal Charlottenborg, Nyhavn 2, 1051 København K...

  19. International tourism network

    Science.gov (United States)

    Miguéns, Joana I. L.; Mendes, José F. F.; Costa, Carlos M. M.

    2007-06-01

    The interest in tourism has always been strong, for its important role in economic flows among nations. On this study we analyze the arrivals of international tourism (edges) over 206 countries and territories (nodes) around the world, on the year 2004. International tourist arrivals reached a record of 763 million in 2004. We characterize analytically the topological and weighted properties of the resulting network. International tourist arrivals are analyzed over in strength and out strength flows, resulting on a highly directed network, with a very heterogeneity of weights and strengths. The inclusion of edge weights and directions on the analysis of network architecture allows a more realistic insight on the structure of the networks. Centrality, assortativity and disparity are measured for the topological and weighted structure. Assortativity measures the tendency of having a high weight edges connecting two nodes with similar degrees. ITN is disassortative, opposite to social network. Disparity quantifies the how similar are the flows on a node neighborhood, measuring the heterogeneity of weights for in flows and out flows of tourism. These results provide an application of the recent methods of weighted and directed networks, showing that weights are relevant and that in general the modeling of complex networks must go beyond topology. The network structure may influence how tourism hubs, distribution of flows, and centralization can be explored on countries strategic positioning and policy making.

  20. 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.

  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. PMID:23162688

  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 Stereotypes in Media.

    Science.gov (United States)

    Baker, Jackie

    1996-01-01

    A high school film teacher studied how students recognized messages in film, examining how film education could help students identify and analyze racial and gender stereotypes. Comparison of students' attitudes before and after the film course found that the course was successful in raising students' consciousness. (SM)

  5. Context-dependent metabolic networks

    CERN Document Server

    Beguerisse-Díaz, Mariano; Oyarzún, Diego; Picó, Jesús; Barahona, Mauricio

    2016-01-01

    Cells adapt their metabolism to survive changes in their environment. We present a framework for the construction and analysis of metabolic reaction networks that can be tailored to reflect different environmental conditions. Using context-dependent flux distributions from Flux Balance Analysis (FBA), we produce directed networks with weighted links representing the amount of metabolite flowing from a source reaction to a target reaction per unit time. Such networks are analyzed with tools from network theory to reveal salient features of metabolite flows in each biological context. We illustrate our approach with the directed network of the central carbon metabolism of Escherichia coli, and study its properties in four relevant biological scenarios. Our results show that both flow and network structure depend drastically on the environment: networks produced from the same metabolic model in different contexts have different edges, components, and flow communities, capturing the biological re-routing of metab...

  6. 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....... More specifically, the article demonstrates how online comments posted on the day of Voice’s 2012 season finale can be grouped into four basic action types: (1) Invitation to consume content, (2) Request for participation, (3) Request for collaboration and (4) Online commenting. These action types...

  7. Um show de cacau

    OpenAIRE

    Rezende, José Francisco; UNIGRANRIO / PPGA; Mello, Simone; UNIGRANRIO

    2016-01-01

    O caso de ensino apresenta a trajetória de Alexandre Tadeu da Costa e da chocolateria Cacau Show. Seu objetivo é levar os estudantes a identificar alternativas e tomar decisões sobre posicionamento para continuidade do desenvolvimento de vantagens competitivas, sustentação de competência logística e possíveis abordagens ao mercado externo. 

  8. Positioning Guests in a Maybrit Illner Talk Show

    Directory of Open Access Journals (Sweden)

    Reinhold Schmitt

    2015-12-01

    Full Text Available In this paper we analyze techniques applied by the producers of a talk show in order to position the talk show guests as relevant participants with respect to the subject of fiscal evasion by celebrities. We analyze how the producers succeed in positioning their guests right from the beginning as prototypical representatives. This positioning is achieved through the coordination of a voice from offstage and the management of the cameras when the guests first appear on screen. Two of five guest introductions are analyzed in detail. The two presented guests demonstrate a clearly antagonistic relationship and their introduction is immediately consecutive. We have reconstructed the introduction of all five guests in detail which resulted in the identification of a network of positions. Unfortunately we cannot present all of our analyses here due to the lack of space. At the positional network's center lies the thematic and personal "antagonism" which we reconstructed. At the periphery we have four representatives of societally relevant positions who contribute to the topic of the talk show. The four guests respectively represent jurisdiction, politics, and ethics via a lay perspective, psychology and theology. The analysis is theoretically framed by the multimodal notion of "positioning" and "recipient design", while the applied methodology is multimodal interaction analysis.

  9. Ocular Response Analyzer

    OpenAIRE

    Kaushik, Sushmita; Pandav, Surinder Singh

    2012-01-01

    Until recently, corneal biomechanical properties could not be measured in vivo. The ocular response analyzer is a new, noninvasive device that analyses corneal biomechanical properties simply and rapidly. The ORA allows cornea compensated IOP measurements and can estimate corneal hysteresis (CH) and corneal resistance factor (CRF). It is designed to improve the accuracy of IOP measurement by using corneal biomechanical data to calculate a biomechanically adjusted estimate of intraocular press...

  10. Analyzing sustainable competitive advantage

    OpenAIRE

    Abdul Malek Nurul Aida; Shahzad Khuram; Takala Josu; Bojnec Stefan; Papler Drago; Liu Yang

    2016-01-01

    In today’s dynamic business environment, a key challenge for all companies is to make adaptive adjustments to their manufacturing strategy. This study demonstrates the competitive priorities of manufacturing strategy in hydro-power case company to evaluate the level of sustainable competitive advantage and also to further analyze how business strategies are aligned with manufacturing strategies. This research is based on new holistic analytical evaluation of manufacturing strategy index, sens...

  11. Taking in a Show.

    Science.gov (United States)

    Boden, Timothy W

    2016-01-01

    Many medical practices have cut back on education and staff development expenses, especially those costs associated with conventions and conferences. But there are hard-to-value returns on your investment in these live events--beyond the obvious benefits of acquired knowledge and skills. Major vendors still exhibit their services and wares at many events, and the exhibit hall is a treasure-house of information and resources for the savvy physician or administrator. Make and stick to a purposeful plan to exploit the trade show. You can compare products, gain new insights and ideas, and even negotiate better deals with representatives anxious to realize returns on their exhibition investments.

  12. 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...... of the scale's reliability, factor structure, and validity on the basis of analyzing data from independent samples of exhibitors at the international trade shows SIAL (Paris) and ANUGA (Cologne); and it concludes with a discussion of potential managerial applications and implications for future research. New...

  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. Inductive dielectric analyzer

    Science.gov (United States)

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

    2017-03-01

    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.

  15. 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.

  16. 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. PMID:25723751

  17. Structure of triadic relations in multiplex networks

    Science.gov (United States)

    Cozzo, Emanuele; Kivelä, Mikko; De Domenico, Manlio; Solé-Ribalta, Albert; Arenas, Alex; Gómez, Sergio; Porter, Mason A.; Moreno, Yamir

    2015-07-01

    Recent advances in the study of networked systems have highlighted that our interconnected world is composed of networks that are coupled to each other through different ‘layers’ that each represent one of many possible subsystems or types of interactions. Nevertheless, it is traditional to aggregate multilayer networks into a single weighted network in order to take advantage of existing tools. This is admittedly convenient, but it is also extremely problematic, as important information can be lost as a result. It is therefore important to develop multilayer generalizations of network concepts. In this paper, we analyze triadic relations and generalize the idea of transitivity to multiplex networks. By focusing on triadic relations, which yield the simplest type of transitivity, we generalize the concept and computation of clustering coefficients to multiplex networks. We show how the layered structure of such networks introduces a new degree of freedom that has a fundamental effect on transitivity. We compute multiplex clustering coefficients for several real multiplex networks and illustrate why one must take great care when generalizing standard network concepts to multiplex networks. We also derive analytical expressions for our clustering coefficients for ensemble averages of networks in a family of random multiplex networks. Our analysis illustrates that social networks have a strong tendency to promote redundancy by closing triads at every layer and that they thereby have a different type of multiplex transitivity from transportation networks, which do not exhibit such a tendency. These insights are invisible if one only studies aggregated networks.

  18. Network neuroscience.

    Science.gov (United States)

    Bassett, Danielle S; Sporns, Olaf

    2017-02-23

    Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.

  19. Field Deployable DNA analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Wheeler, E; Christian, A; Marion, J; Sorensen, K; Arroyo, E; Vrankovich, G; Hara, C; Nguyen, C

    2005-02-09

    This report details the feasibility of a field deployable DNA analyzer. Steps for swabbing cells from surfaces and extracting DNA in an automatable way are presented. Since enzymatic amplification reactions are highly sensitive to environmental contamination, sample preparation is a crucial step to make an autonomous deployable instrument. We perform sample clean up and concentration in a flow through packed bed. For small initial samples, whole genome amplification is performed in the packed bed resulting in enough product for subsequent PCR amplification. In addition to DNA, which can be used to identify a subject, protein is also left behind, the analysis of which can be used to determine exposure to certain substances, such as radionuclides. Our preparative step for DNA analysis left behind the protein complement as a waste stream; we determined to learn if the proteins themselves could be analyzed in a fieldable device. We successfully developed a two-step lateral flow assay for protein analysis and demonstrate a proof of principle assay.

  20. Ring Image Analyzer

    Science.gov (United States)

    Strekalov, Dmitry V.

    2012-01-01

    Ring Image Analyzer software analyzes images to recognize elliptical patterns. It determines the ellipse parameters (axes ratio, centroid coordinate, tilt angle). The program attempts to recognize elliptical fringes (e.g., Newton Rings) on a photograph and determine their centroid position, the short-to-long-axis ratio, and the angle of rotation of the long axis relative to the horizontal direction on the photograph. These capabilities are important in interferometric imaging and control of surfaces. In particular, this program has been developed and applied for determining the rim shape of precision-machined optical whispering gallery mode resonators. The program relies on a unique image recognition algorithm aimed at recognizing elliptical shapes, but can be easily adapted to other geometric shapes. It is robust against non-elliptical details of the image and against noise. Interferometric analysis of precision-machined surfaces remains an important technological instrument in hardware development and quality analysis. This software automates and increases the accuracy of this technique. The software has been developed for the needs of an R&TD-funded project and has become an important asset for the future research proposal to NASA as well as other agencies.

  1. Trace impurity analyzer

    Energy Technology Data Exchange (ETDEWEB)

    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/sub 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. PhosphoSiteAnalyzer

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...... for further interrogation. To answer biologically relevant questions from these complex data sets, it becomes essential to apply computational, statistical, and predictive analytical methods. Here we provide an advanced bioinformatic platform termed "PhosphoSiteAnalyzer" to explore large phosphoproteomic data...... 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...

  3. System performance analyzer

    Science.gov (United States)

    Helbig, H. R.

    1981-01-01

    The System Performance Analyzer (SPA) designed to provide accurate real time information about the operation of complex systems and developed for use on the Airborne Data Analysis/Monitor System (ADAMS), a ROLM 1666 based system is described. The system uses an external processor to operate an intelligent, simulated control panel. Also provided are functions to trace operations, determine frequency of use of memory areas, and time or count user tasks in a multitask environment. This augments the information available from the standard debugger and control panel, and reduces the time and effort needed by ROLM 1666 users in optimizing their system, as well as providing documentation of the effect of any changes. The operation and state of the system are evaluated.

  4. 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.

  5. Analyzing the Information Economy: Tools and Techniques.

    Science.gov (United States)

    Robinson, Sherman

    1986-01-01

    Examines methodologies underlying studies which measure the information economy and considers their applicability and limitations for analyzing policy issues concerning libraries and library networks. Two studies provide major focus for discussion: Porat's "The Information Economy: Definition and Measurement" and Machlup's…

  6. Analyzing Spacecraft Telecommunication Systems

    Science.gov (United States)

    Kordon, Mark; Hanks, David; Gladden, Roy; Wood, Eric

    2004-01-01

    Multi-Mission Telecom Analysis Tool (MMTAT) is a C-language computer program for analyzing proposed spacecraft telecommunication systems. MMTAT utilizes parameterized input and computational models that can be run on standard desktop computers to perform fast and accurate analyses of telecommunication links. MMTAT is easy to use and can easily be integrated with other software applications and run as part of almost any computational simulation. It is distributed as either a stand-alone application program with a graphical user interface or a linkable library with a well-defined set of application programming interface (API) calls. As a stand-alone program, MMTAT provides both textual and graphical output. The graphs make it possible to understand, quickly and easily, how telecommunication performance varies with variations in input parameters. A delimited text file that can be read by any spreadsheet program is generated at the end of each run. The API in the linkable-library form of MMTAT enables the user to control simulation software and to change parameters during a simulation run. Results can be retrieved either at the end of a run or by use of a function call at any time step.

  7. 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.

  8. Enterpreneurial network

    OpenAIRE

    Thoma, Antonela; Nguyen, Lien; Kupsyte, Valdone

    2014-01-01

    Network has become more and more indispensable in the entrepreneurial world. Especially in startup businesses, network is crucial for new entrepreneurs. This project looks at how entrepreneurs in different sectors use network to become successful. We chose to work with three entrepreneurs from three companies that have been operational for a few years and conducted face to face interviews with them. Through the data from the interviews, we analyzed firstly what type of entrepreneurs they are,...

  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. 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.

  11. 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.

  12. Open innovation in networks

    DEFF Research Database (Denmark)

    Hu, Yimei

    Open innovation in networks has been a popular topic for long, this paper rethinks the concepts of innovation network and network organization, and clarifies the differences between them based on the network perspective. Network perspective means that: network is the context of firms; market...... 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. Soft Decision Analyzer

    Science.gov (United States)

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

    2013-01-01

    The Soft Decision Analyzer (SDA) is an instrument that combines hardware, firmware, and software to perform realtime closed-loop end-to-end statistical analysis of single- or dual- channel serial digital RF communications systems operating in very low signal-to-noise conditions. As an innovation, the unique SDA capabilities allow it to perform analysis of situations where the receiving communication system slips bits due to low signal-to-noise conditions or experiences constellation rotations resulting in channel polarity in versions or channel assignment swaps. SDA s closed-loop detection allows it to instrument a live system and correlate observations with frame, codeword, and packet losses, as well as Quality of Service (QoS) and Quality of Experience (QoE) events. The SDA s abilities are not confined to performing analysis in low signal-to-noise conditions. Its analysis provides in-depth insight of a communication system s receiver performance in a variety of operating conditions. The SDA incorporates two techniques for identifying slips. The first is an examination of content of the received data stream s relation to the transmitted data content and the second is a direct examination of the receiver s recovered clock signals relative to a reference. Both techniques provide benefits in different ways and allow the communication engineer evaluating test results increased confidence and understanding of receiver performance. Direct examination of data contents is performed by two different data techniques, power correlation or a modified Massey correlation, and can be applied to soft decision data widths 1 to 12 bits wide over a correlation depth ranging from 16 to 512 samples. The SDA detects receiver bit slips within a 4 bits window and can handle systems with up to four quadrants (QPSK, SQPSK, and BPSK systems). The SDA continuously monitors correlation results to characterize slips and quadrant change and is capable of performing analysis even when the

  14. Regolith Evolved Gas Analyzer

    Science.gov (United States)

    Hoffman, John H.; Hedgecock, Jud; Nienaber, Terry; Cooper, Bonnie; Allen, Carlton; Ming, Doug

    2000-01-01

    The Regolith Evolved Gas Analyzer (REGA) is a high-temperature furnace and mass spectrometer instrument for determining the mineralogical composition and reactivity of soil samples. REGA provides key mineralogical and reactivity data that is needed to understand the soil chemistry of an asteroid, which then aids in determining in-situ which materials should be selected for return to earth. REGA is capable of conducting a number of direct soil measurements that are unique to this instrument. These experimental measurements include: (1) Mass spectrum analysis of evolved gases from soil samples as they are heated from ambient temperature to 900 C; and (2) Identification of liberated chemicals, e.g., water, oxygen, sulfur, chlorine, and fluorine. REGA would be placed on the surface of a near earth asteroid. It is an autonomous instrument that is controlled from earth but does the analysis of regolith materials automatically. The REGA instrument consists of four primary components: (1) a flight-proven mass spectrometer, (2) a high-temperature furnace, (3) a soil handling system, and (4) a microcontroller. An external arm containing a scoop or drill gathers regolith samples. A sample is placed in the inlet orifice where the finest-grained particles are sifted into a metering volume and subsequently moved into a crucible. A movable arm then places the crucible in the furnace. The furnace is closed, thereby sealing the inner volume to collect the evolved gases for analysis. Owing to the very low g forces on an asteroid compared to Mars or the moon, the sample must be moved from inlet to crucible by mechanical means rather than by gravity. As the soil sample is heated through a programmed pattern, the gases evolved at each temperature are passed through a transfer tube to the mass spectrometer for analysis and identification. Return data from the instrument will lead to new insights and discoveries including: (1) Identification of the molecular masses of all of the gases

  15. Social Networks

    OpenAIRE

    Martí, Joan; Zenou, Yves

    2009-01-01

    We survey the literature on social networks by putting together the economics, sociological and physics/applied mathematics approaches, showing their similarities and differences. We expose, in particular, the two main ways of modeling network formation. While the physics/applied mathematics approach is capable of reproducing most observed networks, it does not explain why they emerge. On the contrary, the economics approach is very precise in explaining why networks emerge but does a poor jo...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Social Network Analysis of a Supply Network Structural Investigation of the South Korean Automotive Industry

    OpenAIRE

    Kim, Jin-Baek

    2015-01-01

    Part 3: Knowledge Based Production Management; International audience; In this paper, we analyzed the structure of the South Korean automotive industry using social network analysis (SNA) metrics. Based on the data collected from 275 companies, a social network model of the supply network was constructed. Centrality measures in the SNA field were used to interpret the result and identify key companies. The results show that SNA metrics can be useful to understand the structure of a supply net...

  1. 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

  2. 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.

  3. Communication networks for the tactical edge

    Science.gov (United States)

    Evans, Joseph B.; Pennington, Steven G.; Ewy, Benjamin J.

    2017-04-01

    Information at the tactical level is increasingly critical in today's conflicts. The proliferation of commercial tablets and smart phones has created the ability for extensive information sharing at the tactical edge, beyond the traditional tactical voice communications and location information. This is particularly the case in Gray Zone conflicts, in which tactical decision making and actions are intertwined with information sharing and exploitation. Networking of tactical devices is the key to this information sharing. In this work, we detail and analyze two network models at different parts of the Gray Zone spectrum, and explore a number of networking options including Named Data Networking. We also compare networking approaches in a variety of realistic operating environments. Our results show that Named Data Networking is a good match for the disrupted networking environments found in many tactical situations

  4. 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.

  5. Analyzing the relationship between social networking addiction, interaction anxiousness and levels of loneliness of pre-service teachers

    Öğretmen adaylarının sosyal ağ bağımlılığı, etkileşim kaygısı ve yalnızlık düzeyi arasındaki ilişkinin incelenmesi

    OpenAIRE

    Hasan Özgür

    2013-01-01

    In this research, it was aimed to analyze the social networking addiction of pre-service teachers in terms of various variables and evaluate the relationship between social networking addiction and loneliness and interaction anxiousness. The research was designed according to the relational screening model. The study sample included 349 pre-service teachers studying at Trakya University Faculty of Education in 2012-2013 academic year fall term. The data were obtained using Facebook Addiction ...

  6. 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...

  7. 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.

  8. New EOC Course Shows Power of CHDS Networking

    OpenAIRE

    Center for Homeland Defense and Security

    2012-01-01

    Center for Homeland Defense and Security, PRESS RELEASES The last time a FEMA-backed educational course for management of emergency operations centers (EOC) was completely re-written and updated, social media had yet to be invented and cell phones were...

  9. 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).

  10. Network of networks in Linux operating system

    Science.gov (United States)

    Wang, Haoqin; Chen, Zhen; Xiao, Guanping; Zheng, Zheng

    2016-04-01

    Operating system represents one of the most complex man-made systems. In this paper, we analyze Linux Operating System (LOS) as a complex network via modeling functions as nodes and function calls as edges. It is found that for the LOS network and modularized components within it, the out-degree follows an exponential distribution and the in-degree follows a power-law distribution. For better understanding the underlying design principles of LOS, we explore the coupling correlations of components in LOS from aspects of topology and function. The result shows that the component for device drivers has a strong manifestation in topology while a weak manifestation in function. However, the component for process management shows the contrary phenomenon. Moreover, in an effort to investigate the impact of system failures on networks, we make a comparison between the networks traced from normal and failure status of LOS. This leads to a conclusion that the failure will change function calls which should be executed in normal status and introduce new function calls in the meanwhile.

  11. Is Your (Ethical) Slippage Showing?

    Science.gov (United States)

    Rein, Lowell G.

    1980-01-01

    Analyzes the causes of ethical slippage which damages creditability and invites increased governmental regulation. Suggests 15 concrete steps that can be taken to rectify the situation. Includes an ethics test. (JOW)

  12. Fundamentals of Stochastic Networks

    CERN Document Server

    Ibe, Oliver C

    2011-01-01

    An interdisciplinary approach to understanding queueing and graphical networks In today's era of interdisciplinary studies and research activities, network models are becoming increasingly important in various areas where they have not regularly been used. Combining techniques from stochastic processes and graph theory to analyze the behavior of networks, Fundamentals of Stochastic Networks provides an interdisciplinary approach by including practical applications of these stochastic networks in various fields of study, from engineering and operations management to communications and the physi

  13. Information diversity in structure and dynamics of simulated neuronal networks.

    Science.gov (United States)

    Mäki-Marttunen, Tuomo; Aćimović, Jugoslava; Nykter, Matti; Kesseli, Juha; Ruohonen, Keijo; Yli-Harja, Olli; Linne, Marja-Leena

    2011-01-01

    Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neuronal network is studied using the normalized compression distance. To describe the structure, a scheme for generating distance-dependent networks with identical in-degree distribution but variable strength of dependence on distance is presented. The resulting network structure classes possess differing path length and clustering coefficient distributions. In parallel, comparable realistic neuronal networks are generated with NETMORPH simulator and similar analysis is done on them. To describe the dynamics, network spike trains are simulated using different network structures and their bursting behaviors are analyzed. For the simulation of the network activity the Izhikevich model of spiking neurons is used together with the Tsodyks model of dynamical synapses. We show that the structure of the simulated neuronal networks affects the spontaneous bursting activity when measured with bursting frequency and a set of intraburst measures: the more locally connected networks produce more and longer bursts than the more random networks. The information diversity of the structure of a network is greatest in the most locally connected networks, smallest in random networks, and somewhere in between in the networks between order and disorder. As for the dynamics, the most locally connected networks and some of the in-between networks produce the most complex intraburst spike trains. The same result also holds for sparser of the two considered network densities in the case of full spike trains.

  14. Information Diversity in Structure and Dynamics of Simulated Neuronal Networks

    Directory of Open Access Journals (Sweden)

    Tuomo eMäki-Marttunen

    2011-06-01

    Full Text Available Neuronal networks exhibit a wide diversity of structures, which contributes to the diversity of the dynamics therein. The presented work applies an information theoretic framework to simultaneously analyze structure and dynamics in neuronal networks. Information diversity within the structure and dynamics of a neuronal network is studied using the normalized compression distance (NCD. To describe the structure, a scheme for generating distance-dependent networks with identical in-degree distribution but variable strength of dependence on distance is presented. The resulting network structure classes possess differing path length and clustering coefficient distributions. In parallel, comparable realistic neuronal networks are generated with NETMORPH simulator and similar analysis is done on them. To describe the dynamics, network spike trains are simulated using different network structures and their bursting behaviours are analyzed. For the simulation of the network activity the Izhikevich model of spiking neurons is used together with the Tsodyks model of dynamical synapses.We show that the structure of the simulated neuronal networks affects the spontaneous bursting activity when measured with bursting frequency and a set of intraburst measures: the more locally connected networks produce more and longer bursts than the more random networks. The information diversity of the structure of a network is greatest in the most locally connected networks, smallest in random networks, and somewhere in between in the networks between order and disorder. As for the dynamics, the most locally connected networks and some of the in-between networks produce the most complex intraburst spike trains. The same result also holds for sparser of the two considered network densities in the case of full spike trains.

  15. Molecular ecological network analyses

    Directory of Open Access Journals (Sweden)

    Deng Ye

    2012-05-01

    Full Text Available Abstract Background 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. Results 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

  16. 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.

  17. 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...

  18. 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.

  19. Fractional dynamics of complex networks

    Science.gov (United States)

    Turalska, Malgorzata; West, Bruce J.

    2014-03-01

    The relation between the behavior of a single element and the global dynamics of its host network is an open problem in the science of complex networks. Typically one attempts to infer the global dynamics by combining the behavior of single elements within the system, following a bottom-up approach. Here we address an inverse problem. We show that for a generic model within the Ising universality class it is possible to construct a description of the dynamics of an individual element, given the information about the network's global behavior. We demonstrate that the individual trajectory response to the collective motion of the network is described by a linear fractional differential equation, whose analytic solution is the Mittag-Leffler function. This solution is obtained through a subordination procedure without the necessity of linearizing the underlying dynamics, that is, the solution retains the influence of the nonlinear network dynamics on the individual. Moreover the solutions to the fractional equation of motion suggest a new direction for designing control mechanisms for complex networks. The implications of this new perspective are explored by introducing a control signal into a small number of network elements and analyzing the subsequent change in the network dynamics.

  20. 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...

  1. 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...

  2. Analyzing and constraining signaling networks: parameter estimation for the user.

    Science.gov (United States)

    Geier, Florian; Fengos, Georgios; Felizzi, Federico; Iber, Dagmar

    2012-01-01

    The behavior of most dynamical models not only depends on the wiring but also on the kind and strength of interactions which are reflected in the parameter values of the model. The predictive value of mathematical models therefore critically hinges on the quality of the parameter estimates. Constraining a dynamical model by an appropriate parameterization follows a 3-step process. In an initial step, it is important to evaluate the sensitivity of the parameters of the model with respect to the model output of interest. This analysis points at the identifiability of model parameters and can guide the design of experiments. In the second step, the actual fitting needs to be carried out. This step requires special care as, on the one hand, noisy as well as partial observations can corrupt the identification of system parameters. On the other hand, the solution of the dynamical system usually depends in a highly nonlinear fashion on its parameters and, as a consequence, parameter estimation procedures get easily trapped in local optima. Therefore any useful parameter estimation procedure has to be robust and efficient with respect to both challenges. In the final step, it is important to access the validity of the optimized model. A number of reviews have been published on the subject. A good, nontechnical overview is provided by Jaqaman and Danuser (Nat Rev Mol Cell Biol 7(11):813-819, 2006) and a classical introduction, focussing on the algorithmic side, is given in Press (Numerical recipes: The art of scientific computing, Cambridge University Press, 3rd edn., 2007, Chapters 10 and 15). We will focus on the practical issues related to parameter estimation and use a model of the TGFβ-signaling pathway as an educative example. Corresponding parameter estimation software and models based on MATLAB code can be downloaded from the authors's web page ( http://www.bsse.ethz.ch/cobi ).

  3. 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...

  4. Analyzing Collaborations Through Content-Based Social Networks

    Science.gov (United States)

    Cucchiarelli, Alessandro; D'Antonio, Fulvio; Velardi, Paola

    This chapter presents a methodology and a software application to support the analysis of collaborations and collaboration content in scientific communities. High-quality terminology extraction, semantic graphs, and clustering techniques are used to identify the relevant research topics. Traditional and novel social analysis tools are then used to study the emergence of interests around certain topics, the evolution of collaborations around these themes, and to identify potential for better cooperation.

  5. Research on dynamic routing mechanisms in wireless sensor networks.

    Science.gov (United States)

    Zhao, A Q; Weng, Y N; Lu, Y; Liu, C Y

    2014-01-01

    WirelessHART is the most widely applied standard in wireless sensor networks nowadays. However, it does not provide any dynamic routing mechanism, which is important for the reliability and robustness of the wireless network applications. In this paper, a collection tree protocol based, dynamic routing mechanism was proposed for WirelessHART network. The dynamic routing mechanism was evaluated through several simulation experiments in three aspects: time for generating the topology, link quality, and stability of network. Besides, the data transmission efficiency of this routing mechanism was analyzed. The simulation and evaluation results show that this mechanism can act as a dynamic routing mechanism for the TDMA-based wireless sensor network.

  6. The dichotomy in degree correlation of biological networks.

    Directory of Open Access Journals (Sweden)

    Dapeng Hao

    Full Text Available Most complex networks from different areas such as biology, sociology or technology, show a correlation on node degree where the possibility of a link between two nodes depends on their connectivity. It is widely believed that complex networks are either disassortative (links between hubs are systematically suppressed or assortative (links between hubs are enhanced. In this paper, we analyze a variety of biological networks and find that they generally show a dichotomous degree correlation. We find that many properties of biological networks can be explained by this dichotomy in degree correlation, including the neighborhood connectivity, the sickle-shaped clustering coefficient distribution and the modularity structure. This dichotomy distinguishes biological networks from real disassortative networks or assortative networks such as the Internet and social networks. We suggest that the modular structure of networks accounts for the dichotomy in degree correlation and vice versa, shedding light on the source of modularity in biological networks. We further show that a robust and well connected network necessitates the dichotomy of degree correlation, suggestive of an evolutionary motivation for its existence. Finally, we suggest that a dichotomous degree correlation favors a centrally connected modular network, by which the integrity of network and specificity of modules might be reconciled.

  7. 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.

  8. 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.

  9. Stem Cell Networks

    OpenAIRE

    Werner, Eric

    2016-01-01

    We present a general computational theory of stem cell networks and their developmental dynamics. Stem cell networks are special cases of developmental control networks. Our theory generates a natural classification of all possible stem cell networks based on their network architecture. Each stem cell network has a unique topology and semantics and developmental dynamics that result in distinct phenotypes. We show that the ideal growth dynamics of multicellular systems generated by stem cell ...

  10. 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

  11. Constrained target controllability of complex networks

    Science.gov (United States)

    Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

    2017-06-01

    It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

  12. Digital signal processing in the radio science stability analyzer

    Science.gov (United States)

    Greenhall, C. A.

    1995-01-01

    The Telecommunications Division has built a stability analyzer for testing Deep Space Network installations during flight radio science experiments. The low-frequency part of the analyzer operates by digitizing wave signals with bandwidths between 80 Hz and 45 kHz. Processed outputs include spectra of signal, phase, amplitude, and differential phase; time series of the same quantities; and Allan deviation of phase and differential phase. This article documents the digital signal-processing methods programmed into the analyzer.

  13. Topological analysis of telecommunications networks

    Directory of Open Access Journals (Sweden)

    Milojko V. Jevtović

    2011-01-01

    analyzed in particular. Efficiency as an integral feature of reliability represents a measure of satisfying specific requirements of the mission (adequacy over time (reliability in a certain moment of time (availability. Today, modern telecommunications networks face another condition: the operation in extreme conditions (major floods, catastrophic earthquakes, forest fires, electromagnetic jamming and bombing from aircraft or remote control posts. In order to realize communication in such circumstances, it is necessary to introduce a new parameter - network survivability. The network survivability is defined as the ability of a network to maintain communication features while establishing, maintaining and terminating connections in extremely difficult conditions. This paper proposes a comprehensive definition of telecommunications networks including the network survivability as a very important factor. The best results in terms of network survivability are obtained by the network with full connection, but the drawback is its high implementation cost. The grid network is more favorable since it results in reducing the number of links between network nodes. With the number of branches increasing, the delay in the network also increases. The previous analysis shows that the average path length and the average length of links are critical values when selecting a configuration of functionally resistant telecommunications networks.

  14. 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.

  15. Hey Teacher, Your Personality's Showing!

    Science.gov (United States)

    Paulsen, James R.

    1977-01-01

    A study of 30 fourth, fifth, and sixth grade teachers and 300 of their students showed that a teacher's age, sex, and years of experience did not relate to students' mathematics achievement, but that more effective teachers showed greater "freedom from defensive behavior" than did less effective teachers. (DT)

  16. Planning a Successful Tech Show

    Science.gov (United States)

    Nikirk, Martin

    2011-01-01

    Tech shows are a great way to introduce prospective students, parents, and local business and industry to a technology and engineering or career and technical education program. In addition to showcasing instructional programs, a tech show allows students to demonstrate their professionalism and skills, practice public presentations, and interact…

  17. 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.

  18. Social contagions on weighted networks

    Science.gov (United States)

    Zhu, Yu-Xiao; Wang, Wei; Tang, Ming; Ahn, Yong-Yeol

    2017-07-01

    We investigate critical behaviors of a social contagion model on weighted networks. An edge-weight compartmental approach is applied to analyze the weighted social contagion on strongly heterogenous networks with skewed degree and weight distributions. We find that degree heterogeneity cannot only alter the nature of contagion transition from discontinuous to continuous but also can enhance or hamper the size of adoption, depending on the unit transmission probability. We also show that the heterogeneity of weight distribution always hinders social contagions, and does not alter the transition type.

  19. 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....

  20. The modularity of pollination networks.

    Science.gov (United States)

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

    2007-12-11

    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 network. They were either hubs (i.e., highly linked species within their own module), connectors linking different modules, or both. If these key species go extinct, modules and networks may break apart and initiate cascades of extinction. Thus, species serving as hubs and connectors should receive high conservation priorities.

  1. 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.

  2. Analyzing the regulation of metabolic pathways in human breast cancer

    Science.gov (United States)

    2010-01-01

    Background Tumor therapy mainly attacks the metabolism to interfere the tumor's anabolism and signaling of proliferative second messengers. However, the metabolic demands of different cancers are very heterogeneous and depend on their origin of tissue, age, gender and other clinical parameters. We investigated tumor specific regulation in the metabolism of breast cancer. Methods For this, we mapped gene expression data from microarrays onto the corresponding enzymes and their metabolic reaction network. We used Haar Wavelet transforms on optimally arranged grid representations of metabolic pathways as a pattern recognition method to detect orchestrated regulation of neighboring enzymes in the network. Significant combined expression patterns were used to select metabolic pathways showing shifted regulation of the aggressive tumors. Results Besides up-regulation for energy production and nucleotide anabolism, we found an interesting cellular switch in the interplay of biosynthesis of steroids and bile acids. The biosynthesis of steroids was up-regulated for estrogen synthesis which is needed for proliferative signaling in breast cancer. In turn, the decomposition of steroid precursors was blocked by down-regulation of the bile acid pathway. Conclusion We applied an intelligent pattern recognition method for analyzing the regulation of metabolism and elucidated substantial regulation of human breast cancer at the interplay of cholesterol biosynthesis and bile acid metabolism pointing to specific breast cancer treatment. PMID:20831783

  3. Analyzing the regulation of metabolic pathways in human breast cancer

    Directory of Open Access Journals (Sweden)

    Schramm Gunnar

    2010-09-01

    Full Text Available Abstract Background Tumor therapy mainly attacks the metabolism to interfere the tumor's anabolism and signaling of proliferative second messengers. However, the metabolic demands of different cancers are very heterogeneous and depend on their origin of tissue, age, gender and other clinical parameters. We investigated tumor specific regulation in the metabolism of breast cancer. Methods For this, we mapped gene expression data from microarrays onto the corresponding enzymes and their metabolic reaction network. We used Haar Wavelet transforms on optimally arranged grid representations of metabolic pathways as a pattern recognition method to detect orchestrated regulation of neighboring enzymes in the network. Significant combined expression patterns were used to select metabolic pathways showing shifted regulation of the aggressive tumors. Results Besides up-regulation for energy production and nucleotide anabolism, we found an interesting cellular switch in the interplay of biosynthesis of steroids and bile acids. The biosynthesis of steroids was up-regulated for estrogen synthesis which is needed for proliferative signaling in breast cancer. In turn, the decomposition of steroid precursors was blocked by down-regulation of the bile acid pathway. Conclusion We applied an intelligent pattern recognition method for analyzing the regulation of metabolism and elucidated substantial regulation of human breast cancer at the interplay of cholesterol biosynthesis and bile acid metabolism pointing to specific breast cancer treatment.

  4. 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.

  5. 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.

  6. Information theory perspective on network robustness

    Energy Technology Data Exchange (ETDEWEB)

    Schieber, Tiago A. [Departmento de Engenharia de Produção, Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil); Industrial and Systems Engineering, University of Florida, Gainesville, FL (United States); Carpi, Laura [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Colom 11, Terrassa, 08222, Barcelona (Spain); Frery, Alejandro C. [Laboratório de Computação Científica e Análise Numérica (LaCCAN), Universidade Federal de Alagoas, Maceió, Alagoas (Brazil); Rosso, Osvaldo A. [Instituto de Física, Universidade Federal de Alagoas, Maceió, Alagoas (Brazil); Instituto Tecnológico de Buenos Aires (ITBA), Ciudad Autónoma de Buenos Aires (Argentina); Pardalos, Panos M. [Industrial and Systems Engineering, University of Florida, Gainesville, FL (United States); Ravetti, Martín G., E-mail: martin.ravetti@dep.ufmg.br [Departmento de Engenharia de Produção, Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil); Departament de Física Fonamental, Universitat de Barcelona, Barcelona (Spain)

    2016-01-28

    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.

  7. Sentient networks

    Energy Technology Data Exchange (ETDEWEB)

    Chapline, G.

    1998-03-01

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

  8. Networks as integrated in research methodologies in PER

    DEFF Research Database (Denmark)

    Bruun, Jesper

    2016-01-01

    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...... 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....

  9. 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.

  10. Thermo Scientific Sulfur Dioxide Analyzer Instrument Handbook

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-03-01

    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. 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.

  11. Software-Design-Analyzer System

    Science.gov (United States)

    Tausworthe, Robert C.

    1991-01-01

    CRISP-90 software-design-analyzer system, update of CRISP-80, is set of computer programs constituting software tool for design and documentation of other software and supporting top-down, hierarchical, modular, structured methodologies for design and programming. Written in Microsoft QuickBasic.

  12. Analyzing Software Piracy in Education.

    Science.gov (United States)

    Lesisko, Lee James

    This study analyzes the controversy of software piracy in education. It begins with a real world scenario that presents the setting and context of the problem. The legalities and background of software piracy are explained and true court cases are briefly examined. Discussion then focuses on explaining why individuals and organizations pirate…

  13. 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.

  14. Analyzing Student Difficulties in Reading.

    Science.gov (United States)

    Ediger, Marlow

    According to this paper, a good reading teacher is able to analyze problems faced by students in reading and remediate that which is necessary. The paper stresses that the reading teacher needs to be a good observer of student reading habits to notice where to intervene to improve the skills and attitudes of the reader. It discusses diagnosis and…

  15. 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.

  16. The Users’ Survey of Network Ethics in Taiwan Academic Network

    Directory of Open Access Journals (Sweden)

    Tao-Ming Chuang

    1998-12-01

    Full Text Available The research using the questionnaire methods is to survey the status of users in TANet and to investigate users' valuing system on network moral norms. The purposes have following: 1. analyzing and comparing different kinds of network policies, computing policies, or codes of information ethics in order to conceive the new rules on the information superhighway; 2. investigating users' background, motivation, and valuing system on network ethics; 3. analyzing network educator's attitudes on network moral norms and the methodology of ethical education in network courses; and 4. establishing the course's foundation of network ethics. [Article content in Chinese

  17. 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.

  18. 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.)

  19. Analyzing, Modelling, and Designing Software Ecosystems

    DEFF Research Database (Denmark)

    Manikas, Konstantinos

    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....... This thesis documents the groundwork towards addressing the challenges faced by telemedical technologies today and establishing telemedicine as a means of patient diagnosis and treatment. Furthermore, it serves as an empirical example of designing a software ecosystem....

  20. 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

  1. The role of symmetry in neural networks and their Laplacian spectra.

    Science.gov (United States)

    de Lange, Siemon C; van den Heuvel, Martijn P; de Reus, Marcel A

    2016-11-01

    Human and animal nervous systems constitute complexly wired networks that form the infrastructure for neural processing and integration of information. The organization of these neural networks can be analyzed using the so-called Laplacian spectrum, providing a mathematical tool to produce systems-level network fingerprints. In this article, we examine a characteristic central peak in the spectrum of neural networks, including anatomical brain network maps of the mouse, cat and macaque, as well as anatomical and functional network maps of human brain connectivity. We link the occurrence of this central peak to the level of symmetry in neural networks, an intriguing aspect of network organization resulting from network elements that exhibit similar wiring patterns. Specifically, we propose a measure to capture the global level of symmetry of a network and show that, for both empirical networks and network models, the height of the main peak in the Laplacian spectrum is strongly related to node symmetry in the underlying network. Moreover, examination of spectra of duplication-based model networks shows that neural spectra are best approximated using a trade-off between duplication and diversification. Taken together, our results facilitate a better understanding of neural network spectra and the importance of symmetry in neural networks. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. 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.

  3. Cascading failures in spatially-embedded random networks.

    Science.gov (United States)

    Asztalos, Andrea; Sreenivasan, Sameet; Szymanski, Boleslaw K; Korniss, Gyorgy

    2014-01-01

    Cascading failures constitute an important vulnerability of interconnected systems. Here we focus on the study of such failures on networks in which the connectivity of nodes is constrained by geographical distance. Specifically, we use random geometric graphs as representative examples of such spatial networks, and study the properties of cascading failures on them in the presence of distributed flow. The key finding of this study is that the process of cascading failures is non-self-averaging on spatial networks, and thus, aggregate inferences made from analyzing an ensemble of such networks lead to incorrect conclusions when applied to a single network, no matter how large the network is. We demonstrate that this lack of self-averaging disappears with the introduction of a small fraction of long-range links into the network. We simulate the well studied preemptive node removal strategy for cascade mitigation and show that it is largely ineffective in the case of spatial networks. We introduce an altruistic strategy designed to limit the loss of network nodes in the event of a cascade triggering failure and show that it performs better than the preemptive strategy. Finally, we consider a real-world spatial network viz. a European power transmission network and validate that our findings from the study of random geometric graphs are also borne out by simulations of cascading failures on the empirical network.

  4. Methods for Analyzing Social Media

    DEFF Research Database (Denmark)

    Jensen, Jakob Linaa; [Ukendt], editors

    2013-01-01

    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......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...... 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....

  5. Image analyzers for bioscience applications.

    Science.gov (United States)

    Ramm, P

    1990-01-01

    Image analysis systems are becoming more sophosticated, less costly, and very common in research laboratories. Therefore, the bioscience researcher is faced with a bewildering array of choices in establishing an image analysis facility. Critical components and characteristics of commercial image analyzers are discussed. State-of-the-art systems feature a graphical user interface, a powerful operating system (e.g., Microsoft OS/2), 1000 line image acquisition, processing and display, true color imaging, and very flexible scanner interfaces. Such systems are best suited to technically difficult applications, such as ratio fluorescence, or to automated analysis of anatomical features, particularly in stained material. Less powerful image analyzers offer medium resolution, and typically work with monochrome data acquired from video cameras. Such systems are suitable for many bioscience applications, including quantitative autoradiography and routine morphometry.

  6. 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....

  7. 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.

  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. Analyzing Change Management in Organization

    OpenAIRE

    Yonardy, Charles; Mekel, Peggy A.

    2014-01-01

    Every company will be faced a change either business or non-business company. A change will be happened because of technological change, industry change, and institutional rules change. If the company lack in adapt the changing of competition, business cycles, technology and institutional rules the company might face a bankruptcy. Why? To make a successful change there are steps and process of change. Research objectives are to analyze what should company do in order to do change management a...

  10. Remote Laser Diffraction PSD Analyzer

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-06-01

    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.

  11. 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.

  12. 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.

  13. 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.

  14. Recent Progress on the Resilience of Complex Networks

    Directory of Open Access Journals (Sweden)

    Jianxi Gao

    2015-10-01

    Full Text Available Many complex systems in the real world can be modeled as complex networks, which has captured in recent years enormous attention from researchers of diverse fields ranging from natural sciences to engineering. The extinction of species in ecosystems and the blackouts of power girds in engineering exhibit the vulnerability of complex networks, investigated by empirical data and analyzed by theoretical models. For studying the resilience of complex networks, three main factors should be focused on: the network structure, the network dynamics and the failure mechanism. In this review, we will introduce recent progress on the resilience of complex networks based on these three aspects. For the network structure, increasing evidence shows that biological and ecological networks are coupled with each other and that diverse critical infrastructures interact with each other, triggering a new research hotspot of “networks of networks” (NON, where a network is formed by interdependent or interconnected networks. The resilience of complex networks is deeply influenced by its interdependence with other networks, which can be analyzed and predicted by percolation theory. This review paper shows that the analytic framework for Energies 2015, 8 12188 NON yields novel percolation laws for n interdependent networks and also shows that the percolation theory of a single network studied extensively in physics and mathematics in the last 60 years is a specific limited case of the more general case of n interacting networks. Due to spatial constraints inherent in critical infrastructures, including the power gird, we also review the progress on the study of spatially-embedded interdependent networks, exhibiting extreme vulnerabilities compared to their non-embedded counterparts, especially in the case of localized attack. For the network dynamics, we illustrate the percolation framework and methods using an example of a real transportation system, where the

  15. Analysis of complex network performance and heuristic node removal strategies

    Science.gov (United States)

    Jahanpour, Ehsan; Chen, Xin

    2013-12-01

    Removing important nodes from complex networks is a great challenge in fighting against criminal organizations and preventing disease outbreaks. Six network performance metrics, including four new metrics, are applied to quantify networks' diffusion speed, diffusion scale, homogeneity, and diameter. In order to efficiently identify nodes whose removal maximally destroys a network, i.e., minimizes network performance, ten structured heuristic node removal strategies are designed using different node centrality metrics including degree, betweenness, reciprocal closeness, complement-derived closeness, and eigenvector centrality. These strategies are applied to remove nodes from the September 11, 2001 hijackers' network, and their performance are compared to that of a random strategy, which removes randomly selected nodes, and the locally optimal solution (LOS), which removes nodes to minimize network performance at each step. The computational complexity of the 11 strategies and LOS is also analyzed. Results show that the node removal strategies using degree and betweenness centralities are more efficient than other strategies.

  16. 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.

  17. Multiuser Cooperation with Hybrid Network Coding in Wireless Networks

    Directory of Open Access Journals (Sweden)

    G. Wang

    2014-04-01

    Full Text Available In this paper a hybrid Network Coding Cooperation (hybrid-NCC system is proposed to achieve both reliable transmission and high throughput in wireless networks. To balance the transmission reliability with throughput, the users are divided into cooperative sub-networks based on the geographical information, and the cooperation is implemented in each sub-network. After receiving signals from the cooperative partners, each user encodes them by exploiting hybrid network coding and then forwards the recoded symbols via the Link-Adaptive Regenerative (LAR relaying. First, the Diversity-Multiplexing Tradeoff (DMT is analyzed to demonstrate that the proposed system is bandwidth-efficient. Second, the Symbol Error Probability (SEP is also derived, which shows that the proposed system achieves a higher reliability as compared to the traditional Complex Field Network Coding Cooperation (CFNCC. Moreover, because dedicated relays are not required, our proposed system can both reduce the costs and enhance the flexibility of the implementation. Finally, the analytical results are supported and validated by numerical simulations.

  18. 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 Engineer......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...

  19. 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)

  20. Measuring Asymmetry in Insect-Plant Networks

    Science.gov (United States)

    Cruz, Cláudia P. T.; de Almeida, Adriana M.; Corso, Gilberto

    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, D1, and the plant network, D2. 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 D2 and D1 we test for a set of 23 networks from the ecologic literature networks: the difference in size, ΔL, clustering coefficient difference, ΔC, and mean connectivity difference, Δ. We used a nonparametric statistical test to check the differences in ΔL, ΔC and Δ. Our results indicate that ΔL and Δ show a significative asymmetry.

  1. 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). Copyright © 2014 Elsevier B.V. All rights reserved.

  2. 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.

  3. VOSA: A VO SED Analyzer

    Science.gov (United States)

    Rodrigo, C.; Bayo, A.; Solano, E.

    2017-03-01

    VOSA (VO Sed Analyzer, http://svo2.cab.inta-csic.es/theory/vosa) is a public web-tool developed by the Spanish Virtual Observatory (http://svo.cab.inta-csic.es/) and designed to help users to (1) build Spectral Energy Distributions (SEDs) combining private photometric measurements with data available in VO services, (2) obtain relevant properties of these objects (distance, extinction, etc) from VO catalogs, (3) analyze them comparing observed photometry with synthetic photometry from different collections of theoretical models or observational templates, using different techniques (chi-square minimization, Bayesian analysis) to estimate physical parameters of the observed objects (teff, logg, metallicity, stellar radius/distance ratio, infrared excess, etc), and use these results to (4) estimate masses and ages via interpolation of collections of isochrones and evolutionary tracks from the VO. In particular, VOSA offers the advantage of deriving physical parameters using all the available photometric information instead of a restricted subset of colors. The results can be downloaded in different formats or sent to other VO tools using SAMP. We have upgraded VOSA to provide access to Gaia photometry and give a homogeneous estimation of the physical parameters of thousands of objects at a time. This upgrade has required the implementation of a new computation paradigm, including a distributed environment, the capability of submitting and processing jobs in an asynchronous way, the use of parallelized computing to speed up processes (˜ ten times faster) and a new design of the web interface.

  4. Destabilization of Terrorist Networks through Argument Driven Hypothesis Model

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar

    2007-01-01

    Social network analysis has been used for quite some time to analyze and understand the behavior of nodes in the network.  Theses nodes could be individuals or group of persons, events or organizations etc.  Infact these nodes could be any thing importantly, these nodes propagate and obviously ha......) to predict a path for its destabilization.  This network is selected to benchmark our proposed model framework.  The results obtained with various network analysis shows that it works better than other analysis measures for example based on degree, betweeness and closeness etc.        ...

  5. Epidemic spreading on networks based on stress response

    Science.gov (United States)

    Nian, Fuzhong; Yao, Shuanglong

    2017-06-01

    Based on the stress responses of individuals, the susceptible-infected-susceptible epidemic model was improved on the small-world networks and BA scale-free networks and the simulations were implemented and analyzed. Results indicate that the behaviors of individual’s stress responses could induce the epidemic spreading resistance and adaptation at the network level. This phenomenon showed that networks were learning how to adapt to the disease and the evolution process could improve their immunization to future infectious diseases and would effectively prevent the spreading of infectious diseases.

  6. Scaling solutions for connectivity and conductivity of continuous random networks.

    Science.gov (United States)

    Galindo-Torres, S A; Molebatsi, T; Kong, X-Z; Scheuermann, A; Bringemeier, D; Li, L

    2015-10-01

    Connectivity and conductivity of two-dimensional fracture networks (FNs), as an important type of continuous random networks, are examined systematically through Monte Carlo simulations under a variety of conditions, including different power law distributions of the fracture lengths and domain sizes. The simulation results are analyzed using analogies of the percolation theory for discrete random networks. With a characteristic length scale and conductivity scale introduced, we show that the connectivity and conductivity of FNs can be well described by universal scaling solutions. These solutions shed light on previous observations of scale-dependent FN behavior and provide a powerful method for quantifying effective bulk properties of continuous random networks.

  7. How people interact in evolving online affiliation networks

    CERN Document Server

    Gallos, Lazaros K; Liljeros, Fredrik; Havlin, Shlomo; Makse, Hernan A

    2011-01-01

    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 first show that an accurate estimation of these probabilistic tendencies can only be achieved by following the time evolution of the network. For example, actions that are attributed to the usual friend of a friend mechanism through a static snapshot of the network are overestimated by a factor of two. A detailed analysis of the dynamic network evolution shows that half of those triangles were generated through other mechanisms, in spite of the characteristic static pattern. We start by characterizing every single link when the tie was established in the network. This allows us to describe the probabilistic tendencies of tie formation and extract sociological conclusions as...

  8. Financial Time Series Prediction Using Elman Recurrent Random Neural Networks

    Science.gov (United States)

    Wang, Jie; Wang, Jun; Fang, Wen; Niu, Hongli

    2016-01-01

    In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective function. By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices. PMID:27293423

  9. Fracture Networks in Sea Ice

    Directory of Open Access Journals (Sweden)

    Jonas Nesland Vevatne

    2014-04-01

    Full Text Available Fracturing and refreezing of sea ice in the Kara sea are investigated using complex networkanalysis. By going to the dual network, where the fractures are nodes and their intersectionslinks, we gain access to topological features which are easy to measure and hence comparewith modeled networks. Resulting network reveal statistical properties of the fracturing process.The dual networks have a broad degree distribution, with a scale-free tail, high clusteringand efficiency. The degree-degree correlation profile shows disassortative behavior, indicatingpreferential growth. This implies that long, dominating fractures appear earlier than shorterfractures, and that the short fractures which are created later tend to connect to the longfractures.The knowledge of the fracturing process is used to construct growing fracture network (GFNmodel which provides insight into the generation of fracture networks. The GFN model isprimarily based on the observation that fractures in sea ice are likely to end when hitting existingfractures. Based on an investigation of which fractures survive over time, a simple model forrefreezing is also added to the GFN model, and the model is analyzed and compared to the realnetworks.

  10. 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.

  11. 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.

  12. 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.

  13. Show Me My Health Plans

    Directory of Open Access Journals (Sweden)

    Mary C. Politi PhD

    2016-11-01

    Full Text Available Introduction: Since the Affordable Care Act was passed, more than 12 million individuals have enrolled in the health insurance marketplace. Without support, many struggle to make an informed plan choice that meets their health and financial needs. Methods: We designed and evaluated a decision aid, Show Me My Health Plans (SMHP, that provides education, preference assessment, and an annual out-of-pocket cost calculator with plan recommendations produced by a tailored, risk-adjusted algorithm incorporating age, gender, and health status. We evaluated whether SMHP compared to HealthCare.gov improved health insurance decision quality and the match between plan choice, needs, and preferences among 328 Missourians enrolling in the marketplace. Results: Participants who used SMHP had higher health insurance knowledge (LS-Mean = 78 vs. 62; P < 0.001, decision self-efficacy (LS-Mean = 83 vs. 75; P < 0.002, confidence in their choice (LS-Mean = 3.5 vs. 2.9; P < 0.001, and improved health insurance literacy (odds ratio = 2.52, P < 0.001 compared to participants using HealthCare.gov . Those using SMHP were 10.3 times more likely to select a silver- or gold-tier plan (P < 0.0001. Discussion: SMHP can improve health insurance decision quality and the odds that consumers select an insurance plan with coverage likely needed to meet their health needs. This study represents a unique context through which to apply principles of decision support to improve health insurance choices.

  14. 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.

  15. Network compression as a quality measure for protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Loic Royer

    Full Text Available 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.

  16. 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

  17. The Evolutionary Vaccination Dilemma in Complex Networks

    CERN Document Server

    Cardillo, Alessio; Naranjo, Fernando; Gómez-Gardeñes, Jesús

    2013-01-01

    In this work we analyze the evolution of voluntary vaccination in networked populations by entangling the spreading dynamics of an influenza-like disease with an evolutionary framework taking place at the end of each influenza season so that individuals take or not the vaccine upon their previous experience. Our framework thus put in competition two well-known dynamical properties of scale-free networks: the fast propagation of diseases and the promotion of cooperative behaviours. Our results show that when vaccine is perfect scale-free networks enhance the vaccination behaviour with respect to random graphs with homogeneous connectivity patterns. However, when imperfection appears we find a cross-over effect so that the number of infected (vaccinated) individuals increases (decreases) with respect to homogeneous networks, thus showing up the competition between the aforementioned properties of scale-free graphs.

  18. Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors

    DEFF Research Database (Denmark)

    Österlund, Tobias; Bordel, Sergio; Nielsen, Jens

    2015-01-01

    we analyze the topology and organization of nine transcriptional regulatory networks for E. coli, yeast, mouse and human, and we evaluate how the structure of these networks influences two of their key properties, namely controllability and stability. We calculate the controllability for each network......% for the human network. The high controllability (low number of drivers needed to control the system) in yeast, mouse and human is due to the presence of internal loops in their regulatory networks where the TFs regulate each other in a circular fashion. We refer to these internal loops as circular control...... motifs (CCM). The E. coli transcriptional regulatory network, which does not have any CCMs, shows a hierarchical structure of the transcriptional regulatory network in contrast to the eukaryal networks. The presence of CCMs also has influence on the stability of these networks, as the presence of cycles...

  19. 40 CFR 86.1522 - Carbon monoxide analyzer calibration.

    Science.gov (United States)

    2010-07-01

    ... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE HIGHWAY VEHICLES AND ENGINES (CONTINUED... engineering practice for instrument start-up and operation. Adjust the analyzer to optimize performance on the... § 86.1514-84. (3) Adjust the electrical span network such that the electrical span point is correct...

  20. 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

  1. 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.

  2. Network graph analysis of category fluency testing.

    Science.gov (United States)

    Lerner, Alan J; Ogrocki, Paula K; Thomas, Peter J

    2009-03-01

    Category fluency is impaired early in Alzheimer disease (AD). Graph theory is a technique to analyze complex relationships in networks. Features of interest in network analysis include the number of nodes and edges, and variables related to their interconnectedness. Other properties important in network analysis are "small world properties" and "scale-free" properties. The small world property (popularized as the so-called "6 degrees of separation") arises when the majority of connections are local, but a number of connections are to distant nodes. Scale-free networks are characterized by the presence of a few nodes with many connections, and many more nodes with fewer connections. To determine if category fluency data can be analyzed using graph theory. To compare normal elderly, mild cognitive impairment (MCI) and AD network graphs, and characterize changes seen with increasing cognitive impairment. Category fluency results ("animals" recorded over 60 s) from normals (n=38), MCI (n=33), and AD (n=40) completing uniform data set evaluations were converted to network graphs of all unique cooccurring neighbors, and compared for network variables. For Normal, MCI and AD, mean clustering coefficients were 0.21, 0.22, 0.30; characteristic path lengths were 3.27, 3.17, and 2.65; small world properties decreased with increasing cognitive impairment, and all graphs showed scale-free properties. Rank correlations of the 25 commonest items ranged from 0.75 to 0.83. Filtering of low-degree nodes in normal and MCI graphs resulted in properties similar to the AD network graph. Network graph analysis is a promising technique for analyzing changes in category fluency. Our technique results in nonrandom graphs consistent with well-characterized properties for these types of graphs.

  3. 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 Θ̃(S) for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  4. Percolation on the institute-enterprise R&D collaboration networks

    Science.gov (United States)

    Li, Chenguang; Zhang, Yongan

    2015-01-01

    Realistic network-like systems are usually composed of multiple networks with interacting relations such as school-enterprise research and development (R&D) collaboration networks. Here, we study the percolation properties of a special class of R&D collaboration network, namely institute-enterprise R&D collaboration networks (IERDCNs). We introduce two actual IERDCNs to show their structural properties, and we present a mathematical framework based on generating functions for analyzing an interacting network with any connection probability. Then,we illustrate the percolation threshold and structural parameter arithmetic in the sub-critical and supercritical regimes.We compare the predictions of our mathematical framework and arithmetic to data for two real R&D collaboration networks and a number of simulations. We find that our predictions are in remarkable agreement with the data. We show applications of the framework to electronics R&D collaboration networks

  5. 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...

  6. Insight to the express transport network

    Science.gov (United States)

    Yang, Hua; Nie, Yuchao; Zhang, Hongbin; Di, Zengru; Fan, Ying

    2009-09-01

    The express delivery industry is developing rapidly in recent years and has attracted attention in many fields. Express shipment service requires that parcels be delivered in a limited time with a low operation cost, which requests a high level and efficient express transport network (ETN). The ETN is constructed based on the public transport networks, especially the airline network. It is similar to the airline network in some aspects, while it has its own feature. With the complex network theory, the topological properties of the ETN are analyzed deeply. We find that the ETN has the small-world property, with disassortative mixing behavior and rich club phenomenon. It also shows difference from the airline network in some features, such as edge density and average shortest path. Analysis on the corresponding distance-weighted network shows that the distance distribution displays a truncated power-law behavior. At last, an evolving model, which takes both geographical constraint and preference attachment into account, is proposed. The model shows similar properties with the empirical results.

  7. Network topology and correlation features affiliated with European airline companies

    Science.gov (United States)

    Han, Ding-Ding; Qian, Jiang-Hai; Liu, Jin-Gao

    2009-01-01

    The physics information of four specific airline flight networks in European Continent, namely the Austrian airline, the British airline, the France-Holland airline and the Lufthhansa airline, was quantitatively analyzed by the concepts of a complex network. It displays some features of small-world networks, namely a large clustering coefficient and small average shortest-path length for these specific airline networks. The degree distributions for the small degree branch reveal power law behavior with an exponent value of 2-3 for the Austrian and the British flight networks, and that of 1-2 for the France-Holland and the Lufthhansa airline flight networks. So the studied four airlines are sorted into two classes according to the topology structure. Similarly, the flight weight distributions show two kinds of different decay behavior with the flight weight: one for the Austrian and the British airlines and another for the France-Holland airline and the Lufthhansa airlines. In addition, the degree-degree correlation analysis shows that the network has disassortative behavior for all the value of degree k, and this phenomenon is different from the international airline network and US airline network. Analysis of the clustering coefficient ( C(k)) versus k, indicates that the flight networks of the Austrian Airline and the British Airline reveal a hierarchical organization for all airports, however, the France-Holland Airline and the Lufthhansa Airline show a hierarchical organization mostly for larger airports. The correlation of node strength ( S(k)) and degree is also analyzed, and a power-law fit S(k)∼k1.1 can roughly fit all data of these four airline companies. Furthermore, we mention seasonal changes and holidays may cause the flight network to form a different topology. An example of the Austrian Airline during Christmas was studied and analyzed.

  8. Analyzing Agricultural Agglomeration in China

    Directory of Open Access Journals (Sweden)

    Erling Li

    2017-02-01

    Full Text Available There has been little scholarly research on Chinese agriculture’s geographic pattern of agglomeration and its evolutionary mechanisms, which are essential to sustainable development in China. By calculating the barycenter coordinates, the Gini coefficient, spatial autocorrelation and specialization indices for 11 crops during 1981–2012, we analyze the evolutionary pattern and mechanisms of agricultural agglomeration. We argue that the degree of spatial concentration of Chinese planting has been gradually increasing and that regional specialization and diversification have progressively been strengthened. Furthermore, Chinese crop production is moving from the eastern provinces to the central and western provinces. This is in contrast to Chinese manufacturing growth which has continued to be concentrated in the coastal and southeastern regions. In Northeast China, the Sanjiang and Songnen plains have become agricultural clustering regions, and the earlier domination of aquaculture and rice production in Southeast China has gradually decreased. In summary, this paper provides a political economy framework for understanding the regionalization of Chinese agriculture, focusing on the interaction among the objectives, decisionmaking behavior, path dependencies and spatial effects.

  9. A network of networks.

    Science.gov (United States)

    Iedema, Rick; Verma, Raj; Wutzke, Sonia; Lyons, Nigel; McCaughan, Brian

    2017-04-10

    Purpose To further our insight into the role of networks in health system reform, the purpose of this paper is to investigate how one agency, the NSW Agency for Clinical Innovation (ACI), and the multiple networks and enabling resources that it encompasses, govern, manage and extend the potential of networks for healthcare practice improvement. Design/methodology/approach This is a case study investigation which took place over ten months through the first author's participation in network activities and discussions with the agency's staff about their main objectives, challenges and achievements, and with selected services around the state of New South Wales to understand the agency's implementation and large system transformation activities. Findings The paper demonstrates that ACI accommodates multiple networks whose oversight structures, self-organisation and systems change approaches combined in dynamic ways, effectively yield a diversity of network governances. Further, ACI bears out a paradox of "centralised decentralisation", co-locating agents of innovation with networks of implementation and evaluation expertise. This arrangement strengthens and legitimates the role of the strategic hybrid - the healthcare professional in pursuit of change and improvement, and enhances their influence and impact on the wider system. Research limitations/implications While focussing the case study on one agency only, this study is unique as it highlights inter-network connections. Contributing to the literature on network governance, this paper identifies ACI as a "network of networks" through which resources, expectations and stakeholder dynamics are dynamically and flexibly mediated and enhanced. Practical implications The co-location of and dynamic interaction among clinical networks may create synergies among networks, nurture "strategic hybrids", and enhance the impact of network activities on health system reform. Social implications Network governance requires more

  10. Auditory Display as a Tool for Teaching Network Intrusion Detection

    Directory of Open Access Journals (Sweden)

    M.A. Garcia-Ruiz

    2008-06-01

    Full Text Available Teaching network intrusion detection, or NID(the identification of violations of a security policy in acomputer network is a challenging task, because studentsneed to analyze many data from network logs and in realtime to identify patterns of network attacks, making theseactivities visually tiring. This paper describes an ongoingresearch concerned with designing and applying sounds thatrepresent meaningful information in interfaces(sonification to support teaching of NID. An usability testwas conducted with engineering students. Natural soundeffects (auditory icons and musical sounds (earcons wereused to represent network attacks. A post-activityquestionnaire showed that most students preferred auditoryicons for analyzing NID, and all of them were veryinterested in the design and application of sonifications.

  11. 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.

  12. Stochastic Pooling Networks

    OpenAIRE

    McDonnell, Mark D; Amblard, Pierre-Olivier; Stocks, Nigel G.

    2009-01-01

    We introduce and define the concept of a stochastic pooling network (SPN), as a model for sensor systems where redundancy and two forms of 'noise' -- lossy compression and randomness -- interact in surprising ways. Our approach to analyzing SPNs is information theoretic. We define an SPN as a network with multiple nodes that each produce noisy and compressed measurements of the same information. An SPN must combine all these measurements into a single further compressed network output, in a w...

  13. Reservation information sharing enhancement for deflection routing in OBS network.

    Science.gov (United States)

    Gao, Donghui; Zhang, Hanyi; Zhou, Zhiyu

    2005-03-07

    The resource contention problem is critical in Just-Enough-Time (JET) based optical burst switching (OBS) networks. Although deflection routing (DR) reduces the contention probability in some degree, it does not give much improvement under heavy traffic load. This paper analyzed the inducement causing contention in OBS networks, and proposed Resource Information Sharing Enhancement (RISE) scheme. Theoretical analysis shows that this scheme achieves shorter length of the detour path than normal DR. We simulated this scheme on both full mesh network and practical 14-node NSFNET. The simulation results show that it gives at best 2 orders magnitude improvement in reducing the burst contention probability over its previous routing approaches.

  14. 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.

  15. 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....

  16. 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

  17. Information Theory of Networks

    Directory of Open Access Journals (Sweden)

    Matthias Dehmer

    2011-11-01

    Full Text Available The paper puts the emphasis on surveying information-theoretic network measures for analyzing the structure of networks. In order to apply the quantities interdisciplinarily, we also discuss some of their properties such as their structural interpretation and uniqueness.

  18. 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.

  19. 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.

  20. 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.

  1. Network analysis of unstructured EHR data for clinical research.

    Science.gov (United States)

    Bauer-Mehren, Anna; Lependu, Paea; Iyer, Srinivasan V; Harpaz, Rave; Leeper, Nicholas J; Shah, Nigam H

    2013-01-01

    In biomedical research, network analysis provides a conceptual framework for interpreting data from high-throughput experiments. For example, protein-protein interaction networks have been successfully used to identify candidate disease genes. Recently, advances in clinical text processing and the increasing availability of clinical data have enabled analogous analyses on data from electronic medical records. We constructed networks of diseases, drugs, medical devices and procedures using concepts recognized in clinical notes from the Stanford clinical data warehouse. We demonstrate the use of the resulting networks for clinical research informatics in two ways-cohort construction and outcomes analysis-by examining the safety of cilostazol in peripheral artery disease patients as a use case. We show that the network-based approaches can be used for constructing patient cohorts as well as for analyzing differences in outcomes by comparing with standard methods, and discuss the advantages offered by network-based approaches.

  2. Organizational network analysis for two networks in the Washington State Department of Transportation.

    Science.gov (United States)

    2010-10-01

    Organizational network analysis (ONA) consists of gathering data on information sharing and : connectivity in a group, calculating network measures, creating network maps, and using this : information to analyze and improve the functionality of the g...

  3. Genotype networks, innovation, and robustness in sulfur metabolism

    Science.gov (United States)

    2011-01-01

    Background A metabolism is a complex network of chemical reactions. This network synthesizes multiple small precursor molecules of biomass from chemicals that occur in the environment. The metabolic network of any one organism is encoded by a metabolic genotype, defined as the set of enzyme-coding genes whose products catalyze the network's reactions. Each metabolic genotype has a metabolic phenotype. We define this metabolic phenotype as the spectrum of different sources of a chemical element that a metabolism can use to synthesize biomass. We here focus on the element sulfur. We study properties of the space of all possible metabolic genotypes in sulfur metabolism by analyzing random metabolic genotypes that are viable on different numbers of sulfur sources. Results We show that metabolic genotypes with the same phenotype form large connected genotype networks - networks of metabolic networks - that extend far through metabolic genotype space. How far they reach through this space depends linearly on the number of super-essential reactions. A super-essential reaction is an essential reaction that occurs in all networks viable in a given environment. Metabolic networks can differ in how robust their phenotype is to the removal of individual reactions. We find that this robustness depends on metabolic network size, and on other variables, such as the size of minimal metabolic networks whose reactions are all essential in a specific environment. We show that different neighborhoods of any genotype network harbor very different novel phenotypes, metabolic innovations that can sustain life on novel sulfur sources. We also analyze the ability of evolving populations of metabolic networks to explore novel metabolic phenotypes. This ability is facilitated by the existence of genotype networks, because different neighborhoods of these networks contain very different novel phenotypes. Conclusions We show that the space of metabolic genotypes involved in sulfur metabolism

  4. Forman curvature for directed networks

    CERN Document Server

    Sreejith, R P; Saucan, Emil; Samal, Areejit

    2016-01-01

    A goal in network science is the geometrical characterization of complex networks. In this direction, we have recently introduced the Forman's discretization of Ricci curvature to the realm of undirected networks. Investigation of Forman curvature in diverse model and real-world undirected networks revealed that this measure captures several aspects of the organization of complex undirected networks. However, many important real-world networks are inherently directed in nature, and the Forman curvature for undirected networks is unsuitable for analysis of such directed networks. Hence, we here extend the Forman curvature for undirected networks to the case of directed networks. The simple mathematical formula for the Forman curvature in directed networks elegantly incorporates node weights, edge weights and edge direction. By applying the Forman curvature for directed networks to a variety of model and real-world directed networks, we show that the measure can be used to characterize the structure of complex ...

  5. Latent geometry of bipartite networks

    CERN Document Server

    Kitsak, Maksim; Krioukov, Dmitri

    2016-01-01

    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 appli...

  6. Blind and myopic ants in heterogeneous networks

    Science.gov (United States)

    Hwang, S.; Lee, D.-S.; Kahng, B.

    2014-11-01

    The diffusion processes on complex networks may be described by different Laplacian matrices due to heterogeneous connectivity. Here we investigate the random walks of blind ants and myopic ants on heterogeneous networks: While a myopic ant hops to a neighbor node every step, a blind ant may stay or hop with probabilities that depend on node connectivity. By analyzing the trajectories of blind ants, we show that the asymptotic behaviors of both random walks are related by rescaling time and probability with node connectivity. Using this result, we show how the small eigenvalues of the Laplacian matrices generating the two random walks are related. As an application, we show how the return-to-origin probability of a myopic ant can be used to compute the scaling behaviors of the Edwards-Wilkinson model, a representative model of load balancing on networks.

  7. 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.

  8. Complex Networks and Socioeconomic Applications

    Science.gov (United States)

    Almendral, Juan A.; López, Luis; Mendes, Jose F.; Sanjuán, Miguel A. F.

    2003-04-01

    The study and characterization of complex systems is a fruitful research area nowadays. Special attention has been paid recently to complex networks, where graph and network analysis plays an important role since they reduce a given system to a simpler problem. Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders because the global influence each actor has within the network is completely determined by the hierarchical level occupied. The effect on the efficiency caused by a change in a traditional hierarchical topology is also analyzed. In particular, by introducing the possibility of communication on the same level of the hierarchy.

  9. 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.

  10. 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.

  11. 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.

  12. Scale invariance in road networks.

    Science.gov (United States)

    Kalapala, Vamsi; Sanwalani, Vishal; Clauset, Aaron; Moore, Cristopher

    2006-02-01

    We study the topological and geographic structure of the national road networks of the United States, England, and Denmark. By transforming these networks into their dual representation, where roads are vertices and an edge connects two vertices if the corresponding roads ever intersect, we show that they exhibit both topological and geographic scale invariance. That is, we show that for sufficiently large geographic areas, the dual degree distribution follows a power law with exponent 2.2< or = alpha < or =2.4, and that journeys, regardless of their length, have a largely identical structure. To explain these properties, we introduce and analyze a simple fractal model of road placement that reproduces the observed structure, and suggests a testable connection between the scaling exponent and the fractal dimensions governing the placement of roads and intersections.

  13. 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.

  14. 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.

  15. 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.

  16. Distributed flow optimization and cascading effects in weighted complex networks

    OpenAIRE

    Asztalos, Andrea; Sreenivasan, Sameet; Szymanski, Boleslaw K.; Korniss, G.

    2011-01-01

    We investigate the effect of a specific edge weighting scheme $\\sim (k_i k_j)^{\\beta}$ on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter $\\beta$ and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we show the dependence of transport efficie...

  17. #mytweet via Instagram: Exploring User Behaviour across Multiple Social Networks

    OpenAIRE

    Lim, Bang Hui; Lu, Dongyuan; Chen, Tao; Kan, Min-Yen

    2015-01-01

    We study how users of multiple online social networks (OSNs) employ and share information by studying a common user pool that use six OSNs - Flickr, Google+, Instagram, Tumblr, Twitter, and YouTube. We analyze the temporal and topical signature of users' sharing behaviour, showing how they exhibit distinct behaviorial patterns on different networks. We also examine cross-sharing (i.e., the act of user broadcasting their activity to multiple OSNs near-simultaneously), a previously-unstudied be...

  18. 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

  19. 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.

  20. 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.

  1. Uncoupled Analysis of Stochastic Reaction Networks in Fluctuating Environments

    Science.gov (United States)

    Zechner, Christoph; Koeppl, Heinz

    2014-01-01

    The dynamics of stochastic reaction networks within cells are inevitably modulated by factors considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy numbers for a gene regulatory network. While several recent studies demonstrate the importance of accounting for such extrinsic components, the resulting models are typically hard to analyze. In this work we develop a general mathematical framework that allows to uncouple the network from its dynamic environment by incorporating only the environment's effect onto the network into a new model. More technically, we show how such fluctuating extrinsic components (e.g., chemical species) can be marginalized in order to obtain this decoupled model. We derive its corresponding process- and master equations and show how stochastic simulations can be performed. Using several case studies, we demonstrate the significance of the approach. PMID:25473849

  2. 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)

  3. Assessment of the Sperm Quality Analyzer.

    Science.gov (United States)

    Johnston, R C; Clarke, G N; Liu, D Y; Baker, H W

    1995-05-01

    To assess the relationship between the results of the Sperm Quality Analyzer (United Medical Systems Inc., Santa Ana, CA), which measures motile sperm concentration by light scattering, conventional manual semen analysis characteristics, and computer-assisted sperm motility analyses. Sperm Quality Analyzer measurements and manual and computer-assisted semen analyses were performed on 150 (50, 62, and 38) samples in three laboratories and the results were compared. The study was performed in the Andrology Laboratory of Prince Henry's Institute of Medical Research, Monash Medical Centre, and Andrology Laboratory and Reproductive Biology Unit at the Royal Women's Hospital, Melbourne, Victoria, Australia. Patients presented to the laboratories for routine fertility evaluation in the male and were selected at random to reflect the range of normal and abnormal samples seen in the laboratories. None. Sperm count, motility (percent motility, motility index, velocity, and amplitude of lateral head displacement [ALH]), morphology, and normal acrosomes were evaluated by manual and computer-assisted semen analysis and sperm quality analyzer motility index. Spearman nonparametric univariate analysis showed strong correlations between sperm motility index and manual sperm concentration, motility, abnormal morphology, and normal acrosomes by Pisum sativum agglutinin; and computer-assisted sperm motility analysis sperm concentration, motile concentration, and percent static. Curvilinear velocity, straight-line velocity (VSL), and linearity also were related significantly to sperm motility index values. By multiple regression analysis, the significant covariates of the sperm motility index were motile sperm concentration, abnormal morphology, ALH, and straight-line velocity and these accounted for 85.5% of the variance of the sperm motility index. The Sperm Quality Analyzer is easy to use. The good correlation between the sperm motility index, motile sperm concentration, and, in

  4. 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

  5. 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 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...

  6. 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...

  7. 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

  8. Green-Aware Routing in GMPLS Networks

    DEFF Research Database (Denmark)

    Wang, Jiayuan; Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2012-01-01

    -TE) protocol and a greenaware routing and wavelength assignment (RWA) algorithm for minimizing the GHG emissions by routing connection requests through green network elements (NE). The network behavior and the performance of the algorithm are analyzed through simulations under different scenarios, and results...... show that it is possible to reduce GHGs emissions at the expense of an increase in the path length, and, in some cases, in the blocking probability. The trade-off between emissions and performance is studied. To the authors knowledge, this is the first work that provides a detailed study of a green...

  9. Analysis of Semantic Networks using Complex Networks Concepts

    DEFF Research Database (Denmark)

    Ortiz-Arroyo, Daniel

    2013-01-01

    In this paper we perform a preliminary analysis of semantic networks to determine the most important terms that could be used to optimize a summarization task. In our experiments, we measure how the properties of a semantic network change, when the terms in the network are removed. Our preliminar...... results indicate that this approach provides good results on the semantic network analyzed in this paper....

  10. An application programming interface for CellNetAnalyzer.

    Science.gov (United States)

    Klamt, Steffen; von Kamp, Axel

    2011-08-01

    CellNetAnalyzer (CNA) is a MATLAB toolbox providing computational methods for studying structure and function of metabolic and cellular signaling networks. In order to allow non-experts to use these methods easily, CNA provides GUI-based interactive network maps as a means of parameter input and result visualization. However, with the availability of high-throughput data, there is a need to make CNA's functionality also accessible in batch mode for automatic data processing. Furthermore, as some algorithms of CNA are of general relevance for network analysis it would be desirable if they could be called as sub-routines by other applications. For this purpose, we developed an API (application programming interface) for CNA allowing users (i) to access the content of network models in CNA, (ii) to use CNA's network analysis capabilities independent of the GUI, and (iii) to interact with the GUI to facilitate the development of graphical plugins. Here we describe the organization of network projects in CNA and the application of the new API functions to these projects. This includes the creation of network projects from scratch, loading and saving of projects and scenarios, and the application of the actual analysis methods. Furthermore, API functions for the import/export of metabolic models in SBML format and for accessing the GUI are described. Lastly, two example applications demonstrate the use and versatile applicability of CNA's API. CNA is freely available for academic use and can be downloaded from http://www.mpi-magdeburg.mpg.de/projects/cna/cna.html. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  11. Polymer networks: Modeling and applications

    Science.gov (United States)

    Masoud, Hassan

    Polymer networks are an important class of materials that are ubiquitously found in natural, biological, and man-made systems. The complex mesoscale structure of these soft materials has made it difficult for researchers to fully explore their properties. In this dissertation, we introduce a coarse-grained computational model for permanently cross-linked polymer networks than can properly capture common properties of these materials. We use this model to study several practical problems involving dry and solvated networks. Specifically, we analyze the permeability and diffusivity of polymer networks under mechanical deformations, we examine the release of encapsulated solutes from microgel capsules during volume transitions, and we explore the complex tribological behavior of elastomers. Our simulations reveal that the network transport properties are defined by the network porosity and by the degree of network anisotropy due to mechanical deformations. In particular, the permeability of mechanically deformed networks can be predicted based on the alignment of network filaments that is characterized by a second order orientation tensor. Moreover, our numerical calculations demonstrate that responsive microcapsules can be effectively utilized for steady and pulsatile release of encapsulated solutes. We show that swollen gel capsules allow steady, diffusive release of nanoparticles and polymer chains, whereas gel deswelling causes burst-like discharge of solutes driven by an outward flow of the solvent initially enclosed within a shrinking capsule. We further demonstrate that this hydrodynamic release can be regulated by introducing rigid microscopic rods in the capsule interior. We also probe the effects of velocity, temperature, and normal load on the sliding of elastomers on smooth and corrugated substrates. Our friction simulations predict a bell-shaped curve for the dependence of the friction coefficient on the sliding velocity. Our simulations also illustrate

  12. W-state Analyzer and Multi-party Measurement-device-independent Quantum Key Distribution.

    Science.gov (United States)

    Zhu, Changhua; Xu, Feihu; Pei, Changxing

    2015-12-08

    W-state is an important resource for many quantum information processing tasks. In this paper, we for the first time propose a multi-party measurement-device-independent quantum key distribution (MDI-QKD) protocol based on W-state. With linear optics, we design a W-state analyzer in order to distinguish the four-qubit W-state. This analyzer constructs the measurement device for four-party MDI-QKD. Moreover, we derived a complete security proof of the four-party MDI-QKD, and performed a numerical simulation to study its performance. The results show that four-party MDI-QKD is feasible over 150 km standard telecom fiber with off-the-shelf single photon detectors. This work takes an important step towards multi-party quantum communication and a quantum network.

  13. Exploring network organization in practice

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    that there are different logical considerations when designing a network organization to facilitate innovation. I identify three types of network organizations: market-led, directed and culture-led network organizations. Different types of network organizations show that organizations are dual and even ternary systems...

  14. 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.

  15. 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.

  16. Energy Efficient Evolution of Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Mogensen, Preben

    2011-01-01

    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......, by a maximum of 30%. With regards to the energy efficiency, high deployment of pico sites allowed the network to carry 16% more traffic for the same amount of energy. This, however, results in an increase in cost, specifically operational costs....... 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...

  17. 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.

  18. RMOD: a tool for regulatory motif detection in signaling network.

    Science.gov (United States)

    Kim, Jinki; Yi, Gwan-Su

    2013-01-01

    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.

  19. Quantum synchronization and quantum state sharing in an irregular complex network.

    Science.gov (United States)

    Li, Wenlin; Li, Chong; Song, Heshan

    2017-02-01

    We investigate the quantum synchronization phenomenon of the complex network constituted by coupled optomechanical systems and prove that the unknown identical quantum states can be shared or distributed in the quantum network even though the topology is varying. Considering a channel constructed by quantum correlation, we show that quantum synchronization can sustain and maintain high levels in Markovian dissipation for a long time. We also analyze the state-sharing process between two typical complex networks, and the results predict that linked nodes can be directly synchronized, but the whole network will be synchronized only if some specific synchronization conditions are satisfied. Furthermore, we give the synchronization conditions analytically through analyzing network dynamics. This proposal paves the way for studying multi-interaction synchronization and achieving effective quantum information processing in a complex network.

  20. 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.

  1. 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

  2. Basketball Teams as Strategic Networks

    OpenAIRE

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

    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...

  3. National Seismic Network of Georgia

    Science.gov (United States)

    Tumanova, N.; Kakhoberashvili, S.; Omarashvili, V.; Tserodze, M.; Akubardia, D.

    2016-12-01

    've analyzed data from each station to calculate signal-to-nose ratio. Comparing these calculations with the ones for the existed stations showed that signal-to-nose ratio for new stations has much better value. National Seismic Network of Georgia is planning to install more stations to improve seismic network coverage.

  4. EPMOSt: An Energy-Efficient Passive Monitoring System for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Fernando P. Garcia

    2014-06-01

    Full Text Available Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN. In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios.

  5. EPMOSt: an energy-efficient passive monitoring system for wireless sensor networks.

    Science.gov (United States)

    Garcia, Fernando P; Andrade, Rossana M C; Oliveira, Carina T; de Souza, José Neuman

    2014-06-19

    Monitoring systems are important for debugging and analyzing Wireless Sensor Networks (WSN). In passive monitoring, a monitoring network needs to be deployed in addition to the network to be monitored, named the target network. The monitoring network captures and analyzes packets transmitted by the target network. An energy-efficient passive monitoring system is necessary when we need to monitor a WSN in a real scenario because the lifetime of the monitoring network is extended and, consequently, the target network benefits from the monitoring for a longer time. In this work, we have identified, analyzed and compared the main passive monitoring systems proposed for WSN. During our research, we did not identify any passive monitoring system for WSN that aims to reduce the energy consumption of the monitoring network. Therefore, we propose an Energy-efficient Passive MOnitoring SysTem for WSN named EPMOSt that provides monitoring information using a Simple Network Management Protocol (SNMP) agent. Thus, any management tool that supports the SNMP protocol can be integrated with this monitoring system. Experiments with real sensors were performed in several scenarios. The results obtained show the energy efficiency of the proposed monitoring system and the viability of using it to monitor WSN in real scenarios.

  6. 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.

  7. 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.

  8. 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.

  9. 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). CO2 differential (ΔCO2) increased two-fold with no change in apparent Rd, when the two leaves with higher stomatal density faced outside. These results showed a clear effect of the position of stomata on ΔCO2. Therefore, it can be concluded that leaf position is important to guarantee the improvement of respiration measurements increasing ΔCO2 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.

  10. Chinese lexical networks: The structure, function and formation

    Science.gov (United States)

    Li, Jianyu; Zhou, Jie; Luo, Xiaoyue; Yang, Zhanxin

    2012-11-01

    In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases. To uncover the structural design principles of networks, network motif patterns are studied. It is shown that they serve as basic building blocks to form the whole phrase networks, especially triad 38 (feed forward loop) plays a more important role in forming most of the phrases and other motifs. The distinct structure may not only keep the networks stable and robust, but also be helpful for information processing. The results of the paper can give some insight into Chinese language learning and language acquisition. It strengthens the idea that learning the phrases helps to understand Chinese culture. On the other side, understanding Chinese culture and philosophy does help to learn Chinese phrases. The hub nodes in the networks show the close relationship with Chinese culture and philosophy. Learning or teaching the hub characters, hub-linking phrases and phrases which are meaning related based on motif feature should be very useful and important for Chinese learning and acquisition.

  11. 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.

  12. Lineage grammars: describing, simulating and analyzing population dynamics.

    Science.gov (United States)

    Spiro, Adam; Cardelli, Luca; Shapiro, Ehud

    2014-07-21

    Precise description of the dynamics of biological processes would enable the mathematical analysis and computational simulation of complex biological phenomena. Languages such as Chemical Reaction Networks and Process Algebras cater for the detailed description of interactions among individuals and for the simulation and analysis of ensuing behaviors of populations. However, often knowledge of such interactions is lacking or not available. Yet complete oblivion to the environment would make the description of any biological process vacuous. Here we present a language for describing population dynamics that abstracts away detailed interaction among individuals, yet captures in broad terms the effect of the changing environment, based on environment-dependent Stochastic Tree Grammars (eSTG). It is comprised of a set of stochastic tree grammar transition rules, which are context-free and as such abstract away specific interactions among individuals. Transition rule probabilities and rates, however, can depend on global parameters such as population size, generation count, and elapsed time. We show that eSTGs conveniently describe population dynamics at multiple levels including cellular dynamics, tissue development and niches of organisms. Notably, we show the utilization of eSTG for cases in which the dynamics is regulated by environmental factors, which affect the fate and rate of decisions of the different species. eSTGs are lineage grammars, in the sense that execution of an eSTG program generates the corresponding lineage trees, which can be used to analyze the evolutionary and developmental history of the biological system under investigation. These lineage trees contain a representation of the entire events history of the system, including the dynamics that led to the existing as well as to the extinct individuals. We conclude that our suggested formalism can be used to easily specify, simulate and analyze complex biological systems, and supports modular

  13. 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.

  14. Modeling and analyzing architectural change with alloy

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Ingstrup, Mads

    2010-01-01

    Although adaptivity based on reconfiguration has the potential to improve dependability of systems, the cost of a failed attempt at reconfiguration is prohibitive in precisely the applications where high dependability is required. Existing work on formal modeling and verification of architectural...... reconfigurations partly achieve the goal of ensuring correctness, however the formalisms used often lack tool support and the ensuing models have uncertain relation to a concrete implementation. Thus a practical way to ensure with formal certainty that specific architectural changes are correct remains a barrier...... to the uptake of reconfiguration techniques in industry. Using the Alloy language and associated tool, we propose a practical way to formally model and analyze runtime architectural change expressed as architectural scripts. Our evaluation shows the performance to be acceptable; our experience...

  15. Topological properties of hierarchical networks.

    Science.gov (United States)

    Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

    2015-06-01

    Hierarchical networks are attracting a renewal interest for modeling the organization of a number of biological systems and for tackling the complexity of statistical mechanical models beyond mean-field limitations. Here we consider the Dyson hierarchical construction for ferromagnets, neural networks, and spin glasses, recently analyzed from a statistical-mechanics perspective, and we focus on the topological properties of the underlying structures. In particular, we find that such structures are weighted graphs that exhibit a high degree of clustering and of modularity, with a small spectral gap; the robustness of such features with respect to the presence of thermal noise is also studied. These outcomes are then discussed and related to the statistical-mechanics scenario in full consistency. Last, we look at these weighted graphs as Markov chains and we show that in the limit of infinite size, the emergence of ergodicity breakdown for the stochastic process mirrors the emergence of metastabilities in the corresponding statistical mechanical analysis.

  16. Topological properties of hierarchical networks

    Science.gov (United States)

    Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

    2015-06-01

    Hierarchical networks are attracting a renewal interest for modeling the organization of a number of biological systems and for tackling the complexity of statistical mechanical models beyond mean-field limitations. Here we consider the Dyson hierarchical construction for ferromagnets, neural networks, and spin glasses, recently analyzed from a statistical-mechanics perspective, and we focus on the topological properties of the underlying structures. In particular, we find that such structures are weighted graphs that exhibit a high degree of clustering and of modularity, with a small spectral gap; the robustness of such features with respect to the presence of thermal noise is also studied. These outcomes are then discussed and related to the statistical-mechanics scenario in full consistency. Last, we look at these weighted graphs as Markov chains and we show that in the limit of infinite size, the emergence of ergodicity breakdown for the stochastic process mirrors the emergence of metastabilities in the corresponding statistical mechanical analysis.

  17. 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

  18. 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.

  19. 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.

  20. Assessing dynamics, spatial scale, and uncertainty in task-related brain network analyses.

    Science.gov (United States)

    Stephen, Emily P; Lepage, Kyle Q; Eden, Uri T; Brunner, Peter; Schalk, Gerwin; Brumberg, Jonathan S; Guenther, Frank H; Kramer, Mark A

    2014-01-01

    The brain is a complex network of interconnected elements, whose interactions evolve dynamically in time to cooperatively perform specific functions. A common technique to probe these interactions involves multi-sensor recordings of brain activity during a repeated task. Many techniques exist to characterize the resulting task-related activity, including establishing functional networks, which represent the statistical associations between brain areas. Although functional network inference is commonly employed to analyze neural time series data, techniques to assess the uncertainty-both in the functional network edges and the corresponding aggregate measures of network topology-are lacking. To address this, we describe a statistically principled approach for computing uncertainty in functional networks and aggregate network measures in task-related data. The approach is based on a resampling procedure that utilizes the trial structure common in experimental recordings. We show in simulations that this approach successfully identifies functional networks and associated measures of confidence emergent during a task in a variety of scenarios, including dynamically evolving networks. In addition, we describe a principled technique for establishing functional networks based on predetermined regions of interest using canonical correlation. Doing so provides additional robustness to the functional network inference. Finally, we illustrate the use of these methods on example invasive brain voltage recordings collected during an overt speech task. The general strategy described here-appropriate for static and dynamic network inference and different statistical measures of coupling-permits the evaluation of confidence in network measures in a variety of settings common to neuroscience.

  1. Recommending Learning Activities in Social Network Using Data Mining Algorithms

    Science.gov (United States)

    Mahnane, Lamia

    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…

  2. 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…

  3. Energy efficient topology for Wireless Mesh Networks | Negash ...

    African Journals Online (AJOL)

    We analyze the power control problem using coalition formation game theory employing utilities based on the coverage areas of the access points by associating a cost function with the utility as the payoff of the coalition members. Our work focuses on the access layer of a wireless mesh local area network. We show that by ...

  4. An Equilibrium-Correction Model for Dynamic Network Data

    NARCIS (Netherlands)

    D.J. Dekker (David); Ph.H.B.F. Franses (Philip Hans); D. Krackhardt (David)

    2001-01-01

    textabstractWe propose a two-stage MRQAP to analyze dynamic network data, within the framework of an equilibrium-correction (EC) model. Extensive simulation results indicate practical relevance of our method and its improvement over standard OLS. An empirical illustration additionally shows that the

  5. 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.

  6. Overlapping coalition formation games in wireless communication networks

    CERN Document Server

    Wang, Tianyu; Saad, Walid; Han, Zhu

    2017-01-01

    This brief introduces overlapping coalition formation games (OCF games), a novel mathematical framework from cooperative game theory that can be used to model, design and analyze cooperative scenarios in future wireless communication networks. The concepts of OCF games are explained, and several algorithmic aspects are studied. In addition, several major application scenarios are discussed. These applications are drawn from a variety of fields that include radio resource allocation in dense wireless networks, cooperative spectrum sensing for cognitive radio networks, and resource management for crowd sourcing. For each application, the use of OCF games is discussed in detail in order to show how this framework can be used to solve relevant wireless networking problems. Overlapping Coalition Formation Games in Wireless Communication Networks provides researchers, students and practitioners with a concise overview of existing works in this emerging area, exploring the relevant fundamental theories, key techniqu...

  7. 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.

  8. Common Organizing Mechanisms in Ecological and Socio-economic Networks

    CERN Document Server

    Saavedra, Serguei; Uzzi, Brian

    2011-01-01

    Previous work has shown that species interacting in an ecosystem and actors transacting in an economic context may have notable similarities in behavior. However, the specific mechanism that may underlie similarities in nature and human systems has not been analyzed. Building on stochastic food-web models, we propose a parsimonious bipartite-cooperation model that reproduces the key features of mutualistic networks - degree distribution, nestedness and modularity -- for both ecological networks and socio-economic networks. Our analysis uses two diverse networks. Mutually-beneficial interactions between plants and their pollinators, and cooperative economic exchanges between designers and their contractors. We find that these mutualistic networks share a key hierarchical ordering of their members, along with an exponential constraint in the number and type of partners they can cooperate with. We use our model to show that slight changes in the interaction constraints can produce either extremely nested or rand...

  9. Division of labor, skill complementarity, and heterophily in socioeconomic networks

    CERN Document Server

    Xie, Wen-Jie; Jiang, Zhi-Qiang; Tan, Qun-Zhao; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H Eugene

    2016-01-01

    Constituents of complex systems interact with each other and self-organize to form complex networks. Empirical results show that the link formation process of many real networks follows either the global principle of popularity or the local principle of similarity or a tradeoff between the two. In particular, it has been shown that in social networks individuals exhibit significant homophily when choosing their collaborators. We demonstrate, however, that in populations in which there is a division of labor, skill complementarity is an important factor in the formation of socioeconomic networks and an individual's choice of collaborators is strongly affected by heterophily. We analyze 124 evolving virtual worlds of a popular "massively multiplayer online role-playing game" (MMORPG) in which people belong to three different professions and are allowed to work and interact with each other in a somewhat realistic manner. We find evidence of heterophily in the formation of collaboration networks, where people pre...

  10. Social networks in and between organizations

    NARCIS (Netherlands)

    Groenewegen, P.; Ferguson, J.E.

    2017-01-01

    Social networks form a core topic in the study of organizational and interorganizational processes. Social network research often focuses on individual-level networks, analyzing and theorizing the relations and structures around single actors or organizations. Individual-level network studies are

  11. Core Benefits of Network Participation

    OpenAIRE

    Kheiri Pileh Roud, Ensieh

    2015-01-01

    This study deals with the core benefits of network participation from the maritime companies’ perspective. It mainly focuses on the area of innovation, network qualities and absorptive capacities. A single case study has been conducted to address two research questions; 1) what are the core benefits of network participation for a maritime company? 2) Which qualities of network events influence the benefits for the participants? The main findings show that, the networks are valuable communi...

  12. Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

    Science.gov (United States)

    Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

    2017-01-01

    Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

  13. Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

    Directory of Open Access Journals (Sweden)

    Shameng Wen

    Full Text Available Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

  14. EEG classification of emotions using emotion-specific brain functional network.

    Science.gov (United States)

    Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

    2015-08-01

    The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.

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

    Science.gov (United States)

    Yang, Qiang; Wu, Chunming; Zhang, Min

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

  16. Methods of analyzing regional dermatological care as exemplified by the city of Hamburg.

    Science.gov (United States)

    Augustin, Jobst; Erasmi, Stefan; Reusch, Michael; Augustin, Matthias

    2015-07-01

    The rural-urban divide is often linked to regional inequalities in healthcare. However, studies have also shown regional healthcare disparities within urban areas. To evaluate these studies, further parameters such as accessibility must be added to the standard criteria. The objective of this study was to present methodic tools for evaluating dermatological healthcare provision in Hamburg, primarily focusing on accessibility. Analyzing data from 97 districts, the geographical distribution of 101 dermatologists and the physician-patient ratio were determined. In a second step, network analysis regarding accessibility was performed. There are regional inequalities in Hamburg with respect to dermatological care. Depending on the district, the physician-patient ratio ranges from 44.9 % (undersupply) to > 500 % (oversupply). Similar differences exist regarding accessibility. Although 94.5 % of the population of Hamburg is able to reach the nearest dermatologist within ten minutes (by car), it may take more than 30 minutes depending on district and mode of transportation. Analysis of the physician-patient ratio reveals differences regarding dermatological care in Hamburg. However, results of the network analysis show that these differences do not significantly affect access to dermatological care. Therefore, network analysis should be used as an additional tool to evaluate regional healthcare provision. © 2015 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.

  17. Portable Programmable Multifunction Body Fluids Analyzer Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Liquid Logic proposes to develop a very capable analyzer based on its digital microfluidic technology. Such an analyzer would be:  Capable of both...

  18. Social Network Types and Mental Health Among LGBT Older Adults.

    Science.gov (United States)

    Kim, Hyun-Jun; Fredriksen-Goldsen, Karen I; Bryan, Amanda E B; Muraco, Anna

    2017-02-01

    This study was designed to identify social network types among lesbian, gay, bisexual, and transgender (LGBT) older adults and examine the relationship between social network type and mental health. We analyzed the 2014 survey data of LGBT adults aged 50 and older (N = 2,450) from Aging with Pride: National Health, Aging, and Sexuality/Gender Study. Latent profile analyses were conducted to identify clusters of social network ties based on 11 indicators. Multiple regression analysis was performed to examine the association between social network types and mental health. We found five social network types. Ordered from greatest to least access to family, friend, and other non-family network ties, they were diverse, diverse/no children, immediate family-focused, friend-centered/restricted, and fully restricted. The friend-centered/restricted (33%) and diverse/no children network types (31%) were the most prevalent. Among individuals with the friend-centered/restricted type, access to social networks was limited to friends, and across both types children were not present. The least prevalent type was the fully restricted network type (6%). Social network type was significantly associated with mental health, after controlling for background characteristics and total social network size; those with the fully restricted type showed the poorest mental health. Unique social network types (diverse/no children and friend-centered/restricted) emerge among LGBT older adults. Moreover, individuals with fully restricted social networks are at particular risk due to heightened health needs and limited social resources. This study highlights the importance of understanding heterogeneous social relations and developing tailored interventions to promote social connectedness and mental health in LGBT older adults. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. The network researchers' network

    DEFF Research Database (Denmark)

    Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter

    2009-01-01

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi......The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

  20. Tourism Destinations Network Analysis, Social Network Analysis Approach

    Directory of Open Access Journals (Sweden)

    2015-09-01

    Full Text Available The tourism industry is becoming one of the world's largest economical sources, and is expected to become the world's first industry by 2020. Previous studies have focused on several aspects of this industry including sociology, geography, tourism management and development, but have paid less attention to analytical and quantitative approaches. This study introduces some network analysis techniques and measures aiming at studying the structural characteristics of tourism networks. More specifically, it presents a methodology to analyze tourism destinations network. We apply the methodology to analyze mazandaran’s Tourism destination network, one of the most famous tourism areas of Iran.

  1. Distinction and Connection between Contact Network, Social Network, and Disease Transmission Network

    OpenAIRE

    Chen, Shi; Lanzas, Cristina

    2016-01-01

    In this paper we discuss the distinction and connection between three closely related networks in animal ecology and epidemiology studies: the contact, social, and disease transmission networks. We provide a robust theoretical definition and interpretation of these three networks, demonstrate that social and disease transmission networks can be derived as spanning subgraphs of contact network, and show examples based on real-world high-resolution cattle contact structure data. Furthermore, we...

  2. 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

  3. Rumor Diffusion in an Interests-Based Dynamic Social Network

    Directory of Open Access Journals (Sweden)

    Mingsheng Tang

    2013-01-01

    Full Text Available To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1 positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2 with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3 a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4 a network with a smaller clustering coefficient has a larger efficiency.

  4. The performance analysis of linux networking - packet receiving

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Wenji; Crawford, Matt; Bowden, Mark; /Fermilab

    2006-11-01

    The computing models for High-Energy Physics experiments are becoming ever more globally distributed and grid-based, both for technical reasons (e.g., to place computational and data resources near each other and the demand) and for strategic reasons (e.g., to leverage equipment investments). To support such computing models, the network and end systems, computing and storage, face unprecedented challenges. One of the biggest challenges is to transfer scientific data sets--now in the multi-petabyte (10{sup 15} bytes) range and expected to grow to exabytes within a decade--reliably and efficiently among facilities and computation centers scattered around the world. Both the network and end systems should be able to provide the capabilities to support high bandwidth, sustained, end-to-end data transmission. Recent trends in technology are showing that although the raw transmission speeds used in networks are increasing rapidly, the rate of advancement of microprocessor technology has slowed down. Therefore, network protocol-processing overheads have risen sharply in comparison with the time spent in packet transmission, resulting in degraded throughput for networked applications. More and more, it is the network end system, instead of the network, that is responsible for degraded performance of network applications. In this paper, the Linux system's packet receive process is studied from NIC to application. We develop a mathematical model to characterize the Linux packet receiving process. Key factors that affect Linux systems network performance are analyzed.

  5. Synchrony with shunting inhibition in a feedforward inhibitory network.

    Science.gov (United States)

    Talathi, Sachin S; Hwang, Dong-Uk; Carney, Paul R; Ditto, William L

    2010-04-01

    Recent experiments have shown that GABA(A) receptor mediated inhibition in adult hippocampus is shunting rather than hyperpolarizing. Simulation studies of realistic interneuron networks with strong shunting inhibition have been demonstrated to exhibit robust gamma band (20-80 Hz) synchrony in the presence of heterogeneity in the intrinsic firing rates of individual neurons in the network. In order to begin to understand how shunting can contribute to network synchrony in the presence of heterogeneity, we develop a general theoretical framework using spike time response curves (STRC's) to study patterns of synchrony in a simple network of two unidirectionally coupled interneurons (UCI network) interacting through a shunting synapse in the presence of heterogeneity. We derive an approximate discrete map to analyze the dynamics of synchronous states in the UCI network by taking into account the nonlinear contributions of the higher order STRC terms. We show how the approximate discrete map can be used to successfully predict the domain of synchronous 1:1 phase locked state in the UCI network. The discrete map also allows us to determine the conditions under which the two interneurons can exhibit in-phase synchrony. We conclude by demonstrating how the information from the study of the discrete map for the dynamics of the UCI network can give us valuable insight into the degree of synchrony in a larger feed-forward network of heterogeneous interneurons.

  6. 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

    Our future in personal and professional lives is becoming more attached to the evolution of communication technologies and their applications. Consequently, the way Next Generation Network are currently being planned and deployed, might have a great impact on common people depending on how networks...... 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...

  7. INTERORGANIZATIONAL COOPERATION IN FURNITURE SECTOR: A CASE STUDY USING THE SOCIAL NETWORKS ANALYSIS

    Directory of Open Access Journals (Sweden)

    Marísia Monte Silva Aguiar

    2014-11-01

    Full Text Available This research aims to analyze the elements involved in the development of interorganizational cooperation networks by assessing the design of Network Association of Cabinetmakers in Fortaleza (AMFOR, from his actors, properties and types. For this purpose, the procedures consist on the analytical tools of social networking through the software and Ucinet NetDraw. The results show that within six years of the Network AMFOR, their level of cooperation could enhance this collective enterprise, generating a reasonable number of regular contacts. However, it was realized the need for investment in the relationships of the actors in order to further consolidate the venture.

  8. Contracting for Competitive Supply Chains under Network Externalities and Demand Uncertainty

    Directory of Open Access Journals (Sweden)

    Xiaojing Liu

    2016-01-01

    Full Text Available Based on network externalities and demand uncertainty environment, supply chain competition model is built; we identify the valid mechanism for the alternative range of profit-sharing contracts and also analyze the effect of product substitutability coefficient and network externalities on the alliance and profit-sharing contract. The results show that the vertical alliance contributes profit improvement to both the manufacturer and the retailer when the impact of network externalities on the product substitutability is not strong. However, vertical alliance will be out of operation when the effect of network externalities on the product substitutability is strong.

  9. Autonomous and Decentralized Optimization of Large-Scale Heterogeneous Wireless Networks by Neural Network Dynamics

    Science.gov (United States)

    Hasegawa, Mikio; Tran, Ha Nguyen; Miyamoto, Goh; Murata, Yoshitoshi; Harada, Hiroshi; Kato, Shuzo

    We propose a neurodynamical approach to a large-scale optimization problem in Cognitive Wireless Clouds, in which a huge number of mobile terminals with multiple different air interfaces autonomously utilize the most appropriate infrastructure wireless networks, by sensing available wireless networks, selecting the most appropriate one, and reconfiguring themselves with seamless handover to the target networks. To deal with such a cognitive radio network, game theory has been applied in order to analyze the stability of the dynamical systems consisting of the mobile terminals' distributed behaviors, but it is not a tool for globally optimizing the state of the network. As a natural optimization dynamical system model suitable for large-scale complex systems, we introduce the neural network dynamics which converges to an optimal state since its property is to continually decrease its energy function. In this paper, we apply such neurodynamics to the optimization problem of radio access technology selection. We compose a neural network that solves the problem, and we show that it is possible to improve total average throughput simply by using distributed and autonomous neuron updates on the terminal side.

  10. Comparison and evaluation of network clustering algorithms applied to genetic interaction networks.

    Science.gov (United States)

    Hou, Lin; Wang, Lin; Berg, Arthur; Qian, Minping; Zhu, Yunping; Li, Fangting; Deng, Minghua

    2012-01-01

    The goal of network clustering algorithms detect dense clusters in a network, and provide a first step towards the understanding of large scale biological networks. With numerous recent advances in biotechnologies, large-scale genetic interactions are widely available, but there is a limited understanding of which clustering algorithms may be most effective. In order to address this problem, we conducted a systematic study to compare and evaluate six clustering algorithms in analyzing genetic interaction networks, and investigated influencing factors in choosing algorithms. The algorithms considered in this comparison include hierarchical clustering, topological overlap matrix, bi-clustering, Markov clustering, Bayesian discriminant analysis based community detection, and variational Bayes approach to modularity. Both experimentally identified and synthetically constructed networks were used in this comparison. The accuracy of the algorithms is measured by the Jaccard index in comparing predicted gene modules with benchmark gene sets. The results suggest that the choice differs according to the network topology and evaluation criteria. Hierarchical clustering showed to be best at predicting protein complexes; Bayesian discriminant analysis based community detection proved best under epistatic miniarray profile (EMAP) datasets; the variational Bayes approach to modularity was noticeably better than the other algorithms in the genome-scale networks.

  11. Emergent complex network geometry.

    Science.gov (United States)

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

    2015-05-18

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

  12. Module identification in bipartite and directed networks

    OpenAIRE

    Guimera, R.; Sales-Pardo, M.; Amaral, L. A. N.

    2007-01-01

    Modularity is one of the most prominent properties of real-world complex networks. Here, we address the issue of module identification in two important classes of networks: bipartite networks and directed unipartite networks. Nodes in bipartite networks are divided into two non-overlapping sets, and the links must have one end node from each set. Directed unipartite networks only have one type of nodes, but links have an origin and an end. We show that directed unipartite networks can be conv...

  13. Countering Threat Networks

    Science.gov (United States)

    2016-12-21

    throughout Latin America , and their licit and illicit activities span Asia, Europe, and Africa. e. As the power and influence of these organizations has...networks not bound by geography . Intelligence efforts within the shaping phase show threat network linkages in terms of leadership, organization, size...flow of drugs from Central and South America and the Caribbean into the US from threat networks. From the onset, it became readily apparent that

  14. Affinity driven social networks

    Science.gov (United States)

    Ruyú, B.; Kuperman, M. N.

    2007-04-01

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

  15. Distinction and connection between contact network, social network, and disease transmission network.

    Science.gov (United States)

    Chen, Shi; Lanzas, Cristina

    2016-09-01

    In this paper we discuss the distinction and connection between three closely related networks in animal ecology and epidemiology studies: the contact, social, and disease transmission networks. We provide a robust theoretical definition and interpretation of these three networks, demonstrate that social and disease transmission networks can be derived as spanning subgraphs of contact network, and show examples based on real-world high-resolution cattle contact structure data. Furthermore, we establish a modeling framework to track potential disease transmission dynamics and construct transmission network based on the observed animal contact network. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Network analysis of eight industrial symbiosis systems

    Science.gov (United States)

    Zhang, Yan; Zheng, Hongmei; Shi, Han; Yu, Xiangyi; Liu, Gengyuan; Su, Meirong; Li, Yating; Chai, Yingying

    2016-06-01

    Industrial symbiosis is the quintessential characteristic of an eco-industrial park. To divide parks into different types, previous studies mostly focused on qualitative judgments, and failed to use metrics to conduct quantitative research on the internal structural or functional characteristics of a park. To analyze a park's structural attributes, a range of metrics from network analysis have been applied, but few researchers have compared two or more symbioses using multiple metrics. In this study, we used two metrics (density and network degree centralization) to compare the degrees of completeness and dependence of eight diverse but representative industrial symbiosis networks. Through the combination of the two metrics, we divided the networks into three types: weak completeness, and two forms of strong completeness, namely "anchor tenant" mutualism and "equality-oriented" mutualism. The results showed that the networks with a weak degree of completeness were sparse and had few connections among nodes; for "anchor tenant" mutualism, the degree of completeness was relatively high, but the affiliated members were too dependent on core members; and the members in "equality-oriented" mutualism had equal roles, with diverse and flexible symbiotic paths. These results revealed some of the systems' internal structure and how different structures influenced the exchanges of materials, energy, and knowledge among members of a system, thereby providing insights into threats that may destabilize the network. Based on this analysis, we provide examples of the advantages and effectiveness of recent improvement projects in a typical Chinese eco-industrial park (Shandong Lubei).

  17. Requirements for a Network Storage Service in a supercomputer environment

    Energy Technology Data Exchange (ETDEWEB)

    Kelly, S.M.

    1991-09-26

    Sandia National Laboratories has completed a requirements study for a networked mass storage system. The areas of user functionality, network connectivity, and performance were analyzed to determine specifications for a Network Storage Service to operate in supercomputer environment. 4 refs.

  18. A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

    Science.gov (United States)

    Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

    2015-12-26

    Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

  19. A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Liu Yang

    2015-12-01

    Full Text Available Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs in the network act as routers to transmit data to base station (BS cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

  20. Modular Brain Networks.

    Science.gov (United States)

    Sporns, Olaf; Betzel, Richard F

    2016-01-01

    The development of new technologies for mapping structural and functional brain connectivity has led to the creation of comprehensive network maps of neuronal circuits and systems. The architecture of these brain networks can be examined and analyzed with a large variety of graph theory tools. Methods for detecting modules, or network communities, are of particular interest because they uncover major building blocks or subnetworks that are particularly densely connected, often corresponding to specialized functional components. A large number of methods for community detection have become available and are now widely applied in network neuroscience. This article first surveys a number of these methods, with an emphasis on their advantages and shortcomings; then it summarizes major findings on the existence of modules in both structural and functional brain networks and briefly considers their potential functional roles in brain evolution, wiring minimization, and the emergence of functional specialization and complex dynamics.

  1. Visualization of Social Networks

    Science.gov (United States)

    Chen, Ing-Xiang; Yang, Cheng-Zen

    With the ubiquitous characteristic of the Internet, today many online social environments are provided to connect people. Various social relationships are thus created, connected, and migrated from our real lives to the Internet environment from different social groups. Many social communities and relationships are also quickly constructed and connected via instant personal messengers, blogs, Twitter, Facebook, and a great variety of online social services. Since social network visualizations can structure the complex relationships between different groups of individuals or organizations, they are helpful to analyze the social activities and relationships of actors, particularly over a large number of nodes. Therefore, many studies and visualization tools have been investigated to present social networks with graph representations. In this chapter, we will first review the background of social network analysis and visualization methods, and then introduce various novel visualization applications for social networks. Finally, the challenges and the future development of visualizing online social networks are discussed.

  2. Community structure of complex networks based on continuous neural network

    Science.gov (United States)

    Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou

    2017-09-01

    As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.

  3. Congestion control and routing over satellite networks

    Science.gov (United States)

    Cao, Jinhua

    Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE

  4. Statistical analysis of the road network of India

    Indian Academy of Sciences (India)

    These include the airport network of China [1], the airport network of India [2], the world-wide airport network [3,4], the urban road networks [5] and the railway networks [6–10]. The topology studies of different spatial networks show different degree distributions. Power law degree distribution is seen for Indian airport network ...

  5. Influence network in Chinese stock market

    CERN Document Server

    Gao, Ya-Chun; Cai, Shi-Min

    2015-01-01

    In a stock market, the price fluctuations are interactive, that is, one listed company can influence others. In this paper, we seek to study the influence relationships among listed companies by constructing a directed network on the basis of Chinese stock market. This influence network shows distinct topological properties, particularly, a few large companies that can lead the tendency of stock market are recognized. Furthermore, by analyzing the subnetworks of listed companies distributed in several significant economic sectors, it is found that the influence relationships are totally different from one economic sector to another, of which three types of connectivity as well as hub-like listed companies are identified. In addition, the rankings of listed companies obtained from the centrality metrics of influence network are compared with that according to the assets, which gives inspiration to uncover and understand the importance of listed companies in the stock market. These empirical results are meaning...

  6. Ultra wideband technology for wireless sensor networks

    Science.gov (United States)

    Wang, Yue; Xiong, Weiming

    2011-08-01

    Wireless sensor networks (WSNs) have emerged as an important method for planetary surface exploration. To investigate the optimized wireless technology for WSNs, we summarized the key requirements of WSNs and justified ultra wideband (UWB) technology by comparing with other competitive wireless technologies. We also analyzed network topologies as well as physical and MAC layer designs of IEEE 802.15.4a standard, which adopted impulse radio UWB (IR-UWB) technology. Our analysis showed that IR-UWB-based 802.15.4a standard could enable robust communication, precise ranging, and heterogeneous networking for WSNs applications. The result of our present work implies that UWB-based WSNs can be applied to future planetary surface exploration.

  7. How students use social networks in education?

    Directory of Open Access Journals (Sweden)

    Feshchenko Artem

    2016-01-01

    Full Text Available The aim of this study is analysis of the use of social networks (SN by Russian students in training. The study analyzed the results of the survey respondents from 25 universities of the Russian Federation (375 participants. Results of the study showed that 95% of students use SN in education, 5% refuse them. Students spend about 24% of their time to SN for the purpose of learning. Remaining time they spend on entertainment (41%, finding useful information (28% and other (7%. Distribution of training time takes students: 35% - in the classroom with a teacher, 22% - using a variety of ICT (not including SN and LMS, 21% - extracurricular work without ICT, 15% - in SN, 7% - in LMS. Social networks are the de facto space for learning, and it’s happening at the initiative of the students themselves. And if the teacher offers students interact via the network in the course, the students’ attention more switches from entertainment to education.

  8. Designing value-creating supply chain networks

    CERN Document Server

    Martel, Alain

    2016-01-01

    Focusing on the design of robust value-creating supply chain networks (SCN) and key strategic issues related to the number; location, capacity and mission of supply chain facilities (plants, distribution centers) – as well as the network structure required to provide flexibility and resilience in an uncertain world – this book presents an innovative methodology for SCN reengineering that can be used to significantly improve the bottom line of supply chain dependent businesses. Providing readers with the tools needed to analyze and model value creation activities, Designing Value-Creating Supply Chain Networks examines the risks faced by modern supply chains, and shows how to develop plausible future scenarios to evaluate potential SCN designs. The design methods proposed are based on a visual representation formalism that facilitates the analysis and modeling of SCN design problems, book chapters incorporate several example problems and exercises which can be solved with Excel tools (Analysis tools and So...

  9. Customer Intelligence Analytics on Social Networks

    Directory of Open Access Journals (Sweden)

    Brano MARKIĆ

    2016-08-01

    Full Text Available Discovering needs, habits and consumer behavior is the primary task of marketing analytics. It is necessary to integrate marketing and analytical skills with IT skills. Such knowledge integration allows access to data (structured and unstructured, their analysis and finding out information about the opinions, attitudes, needs and behavior of customers. In the paper is set the hypothesis that software tools can collect data (messages from social networks, analyze the content of messages and get to know the attitudes of customers about a product, service, tourist destination with the ultimate goal of improving customer relations. Experimental results are based on the analysis of the content of social network Facebook by using the package and function R language. This language showed a satisfactory application and development power in analysis of textual data on social networks for marketing analytics.

  10. The predictive power of local properties of financial networks

    Science.gov (United States)

    Caraiani, Petre

    2017-01-01

    The literature on analyzing the dynamics of financial networks has focused so far on the predictive power of global measures of networks like entropy or index cohesive force. In this paper, I show that the local network properties have similar predictive power. I focus on key network measures like average path length, average degree or cluster coefficient, and also consider the diameter and the s-metric. Using Granger causality tests, I show that some of these measures have statistically significant prediction power with respect to the dynamics of aggregate stock market. Average path length is most robust relative to the frequency of data used or specification (index or growth rate). Most measures are found to have predictive power only for monthly frequency. Further evidences that support this view are provided through a simple regression model.

  11. Analytic solution of neural network with disordered lateral inhibition

    Science.gov (United States)

    Hamaguchi, Kosuke; Hatchett, J. P. L.; Okada, Masato

    2006-05-01

    The replica method has played a key role in analyzing systems with disorder, e.g., the Sherrington-Kirkpatrick (SK) model, and associative neural networks. Here we study the influence of disorder in the lateral inhibition type interactions on the cooperative and uncooperative behavior of recurrent neural networks by using the replica method. Although the interaction between neurons has a dependency on distance, our model can be solved analytically. Bifurcation analysis identifies the boundaries between paramagnetic, ferromagnetic, spin-glass, and localized phases. In the localized phase, the network shows a bump like activity, which is often used as a model of spatial working memory or columnar activity in the visual cortex. Simulation results show that disordered interactions can stabilize the drift the of bump position, which is commonly observed in conventional lateral inhibition type neural networks.

  12. Network analysis of breast cancer progression and reversal using a tree-evolving network algorithm.

    Directory of Open Access Journals (Sweden)

    Ankur P Parikh

    2014-07-01

    Full Text Available The HMT3522 progression series of human breast cells have been used to discover how tissue architecture, microenvironment and signaling molecules affect breast cell growth and behaviors. However, much remains to be elucidated about malignant and phenotypic reversion behaviors of the HMT3522-T4-2 cells of this series. We employed a "pan-cell-state" strategy, and analyzed jointly microarray profiles obtained from different state-specific cell populations from this progression and reversion model of the breast cells using a tree-lineage multi-network inference algorithm, Treegl. We found that different breast cell states contain distinct gene networks. The network specific to non-malignant HMT3522-S1 cells is dominated by genes involved in normal processes, whereas the T4-2-specific network is enriched with cancer-related genes. The networks specific to various conditions of the reverted T4-2 cells are enriched with pathways suggestive of compensatory effects, consistent with clinical data showing patient resistance to anticancer drugs. We validated the findings using an external dataset, and showed that aberrant expression values of certain hubs in the identified networks are associated with poor clinical outcomes. Thus, analysis of various reversion conditions (including non-reverted of HMT3522 cells using Treegl can be a good model system to study drug effects on breast cancer.

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

    OpenAIRE

    Lan Liu; Ryan K. L. Ko; Guangming Ren; Xiaoping Xu

    2017-01-01

    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 ne...

  14. Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks.

    Directory of Open Access Journals (Sweden)

    Saket Navlakha

    2015-07-01

    Full Text Available Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains.

  15. 3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

    Science.gov (United States)

    Ross, Muriel D.; Meyer, Glenn; Lam, Tony; Cutler, Lynn; Vaziri, Parshaw

    1990-01-01

    Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

  16. Functional roles of slow enzyme conformational changes in network dynamics.

    Science.gov (United States)

    Wu, Zhanghan; Xing, Jianhua

    2012-09-05

    Extensive studies from different fields reveal that many macromolecules, especially enzymes, show slow transitions among different conformations. This phenomenon is named such things as dynamic disorder, heterogeneity, hysteretic or mnemonic enzymes across these different fields, and has been directly demonstrated by single molecule enzymology and NMR studies recently. We analyzed enzyme slow conformational changes in the context of regulatory networks. A single enzymatic reaction with slow conformational changes can filter upstream network noises, and can either resonantly respond to the system stimulus at certain frequencies or respond adaptively for sustained input signals of the network fluctuations. It thus can serve as a basic functional motif with properties that are normally for larger intermolecular networks in the field of systems biology. We further analyzed examples including enzymes functioning against pH fluctuations, metabolic state change of Artemia embryos, and kinetic insulation of fluctuations in metabolic networks. The study also suggests that hysteretic enzymes may be building blocks of synthetic networks with various properties such as narrow-banded filtering. The work fills the missing gap between studies on enzyme biophysics and network level dynamics, and reveals that the coupling between the two is functionally important; it also suggests that the conformational dynamics of some enzymes may be evolutionally selected. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  17. Network Forensics Method Based on Evidence Graph and Vulnerability Reasoning

    Directory of Open Access Journals (Sweden)

    Jingsha He

    2016-11-01

    Full Text Available As the Internet becomes larger in scale, more complex in structure and more diversified in traffic, the number of crimes that utilize computer technologies is also increasing at a phenomenal rate. To react to the increasing number of computer crimes, the field of computer and network forensics has emerged. The general purpose of network forensics is to find malicious users or activities by gathering and dissecting firm evidences about computer crimes, e.g., hacking. However, due to the large volume of Internet traffic, not all the traffic captured and analyzed is valuable for investigation or confirmation. After analyzing some existing network forensics methods to identify common shortcomings, we propose in this paper a new network forensics method that uses a combination of network vulnerability and network evidence graph. In our proposed method, we use vulnerability evidence and reasoning algorithm to reconstruct attack scenarios and then backtrack the network packets to find the original evidences. Our proposed method can reconstruct attack scenarios effectively and then identify multi-staged attacks through evidential reasoning. Results of experiments show that the evidence graph constructed using our method is more complete and credible while possessing the reasoning capability.

  18. Network Analysis, Architecture, and Design

    CERN Document Server

    McCabe, James D

    2007-01-01

    Traditionally, networking has had little or no basis in analysis or architectural development, with designers relying on technologies they are most familiar with or being influenced by vendors or consultants. However, the landscape of networking has changed so that network services have now become one of the most important factors to the success of many third generation networks. It has become an important feature of the designer's job to define the problems that exist in his network, choose and analyze several optimization parameters during the analysis process, and then prioritize and evalua

  19. Analyzing dialect variation in historical speech corpora.

    Science.gov (United States)

    Renwick, Margaret E L; Olsen, Rachel M

    2017-07-01

    The Linguistic Atlas of the Gulf States is an extensive audio corpus of sociolinguistic interviews with 1121 speakers from eight southeastern U.S. states. Complete interviews have never been fully transcribed, leaving a wealth of phonetic information unexplored. This paper details methods for large-scale acoustic analysis of this historical speech corpus, providing a fuller picture of Southern speech than offered by previous impressionistic analyses. Interviews from 10 speakers (∼36 h) in southeast Georgia were transcribed and analyzed for dialectal features associated with the Southern Vowel Shift and African American Vowel Shift, also considering the effects of age, gender, and race. Multiple tokens of common words were annotated (N = 6085), and formant values of their stressed vowels were extracted. The effects of shifting on relative vowel placement were evaluated via Pillai scores, and vowel dynamics were estimated via functional data analysis and modeled with linear mixed-effects regression. Results indicate that European American speakers show features of the Southern Vowel Shift, though certain speakers shift in more ways than others, and African American speakers' productions are consistent with the African American Vowel Shift. Wide variation is apparent, even within this small geographic region, contributing evidence of the complexity of Southern speech.

  20. Weaponizing Wireless Networks

    DEFF Research Database (Denmark)

    Giannetsos, Athanasios; Tassos, Dimitriou; Prasad, Neeli R.

    2010-01-01

    of a sensor network. Results show that our tool can be flexibly applied to different sensor network operating systems and protocol stacks giving an adversary privileges to which she is not entitled to. We hope that our tool will be used proactively, to study the weaknesses of new security protocols, and......, hopefully, to enhance the level of security provided by these solutions even further....