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Sample records for market network framework

  1. Network Management Framework for Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Kim, Jaewoo; Jeon, Hahnearl; Lee, Jaiyong

    Network Management is the process of managing, monitoring, and controlling the network. Conventional network management was based on wired network which is heavy and unsuitable for resource constrained WSNs. WSNs can have large scale network and it is impossible to manage each node individually. Also, polling mechanism of Simple Network Management Protocol (SNMP) impose heavy management traffic overhead. Since management messages consume resources of WSNs, it can affect the performance of the network. Therefore, it is necessary for WSNs to perform energy efficient network management. In this paper, we will propose network management framework. We will introduce cluster-based network management architecture, and classify the Management Information Base (MIB) according to their characteristics. Then, we will define management messages and message exchange operation for each kind of MIB. The analysis result of the management overhead indicates that the proposed framework can reduce management traffic compared to polling mechanism.

  2. Probabilistic framework for network partition

    NASA Astrophysics Data System (ADS)

    Li, Tiejun; Liu, Jian; E, Weinan

    2009-08-01

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

  3. Network model of bilateral power markets based on complex networks

    NASA Astrophysics Data System (ADS)

    Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li

    2014-06-01

    The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.

  4. Markets on Networks

    NASA Astrophysics Data System (ADS)

    Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy

    2003-03-01

    The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.

  5. Structurally Dynamic Spin Market Networks

    NASA Astrophysics Data System (ADS)

    Horváth, Denis; Kuscsik, Zoltán

    The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.

  6. An analytical framework for local feedforward networks.

    PubMed

    Weaver, S; Baird, L; Polycarpou, M

    1998-01-01

    Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are referred to as spatially local networks. To obtain a better understanding of these properties, a theoretical framework, consisting of a measure of interference and a measure of network localization, is developed. These measures incorporate not only the network weights and architecture but also the learning algorithm. Using this framework to analyze sigmoidal, multilayer perceptron (MLP) networks that employ the backpropagation learning algorithm on the quadratic cost function, we address a familiar misconception that single-hidden-layer sigmoidal networks are inherently nonlocal by demonstrating that given a sufficiently large number of adjustable weights, single-hidden-layer sigmoidal MLP's exist that are arbitrarily local and retain the ability to approximate any continuous function on a compact domain. PMID:18252471

  7. A new policy framework for health care markets.

    PubMed

    Butler, Stuart M

    2004-01-01

    The frustration with health care markets recorded in the paper by Len Nichols and colleagues reflects the general, and accurate, perception that these markets typically do not work well. But markets respond to the framework of rules and tax incentives in which they must operate, and in health care this framework works against efficiency. The sensible response is not to reject market-based approaches in health care as inherently ineffective in achieving efficiency and cost control. Nor is it to add yet another layer of rules and government micromanagement. It is instead to fix the framework so that markets will foster efficiency. PMID:15046127

  8. [Marketing in veterinary practice; a theoretical framework].

    PubMed

    Schuurmans, A J; Smidts, A

    1990-03-15

    An increase in the number of veterinarians, while at the same time the number of animals has remained constant, has resulted in growing competition. By extending the range of products and by enlarging the veterinarians' scope of activities this competition can be decreased. A marketing-orientation will be helpful in this respect. This article indicates in which way marketing concepts can be used in a veterinary practice. The services of the veterinarian will be looked at by means of the Abell approach. This focuses on the functions performed by the services and examines, per function performed, for whom this might be interesting and which alternatives there might be. Next the concept of market segmentation is filled in for a veterinary practice by means of a hypothetical example. The marketing mix (product, place, price, promotion and personnel) is given considerable attention. The last element of marketing in a veterinary practice that is discussed here is the marketing information system. In a next article the question will be answered how marketing-directed the Dutch veterinarian works nowadays. To find this out research has been done; 166 vets were interviewed by telephone for approximately 40 minutes each. PMID:2321238

  9. A Framework for Curriculum Development in Marketing Education.

    ERIC Educational Resources Information Center

    Everett, Donna R.

    This book is designed to show marketing education teachers how Missouri's Show-Me Knowledge and Performance Standards can be reflected in the Marketing Education Framework. It is organized to present each of the nine competency strands (instructional units) by learner outcome and competencies. The instructional units are as follows: communications…

  10. Study of network resource allocation based on market and game theoretic mechanism

    NASA Astrophysics Data System (ADS)

    Liu, Yingmei; Wang, Hongwei; Wang, Gang

    2004-04-01

    We work on the network resource allocation issue concerning network management system function based on market-oriented mechanism. The scheme is to model the telecommunication network resources as trading goods in which the various network components could be owned by different competitive, real-world entities. This is a multidisciplinary framework concentrating on the similarity between resource allocation in network environment and the market mechanism in economic theory. By taking an economic (market-based and game theoretic) approach in routing of communication network, we study the dynamic behavior under game-theoretic framework in allocating network resources. Based on the prior work of Gibney and Jennings, we apply concepts of utility and fitness to the market mechanism with an intention to close the gap between experiment environment and real world situation.

  11. Framework for Network Co-Simulation

    SciTech Connect

    Daily, Jeff; Ciraci, PNNL Selim; Fuller, PNNL Jason; Marinovici, PNNL Laurentiu; Fisher, PNNL Andrew; Lo, PNNL Chaomei; Hauer, PNNL Matthew

    2014-01-09

    The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations can be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.

  12. Stock market index prediction using neural networks

    NASA Astrophysics Data System (ADS)

    Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

    1994-03-01

    A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

  13. Information transfer network of global market indices

    NASA Astrophysics Data System (ADS)

    Kim, Yup; Kim, Jinho; Yook, Soon-Hyung

    2015-07-01

    We study the topological properties of the information transfer networks (ITN) of the global financial market indices for six different periods. ITN is a directed weighted network, in which the direction and weight are determined by the transfer entropy between market indices. By applying the threshold method, it is found that ITN undergoes a crossover from the complete graph to a small-world (SW) network. SW regime of ITN for a global crisis is found to be much more enhanced than that for ordinary periods. Furthermore, when ITN is in SW regime, the average clustering coefficient is found to be synchronized with average volatility of markets. We also compare the results with the topological properties of correlation networks.

  14. A framework for marketing image management.

    PubMed

    Barich, H; Kotler, P

    1991-01-01

    Managers know that the customer's impression of an organization is important. And sometimes companies attempt to determine just what that impression is. They conduct ad hoc surveys and focus groups. But too often the data is insubstantial, or difficult to analyze, or even inaccurate. Barich and Kotler introduce the concept of "marketing image" and describe a system of image management: designing a study, collecting data, analyzing image problems, modifying the image, and tracking responses to that image. They argue that only a systematic approach will yield useful and accurate information that a company can translate into action. PMID:10111301

  15. Framework for Network Co-Simulation

    Energy Science and Technology Software Center (ESTSC)

    2014-01-09

    The Framework for Network Co-Simulation (FNCS) uses a federated approach to integrate simulations which may have differing time scales. Special consideration is given to integration with a communication network simulation such that inter-simulation messages may be optionally routed through and delayed by such a simulation. In addition, FNCS uses novel time synchronization algorithms to accelerate co-simulation including the application of speculative multithreading. FNCS accomplishes all of these improvements with minimal end user intervention. Simulations canmore » be integrated using FNCS while maintaining their original model input files simply by linking with the FNCS library and making appropriate calls into the FNCS API.« less

  16. Framework for State-Level Renewable Energy Market Potential Studies

    SciTech Connect

    Kreycik, C.; Vimmerstedt, L.; Doris, E.

    2010-01-01

    State-level policymakers are relying on estimates of the market potential for renewable energy resources as they set goals and develop policies to accelerate the development of these resources. Therefore, accuracy of such estimates should be understood and possibly improved to appropriately support these decisions. This document provides a framework and next steps for state officials who require estimates of renewable energy market potential. The report gives insight into how to conduct a market potential study, including what supporting data are needed and what types of assumptions need to be made. The report distinguishes between goal-oriented studies and other types of studies, and explains the benefits of each.

  17. Influence network in the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Gao, Ya-Chun; Zeng, Yong; Cai, Shi-Min

    2015-03-01

    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 the Chinese stock market. This influence network shows distinct topological properties. In particular, a few large companies that can lead the tendency of the 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 the influence network are compared with those according to the assets, which gives inspiration to uncover and understand the importance of listed companies on the stock market. These empirical results are meaningful in providing these topological properties of the Chinese stock market and economic sectors as well as revealing the interactive influence relationships among listed companies.

  18. Market-Based Decision Guidance Framework for Power and Alternative Energy Collaboration

    NASA Astrophysics Data System (ADS)

    Altaleb, Hesham

    With the introduction of power energy markets deregulation, innovations have transformed once a static network into a more flexible grid. Microgrids have also been deployed to serve various purposes (e.g., reliability, sustainability, etc.). With the rapid deployment of smart grid technologies, it has become possible to measure and record both, the quantity and time of the consumption of electrical power. In addition, capabilities for controlling distributed supply and demand have resulted in complex systems where inefficiencies are possible and where improvements can be made. Electric power like other volatile resources cannot be stored efficiently, therefore, managing such resource requires considerable attention. Such complex systems present a need for decisions that can streamline consumption, delay infrastructure investments, and reduce costs. When renewable power resources and the need for limiting harmful emissions are added to the equation, the search space for decisions becomes increasingly complex. As a result, the need for a comprehensive decision guidance system for electrical power resources consumption and productions becomes evident. In this dissertation, I formulate and implement a comprehensive framework that addresses different aspect of the electrical power generation and consumption using optimization models and utilizing collaboration concepts. Our solution presents a two-prong approach: managing interaction in real-time for the short-term immediate consumption of already allocated resources; and managing the operational planning for the long-run consumption. More specifically, in real-time, we present and implement a model of how to organize a secondary market for peak-demand allocation and describe the properties of the market that guarantees efficient execution and a method for the fair distribution of collaboration gains. We also propose and implement a primary market for peak demand bounds determination problem with the assumption that

  19. Model framework for describing the dynamics of evolving networks

    NASA Astrophysics Data System (ADS)

    Tobochnik, Jan; Strandburg, Katherine; Csardi, Gabor; Erdi, Peter

    2007-03-01

    We present a model framework for describing the dynamics of evolving networks. In this framework the addition of edges is stochastically governed by some important intrinsic and structural properties of network vertices through an attractiveness function. We discuss the solution of the inverse problem: determining the attractiveness function from the network evolution data. We also present a number of example applications: the description of the US patent citation network using vertex degree, patent age and patent category variables, and we show how the time-dependent version of the method can be used to find and describe important changes in the internal dynamics. We also compare our results to scientific citation networks.

  20. A distributed framework for inter-domain virtual network embedding

    NASA Astrophysics Data System (ADS)

    Wang, Zihua; Han, Yanni; Lin, Tao; Tang, Hui

    2013-03-01

    Network virtualization has been a promising technology for overcoming the Internet impasse. A main challenge in network virtualization is the efficient assignment of virtual resources. Existing work focused on intra-domain solutions whereas inter-domain situation is more practical in realistic setting. In this paper, we present a distributed inter-domain framework for mapping virtual networks to physical networks which can ameliorate the performance of the virtual network embedding. The distributed framework is based on a Multi-agent approach. A set of messages for information exchange is defined. We design different operations and IPTV use scenarios to validate the advantages of our framework. Use cases shows that our framework can solve the inter-domain problem efficiently.

  1. Topological structures in the equities market network

    PubMed Central

    Leibon, Gregory; Pauls, Scott; Rockmore, Daniel; Savell, Robert

    2008-01-01

    We present a new method for articulating scale-dependent topological descriptions of the network structure inherent in many complex systems. The technique is based on “partition decoupled null models,” a new class of null models that incorporate the interaction of clustered partitions into a random model and generalize the Gaussian ensemble. As an application, we analyze a correlation matrix derived from 4 years of close prices of equities in the New York Stock Exchange (NYSE) and National Association of Securities Dealers Automated Quotation (NASDAQ). In this example, we expose (i) a natural structure composed of 2 interacting partitions of the market that both agrees with and generalizes standard notions of scale (e.g., sector and industry) and (ii) structure in the first partition that is a topological manifestation of a well-known pattern of capital flow called “sector rotation.” Our approach gives rise to a natural form of multiresolution analysis of the underlying time series that naturally decomposes the basic data in terms of the effects of the different scales at which it clusters. We support our conclusions and show the robustness of the technique with a successful analysis on a simulated network with an embedded topological structure. The equities market is a prototypical complex system, and we expect that our approach will be of use in understanding a broad class of complex systems in which correlation structures are resident.

  2. Instantiating a Global Network Measurement Framework

    SciTech Connect

    Tierney, Brian L.; Boote, Jeff; Boyd, Eric; Brown, Aaron; Grigoriev, Maxim; Metzger, Joe; Swany, Martin; Zekauskas, Matt; Zurawski, Jason

    2008-12-15

    perfSONAR is a web services-based infrastructure for collecting and publishing network performance monitoring. A primary goal of perfSONAR is making it easier to solve end-to-end performance problems on paths crossing several networks. It contains a set of services delivering performance measurements in a federated environment. These services act as an intermediate layer, between the performance measurement tools and the diagnostic or visualization applications. This layer is aimed at making and exchanging performance measurements across multiple networks and multiple user communities, using well-defined protocols. This paper summarizes the key perfSONAR components, and describes how they are deployed by the US-LHC community to monitor the networks distributing LHC data from CERN. All monitoring data described herein is publicly available, and we hope the availability of this data via a standard schema will inspire others to contribute to the effort by building network data analysis applications that use perfSONAR.

  3. Multitype Library Networking: A Framework for Decision-Making.

    ERIC Educational Resources Information Center

    Griffiths, Jose-Marie; King, Donald W.

    1984-01-01

    Describes framework for library networking which consists of six interdependent dimensions to be used for decision making by libraries: functions to be performed, type of access information, types of materials, products and services, networking configurations, and communications means. Use of a series of cost models describing activities within…

  4. An Organizational Framework of Personal Health Records for Social Networks

    ERIC Educational Resources Information Center

    Hasan, Syed Omair

    2009-01-01

    This work proposes an organizational framework for creating a community to share personal health record (PHR) information in the form of a Health Records Social Network (HRSN). The work builds upon existing social network community concepts as well as the existing Systemized Nomenclature of Medicine (SNOMED) model used by the medical community and…

  5. Adding network approaches to a neurobiological framework of resilience.

    PubMed

    Levit-Binnun, Nava; Golland, Yulia

    2015-01-01

    In their paper, Kalisch et al. make an important attempt to create a unifying theoretical framework for the neuroscientific study of general resilience mechanisms. We suggest that such attempts can benefit tremendously by incorporating the recently emerging network approaches that enable the characterization of complex brain network architecture and dynamics, in both health and disease. PMID:26786965

  6. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

    PubMed Central

    2011-01-01

    Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis. PMID:22784571

  7. Network application and framework for quality of information processing

    NASA Astrophysics Data System (ADS)

    Marcus, Kelvin; Cook, Trevor; Scott, Lisa; Toth, Andrew

    2012-06-01

    To improve the effectiveness of network-centric decision making, we present a distributed network application and framework that provides users with actionable intelligence reports to support counter insurgency operations. ARL's Quality of Information (QoI) Intelligence Report Application uses QoI metrics like timeliness, accuracy, and precision combined with associated network performance data, such as throughput and latency, and mission-specific information requirements to deliver high quality data to users; that is data delivered in a manner which best supports the ability to make more informed decisions as it relates to the current mission. This application serves as a testing platform for integrated experimentation and validation of QoI processing techniques and methodologies. In this paper, we present the software-system framework and architecture, and show an example scenario that highlights how the framework aids in network integration and enables better data-to-decision.

  8. On effectiveness of network sensor-based defense framework

    NASA Astrophysics Data System (ADS)

    Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh

    2012-06-01

    Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

  9. Simulating market dynamics: interactions between consumer psychology and social networks.

    PubMed

    Janssen, Marco A; Jager, Wander

    2003-01-01

    Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network). PMID:14761255

  10. Towards A Network-of-Networks Framework for Cyber Security

    SciTech Connect

    Halappanavar, Mahantesh; Choudhury, Sutanay; Hogan, Emilie A.; Hui, Peter SY; Johnson, John R.; Ray, Indrajit; Holder, Lawrence B.

    2013-06-07

    Networks-of-networks (NoN) is a graph-theoretic model of interdependent networks that have distinct dynamics at each network (layer). By adding special edges to represent relationships between nodes in different layers, NoN provides a unified mechanism to study interdependent systems intertwined in a complex relationship. While NoN based models have been proposed for cyber-physical systems, in this paper we build towards a three-layer NoN model for an enterprise cyber system. Each layer captures a different facet of a cyber system. We then discuss the potential benefits of graph-theoretic analysis enabled from such a model. Our goal is to provide a novel and powerful tool for modeling and analyzing problems in cyber security.

  11. Cyber Security Research Frameworks For Coevolutionary Network Defense

    SciTech Connect

    Rush, George D.; Tauritz, Daniel Remy

    2015-12-03

    Several architectures have been created for developing and testing systems used in network security, but most are meant to provide a platform for running cyber security experiments as opposed to automating experiment processes. In the first paper, we propose a framework termed Distributed Cyber Security Automation Framework for Experiments (DCAFE) that enables experiment automation and control in a distributed environment. Predictive analysis of adversaries is another thorny issue in cyber security. Game theory can be used to mathematically analyze adversary models, but its scalability limitations restrict its use. Computational game theory allows us to scale classical game theory to larger, more complex systems. In the second paper, we propose a framework termed Coevolutionary Agent-based Network Defense Lightweight Event System (CANDLES) that can coevolve attacker and defender agent strategies and capabilities and evaluate potential solutions with a custom network defense simulation. The third paper is a continuation of the CANDLES project in which we rewrote key parts of the framework. Attackers and defenders have been redesigned to evolve pure strategy, and a new network security simulation is devised which specifies network architecture and adds a temporal aspect. We also add a hill climber algorithm to evaluate the search space and justify the use of a coevolutionary algorithm.

  12. Artificial Market Simulation with Embedded Complex Network Structures

    NASA Astrophysics Data System (ADS)

    Uchida, Makoto; Shirayama, Susumu

    We investigate a factor of the `network effect' that affects on communication service markets by a multi-agent based simulation approach. The network effect is one of a market characteristic, whereby the benefit of a service or a product increase with use. So far, the network effect has been studied in terms of macroscopic metrics, and interaction patterns of consumers in the market were often ignored. To investigate an infulence of structures of the interaction patterns, we propose a multi-agent based model for a communication serivce market, in which embedded complex network structures are considered as an interaction pattern of agents. Using several complex network models as the interaction patterns, we study the dynamics of a market in which two providers are competing. By a series of simulations, we show that the structural properties of the complex networks, such as the clustering coefficient and degree correlations, are the major factors of the network effect. We also discuss an adequate model of the interaction pattern for reproducing the market dynamics in the real world by performing simulations exploiting with a real data of social network.

  13. Influence of a network structure on the network effect in the communication service market

    NASA Astrophysics Data System (ADS)

    Uchida, Makoto; Shirayama, Susumu

    2008-09-01

    In this study, we analyze the network effect in a model of a personal communication market, by using a multi-agent based simulation approach. We introduce into the simulation model complex network structures as the interaction patterns of agents. With complex network models, we investigate the dynamics of a market in which two providers are competing. We also examine the structure of networks that affect the complex behavior of the market. By a series of simulations, we show that the structural properties of complex networks, such as the clustering coefficient and degree correlation, have a major influence on the dynamics of the market. We find that the network effect is increased if the interaction pattern of agents is characterized by a high clustering coefficient, or a positive degree correlation. We also discuss a suitable model of the interaction pattern for reproducing market dynamics in the real world, by performing simulations using real data of a social network.

  14. Online Monitor Framework for Network Distributed Data Acquisition Systems

    NASA Astrophysics Data System (ADS)

    Konno, Tomoyuki; Cabrera, Anatael; Ishitsuka, Masaki; Kuze, Masahiro; Sakamoto, Yasunobu; the Double Chooz Collaboration

    Data acquisition (DAQ) systems for recent high energy physics experiments consist of lots of subsystems distributed in the local area network. Therefore, scalability for the number of connections from subsystems and availability of access via the Internet are required. "Online monitor framework" is a general software framework for online data monitoring, which provides a way to collect monitoring information distributed in the network and pass them though the firewalls. The framework consists of two subsystems; "Monitor Sever" and "Monitor Viewer". Monitor Server is a core system of the framework. The server collects monitoring information from the DAQ subsystems to provide them to Monitor Viewer. Monitor Viewer is a graphical user interface of the monitor framework, which displays plots in itself. We adapted two types of technologies; Java and HTML5 with Google Web Toolkit, which are independent of operating systems or plugin-libraries like ROOT and contain some functionalities of communicating via the Internet and drawing graphics. The monitoring framework was developed for the Double Chooz reactor neutrino oscillation experiment but is general enough for other experiments. This document reports the structure of the online monitor framework with some examples from the adaption to the Double Chooz experiment.

  15. Communication and marketing as tools to cultivate the public's health: a proposed "people and places" framework

    PubMed Central

    Maibach, Edward W; Abroms, Lorien C; Marosits, Mark

    2007-01-01

    Background Communication and marketing are rapidly becoming recognized as core functions, or core competencies, in the field of public health. Although these disciplines have fostered considerable academic inquiry, a coherent sense of precisely how these disciplines can inform the practice of public health has been slower to emerge. Discussion In this article we propose a framework – based on contemporary ecological models of health – to explain how communication and marketing can be used to advance public health objectives. The framework identifies the attributes of people (as individuals, as social networks, and as communities or populations) and places that influence health behaviors and health. Communication, i.e., the provision of information, can be used in a variety of ways to foster beneficial change among both people (e.g., activating social support for smoking cessation among peers) and places (e.g., convincing city officials to ban smoking in public venues). Similarly, marketing, i.e., the development, distribution and promotion of products and services, can be used to foster beneficial change among both people (e.g., by making nicotine replacement therapy more accessible and affordable) and places (e.g., by providing city officials with model anti-tobacco legislation that can be adapted for use in their jurisdiction). Summary Public health agencies that use their communication and marketing resources effectively to support people in making healthful decisions and to foster health-promoting environments have considerable opportunity to advance the public's health, even within the constraints of their current resource base. PMID:17519027

  16. A Framework for Dimensioning VDL-2 Air-Ground Networks

    NASA Technical Reports Server (NTRS)

    Ribeiro, Leila Z.; Monticone, Leone C.; Snow, Richard E.; Box, Frank; Apaza, Rafel; Bretmersky, Steven

    2014-01-01

    This paper describes a framework developed at MITRE for dimensioning a Very High Frequency (VHF) Digital Link Mode 2 (VDL-2) Air-to-Ground network. This framework was developed to support the FAA's Data Communications (Data Comm) program by providing estimates of expected capacity required for the air-ground network services that will support Controller-Pilot-Data-Link Communications (CPDLC), as well as the spectrum needed to operate the system at required levels of performance. The Data Comm program is part of the FAA's NextGen initiative to implement advanced communication capabilities in the National Airspace System (NAS). The first component of the framework is the radio-frequency (RF) coverage design for the network ground stations. Then we proceed to describe the approach used to assess the aircraft geographical distribution and the data traffic demand expected in the network. The next step is the resource allocation utilizing optimization algorithms developed in MITRE's Spectrum ProspectorTM tool to propose frequency assignment solutions, and a NASA-developed VDL-2 tool to perform simulations and determine whether a proposed plan meets the desired performance requirements. The framework presented is capable of providing quantitative estimates of multiple variables related to the air-ground network, in order to satisfy established coverage, capacity and latency performance requirements. Outputs include: coverage provided at different altitudes; data capacity required in the network, aggregated or on a per ground station basis; spectrum (pool of frequencies) needed for the system to meet a target performance; optimized frequency plan for a given scenario; expected performance given spectrum available; and, estimates of throughput distributions for a given scenario. We conclude with a discussion aimed at providing insight into the tradeoffs and challenges identified with respect to radio resource management for VDL-2 air-ground networks.

  17. A local area computer network expert system framework

    NASA Technical Reports Server (NTRS)

    Dominy, Robert

    1987-01-01

    Over the past years an expert system called LANES designed to detect and isolate faults in the Goddard-wide Hybrid Local Area Computer Network (LACN) was developed. As a result, the need for developing a more generic LACN fault isolation expert system has become apparent. An object oriented approach was explored to create a set of generic classes, objects, rules, and methods that would be necessary to meet this need. The object classes provide a convenient mechanism for separating high level information from low level network specific information. This approach yeilds a framework which can be applied to different network configurations and be easily expanded to meet new needs.

  18. Elastic Optical Path Network Architecture: Framework for Spectrally-Efficient and Scalable Future Optical Networks

    NASA Astrophysics Data System (ADS)

    Jinno, Masahiko; Takara, Hidehiko; Sone, Yoshiaki; Yonenaga, Kazushige; Hirano, Akira

    This paper presents an elastic optical path network architecture as a novel networking framework to address the looming capacity crunch problem in internet protocol (IP) and optical networks. The basic idea is to introduce elasticity and adaptation into the optical domain to yield spectrally-efficient optical path accommodation, heightened network scalability through IP traffic offloading to the elastic optical layer, and enhanced survivability for serious disasters.

  19. Mathematical Frameworks for Oscillatory Network Dynamics in Neuroscience.

    PubMed

    Ashwin, Peter; Coombes, Stephen; Nicks, Rachel

    2016-12-01

    The tools of weakly coupled phase oscillator theory have had a profound impact on the neuroscience community, providing insight into a variety of network behaviours ranging from central pattern generation to synchronisation, as well as predicting novel network states such as chimeras. However, there are many instances where this theory is expected to break down, say in the presence of strong coupling, or must be carefully interpreted, as in the presence of stochastic forcing. There are also surprises in the dynamical complexity of the attractors that can robustly appear-for example, heteroclinic network attractors. In this review we present a set of mathematical tools that are suitable for addressing the dynamics of oscillatory neural networks, broadening from a standard phase oscillator perspective to provide a practical framework for further successful applications of mathematics to understanding network dynamics in neuroscience. PMID:26739133

  20. Practical use of a framework for network science experimentation

    NASA Astrophysics Data System (ADS)

    Toth, Andrew; Bergamaschi, Flavio

    2014-06-01

    In 2006, the US Army Research Laboratory (ARL) and the UK Ministry of Defence (MoD) established a collaborative research alliance with academia and industry, called the International Technology Alliance (ITA)1 In Network and Information Sciences, to address fundamental issues concerning Network and Information Sciences that will enhance decision making for coalition operations and enable rapid, secure formation of ad hoc teams in coalition environments and enhance US and UK capabilities to conduct coalition warfare. Research conducted under the ITA was extended through collaboration between ARL and IBM UK to characterize and dene a software stack and tooling that has become the reference framework for network science experimentation in support for validation of theoretical research. This paper discusses the composition of the reference framework for experimentation resulting from the ARL/IBM UK collaboration and its use, by the Network Science Collaborative Technology Alliance (NS CTA)2 , in a recent network science experiment conducted at ARL. It also discusses how the experiment was modeled using the reference framework, the integration of two new components, the Apollo Fact-Finder3 tool and the Medusa Crowd Sensing4 application, the limitations identified and how they shall be addressed in future work.

  1. Granger causality stock market networks: Temporal proximity and preferential attachment

    NASA Astrophysics Data System (ADS)

    Výrost, Tomáš; Lyócsa, Štefan; Baumöhl, Eduard

    2015-06-01

    The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings. First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the role of the temporal proximity between market closing times for return spillovers, i.e. the time distance between national stock markets matters. Third, a preferential attachment between stock markets exists, i.e. the probability of the presence of spillover effects between any given two markets increases with their degree of connectedness to others.

  2. Weighted Networks at the Polish Market

    NASA Astrophysics Data System (ADS)

    Chmiel, A. M.; Sienkiewicz, J.; Suchecki, K.; Hołyst, J. A.

    During the last few years various models of networks [1,2] have become a powerful tool for analysis of complex systems in such distant fields as Internet [3], biology [4], social groups [5], ecology [6] and public transport [7]. Modeling behavior of economical agents is a challenging issue that has also been studied from a network point of view. The examples of such studies are models of financial networks [8], supply chains [9, 10], production networks [11], investment networks [12] or collective bank bankrupcies [13, 14]. Relations between different companies have been already analyzed using several methods: as networks of shareholders [15], networks of correlations between stock prices [16] or networks of board directors [17]. In several cases scaling laws for network characteristics have been observed.

  3. Cointegration-based financial networks study in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Tu, Chengyi

    2014-05-01

    We propose a method based on cointegration instead of correlation to construct financial complex network in Chinese stock market. The network is obtained starting from the matrix of p-value calculated by Engle-Granger cointegration test between all pairs of stocks. Then some tools for filtering information in complex network are implemented to prune the complete graph described by the above matrix, such as setting a level of statistical significance as a threshold and Planar Maximally Filtered Graph. We also calculate Partial Correlation Planar Graph of these stocks to compare the above networks. Last, we analyze these directed, weighted and non-symmetric networks by using standard methods of network analysis, including degree centrality, PageRank, HITS, local clustering coefficient, K-shell and strongly and weakly connected components. The results shed a new light on the underlying mechanisms and driving forces in a financial market and deepen our understanding of financial complex network.

  4. Novel indexes based on network structure to indicate financial market

    NASA Astrophysics Data System (ADS)

    Zhong, Tao; Peng, Qinke; Wang, Xiao; Zhang, Jing

    2016-02-01

    There have been various achievements to understand and to analyze the financial market by complex network model. However, current studies analyze the financial network model but seldom present quantified indexes to indicate or forecast the price action of market. In this paper, the stock market is modeled as a dynamic network, in which the vertices refer to listed companies and edges refer to their rank-based correlation based on price series. Characteristics of the network are analyzed and then novel indexes are introduced into market analysis, which are calculated from maximum and fully-connected subnets. The indexes are compared with existing ones and the results confirm that our indexes perform better to indicate the daily trend of market composite index in advance. Via investment simulation, the performance of our indexes is analyzed in detail. The results indicate that the dynamic complex network model could not only serve as a structural description of the financial market, but also work to predict the market and guide investment by indexes.

  5. Conceptual Framework for Developing a Diabetes Information Network

    PubMed Central

    Riazi, Hossein; Langarizadeh, Mostafa; Larijani, Bagher; Shahmoradi, Leila

    2016-01-01

    Objective: To provide a conceptual framework for managing diabetic patient care, and creating an information network for clinical research. Background: A wide range of information technology (IT) based interventions such as distance learning, diabetes registries, personal or electronic health record systems, clinical information systems, and clinical decision support systems have so far been used in supporting diabetic care. Previous studies demonstrated that IT could improve diabetes care at its different aspects. There is however no comprehensive conceptual framework that defines how different IT applications can support diverse aspects of this care. Therefore, a conceptual framework that combines different IT solutions into a wide information network for improving care processes and for research purposes is widely lacking. In this study we describe the theoretical underpin of a big project aiming at building a wide diabetic information network namely DIANET. Research design and methods: A literature review and a survey of national programs and existing regulations for diabetes management was conducted in order to define different aspects of diabetic care that should be supported by IT solutions. Both qualitative and quantitative research methods were used in this study. In addition to the results of a previous systematic literature review, two brainstorming and three expert panel sessions were conducted to identify requirements of a comprehensive information technology solution. Based on these inputs, the requirements for creating a diabetes information network were identified and used to create a questionnaire based on 9-point Likert scale. The questionnaire was finalized after removing some items based on calculated content validity ratio and content validity index coefficients. Cronbach’s alpha reliability coefficient was also calculated (αTotal= 0.98, P<0.05, CI=0.95). The final questionnaire was containing 45 items. It was sent to 13 clinicians at two

  6. A Newtonian framework for community detection in undirected biological networks.

    PubMed

    Narayanan, Tejaswini; Subramaniam, Shankar

    2014-02-01

    Community detection is a key problem of interest in network analysis, with applications in a variety of domains such as biological networks, social network modeling, and communication pattern analysis. In this paper, we present a novel framework for community detection that is motivated by a physical system analogy. We model a network as a system of point masses, and drive the process of community detection, by leveraging the Newtonian interactions between the point masses. Our framework is designed to be generic and extensible relative to the model parameters that are most suited for the problem domain. We illustrate the applicability of our approach by applying the Newtonian Community Detection algorithm on protein-protein interaction networks of E. coli , C. elegans, and S. cerevisiae. We obtain results that are comparable in quality to those obtained from the Newman-Girvan algorithm, a widely employed divisive algorithm for community detection. We also present a detailed analysis of the structural properties of the communities produced by our proposed algorithm, together with a biological interpretation using E. coli protein network as a case study. A functional enrichment heat map is constructed with the Gene Ontology functional mapping, in addition to a pathway analysis for each community. The analysis illustrates that the proposed algorithm elicits communities that are not only meaningful from a topological standpoint, but also possess biological relevance. We believe that our algorithm has the potential to serve as a key computational tool for driving therapeutic applications involving targeted drug development for personalized care delivery. PMID:24681920

  7. A framework for analyzing the impact of data integrity/quality on electricity market operations

    NASA Astrophysics Data System (ADS)

    Choi, Dae Hyun

    a circuit breaker) do network topology estimate, thus leading to the distortion of LMP. We present an analytical framework to quantify real-time LMP sensitivity subject to continuous and discrete data corruption via state estimation. The proposed framework offers system operators an analytical tool to identify economically sensitive buses and transmission lines to data corruption as well as find sensors that impact LMP changes significantly. This dissertation serves as a first step towards rigorous understanding of the fundamental coupling among cyber, physical and economical layers of operations in future smart grid.

  8. A Novel Framework to Maximum Lifetime for Wireless Sensor Network

    NASA Astrophysics Data System (ADS)

    Sheng, Feng; Xiao-Gang, Qi; Ji-Long, Xue

    In this paper, a novel framework is presented to prolong the lifetime of wireless sensor networks to the maximum. This framework consists of two parts. One is a novel topology management mechanism called electric fan topology mechanism (EFTM) and the other is an efficient routing protocol called maximum lifetime routing (MLR). EFTM provides a scheduler strategy to save much energy by turning off some transceivers periodically. MLR is based on the work of EFTM, which selects nodes with high-energy reserves as router. Though we turn off some transceivers periodically, we have developed receiver-based packet routing policy and last-mile algorithm to accommodate rapid change of topology and to guarantee the robust of networks. Simulation results show that MLR based on the work of EFTM extends the lifetime of networks to the maximum. MLR is suitable for large scale non-real time wireless sensor applications. When all trajectories are unavailable, nodes can still send packets to sink efficiently. The network using MLR can adapt to the rapid change of network topology very well.

  9. An integrated text mining framework for metabolic interaction network reconstruction.

    PubMed

    Patumcharoenpol, Preecha; Doungpan, Narumol; Meechai, Asawin; Shen, Bairong; Chan, Jonathan H; Vongsangnak, Wanwipa

    2016-01-01

    Text mining (TM) in the field of biology is fast becoming a routine analysis for the extraction and curation of biological entities (e.g., genes, proteins, simple chemicals) as well as their relationships. Due to the wide applicability of TM in situations involving complex relationships, it is valuable to apply TM to the extraction of metabolic interactions (i.e., enzyme and metabolite interactions) through metabolic events. Here we present an integrated TM framework containing two modules for the extraction of metabolic events (Metabolic Event Extraction module-MEE) and for the construction of a metabolic interaction network (Metabolic Interaction Network Reconstruction module-MINR). The proposed integrated TM framework performed well based on standard measures of recall, precision and F-score. Evaluation of the MEE module using the constructed Metabolic Entities (ME) corpus yielded F-scores of 59.15% and 48.59% for the detection of metabolic events for production and consumption, respectively. As for the testing of the entity tagger for Gene and Protein (GP) and metabolite with the test corpus, the obtained F-score was greater than 80% for the Superpathway of leucine, valine, and isoleucine biosynthesis. Mapping of enzyme and metabolite interactions through network reconstruction showed a fair performance for the MINR module on the test corpus with F-score >70%. Finally, an application of our integrated TM framework on a big-scale data (i.e., EcoCyc extraction data) for reconstructing a metabolic interaction network showed reasonable precisions at 69.93%, 70.63% and 46.71% for enzyme, metabolite and enzyme-metabolite interaction, respectively. This study presents the first open-source integrated TM framework for reconstructing a metabolic interaction network. This framework can be a powerful tool that helps biologists to extract metabolic events for further reconstruction of a metabolic interaction network. The ME corpus, test corpus, source code, and virtual

  10. An integrated text mining framework for metabolic interaction network reconstruction

    PubMed Central

    Doungpan, Narumol; Meechai, Asawin; Shen, Bairong

    2016-01-01

    Text mining (TM) in the field of biology is fast becoming a routine analysis for the extraction and curation of biological entities (e.g., genes, proteins, simple chemicals) as well as their relationships. Due to the wide applicability of TM in situations involving complex relationships, it is valuable to apply TM to the extraction of metabolic interactions (i.e., enzyme and metabolite interactions) through metabolic events. Here we present an integrated TM framework containing two modules for the extraction of metabolic events (Metabolic Event Extraction module—MEE) and for the construction of a metabolic interaction network (Metabolic Interaction Network Reconstruction module—MINR). The proposed integrated TM framework performed well based on standard measures of recall, precision and F-score. Evaluation of the MEE module using the constructed Metabolic Entities (ME) corpus yielded F-scores of 59.15% and 48.59% for the detection of metabolic events for production and consumption, respectively. As for the testing of the entity tagger for Gene and Protein (GP) and metabolite with the test corpus, the obtained F-score was greater than 80% for the Superpathway of leucine, valine, and isoleucine biosynthesis. Mapping of enzyme and metabolite interactions through network reconstruction showed a fair performance for the MINR module on the test corpus with F-score >70%. Finally, an application of our integrated TM framework on a big-scale data (i.e., EcoCyc extraction data) for reconstructing a metabolic interaction network showed reasonable precisions at 69.93%, 70.63% and 46.71% for enzyme, metabolite and enzyme–metabolite interaction, respectively. This study presents the first open-source integrated TM framework for reconstructing a metabolic interaction network. This framework can be a powerful tool that helps biologists to extract metabolic events for further reconstruction of a metabolic interaction network. The ME corpus, test corpus, source code, and

  11. Introducing FNCS: Framework for Network Co-Simulation

    SciTech Connect

    2014-10-23

    This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

  12. U.S. stock market interaction network as learned by the Boltzmann machine

    NASA Astrophysics Data System (ADS)

    Borysov, Stanislav S.; Roudi, Yasser; Balatsky, Alexander V.

    2015-12-01

    We study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented results show that binarization preserves the correlation structure of the market. Properties of distributions of external fields and couplings as well as the market interaction network and industry sector clustering structure are studied for different historical dates and moving window sizes. We demonstrate that the observed positive heavy tail in distribution of couplings is related to the sparse clustering structure of the market. We also show that discrepancies between the model's parameters might be used as a precursor of financial instabilities.

  13. U.S. stock market interaction network as learned by the Boltzmann machine

    SciTech Connect

    Borysov, Stanislav S.; Roudi, Yasser; Balatsky, Alexander V.

    2015-12-07

    Here, we study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented results show that binarization preserves the correlation structure of the market. Properties of distributions of external fields and couplings as well as the market interaction network and industry sector clustering structure are studied for different historical dates and moving window sizes. We demonstrate that the observed positive heavy tail in distribution of couplings is related to the sparse clustering structure of the market. We also show that discrepancies between the model’s parameters might be used as a precursor of financial instabilities.

  14. E-Services quality assessment framework for collaborative networks

    NASA Astrophysics Data System (ADS)

    Stegaru, Georgiana; Danila, Cristian; Sacala, Ioan Stefan; Moisescu, Mihnea; Mihai Stanescu, Aurelian

    2015-08-01

    In a globalised networked economy, collaborative networks (CNs) are formed to take advantage of new business opportunities. Collaboration involves shared resources and capabilities, such as e-Services that can be dynamically composed to automate CN participants' business processes. Quality is essential for the success of business process automation. Current approaches mostly focus on quality of service (QoS)-based service selection and ranking algorithms, overlooking the process of service composition which requires interoperable, adaptable and secure e-Services to ensure seamless collaboration, data confidentiality and integrity. Lack of assessment of these quality attributes can result in e-Service composition failure. The quality of e-Service composition relies on the quality of each e-Service and on the quality of the composition process. Therefore, there is the need for a framework that addresses quality from both views: product and process. We propose a quality of e-Service composition (QoESC) framework for quality assessment of e-Service composition for CNs which comprises of a quality model for e-Service evaluation and guidelines for quality of e-Service composition process. We implemented a prototype considering a simplified telemedicine use case which involves a CN in e-Healthcare domain. To validate the proposed quality-driven framework, we analysed service composition reliability with and without using the proposed framework.

  15. STOCK Market Differences in Correlation-Based Weighted Network

    NASA Astrophysics Data System (ADS)

    Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

    We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

  16. Networks in financial markets based on the mutual information rate

    NASA Astrophysics Data System (ADS)

    Fiedor, Paweł

    2014-05-01

    In the last few years there have been many efforts in econophysics studying how network theory can facilitate understanding of complex financial markets. These efforts consist mainly of the study of correlation-based hierarchical networks. This is somewhat surprising as the underlying assumptions of research looking at financial markets are that they are complex systems and thus behave in a nonlinear manner, which is confirmed by numerous studies, making the use of correlations which are inherently dealing with linear dependencies only baffling. In this paper we introduce a way to incorporate nonlinear dynamics and dependencies into hierarchical networks to study financial markets using mutual information and its dynamical extension: the mutual information rate. We show that this approach leads to different results than the correlation-based approach used in most studies, on the basis of 91 companies listed on the New York Stock Exchange 100 between 2003 and 2013, using minimal spanning trees and planar maximally filtered graphs.

  17. The structure and resilience of financial market networks.

    PubMed

    Peron, Thomas Kaue Dal'Maso; Costa, Luciano da Fontoura; Rodrigues, Francisco A

    2012-03-01

    Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. PMID:22462993

  18. The structure and resilience of financial market networks

    NASA Astrophysics Data System (ADS)

    Kauê Dal'Maso Peron, Thomas; da Fontoura Costa, Luciano; Rodrigues, Francisco A.

    2012-03-01

    Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.

  19. An autocatalytic network model for stock markets

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2015-02-01

    The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.

  20. Analytical framework for recurrence network analysis of time series

    NASA Astrophysics Data System (ADS)

    Donges, Jonathan F.; Heitzig, Jobst; Donner, Reik V.; Kurths, Jürgen

    2012-04-01

    Recurrence networks are a powerful nonlinear tool for time series analysis of complex dynamical systems. While there are already many successful applications ranging from medicine to paleoclimatology, a solid theoretical foundation of the method has still been missing so far. Here, we interpret an ɛ-recurrence network as a discrete subnetwork of a “continuous” graph with uncountably many vertices and edges corresponding to the system's attractor. This step allows us to show that various statistical measures commonly used in complex network analysis can be seen as discrete estimators of newly defined continuous measures of certain complex geometric properties of the attractor on the scale given by ɛ. In particular, we introduce local measures such as the ɛ-clustering coefficient, mesoscopic measures such as ɛ-motif density, path-based measures such as ɛ-betweennesses, and global measures such as ɛ-efficiency. This new analytical basis for the so far heuristically motivated network measures also provides an objective criterion for the choice of ɛ via a percolation threshold, and it shows that estimation can be improved by so-called node splitting invariant versions of the measures. We finally illustrate the framework for a number of archetypical chaotic attractors such as those of the Bernoulli and logistic maps, periodic and two-dimensional quasiperiodic motions, and for hyperballs and hypercubes by deriving analytical expressions for the novel measures and comparing them with data from numerical experiments. More generally, the theoretical framework put forward in this work describes random geometric graphs and other networks with spatial constraints, which appear frequently in disciplines ranging from biology to climate science.

  1. Knowledge Discovery Using Bayesian Network Framework for Intelligent Telecommunication Network Management

    NASA Astrophysics Data System (ADS)

    Bashar, Abul; Parr, Gerard; McClean, Sally; Scotney, Bryan; Nauck, Detlef

    The ever-evolving nature of telecommunication networks has put enormous pressure on contemporary Network Management Systems (NMSs) to come up with improved functionalities for efficient monitoring, control and management. In such a context, the rapid deployments of Next Generation Networks (NGN) and their management requires intelligent, autonomic and resilient mechanisms to guarantee Quality of Service (QoS) to the end users and at the same time to maximize revenue for the service/network providers. We present a framework for evaluating a Bayesian Networks (BN) based Decision Support System (DSS) for assisting and improving the performance of a Simple Network Management Protocol (SNMP) based NMS. More specifically, we describe our methodology through a case study which implements the function of Call Admission Control (CAC) in a multi-class video conferencing service scenario. Simulation results are presented for a proof of concept, followed by a critical analysis of our proposed approach and its application.

  2. An improved unified network protocol framework for large-scale wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Ding, Jin; Sivalingam, Krishna M.

    2004-08-01

    Rapid technological advances in wireless communication have made it possible for networking sensor devices. Given the low computation and battery power capacities of these sensor nodes, the key design factors of network protocols are self-configuring, energy-efficient, adaptive, and scalable. We presented the multi-hop infrastructure network architecture (MINA) for a wireless sensor network consisting of a few hundred sensors that communicate data to a base station (BS). We designed a Unified Network Protocol Framework for MINA that encompasses network organization, medium access control (MAC) and routing protocols. In this paper, we improve it by adaptively varying transmission range to maintain network connectivity. It is a derivative-free optimization algorithm. The BS periodically evaluates the objective function, chooses the appropriate transmission range and broadcasts it to the sensor nodes that then update the transmission range. The advantages are: (i) Avoids the disconnectivity; (ii) Maximizes the number of nodes that can be connected to the BS, (iii) Minimizes the energyxdelay metric and (iv) Avoids the "hot-spot" nodes in the network. The performance in terms of delay, throughput, energy consumption and network lifetimes, is studied in detail using discrete-event simulation compared with other protocol. The results show that it is energy efficient in a large scale network.

  3. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  4. Topological Isomorphisms of Human Brain and Financial Market Networks

    PubMed Central

    Vértes, Petra E.; Nicol, Ruth M.; Chapman, Sandra C.; Watkins, Nicholas W.; Robertson, Duncan A.; Bullmore, Edward T.

    2011-01-01

    Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets – the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular – more highly optimized for information processing – than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph-theoretically mediated interface between systems neuroscience and the statistical physics of financial markets. PMID:22007161

  5. A framework for integration of heterogeneous medical imaging networks.

    PubMed

    Viana-Ferreira, Carlos; Ribeiro, Luís S; Costa, Carlos

    2014-01-01

    Medical imaging is increasing its importance in matters of medical diagnosis and in treatment support. Much is due to computers that have revolutionized medical imaging not only in acquisition process but also in the way it is visualized, stored, exchanged and managed. Picture Archiving and Communication Systems (PACS) is an example of how medical imaging takes advantage of computers. To solve problems of interoperability of PACS and medical imaging equipment, the Digital Imaging and Communications in Medicine (DICOM) standard was defined and widely implemented in current solutions. More recently, the need to exchange medical data between distinct institutions resulted in Integrating the Healthcare Enterprise (IHE) initiative that contains a content profile especially conceived for medical imaging exchange: Cross Enterprise Document Sharing for imaging (XDS-i). Moreover, due to application requirements, many solutions developed private networks to support their services. For instance, some applications support enhanced query and retrieve over DICOM objects metadata. This paper proposes anintegration framework to medical imaging networks that provides protocols interoperability and data federation services. It is an extensible plugin system that supports standard approaches (DICOM and XDS-I), but is also capable of supporting private protocols. The framework is being used in the Dicoogle Open Source PACS. PMID:25279021

  6. A Framework for Integration of Heterogeneous Medical Imaging Networks

    PubMed Central

    Viana-Ferreira, Carlos; Ribeiro, Luís S; Costa, Carlos

    2014-01-01

    Medical imaging is increasing its importance in matters of medical diagnosis and in treatment support. Much is due to computers that have revolutionized medical imaging not only in acquisition process but also in the way it is visualized, stored, exchanged and managed. Picture Archiving and Communication Systems (PACS) is an example of how medical imaging takes advantage of computers. To solve problems of interoperability of PACS and medical imaging equipment, the Digital Imaging and Communications in Medicine (DICOM) standard was defined and widely implemented in current solutions. More recently, the need to exchange medical data between distinct institutions resulted in Integrating the Healthcare Enterprise (IHE) initiative that contains a content profile especially conceived for medical imaging exchange: Cross Enterprise Document Sharing for imaging (XDS-i). Moreover, due to application requirements, many solutions developed private networks to support their services. For instance, some applications support enhanced query and retrieve over DICOM objects metadata. This paper proposes anintegration framework to medical imaging networks that provides protocols interoperability and data federation services. It is an extensible plugin system that supports standard approaches (DICOM and XDS-I), but is also capable of supporting private protocols. The framework is being used in the Dicoogle Open Source PACS. PMID:25279021

  7. Dynamics of cluster structures in a financial market network

    NASA Astrophysics Data System (ADS)

    Kocheturov, Anton; Batsyn, Mikhail; Pardalos, Panos M.

    2014-11-01

    In the course of recent fifteen years the network analysis has become a powerful tool for studying financial markets. In this work we analyze stock markets of the USA and Sweden. We study cluster structures of a market network constructed from a correlation matrix of returns of the stocks traded in each of these markets. Such cluster structures are obtained by means of the P-Median Problem (PMP) whose objective is to maximize the total correlation between a set of stocks called medians of size p and other stocks. Every cluster structure is an undirected disconnected weighted graph in which every connected component (cluster) is a star, or a tree with one central node (called a median) and several leaf nodes connected with the median by weighted edges. Our main observation is that in non-crisis periods of time cluster structures change more chaotically, while during crises they show more stable behavior and fewer changes. Thus an increasing stability of a market graph cluster structure obtained via the PMP could be used as an indicator of a coming crisis.

  8. A network access control framework for 6LoWPAN networks.

    PubMed

    Oliveira, Luís M L; Rodrigues, Joel J P C; de Sousa, Amaro F; Lloret, Jaime

    2013-01-01

    Low power over wireless personal area networks (LoWPAN), in particular wireless sensor networks, represent an emerging technology with high potential to be employed in critical situations like security surveillance, battlefields, smart-grids, and in e-health applications. The support of security services in LoWPAN is considered a challenge. First, this type of networks is usually deployed in unattended environments, making them vulnerable to security attacks. Second, the constraints inherent to LoWPAN, such as scarce resources and limited battery capacity, impose a careful planning on how and where the security services should be deployed. Besides protecting the network from some well-known threats, it is important that security mechanisms be able to withstand attacks that have not been identified before. One way of reaching this goal is to control, at the network access level, which nodes can be attached to the network and to enforce their security compliance. This paper presents a network access security framework that can be used to control the nodes that have access to the network, based on administrative approval, and to enforce security compliance to the authorized nodes. PMID:23334610

  9. A Network Access Control Framework for 6LoWPAN Networks

    PubMed Central

    Oliveira, Luís M. L.; Rodrigues, Joel J. P. C.; de Sousa, Amaro F.; Lloret, Jaime

    2013-01-01

    Low power over wireless personal area networks (LoWPAN), in particular wireless sensor networks, represent an emerging technology with high potential to be employed in critical situations like security surveillance, battlefields, smart-grids, and in e-health applications. The support of security services in LoWPAN is considered a challenge. First, this type of networks is usually deployed in unattended environments, making them vulnerable to security attacks. Second, the constraints inherent to LoWPAN, such as scarce resources and limited battery capacity, impose a careful planning on how and where the security services should be deployed. Besides protecting the network from some well-known threats, it is important that security mechanisms be able to withstand attacks that have not been identified before. One way of reaching this goal is to control, at the network access level, which nodes can be attached to the network and to enforce their security compliance. This paper presents a network access security framework that can be used to control the nodes that have access to the network, based on administrative approval, and to enforce security compliance to the authorized nodes. PMID:23334610

  10. Neural network based load and price forecasting and confidence interval estimation in deregulated power markets

    NASA Astrophysics Data System (ADS)

    Zhang, Li

    With the deregulation of the electric power market in New England, an independent system operator (ISO) has been separated from the New England Power Pool (NEPOOL). The ISO provides a regional spot market, with bids on various electricity-related products and services submitted by utilities and independent power producers. A utility can bid on the spot market and buy or sell electricity via bilateral transactions. Good estimation of market clearing prices (MCP) will help utilities and independent power producers determine bidding and transaction strategies with low risks, and this is crucial for utilities to compete in the deregulated environment. MCP prediction, however, is difficult since bidding strategies used by participants are complicated and MCP is a non-stationary process. The main objective of this research is to provide efficient short-term load and MCP forecasting and corresponding confidence interval estimation methodologies. In this research, the complexity of load and MCP with other factors is investigated, and neural networks are used to model the complex relationship between input and output. With improved learning algorithm and on-line update features for load forecasting, a neural network based load forecaster was developed, and has been in daily industry use since summer 1998 with good performance. MCP is volatile because of the complexity of market behaviors. In practice, neural network based MCP predictors usually have a cascaded structure, as several key input factors need to be estimated first. In this research, the uncertainties involved in a cascaded neural network structure for MCP prediction are analyzed, and prediction distribution under the Bayesian framework is developed. A fast algorithm to evaluate the confidence intervals by using the memoryless Quasi-Newton method is also developed. The traditional back-propagation algorithm for neural network learning needs to be improved since MCP is a non-stationary process. The extended Kalman

  11. A Generic Framework of Performance Measurement in Networked Enterprises

    NASA Astrophysics Data System (ADS)

    Kim, Duk-Hyun; Kim, Cheolhan

    Performance measurement (PM) is essential for managing networked enterprises (NEs) because it greatly affects the effectiveness of collaboration among members of NE.PM in NE requires somewhat different approaches from PM in a single enterprise because of heterogeneity, dynamism, and complexity of NE’s. This paper introduces a generic framework of PM in NE (we call it NEPM) based on the Balanced Scorecard (BSC) approach. In NEPM key performance indicators and cause-and-effect relationships among them are defined in a generic strategy map. NEPM could be applied to various types of NEs after specializing KPIs and relationships among them. Effectiveness of NEPM is shown through a case study of some Korean NEs.

  12. A cognitive information processing framework for distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Wang, Feiyi; Qi, Hairong

    2004-09-01

    In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

  13. Conductive metal-organic frameworks and networks: fact or fantasy?

    PubMed

    Hendon, Christopher H; Tiana, Davide; Walsh, Aron

    2012-10-14

    Electrical conduction is well understood in materials formed from inorganic or organic building blocks, but their combination to produce conductive hybrid frameworks and networks is an emerging and rapidly developing field of research. Self-assembling organic-inorganic compounds offer immense potential for functionalising material properties for a wide scope of applications including solar cells, light emitters, gas sensors and bipolar transparent conductors. The flexibility of combining two distinct material classes into a single solid-state system provides an almost infinite number of chemical and structural possibilities; however, there is currently no systematic approach established for designing new compositions and configurations with targeted electronic or optical properties. We review the current status in the field, in particular, the range of hybrid systems reported to date and the important role of materials modelling in the field. From theoretical arguments, the Mott insulator-to-metal transition should be possible in semiconducting metal-organic frameworks, but has yet to be observed. The question remains as to whether electro-active hybrid materials will evolve from chemical curiosities towards practical applications in the near term. PMID:22858739

  14. A computational molecular design framework for crosslinked polymer networks.

    PubMed

    Eslick, J C; Ye, Q; Park, J; Topp, E M; Spencer, P; Camarda, K V

    2009-05-21

    Crosslinked polymers are important in a very wide range of applications including dental restorative materials. However, currently used polymeric materials experience limited durability in the clinical oral environment. Researchers in the dental polymer field have generally used a time-consuming experimental trial-and-error approach to the design of new materials. The application of computational molecular design (CMD) to crosslinked polymer networks has the potential to facilitate development of improved polymethacrylate dental materials. CMD uses quantitative structure property relations (QSPRs) and optimization techniques to design molecules possessing desired properties. This paper describes a mathematical framework which provides tools necessary for the application of CMD to crosslinked polymer systems. The novel parts of the system include the data structures used, which allow for simple calculation of structural descriptors, and the formulation of the optimization problem. A heuristic optimization method, Tabu Search, is used to determine candidate monomers. Use of a heuristic optimization algorithm makes the system more independent of the types of QSPRs used, and more efficient when applied to combinatorial problems. A software package has been created which provides polymer researchers access to the design framework. A complete example of the methodology is provided for polymethacrylate dental materials. PMID:23904665

  15. RUASN: A Robust User Authentication Framework for Wireless Sensor Networks

    PubMed Central

    Kumar, Pardeep; Choudhury, Amlan Jyoti; Sain, Mangal; Lee, Sang-Gon; Lee, Hoon-Jae

    2011-01-01

    In recent years, wireless sensor networks (WSNs) have been considered as a potential solution for real-time monitoring applications and these WSNs have potential practical impact on next generation technology too. However, WSNs could become a threat if suitable security is not considered before the deployment and if there are any loopholes in their security, which might open the door for an attacker and hence, endanger the application. User authentication is one of the most important security services to protect WSN data access from unauthorized users; it should provide both mutual authentication and session key establishment services. This paper proposes a robust user authentication framework for wireless sensor networks, based on a two-factor (password and smart card) concept. This scheme facilitates many services to the users such as user anonymity, mutual authentication, secure session key establishment and it allows users to choose/update their password regularly, whenever needed. Furthermore, we have provided the formal verification using Rubin logic and compare RUASN with many existing schemes. As a result, we found that the proposed scheme possesses many advantages against popular attacks, and achieves better efficiency at low computation cost. PMID:22163888

  16. RUASN: a robust user authentication framework for wireless sensor networks.

    PubMed

    Kumar, Pardeep; Choudhury, Amlan Jyoti; Sain, Mangal; Lee, Sang-Gon; Lee, Hoon-Jae

    2011-01-01

    In recent years, wireless sensor networks (WSNs) have been considered as a potential solution for real-time monitoring applications and these WSNs have potential practical impact on next generation technology too. However, WSNs could become a threat if suitable security is not considered before the deployment and if there are any loopholes in their security, which might open the door for an attacker and hence, endanger the application. User authentication is one of the most important security services to protect WSN data access from unauthorized users; it should provide both mutual authentication and session key establishment services. This paper proposes a robust user authentication framework for wireless sensor networks, based on a two-factor (password and smart card) concept. This scheme facilitates many services to the users such as user anonymity, mutual authentication, secure session key establishment and it allows users to choose/update their password regularly, whenever needed. Furthermore, we have provided the formal verification using Rubin logic and compare RUASN with many existing schemes. As a result, we found that the proposed scheme possesses many advantages against popular attacks, and achieves better efficiency at low computation cost. PMID:22163888

  17. An efficient automated parameter tuning framework for spiking neural networks

    PubMed Central

    Carlson, Kristofor D.; Nageswaran, Jayram Moorkanikara; Dutt, Nikil; Krichmar, Jeffrey L.

    2014-01-01

    As the desire for biologically realistic spiking neural networks (SNNs) increases, tuning the enormous number of open parameters in these models becomes a difficult challenge. SNNs have been used to successfully model complex neural circuits that explore various neural phenomena such as neural plasticity, vision systems, auditory systems, neural oscillations, and many other important topics of neural function. Additionally, SNNs are particularly well-adapted to run on neuromorphic hardware that will support biological brain-scale architectures. Although the inclusion of realistic plasticity equations, neural dynamics, and recurrent topologies has increased the descriptive power of SNNs, it has also made the task of tuning these biologically realistic SNNs difficult. To meet this challenge, we present an automated parameter tuning framework capable of tuning SNNs quickly and efficiently using evolutionary algorithms (EA) and inexpensive, readily accessible graphics processing units (GPUs). A sample SNN with 4104 neurons was tuned to give V1 simple cell-like tuning curve responses and produce self-organizing receptive fields (SORFs) when presented with a random sequence of counterphase sinusoidal grating stimuli. A performance analysis comparing the GPU-accelerated implementation to a single-threaded central processing unit (CPU) implementation was carried out and showed a speedup of 65× of the GPU implementation over the CPU implementation, or 0.35 h per generation for GPU vs. 23.5 h per generation for CPU. Additionally, the parameter value solutions found in the tuned SNN were studied and found to be stable and repeatable. The automated parameter tuning framework presented here will be of use to both the computational neuroscience and neuromorphic engineering communities, making the process of constructing and tuning large-scale SNNs much quicker and easier. PMID:24550771

  18. Geotube: a network based framework for Goescience dissemination

    NASA Astrophysics Data System (ADS)

    Grieco, Giovanni; Porta, Marina; Merlini, Anna Elisabetta; Caironi, Valeria; Reggiori, Donatella

    2016-04-01

    Geotube is a project promoted by Il Geco cultural association for the dissemination of Geoscience education in schools by open multimedia environments. The approach is based on the following keystones: • A deep and permanent epistemological reflection supported by confrontation within the International Scientific Community • A close link with the territory • A local to global inductive approach to basic concepts in Geosciences • The construction of an open framework to stimulate creativity The project has been developed as an educational activity for secondary schools (11 to 18 years old students). It provides for the creation of a network of institutions to be involved in order to ensure the required diversified expertise. They can comprise: Universities, Natural Parks, Mountain Communities, Municipalities, schools, private companies working in the sector, and so on. A single project lasts for one school year (October to June) and requires 8-12 work hours at school, one or two half day or full day excursions and a final event of presentation of outputs. The possible outputs comprise a pdf or ppt guidebook, a script and a video completely shooted and edited by the students. The framework is open in order to adapt to the single class or workgroup needs, the level and type of school, the time available and different subjects in Geosciences. In the last two years the two parts of the project have been successfully tested separately, while the full project will be presented at schools in in its full form in April 2016, in collaboration with University of Milan, Campo dei Fiori Natural Park, Piambello Mountain Community and Cunardo Municipality. The production of geotube outputs has been tested in a high school for three consecutive years. Students produced scripts and videos on the following subjects: geologic hazards, volcanoes and earthquakes, and climate change. The excursions have been tested with two different high schools. Firstly two areas have been

  19. Teaching Students How to Integrate and Assess Social Networking Tools in Marketing Communications

    ERIC Educational Resources Information Center

    Schlee, Regina Pefanis; Harich, Katrin R.

    2013-01-01

    This research is based on two studies that focus on teaching students how to integrate and assess social networking tools in marketing communications. Study 1 examines how students in marketing classes utilize social networking tools and explores their attitudes regarding the use of such tools for marketing communications. Study 2 focuses on an…

  20. U.S. stock market interaction network as learned by the Boltzmann machine

    DOE PAGESBeta

    Borysov, Stanislav S.; Roudi, Yasser; Balatsky, Alexander V.

    2015-12-07

    Here, we study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented results show that binarization preserves the correlation structure of the market. Properties of distributions of external fields and couplings as well as themore » market interaction network and industry sector clustering structure are studied for different historical dates and moving window sizes. We demonstrate that the observed positive heavy tail in distribution of couplings is related to the sparse clustering structure of the market. We also show that discrepancies between the model’s parameters might be used as a precursor of financial instabilities.« less

  1. Statistical properties of the stock and credit market: RMT and network topology

    NASA Astrophysics Data System (ADS)

    Lim, Kyuseong; Kim, Min Jae; Kim, Sehyun; Kim, Soo Yong

    We analyzed the dependence structure of the credit and stock market using random matrix theory and network topology. The dynamics of both markets have been spotlighted throughout the subprime crisis. In this study, we compared these two markets in view of the market-wide effect from random matrix theory and eigenvalue analysis. We found that the largest eigenvalue of the credit market as a whole preceded that of the stock market in the beginning of the financial crisis and that of two markets tended to be synchronized after the crisis. The correlation between the companies of both markets became considerably stronger after the crisis as well.

  2. A study of the spreading scheme for viral marketing based on a complex network model

    NASA Astrophysics Data System (ADS)

    Yang, Jianmei; Yao, Canzhong; Ma, Weicheng; Chen, Guanrong

    2010-02-01

    Buzzword-based viral marketing, known also as digital word-of-mouth marketing, is a marketing mode attached to some carriers on the Internet, which can rapidly copy marketing information at a low cost. Viral marketing actually uses a pre-existing social network where, however, the scale of the pre-existing network is believed to be so large and so random, so that its theoretical analysis is intractable and unmanageable. There are very few reports in the literature on how to design a spreading scheme for viral marketing on real social networks according to the traditional marketing theory or the relatively new network marketing theory. Complex network theory provides a new model for the study of large-scale complex systems, using the latest developments of graph theory and computing techniques. From this perspective, the present paper extends the complex network theory and modeling into the research of general viral marketing and develops a specific spreading scheme for viral marking and an approach to design the scheme based on a real complex network on the QQ instant messaging system. This approach is shown to be rather universal and can be further extended to the design of various spreading schemes for viral marketing based on different instant messaging systems.

  3. Switching benefits and costs in competitive health insurance markets: A conceptual framework and empirical evidence from the Netherlands.

    PubMed

    Duijmelinck, Daniëlle M I D; Mosca, Ilaria; van de Ven, Wynand P M M

    2015-05-01

    Competitive health insurance markets will only enhance cost-containment, efficiency, quality, and consumer responsiveness if all consumers feel free to easily switch insurer. Consumers will switch insurer if their perceived switching benefits outweigh their perceived switching costs. We developed a conceptual framework with potential switching benefits and costs in competitive health insurance markets. Moreover, we used a questionnaire among Dutch consumers (1091 respondents) to empirically examine the relevance of the different switching benefits and costs in consumers' decision to (not) switch insurer. Price, insurers' service quality, insurers' contracted provider network, the benefits of supplementary insurance, and welcome gifts are potential switching benefits. Transaction costs, learning costs, 'benefit loss' costs, uncertainty costs, the costs of (not) switching provider, and sunk costs are potential switching costs. In 2013 most Dutch consumers switched insurer because of (1) price and (2) benefits of supplementary insurance. Nearly half of the non-switchers - and particularly unhealthy consumers - mentioned one of the switching costs as their main reason for not switching. Because unhealthy consumers feel not free to easily switch insurer, insurers have reduced incentives to invest in high-quality care for them. Therefore, policymakers should develop strategies to increase consumer choice. PMID:25530069

  4. Cournot games with network effects for electric power markets

    NASA Astrophysics Data System (ADS)

    Spezia, Carl John

    The electric utility industry is moving from regulated monopolies with protected service areas to an open market with many wholesale suppliers competing for consumer load. This market is typically modeled by a Cournot game oligopoly where suppliers compete by selecting profit maximizing quantities. The classical Cournot model can produce multiple solutions when the problem includes typical power system constraints. This work presents a mathematical programming formulation of oligopoly that produces unique solutions when constraints limit the supplier outputs. The formulation casts the game as a supply maximization problem with power system physical limits and supplier incremental profit functions as constraints. The formulation gives Cournot solutions identical to other commonly used algorithms when suppliers operate within the constraints. Numerical examples demonstrate the feasibility of the theory. The results show that the maximization formulation will give system operators more transmission capacity when compared to the actions of suppliers in a classical constrained Cournot game. The results also show that the profitability of suppliers in constrained networks depends on their location relative to the consumers' load concentration.

  5. A multiobjective optimization framework for multicontaminant industrial water network design.

    PubMed

    Boix, Marianne; Montastruc, Ludovic; Pibouleau, Luc; Azzaro-Pantel, Catherine; Domenech, Serge

    2011-07-01

    The optimal design of multicontaminant industrial water networks according to several objectives is carried out in this paper. The general formulation of the water allocation problem (WAP) is given as a set of nonlinear equations with binary variables representing the presence of interconnections in the network. For optimization purposes, three antagonist objectives are considered: F(1), the freshwater flow-rate at the network entrance, F(2), the water flow-rate at inlet of regeneration units, and F(3), the number of interconnections in the network. The multiobjective problem is solved via a lexicographic strategy, where a mixed-integer nonlinear programming (MINLP) procedure is used at each step. The approach is illustrated by a numerical example taken from the literature involving five processes, one regeneration unit and three contaminants. The set of potential network solutions is provided in the form of a Pareto front. Finally, the strategy for choosing the best network solution among those given by Pareto fronts is presented. This Multiple Criteria Decision Making (MCDM) problem is tackled by means of two approaches: a classical TOPSIS analysis is first implemented and then an innovative strategy based on the global equivalent cost (GEC) in freshwater that turns out to be more efficient for choosing a good network according to a practical point of view. PMID:21435775

  6. Structure-dynamics relationships in bursting neuronal networks revealed using a prediction framework.

    PubMed

    Mäki-Marttunen, Tuomo; Aćimović, Jugoslava; Ruohonen, Keijo; Linne, Marja-Leena

    2013-01-01

    The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small ([Formula: see text]) networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger ([Formula: see text]) networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure

  7. Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework

    PubMed Central

    Mäki-Marttunen, Tuomo; Aćimović, Jugoslava; Ruohonen, Keijo; Linne, Marja-Leena

    2013-01-01

    The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small () networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger () networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure-dynamics studies in biosciences. PMID:23935998

  8. Developing a Framework for Effective Network Capacity Planning

    NASA Technical Reports Server (NTRS)

    Yaprak, Ece

    2005-01-01

    As Internet traffic continues to grow exponentially, developing a clearer understanding of, and appropriately measuring, network's performance is becoming ever more critical. An important challenge faced by the Information Resources Directorate (IRD) at the Johnson Space Center in this context remains not only monitoring and maintaining a secure network, but also better understanding the capacity and future growth potential boundaries of its network. This requires capacity planning which involves modeling and simulating different network alternatives, and incorporating changes in design as technologies, components, configurations, and applications change, to determine optimal solutions in light of IRD's goals, objectives and strategies. My primary task this summer was to address this need. I evaluated network-modeling tools from OPNET Technologies Inc. and Compuware Corporation. I generated a baseline model for Building 45 using both tools by importing "real" topology/traffic information using IRD's various network management tools. I compared each tool against the other in terms of the advantages and disadvantages of both tools to accomplish IRD's goals. I also prepared step-by-step "how to design a baseline model" tutorial for both OPNET and Compuware products.

  9. An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

    NASA Astrophysics Data System (ADS)

    Haghnevis, Moeed

    The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

  10. Security Frameworks for Machine-to-Machine Devices and Networks

    NASA Astrophysics Data System (ADS)

    Demblewski, Michael

    Attacks against mobile systems have escalated over the past decade. There have been increases of fraud, platform attacks, and malware. The Internet of Things (IoT) offers a new attack vector for Cybercriminals. M2M contributes to the growing number of devices that use wireless systems for Internet connection. As new applications and platforms are created, old vulnerabilities are transferred to next-generation systems. There is a research gap that exists between the current approaches for security framework development and the understanding of how these new technologies are different and how they are similar. This gap exists because system designers, security architects, and users are not fully aware of security risks and how next-generation devices can jeopardize safety and personal privacy. Current techniques, for developing security requirements, do not adequately consider the use of new technologies, and this weakens countermeasure implementations. These techniques rely on security frameworks for requirements development. These frameworks lack a method for identifying next generation security concerns and processes for comparing, contrasting and evaluating non-human device security protections. This research presents a solution for this problem by offering a novel security framework that is focused on the study of the "functions and capabilities" of M2M devices and improves the systems development life cycle for the overall IoT ecosystem.

  11. Framework to study dynamic dependencies in networks of interacting processes

    NASA Astrophysics Data System (ADS)

    Chicharro, Daniel; Ledberg, Anders

    2012-10-01

    The analysis of dynamic dependencies in complex systems such as the brain helps to understand how emerging properties arise from interactions. Here we propose an information-theoretic framework to analyze the dynamic dependencies in multivariate time-evolving systems. This framework constitutes a fully multivariate extension and unification of previous approaches based on bivariate or conditional mutual information and Granger causality or transfer entropy. We define multi-information measures that allow us to study the global statistical structure of the system as a whole, the total dependence between subsystems, and the temporal statistical structure of each subsystem. We develop a stationary and a nonstationary formulation of the framework. We then examine different decompositions of these multi-information measures. The transfer entropy naturally appears as a term in some of these decompositions. This allows us to examine its properties not as an isolated measure of interdependence but in the context of the complete framework. More generally we use causal graphs to study the specificity and sensitivity of all the measures appearing in these decompositions to different sources of statistical dependence arising from the causal connections between the subsystems. We illustrate that there is no straightforward relation between the strength of specific connections and specific terms in the decompositions. Furthermore, causal and noncausal statistical dependencies are not separable. In particular, the transfer entropy can be nonmonotonic in dependence on the connectivity strength between subsystems and is also sensitive to internal changes of the subsystems, so it should not be interpreted as a measure of connectivity strength. Altogether, in comparison to an analysis based on single isolated measures of interdependence, this framework is more powerful to analyze emergent properties in multivariate systems and to characterize functionally relevant changes in the

  12. Framework to study dynamic dependencies in networks of interacting processes.

    PubMed

    Chicharro, Daniel; Ledberg, Anders

    2012-10-01

    The analysis of dynamic dependencies in complex systems such as the brain helps to understand how emerging properties arise from interactions. Here we propose an information-theoretic framework to analyze the dynamic dependencies in multivariate time-evolving systems. This framework constitutes a fully multivariate extension and unification of previous approaches based on bivariate or conditional mutual information and Granger causality or transfer entropy. We define multi-information measures that allow us to study the global statistical structure of the system as a whole, the total dependence between subsystems, and the temporal statistical structure of each subsystem. We develop a stationary and a nonstationary formulation of the framework. We then examine different decompositions of these multi-information measures. The transfer entropy naturally appears as a term in some of these decompositions. This allows us to examine its properties not as an isolated measure of interdependence but in the context of the complete framework. More generally we use causal graphs to study the specificity and sensitivity of all the measures appearing in these decompositions to different sources of statistical dependence arising from the causal connections between the subsystems. We illustrate that there is no straightforward relation between the strength of specific connections and specific terms in the decompositions. Furthermore, causal and noncausal statistical dependencies are not separable. In particular, the transfer entropy can be nonmonotonic in dependence on the connectivity strength between subsystems and is also sensitive to internal changes of the subsystems, so it should not be interpreted as a measure of connectivity strength. Altogether, in comparison to an analysis based on single isolated measures of interdependence, this framework is more powerful to analyze emergent properties in multivariate systems and to characterize functionally relevant changes in the

  13. Multiple Hub Network Choice in the Liberalized European Market

    NASA Technical Reports Server (NTRS)

    Berechman, Joseph; deWit, Jaap

    1997-01-01

    . In the meantime, open skies agreements have been concluded between the USA and most of the EU member states to facilitate strategic alliances between airlines of the states involved. As a result of this on-going liberalization the model of the single 'national' carrier using the national home base as its single hub for the designated third, fourth and sixth freedom operations will stepwise disappear. Within the EU the concept of the national carrier has already been replaced by that of the community carrier. State ownership in more and more European carriers is reduced. On the longer run mergers or even bankruptcy will further undermine the "single national carrier - single national hub" model in Europe. In the meantime, strategic alliances between national carriers in Europe will already reduce the airlines' loyalty to a single airport. Profit maximization and accountability to share holders will supersede the loyalty of these newly emerging alliances, probably looking for the opportunities of a multiple hub network to adequately cover the whole European market. As a consequence, some European airports might see a substantial decline in arriving, departing and transfer traffic, thus in revenues and financial solvency, as well as in their connection to other inter-continental and intra-European destinations. At the same time, other airports might realize a significant increase in traffic as they will be sought after by the profit maximizing airlines as their major gateway hubs. Which will be the losing airports and which will be the winning ones? Can airports anticipate the actions of airlines in deregulated markets and utilize policies which will improve their relative position? If so, what should be these anticipatory policies? These questions become the more urgent, since an increasing number of major European airports will be privatized in the near future. Although increasing airport congestion in Europe will also be reflected in a growing demand pressure for

  14. Using LinkedIn in the Marketing Classroom: Exploratory Insights and Recommendations for Teaching Social Media/Networking

    ERIC Educational Resources Information Center

    McCorkle, Denny E.; McCorkle, Yuhua Li

    2012-01-01

    With the rapid growth of social networking and media comes their consideration for use in the marketing classroom. Social networking skills are becoming essential for personal branding (e.g., networking, self-marketing) and corporate/product branding (e.g., marketing communication). This paper addresses the use of LinkedIn (i.e., an online…

  15. A Rule-Based and Hypertextual Electronic Mail System for Electronic Learning Environments: Applying the Distributed Network Learning Framework.

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Levin, James A.

    This paper discusses issues related to the design of software tools that support learners in their participation in network-based learning activities. To guide the development and use of a new class of educationally-oriented network tools, this paper proposes a cognitively-based, distributed network learning framework (DNLF). This framework has…

  16. AUCTION MECHANISMS FOR IMPLEMENTING TRADABLE NETWORK PERMIT MARKETS

    NASA Astrophysics Data System (ADS)

    Wada, Kentaro; Akamatsu, Takashi

    This paper proposes a new auction mechanism for implementing the tradable network permit markets. Assuming that each user makes a trip from an origin to a destination along a path in a specific time period, we design an auction mechanism that enables each user to purchase a bundle of permits corresponding to a set of links in the user's preferred path. The objective of the proposed mechanism is to achieve a socially optimal state with minimal revelation of users' private information. In order to achieve this, the mechanism employs an evolutionary approach that has an auction phase and a path capacity adjustment phase, which are repeated on a day-to-day basis. We prove that the proposed mechanism has the following desirable properties: (1) truthful bidding is the dominant strategy for each user and (2) the proposed mechanism converges to an approximate socially optimal state in the sense that the achieved value of the social surplus reaches its maximum value when the number of users is large.

  17. Analysis of a Real Online Social Network Using Semantic Web Frameworks

    NASA Astrophysics Data System (ADS)

    Erétéo, Guillaume; Buffa, Michel; Gandon, Fabien; Corby, Olivier

    Social Network Analysis (SNA) provides graph algorithms to characterize the structure of social networks, strategic positions in these networks, specific sub-networks and decompositions of people and activities. Online social platforms like Facebook form huge social networks, enabling people to connect, interact and share their online activities across several social applications. We extended SNA operators using semantic web frameworks to include the semantics of these graph-based representations when analyzing such social networks and to deal with the diversity of their relations and interactions. We present here the results of this approach when it was used to analyze a real social network with 60,000 users connecting, interacting and sharing content.

  18. A Framework for Supporting Survivability, Network Planning and Cross-Layer Optimization in Future Multi-Domain Terabit Networks

    SciTech Connect

    Baldin, Ilya; Huang, Shu; Gopidi, Rajesh

    2015-01-28

    This final project report describes the accomplishments, products and publications from the award. It includes the overview of the project goals to devise a framework for managing resources in multi-domain, multi-layer networks, as well the details of the mathematical problem formulation and the description of the prototype built to prove the concept.

  19. Extended evolution: A conceptual framework for integrating regulatory networks and niche construction

    PubMed Central

    Renn, Jürgen

    2015-01-01

    ABSTRACT This paper introduces a conceptual framework for the evolution of complex systems based on the integration of regulatory network and niche construction theories. It is designed to apply equally to cases of biological, social and cultural evolution. Within the conceptual framework we focus especially on the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches and argue that these are an important part of evolutionary explanations. This conceptual framework extends previous evolutionary models and focuses on several challenges, such as the path‐dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems. J. Exp. Zool. (Mol. Dev. Evol.) 324B: 565–577, 2015. © 2015 The Authors. Journal of Experimental Zoology Part B: Molecular and Developmental Evolution published by Wiley Periodicals, Inc. PMID:26097188

  20. Security framework for networked storage system based on artificial immune system

    NASA Astrophysics Data System (ADS)

    Huang, Jianzhong; Xie, Changsheng; Zhang, Chengfeng; Zhan, Ling

    2007-11-01

    This paper proposed a theoretical framework for the networked storage system addressing the storage security. The immune system is an adaptive learning system, which can recognize, classify and eliminate 'non-self' such as foreign pathogens. Thus, we introduced the artificial immune technique to the storage security research, and proposed a full theoretical framework for storage security system. Under this framework, it is possible to carry out the quantitative evaluation for the storage security system using modeling language of artificial immune system (AIS), and the evaluation can offer security consideration for the deployment of networked storage system. Meanwhile, it is potential to obtain the active defense technique suitable for networked storage system via exploring the principle of AIS and achieve a highly secure storage system with immune characteristic.

  1. A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

    PubMed

    Kentzoglanakis, Kyriakos; Poole, Matthew

    2012-01-01

    In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures. PMID:21576756

  2. Multi-agent modelling framework for water, energy and other resource networks

    NASA Astrophysics Data System (ADS)

    Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

    2015-12-01

    Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be

  3. Multi-Agent Framework in Visual Sensor Networks

    NASA Astrophysics Data System (ADS)

    Patricio, M. A.; Carbó, J.; Pérez, O.; García, J.; Molina, J. M.

    2006-12-01

    The recent interest in the surveillance of public, military, and commercial scenarios is increasing the need to develop and deploy intelligent and/or automated distributed visual surveillance systems. Many applications based on distributed resources use the so-called software agent technology. In this paper, a multi-agent framework is applied to coordinate videocamera-based surveillance. The ability to coordinate agents improves the global image and task distribution efficiency. In our proposal, a software agent is embedded in each camera and controls the capture parameters. Then coordination is based on the exchange of high-level messages among agents. Agents use an internal symbolic model to interpret the current situation from the messages from all other agents to improve global coordination.

  4. Collaborative Procurement within Enterprise Networks: A Literature Review, a Reference Framework and a Case Study

    NASA Astrophysics Data System (ADS)

    Cagnazzo, Luca; Taticchi, Paolo; Bidini, Gianni; Sameh, Mohamed

    Collaboration among companies is nowadays a success leverage from those involved, especially for SMEs. The networking advantages are several and among them, reducing costs is a critical one. Costs reduction due to the possibility of Collaborative Procurement (CP) among partners is one of the most important achievements in a network. While the literature available offers good bases for managing single contractor procurement issues, little research addresses the case of CP within Enterprise Networks (ENs). This paper explore the mentioned issue and proposes a general framework for managing CP in ENs, those with the Virtual Development Office (VDO) structure. The findings from the application of the framework proposed in an Italian network are highlighted so as to provide preliminary results and drive future research.

  5. Cointegration analysis and influence rank—A network approach to global stock markets

    NASA Astrophysics Data System (ADS)

    Yang, Chunxia; Chen, Yanhua; Niu, Lei; Li, Qian

    2014-04-01

    In this paper, cointegration relationships among 26 global stock market indices over the periods of sub-prime and European debt crisis and their influence rank are investigated by constructing and analyzing directed and weighted cointegration networks. The obtained results are shown as follows: the crises have changed cointegration relationships among stock market indices, their cointegration relationship increased after the Lehman Brothers collapse, while the degree of cointegration gradually decreased from the sub-prime to European debt crisis. The influence of US, Japan and China market indices are entirely distinguished over different periods. Before European debt crisis US stock market is a ‘global factor’ which leads the developed and emerging markets, while the influence of US stock market decreased evidently during the European debt crisis. Before sub-prime crisis, there is no significant evidence to show that other stock markets co-move with China stock market, while it becomes more integrated with other markets during the sub-prime and European debt crisis. Among developed and emerging stock markets, the developed stock markets lead the world stock markets before European debt crisis, while due to the shock of sub-prime and European debt crisis, their influences decreased and emerging stock markets replaced them to lead global stock markets.

  6. A Framework for Managing Inter-Site Storage Area Networks using Grid Technologies

    NASA Technical Reports Server (NTRS)

    Kobler, Ben; McCall, Fritz; Smorul, Mike

    2006-01-01

    The NASA Goddard Space Flight Center and the University of Maryland Institute for Advanced Computer Studies are studying mechanisms for installing and managing Storage Area Networks (SANs) that span multiple independent collaborating institutions using Storage Area Network Routers (SAN Routers). We present a framework for managing inter-site distributed SANs that uses Grid Technologies to balance the competing needs to control local resources, share information, delegate administrative access, and manage the complex trust relationships between the participating sites.

  7. DYVIPAC: an integrated analysis and visualisation framework to probe multi-dimensional biological networks

    PubMed Central

    Nguyen, Lan K.; Degasperi, Andrea; Cotter, Philip; Kholodenko, Boris N.

    2015-01-01

    Biochemical networks are dynamic and multi-dimensional systems, consisting of tens or hundreds of molecular components. Diseases such as cancer commonly arise due to changes in the dynamics of signalling and gene regulatory networks caused by genetic alternations. Elucidating the network dynamics in health and disease is crucial to better understand the disease mechanisms and derive effective therapeutic strategies. However, current approaches to analyse and visualise systems dynamics can often provide only low-dimensional projections of the network dynamics, which often does not present the multi-dimensional picture of the system behaviour. More efficient and reliable methods for multi-dimensional systems analysis and visualisation are thus required. To address this issue, we here present an integrated analysis and visualisation framework for high-dimensional network behaviour which exploits the advantages provided by parallel coordinates graphs. We demonstrate the applicability of the framework, named “Dynamics Visualisation based on Parallel Coordinates” (DYVIPAC), to a variety of signalling networks ranging in topological wirings and dynamic properties. The framework was proved useful in acquiring an integrated understanding of systems behaviour. PMID:26220783

  8. Marketing Career Speed Networking: A Classroom Event to Foster Career Awareness

    ERIC Educational Resources Information Center

    Buff, Cheryl L.; O'Connor, Suzanne

    2012-01-01

    This paper describes the design, implementation, and evaluation of a marketing career speed networking event held during class time in two sections of the consumer behavior class. The event was coordinated through a partnering effort with marketing faculty and the college's Career Center. A total of 57 students participated in the event, providing…

  9. Marketing of Academic Library Services through Social Networking Sites: Implications of Electronic Word-of-Mouth

    ERIC Educational Resources Information Center

    Siddike, Md. Abul Kalam; Kiran, K.

    2015-01-01

    The main objective of this study is to investigate the perceptions of academic librarians towards the marketing of library services through social networking sites (SNSs) and their understanding of using electronic word-of-mouth (eWOM) as a marketing tool in academic libraries. This study follows a qualitative data-gathering approach of structured…

  10. Rural physicians, rural networks, and free market health care in the 1990s.

    PubMed

    Rosenthal, T C; James, P; Fox, C; Wysong, J; FitzPatrick, P G

    1997-01-01

    The changes brought about by managed care in America's urban communities will have profound effects on rural physicians and hospitals. The rural health care market characterized by small, independent group practices working with community hospitals is being offered affiliations with large, often urban-based health care organizations. Health care is evolving into a free market system characterized by large networks of organizations capable of serving whole regions. Rural provider-initiated networks can assure local representation when participating in the new market and improve the rural health infrastructure. Although an extensive review of the literature from 1970 to 1996 reveals little definitive research about networks, many rural hospitals have embraced networking as one strategy to unify health care systems with minimal capitalization. These networks, now licensed in Minnesota and New York, offer rural physicians the opportunity to team up with their community hospital and enhance local health care accessibility. PMID:9225701

  11. Identifying emergent social networks at a federally qualified health center-based farmers' market.

    PubMed

    Alia, Kassandra A; Freedman, Darcy A; Brandt, Heather M; Browne, Teri

    2014-06-01

    Identifying potential mechanisms connecting farmers' market interventions with health, economic, and community outcomes could inform strategies for addressing health disparities. The present study used social network theory to guide the in-depth examination of naturally occurring social interactions at a farmers' market located at a federally qualified health center located in a rural, low-income community. Trained observers recorded 61 observation logs at the market over 18 weeks. Thematic analysis revealed a range of actors and nonhuman facilitators instrumental to the farmers' market context. These actors connected with one another for communication and relationship development, economic and financial exchange, education, resource sharing, community ownership of the farmers' market, and conflict resolution. These interactions provided opportunities for social networks to develop among attendees, which may have facilitated the acquisition of social supports related to improved health, economic and community outcomes. Results provide insight into the role social networks may play in mediating the relationship between a farmers' market intervention and individual benefits. Findings also contribute to defining the typology of social networks, which may further disentangle the complex relationships between social networks and health outcomes. Future research should identify strategies for purposefully targeting social networks as a way to reduce diet-related health disparities. PMID:24352510

  12. A framework on the emergence and effectiveness of global health networks.

    PubMed

    Shiffman, Jeremy; Quissell, Kathryn; Schmitz, Hans Peter; Pelletier, David L; Smith, Stephanie L; Berlan, David; Gneiting, Uwe; Van Slyke, David; Mergel, Ines; Rodriguez, Mariela; Walt, Gill

    2016-04-01

    Since 1990 mortality and morbidity decline has been more extensive for some conditions prevalent in low- and middle-income countries than for others. One reason may be differences in the effectiveness of global health networks, which have proliferated in recent years. Some may be more capable than others in attracting attention to a condition, in generating funding, in developing interventions and in convincing national governments to adopt policies. This article introduces a supplement on the emergence and effectiveness of global health networks. The supplement examines networks concerned with six global health problems: tuberculosis (TB), pneumonia, tobacco use, alcohol harm, maternal mortality and newborn deaths. This article presents a conceptual framework delineating factors that may shape why networks crystallize more easily surrounding some issues than others, and once formed, why some are better able than others to shape policy and public health outcomes. All supplement papers draw on this framework. The framework consists of 10 factors in three categories: (1) features of the networks and actors that comprise them, including leadership, governance arrangements, network composition and framing strategies; (2) conditions in the global policy environment, including potential allies and opponents, funding availability and global expectations concerning which issues should be prioritized; (3) and characteristics of the issue, including severity, tractability and affected groups. The article also explains the design of the project, which is grounded in comparison of networks surrounding three matched issues: TB and pneumonia, tobacco use and alcohol harm, and maternal and newborn survival. Despite similar burden and issue characteristics, there has been considerably greater policy traction for the first in each pair. The supplement articles aim to explain the role of networks in shaping these differences, and collectively represent the first comparative effort

  13. Integrated Bayesian network framework for modeling complex ecological issues.

    PubMed

    Johnson, Sandra; Mengersen, Kerrie

    2012-07-01

    The management of environmental problems is multifaceted, requiring varied and sometimes conflicting objectives and perspectives to be considered. Bayesian network (BN) modeling facilitates the integration of information from diverse sources and is well suited to tackling the management challenges of complex environmental problems. However, combining several perspectives in one model can lead to large, unwieldy BNs that are difficult to maintain and understand. Conversely, an oversimplified model may lead to an unrealistic representation of the environmental problem. Environmental managers require the current research and available knowledge about an environmental problem of interest to be consolidated in a meaningful way, thereby enabling the assessment of potential impacts and different courses of action. Previous investigations of the environmental problem of interest may have already resulted in the construction of several disparate ecological models. On the other hand, the opportunity may exist to initiate this modeling. In the first instance, the challenge is to integrate existing models and to merge the information and perspectives from these models. In the second instance, the challenge is to include different aspects of the environmental problem incorporating both the scientific and management requirements. Although the paths leading to the combined model may differ for these 2 situations, the common objective is to design an integrated model that captures the available information and research, yet is simple to maintain, expand, and refine. BN modeling is typically an iterative process, and we describe a heuristic method, the iterative Bayesian network development cycle (IBNDC), for the development of integrated BN models that are suitable for both situations outlined above. The IBNDC approach facilitates object-oriented BN (OOBN) modeling, arguably viewed as the next logical step in adaptive management modeling, and that embraces iterative development

  14. Multilayer network of language: A unified framework for structural analysis of linguistic subsystems

    NASA Astrophysics Data System (ADS)

    Martinčić-Ipšić, Sanda; Margan, Domagoj; Meštrović, Ana

    2016-09-01

    Recently, the focus of complex networks' research has shifted from the analysis of isolated properties of a system toward a more realistic modeling of multiple phenomena - multilayer networks. Motivated by the prosperity of multilayer approach in social, transport or trade systems, we introduce the multilayer networks for language. The multilayer network of language is a unified framework for modeling linguistic subsystems and their structural properties enabling the exploration of their mutual interactions. Various aspects of natural language systems can be represented as complex networks, whose vertices depict linguistic units, while links model their relations. The multilayer network of language is defined by three aspects: the network construction principle, the linguistic subsystem and the language of interest. More precisely, we construct a word-level (syntax and co-occurrence) and a subword-level (syllables and graphemes) network layers, from four variations of original text (in the modeled language). The analysis and comparison of layers at the word and subword-levels are employed in order to determine the mechanism of the structural influences between linguistic units and subsystems. The obtained results suggest that there are substantial differences between the networks' structures of different language subsystems, which are hidden during the exploration of an isolated layer. The word-level layers share structural properties regardless of the language (e.g. Croatian or English), while the syllabic subword-level expresses more language dependent structural properties. The preserved weighted overlap quantifies the similarity of word-level layers in weighted and directed networks. Moreover, the analysis of motifs reveals a close topological structure of the syntactic and syllabic layers for both languages. The findings corroborate that the multilayer network framework is a powerful, consistent and systematic approach to model several linguistic subsystems

  15. Heat-Passing Framework for Robust Interpretation of Data in Networks

    PubMed Central

    Fang, Yi; Sun, Mengtian; Ramani, Karthik

    2015-01-01

    Researchers are regularly interested in interpreting the multipartite structure of data entities according to their functional relationships. Data is often heterogeneous with intricately hidden inner structure. With limited prior knowledge, researchers are likely to confront the problem of transforming this data into knowledge. We develop a new framework, called heat-passing, which exploits intrinsic similarity relationships within noisy and incomplete raw data, and constructs a meaningful map of the data. The proposed framework is able to rank, cluster, and visualize the data all at once. The novelty of this framework is derived from an analogy between the process of data interpretation and that of heat transfer, in which all data points contribute simultaneously and globally to reveal intrinsic similarities between regions of data, meaningful coordinates for embedding the data, and exemplar data points that lie at optimal positions for heat transfer. We demonstrate the effectiveness of the heat-passing framework for robustly partitioning the complex networks, analyzing the globin family of proteins and determining conformational states of macromolecules in the presence of high levels of noise. The results indicate that the methodology is able to reveal functionally consistent relationships in a robust fashion with no reference to prior knowledge. The heat-passing framework is very general and has the potential for applications to a broad range of research fields, for example, biological networks, social networks and semantic analysis of documents. PMID:25668316

  16. Institutional Ethnography and Actor-Network Theory: A Framework for Researching the Assessment of Trainee Teachers

    ERIC Educational Resources Information Center

    Tummons, Jonathan

    2010-01-01

    This article provides an analysis of assessment practices on one university-led teacher-training course in England, delivered across a network of further education colleges. After establishing that assessment practices are bound up in texts of different kinds, this article draws on two theoretical frameworks--institutional ethnography and…

  17. A Theoretical Framework for Building Online Communities of Practice with Social Networking Tools

    ERIC Educational Resources Information Center

    Gunawardena, Charlotte N.; Hermans, Mary Beth; Sanchez, Damien; Richmond, Carol; Bohley, Maribeth; Tuttle, Rebekah

    2009-01-01

    This paper proposes a theoretical framework as a foundation for building online communities of practice when a suite of social networking applications referred to as collective intelligence tools are utilized to develop a product or solutions to a problem. Drawing on recent developments in Web 2.0 tools, research on communities of practice and…

  18. Mobile Applications and 4G Wireless Networks: A Framework for Analysis

    ERIC Educational Resources Information Center

    Yang, Samuel C.

    2012-01-01

    Purpose: The use of mobile wireless data services continues to increase worldwide. New fourth-generation (4G) wireless networks can deliver data rates exceeding 2 Mbps. The purpose of this paper is to develop a framework of 4G mobile applications that utilize such high data rates and run on small form-factor devices. Design/methodology/approach:…

  19. MODELING FRAMEWORK FOR EVALUATING SEDIMENTATION IN STREAM NETWORKS: FOR USE IN SEDIMENT TMDL ANALYSIS

    EPA Science Inventory

    A modeling framework that can be used to evaluate sedimentation in stream networks is described. This methodology can be used to determine sediment Total Maximum Daily Loads (TMDLs) in sediment impaired waters, and provide the necessary hydrodynamic and sediment-related data t...

  20. Metadata and network API aspects of a framework for storing and retrieving civil infrastructure monitoring data

    NASA Astrophysics Data System (ADS)

    Wong, John-Michael; Stojadinovic, Bozidar

    2005-05-01

    A framework has been defined for storing and retrieving civil infrastructure monitoring data over a network. The framework consists of two primary components: metadata and network communications. The metadata component provides the descriptions and data definitions necessary for cataloging and searching monitoring data. The communications component provides Java classes for remotely accessing the data. Packages of Enterprise JavaBeans and data handling utility classes are written to use the underlying metadata information to build real-time monitoring applications. The utility of the framework was evaluated using wireless accelerometers on a shaking table earthquake simulation test of a reinforced concrete bridge column. The NEESgrid data and metadata repository services were used as a backend storage implementation. A web interface was created to demonstrate the utility of the data model and provides an example health monitoring application.

  1. Experimental analysis of chaotic neural network models for combinatorial optimization under a unifying framework.

    PubMed

    Kwok, T; Smith, K A

    2000-09-01

    The aim of this paper is to study both the theoretical and experimental properties of chaotic neural network (CNN) models for solving combinatorial optimization problems. Previously we have proposed a unifying framework which encompasses the three main model types, namely, Chen and Aihara's chaotic simulated annealing (CSA) with decaying self-coupling, Wang and Smith's CSA with decaying timestep, and the Hopfield network with chaotic noise. Each of these models can be represented as a special case under the framework for certain conditions. This paper combines the framework with experimental results to provide new insights into the effect of the chaotic neurodynamics of each model. By solving the N-queen problem of various sizes with computer simulations, the CNN models are compared in different parameter spaces, with optimization performance measured in terms of feasibility, efficiency, robustness and scalability. Furthermore, characteristic chaotic neurodynamics crucial to effective optimization are identified, together with a guide to choosing the corresponding model parameters. PMID:11152205

  2. Applying temporal network analysis to the venture capital market

    NASA Astrophysics Data System (ADS)

    Zhang, Xin; Feng, Ling; Zhu, Rongqian; Stanley, H. Eugene

    2015-10-01

    Using complex network theory to study the investment relationships of venture capital firms has produced a number of significant results. However, previous studies have often neglected the temporal properties of those relationships, which in real-world scenarios play a pivotal role. Here we examine the time-evolving dynamics of venture capital investment in China by constructing temporal networks to represent (i) investment relationships between venture capital firms and portfolio companies and (ii) the syndication ties between venture capital investors. The evolution of the networks exhibits rich variations in centrality, connectivity and local topology. We demonstrate that a temporal network approach provides a dynamic and comprehensive analysis of real-world networks.

  3. A Comprehensive Review on Adaptability of Network Forensics Frameworks for Mobile Cloud Computing

    PubMed Central

    Abdul Wahab, Ainuddin Wahid; Han, Qi; Bin Abdul Rahman, Zulkanain

    2014-01-01

    Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC. PMID:25097880

  4. Dynamic Graph Analytic Framework (DYGRAF): greater situation awareness through layered multi-modal network analysis

    NASA Astrophysics Data System (ADS)

    Margitus, Michael R.; Tagliaferri, William A., Jr.; Sudit, Moises; LaMonica, Peter M.

    2012-06-01

    Understanding the structure and dynamics of networks are of vital importance to winning the global war on terror. To fully comprehend the network environment, analysts must be able to investigate interconnected relationships of many diverse network types simultaneously as they evolve both spatially and temporally. To remove the burden from the analyst of making mental correlations of observations and conclusions from multiple domains, we introduce the Dynamic Graph Analytic Framework (DYGRAF). DYGRAF provides the infrastructure which facilitates a layered multi-modal network analysis (LMMNA) approach that enables analysts to assemble previously disconnected, yet related, networks in a common battle space picture. In doing so, DYGRAF provides the analyst with timely situation awareness, understanding and anticipation of threats, and support for effective decision-making in diverse environments.

  5. Mississippi Curriculum Framework for Fashion Marketing Technology (Program CIP: 08.0101--Apparel and Accessories Mkt. Op., Gen.). Postsecondary Programs.

    ERIC Educational Resources Information Center

    Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

    This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for the course sequences in the fashion marketing technology programs cluster. Presented in the introductory section are a description of the program and suggested course sequence. Section I lists baseline competencies,…

  6. Mississippi Curriculum Framework for Marketing Management Technology (Program CIP: 52.1401--Business Mkt. & Mkt. Mgmt.). Postsecondary Programs.

    ERIC Educational Resources Information Center

    Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

    This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for the course sequences in the state's marketing management technology program. Presented in the introduction are a program description and suggested course sequence. Section I lists baseline competencies for the…

  7. Design and architecture of the Mars relay network planning and analysis framework

    NASA Technical Reports Server (NTRS)

    Cheung, K. M.; Lee, C. H.

    2002-01-01

    In this paper we describe the design and architecture of the Mars Network planning and analysis framework that supports generation and validation of efficient planning and scheduling strategy. The goals are to minimize the transmitting time, minimize the delaying time, and/or maximize the network throughputs. The proposed framework would require (1) a client-server architecture to support interactive, batch, WEB, and distributed analysis and planning applications for the relay network analysis scheme, (2) a high-fidelity modeling and simulation environment that expresses link capabilities between spacecraft to spacecraft and spacecraft to Earth stations as time-varying resources, and spacecraft activities, link priority, Solar System dynamic events, the laws of orbital mechanics, and other limiting factors as spacecraft power and thermal constraints, (3) an optimization methodology that casts the resource and constraint models into a standard linear and nonlinear constrained optimization problem that lends itself to commercial off-the-shelf (COTS)planning and scheduling algorithms.

  8. A multiexpert framework for character recognition: a novel application of Clifford networks.

    PubMed

    Rahman, A R; Howells, W J; Fairhurst, M C

    2001-01-01

    A novel multiple-expert framework for recognition of handwritten characters is presented. The proposed framework is composed of multiple classifiers (experts) put together in such a manner as to enhance the recognition capability of the combined network compared to the best performing individual expert participating in the framework. Each of these experts has been derived from a novel neural structure in which the weight values are derived from Clifford algebra. A Clifford algebra is a mathematical paradigm capable of capturing the interdimensional dependencies found in multidimensional data. It offers a technique for concise data storage and processing by representing dependencies between the component dimensions of the data which is otherwise difficult to encode and hence is often employed in analyzing multidimensional data. Results achieved by the proposed multiple-expert framework demonstrates significant improvement over alternative techniques. PMID:18244366

  9. MOVE: a multi-level ontology-based visualization and exploration framework for genomic networks.

    PubMed

    Bosman, Diederik W J; Blom, Evert-Jan; Ogao, Patrick J; Kuipers, Oscar P; Roerdink, Jos B T M

    2007-01-01

    Among the various research areas that comprise bioinformatics, systems biology is gaining increasing attention. An important goal of systems biology is the unraveling of dynamic interactions between components of living cells (e. g., proteins, genes). These interactions exist among others on genomic, transcriptomic, proteomic and metabolomic levels. The levels themselves are heavily interconnected, resulting in complex networks of different interacting biological entities. Currently, various bioinformatics tools exist which are able to perform a particular analysis on a particular type of network. Unfortunately, each tool has its own disadvantages hampering it to be used consistently for different types of networks or analytical methods. This paper describes the conceptual development of an open source extensible software framework that supports visualization and exploration of highly complex genomic networks, like metabolic or gene regulatory networks. The focus is on the conceptual foundations, starting from requirements, a description of the state of the art of network visualization systems, and an analysis of their shortcomings. We describe the implementation of some initial modules of the framework and apply them to a biological test case in bacterial regulation, which shows the relevance and feasibility of the proposed approach. PMID:17688427

  10. A Two-Part Mixed-Effects Modeling Framework For Analyzing Whole-Brain Network Data

    PubMed Central

    Simpson, Sean L.; Laurienti, Paul J.

    2015-01-01

    Whole-brain network analyses remain the vanguard in neuroimaging research, coming to prominence within the last decade. Network science approaches have facilitated these analyses and allowed examining the brain as an integrated system. However, statistical methods for modeling and comparing groups of networks have lagged behind. Fusing multivariate statistical approaches with network science presents the best path to develop these methods. Toward this end, we propose a two-part mixed-effects modeling framework that allows modeling both the probability of a connection (presence/absence of an edge) and the strength of a connection if it exists. Models within this framework enable quantifying the relationship between an outcome (e.g., disease status) and connectivity patterns in the brain while reducing spurious correlations through inclusion of confounding covariates. They also enable prediction about an outcome based on connectivity structure and vice versa, simulating networks to gain a better understanding of normal ranges of topological variability, and thresholding networks leveraging group information. Thus, they provide a comprehensive approach to studying system level brain properties to further our understanding of normal and abnormal brain function. PMID:25796135

  11. Measuring performance in off-patent drug markets: a methodological framework and empirical evidence from twelve EU Member States.

    PubMed

    Kanavos, Panos

    2014-11-01

    This paper develops a methodological framework to help evaluate the performance of generic pharmaceutical policies post-patent expiry or after loss of exclusivity in non-tendering settings, comprising five indicators (generic availability, time delay to and speed of generic entry, number of generic competitors, price developments, and generic volume share evolution) and proposes a series of metrics to evaluate performance. The paper subsequently tests this framework across twelve EU Member States (MS) by using IMS data on 101 patent expired molecules over the 1998-2010 period. Results indicate that significant variation exists in generic market entry, price competition and generic penetration across the study countries. Size of a geographical market is not a predictor of generic market entry intensity or price decline. Regardless of geographic or product market size, many off patent molecules lack generic competitors two years after loss of exclusivity. The ranges in each of the five proposed indicators suggest, first, that there are numerous factors--including institutional ones--contributing to the success of generic entry, price decline and market penetration and, second, MS should seek a combination of supply and demand-side policies in order to maximise cost-savings from generics. Overall, there seems to be considerable potential for faster generic entry, uptake and greater generic competition, particularly for molecules at the lower end of the market. PMID:25201433

  12. Fiber Access Networks: Reliability Analysis and Swedish Broadband Market

    NASA Astrophysics Data System (ADS)

    Wosinska, Lena; Chen, Jiajia; Larsen, Claus Popp

    Fiber access network architectures such as active optical networks (AONs) and passive optical networks (PONs) have been developed to support the growing bandwidth demand. Whereas particularly Swedish operators prefer AON, this may not be the case for operators in other countries. The choice depends on a combination of technical requirements, practical constraints, business models, and cost. Due to the increasing importance of reliable access to the network services, connection availability is becoming one of the most crucial issues for access networks, which should be reflected in the network owner's architecture decision. In many cases protection against failures is realized by adding backup resources. However, there is a trade off between the cost of protection and the level of service reliability since improving reliability performance by duplication of network resources (and capital expenditures CAPEX) may be too expensive. In this paper we present the evolution of fiber access networks and compare reliability performance in relation to investment and management cost for some representative cases. We consider both standard and novel architectures for deployment in both sparsely and densely populated areas. While some recent works focused on PON protection schemes with reduced CAPEX the current and future effort should be put on minimizing the operational expenditures (OPEX) during the access network lifetime.

  13. A Computational Framework for the Automated Construction of Glycosylation Reaction Networks

    PubMed Central

    Liu, Gang; Neelamegham, Sriram

    2014-01-01

    Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS) data. The features described above are illustrated using three case studies that examine: i) O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii) automated N-linked glycosylation pathway construction; and iii) the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme biochemistry. All

  14. A computational framework for the automated construction of glycosylation reaction networks.

    PubMed

    Liu, Gang; Neelamegham, Sriram

    2014-01-01

    Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS) data. The features described above are illustrated using three case studies that examine: i) O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii) automated N-linked glycosylation pathway construction; and iii) the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme biochemistry. All

  15. An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

    PubMed Central

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-01-01

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

  16. An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

    PubMed

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-01-01

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

  17. Health economic value of an innovation: delimiting the scope and framework of future market entry agreements

    PubMed Central

    Launois, Robert; Navarrete, Lucia Fiestas; Ethgen, Olivier; Le Moine, Jean-Gabriel; Gatsinga, René

    2014-01-01

    Background and objectives The objective of our paper is to offer a new, payer-friendly taxonomy of market entry agreements (MEAs) that aims to twin contracts with their methodological designs in an effort to clarify the distinction between contracts that are based on performance and those that are based on demonstrated effect. Methods Our analysis proceeds in two stages: First, we delimit the scope and framework of pay for performance (P4P) and pay for demonstrated effect (P4E) agreements. Second, we distinguish the methodological designs supporting the implementation of each of these contracts. Results We elucidate why P4P contracts prevent the payer from funding the true effectiveness of an innovation by expanding on their limitations. These include: 1) the normative nature of comparisons, 2) the impossibility of true effect imputability for each individual, and 3) the use of intermediary outcome measures. We then explore three main criticisms that payers must take into account when reasoning in terms of performance rather than in terms of the product effectiveness. Conclusion The potential effect that performance-based reimbursements may have on dissociating the components of the cost-effectiveness ratio constitutes an obstacle to a true health economic reasoning. PMID:27226844

  18. A Network Approach to Environmental Impact in Psychotic Disorder: Brief Theoretical Framework.

    PubMed

    Isvoranu, Adela-Maria; Borsboom, Denny; van Os, Jim; Guloksuz, Sinan

    2016-07-01

    The spectrum of psychotic disorder represents a multifactorial and heterogeneous condition and is thought to result from a complex interplay between genetic and environmental factors. In the current paper, we analyze this interplay using network analysis, which has been recently proposed as a novel psychometric framework for the study of mental disorders. Using general population data, we construct network models for the relation between 3 environmental risk factors (cannabis use, developmental trauma, and urban environment), dimensional measures of psychopathology (anxiety, depression, interpersonal sensitivity, obsessive-compulsive disorder, phobic anxiety, somatizations, and hostility), and a composite measure of psychosis expression. Results indicate the existence of specific paths between environmental factors and symptoms. These paths most often involve cannabis use. In addition, the analyses suggest that symptom networks are more strongly connected for people exposed to environmental risk factors, implying that environmental exposure may lead to less resilient symptom networks. PMID:27179124

  19. An integrated framework for targeting functional networks via transcranial magnetic stimulation.

    PubMed

    Opitz, Alexander; Fox, Michael D; Craddock, R Cameron; Colcombe, Stan; Milham, Michael P

    2016-02-15

    Transcranial magnetic stimulation (TMS) is a powerful investigational tool for in vivo manipulation of regional or network activity, with a growing number of potential clinical applications. Unfortunately, the vast majority of targeting strategies remain limited by their reliance on non-realistic brain models and assumptions that anatomo-functional relationships are 1:1. Here, we present an integrated framework that combines anatomically realistic finite element models of the human head with resting functional MRI to predict functional networks targeted via TMS at a given coil location and orientation. Using data from the Human Connectome Project, we provide an example implementation focused on dorsolateral prefrontal cortex (DLPFC). Three distinct DLPFC stimulation zones were identified, differing with respect to the network to be affected (default, frontoparietal) and sensitivity to coil orientation. Network profiles generated for DLPFC targets previously published for treating depression revealed substantial variability across studies, highlighting a potentially critical technical issue. PMID:26608241

  20. Unraveling chaotic attractors by complex networks and measurements of stock market complexity

    SciTech Connect

    Cao, Hongduo; Li, Ying

    2014-03-15

    We present a novel method for measuring the complexity of a time series by unraveling a chaotic attractor modeled on complex networks. The complexity index R, which can potentially be exploited for prediction, has a similar meaning to the Kolmogorov complexity (calculated from the Lempel–Ziv complexity), and is an appropriate measure of a series' complexity. The proposed method is used to research the complexity of the world's major capital markets. None of these markets are completely random, and they have different degrees of complexity, both over the entire length of their time series and at a level of detail. However, developing markets differ significantly from mature markets. Specifically, the complexity of mature stock markets is stronger and more stable over time, whereas developing markets exhibit relatively low and unstable complexity over certain time periods, implying a stronger long-term price memory process.

  1. Complex network analysis of conventional and Islamic stock market in Indonesia

    NASA Astrophysics Data System (ADS)

    Rahmadhani, Andri; Purqon, Acep; Kim, Sehyun; Kim, Soo Yong

    2015-09-01

    The rising popularity of Islamic financial products in Indonesia has become a new interesting topic to be analyzed recently. We introduce a complex network analysis to compare conventional and Islamic stock market in Indonesia. Additionally, Random Matrix Theory (RMT) has been added as a part of reference to expand the analysis of the result. Both of them are based on the cross correlation matrix of logarithmic price returns. Closing price data, which is taken from June 2011 to July 2012, is used to construct logarithmic price returns. We also introduce the threshold value using winner-take-all approach to obtain scale-free property of the network. This means that the nodes of the network that has a cross correlation coefficient below the threshold value should not be connected with an edge. As a result, we obtain 0.5 as the threshold value for all of the stock market. From the RMT analysis, we found that there is only market wide effect on both stock market and no clustering effect has been found yet. From the network analysis, both of stock market networks are dominated by the mining sector. The length of time series of closing price data must be expanded to get more valuable results, even different behaviors of the system.

  2. Metal-Organic Framework Isomers with Diamondoid Networks Constructed of a Semi-Rigid Tetrahedral Linker

    SciTech Connect

    Tian, Jian; Motkuri, Radha K.; Thallapally, Praveen K.; McGrail, B. Peter

    2010-10-19

    Solvothermal assembly of a semi-rigid tetrahedral carboxylate ligand tetrakis[4-(carboxyphenyl)oxamethyl]methane acid (H4X) with Cd(II) ion in different solvent systems yields three novel metal-organic framework isomers (1-3) based on different secondary building units (SBUs). Although all three frameworks have the same dia (diamondoid) topology, complex 1 and 3 are chiral and complex 2 is achiral. One of the networks, 3 shows cross-linked three-fold interpenetration of the single dia net and exhibits permanent porosities, as confirmed by BET and selective CO2 adsorption.

  3. Building oceanographic and atmospheric observation networks by composition: unmanned vehicles, communication networks, and planning and execution control frameworks

    NASA Astrophysics Data System (ADS)

    Sousa, J. T.; Pinto, J.; Martins, R.; Costa, M.; Ferreira, F.; Gomes, R.

    2014-12-01

    The problem of developing mobile oceanographic and atmospheric observation networks (MOAO) with coordinated air and ocean vehicles is discussed in the framework of the communications and control software tool chain developed at Underwater Systems and Technologies Laboratory (LSTS) from Porto University. This is done with reference to field experiments to illustrate key capabilities and to assess future MOAO operations. First, the motivation for building MOAO by "composition" of air and ocean vehicles, communication networks, and planning and execution control frameworks is discussed - in networked vehicle systems information and commands are exchanged among multiple vehicles and operators, and the roles, relative positions, and dependencies of these vehicles and operators change during operations. Second, the planning and execution control framework developed at LSTS for multi-vehicle systems is discussed with reference to key concepts such as autonomy, mixed-initiative interactions, and layered organization. Third, the LSTS tool software tool chain is presented to show how to develop MOAO by composition. The tool chain comprises the Neptus command and control framework for mixed initiative interactions, the underlying IMC messaging protocol, and the DUNE on-board software. Fourth, selected LSTS operational deployments illustrate MOAO capability building. In 2012 we demonstrated the use of UAS to "ferry" data from UUVs located beyond line of sight (BLOS). In 2013 we demonstrated coordinated observations of coastal fronts with small UAS and UUVs, "bent" BLOS through the use of UAS as communication relays, and UAS tracking of juvenile hammer-head sharks. In 2014 we demonstrated UUV adaptive sampling with the closed loop controller of the UUV residing on a UAS; this was done with the help of a Wave Glider ASV with a communications gateway. The results from these experiments provide a background for assessing potential future UAS operations in a compositional MOAO.

  4. A Framework of Algorithms: Computing the Bias and Prestige of Nodes in Trust Networks

    PubMed Central

    Li, Rong-Hua; Yu, Jeffrey Xu; Huang, Xin; Cheng, Hong

    2012-01-01

    A trust network is a social network in which edges represent the trust relationship between two nodes in the network. In a trust network, a fundamental question is how to assess and compute the bias and prestige of the nodes, where the bias of a node measures the trustworthiness of a node and the prestige of a node measures the importance of the node. The larger bias of a node implies the lower trustworthiness of the node, and the larger prestige of a node implies the higher importance of the node. In this paper, we define a vector-valued contractive function to characterize the bias vector which results in a rich family of bias measurements, and we propose a framework of algorithms for computing the bias and prestige of nodes in trust networks. Based on our framework, we develop four algorithms that can calculate the bias and prestige of nodes effectively and robustly. The time and space complexities of all our algorithms are linear with respect to the size of the graph, thus our algorithms are scalable to handle large datasets. We evaluate our algorithms using five real datasets. The experimental results demonstrate the effectiveness, robustness, and scalability of our algorithms. PMID:23239990

  5. Effects of global financial crisis on network structure in a local stock market

    NASA Astrophysics Data System (ADS)

    Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

    2014-08-01

    This study considers the effects of the 2008 global financial crisis on threshold networks of a local Korean financial market around the time of the crisis. Prices of individual stocks belonging to KOSPI 200 (Korea Composite Stock Price Index 200) are considered for three time periods, namely before, during, and after the crisis. Threshold networks are constructed from fully connected cross-correlation networks, and thresholds of cross-correlation coefficients are assigned to obtain threshold networks. At the high threshold, only one large cluster consisting of firms in the financial sector, heavy industry, and construction is observed during the crisis. However, before and after the crisis, there are several fragmented clusters belonging to various sectors. The power law of the degree distribution in threshold networks is observed within the limited range of thresholds. Threshold networks are fatter during the crisis than before or after the crisis. The clustering coefficient of the threshold network follows the power law in the scaling range.

  6. A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks

    PubMed Central

    Jenney, Anne; MacBeath, Gavin; Sorger, Peter K.

    2014-01-01

    Functional interpretation of genomic variation is critical to understanding human disease but it remains difficult to predict the effects of specific mutations on protein interaction networks and the phenotypes they regulate. We describe an analytical framework based on multiscale statistical mechanics that integrates genomic and biophysical data to model the human SH2-phosphoprotein network in normal and cancer cells. We apply our approach to data in The Cancer Genome Atlas (TCGA) and test model predictions experimentally. We find that mutations in phosphoproteins often create new interactions but that mutations in SH2 domains result almost exclusively in loss of interactions. Some of these mutations eliminate all interactions but many cause more selective loss, thereby rewiring specific edges in highly connected subnetworks. Moreover, idiosyncratic mutations appear to be as functionally consequential as recurrent mutations. By synthesizing genomic, structural, and biochemical data our framework represents a new approach to the interpretation of genetic variation. PMID:25362484

  7. Framework for a hydrologic climate-response network in New England

    USGS Publications Warehouse

    Lent, Robert M.; Hodgkins, Glenn A.; Dudley, Robert W.; Schalk, Luther F.

    2015-01-01

    Many climate-related hydrologic variables in New England have changed in the past century, and many are expected to change during the next century. It is important to understand and monitor these changes because they can affect human water supply, hydroelectric power generation, transportation infrastructure, and stream and riparian ecology. This report describes a framework for hydrologic monitoring in New England by means of a climate-response network. The framework identifies specific inland hydrologic variables that are sensitive to climate variation; identifies geographic regions with similar hydrologic responses; proposes a fixed-station monitoring network composed of existing streamflow, groundwater, lake ice, snowpack, and meteorological data-collection stations for evaluation of hydrologic response to climate variation; and identifies streamflow basins for intensive, process-based studies and for estimates of future hydrologic conditions.

  8. Self-organizing Ising model of artificial financial markets with small-world network topology

    NASA Astrophysics Data System (ADS)

    Zhao, Haijie; Zhou, Jie; Zhang, Anghui; Su, Guifeng; Zhang, Yi

    2013-01-01

    We study a self-organizing Ising-like model of artificial financial markets with underlying small-world (SW) network topology. The asset price dynamics results from the collective decisions of interacting agents which are located on a small-world complex network (the nodes symbolize the agents of a financial market). The model incorporates the effects of imitation, the impact of external news and private information. We also investigate the influence of different network topologies, from regular lattice to random graph, on the asset price dynamics by adjusting the probability of the rewiring procedure. We find that a specific combination of model parameters reproduce main stylized facts of real-world financial markets.

  9. Untangling complex networks: risk minimization in financial markets through accessible spin glass ground states

    PubMed Central

    Lisewski, Andreas Martin; Lichtarge, Olivier

    2010-01-01

    Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the relative margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network's Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields. PMID:20625477

  10. A Framework for Understanding and Applying Ethical Principles in Network and Security Research

    NASA Astrophysics Data System (ADS)

    Kenneally, Erin; Bailey, Michael; Maughan, Douglas

    Current information and communications technology poses a variety of ethical challenges for researchers. In this paper, we present an intellectual framework for understanding and applying ethical principles in networking and security research rooted in the guidance suggested by an ongoing Department of Homeland Security working group on ethics. By providing this prototype ethical impact assessment, we seek to encourage community feedback on the working group's nascent efforts and spur researchers to concretely evaluate the ethical impact of their work.

  11. Market Related System Analysis of Satellite Communication Networks

    NASA Astrophysics Data System (ADS)

    Malyshev, V. V.; Panasenkova, M. V.

    2002-01-01

    The report is devoted to the technique of effectiveness analysis of communication space system with satellites in geostationary orbit using market models. The technique is worked out in order to choose the most optimal alternative of communication space system design. The alternative considered optimal and the system effective when the maximum profit from the system with limited system costs is achieved. The key point of the technique is a wide use of market models and application of market related parameters as an integral part of the design technique in order to secure the high commercial output of the communication space system. A range of models for decisive characteristics of communication space system is synthesized in terms of the technique. Flexible market model with detailed insight into the structure of the given market sector and its trends is created. The technique enables to choose the image and key parameters of the future system such as payload and ground sector characteristics so as to make the system most cost-effective and profitable. It is shown that such factors as the choice of launch vehicle can influence the system effectiveness rather dramatically. In particular, it is shown that under certain conditions delivering the small (five hundred kg) satellite to the geostationary orbit with the help of light-weight launch vehicle and the satellite's own electro-rocket thrusters is forty per cent more cost- effective than when the satellite is delivered with the help of the medium-size launch vehicle. The latter case can lead to the significant losses due to high launch costs that are nearly two times higher for the medium size launch vehicle than for the light launce vehicle. The technique is applicable both for designing a wide range of communication space systems and is recommended for those dealing with designing commercial systems. It can also be used to update and improve the systems that are already in operation.

  12. Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework.

    PubMed

    Song, H Francis; Yang, Guangyu R; Wang, Xiao-Jing

    2016-02-01

    The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, "trained" networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale's principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns

  13. A holistic framework for design of cost-effective minimum water utilization network.

    PubMed

    Wan Alwi, S R; Manan, Z A; Samingin, M H; Misran, N

    2008-07-01

    Water pinch analysis (WPA) is a well-established tool for the design of a maximum water recovery (MWR) network. MWR, which is primarily concerned with water recovery and regeneration, only partly addresses water minimization problem. Strictly speaking, WPA can only lead to maximum water recovery targets as opposed to the minimum water targets as widely claimed by researchers over the years. The minimum water targets can be achieved when all water minimization options including elimination, reduction, reuse/recycling, outsourcing and regeneration have been holistically applied. Even though WPA has been well established for synthesis of MWR network, research towards holistic water minimization has lagged behind. This paper describes a new holistic framework for designing a cost-effective minimum water network (CEMWN) for industry and urban systems. The framework consists of five key steps, i.e. (1) Specify the limiting water data, (2) Determine MWR targets, (3) Screen process changes using water management hierarchy (WMH), (4) Apply Systematic Hierarchical Approach for Resilient Process Screening (SHARPS) strategy, and (5) Design water network. Three key contributions have emerged from this work. First is a hierarchical approach for systematic screening of process changes guided by the WMH. Second is a set of four new heuristics for implementing process changes that considers the interactions among process changes options as well as among equipment and the implications of applying each process change on utility targets. Third is the SHARPS cost-screening technique to customize process changes and ultimately generate a minimum water utilization network that is cost-effective and affordable. The CEMWN holistic framework has been successfully implemented on semiconductor and mosque case studies and yielded results within the designer payback period criterion. PMID:17449168

  14. Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

    PubMed Central

    Wang, Xiao-Jing

    2016-01-01

    The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity

  15. Discovering the influential users oriented to viral marketing based on online social networks

    NASA Astrophysics Data System (ADS)

    Zhu, Zhiguo

    2013-08-01

    The target of viral marketing on the platform of popular online social networks is to rapidly propagate marketing information at lower cost and increase sales, in which a key problem is how to precisely discover the most influential users in the process of information diffusion. A novel method is proposed in this paper for helping companies to identify such users as seeds to maximize information diffusion in the viral marketing. Firstly, the user trust network oriented to viral marketing and users’ combined interest degree in the network including isolated users are extensively defined. Next, we construct a model considering the time factor to simulate the process of information diffusion in viral marketing and propose a dynamic algorithm description. Finally, experiments are conducted with a real dataset extracted from the famous SNS website Epinions. The experimental results indicate that the proposed algorithm has better scalability and is less time-consuming. Compared with the classical model, the proposed algorithm achieved a better performance than does the classical method on the two aspects of network coverage rate and time-consumption in our four sub-datasets.

  16. Network analysis of returns and volume trading in stock markets: The Euro Stoxx case

    NASA Astrophysics Data System (ADS)

    Brida, Juan Gabriel; Matesanz, David; Seijas, Maria Nela

    2016-02-01

    This study applies network analysis to analyze the structure of the Euro Stoxx market during the long period from 2002 up to 2014. The paper generalizes previous research on stock market networks by including asset returns and volume trading as the main variables to study the financial market. A multidimensional generalization of the minimal spanning tree (MST) concept is introduced, by adding the role of trading volume to the traditional approach which only includes price returns. Additionally, we use symbolization methods to the raw data to study the behavior of the market structure in different, normal and critical, situations. The hierarchical organization of the network is derived, and the MST for different sub-periods of 2002-2014 is created to illustrate how the structure of the market evolves over time. From the structural topologies of these trees, different clusters of companies are identified and analyzed according to their geographical and economic links. Two important results are achieved. Firstly, as other studies have highlighted, at the time of the financial crisis after 2008 the network becomes a more centralized one. Secondly and most important, during our second period of analysis, 2008-2014, we observe that hierarchy becomes more country-specific where different sub-clusters of stocks belonging to France, Germany, Spain or Italy are found apart from their business sector group. This result may suggest that during this period of time financial investors seem to be worried most about country specific economic circumstances.

  17. Threshold network of a financial market using the P-value of correlation coefficients

    NASA Astrophysics Data System (ADS)

    Ha, Gyeong-Gyun; Lee, Jae Woo; Nobi, Ashadun

    2015-06-01

    Threshold methods in financial networks are important tools for obtaining important information about the financial state of a market. Previously, absolute thresholds of correlation coefficients have been used; however, they have no relation to the length of time. We assign a threshold value depending on the size of the time window by using the P-value concept of statistics. We construct a threshold network (TN) at the same threshold value for two different time window sizes in the Korean Composite Stock Price Index (KOSPI). We measure network properties, such as the edge density, clustering coefficient, assortativity coefficient, and modularity. We determine that a significant difference exists between the network properties of the two time windows at the same threshold, especially during crises. This implies that the market information depends on the length of the time window when constructing the TN. We apply the same technique to Standard and Poor's 500 (S&P500) and observe similar results.

  18. Legitimising neural network river forecasting models: a new data-driven mechanistic modelling framework

    NASA Astrophysics Data System (ADS)

    Mount, N. J.; Dawson, C. W.; Abrahart, R. J.

    2013-01-01

    In this paper we address the difficult problem of gaining an internal, mechanistic understanding of a neural network river forecasting (NNRF) model. Neural network models in hydrology have long been criticised for their black-box character, which prohibits adequate understanding of their modelling mechanisms and has limited their broad acceptance by hydrologists. In response, we here present a new, data-driven mechanistic modelling (DDMM) framework that incorporates an evaluation of the legitimacy of a neural network's internal modelling mechanism as a core element in the model development process. The framework is exemplified for two NNRF modelling scenarios, and uses a novel adaptation of first order, partial derivate, relative sensitivity analysis methods as the means by which each model's mechanistic legitimacy is explored. The results demonstrate the limitations of standard, goodness-of-fit validation procedures applied by NNRF modellers, by highlighting how the internal mechanisms of complex models that produce the best fit scores can have much lower legitimacy than simpler counterparts whose scores are only slightly inferior. The study emphasises the urgent need for better mechanistic understanding of neural network-based hydrological models and the further development of methods for elucidating their mechanisms.

  19. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks

    PubMed Central

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-01-01

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting—both in terms of data and energy—data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios. PMID:26270664

  20. A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies.

    PubMed

    Ochs, Christopher; Geller, James; Perl, Yehoshua; Musen, Mark A

    2016-08-01

    Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving "live partial-area taxonomies" is demonstrated. PMID:27345947

  1. On the Optimization of a Probabilistic Data Aggregation Framework for Energy Efficiency in Wireless Sensor Networks.

    PubMed

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-01-01

    Among the key aspects of the Internet of Things (IoT) is the integration of heterogeneous sensors in a distributed system that performs actions on the physical world based on environmental information gathered by sensors and application-related constraints and requirements. Numerous applications of Wireless Sensor Networks (WSNs) have appeared in various fields, from environmental monitoring, to tactical fields, and healthcare at home, promising to change our quality of life and facilitating the vision of sensor network enabled smart cities. Given the enormous requirements that emerge in such a setting-both in terms of data and energy-data aggregation appears as a key element in reducing the amount of traffic in wireless sensor networks and achieving energy conservation. Probabilistic frameworks have been introduced as operational efficient and performance effective solutions for data aggregation in distributed sensor networks. In this work, we introduce an overall optimization approach that improves and complements such frameworks towards identifying the optimal probability for a node to aggregate packets as well as the optimal aggregation period that a node should wait for performing aggregation, so as to minimize the overall energy consumption, while satisfying certain imposed delay constraints. Primal dual decomposition is employed to solve the corresponding optimization problem while simulation results demonstrate the operational efficiency of the proposed approach under different traffic and topology scenarios. PMID:26270664

  2. Marketing.

    ERIC Educational Resources Information Center

    Doyle, Peter

    1987-01-01

    Explores the role of marketing in the modern firm and the key tasks of marketing management. Defines the term "marketing" and discusses it as an economic concept. Discusses three key marketing principals. (RKM)

  3. Network-Based Inference Framework for Identifying Cancer Genes from Gene Expression Data

    PubMed Central

    Yang, Bo; Zhang, Junying; Yin, Yaling; Zhang, Yuanyuan

    2013-01-01

    Great efforts have been devoted to alleviate uncertainty of detected cancer genes as accurate identification of oncogenes is of tremendous significance and helps unravel the biological behavior of tumors. In this paper, we present a differential network-based framework to detect biologically meaningful cancer-related genes. Firstly, a gene regulatory network construction algorithm is proposed, in which a boosting regression based on likelihood score and informative prior is employed for improving accuracy of identification. Secondly, with the algorithm, two gene regulatory networks are constructed from case and control samples independently. Thirdly, by subtracting the two networks, a differential-network model is obtained and then used to rank differentially expressed hub genes for identification of cancer biomarkers. Compared with two existing gene-based methods (t-test and lasso), the method has a significant improvement in accuracy both on synthetic datasets and two real breast cancer datasets. Furthermore, identified six genes (TSPYL5, CD55, CCNE2, DCK, BBC3, and MUC1) susceptible to breast cancer were verified through the literature mining, GO analysis, and pathway functional enrichment analysis. Among these oncogenes, TSPYL5 and CCNE2 have been already known as prognostic biomarkers in breast cancer, CD55 has been suspected of playing an important role in breast cancer prognosis from literature evidence, and other three genes are newly discovered breast cancer biomarkers. More generally, the differential-network schema can be extended to other complex diseases for detection of disease associated-genes. PMID:24073403

  4. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations

    PubMed Central

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology. PMID:26441628

  5. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations.

    PubMed

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology. PMID:26441628

  6. A novel framework of classical and quantum prisoner’s dilemma games on coupled networks

    NASA Astrophysics Data System (ADS)

    Deng, Xinyang; Zhang, Qi; Deng, Yong; Wang, Zhen

    2016-03-01

    Evolutionary games on multilayer networks are attracting growing interest. While among previous studies, the role of quantum games in such a infrastructure is still virgin and may become a fascinating issue across a myriad of research realms. To mimick two kinds of different interactive environments and mechanisms, in this paper a new framework of classical and quantum prisoner’s dilemma games on two-layer coupled networks is considered. Within the proposed model, the impact of coupling factor of networks and entanglement degree in quantum games on the evolutionary process has been studied. Simulation results show that the entanglement has no impact on the evolution of the classical prisoner’s dilemma, while the rise of the coupling factor obviously impedes cooperation in this game, and the evolution of quantum prisoner’s dilemma is greatly impacted by the combined effect of entanglement and coupling.

  7. A novel framework of classical and quantum prisoner's dilemma games on coupled networks.

    PubMed

    Deng, Xinyang; Zhang, Qi; Deng, Yong; Wang, Zhen

    2016-01-01

    Evolutionary games on multilayer networks are attracting growing interest. While among previous studies, the role of quantum games in such a infrastructure is still virgin and may become a fascinating issue across a myriad of research realms. To mimick two kinds of different interactive environments and mechanisms, in this paper a new framework of classical and quantum prisoner's dilemma games on two-layer coupled networks is considered. Within the proposed model, the impact of coupling factor of networks and entanglement degree in quantum games on the evolutionary process has been studied. Simulation results show that the entanglement has no impact on the evolution of the classical prisoner's dilemma, while the rise of the coupling factor obviously impedes cooperation in this game, and the evolution of quantum prisoner's dilemma is greatly impacted by the combined effect of entanglement and coupling. PMID:26975447

  8. A novel framework of classical and quantum prisoner’s dilemma games on coupled networks

    PubMed Central

    Deng, Xinyang; Zhang, Qi; Deng, Yong; Wang, Zhen

    2016-01-01

    Evolutionary games on multilayer networks are attracting growing interest. While among previous studies, the role of quantum games in such a infrastructure is still virgin and may become a fascinating issue across a myriad of research realms. To mimick two kinds of different interactive environments and mechanisms, in this paper a new framework of classical and quantum prisoner’s dilemma games on two-layer coupled networks is considered. Within the proposed model, the impact of coupling factor of networks and entanglement degree in quantum games on the evolutionary process has been studied. Simulation results show that the entanglement has no impact on the evolution of the classical prisoner’s dilemma, while the rise of the coupling factor obviously impedes cooperation in this game, and the evolution of quantum prisoner’s dilemma is greatly impacted by the combined effect of entanglement and coupling. PMID:26975447

  9. A scalable computational framework for establishing long-term behavior of stochastic reaction networks.

    PubMed

    Gupta, Ankit; Briat, Corentin; Khammash, Mustafa

    2014-06-01

    Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed. PMID:24968191

  10. A Scalable Computational Framework for Establishing Long-Term Behavior of Stochastic Reaction Networks

    PubMed Central

    Khammash, Mustafa

    2014-01-01

    Reaction networks are systems in which the populations of a finite number of species evolve through predefined interactions. Such networks are found as modeling tools in many biological disciplines such as biochemistry, ecology, epidemiology, immunology, systems biology and synthetic biology. It is now well-established that, for small population sizes, stochastic models for biochemical reaction networks are necessary to capture randomness in the interactions. The tools for analyzing such models, however, still lag far behind their deterministic counterparts. In this paper, we bridge this gap by developing a constructive framework for examining the long-term behavior and stability properties of the reaction dynamics in a stochastic setting. In particular, we address the problems of determining ergodicity of the reaction dynamics, which is analogous to having a globally attracting fixed point for deterministic dynamics. We also examine when the statistical moments of the underlying process remain bounded with time and when they converge to their steady state values. The framework we develop relies on a blend of ideas from probability theory, linear algebra and optimization theory. We demonstrate that the stability properties of a wide class of biological networks can be assessed from our sufficient theoretical conditions that can be recast as efficient and scalable linear programs, well-known for their tractability. It is notably shown that the computational complexity is often linear in the number of species. We illustrate the validity, the efficiency and the wide applicability of our results on several reaction networks arising in biochemistry, systems biology, epidemiology and ecology. The biological implications of the results as well as an example of a non-ergodic biological network are also discussed. PMID:24968191

  11. Optimality problem of network topology in stocks market analysis

    NASA Astrophysics Data System (ADS)

    Djauhari, Maman Abdurachman; Gan, Siew Lee

    2015-02-01

    Since its introduction fifteen years ago, minimal spanning tree has become an indispensible tool in econophysics. It is to filter the important economic information contained in a complex system of financial markets' commodities. Here we show that, in general, that tool is not optimal in terms of topological properties. Consequently, the economic interpretation of the filtered information might be misleading. To overcome that non-optimality problem, a set of criteria and a selection procedure of an optimal minimal spanning tree will be developed. By using New York Stock Exchange data, the advantages of the proposed method will be illustrated in terms of the power-law of degree distribution.

  12. Market analyses of livestock trade networks to inform the prevention of joint economic and epidemiological risks

    PubMed Central

    Gilligan, Christopher A.; Belloc, Catherine; Filipe, João A. N.; Vergu, Elisabeta

    2016-01-01

    Conventional epidemiological studies of infections spreading through trade networks, e.g. via livestock movements, generally show that central large-size holdings (hubs) should be preferentially surveyed and controlled in order to reduce epidemic spread. However, epidemiological strategies alone may not be economically optimal when costs of control are factored in together with risks of market disruption from targeting core holdings in a supply chain. Using extensive data on animal movements in supply chains for cattle and swine in France, we introduce a method to identify effective strategies for preventing outbreaks with limited budgets while minimizing the risk of market disruptions. Our method involves the categorization of holdings based on position along the supply chain and degree of market share. Our analyses suggest that trade has a higher risk of propagating epidemics through cattle networks, which are dominated by exchanges involving wholesalers, than for swine. We assess the effectiveness of contrasting interventions from the perspectives of regulators and the market, using percolation analysis. We show that preferentially targeting minor, non-central agents can outperform targeting of hubs when the costs to stakeholders and the risks of market disturbance are considered. Our study highlights the importance of assessing joint economic–epidemiological risks in networks underlying pathogen propagation and trade. PMID:26984191

  13. Market analyses of livestock trade networks to inform the prevention of joint economic and epidemiological risks.

    PubMed

    Moslonka-Lefebvre, Mathieu; Gilligan, Christopher A; Monod, Hervé; Belloc, Catherine; Ezanno, Pauline; Filipe, João A N; Vergu, Elisabeta

    2016-03-01

    Conventional epidemiological studies of infections spreading through trade networks, e.g., via livestock movements, generally show that central large-size holdings (hubs) should be preferentially surveyed and controlled in order to reduce epidemic spread. However, epidemiological strategies alone may not be economically optimal when costs of control are factored in together with risks of market disruption from targeting core holdings in a supply chain. Using extensive data on animal movements in supply chains for cattle and swine in France, we introduce a method to identify effective strategies for preventing outbreaks with limited budgets while minimizing the risk of market disruptions. Our method involves the categorization of holdings based on position along the supply chain and degree of market share. Our analyses suggest that trade has a higher risk of propagating epidemics through cattle networks, which are dominated by exchanges involving wholesalers, than for swine. We assess the effectiveness of contrasting interventions from the perspectives of regulators and the market, using percolation analysis. We show that preferentially targeting minor, non-central agents can outperform targeting of hubs when the costs to stakeholders and the risks of market disturbance are considered. Our study highlights the importance of assessing joint economic-epidemiological risks in networks underlying pathogen propagation and trade. PMID:26984191

  14. Beyond the Labor Market Paradigm: A Social Network Perspective on Teacher Recruitment and Retention

    ERIC Educational Resources Information Center

    Baker-Doyle, Kira

    2010-01-01

    This article identifies limits of the dominant labor market perspective (LMP) in research on teacher recruitment and retention and describes how research that incorporates a social network perspective (SNP) can contribute to the knowledge base and development of teacher education, staffing, and professional development approaches. A discussion of…

  15. An intra-body molecular communication networks framework for continuous health monitoring and diagnosis.

    PubMed

    Chahibi, Youssef; Balasingham, Ilangko

    2015-01-01

    Intra-body communication networks are designed to interconnect nano- or micro-sized sensors located inside the body for health monitoring and drug delivery. The most promising solutions are made of implanted nanosensors to timely monitor the body for the presence of specific diseases and pronounce a diagnosis without the intervention of a physician. In this manner, several deadly health conditions such as heart attacks are avoided through the early in vivo detection of their biomarkers. In reality, nanosensors are challenged by the individual specificities, molecular noise, limited durability, and low energy resources. In this paper, a framework is proposed for estimating and detecting diseases and localizing the nanosensors. This framework is based on molecular communication, a novel communication paradigm where information is conveyed through molecules. Through the case study of the shedding of endothelial cells as an early biomarker for heart attack, the intra-body molecular communication networks framework is shown to resolve major issues with in vivo nanosensors and lay the foundations of low-complexity biomedical signal processing algorithms for continuous disease monitoring and diagnosis. PMID:26737190

  16. Physics of transportation: Towards optimal capacity using the multilayer network framework

    PubMed Central

    Du, Wen-Bo; Zhou, Xing-Lian; Jusup, Marko; Wang, Zhen

    2016-01-01

    Because of the critical role of transportation in modern times, one of the most successful application areas of statistical physics of complex networks is the study of traffic dynamics. However, the vast majority of works treat transportation networks as an isolated system, which is inconsistent with the fact that many complex networks are interrelated in a nontrivial way. To mimic a realistic scenario, we use the framework of multilayer networks to construct a two-layered traffic model, whereby the upper layer provides higher transport speed than the lower layer. Moreover, passengers are guided to travel along the path of minimal travelling time and with the additional cost they can transfer from one layer to another to avoid congestion and/or reach the final destination faster. By means of numerical simulations, we show that a degree distribution-based strategy, although facilitating the cooperation between both layers, can be further improved by enhancing the critical generating rate of passengers using a particle swarm optimisation (PSO) algorithm. If initialised with the prior knowledge from the degree distribution-based strategy, the PSO algorithm converges considerably faster. Our work exemplifies how statistical physics of complex networks can positively affect daily life. PMID:26791580

  17. Physics of transportation: Towards optimal capacity using the multilayer network framework

    NASA Astrophysics Data System (ADS)

    Du, Wen-Bo; Zhou, Xing-Lian; Jusup, Marko; Wang, Zhen

    2016-01-01

    Because of the critical role of transportation in modern times, one of the most successful application areas of statistical physics of complex networks is the study of traffic dynamics. However, the vast majority of works treat transportation networks as an isolated system, which is inconsistent with the fact that many complex networks are interrelated in a nontrivial way. To mimic a realistic scenario, we use the framework of multilayer networks to construct a two-layered traffic model, whereby the upper layer provides higher transport speed than the lower layer. Moreover, passengers are guided to travel along the path of minimal travelling time and with the additional cost they can transfer from one layer to another to avoid congestion and/or reach the final destination faster. By means of numerical simulations, we show that a degree distribution-based strategy, although facilitating the cooperation between both layers, can be further improved by enhancing the critical generating rate of passengers using a particle swarm optimisation (PSO) algorithm. If initialised with the prior knowledge from the degree distribution-based strategy, the PSO algorithm converges considerably faster. Our work exemplifies how statistical physics of complex networks can positively affect daily life.

  18. Physics of transportation: Towards optimal capacity using the multilayer network framework.

    PubMed

    Du, Wen-Bo; Zhou, Xing-Lian; Jusup, Marko; Wang, Zhen

    2016-01-01

    Because of the critical role of transportation in modern times, one of the most successful application areas of statistical physics of complex networks is the study of traffic dynamics. However, the vast majority of works treat transportation networks as an isolated system, which is inconsistent with the fact that many complex networks are interrelated in a nontrivial way. To mimic a realistic scenario, we use the framework of multilayer networks to construct a two-layered traffic model, whereby the upper layer provides higher transport speed than the lower layer. Moreover, passengers are guided to travel along the path of minimal travelling time and with the additional cost they can transfer from one layer to another to avoid congestion and/or reach the final destination faster. By means of numerical simulations, we show that a degree distribution-based strategy, although facilitating the cooperation between both layers, can be further improved by enhancing the critical generating rate of passengers using a particle swarm optimisation (PSO) algorithm. If initialised with the prior knowledge from the degree distribution-based strategy, the PSO algorithm converges considerably faster. Our work exemplifies how statistical physics of complex networks can positively affect daily life. PMID:26791580

  19. A minimum resource neural network framework for solving multiconstraint shortest path problems.

    PubMed

    Zhang, Junying; Zhao, Xiaoxue; He, Xiaotao

    2014-08-01

    Characterized by using minimum hard (structural) and soft (computational) resources, a novel parameter-free minimal resource neural network (MRNN) framework is proposed for solving a wide range of single-source shortest path (SP) problems for various graph types. The problems are the k-shortest time path problems with any combination of three constraints: time, hop, and label constraints, and the graphs can be directed, undirected, or bidirected with symmetric and/or asymmetric traversal time, which can be real and time dependent. Isomorphic to the graph where the SP is to be sought, the network is activated by generating autowave at source neuron and the autowave travels automatically along the paths with the speed of a hop in an iteration. Properties of the network are studied, algorithms are presented, and computation complexity is analyzed. The framework guarantees globally optimal solutions of a series of problems during the iteration process of the network, which provides insight into why even the SP is still too long to be satisfied. The network facilitates very large scale integrated circuit implementation and adapt to very large scale problems due to its massively parallel processing and minimum resource utilization. When implemented in a sequentially processing computer, experiments on synthetic graphs, road maps of cities of the USA, and vehicle routing with time windows indicate that the MRNN is especially efficient for large scale sparse graphs and even dense graphs with some constraints, e.g., the CPU time taken and the iteration number used for the road maps of cities of the USA is even less than  ∼ 2% and 0.5% that of the Dijkstra's algorithm. PMID:25050952

  20. Untangling complex networks: Risk minimization in financial markets through accessible spin glass ground states

    NASA Astrophysics Data System (ADS)

    Lisewski, Andreas Martin; Lichtarge, Olivier

    2010-08-01

    Recurrent international financial crises inflict significant damage to societies and stress the need for mechanisms or strategies to control risk and tamper market uncertainties. Unfortunately, the complex network of market interactions often confounds rational approaches to optimize financial risks. Here we show that investors can overcome this complexity and globally minimize risk in portfolio models for any given expected return, provided the margin requirement remains below a critical, empirically measurable value. In practice, for markets with centrally regulated margin requirements, a rational stabilization strategy would be keeping margins small enough. This result follows from ground states of the random field spin glass Ising model that can be calculated exactly through convex optimization when relative spin coupling is limited by the norm of the network’s Laplacian matrix. In that regime, this novel approach is robust to noise in empirical data and may be also broadly relevant to complex networks with frustrated interactions that are studied throughout scientific fields.

  1. Development of a privacy and security policy framework for a multistate comparative effectiveness research network.

    PubMed

    Kim, Katherine K; McGraw, Deven; Mamo, Laura; Ohno-Machado, Lucila

    2013-08-01

    Comparative effectiveness research (CER) conducted in distributed research networks (DRNs) is subject to different state laws and regulations as well as institution-specific policies intended to protect privacy and security of health information. The goal of the Scalable National Network for Effectiveness Research (SCANNER) project is to develop and demonstrate a scalable, flexible technical infrastructure for DRNs that enables near real-time CER consistent with privacy and security laws and best practices. This investigation began with an analysis of privacy and security laws and state health information exchange (HIE) guidelines applicable to SCANNER participants from California, Illinois, Massachusetts, and the Federal Veteran's Administration. A 7-member expert panel of policy and technical experts reviewed the analysis and gave input into the framework during 5 meetings held in 2011-2012. The state/federal guidelines were applied to 3 CER use cases: safety of new oral hematologic medications; medication therapy management for patients with diabetes and hypertension; and informational interventions for providers in the treatment of acute respiratory infections. The policy framework provides flexibility, beginning with a use-case approach rather than a one-size-fits-all approach. The policies may vary depending on the type of patient data shared (aggregate counts, deidentified, limited, and fully identified datasets) and the flow of data. The types of agreements necessary for a DRN may include a network-level and data use agreements. The need for flexibility in the development and implementation of policies must be balanced with responsibilities of data stewardship. PMID:23774516

  2. Curation-Based Network Marketing: Strategies for Network Growth and Electronic Word-of-Mouth Diffusion

    ERIC Educational Resources Information Center

    Church, Earnie Mitchell, Jr.

    2013-01-01

    In the last couple of years, a new aspect of online social networking has emerged, in which the strength of social network connections is based not on social ties but mutually shared interests. This dissertation studies these "curation-based" online social networks (CBN) and their suitability for the diffusion of electronic word-of-mouth…

  3. Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market.

    PubMed

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

    This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk. PMID:27257816

  4. Can Network Linkage Effects Determine Return? Evidence from Chinese Stock Market

    PubMed Central

    Qiao, Haishu; Xia, Yue; Li, Ying

    2016-01-01

    This study used the dynamic conditional correlations (DCC) method to identify the linkage effects of Chinese stock market, and further detected the influence of network linkage effects on magnitude of security returns across different industries. Applying two physics-derived techniques, the minimum spanning tree and the hierarchical tree, we analyzed the stock interdependence within the network of the China Securities Index (CSI) industry index basket. We observed that that obvious linkage effects existed among stock networks. CII and CCE, CAG and ITH as well as COU, CHA and REI were confirmed as the core nodes in the three different networks respectively. We also investigated the stability of linkage effects by estimating the mean correlations and mean distances, as well as the normalized tree length of these indices. In addition, using the GMM model approach, we found inter-node influence within the stock network had a pronounced effect on stock returns. Our results generally suggested that there appeared to be greater clustering effect among the indexes belonging to related industrial sectors than those of diverse sectors, and network comovement was significantly affected by impactive financial events in the reality. Besides, stocks that were more central within the network of stock market usually had higher returns for compensation because they endured greater exposure to correlation risk. PMID:27257816

  5. Is there any connection between the network morphology and the fluctuations of the stock market index?

    NASA Astrophysics Data System (ADS)

    Stefan, F. M.; Atman, A. P. F.

    2015-02-01

    Models which consider behavioral aspects of the investors have attracted increasing interest in the Finance and Econophysics literature in the last years. Different behavioral profiles (imitation, anti-imitation, indifference) were proposed for the investors, which take their decision based on their trust network (neighborhood). Results from agent-based models have shown that most of the features observed in actual stock market indices can be replicated in simulations. Here, we present a deeper investigation of an agent based model considering different network morphologies (regular, random, small-world) for the investors' trust network, in an attempt to answer the question raised in the title. We study the model by considering four scenarios for the investors and different initial conditions to analyze their influence in the stock market fluctuations. We have characterized the stationary limit for each scenario tested, focusing on the changes introduced when complex networks were used, and calculated the Hurst exponent in some cases. Simulations showed interesting results suggesting that the fluctuations of the stock market index are strongly affected by the network morphology, a remarkable result which we believe was never reported or predicted before.

  6. Analysis of network clustering behavior of the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Chen, Huan; Mai, Yong; Li, Sai-Ping

    2014-11-01

    Random Matrix Theory (RMT) and the decomposition of correlation matrix method are employed to analyze spatial structure of stocks interactions and collective behavior in the Shanghai and Shenzhen stock markets in China. The result shows that there exists prominent sector structures, with subsectors including the Real Estate (RE), Commercial Banks (CB), Pharmaceuticals (PH), Distillers&Vintners (DV) and Steel (ST) industries. Furthermore, the RE and CB subsectors are mostly anti-correlated. We further study the temporal behavior of the dataset and find that while the sector structures are relatively stable from 2007 through 2013, the correlation between the real estate and commercial bank stocks shows large variations. By employing the ensemble empirical mode decomposition (EEMD) method, we show that this anti-correlation behavior is closely related to the monetary and austerity policies of the Chinese government during the period of study.

  7. A Multi-Agent Framework for Packet Routing in Wireless Sensor Networks

    PubMed Central

    Ye, Dayon; Zhang, Minji; Yang, Yu

    2015-01-01

    Wireless sensor networks (WSNs) have been widely investigated in recent years. One of the fundamental issues in WSNs is packet routing, because in many application domains, packets have to be routed from source nodes to destination nodes as soon and as energy efficiently as possible. To address this issue, a large number of routing approaches have been proposed. Although every existing routing approach has advantages, they also have some disadvantages. In this paper, a multi-agent framework is proposed that can assist existing routing approaches to improve their routing performance. This framework enables each sensor node to build a cooperative neighbour set based on past routing experience. Such cooperative neighbours, in turn, can help the sensor to effectively relay packets in the future. This framework is independent of existing routing approaches and can be used to assist many existing routing approaches. Simulation results demonstrate the good performance of this framework in terms of four metrics: average delivery latency, successful delivery ratio, number of live nodes and total sensing coverage. PMID:25928063

  8. A coarse-grained framework for spiking neuronal networks: between homogeneity and synchrony.

    PubMed

    Zhang, Jiwei; Zhou, Douglas; Cai, David; Rangan, Aaditya V

    2014-08-01

    Homogeneously structured networks of neurons driven by noise can exhibit a broad range of dynamic behavior. This dynamic behavior can range from homogeneity to synchrony, and often incorporates brief spurts of collaborative activity which we call multiple-firing-events (MFEs). These multiple-firing-events depend on neither structured architecture nor structured input, and are an emergent property of the system. Although these MFEs likely play a major role in the neuronal avalanches observed in culture and in vivo, the mechanisms underlying these MFEs cannot easily be captured using current population-dynamics models. In this work we introduce a coarse-grained framework which illustrates certain dynamics responsible for the generation of MFEs. By using a new kind of ensemble-average, this coarse-grained framework can not only address the nucleation of MFEs, but can also faithfully capture a broad range of dynamic regimes ranging from homogeneity to synchrony. PMID:24338105

  9. Scale-Free Networks Provide a Unifying Framework for the Emergence of Cooperation

    NASA Astrophysics Data System (ADS)

    Santos, F. C.; Pacheco, J. M.

    2005-08-01

    We study the evolution of cooperation in the framework of evolutionary game theory, adopting the prisoner’s dilemma and snowdrift game as metaphors of cooperation between unrelated individuals. In sharp contrast with previous results we find that, whenever individuals interact following networks of contacts generated via growth and preferential attachment, leading to strong correlations between individuals, cooperation becomes the dominating trait throughout the entire range of parameters of both games, as such providing a unifying framework for the emergence of cooperation. Such emergence is shown to be inhibited whenever the correlations between individuals are decreased or removed. These results are shown to apply from very large population sizes down to small communities with nearly 100 individuals.

  10. Measuring youth exposure to alcohol marketing on social networking sites: challenges and prospects.

    PubMed

    Jernigan, David H; Rushman, Anne E

    2014-02-01

    Youth exposure to alcohol marketing has been linked to increased alcohol consumption and problems. On relatively new and highly interactive social networking sites (SNS) that are popular with youth, tools for measuring youth exposure to alcohol marketing in traditional media are inadequate. We critically review the existing policies of Facebook, Twitter, and YouTube designed to keep branded alcohol content away from underage youth. Looking at brand and user activity on Facebook for the 15 alcohol brands most popular among US youth, we found activity has grown dramatically in the past 3 years, and underage users may be accounting for some of this activity. Surveys of youth and adult participation in alcohol marketing on SNS will be needed to inform debate over these marketing practices. PMID:24284473

  11. Evaluation of Metal-Organic Frameworks and Porous Polymer Networks for CO2 -Capture Applications.

    PubMed

    Verdegaal, Wolfgang M; Wang, Kecheng; Sculley, Julian P; Wriedt, Mario; Zhou, Hong-Cai

    2016-03-21

    This manuscript presents experimental data for 20 adsorption materials (metal-organic frameworks, porous polymer networks, and Zeolite-5A), including CO2 and N2 isotherms and heat capacities. With input from only experimental data, working capacities per energy for each material were calculated. Furthermore, by running seven different carbon-capture scenarios in which the initial flue-gas composition and process temperature was systematically changed, we present a range of performances for each material and quantify how sensitive each is to these varying parameters. The presented calculations provide researchers with a tool to investigate promising carbon-capture materials more easily and completely. PMID:26840979

  12. Model‐Based Network Meta‐Analysis: A Framework for Evidence Synthesis of Clinical Trial Data

    PubMed Central

    Bennetts, M; Dias, S; Boucher, M; Welton, NJ

    2016-01-01

    Model‐based meta‐analysis (MBMA) is increasingly used in drug development to inform decision‐making and future trial designs, through the use of complex dose and/or time course models. Network meta‐analysis (NMA) is increasingly being used by reimbursement agencies to estimate a set of coherent relative treatment effects for multiple treatments that respect the randomization within the trials. However, NMAs typically either consider different doses completely independently or lump them together, with few examples of models for dose. We propose a framework, model‐based network meta‐analysis (MBNMA), that combines both approaches, that respects randomization, and allows estimation and prediction for multiple agents and a range of doses, using plausible physiological dose‐response models. We illustrate our approach with an example comparing the efficacies of triptans for migraine relief. This uses a binary endpoint, although we note that the model can be easily modified for other outcome types. PMID:27479782

  13. A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths

    NASA Astrophysics Data System (ADS)

    Passalacqua, Paola; Do Trung, Tien; Foufoula-Georgiou, Efi; Sapiro, Guillermo; Dietrich, William E.

    2010-03-01

    A geometric framework for the automatic extraction of channels and channel networks from high-resolution digital elevation data is introduced in this paper. The proposed approach incorporates nonlinear diffusion for the preprocessing of the data, both to remove noise and to enhance features that are critical to the network extraction. Following this preprocessing, channels are defined as curves of minimal effort, or geodesics, where the effort is measured on the basis of fundamental geomorphological characteristics such as flow accumulation area and isoheight contours curvature. The merits of the proposed methodology, and especially the computational efficiency and accurate localization of the extracted channels, are demonstrated using light detection and ranging (lidar) data of the Skunk Creek, a tributary of the South Fork Eel River basin in northern California.

  14. FNCS: A Framework for Power System and Communication Networks Co-Simulation

    SciTech Connect

    Ciraci, Selim; Daily, Jeffrey A.; Fuller, Jason C.; Fisher, Andrew R.; Marinovici, Laurentiu D.; Agarwal, Khushbu

    2014-04-13

    This paper describes the Fenix framework that uses a federated approach for integrating power grid and communication network simulators. Compared existing approaches, Fenix al- lows co-simulation of both transmission and distribution level power grid simulators with the communication network sim- ulator. To reduce the performance overhead of time synchro- nization, Fenix utilizes optimistic synchronization strategies that make speculative decisions about when the simulators are going to exchange messages. GridLAB-D (a distribution simulator), PowerFlow (a transmission simulator), and ns-3 (a telecommunication simulator) are integrated with the frame- work and are used to illustrate the enhanced performance pro- vided by speculative multi-threading on a smart grid applica- tion. Our speculative multi-threading approach achieved on average 20% improvement over the existing synchronization methods

  15. Explicit synchronisation of heterogeneous dynamics networks via three-layer communication framework

    NASA Astrophysics Data System (ADS)

    Wang, Bohui; Wang, Jingcheng; Zhang, Langwen; Zhang, Bin

    2016-06-01

    This paper addresses the explicit synchronisation of heterogeneous dynamics networks via three-layer communication framework. The main contribution is to propose an explicit synchronisation algorithm, in which the synchronisation errors of all the agents are decoupled. By constructing a three-layer node model, the proposed algorithm removes the assumptions that the topology is fixed and the synchronisation process is coupled. By introducing appropriate assumptions, the algorithm leads to a class of explicit synchronisation protocols based on the states of agents in different layers. It is proved in the sense of Lyapunov that, if the dwell time is larger than a threshold, the explicit synchronisation can be achieved for closed-loop heterogeneous dynamics networks under switching topologies. The results are further extended to the cases in which the switching topologies are only frequently but not always connected. Simulation results are presented with four single-link manipulators to verify the theoretical analysis.

  16. Framework and Method for Controlling a Robotic System Using a Distributed Computer Network

    NASA Technical Reports Server (NTRS)

    Sanders, Adam M. (Inventor); Barajas, Leandro G. (Inventor); Permenter, Frank Noble (Inventor); Strawser, Philip A. (Inventor)

    2015-01-01

    A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.

  17. FERN – a Java framework for stochastic simulation and evaluation of reaction networks

    PubMed Central

    Erhard, Florian; Friedel, Caroline C; Zimmer, Ralf

    2008-01-01

    Background Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. Results In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. Conclusion FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand

  18. A framework for performance measurement in university using extended network data envelopment analysis (DEA) structures

    NASA Astrophysics Data System (ADS)

    Kashim, Rosmaini; Kasim, Maznah Mat; Rahman, Rosshairy Abd

    2015-12-01

    Measuring university performance is essential for efficient allocation and utilization of educational resources. In most of the previous studies, performance measurement in universities emphasized the operational efficiency and resource utilization without investigating the university's ability to fulfill the needs of its stakeholders and society. Therefore, assessment of the performance of university should be separated into two stages namely efficiency and effectiveness. In conventional DEA analysis, a decision making unit (DMU) or in this context, a university is generally treated as a black-box which ignores the operation and interdependence of the internal processes. When this happens, the results obtained would be misleading. Thus, this paper suggest an alternative framework for measuring the overall performance of a university by incorporating both efficiency and effectiveness and applies network DEA model. The network DEA models are recommended because this approach takes into account the interrelationship between the processes of efficiency and effectiveness in the system. This framework also focuses on the university structure which is expanded from the hierarchical to form a series of horizontal relationship between subordinate units by assuming both intermediate unit and its subordinate units can generate output(s). Three conceptual models are proposed to evaluate the performance of a university. An efficiency model is developed at the first stage by using hierarchical network model. It is followed by an effectiveness model which take output(s) from the hierarchical structure at the first stage as a input(s) at the second stage. As a result, a new overall performance model is proposed by combining both efficiency and effectiveness models. Thus, once this overall model is realized and utilized, the university's top management can determine the overall performance of each unit more accurately and systematically. Besides that, the result from the network

  19. Uniform framework for the recurrence-network analysis of chaotic time series

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

    We propose a general method for the construction and analysis of unweighted ɛ -recurrence networks from chaotic time series. The selection of the critical threshold ɛc in our scheme is done empirically and we show that its value is closely linked to the embedding dimension M . In fact, we are able to identify a small critical range Δ ɛ numerically that is approximately the same for the random and several standard chaotic time series for a fixed M . This provides us a uniform framework for the nonsubjective comparison of the statistical measures of the recurrence networks constructed from various chaotic attractors. We explicitly show that the degree distribution of the recurrence network constructed by our scheme is characteristic to the structure of the attractor and display statistical scale invariance with respect to increase in the number of nodes N . We also present two practical applications of the scheme, detection of transition between two dynamical regimes in a time-delayed system and identification of the dimensionality of the underlying system from real-world data with a limited number of points through recurrence network measures. The merits, limitations, and the potential applications of the proposed method are also highlighted.

  20. Periodic synchronization control of discontinuous delayed networks by using extended Filippov-framework.

    PubMed

    Cai, Zuowei; Huang, Lihong; Guo, Zhenyuan; Zhang, Lingling; Wan, Xuting

    2015-08-01

    This paper is concerned with the periodic synchronization problem for a general class of delayed neural networks (DNNs) with discontinuous neuron activation. One of the purposes is to analyze the problem of periodic orbits. To do so, we introduce new tools including inequality techniques and Kakutani's fixed point theorem of set-valued maps to derive the existence of periodic solution. Another purpose is to design a switching state-feedback control for realizing global exponential synchronization of the drive-response network system with periodic coefficients. Unlike the previous works on periodic synchronization of neural network, both the neuron activations and controllers in this paper are allowed to be discontinuous. Moreover, owing to the occurrence of delays in neuron signal, the neural network model is described by the functional differential equation. So we introduce extended Filippov-framework to deal with the basic issues of solutions for discontinuous DNNs. Finally, two examples and simulation experiments are given to illustrate the proposed method and main results which have an important instructional significance in the design of periodic synchronized DNNs circuits involving discontinuous or switching factors. PMID:26005005

  1. Forecasting Volatility in Indian Stock Market using Artificial Neural Network with Multiple Inputs and Outputs

    NASA Astrophysics Data System (ADS)

    DattaChaudhuri, Tamal; Ghosh, Indranil

    2015-06-01

    Volatility in stock markets has been extensively studied in the applied finance literature. In this paper, Artificial Neural Network models based on various back propagation algorithms have been constructed to predict volatility in the Indian stock market through volatility of NIFTY returns and volatility of gold returns. This model considers India VIX, CBOE VIX, volatility of crude oil returns (CRUDESDR), volatility of DJIA returns (DJIASDR), volatility of DAX returns (DAXSDR), volatility of Hang Seng returns (HANGSDR) and volatility of Nikkei returns (NIKKEISDR) as predictor variables. Three sets of experiments have been performed over three time periods to judge the effectiveness of the approach.

  2. Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty

    PubMed Central

    Casnici, Niccolò; Dondio, Pierpaolo; Casarin, Roberto; Squazzoni, Flaminio

    2015-01-01

    This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors' network structure by measuring the investors' communication patterns. Our results showed that the investors' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks. PMID:26244550

  3. Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty.

    PubMed

    Casnici, Niccolò; Dondio, Pierpaolo; Casarin, Roberto; Squazzoni, Flaminio

    2015-01-01

    This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors' network structure by measuring the investors' communication patterns. Our results showed that the investors' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum's reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks. PMID:26244550

  4. A web-based modular framework for real-time monitoring of large scale sensor networks

    NASA Astrophysics Data System (ADS)

    Newman, R. L.; Lindquist, K. G.; Vernon, F. L.

    2007-12-01

    The Antelope Real Time System (ARTS) is an integrated combination of protocols, acquisition systems and applications designed for real-time data collection and analysis from an array of deployed field sensors. Historically these were seismic sensors, however the open architecture of the ARTS facilitated development of acquisition protocols for a diverse group of sensors, including data streams from hf radar, meteorological instrumentation and cameras. In parallel with the expansion of data-type ingestion, a web-based interface to the ARTS was developed in PHP, a popular HTML embedded scripting language. The application-driven development of web-based software to Antelope-stored data has risen exponentially over the last four years, from simple database interactions to web-based AJAX applications similar in look and feel to desktop software. As the web-based applications have grown in complexity, the architecture around their development has matured into an extensible framework with "plug'n'play" capabilities. Their modular design has allowed multiple institutions to deploy the same web-based applications, tailored for their specific requirements. Examples include the NSF Earthscope USArray Transportable Array, ROADNet's Realtime Imagebank, the broadband seismic network monitoring of the University of Nevada Reno and University of California San Diego, and monitoring of the downhole arrays maintained by the University of California Santa Barbara. The success of these deployments suggest that such a framework could be applicable to other large scale sensor networks, including the developing Ocean Observatories project.

  5. An Energy-Efficient Target Tracking Framework in Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Yu, Zhijun; Wei, Jianming; Liu, Haitao

    2009-12-01

    This study devises and evaluates an energy-efficient distributed collaborative signal and information processing framework for acoustic target tracking in wireless sensor networks. The distributed processing algorithm is based on mobile agent computing paradigm and sequential Bayesian estimation. At each time step, the short detection reports of cluster members will be collected by cluster head, and a sensor node with the highest signal-to-noise ratio (SNR) is chosen there as reference node for time difference of arrive (TDOA) calculation. During the mobile agent migration, the target state belief is transmitted among nodes and updated using the TDOA measurement of these fusion nodes one by one. The computing and processing burden is evenly distributed in the sensor network. To decrease the wireless communications, we propose to represent the belief by parameterized methods such as Gaussian approximation or Gaussian mixture model approximation. Furthermore, we present an attraction force function to handle the mobile agent migration planning problem, which is a combination of the node residual energy, useful information, and communication cost. Simulation examples demonstrate the estimation effectiveness and energy efficiency of the proposed distributed collaborative target tracking framework.

  6. The structural role of weak and strong links in a financial market network

    NASA Astrophysics Data System (ADS)

    Garas, A.; Argyrakis, P.; Havlin, S.

    2008-05-01

    We investigate the properties of correlation based networks originating from economic complex systems, such as the network of stocks traded at the New York Stock Exchange (NYSE). The weaker links (low correlation) of the system are found to contribute to the overall connectivity of the network significantly more than the strong links (high correlation). We find that nodes connected through strong links form well defined communities. These communities are clustered together in more complex ways compared to the widely used classification according to the economic activity. We find that some companies, such as General Electric (GE), Coca Cola (KO), and others, can be involved in different communities. The communities are found to be quite stable over time. Similar results were obtained by investigating markets completely different in size and properties, such as the Athens Stock Exchange (ASE). The present method may be also useful for other networks generated through correlations.

  7. Landscape and Flux Framework for Non-Equilibrium Networks: Kinetic Paths and Rate Dynamics

    NASA Astrophysics Data System (ADS)

    Wang, Jin

    2012-02-01

    We developed a general framework to quantify three key ingredients for dynamics of nonequilibrium systems through path integrals in length space. First, we identify dominant kinetic paths as the ones with optimal weights, leading to effective reduction of dimensionality or degrees of freedom from exponential to polynomial so large systems can be treated. Second, we uncover the underlying nonequilibrium potential landscapes from the explorations of the state space through kinetic paths. We apply our framework to a specific example of nonequilibrium network system: lambda phage genetic switch. Two distinct basins of attractions emerge. The dominant kinetic paths from one basin to another are irreversible and do not follow the usual steepest descent or gradient path along the landscape. It reflects the fact that the dynamics of nonequilibrium systems is not just determined by potential gradient but also the residual curl flux force, suggesting experiments to test theoretical predictions. Third, we have calculated dynamic transition time scales from one basin to another critical for stability of the system through instantons. Theoretical predictions are in good agreements with wild type and mutant experiments.We further uncover the correlations between the kinetic transition time scales and the underlying landscape topography: the barrier heights along the dominant paths. We found that both the dominant paths and the landscape are relatively robust against the influences of external environmental perturbations and the system tends to dissipate less with less fluctuations. Our theoretical framework is general and can be applied to other nonequilibrium systems.

  8. Modelling Framework and the Quantitative Analysis of Distributed Energy Resources in Future Distribution Networks

    NASA Astrophysics Data System (ADS)

    Han, Xue; Sandels, Claes; Zhu, Kun; Nordström, Lars

    2013-08-01

    There has been a large body of statements claiming that the large-scale deployment of Distributed Energy Resources (DERs) could eventually reshape the future distribution grid operation in numerous ways. Thus, it is necessary to introduce a framework to measure to what extent the power system operation will be changed by various parameters of DERs. This article proposed a modelling framework for an overview analysis on the correlation between DERs. Furthermore, to validate the framework, the authors described the reference models of different categories of DERs with their unique characteristics, comprising distributed generation, active demand and electric vehicles. Subsequently, quantitative analysis was made on the basis of the current and envisioned DER deployment scenarios proposed for Sweden. Simulations are performed in two typical distribution network models for four seasons. The simulation results show that in general the DER deployment brings in the possibilities to reduce the power losses and voltage drops by compensating power from the local generation and optimizing the local load profiles.

  9. Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets.

    PubMed

    Mureddu, Mario; Caldarelli, Guido; Chessa, Alessandro; Scala, Antonio; Damiano, Alfonso

    2015-01-01

    The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players' behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents' behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data. PMID:26335705

  10. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model

    PubMed Central

    Qiu, Mingyue; Song, Yu

    2016-01-01

    In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders’ expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day’s price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

  11. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

    PubMed

    Qiu, Mingyue; Song, Yu

    2016-01-01

    In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

  12. Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets

    PubMed Central

    Mureddu, Mario; Caldarelli, Guido; Chessa, Alessandro; Scala, Antonio; Damiano, Alfonso

    2015-01-01

    The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players’ behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents’ behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data. PMID:26335705

  13. Shareholding relationships in the Euro Area banking market: A network perspective

    NASA Astrophysics Data System (ADS)

    Pecora, Nicolò; Spelta, Alessandro

    2015-09-01

    In this paper we analyze the topological properties of the network of the Euro Area banking market network, with the primary aim of assessing the importance of a bank in the financial system with respect to ownership and control of other credit institutions. The network displays power law distributions in both binary and weighted degree metrics indicating a robust yet fragile structure and a direct link between an increase of control diversification and a rise in the market power. Therefore while in good time the network is seemingly robust, in bad times many banks can simultaneously go into distress. This behavior paves the way for Central bank's actions. In particular we investigate whether the Single Supervisory Mechanism introduced by the European Central Banks and based on banks' total asset is a good proxy to quantify their systemic importance. Results indicate that not all the financial institutions with high valued total assets are systemically important but only few of them. Moreover the network structure reveals that control is highly concentrated, with few important shareholders approximately controlling a separate subset of banks.

  14. Framework and implementation of a continuous network-wide health monitoring system for roadways

    NASA Astrophysics Data System (ADS)

    Wang, Ming; Birken, Ralf; Shahini Shamsabadi, Salar

    2014-03-01

    According to the 2013 ASCE report card America's infrastructure scores only a D+. There are more than four million miles of roads (grade D) in the U.S. requiring a broad range of maintenance activities. The nation faces a monumental problem of infrastructure management in the scheduling and implementation of maintenance and repair operations, and in the prioritization of expenditures within budgetary constraints. The efficient and effective performance of these operations however is crucial to ensuring roadway safety, preventing catastrophic failures, and promoting economic growth. There is a critical need for technology that can cost-effectively monitor the condition of a network-wide road system and provide accurate, up-to-date information for maintenance activity prioritization. The Versatile Onboard Traffic Embedded Roaming Sensors (VOTERS) project provides a framework and the sensing capability to complement periodical localized inspections to continuous network-wide health monitoring. Research focused on the development of a cost-effective, lightweight package of multi-modal sensor systems compatible with this framework. An innovative software infrastructure is created that collects, processes, and evaluates these large time-lapse multi-modal data streams. A GIS-based control center manages multiple inspection vehicles and the data for further analysis, visualization, and decision making. VOTERS' technology can monitor road conditions at both the surface and sub-surface levels while the vehicle is navigating through daily traffic going about its normal business, thereby allowing for network-wide frequent assessment of roadways. This deterioration process monitoring at unprecedented time and spatial scales provides unique experimental data that can be used to improve life-cycle cost analysis models.

  15. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    PubMed Central

    Santra, Tapesh

    2014-01-01

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances. PMID:25152886

  16. A General Framework for a Collaborative Water Quality Knowledge and Information Network

    NASA Astrophysics Data System (ADS)

    Dalcanale, Fernanda; Fontane, Darrell; Csapo, Jorge

    2011-03-01

    Increasing knowledge about the environment has brought about a better understanding of the complexity of the issues, and more information publicly available has resulted into a steady shift from centralized decision making to increasing levels of participatory processes. The management of that information, in turn, is becoming more complex. One of the ways to deal with the complexity is the development of tools that would allow all players, including managers, researchers, educators, stakeholders and the civil society, to be able to contribute to the information system, in any level they are inclined to do so. In this project, a search for the available technology for collaboration, methods of community filtering, and community-based review was performed and the possible implementation of these tools to create a general framework for a collaborative "Water Quality Knowledge and Information Network" was evaluated. The main goals of the network are to advance water quality education and knowledge; encourage distribution and access to data; provide networking opportunities; allow public perceptions and concerns to be collected; promote exchange of ideas; and, give general, open, and free access to information. A reference implementation was made available online and received positive feedback from the community, which also suggested some possible improvements.

  17. Energy-saving framework for passive optical networks with ONU sleep/doze mode.

    PubMed

    Van, Dung Pham; Valcarenghi, Luca; Dias, Maluge Pubuduni Imali; Kondepu, Koteswararao; Castoldi, Piero; Wong, Elaine

    2015-02-01

    This paper proposes an energy-saving passive optical network framework (ESPON) that aims to incorporate optical network unit (ONU) sleep/doze mode into dynamic bandwidth allocation (DBA) algorithms to reduce ONU energy consumption. In the ESPON, the optical line terminal (OLT) schedules both downstream (DS) and upstream (US) transmissions in the same slot in an online and dynamic fashion whereas the ONU enters sleep mode outside the slot. The ONU sleep time is maximized based on both DS and US traffic. Moreover, during the slot, the ONU might enter doze mode when only its transmitter is idle to further improve energy efficiency. The scheduling order of data transmission, control message exchange, sleep period, and doze period defines an energy-efficient scheme under the ESPON. Three schemes are designed and evaluated in an extensive FPGA-based evaluation. Results show that whilst all the schemes significantly save ONU energy for different evaluation scenarios, the scheduling order has great impact on their performance. In addition, the ESPON allows for a scheduling order that saves ONU energy independently of the network reach. PMID:25836235

  18. Short-term load forecasting using generalized regression and probabilistic neural networks in the electricity market

    SciTech Connect

    Tripathi, M.M.; Upadhyay, K.G.; Singh, S.N.

    2008-11-15

    For the economic and secure operation of power systems, a precise short-term load forecasting technique is essential. Modern load forecasting techniques - especially artificial neural network methods - are particularly attractive, as they have the ability to handle the non-linear relationships between load, weather temperature, and the factors affecting them directly. A test of two different ANN models on data from Australia's Victoria market is promising. (author)

  19. A Human Sensor Network Framework in Support of Near Real Time Situational Geophysical Modeling

    NASA Astrophysics Data System (ADS)

    Aulov, O.; Price, A.; Smith, J. A.; Halem, M.

    2013-12-01

    The area of Disaster Management is well established among Federal Agencies such as FEMA, EPA, NOAA and NASA. These agencies have well formulated frameworks for response and mitigation based on near real time satellite and conventional observing networks for assimilation into geophysical models. Forecasts from these models are used to communicate with emergency responders and the general public. More recently, agencies have started using social media to broadcast warnings and alerts to potentially affected communities. In this presentation, we demonstrate the added benefits of mining and assimilating the vast amounts of social media data available from heterogeneous hand held devices and social networks into established operational geophysical modeling frameworks as they apply to the five cornerstones of disaster management - Prevention, Mitigation, Preparedness, Response and Recovery. Often, in situations of extreme events, social media provide the earliest notification of adverse extreme events. However, various forms of social media data also can provide useful geolocated and time stamped in situ observations, complementary to directly sensed conventional observations. We use the concept of a Human Sensor Network where one views social media users as carrying field deployed "sensors" whose posts are the remotely "sensed instrument measurements.' These measurements can act as 'station data' providing the resolution and coverage needed for extreme event specific modeling and validation. Here, we explore the use of social media through the use of a Human Sensor Network (HSN) approach as another data input source for assimilation into geophysical models. Employing the HSN paradigm can provide useful feedback in near real-time, but presents software challenges for rapid access, quality filtering and transforming massive social media data into formats consistent with the operational models. As a use case scenario, we demonstrate the value of HSN for disaster management

  20. MASM: a market architecture for sensor management in distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Viswanath, Avasarala; Mullen, Tracy; Hall, David; Garga, Amulya

    2005-03-01

    Rapid developments in sensor technology and its applications have energized research efforts towards devising a firm theoretical foundation for sensor management. Ubiquitous sensing, wide bandwidth communications and distributed processing provide both opportunities and challenges for sensor and process control and optimization. Traditional optimization techniques do not have the ability to simultaneously consider the wildly non-commensurate measures involved in sensor management in a single optimization routine. Market-oriented programming provides a valuable and principled paradigm to designing systems to solve this dynamic and distributed resource allocation problem. We have modeled the sensor management scenario as a competitive market, wherein the sensor manager holds a combinatorial auction to sell the various items produced by the sensors and the communication channels. However, standard auction mechanisms have been found not to be directly applicable to the sensor management domain. For this purpose, we have developed a specialized market architecture MASM (Market architecture for Sensor Management). In MASM, the mission manager is responsible for deciding task allocations to the consumers and their corresponding budgets and the sensor manager is responsible for resource allocation to the various consumers. In addition to having a modified combinatorial winner determination algorithm, MASM has specialized sensor network modules that address commensurability issues between consumers and producers in the sensor network domain. A preliminary multi-sensor, multi-target simulation environment has been implemented to test the performance of the proposed system. MASM outperformed the information theoretic sensor manager in meeting the mission objectives in the simulation experiments.

  1. Using the social structure of markets as a framework for analyzing vaccination debates: The case of emergency polio vaccination.

    PubMed

    Connelly, Yaron; Ziv, Arnona; Goren, Uri; Tal, Orna; Kaplan, Giora; Velan, Baruch

    2016-07-01

    The framework of the social structure of markets was used to analyze an online debate revolving around an emergency poliovirus vaccination campaign in Israel. Examination of a representative sample of 200 discussions revealed the activity of three parties: authoritative agents promoting vaccinations, alternative agents promoting anti-vaccination, both representing sellers, and the impartial agents, representing the customers-the general public deliberating whether to comply with vaccination or not. Both sellers interacted with consumers using mechanisms of luring and convincing. The authoritative agents conveyed their message by exhibiting professionalism, building trust and offering to share information. The alternative agents spread doubts and evoked negative emotions of distrust and fear. Among themselves, the alternative agents strived to discredit the authoritative agents, while the latter preferred to ignore the former. Content analysis of discussions conducted by the general public reveal reiteration of the messages conveyed by the sellers, implying that the transaction of pro and anti-vaccination ideas indeed took place. We suggest that the framework of the market as a social structure can be applied to the analysis of other vaccination debates, and thereby provide additional insights into vaccination polemics. PMID:27058586

  2. Segment-based Mass Customization: An Exploration of a New Conceptual Marketing Framework.

    ERIC Educational Resources Information Center

    Jiang, Pingjun

    2000-01-01

    Suggests that the concept of mass customization should be seen as an integral part of market segmentation theory which offers the best way to satisfy consumers' unique needs and wants while yielding profits to companies. Proposes a new concept of "segment-based based mass customization," and offers a series of propositions which are relevant to…

  3. Interventions for avian influenza A (H5N1) risk management in live bird market networks

    PubMed Central

    Fournié, Guillaume; Guitian, Javier; Desvaux, Stéphanie; Cuong, Vu Chi; Dung, Do Huu; Pfeiffer, Dirk Udo; Mangtani, Punam; Ghani, Azra C.

    2013-01-01

    Highly pathogenic avian influenza virus subtype H5N1 is endemic in Asia, with live bird trade as a major disease transmission pathway. A cross-sectional survey was undertaken in northern Vietnam to investigate the structure of the live bird market (LBM) contact network and the implications for virus spread. Based on the movements of traders between LBMs, weighted and directed networks were constructed and used for social network analysis and individual-based modeling. Most LBMs were connected to one another, suggesting that the LBM network may support large-scale disease spread. Because of cross-border trade, it also may promote transboundary virus circulation. However, opportunities for disease control do exist. The implementation of thorough, daily disinfection of the market environment as well as of traders’ vehicles and equipment in only a small number of hubs can disconnect the network dramatically, preventing disease spread. These targeted interventions would be an effective alternative to the current policy of a complete ban of LBMs in some areas. Some LBMs that have been banned still are very active, and they likely have a substantial impact on disease dynamics, exhibiting the highest levels of susceptibility and infectiousness. The number of trader visits to markets, information that can be collected quickly and easily, may be used to identify LBMs suitable for implementing interventions. This would not require prior knowledge of the force of infection, for which laboratory-confirmed surveillance would be necessary. These findings are of particular relevance for policy development in resource-scarce settings. PMID:23650388

  4. The Privacy Jungle:On the Market for Data Protection in Social Networks

    NASA Astrophysics Data System (ADS)

    Bonneau, Joseph; Preibusch, Sören

    We have conducted the first thorough analysis of the market for privacy practices and policies in online social networks. From an evaluation of 45 social networking sites using 260 criteria we find that many popular assumptions regarding privacy and social networking need to be revisited when considering the entire ecosystem instead of only a handful of well-known sites. Contrary to the common perception of an oligopolistic market, we find evidence of vigorous competition for new users. Despite observing many poor security practices, there is evidence that social network providers are making efforts to implement privacy enhancing technologies with substantial diversity in the amount of privacy control offered. However, privacy is rarely used as a selling point, even then only as auxiliary, nondecisive feature. Sites also failed to promote their existing privacy controls within the site. We similarly found great diversity in the length and content of formal privacy policies, but found an opposite promotional trend: though almost all policies are not accessible to ordinary users due to obfuscating legal jargon, they conspicuously vaunt the sites' privacy practices. We conclude that the market for privacy in social networks is dysfunctional in that there is significant variation in sites' privacy controls, data collection requirements, and legal privacy policies, but this is not effectively conveyed to users. Our empirical findings motivate us to introduce the novel model of a privacy communication game, where the economically rational choice for a site operator is to make privacy control available to evade criticism from privacy fundamentalists, while hiding the privacy control interface and privacy policy to maximize sign-up numbers and encourage data sharing from the pragmatic majority of users.

  5. Interventions for avian influenza A (H5N1) risk management in live bird market networks.

    PubMed

    Fournié, Guillaume; Guitian, Javier; Desvaux, Stéphanie; Cuong, Vu Chi; Dung, Do Huu; Pfeiffer, Dirk Udo; Mangtani, Punam; Ghani, Azra C

    2013-05-28

    Highly pathogenic avian influenza virus subtype H5N1 is endemic in Asia, with live bird trade as a major disease transmission pathway. A cross-sectional survey was undertaken in northern Vietnam to investigate the structure of the live bird market (LBM) contact network and the implications for virus spread. Based on the movements of traders between LBMs, weighted and directed networks were constructed and used for social network analysis and individual-based modeling. Most LBMs were connected to one another, suggesting that the LBM network may support large-scale disease spread. Because of cross-border trade, it also may promote transboundary virus circulation. However, opportunities for disease control do exist. The implementation of thorough, daily disinfection of the market environment as well as of traders' vehicles and equipment in only a small number of hubs can disconnect the network dramatically, preventing disease spread. These targeted interventions would be an effective alternative to the current policy of a complete ban of LBMs in some areas. Some LBMs that have been banned still are very active, and they likely have a substantial impact on disease dynamics, exhibiting the highest levels of susceptibility and infectiousness. The number of trader visits to markets, information that can be collected quickly and easily, may be used to identify LBMs suitable for implementing interventions. This would not require prior knowledge of the force of infection, for which laboratory-confirmed surveillance would be necessary. These findings are of particular relevance for policy development in resource-scarce settings. PMID:23650388

  6. A Geostatistical Framework for Estimating Rain Intensity Fields Using Dense Rain Gauge Networks

    NASA Astrophysics Data System (ADS)

    Benoit, L.; Mariethoz, G.

    2015-12-01

    Rain gauges provide direct and continuous observations of rain accumulation with a high time resolution (up to 1min). However the representativeness of these measurements is restricted to the funnel where rainwater is collected. Due to the high spatial heterogeneity of rainfall, this poor spatial representativeness is a strong limitation for the detailed reconstruction of rain intensity fields. Here we propose a geostatistical framework that is able to generate an ensemble of simulated rain fields based on data from a dense rain gauge network. When the density of rain gauges is high (sensor spacing in the range 500m to 1km), the spatial correlation between precipitation time series becomes sufficient to identify and track the rain patterns observed at the rain gauge sampling rate. Rain observations derived from such networks can thus be used to reconstruct the rain field with a high resolution in both space and time (i.e. 1min in time, 100m in space). Our method produces an ensemble of realizations that honor the rain intensities measured throughout the rain gauge network and preserve the main features of the rain intensity field at the considered scale, i.e.: the advection and morphing properties of rain cells over time, the intermittency and the skewed distribution of rainfall, and the decrease of the rain rate near the rain cell borders (dry drift). This allows to image the observed rain field and characterize its main features, as well as to quantify the related uncertainty. The obtained reconstruction of the rainfall are continuous in time, and therefore can complement weather radar observations which are snapshots of the rain field. In addition, the application of this method to networks with a spatial extent comparable to the one of a radar pixel (i.e. around 1km2) could allow exploration of the rain field within a single radar pixel.

  7. Market scenarios and alternative administrative frameworks for US educational satellite systems

    NASA Technical Reports Server (NTRS)

    Walkmeyer, J. E., Jr.; Morgan, R. P.; Singh, J. P.

    1975-01-01

    Costs and benefits of developing an operational educational satellite system in the U.S. are analyzed. Scenarios are developed for each educational submarket and satellite channel and ground terminal requirements for a large-scale educational telecommunications system are estimated. Alternative organizational frameworks for such a system are described.

  8. An Efficient Framework for Large Scale Multimedia Content Distribution in P2P Network: I2NC.

    PubMed

    Anandaraj, M; Ganeshkumar, P; Vijayakumar, K P; Selvaraj, K

    2015-01-01

    Network coding (NC) makes content distribution more effective and easier in P2P content distribution network and reduces the burden of the original seeder. It generalizes traditional network routing by allowing the intermediate nodes to generate new coded packet by combining the received packets. The randomization introduced by network coding makes all packets equally important and resolves the problem of locating the rarest block. Further, it reduces traffic in the network. In this paper, we analyze the performance of traditional network coding in P2P content distribution network by using a mathematical model and it is proved that traffic reduction has not been fully achieved in P2P network using traditional network coding. It happens due to the redundant transmission of noninnovative information block among the peers in the network. Hence, we propose a new framework, called I2NC (intelligent-peer selection and incremental-network coding), to eliminate the unnecessary flooding of noninnovative coded packets and thereby to improve the performance of network coding in P2P content distribution further. A comparative study and analysis of the proposed system is made through various related implementations and the results show that 10-15% of traffic reduced and improved the average and maximum download time by reducing original seeder's workload. PMID:26605375

  9. An Efficient Framework for Large Scale Multimedia Content Distribution in P2P Network: I2NC

    PubMed Central

    Anandaraj, M.; Ganeshkumar, P.; Vijayakumar, K. P.; Selvaraj, K.

    2015-01-01

    Network coding (NC) makes content distribution more effective and easier in P2P content distribution network and reduces the burden of the original seeder. It generalizes traditional network routing by allowing the intermediate nodes to generate new coded packet by combining the received packets. The randomization introduced by network coding makes all packets equally important and resolves the problem of locating the rarest block. Further, it reduces traffic in the network. In this paper, we analyze the performance of traditional network coding in P2P content distribution network by using a mathematical model and it is proved that traffic reduction has not been fully achieved in P2P network using traditional network coding. It happens due to the redundant transmission of noninnovative information block among the peers in the network. Hence, we propose a new framework, called I2NC (intelligent-peer selection and incremental-network coding), to eliminate the unnecessary flooding of noninnovative coded packets and thereby to improve the performance of network coding in P2P content distribution further. A comparative study and analysis of the proposed system is made through various related implementations and the results show that 10–15% of traffic reduced and improved the average and maximum download time by reducing original seeder's workload. PMID:26605375

  10. [Market and public policy network failures: challenges and possibilities for the Brazilian Unified Health System].

    PubMed

    Pinheiro Filho, Francisco Percival; Sarti, Flávia Mori

    2012-11-01

    The principles and guidelines of the Brazilian Unified Health System (SUS) impose a healthcare service structure based on public policy networks which, combined with the financing model adopted, leads to market failings. This imposes barriers to the management of the public health system and the enactment of SUS objectives. The institutional characteristics and the heterogeneity of players, allied to the existence of different healthcare approaches, generate analytical complexity in the study of the global dynamics of the SUS network. There are limitations in the use of quantitative methods based on static analysis of retrospective SUS data. Thus, an approach taking SUS as a complex system using innovative quantitative methodology based on computational simulation is proposed. This paper sought to analyze challenges and possibilities of the combined application of cellular automata modeling and agent-based modeling for simulation of the evolution of the SUS healthcare service network. This approach should permit better understanding of the organization, heterogeneity and structural dynamics of the SUS service network and a minimization of the effects of market failings on the Brazilian health system. PMID:23175305

  11. A study of IEEE 802.15.4 security framework for wireless body area networks.

    PubMed

    Saleem, Shahnaz; Ullah, Sana; Kwak, Kyung Sup

    2011-01-01

    A Wireless Body Area Network (WBAN) is a collection of low-power and lightweight wireless sensor nodes that are used to monitor the human body functions and the surrounding environment. It supports a number of innovative and interesting applications, including ubiquitous healthcare and Consumer Electronics (CE) applications. Since WBAN nodes are used to collect sensitive (life-critical) information and may operate in hostile environments, they require strict security mechanisms to prevent malicious interaction with the system. In this paper, we first highlight major security requirements and Denial of Service (DoS) attacks in WBAN at Physical, Medium Access Control (MAC), Network, and Transport layers. Then we discuss the IEEE 802.15.4 security framework and identify the security vulnerabilities and major attacks in the context of WBAN. Different types of attacks on the Contention Access Period (CAP) and Contention Free Period (CFP) parts of the superframe are analyzed and discussed. It is observed that a smart attacker can successfully corrupt an increasing number of GTS slots in the CFP period and can considerably affect the Quality of Service (QoS) in WBAN (since most of the data is carried in CFP period). As we increase the number of smart attackers the corrupted GTS slots are eventually increased, which prevents the legitimate nodes to utilize the bandwidth efficiently. This means that the direct adaptation of IEEE 802.15.4 security framework for WBAN is not totally secure for certain WBAN applications. New solutions are required to integrate high level security in WBAN. PMID:22319358

  12. A Study of IEEE 802.15.4 Security Framework for Wireless Body Area Networks

    PubMed Central

    Saleem, Shahnaz; Ullah, Sana; Kwak, Kyung Sup

    2011-01-01

    A Wireless Body Area Network (WBAN) is a collection of low-power and lightweight wireless sensor nodes that are used to monitor the human body functions and the surrounding environment. It supports a number of innovative and interesting applications, including ubiquitous healthcare and Consumer Electronics (CE) applications. Since WBAN nodes are used to collect sensitive (life-critical) information and may operate in hostile environments, they require strict security mechanisms to prevent malicious interaction with the system. In this paper, we first highlight major security requirements and Denial of Service (DoS) attacks in WBAN at Physical, Medium Access Control (MAC), Network, and Transport layers. Then we discuss the IEEE 802.15.4 security framework and identify the security vulnerabilities and major attacks in the context of WBAN. Different types of attacks on the Contention Access Period (CAP) and Contention Free Period (CFP) parts of the superframe are analyzed and discussed. It is observed that a smart attacker can successfully corrupt an increasing number of GTS slots in the CFP period and can considerably affect the Quality of Service (QoS) in WBAN (since most of the data is carried in CFP period). As we increase the number of smart attackers the corrupted GTS slots are eventually increased, which prevents the legitimate nodes to utilize the bandwidth efficiently. This means that the direct adaptation of IEEE 802.15.4 security framework for WBAN is not totally secure for certain WBAN applications. New solutions are required to integrate high level security in WBAN. PMID:22319358

  13. A Bayesian framework for cell-level protein network analysis for multivariate proteomics image data

    NASA Astrophysics Data System (ADS)

    Kovacheva, Violet N.; Sirinukunwattana, Korsuk; Rajpoot, Nasir M.

    2014-03-01

    The recent development of multivariate imaging techniques, such as the Toponome Imaging System (TIS), has facilitated the analysis of multiple co-localisation of proteins. This could hold the key to understanding complex phenomena such as protein-protein interaction in cancer. In this paper, we propose a Bayesian framework for cell level network analysis allowing the identification of several protein pairs having significantly higher co-expression levels in cancerous tissue samples when compared to normal colon tissue. It involves segmenting the DAPI-labeled image into cells and determining the cell phenotypes according to their protein-protein dependence profile. The cells are phenotyped using Gaussian Bayesian hierarchical clustering (GBHC) after feature selection is performed. The phenotypes are then analysed using Difference in Sums of Weighted cO-dependence Profiles (DiSWOP), which detects differences in the co-expression patterns of protein pairs. We demonstrate that the pairs highlighted by the proposed framework have high concordance with recent results using a different phenotyping method. This demonstrates that the results are independent of the clustering method used. In addition, the highlighted protein pairs are further analysed via protein interaction pathway databases and by considering the localization of high protein-protein dependence within individual samples. This suggests that the proposed approach could identify potentially functional protein complexes active in cancer progression and cell differentiation.

  14. Response Surfaces of Neural Networks Learned Using Bayesian Framework and Its Application to Optimization Problem

    NASA Astrophysics Data System (ADS)

    Takeda, Norio

    We verified the generalization ability of the response surfaces of artificial neural networks (NNs), and that the surfaces could be applied to an engineering-design problem. A Bayesian framework to regularize NNs, which was proposed by Gull and Skilling, can be used to generate NN response surfaces with excellent generalization ability, i.e., to determine the regularizing constants in an objective function minimized during NN learning. This well-generalized NN might be useful to find an optimal solution in the process of response surface methodology (RSM). We, therefore, describe three rules based on the Bayesian framework to update the regularizing constants, utilizing these rules to generate NN response surfaces with noisy teacher data drawn from a typical unimodal or multimodal function. Good generalization ability was achieved with regularized NN response surfaces, even though an update rule including trace evaluation failed to determine the regularizing constants regardless of the response function. We, next, selected the most appropriate update rule, which included eigenvalue evaluation, and then the NN response surface regularized using the update rule was applied to finding the optimal solution to an illustrative engineering-design problem. The NN response surface did not fit the noise in the teacher data, and consequently, it could effectively be used to achieve a satisfactory solution. This may increase the opportunities for using NN in the process of RSM.

  15. A Web Service-based framework model for people-centric sensing applications applied to social networking.

    PubMed

    Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

    2012-01-01

    As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users' activities and locations, sharing this information amongst the user's friends within a social networking site. We also present some screenshot results of our experimental prototype. PMID:22438732

  16. A novel framework for command and control of networked sensor systems

    NASA Astrophysics Data System (ADS)

    Chen, Genshe; Tian, Zhi; Shen, Dan; Blasch, Erik; Pham, Khanh

    2007-04-01

    In this paper, we have proposed a highly innovative advanced command and control framework for sensor networks used for future Integrated Fire Control (IFC). The primary goal is to enable and enhance target detection, validation, and mitigation for future military operations by graphical game theory and advanced knowledge information fusion infrastructures. The problem is approached by representing distributed sensor and weapon systems as generic warfare resources which must be optimized in order to achieve the operational benefits afforded by enabling a system of systems. This paper addresses the importance of achieving a Network Centric Warfare (NCW) foundation of information superiority-shared, accurate, and timely situational awareness upon which advanced automated management aids for IFC can be built. The approach uses the Data Fusion Information Group (DFIG) Fusion hierarchy of Level 0 through Level 4 to fuse the input data into assessments for the enemy target system threats in a battlespace to which military force is being applied. Compact graph models are employed across all levels of the fusion hierarchy to accomplish integrative data fusion and information flow control, as well as cross-layer sensor management. The functional block at each fusion level will have a set of innovative algorithms that not only exploit the corresponding graph model in a computationally efficient manner, but also permit combined functional experiments across levels by virtue of the unifying graphical model approach.

  17. An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework

    PubMed Central

    Guan, Xiangmin; Zhang, Xuejun; Zhu, Yanbo; Sun, Dengfeng; Lei, Jiaxing

    2015-01-01

    Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. PMID:26180840

  18. A Secure Multicast Framework in Large and High-Mobility Network Groups

    NASA Astrophysics Data System (ADS)

    Lee, Jung-San; Chang, Chin-Chen

    With the widespread use of Internet applications such as Teleconference, Pay-TV, Collaborate tasks, and Message services, how to construct and distribute the group session key to all group members securely is becoming and more important. Instead of adopting the point-to-point packet delivery, these emerging applications are based upon the mechanism of multicast communication, which allows the group member to communicate with multi-party efficiently. There are two main issues in the mechanism of multicast communication: Key Distribution and Scalability. The first issue is how to distribute the group session key to all group members securely. The second one is how to maintain the high performance in large network groups. Group members in conventional multicast systems have to keep numerous secret keys in databases, which makes it very inconvenient for them. Furthermore, in case that a member joins or leaves the communication group, many involved participants have to change their own secret keys to preserve the forward secrecy and the backward secrecy. We consequently propose a novel version for providing secure multicast communication in large network groups. Our proposed framework not only preserves the forward secrecy and the backward secrecy but also possesses better performance than existing alternatives. Specifically, simulation results demonstrate that our scheme is suitable for high-mobility environments.

  19. An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework.

    PubMed

    Guan, Xiangmin; Zhang, Xuejun; Zhu, Yanbo; Sun, Dengfeng; Lei, Jiaxing

    2015-01-01

    Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. PMID:26180840

  20. A framework for recovery-oriented, COTS-based ground station networks

    NASA Astrophysics Data System (ADS)

    Cutler, James William

    The complexity of space communication has limited our access to space systems and kept mission operations costs high. Ultimately, this results in reduced mission capabilities and yields. In particular, ground stations, the access point between space and terrestrial networks, suffer from monolithic designs, narrow interfaces, and unreliability that raise significant financial barriers for low-cost, experimental satellite missions. This research reduces these barriers by developing technology for recovery-oriented, flexible access networks built from commercial-off-the-shelf (COTS) components. Based on our extensive small satellite experiences, we decomposed ground station services and captured them in an extensible framework that simplified reuse of ground station services and improved portability across heterogeneous installations. This capability, combined with selective customization through virtual machine technology, allowed us to deliver "just in time" ground stations for QuakeSat-1 at a fraction of the price of current commodity solutions. This decomposition is also informed by principles of robust system design. Thus, our ground station reference implementation called Mercury was a candidate for recursive recovery (RR), a high availability technique whose effectiveness in reducing recovery time has been demonstrated on research prototypes of Internet server systems. Augmenting Mercury to implement RR reduced recovery time of typical ground station software failures by a factor of four, dropping recovery time to within the "window of recovery" and effectively eliminating the adverse effects of these failures. Since the time of failures cannot be predicted, RR allowed us to mitigate the effects of the failures and greatly reduce their potential impact on ground station operations. Our ground station architecture harnessed the benefits of COTS components, including rapid prototyping and deployment, while overcoming the challenges of COTS reliability and mission

  1. A program for the Bayesian Neural Network in the ROOT framework

    NASA Astrophysics Data System (ADS)

    Zhong, Jiahang; Huang, Run-Sheng; Lee, Shih-Chang

    2011-12-01

    We present a Bayesian Neural Network algorithm implemented in the TMVA package (Hoecker et al., 2007 [1]), within the ROOT framework (Brun and Rademakers, 1997 [2]). Comparing to the conventional utilization of Neural Network as discriminator, this new implementation has more advantages as a non-parametric regression tool, particularly for fitting probabilities. It provides functionalities including cost function selection, complexity control and uncertainty estimation. An example of such application in High Energy Physics is shown. The algorithm is available with ROOT release later than 5.29. Program summaryProgram title: TMVA-BNN Catalogue identifier: AEJX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: BSD license No. of lines in distributed program, including test data, etc.: 5094 No. of bytes in distributed program, including test data, etc.: 1,320,987 Distribution format: tar.gz Programming language: C++ Computer: Any computer system or cluster with C++ compiler and UNIX-like operating system Operating system: Most UNIX/Linux systems. The application programs were thoroughly tested under Fedora and Scientific Linux CERN. Classification: 11.9 External routines: ROOT package version 5.29 or higher ( http://root.cern.ch) Nature of problem: Non-parametric fitting of multivariate distributions Solution method: An implementation of Neural Network following the Bayesian statistical interpretation. Uses Laplace approximation for the Bayesian marginalizations. Provides the functionalities of automatic complexity control and uncertainty estimation. Running time: Time consumption for the training depends substantially on the size of input sample, the NN topology, the number of training iterations, etc. For the example in this manuscript, about 7 min was used on a PC/Linux with 2.0 GHz processors.

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

    PubMed Central

    2010-01-01

    Background 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. Results 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. Conclusions 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. PMID:20105306

  3. Polyoxometalate-based eight-connected self-catenated network and fivefold interpenetrating framework

    SciTech Connect

    Zhang Zhiming; Liu Jia; Li Yangguang; Yao Shuang; Wang Enbo; Wang Xinlong

    2010-01-15

    Two entangled compounds [(bpy){sub 6}Cu{sup I}{sub 6}Cl{sub 3}(Mo{sup V}W{sub 5}O{sub 19})] (1) and [(bpy){sub 7}Cu{sup I}{sub 7}Cl{sub 2}(BW{sub 12}O{sub 40})].H{sub 2}O (2) (bpy=4,4'-bipyridine), have been successfully synthesized under hydrothermal conditions and characterized by element analysis, IR spectroscopy, thermal gravimetric analysis, X-ray photoelectron spectroscopy, and single crystal X-ray diffraction analyses. Compound 1 represents the first eight-connected self-penetrating network constructed from cuprous chloride clusters [Cu{sub 6}Cl{sub 3}] and Lindquist-type polyoxoanions. Compound 2 exhibits an interesting fivefold interpenetrating network consisting of Keggin polyoxoanions and Cu{sup +}-metal-organic framework. Crystal data of the two compounds are following: 1, triclinic, P1-bar, a=11.502(2) A, b=13.069(3) A, c=13.296(3) A, alpha=90.55(3){sup o}, beta=113.74(3){sup o}, gamma=110.48(3){sup o}, Z=1; 2, triclinic, P1-bar, a=12.341(3) A, b=13.119(3) A, c=15.367(3) A, alpha=99.12(3){sup o}, beta=90.53(3){sup o}, gamma=104.49(3){sup o}, Z=1. - Graphical abstract: Compound 1 is the POM-based unprecedented eight-connected self-penetrating organic-inorganic hybrid network constructed from the cuprous chloride clusters [Cu{sub 6}Cl{sub 3}], Lindquist-type polyoxoanions [Mo{sup V}W{sub 5}O{sub 19}], and the 4,4'-bipyridine ligands.

  4. 76 FR 53443 - ENBALA Power Networks (USA), Inc.; Supplemental Notice That Initial Market-Based Rate Filing...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-26

    ... Federal Energy Regulatory Commission ENBALA Power Networks (USA), Inc.; Supplemental Notice That Initial Market-Based Rate Filing Includes Request for Blanket Section 204 Authorization This is a supplemental notice in the above-referenced proceeding of ENBALA Power Networks (USA), Inc.'s application for...

  5. The co-evolutionary dynamics of directed network of spin market agents

    NASA Astrophysics Data System (ADS)

    Horváth, Denis; Kuscsik, Zoltán; Gmitra, Martin

    2006-09-01

    The spin market model [S. Bornholdt, Int. J. Mod. Phys. C 12 (2001) 667] is generalized by employing co-evolutionary principles, where strategies of the interacting and competitive traders are represented by local and global couplings between the nodes of dynamic directed stochastic network. The co-evolutionary principles are applied in the frame of Bak-Sneppen self-organized dynamics [P. Bak, K. Sneppen, Phys. Rev. Lett. 71 (1993) 4083] that includes the processes of selection and extinction actuated by the local (node) fitness. The local fitness is related to orientation of spin agent with respect to the instant magnetization. The stationary regime is formed due to the interplay of self-organization and adaptivity effects. The fat tailed distributions of log-price returns are identified numerically. The non-trivial model consequence is the evidence of the long time market memory indicated by the power-law range of the autocorrelation function of volatility with exponent smaller than one. The simulations yield network topology with broad-scale node degree distribution characterized by the range of exponents 1.3<γin<3 coinciding with social networks.

  6. Blogs and Social Network Sites as Activity Systems: Exploring Adult Informal Learning Process through Activity Theory Framework

    ERIC Educational Resources Information Center

    Heo, Gyeong Mi; Lee, Romee

    2013-01-01

    This paper uses an Activity Theory framework to explore adult user activities and informal learning processes as reflected in their blogs and social network sites (SNS). Using the assumption that a web-based space is an activity system in which learning occurs, typical features of the components were investigated and each activity system then…

  7. Intelligent microchip networks: an agent-on-chip synthesis framework for the design of smart and robust sensor networks

    NASA Astrophysics Data System (ADS)

    Bosse, Stefan

    2013-05-01

    Sensorial materials consisting of high-density, miniaturized, and embedded sensor networks require new robust and reliable data processing and communication approaches. Structural health monitoring is one major field of application for sensorial materials. Each sensor node provides some kind of sensor, electronics, data processing, and communication with a strong focus on microchip-level implementation to meet the goals of miniaturization and low-power energy environments, a prerequisite for autonomous behaviour and operation. Reliability requires robustness of the entire system in the presence of node, link, data processing, and communication failures. Interaction between nodes is required to manage and distribute information. One common interaction model is the mobile agent. An agent approach provides stronger autonomy than a traditional object or remote-procedure-call based approach. Agents can decide for themselves, which actions are performed, and they are capable of flexible behaviour, reacting on the environment and other agents, providing some degree of robustness. Traditionally multi-agent systems are abstract programming models which are implemented in software and executed on program controlled computer architectures. This approach does not well scale to micro-chip level and requires full equipped computers and communication structures, and the hardware architecture does not consider and reflect the requirements for agent processing and interaction. We propose and demonstrate a novel design paradigm for reliable distributed data processing systems and a synthesis methodology and framework for multi-agent systems implementable entirely on microchip-level with resource and power constrained digital logic supporting Agent-On-Chip architectures (AoC). The agent behaviour and mobility is fully integrated on the micro-chip using pipelined communicating processes implemented with finite-state machines and register-transfer logic. The agent behaviour

  8. Dietary supplements: International legal framework and adulteration profiles, and characteristics of products on the Brazilian clandestine market.

    PubMed

    da Justa Neves, Diana Brito; Caldas, Eloisa Dutra

    2015-10-01

    The objectives of this work were to evaluate current legislation on dietary supplements in the United States, the European Union and Brazil, and the profile of adulterated and/or irregular products on these markets. Due to a less restrictive legal framework, a supplement product that is freely available in the US may be considered a drug or even be proscribed in the EU and Brazil, thus giving rise to a clandestine market based on smuggling. From 2007 to 2014, the United States Food and Drug Administration reported 572 cases of supplement adulterations in the country, mainly products for sexual enhancement (41.6%). Data from the European Union Rapid Alert System for Food and Feed showed 929 adulterations during the same period, over 40% due to unauthorized ingredients or undeclared medicines. From 2007 to 2013, the Brazilian Federal Police Department seized 5470 supplement products, 92.2% with an American-declared origin. Qualitative chemical analyses performed on 2898 products found 180 adulterations, 41.1% due to undeclared drugs, mainly anabolic steroids, anorectics and products for erectile dysfunction, all considered medicines in Brazil. Educating the public regarding the potential risks they are taking when consuming adulterated or irregular products is necessary to protect the health of consumers. PMID:26107294

  9. Pharma Pricing & Market Access Europe 2016--Health Network Communications' Tenth Annual Conference (February 23-25, 2016--London, UK).

    PubMed

    D'Souza, P

    2016-03-01

    Tighter national budgets and escalating drug prices continue to present challenges for pharmaceutical market access strategies and societal cost of care. As pharmaceutical companies and medical governmental advisory organizations enter tougher negotiations, hospital trusts and other dispensary firms face barriers to receiving the best medical treatment, and as a result patient access is limited. The 2016 HealthNetwork Communications' Pharma Pricing & Market Access Europe meeting brought together pharmaceutical, medical governmental advisory and stakeholders and market access/pricing consultants, to encourage discussions and negotiations into how to improve the drug pricing system and consequential market access strategies while achieving the respective reimbursement and affordability objectives. PMID:27186595

  10. Marketing.

    ERIC Educational Resources Information Center

    Appel, David L.

    This booklet suggests ways in which institutions--Catholic schools in particular--can move beyond public relations and advertising to engage in the broader arena of marketing with its focus on consumer satisfaction. The first of the book's three chapters reviews the concept of marketing, providing definitions of key terms, clarification of…

  11. A Unified Multiscale Field/Network/Agent Based Modeling Framework for Human and Ecological Health Risk Analysis

    PubMed Central

    Georgopoulos, Panos G.; Isukapalli, Sastry S.

    2011-01-01

    A conceptual framework is presented for multiscale field/network/agent-based modeling to support human and ecological health risk assessments. This framework is based on the representation of environmental dynamics in terms of interacting networks, agents that move across different networks, fields representing spatiotemporal distributions of physical properties, rules governing constraints and interactions, and actors that make decisions affecting the state of the system. Different deterministic and stochastic modeling case studies focusing on environmental exposures and associated risks are provided as examples, utilizing the bidirectional mapping between discrete, agent based approaches and continuous, equation based approaches. These examples include problems describing human health risk assessment, ecological risk assessment, and environmentally caused disease. PMID:19964423

  12. Topology of the South African stock market network across the 2008 financial crisis

    NASA Astrophysics Data System (ADS)

    Majapa, Mohamed; Gossel, Sean Joss

    2016-03-01

    This study uses the cross-correlations in the daily closing prices of the South African Top 100 companies listed on the JSE All share index (ALSI) from June 2003 to June 2013 to compute minimum spanning tree maps. In addition to the full sample, the analysis also uses three sub-periods to investigate the topological evolution before, during, and after the 2008 financial crisis. The findings show that although there is substantial clustering and homogeneity on the JSE, the most connected nodes are in the financial and resources sectors. The sub-sample results further reveal that the JSE network tree shrank in the run-up to, and during the financial crisis, and slowly expanded afterwards. In addition, the different clusters in the network are connected by various nodes that are significantly affected by diversification and credit market dynamics.

  13. A Hybrid Memetic Framework for Coverage Optimization in Wireless Sensor Networks.

    PubMed

    Chen, Chia-Pang; Mukhopadhyay, Subhas Chandra; Chuang, Cheng-Long; Lin, Tzu-Shiang; Liao, Min-Sheng; Wang, Yung-Chung; Jiang, Joe-Air

    2015-10-01

    One of the critical concerns in wireless sensor networks (WSNs) is the continuous maintenance of sensing coverage. Many particular applications, such as battlefield intrusion detection and object tracking, require a full-coverage at any time, which is typically resolved by adding redundant sensor nodes. With abundant energy, previous studies suggested that the network lifetime can be maximized while maintaining full coverage through organizing sensor nodes into a maximum number of disjoint sets and alternately turning them on. Since the power of sensor nodes is unevenly consumed over time, and early failure of sensor nodes leads to coverage loss, WSNs require dynamic coverage maintenance. Thus, the task of permanently sustaining full coverage is particularly formulated as a hybrid of disjoint set covers and dynamic-coverage-maintenance problems, and both have been proven to be nondeterministic polynomial-complete. In this paper, a hybrid memetic framework for coverage optimization (Hy-MFCO) is presented to cope with the hybrid problem using two major components: 1) a memetic algorithm (MA)-based scheduling strategy and 2) a heuristic recursive algorithm (HRA). First, the MA-based scheduling strategy adopts a dynamic chromosome structure to create disjoint sets, and then the HRA is utilized to compensate the loss of coverage by awaking some of the hibernated nodes in local regions when a disjoint set fails to maintain full coverage. The results obtained from real-world experiments using a WSN test-bed and computer simulations indicate that the proposed Hy-MFCO is able to maximize sensing coverage while achieving energy efficiency at the same time. Moreover, the results also show that the Hy-MFCO significantly outperforms the existing methods with respect to coverage preservation and energy efficiency. PMID:25532143

  14. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications

    PubMed Central

    Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

    2015-01-01

    It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs’ route planning for small and medium-scale networks. PMID:26076404

  15. A predicted functional gene network for the plant pathogen Phytophthora infestans as a framework for genomic biology

    PubMed Central

    2013-01-01

    Background Associations between proteins are essential to understand cell biology. While this complex interplay between proteins has been studied in model organisms, it has not yet been described for the oomycete late blight pathogen Phytophthora infestans. Results We present an integrative probabilistic functional gene network that provides associations for 37 percent of the predicted P. infestans proteome. Our method unifies available genomic, transcriptomic and comparative genomic data into a single comprehensive network using a Bayesian approach. Enrichment of proteins residing in the same or related subcellular localization validates the biological coherence of our predictions. The network serves as a framework to query existing genomic data using network-based methods, which thus far was not possible in Phytophthora. We used the network to study the set of interacting proteins that are encoded by genes co-expressed during sporulation. This identified potential novel roles for proteins in spore formation through their links to proteins known to be involved in this process such as the phosphatase Cdc14. Conclusions The functional association network represents a novel genome-wide data source for P. infestans that also acts as a framework to interrogate other system-wide data. In both capacities it will improve our understanding of the complex biology of P. infestans and related oomycete pathogens. PMID:23865555

  16. A Space-Time Network-Based Modeling Framework for Dynamic Unmanned Aerial Vehicle Routing in Traffic Incident Monitoring Applications.

    PubMed

    Zhang, Jisheng; Jia, Limin; Niu, Shuyun; Zhang, Fan; Tong, Lu; Zhou, Xuesong

    2015-01-01

    It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network- based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs' route planning for small and medium-scale networks. PMID:26076404

  17. A neural networks framework for real-time unfolding of neutron spectroscopic data at JET.

    PubMed

    Ronchi, E; Conroy, S; Sundén, E A; Ericsson, G; Hjalmarsson, A; Hellesen, C; Johnson, M G; Weiszflog, M

    2008-10-01

    A determination of fast ion population parameters such as intensity and kinetic temperature is important for fusion reactors. This becomes more challenging with finer time resolution of the measurements, since the limited data in each time slice cause increasing statistical variations in the data. This paper describes a framework using Bayesian-regularized neural networks (NNs) designed for such a task. The method is applied to the TOFOR 2.5 MeV fusion neutron spectrometer at JET. NN training data are generated by random sampling of variables in neutron spectroscopy models. Ranges and probability distributions of the parameters are chosen to match the experimental data. Results have shown good performance both on synthetic and experimental data. The latter was assessed by statistical considerations and by examining the robustness and time consistency of the results. The regularization of the training algorithm allowed for higher time resolutions than simple forward methods. The fast execution time makes this approach suitable for real-time analysis with a time resolution limit in the microsecond time scale. PMID:19068505

  18. A neural networks framework for real-time unfolding of neutron spectroscopic data at JET

    SciTech Connect

    Ronchi, E.; Conroy, S.; Sunden, E. A.; Ericsson, G.; Hjalmarsson, A.; Hellesen, C.; Johnson, M. G.; Weiszflog, M.

    2008-10-15

    A determination of fast ion population parameters such as intensity and kinetic temperature is important for fusion reactors. This becomes more challenging with finer time resolution of the measurements, since the limited data in each time slice cause increasing statistical variations in the data. This paper describes a framework using Bayesian-regularized neural networks (NNs) designed for such a task. The method is applied to the TOFOR 2.5 MeV fusion neutron spectrometer at JET. NN training data are generated by random sampling of variables in neutron spectroscopy models. Ranges and probability distributions of the parameters are chosen to match the experimental data. Results have shown good performance both on synthetic and experimental data. The latter was assessed by statistical considerations and by examining the robustness and time consistency of the results. The regularization of the training algorithm allowed for higher time resolutions than simple forward methods. The fast execution time makes this approach suitable for real-time analysis with a time resolution limit in the microsecond time scale.

  19. A Geographic Information System framework for the dataset visualization in Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Shufean, Md Abu

    In Wireless Sensor Networks (WSNs), collecting data from sensor nodes and analyzing them is a challenging task. A Geographic Information System (GIS) could be a better way to analyze, manage, and represent the dataset collected by sensor nodes. Motivated by these considerations, we proposed a system to visualize the WSN dataset in real time using a software implementation of the GIS framework called ArcGIS. In this research, we have implemented our proposed system where a couple of sensor nodes has been deployed to collect Dissolved Oxygen (DO) and water pH value continuously from the John Gray Center pond of Lamar University. To keep track of each sensor node we have accumulated their precise location, sensing time, and corresponding data in our lab. After analyzing couple of data storing technique, we have decided to use PostGIS (a geospatial database) to store data and developed an ArcGIS centric application. Finally, with the help of that application, a web map was designed combining all different data source layers for end users where all the technical details have been encapsulated behind a base map. This web map has been hosted in a web server so that users sitting in any location can easily access and visualize desired data with a real time update. This research work has been supported by National Science Foundation under Grants CNS-0922888 and CNS-1427838.

  20. a New Framework for Geospatial Site Selection Using Artificial Neural Networks as Decision Rules: a Case Study on Landfill Sites

    NASA Astrophysics Data System (ADS)

    Abujayyab, S. K. M.; Ahamad, M. A. S.; Yahya, A. S.; Saad, A.-M. H. Y.

    2015-10-01

    This paper briefly introduced the theory and framework of geospatial site selection (GSS) and discussed the application and framework of artificial neural networks (ANNs). The related literature on the use of ANNs as decision rules in GSS is scarce from 2000 till 2015. As this study found, ANNs are not only adaptable to dynamic changes but also capable of improving the objectivity of acquisition in GSS, reducing time consumption, and providing high validation. ANNs make for a powerful tool for solving geospatial decision-making problems by enabling geospatial decision makers to implement their constraints and imprecise concepts. This tool offers a way to represent and handle uncertainty. Specifically, ANNs are decision rules implemented to enhance conventional GSS frameworks. The main assumption in implementing ANNs in GSS is that the current characteristics of existing sites are indicative of the degree of suitability of new locations with similar characteristics. GSS requires several input criteria that embody specific requirements and the desired site characteristics, which could contribute to geospatial sites. In this study, the proposed framework consists of four stages for implementing ANNs in GSS. A multilayer feed-forward network with a backpropagation algorithm was used to train the networks from prior sites to assess, generalize, and evaluate the outputs on the basis of the inputs for the new sites. Two metrics, namely, confusion matrix and receiver operating characteristic tests, were utilized to achieve high accuracy and validation. Results proved that ANNs provide reasonable and efficient results as an accurate and inexpensive quantitative technique for GSS.

  1. Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity

    NASA Astrophysics Data System (ADS)

    Sonubi, A.; Arcagni, A.; Stefani, S.; Ausloos, M.

    2016-08-01

    A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

  2. A deadline-aware transmission framework for H.264/AVC video over IEEE 802.11e EDCA wireless networks

    NASA Astrophysics Data System (ADS)

    Du, Jianchao; Chen, Chang Wen

    2010-07-01

    One of the most challenging issues in video transmission over wireless networks is to address the rigid time bounded constraint for video delivery. We propose in this paper a deadline-aware transmission framework (DATF) for video over IEEE 802.11e EDCA wireless networks. In this new framework, we estimate the deadline for time bounded video delivery for each packet in queues at MAC layer according to the sequence number of a frame a given video data packet belonging to as well as the current network delay. Then, the MAC layer determines whether a packet should be sent or should be dropped based on the estimated deadline information. To accomplish the scheme of DATF, we propose to modify the mapping scheme in IEEE 802.11e EDCA to facilitate unequal deadline requirement of video packets. Instead of mapping all video packets into class AC_VI, which is defined for video data in IEEE 802.11e EDCA, we differentiate video packets further based on the dependency characteristics of a given frame type. The proposed DATF scheme has been implemented with NS-2 simulation based on the scenario of wired-cum-wireless network architecture. We compare the proposed approach with several competing schemes and the simulation results show that the proposed scheme outperforms these competing schemes in terms of both wireless networking metrics and received video quality.

  3. Networking Activities and Perceptions of HIV Risk Among Male Migrant Market Vendors in China

    PubMed Central

    Wang, Wenqing; Muessig, Kathryn E.; Li, Mingqiang; Zhang, Yingxia

    2013-01-01

    HIV research among internal migrants in China has not fully explored the contexts and perceptions of “risk”. In 2011, urban markets in Liuzhou, China were mapped, and sixty male vendors, age 22 to 56, were selected for in-depth interviews on migration, social and family life, and perceptions and practices of sexual risk behavior. Participants were evenly divided among higher income shop and small stall vendors. All men were sexually active. Only the shop vendors reported non-marital sexual partners, including concurrent partners (n=15), commercial partners (n=10), and other sexual relationships (n=11). Shop vendors engaged in networking activities that facilitated commercial and non-commercial high-risk sex. Perceptions of HIV risk from commercial sex led some men to doubt the protective ability of condoms and rely on local (unproven) self-protection techniques. Networking activities played a role in high-risk sex and shaping migrants' risk perceptions and health practices. The networks created through these processes could also be used to facilitate health promotion activities. PMID:23572155

  4. Insight into the crystallization of amorphous imine-linked polymer networks to 2D covalent organic frameworks.

    PubMed

    Smith, Brian J; Overholts, Anna C; Hwang, Nicky; Dichtel, William R

    2016-03-01

    We explore the crystallization of a high surface area imine-linked two-dimensional covalent organic framework (2D COF). The growth process reveals rapid initial formation of an amorphous network that subsequently crystallizes into the layered 2D network. The metastable amorphous polymer may be isolated and resubjected to growth conditions to form the COF. These experiments provide the first mechanistic insight into the mechanism of imine-linked 2D COF formation, which is distinct from that of boronate-ester linked COFs. PMID:26857035

  5. Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability.

    PubMed

    van der Linden, Joost H; Narsilio, Guillermo A; Tordesillas, Antoinette

    2016-08-01

    We present a data-driven framework to study the relationship between fluid flow at the macroscale and the internal pore structure, across the micro- and mesoscales, in porous, granular media. Sphere packings with varying particle size distribution and confining pressure are generated using the discrete element method. For each sample, a finite element analysis of the fluid flow is performed to compute the permeability. We construct a pore network and a particle contact network to quantify the connectivity of the pores and particles across the mesoscopic spatial scales. Machine learning techniques for feature selection are employed to identify sets of microstructural properties and multiscale complex network features that optimally characterize permeability. We find a linear correlation (in log-log scale) between permeability and the average closeness centrality of the weighted pore network. With the pore network links weighted by the local conductance, the average closeness centrality represents a multiscale measure of efficiency of flow through the pore network in terms of the mean geodesic distance (or shortest path) between all pore bodies in the pore network. Specifically, this study objectively quantifies a hypothesized link between high permeability and efficient shortest paths that thread through relatively large pore bodies connected to each other by high conductance pore throats, embodying connectivity and pore structure. PMID:27627377

  6. Network-on-chip emulation framework for multimedia SoC development

    NASA Astrophysics Data System (ADS)

    Singla, Garbí; Tobajas, Félix; de Armas, Valentín.

    2013-05-01

    Current tendencies of consumer electronics have envisaged multiprocessor System-on-Chip (SoC) as a promising solution for the high performance embedding systems, and, in this scenario, Network-on-chip communication paradigm is considered as a way to improve on-chip communication efficiency. In this paper, a NoC based SoC emulation framework is designed and implemented on a low-cost FPGA device. The objective of this work is the design and implementation of a prototyping platform with NoC topology, which provides a demonstrator for the implementation of multimedia applications. The emulation platform will allow evaluation, comparison, and verification of different aspects of a NoC design for SoCs intended for the execution of multimedia applications. The proposed emulation platform consists of different type of functional IP blocks (microprocessors, memory blocks, peripherals, additional blocks, etc.) interconnected through an interconnection infrastructure based on NoC. In order to provide a low-cost solution, the platform design is restricted to use a single FPGA, resulting in a low-scale SoC due to the limited resources available in the FPGA used. However, the proposed design may be scalable and replicate in large scale FPGA or multi-FPGA devices to increase emulation performance. In this work, a design flow, which integrates different commercial EDA tools, is presented, and integration process is discussed in detail due to problems experienced in this stage. The platform is fully implemented on a Xilinx Spartan-6 LX45T FPGA and special attention is given to verification and floorplanning stages. Finally, various multimedia applications with real-time requirements are executed on the NoC-based SoC platform. At this stage, the performance results are analyzed according to the type of application, as well as the number of processors required.

  7. Data Quality Control of the French Permanent Broadband Network in the RESIF Framework.

    NASA Astrophysics Data System (ADS)

    Grunberg, M.; Lambotte, S.; Engels, F.

    2014-12-01

    In the framework of the RESIF (Réseau Sismologique et géodésique Français) project, a new information system is setting up, allowing the improvement of the management and the distribution of high quality data from the different elements of RESIF. Within this information system, EOST (in Strasbourg) is in charge of collecting real-time permanent broadband seismic waveform, and performing Quality Control on these data. The real-time and validated data set are pushed to the French National Distribution Center (Isterre/Grenoble) to make them publicly available. Furthermore EOST hosts the BCSF-ReNaSS, in charge of the French metropolitan seismic bulletin. This allows to benefit from some high-end quality control based on the national and world-wide seismicity. Here we present the real-time seismic data flow from the stations of the French National Broad Band Network to EOST, and then, the data Quality Control procedures that were recently installed, including some new developments.The data Quality Control consists in applying a variety of processes to check the consistency of the whole system from the stations to the data center. This allows us to verify that instruments and data transmission are operating correctly. Moreover, time quality is critical for most of the scientific data applications. To face this challenge and check the consistency of polarities and amplitudes, we deployed several high-end processes including a noise correlation procedure to check for timing accuracy (intrumental time errors result in a time-shift of the whole cross-correlation, clearly distinct from those due to change in medium physical properties), and a systematic comparison of synthetic and real data for teleseismic earthquakes of magnitude larger than 6.5 to detect timing errors as well as polarity and amplitude problems.

  8. Review on the worldwide regulatory framework for biosimilars focusing on the Mexican case as an emerging market in Latin America.

    PubMed

    Ibarra-Cabrera, Ricardo; Mena-Pérez, Sandra Carolina; Bondani-Guasti, Augusto; García-Arrazola, Roeb

    2013-12-01

    The global biopharmaceutical market is worth over $100 billion USD. Nearly 90% of these products will lose their patent in the next ten years, leading to the commercialization of their subsequent versions, known as 'biosimilars'. Biosimilars are much more complex molecules than chemically synthesized generics in terms of size, structure, stability, microheterogeneity, manufacture, etc. Therefore, a specific regulatory framework is needed in order to demonstrate their comparability with innovative products, as well as their quality, safety and efficacy. The EU published the first regulatory pathway in 2005 and has approved 14 biosimilars. Mexico has recently developed a clear regulatory pathway for these products. Their legal basis was established in Article 222 Bis of General Law of Health in 2009, clear specifications in the Regulation for Health Goods in 2011, and further requirements in the Mexican Official Norm NOM-EM-001-SSA1-2012. The aim of this review is to summarize the regulatory pathways for biosimilars in the world with a special focus on Mexican experience, so as contribute to the development of regulations in other countries. PMID:23714280

  9. Directed Growth of Metal-Organic Frameworks and Their Derived Carbon-Based Network for Efficient Electrocatalytic Oxygen Reduction.

    PubMed

    Li, Zhenhua; Shao, Mingfei; Zhou, Lei; Zhang, Ruikang; Zhang, Cong; Wei, Min; Evans, David G; Duan, Xue

    2016-03-23

    A honeycomb-like carbon-based network is obtained by in situ nucleation and directed growth of metal-organic framework (MOF) arrays on the surface of layered double hydroxide (LDH) nanoplatelets, followed by a subsequent pyrolysis process, which exhibits largely enhanced electrocatalytic ORR performances. A successful paradigm for the directed growth of highly oriented MOF arrays is demonstrated, with potential applications for energy storage and conversion. PMID:26808408

  10. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology

    PubMed Central

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

  11. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-offs on Phenotype Robustness in Biological Networks. Part III: Synthetic Gene Networks in Synthetic Biology.

    PubMed

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental

  12. Executive Leadership in School Improvement Networks: A Conceptual Framework and Agenda for Research

    ERIC Educational Resources Information Center

    Peurach, Donald J.; Gumus, Emine

    2011-01-01

    The purpose of this analysis is to improve understanding of executive leadership in school improvement networks: for example, networks supported by comprehensive school reform providers, charter management organizations, and education management organizations. In this analysis, we review the literature on networks and executive leadership. We draw…

  13. User-Centric Secure Cross-Site Interaction Framework for Online Social Networking Services

    ERIC Educational Resources Information Center

    Ko, Moo Nam

    2011-01-01

    Social networking service is one of major technological phenomena on Web 2.0. Hundreds of millions of users are posting message, photos, and videos on their profiles and interacting with other users, but the sharing and interaction are limited within the same social networking site. Although users can share some content on a social networking site…

  14. Resource allocation in integrated delivery systems and healthcare networks: a proposed framework to guide ethical thinking.

    PubMed

    Macdonald, M

    1999-01-01

    Drawing on a management perspective and the literature, this article suggests an ethical framework to be used at the meso or community level of resource allocation in a Canadian setting. The suggested framework enlarges on the program-level framework developed by Meslin et al primarily by building in stakeholder inclusiveness and public accountability, both of which are essential to resource allocation at the population-based level. PMID:10788068

  15. A network-based framework for assessing infrastructure resilience: a case study of the London metro system.

    PubMed

    Chopra, Shauhrat S; Dillon, Trent; Bilec, Melissa M; Khanna, Vikas

    2016-05-01

    Modern society is increasingly dependent on the stability of a complex system of interdependent infrastructure sectors. It is imperative to build resilience of large-scale infrastructures like metro systems for addressing the threat of natural disasters and man-made attacks in urban areas. Analysis is needed to ensure that these systems are capable of withstanding and containing unexpected perturbations, and develop heuristic strategies for guiding the design of more resilient networks in the future. We present a comprehensive, multi-pronged framework that analyses information on network topology, spatial organization and passenger flow to understand the resilience of the London metro system. Topology of the London metro system is not fault tolerant in terms of maintaining connectivity at the periphery of the network since it does not exhibit small-world properties. The passenger strength distribution follows a power law, suggesting that while the London metro system is robust to random failures, it is vulnerable to disruptions on a few critical stations. The analysis further identifies particular sources of structural and functional vulnerabilities that need to be mitigated for improving the resilience of the London metro network. The insights from our framework provide useful strategies to build resilience for both existing and upcoming metro systems. PMID:27146689

  16. A Web Service-Based Framework Model for People-Centric Sensing Applications Applied to Social Networking

    PubMed Central

    Nunes, David; Tran, Thanh-Dien; Raposo, Duarte; Pinto, André; Gomes, André; Silva, Jorge Sá

    2012-01-01

    As the Internet evolved, social networks (such as Facebook) have bloomed and brought together an astonishing number of users. Mashing up mobile phones and sensors with these social environments enables the creation of people-centric sensing systems which have great potential for expanding our current social networking usage. However, such systems also have many associated technical challenges, such as privacy concerns, activity detection mechanisms or intermittent connectivity, as well as limitations due to the heterogeneity of sensor nodes and networks. Considering the openness of the Web 2.0, good technical solutions for these cases consist of frameworks that expose sensing data and functionalities as common Web-Services. This paper presents our RESTful Web Service-based model for people-centric sensing frameworks, which uses sensors and mobile phones to detect users’ activities and locations, sharing this information amongst the user’s friends within a social networking site. We also present some screenshot results of our experimental prototype. PMID:22438732

  17. Neural network modeling and an uncertainty analysis in Bayesian framework: A case study from the KTB borehole site

    NASA Astrophysics Data System (ADS)

    Maiti, Saumen; Tiwari, Ram Krishna

    2010-10-01

    A new probabilistic approach based on the concept of Bayesian neural network (BNN) learning theory is proposed for decoding litho-facies boundaries from well-log data. We show that how a multi-layer-perceptron neural network model can be employed in Bayesian framework to classify changes in litho-log successions. The method is then applied to the German Continental Deep Drilling Program (KTB) well-log data for classification and uncertainty estimation in the litho-facies boundaries. In this framework, a posteriori distribution of network parameter is estimated via the principle of Bayesian probabilistic theory, and an objective function is minimized following the scaled conjugate gradient optimization scheme. For the model development, we inflict a suitable criterion, which provides probabilistic information by emulating different combinations of synthetic data. Uncertainty in the relationship between the data and the model space is appropriately taken care by assuming a Gaussian a priori distribution of networks parameters (e.g., synaptic weights and biases). Prior to applying the new method to the real KTB data, we tested the proposed method on synthetic examples to examine the sensitivity of neural network hyperparameters in prediction. Within this framework, we examine stability and efficiency of this new probabilistic approach using different kinds of synthetic data assorted with different level of correlated noise. Our data analysis suggests that the designed network topology based on the Bayesian paradigm is steady up to nearly 40% correlated noise; however, adding more noise (˜50% or more) degrades the results. We perform uncertainty analyses on training, validation, and test data sets with and devoid of intrinsic noise by making the Gaussian approximation of the a posteriori distribution about the peak model. We present a standard deviation error-map at the network output corresponding to the three types of the litho-facies present over the entire litho

  18. Trading Rules on Stock Markets Using Genetic Network Programming with Reinforcement Learning and Importance Index

    NASA Astrophysics Data System (ADS)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

    Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

  19. A comprehensive framework for post-earthquake rehabilitation plan of lifeline networks

    SciTech Connect

    Liang, J.W.

    1996-12-01

    Post-earthquake rehabilitation process of lifeline networks can be divided into three stages: emergency operation, short-term restoration, and long-term restoration, and different rehabilitation measures should be taken for different stages. This paper outlines the post-earthquake rehabilitation plan of lifeline networks which is being developed for Tianjin City. The objective of this plane is to shorten the time for restoration of lifeline networks and to reduce secondary disasters.

  20. Envirodynamics on river networks: A minimal complexity framework for transport studies

    NASA Astrophysics Data System (ADS)

    Zaliapin, Ilya; Foufoula-Georgiou, Efi; Ghil, Michael

    2010-05-01

    In this study we apply complex-network methods to the problems of environmental transport on river networks. Such problems involve the flux of water, sediment, pollutants and biota. We establish statistical properties of a flow along a directed branching network and suggest a compact representation for it. The downstream transport is treated as a particular case of nearest-neighbor hierarchical aggregation with respect to the metric induced by the branching structure of the river network. Specifically, we describe the static geometric structure of a drainage network by a tree, referred to as the static tree, and introduce an associated dynamic tree that describes the transport along the static tree. It is well known that the static branching structure of river networks can be described by self-similar trees; we demonstrate that the corresponding dynamic trees are also self-similar, albeit with different values of the self-similarity parameters. Furthermore, we introduce and study a related object, which we call a dynamic network; this network reflects the actual physical mixing of fluxes that propagate along a static tree. Boolean delay equations (BDEs) are used to model the downstream transport along real and synthetic river networks. We report an unexpected phase transition in the environmental dynamics of real river basins, demonstrate the universal features of this transition, and seek to interpret it in hydrological terms.

  1. Unified Framework for Robust Estimation of Brain Networks From fMRI Using Temporal and Spatial Correlation Analyses

    PubMed Central

    Wang, Yongmei Michelle; Xia, Jing

    2011-01-01

    There is a rapidly growing interest in the neuroimaging field to use functional magnetic resonance imaging (fMRI) to explore brain networks, i.e., how regions of the brain communicate with one another. This paper presents a general and novel statistical framework for robust and more complete estimation of brain functional connectivity from fMRI based on correlation analyses and hypothesis testing. In addition to the ability of examining the correlations with each individual seed as in the standard and existing methods, the proposed framework can detect functional interactions by simultaneously examining multiseed correlations via multiple correlation coefficients. Spatially structured noise in fMRI is also taken into account during the identification of functional interconnection networks through noncentral F hypothesis tests. The associated issues for the multiple testing and the effective degrees-of-freedom are considered as well. Furthermore, partial multiple correlations are introduced and formulated to measure any additional task-induced but not stimulus-locked relation over brain regions so that we can take the analysis of functional connectivity closer to the characterization of direct functional interactions of the brain. Evaluation for accuracy and advantages, and comparisons of the new approaches in the presented general framework are performed using both realistic synthetic data and in vivo fMRI data. PMID:19237342

  2. Developmental Evaluation Framework for Innovation and Learning Networks: Integration of the Structure, Process and Outcomes

    ERIC Educational Resources Information Center

    Ramstad, Elise

    2009-01-01

    Purpose: During the past decade new types of broader networks that aim to achieve widespread effects in the working life have emerged. These are typically based on an interactive innovation approach, where knowledge is created jointly together with diverse players. At the moment, the challenge is how to evaluate these complex networks and learning…

  3. Network-Based Leadership Development: A Guiding Framework and Resources for Management Educators

    ERIC Educational Resources Information Center

    Cullen-Lester, Kristin L.; Woehler, Meredith L.; Willburn, Phil

    2016-01-01

    Management education and leadership development has traditionally focused on improving human capital (i.e., knowledge, skills, and abilities). Social capital, networks, and networking skills have received less attention. When this content has been incorporated into learning and development experiences, it has often been more ad hoc and has…

  4. A Markovian event-based framework for stochastic spiking neural networks.

    PubMed

    Touboul, Jonathan D; Faugeras, Olivier D

    2011-11-01

    In spiking neural networks, the information is conveyed by the spike times, that depend on the intrinsic dynamics of each neuron, the input they receive and on the connections between neurons. In this article we study the Markovian nature of the sequence of spike times in stochastic neural networks, and in particular the ability to deduce from a spike train the next spike time, and therefore produce a description of the network activity only based on the spike times regardless of the membrane potential process. To study this question in a rigorous manner, we introduce and study an event-based description of networks of noisy integrate-and-fire neurons, i.e. that is based on the computation of the spike times. We show that the firing times of the neurons in the networks constitute a Markov chain, whose transition probability is related to the probability distribution of the interspike interval of the neurons in the network. In the cases where the Markovian model can be developed, the transition probability is explicitly derived in such classical cases of neural networks as the linear integrate-and-fire neuron models with excitatory and inhibitory interactions, for different types of synapses, possibly featuring noisy synaptic integration, transmission delays and absolute and relative refractory period. This covers most of the cases that have been investigated in the event-based description of spiking deterministic neural networks. PMID:21499739

  5. Online Data Monitoring Framework Based on Histogram Packaging in Network Distributed Data Acquisition Systems

    NASA Astrophysics Data System (ADS)

    Konno, T.; Cabarera, A.; Ishitsuka, M.; Kuze, M.; Sakamoto, Y.

    2011-12-01

    "Online monitor framework" is a new general software framework for online data monitoring, which provides a way to collect information from online systems, including data acquisition, and displays them to shifters far from experimental sites. "Monitor Server", a core system in this framework gathers the monitoring information from the online subsystems and the information is handled as collections of histograms named "Histogram Package". Monitor Server broadcasts the histogram packages to "Monitor Viewers", graphical user interfaces in the framework. We developed two types of the viewers with different technologies: Java and web browser. We adapted XML based file for the configuration of GUI components on the windows and graphical objects on the canvases. Monitor Viewer creates its GUIs automatically with the configuration files.This monitoring framework has been developed for the Double Chooz reactor neutrino oscillation experiment in France, but can be extended for general application to be used in other experiments. This document reports the structure of the online monitor framework with some examples from the adaption to the Double Chooz experiment.

  6. Control of Multilayer Networks

    PubMed Central

    Menichetti, Giulia; Dall’Asta, Luca; Bianconi, Ginestra

    2016-01-01

    The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has been characterized only on isolated networks, while the vast majority of complex systems are formed by multilayer networks. Here we build a theoretical framework for the linear controllability of multilayer networks by mapping the problem into a combinatorial matching problem. We found that correlating the external signals in the different layers can significantly reduce the multiplex network robustness to node removal, as it can be seen in conjunction with a hybrid phase transition occurring in interacting Poisson networks. Moreover we observe that multilayer networks can stabilize the fully controllable multiplex network configuration that can be stable also when the full controllability of the single network is not stable. PMID:26869210

  7. Frameworks for Understanding the Nature of Interactions, Networking, and Community in a Social Networking Site for Academic Practice

    ERIC Educational Resources Information Center

    Conole, Grainne; Galley, Rebecca; Culver, Juliette

    2011-01-01

    This paper describes a new social networking site, Cloudworks, which has been developed to enable discussion and sharing of learning and teaching ideas/designs and to promote reflective academic practice. The site aims to foster new forms of social and participatory practices (peer critiquing, sharing, user-generated content, aggregation, and…

  8. A Three-Dimensional Dynamic Metal-Organic Framework with Fourfold Interpenetrating Diamondoid Networks and Selective Adsorption Properties.

    PubMed

    Ju, Ping; Jiang, Long; Lu, Tong-Bu

    2015-07-01

    A three-dimensional metal-organic framework (1) with fourfold interpenetrating diamondoid networks was constructed using a macrocyclic nickel(II) complex and a tetracarboxylic ligand 4,4',4″,4‴-(cyclohexane-1,2-diyibis(azanetriyl))tetrakis(methylene)tetrabenzoic acid as building blocks. Despite the fourfold interpenetration, 1 possesses one-dimensional channels that are occupied by water and CH3CN guest molecules. Once the guest molecules were removed, the framework and pores in desolvated 1 are dynamic with large adsorption hysteresis loops, which exhibit selective gas adsorption for CO2 at 195 K over N2 and H2 at 77 K and selective adsorption for methanol, ethanol, and n-propanol over isopropanol at 298 K. PMID:26083145

  9. Development of NETCONF-Based Network Management Systems in Web Services Framework

    NASA Astrophysics Data System (ADS)

    Iijima, Tomoyuki; Kimura, Hiroyasu; Kitani, Makoto; Atarashi, Yoshifumi

    To develop a network management system (NMS) more easily, the authors developed an application programming interface (API) for configuring network devices. Because this API is used in a Java development environment, an NMS can be developed by utilizing the API and other commonly available Java libraries. It is thus possible to easily develop an NMS that is highly compatible with other IT systems. And operations that are generated from the API and that are exchanged between the NMS and network devices are based on NETCONF, which is standardized by the Internet Engineering Task Force (IETF) as a next-generation network-configuration protocol. Adopting a standardized technology ensures that the NMS developed by using the API can manage network devices provided from multi-vendors in a unified manner. Furthermore, the configuration items exchanged over NETCONF are specified in an object-oriented design. They are therefore easier to manage than such items in the Management Information Base (MIB), which is defined as data to be managed by the Simple Network Management Protocol (SNMP). We actually developed several NMSs by using the API. Evaluation of these NMSs showed that, in terms of configuration time and development time, the NMS developed by using the API performed as well as NMSs developed by using a command line interface (CLI) and SNMP. The NMS developed by using the API showed feasibility to achieve “autonomic network management” and “high interoperability with IT systems.”

  10. A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

    SciTech Connect

    Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; Ukkusuri, Satish V.

    2015-01-31

    Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plans in terms of average delay, number of stops, and vehicular emissions at the network level.

  11. A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

    DOE PAGESBeta

    Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; Ukkusuri, Satish V.

    2015-01-31

    Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

  12. Use of a Proven Framework for Computer Decision Support within the Intermountain Healthcare Network.

    PubMed

    Evans, R Scott; Lloyd, James F; Johnson, Kyle V; Howe, Stephen; Tripp, Jacob S

    2015-01-01

    Hospitalized patients in the U.S. do not always receive optimal care. In light of this, Computerized Decision Support (CDS) has been recommended to for the improvement of patient care. A number of methodologies, standards, and frameworks have been developed to facilitate the development and interoperability of computerized clinical guidelines and CDS logic. In addition, Health Information Exchange using Service-Oriented Architecture holds some promise to help realize that goal. We have used a framework at Intermountain Healthcare that employs familiar programming languages and technology to develop over 40 CDS applications during the past 13 years, which clinicians are dependent on each day. This paper describes the framework, technology, and CDS application development methods, while providing three distinct examples of applications that illustrate the need and use of the framework for patient care improvement. The main limitation of this framework is its dependence on point-to-point interfaces to access patient data. We look forward to the use of validated and accessible Service-Oriented Architecture to facilitate patient data access across diverse databases. PMID:26262053

  13. MATIN: a random network coding based framework for high quality peer-to-peer live video streaming.

    PubMed

    Barekatain, Behrang; Khezrimotlagh, Dariush; Aizaini Maarof, Mohd; Ghaeini, Hamid Reza; Salleh, Shaharuddin; Quintana, Alfonso Ariza; Akbari, Behzad; Cabrera, Alicia Triviño

    2013-01-01

    In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay. PMID:23940530

  14. MATIN: A Random Network Coding Based Framework for High Quality Peer-to-Peer Live Video Streaming

    PubMed Central

    Barekatain, Behrang; Khezrimotlagh, Dariush; Aizaini Maarof, Mohd; Ghaeini, Hamid Reza; Salleh, Shaharuddin; Quintana, Alfonso Ariza; Akbari, Behzad; Cabrera, Alicia Triviño

    2013-01-01

    In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay. PMID:23940530

  15. A Computational Framework for Quantifying and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation

    NASA Astrophysics Data System (ADS)

    Cioaca, Alexandru

    A deep scientific understanding of complex physical systems, such as the atmosphere, can be achieved neither by direct measurements nor by numerical simulations alone. Data assimila- tion is a rigorous procedure to fuse information from a priori knowledge of the system state, the physical laws governing the evolution of the system, and real measurements, all with associated error statistics. Data assimilation produces best (a posteriori) estimates of model states and parameter values, and results in considerably improved computer simulations. The acquisition and use of observations in data assimilation raises several important scientific questions related to optimal sensor network design, quantification of data impact, pruning redundant data, and identifying the most beneficial additional observations. These questions originate in operational data assimilation practice, and have started to attract considerable interest in the recent past. This dissertation advances the state of knowledge in four dimensional variational (4D-Var) data assimilation by developing, implementing, and validating a novel computational framework for estimating observation impact and for optimizing sensor networks. The framework builds on the powerful methodologies of second-order adjoint modeling and the 4D-Var sensitivity equations. Efficient computational approaches for quantifying the observation impact include matrix free linear algebra algorithms and low-rank approximations of the sensitivities to observations. The sensor network configuration problem is formulated as a meta-optimization problem. Best values for parameters such as sensor location are obtained by optimizing a performance criterion, subject to the constraint posed by the 4D-Var optimization. Tractable computational solutions to this "optimization-constrained" optimization problem are provided. The results of this work can be directly applied to the deployment of intelligent sensors and adaptive observations, as well as

  16. Networks and the ecology of parasite transmission: A framework for wildlife parasitology☆

    PubMed Central

    Godfrey, Stephanie S.

    2013-01-01

    Social network analysis has recently emerged as a popular tool for understanding disease transmission in host populations. Although social networks have most extensively been applied to modelling the transmission of diseases through human populations, more recently the method has been applied to wildlife populations. The majority of examples from wildlife involve modelling the transmission of contagious microbes (mainly viruses and bacteria), normally in context of understanding wildlife disease epidemics. However, a growing number of studies have used networks to explore the ecology of parasite transmission in wildlife populations for a range of endemic parasites representing a diversity of life cycles and transmission methods. This review addresses the application of network models in representing the transmission of parasites with more complex life cycles, and illustrates the way in which this approach can be used to answer ecological questions about the transmission of parasites in wildlife populations. PMID:24533342

  17. Cluster imaging of multi-brain networks (CIMBN): a general framework for hyperscanning and modeling a group of interacting brains.

    PubMed

    Duan, Lian; Dai, Rui-Na; Xiao, Xiang; Sun, Pei-Pei; Li, Zheng; Zhu, Chao-Zhe

    2015-01-01

    Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called "Cluster Imaging of Multi-brain Networks" (CIMBN). CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS) systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN) modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network's properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology. PMID:26283906

  18. Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions

    PubMed Central

    Testolin, Alberto; Zorzi, Marco

    2016-01-01

    Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage. PMID:27468262

  19. Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions.

    PubMed

    Testolin, Alberto; Zorzi, Marco

    2016-01-01

    Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage. PMID:27468262

  20. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology

    PubMed Central

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240

  1. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Trade-off on Phenotype Robustness in Biological Networks Part I: Gene Regulatory Networks in Systems and Evolutionary Biology.

    PubMed

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240

  2. How many suffice? A computational framework for sizing sentinel surveillance networks

    PubMed Central

    2013-01-01

    Background Data from surveillance networks help epidemiologists and public health officials detect emerging diseases, conduct outbreak investigations, manage epidemics, and better understand the mechanics of a particular disease. Surveillance networks are used to determine outbreak intensity (i.e., disease burden) and outbreak timing (i.e., the start, peak, and end of the epidemic), as well as outbreak location. Networks can be tuned to preferentially perform these tasks. Given that resources are limited, careful site selection can save costs while minimizing performance loss. Methods We study three different site placement algorithms: two algorithms based on the maximal coverage model and one based on the K-median model. The maximal coverage model chooses sites that maximize the total number of people within a specified distance of a site. The K-median model minimizes the sum of the distances from each individual to the individual’s nearest site. Using a ground truth dataset consisting of two million de-identified Medicaid billing records representing eight complete influenza seasons and an evaluation function based on the Huff spatial interaction model, we empirically compare networks against the existing Iowa Department of Public Health influenza-like illness network by simulating the spread of influenza across the state of Iowa. Results We show that it is possible to design a network that achieves outbreak intensity performance identical to the status quo network using two fewer sites. We also show that if outbreak timing detection is of primary interest, it is actually possible to create a network that matches the existing network’s performance using 59% fewer sites. Conclusions By simulating the spread of influenza across the state of Iowa, we show that our methods are capable of designing networks that perform better than the status quo in terms of both outbreak intensity and timing. Additionally, our results suggest that network size may only play a

  3. Welfare state, labour market inequalities and health. In a global context: an integrated framework. SESPAS report 2010.

    PubMed

    Muntaner, Carles; Benach, Joan; Chung, Haejoo; Edwin, N G; Schrecker, Ted

    2010-12-01

    Since the nineteen seventies, high- and low-income countries have undergone a pattern of transnational economic and cultural integration known as globalization. The weight of the available evidence suggests that the effects of globalization on labor markets have increased economic inequality and various forms of economic insecurity that negatively affect workers' health. Research on the relation between labor markets and health is hampered by the social invisibility of many of these health inequalities. Empirical evidence of the impact of employment relations on health inequalities is scarce for low-income countries, small firms, rural settings, and sectors of the economy in which "informality" is widespread. Information is also scarce on the effectiveness of labor market interventions in reducing health inequalities. This pattern is likely to continue in the future unless governments adopt active labor market policies. Such policies include creating jobs through state intervention, regulating the labor market to protect employment, supporting unions, and ensuring occupational safety and health standards. PMID:21075490

  4. Hubba: hub objects analyzer--a framework of interactome hubs identification for network biology.

    PubMed

    Lin, Chung-Yen; Chin, Chia-Hao; Wu, Hsin-Hung; Chen, Shu-Hwa; Ho, Chin-Wen; Ko, Ming-Tat

    2008-07-01

    One major task in the post-genome era is to reconstruct proteomic and genomic interacting networks using high-throughput experiment data. To identify essential nodes/hubs in these interactomes is a way to decipher the critical keys inside biochemical pathways or complex networks. These essential nodes/hubs may serve as potential drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens. Hub Objects Analyzer (Hubba) is a web-based service for exploring important nodes in an interactome network generated from specific small- or large-scale experimental methods based on graph theory. Two characteristic analysis algorithms, Maximum Neighborhood Component (MNC) and Density of Maximum Neighborhood Component (DMNC) are developed for exploring and identifying hubs/essential nodes from interactome networks. Users can submit their own interaction data in PSI format (Proteomics Standards Initiative, version 2.5 and 1.0), tab format and tab with weight values. User will get an email notification of the calculation complete in minutes or hours, depending on the size of submitted dataset. Hubba result includes a rank given by a composite index, a manifest graph of network to show the relationship amid these hubs, and links for retrieving output files. This proposed method (DMNC || MNC) can be applied to discover some unrecognized hubs from previous dataset. For example, most of the Hubba high-ranked hubs (80% in top 10 hub list, and >70% in top 40 hub list) from the yeast protein interactome data (Y2H experiment) are reported as essential proteins. Since the analysis methods of Hubba are based on topology, it can also be used on other kinds of networks to explore the essential nodes, like networks in yeast, rat, mouse and human. The website of Hubba is freely available at http://hub.iis.sinica.edu.tw/Hubba. PMID:18503085

  5. Facilitating Organizational Information Access in Global Network Environments: Towards a New Framework for Intranet Design.

    ERIC Educational Resources Information Center

    Detlor, Brian

    This paper proposes a user-centered framework for intranet design that is based on an understanding of people, their typical problems, information behaviors, and situated contexts. It is argued that by adopting such an approach, intranets can be designed which facilitate organizational information access and use. The first section of the paper…

  6. An Open Framework for Low-Latency Communications across the Smart Grid Network

    ERIC Educational Resources Information Center

    Sturm, John Andrew

    2011-01-01

    The recent White House (2011) policy paper for the Smart Grid that was released on June 13, 2011, "A Policy Framework for the 21st Century Grid: Enabling Our Secure Energy Future," defines four major problems to be solved and the one that is addressed in this dissertation is Securing the Grid. Securing the Grid is referred to as one of…

  7. A Re-Examination of the Community of Inquiry Framework: Social Network and Content Analysis

    ERIC Educational Resources Information Center

    Shea, Peter; Hayes, Suzanne; Vickers, Jason; Gozza-Cohen, Mary; Uzuner, Sedef; Mehta, Ruchi; Valchova, Anna; Rangan, Prahalad

    2010-01-01

    This study provides a simultaneous examination of all components of the Community of Inquiry (CoI) framework (Garrison, Anderson & Archer, 2000; Anderson, Rourke, Garrison & Archer, 2001; and Rourke, Garrison, Anderson & Archer, 1999) and seeks to extend previous work into the nature, development, and relationships between the constructs of…

  8. Evaluating Action-Learning and Professional Networking as a Framework for Educational Leadership Capacity Development

    ERIC Educational Resources Information Center

    Gunn, Cathy; Lefoe, Geraldine

    2013-01-01

    This article describes the responsive evaluation component of an educational leadership capacity-building initiative developed at one Australian university and implemented by three others. The project aimed to develop, implement and disseminate an innovative framework to address the national strategic goal to increase the pool of qualified…

  9. ENERGY-NET (Energy, Environment and Society Learning Network): Enhancing opportunities for learning using an Earth systems science framework

    NASA Astrophysics Data System (ADS)

    Elliott, E. M.; Bain, D. J.; Divers, M. T.; Crowley, K. J.; Povis, K.; Scardina, A.; Steiner, M.

    2012-12-01

    We describe a newly funded collaborative NSF initiative, ENERGY-NET (Energy, Environment and Society Learning Network), that brings together the Carnegie Museum of Natural History (CMNH) with the Learning Science and Geoscience research strengths at the University of Pittsburgh. ENERGY-NET aims to create rich opportunities for participatory learning and public education in the arena of energy, the environment, and society using an Earth systems science framework. We build upon a long-established teen docent program at CMNH and to form Geoscience Squads comprised of underserved teens. Together, the ENERGY-NET team, including museum staff, experts in informal learning sciences, and geoscientists spanning career stage (undergraduates, graduate students, faculty) provides inquiry-based learning experiences guided by Earth systems science principles. Together, the team works with Geoscience Squads to design "Exploration Stations" for use with CMNH visitors that employ an Earth systems science framework to explore the intersecting lenses of energy, the environment, and society. The goals of ENERGY-NET are to: 1) Develop a rich set of experiential learning activities to enhance public knowledge about the complex dynamics between Energy, Environment, and Society for demonstration at CMNH; 2) Expand diversity in the geosciences workforce by mentoring underrepresented teens, providing authentic learning experiences in earth systems science and life skills, and providing networking opportunities with geoscientists; and 3) Institutionalize ENERGY-NET collaborations among geosciences expert, learning researchers, and museum staff to yield long-term improvements in public geoscience education and geoscience workforce recruiting.

  10. Kinetic paths, time scale, and underlying landscapes: A path integral framework to study global natures of nonequilibrium systems and networks

    NASA Astrophysics Data System (ADS)

    Wang, Jin; Zhang, Kun; Wang, Erkwang

    2010-09-01

    We developed a general framework to quantify three key ingredients for dynamics of nonequilibrium systems through path integrals in length space. First, we identify dominant kinetic paths as the ones with optimal weights, leading to effective reduction of dimensionality or degrees of freedom from exponential to polynomial so large systems can be treated. Second, we uncover the underlying nonequilibrium potential landscapes from the explorations of the state space through kinetic paths. We apply our framework to a specific example of nonequilibrium network system: lambda phage genetic switch. Two distinct basins of attractions emerge. The dominant kinetic paths from one basin to another are irreversible and do not follow the usual steepest descent or gradient path along the landscape. It reflects the fact that the dynamics of nonequilibrium systems is not just determined by potential gradient but also the residual curl flux force, suggesting experiments to test theoretical predictions. Third, we have calculated dynamic transition time scales from one basin to another critical for stability of the system through instantons. Theoretical predictions are in good agreements with wild type and mutant experiments. We further uncover the correlations between the kinetic transition time scales and the underlying landscape topography: the barrier heights along the dominant paths. We found that both the dominant paths and the landscape are relatively robust against the influences of external environmental perturbations and the system tends to dissipate less with less fluctuations. Our general framework can be applied to other nonequilibrium systems.

  11. The Framework for Simulation of Bioinspired Security Mechanisms against Network Infrastructure Attacks

    PubMed Central

    Kotenko, Igor

    2014-01-01

    The paper outlines a bioinspired approach named “network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed prosedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine nessesary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described. PMID:25254229

  12. The framework for simulation of bioinspired security mechanisms against network infrastructure attacks.

    PubMed

    Shorov, Andrey; Kotenko, Igor

    2014-01-01

    The paper outlines a bioinspired approach named "network nervous system" and methods of simulation of infrastructure attacks and protection mechanisms based on this approach. The protection mechanisms based on this approach consist of distributed procedures of information collection and processing, which coordinate the activities of the main devices of a computer network, identify attacks, and determine necessary countermeasures. Attacks and protection mechanisms are specified as structural models using a set-theoretic approach. An environment for simulation of protection mechanisms based on the biological metaphor is considered; the experiments demonstrating the effectiveness of the protection mechanisms are described. PMID:25254229

  13. Using Essential Biodiversity Variables (EBVs) As a Framework for Coordination Between Research and Monitoring Networks: A Case Study with Phenology

    NASA Astrophysics Data System (ADS)

    Weltzin, J. F.; Jones, K. D.; Brown, J. F.; Elmendorf, S.; Enquist, C.; Rosemartin, A.; Thorpe, A.; Wee, B.

    2014-12-01

    The United Nations Convention on Biological Diversity (CBD) was organized to encourage countries to take action to address issues of declining biodiversity. In2010, the CBD identified specific goals for 2011-2020 (the "Aichi Targets") and a tiered system of indicators necessary to achieve those targets. Essential biodiversity variables (EBVs) are the standardized measurements and observations at the base of this system; they are the basic level of information that is necessary to calculate these indicators. By providing a list of pre-defined EBVs, existing research and research planned for the future can align measurements to address common questions. We assessed the applicability of phenology EBVs for standardizing measurements across observation networks within the US as a test case for use of the standardized used of EBVs. Phenology products from the USA National Phenology Network, a citizen science observer based program, NEON, a multi-scale ecological observatory, and remotely sensed data from USGS EROS were considered for this purpose. Essential Biodiversity Variables currently defined for phenology are insufficient to support consistent measurement across monitoring networks. Specifically, phenology which is a field of study, is currently listed as a single EBV within the general category of 'species traits'. With the only guidance provided to future observation networks being that of measuring 'phenology,' there would likely be as many approaches to achieving this goal as networks participating. We propose more narrowly defined variables which may be more appropriate for standardization and demonstrate how these measurements satisfy the basic characteristics of an EBV in that they are relevant, sensitive to change, biological and generalizable, scalable, feasible, stable and, represent state variables. We map these variables to the tiered indicators identified by the CBD and, finally, to Aichi Targets to which they contribute. EBVs may be used not only to

  14. Cluster imaging of multi-brain networks (CIMBN): a general framework for hyperscanning and modeling a group of interacting brains

    PubMed Central

    Duan, Lian; Dai, Rui-Na; Xiao, Xiang; Sun, Pei-Pei; Li, Zheng; Zhu, Chao-Zhe

    2015-01-01

    Studying the neural basis of human social interactions is a key topic in the field of social neuroscience. Brain imaging studies in this field usually focus on the neural correlates of the social interactions between two participants. However, as the participant number further increases, even by a small amount, great difficulties raise. One challenge is how to concurrently scan all the interacting brains with high ecological validity, especially for a large number of participants. The other challenge is how to effectively model the complex group interaction behaviors emerging from the intricate neural information exchange among a group of socially organized people. Confronting these challenges, we propose a new approach called “Cluster Imaging of Multi-brain Networks” (CIMBN). CIMBN consists of two parts. The first part is a cluster imaging technique with high ecological validity based on multiple functional near-infrared spectroscopy (fNIRS) systems. Using this technique, we can easily extend the simultaneous imaging capacity of social neuroscience studies up to dozens of participants. The second part of CIMBN is a multi-brain network (MBN) modeling method based on graph theory. By taking each brain as a network node and the relationship between any two brains as a network edge, one can construct a network model for a group of interacting brains. The emergent group social behaviors can then be studied using the network's properties, such as its topological structure and information exchange efficiency. Although there is still much work to do, as a general framework for hyperscanning and modeling a group of interacting brains, CIMBN can provide new insights into the neural correlates of group social interactions, and advance social neuroscience and social psychology. PMID:26283906

  15. A framework for rapid post-earthquake assessment of bridges and restoration of transportation network functionality using structural health monitoring

    NASA Astrophysics Data System (ADS)

    Omenzetter, Piotr; Ramhormozian, Shahab; Mangabhai, Poonam; Singh, Ravikash; Orense, Rolando

    2013-04-01

    Quick and reliable assessment of the condition of bridges in a transportation network after an earthquake can greatly assist immediate post-disaster response and long-term recovery. However, experience shows that available resources, such as qualified inspectors and engineers, will typically be stretched for such tasks. Structural health monitoring (SHM) systems can therefore make a real difference in this context. SHM, however, needs to be deployed in a strategic manner and integrated into the overall disaster response plans and actions to maximize its benefits. This study presents, in its first part, a framework of how this can be achieved. Since it will not be feasible, or indeed necessary, to use SHM on every bridge, it is necessary to prioritize bridges within individual networks for SHM deployment. A methodology for such prioritization based on structural and geotechnical seismic risks affecting bridges and their importance within a network is proposed in the second part. An example using the methodology application to selected bridges in the medium-sized transportation network of Wellington, New Zealand is provided. The third part of the paper is concerned with using monitoring data for quick assessment of bridge condition and damage after an earthquake. Depending on the bridge risk profile, it is envisaged that data will be obtained from either local or national seismic monitoring arrays or SHM systems installed on bridges. A method using artificial neural networks is proposed for using data from a seismic array to infer key ground motion parameters at an arbitrary bridges site. The methodology is applied to seismic data collected in Christchurch, New Zealand. Finally, how such ground motion parameters can be used in bridge damage and condition assessment is outlined.

  16. Unified Framework for Deriving Simultaneous Equation Algorithms for Water Distribution Networks

    EPA Science Inventory

    The known formulations for steady state hydraulics within looped water distribution networks are re-derived in terms of linear and non-linear transformations of the original set of partly linear and partly non-linear equations that express conservation of mass and energy. All of ...

  17. A Game Theoretic Framework for Bandwidth Allocation and Pricing in Federated Wireless Networks

    NASA Astrophysics Data System (ADS)

    Gu, Bo; Yamori, Kyoko; Xu, Sugang; Tanaka, Yoshiaki

    With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.

  18. The application of statistical mechanics on the study of glassy behaviors in transportation networks and dynamics in models of financial markets

    NASA Astrophysics Data System (ADS)

    Yeung, Chi Ho

    In this thesis, we study two interdisciplinary problems in the framework of statistical physics, which show the broad applicability of physics on problems with various origins. The first problem corresponds to an optimization problem in allocating resources on random regular networks. Frustrations arise from competition for resources. When the initial resources are uniform, different regimes with discrete fractions of satisfied nodes are observed, resembling the Devil's staircase. We apply the spin glass theory in analyses and demonstrate how functional recursions are converted to simple recursions of probabilities. Equilibrium properties such as the average energy and the fraction of free nodes are derived. When the initial resources are bimodally distributed, increases in the fraction of rich nodes induce a glassy transition, entering a glassy phase described by the existence of multiple metastable states, in which we employ the replica symmetry breaking ansatz for analysis. The second problem corresponds to the study of multi-agent systems modeling financial markets. Agents in the system trade among themselves, and self-organize to produce macroscopic trading behaviors resembling the real financial markets. These behaviors include the arbitraging activities, the setting up and the following of price trends. A phase diagram of these behaviors is obtained, as a function of the sensitivity of price and the market impact factor. We finally test the applicability of the models with real financial data including the Hang Seng Index, the Nasdaq Composite and the Dow Jones Industrial Average. A substantial fraction of agents gains faster than the inflation rate of the indices, suggesting the possibility of using multi-agent systems as a tool for real trading.

  19. Data collection framework for energy efficient privacy preservation in wireless sensor networks having many-to-many structures.

    PubMed

    Bahşi, Hayretdin; Levi, Albert

    2010-01-01

    Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-to-many structures evolved due to the need for conveying collected event information to multiple sinks. Privacy preserved data collection models in the literature do not solve the problems of WSN applications in which network has multiple un-trusted sinks with different level of privacy requirements. This study proposes a data collection framework bases on k-anonymity for preventing record disclosure of collected event information in WSNs. Proposed method takes the anonymity requirements of multiple sinks into consideration by providing different levels of privacy for each destination sink. Attributes, which may identify an event owner, are generalized or encrypted in order to meet the different anonymity requirements of sinks at the same anonymized output. If the same output is formed, it can be multicasted to all sinks. The other trivial solution is to produce different anonymized outputs for each sink and send them to related sinks. Multicasting is an energy efficient data sending alternative for some sensor nodes. Since minimization of energy consumption is an important design criteria for WSNs, multicasting the same event information to multiple sinks reduces the energy consumption of overall network. PMID:22163660

  20. Data Collection Framework for Energy Efficient Privacy Preservation in Wireless Sensor Networks Having Many-to-Many Structures

    PubMed Central

    Bahşi, Hayretdin; Levi, Albert

    2010-01-01

    Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-to-many structures evolved due to the need for conveying collected event information to multiple sinks. Privacy preserved data collection models in the literature do not solve the problems of WSN applications in which network has multiple un-trusted sinks with different level of privacy requirements. This study proposes a data collection framework bases on k-anonymity for preventing record disclosure of collected event information in WSNs. Proposed method takes the anonymity requirements of multiple sinks into consideration by providing different levels of privacy for each destination sink. Attributes, which may identify an event owner, are generalized or encrypted in order to meet the different anonymity requirements of sinks at the same anonymized output. If the same output is formed, it can be multicasted to all sinks. The other trivial solution is to produce different anonymized outputs for each sink and send them to related sinks. Multicasting is an energy efficient data sending alternative for some sensor nodes. Since minimization of energy consumption is an important design criteria for WSNs, multicasting the same event information to multiple sinks reduces the energy consumption of overall network. PMID:22163660

  1. Design of a new monitoring network and first testing of new biological assessment methods according to water framework directive.

    PubMed

    Sommerhäuser, Mario; Scharner, Christoph; Schimmer, Hannes; Schindler, Anna; Plantikow, Kerstin; Vietoris, Friederike

    2007-09-01

    In most European member states, more or less completely new monitoring networks and assessment methods had to be developed as basic technical tools for the implementation of the EU Water Framework Directive (WFD). In the river basin of the Stever, the largest tributary to the river Lippe (River Rhine, Northrhine-Westphalia, Germany), a WFD-monitoring network was developed, and new German biological methods for rivers, developed for the purposes of the WFD, have been applied. Like most rivers in the German lowland areas, nearly all the river courses of the Stever system are altered by hydro-morphological degradation (straightening, bank fixation, lack of canopy etc.). In 2005 and 2006, the biological quality components of macroinvertebrates, fish and macrophytes were investigated and evaluated for the assessment of the ecological status of about 50 surface water bodies within the whole Stever system. Basic physical and chemical parameters, as well as priority substances, have been analysed in the same period. In this contribution, the design of the new monitoring network, the core principles of the German biological methods, and the most important results of the pilot monitoring will be presented. As main impacts with severe effects on the faunal and floral communities, the many migration barriers and the bad quality of the river morphology could be stated. Organic pollution is no more a severe problem in the Stever. The pilot project was successfully conducted in close collaboration with the water authorities (District Government Münster) and the water association Lippeverband. PMID:17726557

  2. The sexual erotic market as an analytical framework for understanding erotic-affective exchanges in interracial sexually intimate and affective relationships.

    PubMed

    Vigoya, Mara Viveros

    2015-01-01

    This paper examines the way in which erotic-affective exchanges in interracial relationships have been analysed in Latin America. It considers how race, gender and class operate within a market of values such that erotic, affective and economic status are shaped by racial, gender and class hierarchies. In this paper I analyse historical and social arrangements that embody the region's political economy of race and sex. Such a perspective allows me to address the simultaneous co-existence of socio-racial exclusion and inclusion and the repressive and productive effects of power, attraction and anxiety as aspects of lived experiences in relation to sexuality. From there, I outline an analytical framework that references an erotic or pleasure-based market in which capital and other resources are exchanged from a structural perspective stressing relationship alliances. I conclude by identifying the scope and limits of such an approach. PMID:25431884

  3. A statistical framework for evaluating neural networks to predict recurrent events in breast cancer

    NASA Astrophysics Data System (ADS)

    Gorunescu, Florin; Gorunescu, Marina; El-Darzi, Elia; Gorunescu, Smaranda

    2010-07-01

    Breast cancer is the second leading cause of cancer deaths in women today. Sometimes, breast cancer can return after primary treatment. A medical diagnosis of recurrent cancer is often a more challenging task than the initial one. In this paper, we investigate the potential contribution of neural networks (NNs) to support health professionals in diagnosing such events. The NN algorithms are tested and applied to two different datasets. An extensive statistical analysis has been performed to verify our experiments. The results show that a simple network structure for both the multi-layer perceptron and radial basis function can produce equally good results, not all attributes are needed to train these algorithms and, finally, the classification performances of all algorithms are statistically robust. Moreover, we have shown that the best performing algorithm will strongly depend on the features of the datasets, and hence, there is not necessarily a single best classifier.

  4. A multilevel approach to network meta-analysis within a frequentist framework.

    PubMed

    Greco, Teresa; Edefonti, Valeria; Biondi-Zoccai, Giuseppe; Decarli, Adriano; Gasparini, Mauro; Zangrillo, Alberto; Landoni, Giovanni

    2015-05-01

    Meta-analysis is a powerful tool to summarize knowledge. Pairwise or network meta-analysis may be carried out with multivariate models that account for the dependence between treatment estimates and quantify the correlation across studies. From a different perspective, meta-analysis may be viewed as a special case of multilevel analysis having a hierarchical data structure. Hence, we introduce an alternative frequentist approach, called multilevel network meta-analysis, which also allows to account for publication bias and the presence of inconsistency. We propose our approach for a three-level data structure set-up: arms within studies at the first level, studies within study designs at the second level and design configuration at the third level. This strategy differs from the traditional frequentist modeling because it works directly on an arm-based data structure. An advantage of using multilevel analysis is its flexibility, since it naturally allows to add further levels to the model and to accommodate for multiple outcome variables. Moreover, multilevel modeling may be carried out with widely available statistical programs. Finally, we compare the results from our approach with those from a Bayesian network meta-analysis on a binary endpoint which examines the effect on mortality of some anesthetics at the longest follow-up available. In addition, we compare results from the Bayesian and multilevel network meta-analysis approaches on a publicly available "Thrombolytic drugs" database. We also provide the reader with a blueprint of SAS codes for fitting the proposed models, although our approach does not rely on any specific software. PMID:25804722

  5. DFNWorks. A discrete fracture network framework for modeling subsurface flow and transport

    DOE PAGESBeta

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-08-10

    DFNWorks is a parallalized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using dfnGen, which combines fram (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs on the basis of site specific data with the LaGriT meshing toolbox to create a high-quality computational mesh representation, specifically a conforming Delaunay triangulation suitable for high performance computingmore » finite volume solvers, of the DFN in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code pflotran. A Lagrangian approach to simulating transport through the DFN is adopted within dfnTrans, which is an extension of the walkabout particle tracking method to determine pathlines through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.« less

  6. dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

    SciTech Connect

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-11-01

    DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

  7. DFNWORKS: A discrete fracture network framework for modeling subsurface flow and transport

    NASA Astrophysics Data System (ADS)

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-11-01

    DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LAGRIT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated in DFNFLOW, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

  8. DFNWorks. A discrete fracture network framework for modeling subsurface flow and transport

    SciTech Connect

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-08-10

    DFNWorks is a parallalized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using dfnGen, which combines fram (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs on the basis of site specific data with the LaGriT meshing toolbox to create a high-quality computational mesh representation, specifically a conforming Delaunay triangulation suitable for high performance computing finite volume solvers, of the DFN in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code pflotran. A Lagrangian approach to simulating transport through the DFN is adopted within dfnTrans, which is an extension of the walkabout particle tracking method to determine pathlines through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

  9. dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

    DOE PAGESBeta

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-11-01

    DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in anmore » intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.« less

  10. Probabilistic Boolean Network Modelling and Analysis Framework for mRNA Translation.

    PubMed

    Zhao, Yun-Bo; Krishnan, J

    2016-01-01

    mRNA translation is a complex process involving the progression of ribosomes on the mRNA, resulting in the synthesis of proteins, and is subject to multiple layers of regulation. This process has been modelled using different formalisms, both stochastic and deterministic. Recently, we introduced a Probabilistic Boolean modelling framework for mRNA translation, which possesses the advantage of tools for numerically exact computation of steady state probability distribution, without requiring simulation. Here, we extend this model to incorporate both random sequential and parallel update rules, and demonstrate its effectiveness in various settings, including its flexibility in accommodating additional static and dynamic biological complexities and its role in parameter sensitivity analysis. In these applications, the results from the model analysis match those of TASEP model simulations. Importantly, the proposed modelling framework maintains the stochastic aspects of mRNA translation and provides a way to exactly calculate probability distributions, providing additional tools of analysis in this context. Finally, the proposed modelling methodology provides an alternative approach to the understanding of the mRNA translation process, by bridging the gap between existing approaches, providing new analysis tools, and contributing to a more robust platform for modelling and understanding translation. PMID:26390498

  11. Quantitative Assessment of a Framework for Creating Anatomical Brain Networks via Global Tractography

    PubMed Central

    Li, Longchuan; Rilling, James K.; Preuss, Todd M.; Glasser, Matthew F.; Damen, Frederick W.; Hu, Xiaoping

    2012-01-01

    Interregional connections of the brain measured with diffusion tractography can be used to infer valuable information regarding both brain structure and function. However, different tractography algorithms can generate networks that exhibit different characteristics, resulting in poor reproducibility across studies. Therefore, it is important to benchmark different tractography algorithms to quantitatively assess their performance. Here we systematically evaluated a newly introduced tracking algorithm, global tractography, to derive anatomical brain networks in a fiber phantom, 2 post-mortem macaque brains, and 20 living humans, and compared the results with an established local tracking algorithm. Our results demonstrated that global tractography accurately characterized the phantom network in terms of graph-theoretic measures, and significantly outperformed the local tracking approach. Results in brain tissues (post-mortem macaques and in vivo humans), however, showed that although the performance of global tractography demonstrated a trend of improvement, the results were not vastly different than that of local tractography, possibly resulting from the increased fiber complexity of real tissues. When using macaque tracer-derived connections as the ground truth, we found that both global and local algorithms generated non-random patterns of false negative and false positive connections that were probably related to specific fiber systems and largely independent of the tractography algorithm or tissue type (post-mortem vs. in vivo) used in the current study. Moreover, a close examination of the transcallosal motor connections, reconstructed via either global or local tractography, demonstrated that the lateral transcallosal fibers in humans and macaques did not exhibit the denser homotopic connections found in primate tracer studies, indicating the need for more robust brain mapping techniques based on diffusion MRI data. PMID:22484406

  12. A Framework for Modeling the Growth and Development of Neurons and Networks

    PubMed Central

    Zubler, Frederic; Douglas, Rodney

    2009-01-01

    The development of neural tissue is a complex organizing process, in which it is difficult to grasp how the various localized interactions between dividing cells leads relentlessly to global network organization. Simulation is a useful tool for exploring such complex processes because it permits rigorous analysis of observed global behavior in terms of the mechanistic axioms declared in the simulated model. We describe a novel simulation tool, CX3D, for modeling the development of large realistic neural networks such as the neocortex, in a physical 3D space. In CX3D, as in biology, neurons arise by the replication and migration of precursors, which mature into cells able to extend axons and dendrites. Individual neurons are discretized into spherical (for the soma) and cylindrical (for neurites) elements that have appropriate mechanical properties. The growth functions of each neuron are encapsulated in set of pre-defined modules that are automatically distributed across its segments during growth. The extracellular space is also discretized, and allows for the diffusion of extracellular signaling molecules, as well as the physical interactions of the many developing neurons. We demonstrate the utility of CX3D by simulating three interesting developmental processes: neocortical lamination based on mechanical properties of tissues; a growth model of a neocortical pyramidal cell based on layer-specific guidance cues; and the formation of a neural network in vitro by employing neurite fasciculation. We also provide some examples in which previous models from the literature are re-implemented in CX3D. Our results suggest that CX3D is a powerful tool for understanding neural development. PMID:19949465

  13. SelectAudit: A Secure and Efficient Audit Framework for Networked Virtual Environments

    NASA Astrophysics Data System (ADS)

    Phan, Tuan; Yao, Danfeng (Daphne)

    Networked virtual environments (NVE) refer to the category of distributed applications that allow a large number of distributed users to interact with one or more central servers in a virtual environment setting. Recent studies identify that malicious users may compromise the semantic integrity of NVE applications and violate the semantic rules of the virtual environments without being detected. In this paper, we propose an efficient audit protocol to detect violations of semantic integrity through a probabilistic checking mechanism done by a third-party audit server.

  14. A framework to approach problems of forensic anthropology using complex networks

    NASA Astrophysics Data System (ADS)

    Caridi, Inés; Dorso, Claudio O.; Gallo, Pablo; Somigliana, Carlos

    2011-05-01

    We have developed a method to analyze and interpret emerging structures in a set of data which lacks some information. It has been conceived to be applied to the problem of getting information about people who disappeared in the Argentine state of Tucumán from 1974 to 1981. Even if the military dictatorship formally started in Argentina had begun in 1976 and lasted until 1983, the disappearance and assassination of people began some months earlier. During this period several circuits of Illegal Detention Centres (IDC) were set up in different locations all over the country. In these secret centres, disappeared people were illegally kept without any sort of constitutional guarantees, and later assassinated. Even today, the final destination of most of the disappeared people’s remains is still unknown. The fundamental hypothesis in this work is that a group of people with the same political affiliation whose disappearances were closely related in time and space shared the same place of captivity (the same IDC or circuit of IDCs). This hypothesis makes sense when applied to the systematic method of repression and disappearances which was actually launched in Tucumán, Argentina (2007) [11]. In this work, the missing individuals are identified as nodes on a network and connections are established among them based on the individuals’ attributes while they were alive, by using rules to link them. In order to determine which rules are the most effective in defining the network, we use other kind of knowledge available in this problem: previous results from the anthropological point of view (based on other sources of information, both oral and written, historical and anthropological data, etc.); and information about the place (one or more IDCs) where some people were kept during their captivity. For these best rules, a prediction about these people’s possible destination is assigned (one or more IDCs where they could have been kept), and the success of the

  15. Run-time interoperability between neuronal network simulators based on the MUSIC framework.

    PubMed

    Djurfeldt, Mikael; Hjorth, Johannes; Eppler, Jochen M; Dudani, Niraj; Helias, Moritz; Potjans, Tobias C; Bhalla, Upinder S; Diesmann, Markus; Kotaleski, Jeanette Hellgren; Ekeberg, Orjan

    2010-03-01

    MUSIC is a standard API allowing large scale neuron simulators to exchange data within a parallel computer during runtime. A pilot implementation of this API has been released as open source. We provide experiences from the implementation of MUSIC interfaces for two neuronal network simulators of different kinds, NEST and MOOSE. A multi-simulation of a cortico-striatal network model involving both simulators is performed, demonstrating how MUSIC can promote inter-operability between models written for different simulators and how these can be re-used to build a larger model system. Benchmarks show that the MUSIC pilot implementation provides efficient data transfer in a cluster computer with good scaling. We conclude that MUSIC fulfills the design goal that it should be simple to adapt existing simulators to use MUSIC. In addition, since the MUSIC API enforces independence of the applications, the multi-simulation could be built from pluggable component modules without adaptation of the components to each other in terms of simulation time-step or topology of connections between the modules. PMID:20195795

  16. Aerosol Optical Depth Measurements in the Southern Ocean Within the Framework of Maritime Aerosol Network

    NASA Astrophysics Data System (ADS)

    Smirnov, A.; Holben, B. N.; Sayer, A. M.; Sakerin, S. M.; Radionov, V. F.; Courcoux, Y.; Broccardo, S. P.; Evangelista, H.; Croot, P. L.; Disterhoft, P.; Piketh, S.; Milinevsky, G. P.; O'Neill, N. T.; Slutsker, I.; Giles, D. M.

    2013-12-01

    Aerosol production sources over the World Ocean and various factors determining aerosol spatial and temporal distribution are important for understanding the Earth's radiation budget and aerosol-cloud interactions. The Maritime Aerosol Network (MAN) as a component of AERONET has been collecting aerosol optical depth data over the oceans since 2006. A significant progress has been made in data acquisition over areas that previously had very little or no coverage. Data collection included intensive study areas in the Southern Ocean and off the coast of Antarctica including a number of circumnavigation cruises in high southern latitudes. It made an important contribution to MAN and provided a valuable reference point in atmospheric aerosol optical studies. The paper presents results of this international and multi-agency effort in studying aerosol optical properties over Southern Ocean and adjacent areas. The ship-borne aerosol optical depth measurements offer an excellent opportunity for comparison with global aerosol transport models, satellite retrievals and provide useful information on aerosol distribution over the World Ocean. A public domain web-based database dedicated to the MAN activity can be found at http://aeronet.gsfc.nasa.gov/new_web/maritime_aerosol_network.html.

  17. Context-rich semantic framework for effective data-to-decisions in coalition networks

    NASA Astrophysics Data System (ADS)

    Grueneberg, Keith; de Mel, Geeth; Braines, Dave; Wang, Xiping; Calo, Seraphin; Pham, Tien

    2013-05-01

    In a coalition context, data fusion involves combining of soft (e.g., field reports, intelligence reports) and hard (e.g., acoustic, imagery) sensory data such that the resulting output is better than what it would have been if the data are taken individually. However, due to the lack of explicit semantics attached with such data, it is difficult to automatically disseminate and put the right contextual data in the hands of the decision makers. In order to understand the data, explicit meaning needs to be added by means of categorizing and/or classifying the data in relationship to each other from base reference sources. In this paper, we present a semantic framework that provides automated mechanisms to expose real-time raw data effectively by presenting appropriate information needed for a given situation so that an informed decision could be made effectively. The system utilizes controlled natural language capabilities provided by the ITA (International Technology Alliance) Controlled English (CE) toolkit to provide a human-friendly semantic representation of messages so that the messages can be directly processed in human/machine hybrid environments. The Real-time Semantic Enrichment (RTSE) service adds relevant contextual information to raw data streams from domain knowledge bases using declarative rules. The rules define how the added semantics and context information are derived and stored in a semantic knowledge base. The software framework exposes contextual information from a variety of hard and soft data sources in a fast, reliable manner so that an informed decision can be made using semantic queries in intelligent software systems.

  18. Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

    PubMed Central

    Bockholt, Henry J.; Scully, Mark; Courtney, William; Rachakonda, Srinivas; Scott, Adam; Caprihan, Arvind; Fries, Jill; Kalyanam, Ravi; Segall, Judith M.; de la Garza, Raul; Lane, Susan; Calhoun, Vince D.

    2009-01-01

    A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining. PMID:20461147

  19. Mississippi Curriculum Framework for Marketing and Fashion Merchandising (Program CIP: 08.0705--General Retailing Operations). Secondary Programs.

    ERIC Educational Resources Information Center

    Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

    This document, which reflects Mississippi's statutory requirement that instructional programs be based on core curricula and performance-based assessment, contains outlines of the instructional units required in local instructional management plans and daily lesson plans for marketing I-II and fashion merchandising. Presented first are a program…

  20. Towards a Theoretical Framework for the Comparative Understanding of Globalisation, Higher Education, the Labour Market and Inequality

    ERIC Educational Resources Information Center

    Kupfer, Antonia

    2011-01-01

    This paper is a theoretical examination of three major empirical trends that affect many people: globalisation, increasingly close relations between higher education (HE) and labour markets, and increasing social inequality. Its aim is to identify key theoretical resources and their contribution to the development of a comparative theoretical…

  1. "Technohesion": Engaging Students of Higher Education through Digital Technology and Interactive Marketing--A Research Agenda and Theoretical Framework

    ERIC Educational Resources Information Center

    Thorpe, Anthony; Lim, Lynn L. K.

    2013-01-01

    This article examines how the development of techno-marketing campaigns might facilitate the engagement of university students in voluntary activities on campus which promote active citizenship and community cohesion where there is a concern about a low take up of such opportunities. The increasing influence of technology upon the forms of social…

  2. Joint marketing as a framework for targeting men who have sex with men in China: a pilot intervention study.

    PubMed

    Tan, Jingguang; Cai, Rui; Lu, Zuxun; Cheng, Jinquan; de Vlas, Sake J; Richardus, Jan Hendrik

    2013-04-01

    To apply the joint marketing principle as a new intervention approach for targeting men who have sex with men (MSM) who are often difficult to reach in societies with discrimination towards homosexuality and HIV/AIDS. A pilot intervention according to the principles of joint marketing was carried out by the CDC in Shenzhen, China, in MSM social venues. A self-designed questionnaire of HIV knowledge, condom use, and access to HIV-related services was used before and after the pilot intervention to evaluate its effectiveness. The CDC supported gatekeepers of MSM social venues in running their business and thereby increasing their respectability and income. In return, the gatekeepers cooperated with the CDC in reaching the MSM at the venues with health promotion messages and materials. Thus a win-win situation was created, bringing together two noncompetitive parties in reaching out to a shared customer, the MSM. The pilot intervention succeeded in demonstrating acceptability and feasibility of the joint marketing approach targeting MSM. HIV knowledge, the rate of condom use, and access to HIV-related services of participants in the pilot intervention increased significantly. The joint marketing intervention is an innovative way to create synergies between the gatekeepers of MSM social venues and public health officials for reaching and potentially changing HIV high-risk behaviors among MSM. PMID:23514078

  3. Senior market tough to crack. MacNeal Health Network, Berwyn, IL.

    PubMed

    Plank, D; Moore, P L

    1997-01-01

    Seniors, often thought of as a stodgy, conservative market, actually constitute one of the most vibrant, diverse age groups of all. Here's how people who have discovered the secrets of the mature market use that diversity to their advantage. PMID:10167483

  4. Correlation network analysis for multi-dimensional data in stocks market

    NASA Astrophysics Data System (ADS)

    Kazemilari, Mansooreh; Djauhari, Maman Abdurachman

    2015-07-01

    This paper shows how the concept of vector correlation can appropriately measure the similarity among multivariate time series in stocks network. The motivation of this paper is (i) to apply the RV coefficient to define the network among stocks where each of them is represented by a multivariate time series; (ii) to analyze that network in terms of topological structure of the stocks of all minimum spanning trees, and (iii) to compare the network topology between univariate correlation based on r and multivariate correlation network based on RV coefficient.

  5. Developing a culturally competent health network: a planning framework and guide.

    PubMed

    Gertner, Eric J; Sabino, Judith N; Mahady, Erica; Deitrich, Lynn M; Patton, Jarret R; Grim, Mary Kay; Geiger, James F; Salas-Lopez, Debbie

    2010-01-01

    The number of cultural competency initiatives in healthcare is increasing due to many factors, including changing demographics, quality improvement and regulatory requirements, equitable care missions, and accreditation standards. To facilitate organization-wide transformation, a hospital or healthcare system must establish strategic goals, objectives, and implementation tasks for culturally competent provision of care. This article reports the largely successful results of a cultural competency program instituted at a large system in eastern Pennsylvania. Prior to the development of its cultural competency initiative, Lehigh Valley Health Network, Allentown, Pennsylvania, saw isolated activities producing innovative solutions to diversity and culture issues in the provision of equitable care. But it took a transformational event to support an organization-wide program in cultural competency by strengthening leadership buy-in and providing a sense of urgency, excitement, and shared vision among multiple stakeholders. A multidisciplinary task force, including senior leaders and a diverse group of employees, was created with the authority and responsibility to enact changes. Through a well-organized strategic planning process, existing patient and community demographic data were reviewed to describe existing disparities, a baseline assessment was completed, a mission statement was created, and clear metrics were developed. The strategic plan, which focused on five key areas (demographics, language-appropriate services, employees, training, and education/communication), was approved by the network's chief executive officer and senior managers to demonstrate commitment prior to implementation. Strategic plan implementation proceeded through a project structure consisting of subproject teams charged with achieving the following specific objectives: develop a cultural material repository, enhance employee recruitment/retention, establish a baseline assessment

  6. Entangled Uranyl Organic Frameworks with (10,3)-b Topology and Polythreading Network: Structure, Luminescence, and Computational Investigation.

    PubMed

    Liu, Chao; Gao, Chao-Ying; Yang, Weiting; Chen, Fang-Yuan; Pan, Qing-Jiang; Li, Jiyang; Sun, Zhong-Ming

    2016-06-01

    Two 3D uranyl organic frameworks (UOFs) with entangled structures, (HPhen)2[(UO2)2L2]·4.5H2O (1) and [(UO2)3(H2O)4L2]·6H2O (2), were synthesized using a rigid tripodal linker (4,4',4″-(phenylsilanetriyl)tribenzoic acid, H3L). Compound 1 represents a 2-fold interpenetrating UOF with the unique (10,3)-b topology. Compound 2 is composed of three interlocked sets of identical singlet networks and thus exhibits a rare 3D polythreading network with (3,4)-connected topology. These two compounds have been characterized by IR, UV-vis, and photoluminescent spectroscopy. A density functional theory (DFT) study on the model compounds of 1 and 2 shows good agreement of structural parameters and U═O stretching vibrational frequencies with experimental data. The experimentally measured absorption bands were well reproduced by the time-dependent DFT calculations. PMID:27171364

  7. Metal organic frameworks derived porous lithium iron phosphate with continuous nitrogen-doped carbon networks for lithium ion batteries

    NASA Astrophysics Data System (ADS)

    Liu, Yuanyuan; Gu, Junjie; Zhang, Jinli; Yu, Feng; Dong, Lutao; Nie, Ning; Li, Wei

    2016-02-01

    Lithium iron phosphate (LiFePO4) nanoparticles embedded in the continuous interconnected nitrogen-doped carbon networks (LFP/N-CNWs) is an optimal architecture to fast electron and Li+ conduction. This paper, for the first time, reports a reasonable design and successful preparation of porous hierarchical LFP/N-CNWs composites using unique Fe-based metal organic framework (MIL-100(Fe)) as both template and starting material of Fe and C. Such nitrogen-doped carbon networks (N-CNWs) surrounding the lithium iron phosphate nanoparticles facilitate the transfer of Li+ and electrons throughout the electrodes, which significantly decreases the internal resistance for the electrodes and results in the efficient utilization of LiFePO4. The synthesized LFP/N-CNWs composites possess a porous structure with an amazing surface area of 129 m2 g-1, considerably enhanced electrical conductivities of 7.58 × 10-2 S cm-1 and Li+ diffusion coefficient of 8.82 × 10-14 cm2 s-1, thereby delivering excellent discharge capacities of 161.5 and 93.6 mAh·g-1 at 0.1C and 20C, respectively.

  8. Agent-based spin model for financial markets on complex networks: Emergence of two-phase phenomena

    NASA Astrophysics Data System (ADS)

    Kim, Yup; Kim, Hong-Joo; Yook, Soon-Hyung

    2008-09-01

    We study a microscopic model for financial markets on complex networks, motivated by the dynamics of agents and their structure of interaction. The model consists of interacting agents (spins) with local ferromagnetic coupling and global antiferromagnetic coupling. In order to incorporate more realistic situations, we also introduce an external field which changes in time. From numerical simulations, we find that the model shows two-phase phenomena. When the local ferromagnetic interaction is balanced with the global antiferromagnetic interaction, the resulting return distribution satisfies a power law having a single peak at zero values of return, which corresponds to the market equilibrium phase. On the other hand, if local ferromagnetic interaction is dominant, then the return distribution becomes double peaked at nonzero values of return, which characterizes the out-of-equilibrium phase. On random networks, the crossover between two phases comes from the competition between two different interactions. However, on scale-free networks, not only the competition between the different interactions but also the heterogeneity of underlying topology causes the two-phase phenomena. Possible relationships between the critical phenomena of spin system and the two-phase phenomena are discussed.

  9. Market Scenarios and Alternative Administrative Frameworks for U.S. Educational Satellite Systems. Memorandum No. CG-75/2.

    ERIC Educational Resources Information Center

    Walkmeyer, John E., Jr.; And Others

    Intended as a framework for analysis of the costs and benefits of developing an operational educational satellite system in the United States, this memorandum presents a series of scenarios of potential applications together with alternative organizational arrangements to support them. The number of satellite channels (25) and the number of ground…

  10. An integer programming framework for inferring disease complexes from network data

    PubMed Central

    Mazza, Arnon; Klockmeier, Konrad; Wanker, Erich; Sharan, Roded

    2016-01-01

    Motivation: Unraveling the molecular mechanisms that underlie disease calls for methods that go beyond the identification of single causal genes to inferring larger protein assemblies that take part in the disease process. Results: Here, we develop an exact, integer-programming-based method for associating protein complexes with disease. Our approach scores proteins based on their proximity in a protein–protein interaction network to a prior set that is known to be relevant for the studied disease. These scores are combined with interaction information to infer densely interacting protein complexes that are potentially disease-associated. We show that our method outperforms previous ones and leads to predictions that are well supported by current experimental data and literature knowledge. Availability and Implementation: The datasets we used, the executables and the results are available at www.cs.tau.ac.il/roded/disease_complexes.zip Contact: roded@post.tau.ac.il PMID:27307626

  11. Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks

    PubMed Central

    Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

    2014-01-01

    Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the “small sample size” (SSS) problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1) how to define diverse base classifiers from the small data; (2) how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0–1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system. PMID:25494350

  12. Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks.

    PubMed

    Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

    2014-01-01

    Multi-camera networks have gained great interest in video-based surveillance systems for security monitoring, access control, etc. Person re-identification is an essential and challenging task in multi-camera networks, which aims to determine if a given individual has already appeared over the camera network. Individual recognition often uses faces as a trial and requires a large number of samples during the training phrase. This is difficult to fulfill due to the limitation of the camera hardware system and the unconstrained image capturing conditions. Conventional face recognition algorithms often encounter the "small sample size" (SSS) problem arising from the small number of training samples compared to the high dimensionality of the sample space. To overcome this problem, interest in the combination of multiple base classifiers has sparked research efforts in ensemble methods. However, existing ensemble methods still open two questions: (1) how to define diverse base classifiers from the small data; (2) how to avoid the diversity/accuracy dilemma occurring during ensemble. To address these problems, this paper proposes a novel generic learning-based ensemble framework, which augments the small data by generating new samples based on a generic distribution and introduces a tailored 0-1 knapsack algorithm to alleviate the diversity/accuracy dilemma. More diverse base classifiers can be generated from the expanded face space, and more appropriate base classifiers are selected for ensemble. Extensive experimental results on four benchmarks demonstrate the higher ability of our system to cope with the SSS problem compared to the state-of-the-art system. PMID:25494350

  13. To supplement or not to supplement: a metabolic network framework for human nutritional supplements.

    PubMed

    Nogiec, Christopher D; Kasif, Simon

    2013-01-01

    Flux balance analysis and constraint based modeling have been successfully used in the past to elucidate the metabolism of single cellular organisms. However, limited work has been done with multicellular organisms and even less with humans. The focus of this paper is to present a novel use of this technique by investigating human nutrition, a challenging field of study. Specifically, we present a steady state constraint based model of skeletal muscle tissue to investigate amino acid supplementation's effect on protein synthesis. We implement several in silico supplementation strategies to study whether amino acid supplementation might be beneficial for increasing muscle contractile protein synthesis. Concurrent with published data on amino acid supplementation's effect on protein synthesis in a post resistance exercise state, our results suggest that increasing bioavailability of methionine, arginine, and the branched-chain amino acids can increase the flux of contractile protein synthesis. The study also suggests that a common commercial supplement, glutamine, is not an effective supplement in the context of increasing protein synthesis and thus, muscle mass. Similar to any study in a model organism, the computational modeling of this research has some limitations. Thus, this paper introduces the prospect of using systems biology as a framework to formally investigate how supplementation and nutrition can affect human metabolism and physiology. PMID:23967053

  14. Neural Networks for Computer Vision: A Framework for Specifications of a General Purpose Vision System

    NASA Astrophysics Data System (ADS)

    Skrzypek, Josef; Mesrobian, Edmond; Gungner, David J.

    1989-03-01

    The development of autonomous land vehicles (ALV) capable of operating in an unconstrained environment has proven to be a formidable research effort. The unpredictability of events in such an environment calls for the design of a robust perceptual system, an impossible task requiring the programming of a system bases on the expectation of future, unconstrained events. Hence, the need for a "general purpose" machine vision system that is capable of perceiving and understanding images in an unconstrained environment in real-time. The research undertaken at the UCLA Machine Perception Laboratory addresses this need by focusing on two specific issues: 1) the long term goals for machine vision research as a joint effort between the neurosciences and computer science; and 2) a framework for evaluating progress in machine vision. In the past, vision research has been carried out independently within different fields including neurosciences, psychology, computer science, and electrical engineering. Our interdisciplinary approach to vision research is based on the rigorous combination of computational neuroscience, as derived from neurophysiology and neuropsychology, with computer science and electrical engineering. The primary motivation behind our approach is that the human visual system is the only existing example of a "general purpose" vision system and using a neurally based computing substrate, it can complete all necessary visual tasks in real-time.

  15. An enhanced backbone-assisted reliable framework for wireless sensor networks.

    PubMed

    Tufail, Ali; Khayam, Syed Ali; Raza, Muhammad Taqi; Ali, Amna; Kim, Ki-Hyung

    2010-01-01

    An extremely reliable source to sink communication is required for most of the contemporary WSN applications especially pertaining to military, healthcare and disaster-recovery. However, due to their intrinsic energy, bandwidth and computational constraints, Wireless Sensor Networks (WSNs) encounter several challenges in reliable source to sink communication. In this paper, we present a novel reliable topology that uses reliable hotlines between sensor gateways to boost the reliability of end-to-end transmissions. This reliable and efficient routing alternative reduces the number of average hops from source to the sink. We prove, with the help of analytical evaluation, that communication using hotlines is considerably more reliable than traditional WSN routing. We use reliability theory to analyze the cost and benefit of adding gateway nodes to a backbone-assisted WSN. However, in hotline assisted routing some scenarios where source and the sink are just a couple of hops away might bring more latency, therefore, we present a Signature Based Routing (SBR) scheme. SBR enables the gateways to make intelligent routing decisions, based upon the derived signature, hence providing lesser end-to-end delay between source to the sink communication. Finally, we evaluate our proposed hotline based topology with the help of a simulation tool and show that the proposed topology provides manifold increase in end-to-end reliability. PMID:22294890

  16. An Enhanced Backbone-Assisted Reliable Framework for Wireless Sensor Networks

    PubMed Central

    Tufail, Ali; Khayam, Syed Ali; Raza, Muhammad Taqi; Ali, Amna; Kim, Ki-Hyung

    2010-01-01

    An extremely reliable source to sink communication is required for most of the contemporary WSN applications especially pertaining to military, healthcare and disaster-recovery. However, due to their intrinsic energy, bandwidth and computational constraints, Wireless Sensor Networks (WSNs) encounter several challenges in reliable source to sink communication. In this paper, we present a novel reliable topology that uses reliable hotlines between sensor gateways to boost the reliability of end-to-end transmissions. This reliable and efficient routing alternative reduces the number of average hops from source to the sink. We prove, with the help of analytical evaluation, that communication using hotlines is considerably more reliable than traditional WSN routing. We use reliability theory to analyze the cost and benefit of adding gateway nodes to a backbone-assisted WSN. However, in hotline assisted routing some scenarios where source and the sink are just a couple of hops away might bring more latency, therefore, we present a Signature Based Routing (SBR) scheme. SBR enables the gateways to make intelligent routing decisions, based upon the derived signature, hence providing lesser end-to-end delay between source to the sink communication. Finally, we evaluate our proposed hotline based topology with the help of a simulation tool and show that the proposed topology provides manifold increase in end-to-end reliability. PMID:22294890

  17. Temporal condensation and dynamic λ-transition within the complex network: an application to real-life market evolution

    NASA Astrophysics Data System (ADS)

    Wiliński, Mateusz; Szewczak, Bartłomiej; Gubiec, Tomasz; Kutner, Ryszard; Struzik, Zbigniew R.

    2015-02-01

    We fill a void in merging empirical and phenomenological characterisation of the dynamical phase transitions in complex networks by identifying and thoroughly characterising a triple sequence of such transitions on a real-life financial market. We extract and interpret the empirical, numerical, and analytical evidences for the existence of these dynamical phase transitions, by considering the medium size Frankfurt stock exchange (FSE), as a typical example of a financial market. By using the canonical object for the graph theory, i.e. the minimal spanning tree (MST) network, we observe: (i) the (initial) dynamical phase transition from equilibrium to non-equilibrium nucleation phase of the MST network, occurring at some critical time. Coalescence of edges on the FSE's transient leader (defined by its largest degree) is observed within the nucleation phase; (ii) subsequent acceleration of the process of nucleation and the emergence of the condensation phase (the second dynamical phase transition), forming a logarithmically diverging temporal λ-peak of the leader's degree at the second critical time; (iii) the third dynamical fragmentation phase transition (after passing the second critical time), where the λ-peak logarithmically relaxes over three quarters of the year, resulting in a few loosely connected sub-graphs. This λ-peak (comparable to that of the specific heat vs. temperature forming during the equilibrium continuous phase transition from the normal fluid I 4He to the superfluid II 4He) is considered as a prominent result of a non-equilibrium superstar-like superhub or a dragon-king's abrupt evolution over about two and a half year of market evolution. We capture and meticulously characterise a remarkable phenomenon in which a peripheral company becomes progressively promoted to become the dragon-king strongly dominating the complex network over an exceptionally long period of time containing the crash. Detailed analysis of the complete trio of the

  18. Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding.

    PubMed

    Ghanbari, Yasser; Smith, Alex R; Schultz, Robert T; Verma, Ragini

    2014-12-01

    Diffusion tensor imaging (DTI) offers rich insights into the physical characteristics of white matter (WM) fiber tracts and their development in the brain, facilitating a network representation of brain's traffic pathways. Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging. The high dimensionality of these connectivity networks necessitates the development of methods that identify the connectivity building blocks or sub-network components that characterize the underlying variation in the population. In addition, the projection of the subject networks into the basis set provides a low dimensional representation of it, that teases apart different sources of variation in the sample, facilitating variation-specific statistical analysis. We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive basis set, as well as, additional basis sets representing variational sources in the population like age and pathology. The proposed framework is applied to a study of diffusion-based connectivity in subjects with autism that shows localized sparse sub-networks which mostly capture the changes related to pathology and developmental variations. PMID:25037933

  19. Development of Improved Models, Stochasticity, and Frameworks for the MIT Extensible Air Network Simulation

    NASA Technical Reports Server (NTRS)

    Clarke, John-Paul

    2004-01-01

    MEANS, the MIT Extensible Air Network Simulation, was created in February of 2001, and has been developed with support from NASA Ames since August of 2001. MEANS is a simulation tool which is designed to maximize fidelity without requiring data of such a low level as to preclude easy examination of alternative scenarios. To this end, MEANS is structured in a modular fashion to allow more detailed components to be brought in when desired, and left out when they would only be an impediment. Traditionally, one of the difficulties with high-fidelity models is that they require a level of detail in their data that is difficult to obtain. For analysis of past scenarios, the required data may not have been collected, or may be considered proprietary and thus difficult for independent researchers to obtain. For hypothetical scenarios, generation of the data is sufficiently difficult to be a task in and of itself. Often, simulations designed by a researcher will model exactly one element of the problem well and in detail, while assuming away other parts of the problem which are not of interest or for which data is not available. While these models are useful for working with the task at hand, they are very often not applicable to future problems. The MEAN Simulation attempts to address these problems by using a modular design which provides components of varying fidelity for each aspect of the simulation. This allows for the most accurate model for which data is available to be used. It also provides for easy analysis of sensitivity to data accuracy. This can be particularly useful in the case where accurate data is available for some subset of the situations that are to be considered. Furthermore, the ability to use the same model while examining effects on different parts of a system reduces the time spent learning the simulation, and provides for easier comparisons between changes to different parts of the system.

  20. The use of existing environmental networks for the post-market monitoring of GM crop cultivation in the EU.

    PubMed

    Smets, G; Alcalde, E; Andres, D; Carron, D; Delzenne, P; Heise, A; Legris, G; Martinez Parrilla, M; Verhaert, J; Wandelt, C; Ilegems, M; Rüdelsheim, P

    2014-07-01

    The European Union (EU) Directive 2001/18/EC on the deliberate release of genetically modified organisms (GMOs) into the environment requires that both Case-Specific Monitoring (CSM) and General Surveillance (GS) are considered as post-market implementing measures. Whereas CSM is directed to monitor potential adverse effects of GMOs or their use identified in the environmental risk assessment, GS aims to detect un-intended adverse effects of GMOs or their use on human and animal health or the environment. Guidance documents on the monitoring of genetically modified (GM) plants from the Commission and EFSA clarify that, as appropriate, GS can make use of established routine surveillance practices. Networks involved in routine surveillance offer recognised expertise in a particular domain and are designed to collect information on important environmental aspects over a large geographical area. However, as the suitability of existing monitoring networks to provide relevant data for monitoring impacts of GMOs is not known, plant biotechnology companies developed an approach to describe the processes and criteria that will be used for selecting and evaluating existing monitoring systems. In this paper, the availability of existing monitoring networks for this purpose is evaluated. By cataloguing the existing environmental monitoring networks in the EU, it can be concluded that they can only be used, in the context of GMO cultivation monitoring, as secondary tools to collect baseline information. PMID:24836113

  1. Building cost-effective networks for the home market, using programmable splitters and flexible PONs

    NASA Astrophysics Data System (ADS)

    Queller, Abe

    2005-02-01

    PONs are gaining popularity in areas with high population density. Extensive deployment of fiber plant, along with the introduction of cost effective network devices promise ample of affordable bandwidth to the home and the premise. The distribution network is typically organized as tree architecture and utilizes simple optical splitters. The use of fixed splitters results, however, in a rigid topology, incapable of changes or expansion to meet the needs of demographic changes. A new breed of splitters, based on Planar Lightwave Circuit (PLC) technology, allows service providers to programmatically change the split rations. This feature facilitates a phased build-out of the PON network or changes to the network topology. This article describes the underlying technology for these programmable splitters and explains how they can add flexibility to PON networks.

  2. Modeling cell apoptosis for simulating three-dimensional multicellular morphogenesis based on a reversible network reconnection framework.

    PubMed

    Okuda, Satoru; Inoue, Yasuhiro; Eiraku, Mototsugu; Adachi, Taiji; Sasai, Yoshiki

    2016-08-01

    Morphogenesis in multicellular organisms is accompanied by apoptotic cell behaviors: cell shrinkage and cell disappearance. The mechanical effects of these behaviors are spatiotemporally regulated within multicellular dynamics to achieve proper tissue sizes and shapes in three-dimensional (3D) space. To analyze 3D multicellular dynamics, 3D vertex models have been suggested, in which a reversible network reconnection (RNR) model has successfully expressed 3D cell rearrangements during large deformations. To analyze the effects of apoptotic cell behaviors on 3D multicellular morphogenesis, we modeled cell apoptosis based on the RNR model framework. Cell shrinkage was modeled by the potential energy as a function of individual cell times during the apoptotic phase. Cell disappearance was modeled by merging neighboring polyhedrons at their boundary surface according to the topological rules of the RNR model. To establish that the apoptotic cell behaviors could be expressed as modeled, we simulated morphogenesis driven by cell apoptosis in two types of tissue topology: 3D monolayer cell sheet and 3D compacted cell aggregate. In both types of tissue topology, the numerical simulations successfully illustrated that cell aggregates gradually shrank because of successive cell apoptosis. During tissue shrinkage, the number of cells in aggregates decreased while maintaining individual cell size and shape. Moreover, in case of localizing apoptotic cells within a part of the 3D monolayer cell aggregate, the cell apoptosis caused the global tissue bending by pulling on surrounding cells. In case of localizing apoptotic cells on the surface of the 3D compacted cell aggregate, the cell apoptosis caused successive, directional cell rearrangements from the inside to the surface. Thus, the proposed model successfully provided a basis for expressing apoptotic cell behaviors during 3D multicellular morphogenesis based on an RNR model framework. PMID:26361766

  3. The Pan-University Network for Global Health: framework for collaboration and review of global health needs.

    PubMed

    Winchester, M S; BeLue, R; Oni, T; Wittwer-Backofen, U; Deobagkar, D; Onya, H; Samuels, T A; Matthews, S A; Stone, C; Airhihenbuwa, C

    2016-01-01

    In the current United Nations efforts to plan for post 2015-Millennium Development Goals, global partnership to address non-communicable diseases (NCDs) has become a critical goal to effectively respond to the complex global challenges of which inequity in health remains a persistent challenge. Building capacity in terms of well-equipped local researchers and service providers is a key to bridging the inequity in global health. Launched by Penn State University in 2014, the Pan University Network for Global Health responds to this need by bridging researchers at more than 10 universities across the globe. In this paper we outline our framework for international and interdisciplinary collaboration, as well the rationale for our research areas, including a review of these two themes. After its initial meeting, the network has established two central thematic priorities: 1) urbanization and health and 2) the intersection of infectious diseases and NCDs. The urban population in the global south will nearly double in 25 years (approx. 2 billion today to over 3.5 billion by 2040). Urban population growth will have a direct impact on global health, and this growth will be burdened with uneven development and the persistence of urban spatial inequality, including health disparities. The NCD burden, which includes conditions such as hypertension, stroke, and diabetes, is outstripping infectious disease in countries in the global south that are considered to be disproportionately burdened by infectious diseases. Addressing these two priorities demands an interdisciplinary and multi-institutional model to stimulate innovation and synergy that will influence the overall framing of research questions as well as the integration and coordination of research. PMID:27097634

  4. Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules.

    PubMed

    Menon, Govind; Krishnan, J

    2016-07-21

    While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks. PMID:27448907

  5. Bridging the gap between modules in isolation and as part of networks: A systems framework for elucidating interaction and regulation of signalling modules

    NASA Astrophysics Data System (ADS)

    Menon, Govind; Krishnan, J.

    2016-07-01

    While signalling and biochemical modules have been the focus of numerous studies, they are typically studied in isolation, with no examination of the effects of the ambient network. In this paper we formulate and develop a systems framework, rooted in dynamical systems, to understand such effects, by studying the interaction of signalling modules. The modules we consider are (i) basic covalent modification, (ii) monostable switches, (iii) bistable switches, (iv) adaptive modules, and (v) oscillatory modules. We systematically examine the interaction of these modules by analyzing (a) sequential interaction without shared components, (b) sequential interaction with shared components, and (c) oblique interactions. Our studies reveal that the behaviour of a module in isolation may be substantially different from that in a network, and explicitly demonstrate how the behaviour of a given module, the characteristics of the ambient network, and the possibility of shared components can result in new effects. Our global approach illuminates different aspects of the structure and functioning of modules, revealing the importance of dynamical characteristics as well as biochemical features; this provides a methodological platform for investigating the complexity of natural modules shaped by evolution, elucidating the effects of ambient networks on a module in multiple cellular contexts, and highlighting the capabilities and constraints for engineering robust synthetic modules. Overall, such a systems framework provides a platform for bridging the gap between non-linear information processing modules, in isolation and as parts of networks, and a basis for understanding new aspects of natural and engineered cellular networks.

  6. Developing a conceptual framework for an evaluation system for the NIAID HIV/AIDS clinical trials networks

    PubMed Central

    Kagan, Jonathan M; Kane, Mary; Quinlan, Kathleen M; Rosas, Scott; Trochim, William MK

    2009-01-01

    Globally, health research organizations are called upon to re-examine their policies and practices to more efficiently and effectively address current scientific and social needs, as well as increasing public demands for accountability. Through a case study approach, the authors examine an effort undertaken by the National Institute of Allergy & Infectious Diseases (part of the National Institutes of Health, Department of Health & Human Services, United States Government) to develop an evaluation system for its recently restructured HIV/AIDS clinical trials program. The challenges in designing, operationalizing, and managing global clinical trials programs are considered in the context of large scale scientific research initiatives. Through a process of extensive stakeholder input, a framework of success factors was developed that enables both a prospective view of the elements that must be addressed in an evaluation of this research and a current state assessment of the extent to which the goals of the restructuring are understood by stakeholders across the DAIDS clinical research networks. PMID:19460164

  7. Improvements of the Regional Seismic network of Northwestern Italy in the framework of ALCoTra program activities

    NASA Astrophysics Data System (ADS)

    Bosco, Fabrizio

    2014-05-01

    Arpa Piemonte (Regional Agency for Environmental Protection), in partnership with University of Genoa, manages the regional seismic network, which is part of the Regional Seismic network of Northwestern Italy (RSNI). The network operates since the 80s and, over the years, it has developed in technological features, analysis procedures and geographical coverage. In particular in recent years the network has been further enhanced through the integration of Swiss and French stations installed in the cross-border area. The environmental context enables the installation of sensors in sites with good conditions as regards ambient noise and limited local amplification effects (as proved by PSD analysis, signal quality monitoring via PQLX, H/V analysis). The instrumental equipment consists of Broadband and Very Broadband sensors (Nanometrics Trillium 40" and 240") and different technological solutions for signals real-time transmission (cable, satellite, GPRS), according to the different local environment, with redundant connections and with experimental innovative systems. Digital transmission and acquisition systems operate through standard protocols (Nanometrics, SeedLink), with redundancy in data centers (Genoa, Turin, Rome). Both real-time automatic and manual operational procedures are in use for signals analysis (events detection, picking, focal parameters and ground shaking determination). In the framework of cross-border cooperation program ALCoTra (http://www.interreg-alcotra.org), approved by the European Commission, several projects have been developed to improve the performances of seismic monitoring systems used by partners (Arpa Piemonte, Aosta Valley Region, CNRS, Joseph Fourier University). The cross-border context points out first of all the importance of signals sharing (from 14 to 23 stations in narrow French-Italian border area, with an increase of over 50%) and of coordination during new stations planning and installation in the area. In the ongoing

  8. [Reform steps toward networking sheltered workshops and the general labour market].

    PubMed

    Wendt, S

    2010-02-01

    Only 0.16% of disabled employees are enabled to change from sheltered workshops to the general labour market. At the same time the number of disabled employees in sheltered workshops is increasing more than anticipated. Investigations into the growing admissions to sheltered workshops resulted in recommendations to improve the practice of change over. More and more admissions of students having finished special schools could be reduced by improved cooperation between special schools and the local employment market. Special schools should offer suitable job trainings and support students to develop an understanding of the requirements of specific jobs and of their opportunities to develop their skills to do these jobs. In 2009, supported employment has been regulated in social security law, lasting up to three years and aimed at qualifying disabled youngsters for employment in the general labour market instead of entering sheltered workshops. The majority of admissions to sheltered workshops in the meantime concern people with psychological handicaps, with more than 30% however leaving the workshops later on. For this population, "virtual sheltered workshops" are offering more suitable means for reintegration in the general labour market, such as temporary employment in the general labour market or in occupations with small earnings. The personal budget for work is meant to be a model project within the German Länder, to transfer personal support from the sheltered workshop into the general labour market. The conference of German Länder Ministers of Social Affairs has been active since 2007 to develop a concept for reform of the social security law concerning integration assistance for disabled people, which in future is to concentrate on individual needs, removal of obstacles in the law to facilitate the transition from sheltered workshops into the general labour market. The "Deutsche Verein für öffentliche und private Fürsorge" (German association for public

  9. Investigating the Evolution of Key Member Roles in Socio-Technical Networks--Introducing the Composite Role Framework

    ERIC Educational Resources Information Center

    Lid, Viil

    2013-01-01

    The vitality of socio-technical networks, like online communities and social networks, is predominantly dependent upon active member participation. In most socio-technical networks a minority of members participate more than others and thus play key roles that sustain the value of the network. The overarching objective of this study was to extend…

  10. Using a social marketing framework to evaluate recruitment of a prospective study of genetic counseling and testing for the deaf community

    PubMed Central

    2013-01-01

    -based locations (Place). English-users were more likely to be recruited through mass media (Promotion) while ASL-users were more likely to be recruited through community events and to respond to messaging that emphasized inclusion of a Deaf perspective. Conclusions This study design effectively engaged the deaf population, particularly sign language-users. Results suggest that the deaf population’s cultural and linguistic diversity, geography, and forms of information exchange must be taken into account in study designs for successful recruitment. A social marketing approach that incorporates critical social determinants of health provides a novel and important framework for genetics health service research targeting specific, and hard-to-reach, underserved groups. PMID:24274380

  11. Networking health: multi-level marketing of health products in Ghana.

    PubMed

    Droney, Damien

    2016-01-01

    Multi-level marketing (MLM0), a business model in which product distributors are compensated for enrolling further distributors as well as for selling products, has experienced dramatic growth in recent decades, especially in the so-called global South. This paper argues that the global success of MLM is due to its involvement in local health markets. While MLM has been subject to a number of critiques, few have analyzed the explicit health claims of MLM distributors. The majority of the products distributed through MLM are health products, which are presented as offering transformative health benefits. Based on interviews with MLM distributors in Ghana, but focusing on the experiences of one woman, this paper shows that MLM companies become intimately entwined with Ghanaian quests for health by providing their distributors with the materials to become informal health experts, allowing their distributors to present their products as medicines, and presenting MLM as an avenue to middle class cosmopolitanism. Ghanaian distributors promote MLM products as medically powerful, and the distribution of these products as an avenue to status and profit. As a result, individuals seeking health become a part of ethically questionable forms of medical provision based on the exploitation of personal relationships. The success of MLM therefore suggests that the health industry is at the forefront of transnational corporations' extraction of value from informal economies, drawing on features of health markets to monetize personal relationships. PMID:26130429

  12. Effective and Efficient Correlation Analysis with Application to Market Basket Analysis and Network Community Detection

    ERIC Educational Resources Information Center

    Duan, Lian

    2012-01-01

    Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. For example, what kinds of items should be recommended with regard to what has been purchased by a customer? How to arrange the store shelf in order to increase sales? How to partition the whole social network into…

  13. Inferring the interplay between network structure and market effects in Bitcoin

    NASA Astrophysics Data System (ADS)

    Kondor, Dániel; Csabai, István; Szüle, János; Pósfai, Márton; Vattay, Gábor

    2014-12-01

    A main focus in economics research is understanding the time series of prices of goods and assets. While statistical models using only the properties of the time series itself have been successful in many aspects, we expect to gain a better understanding of the phenomena involved if we can model the underlying system of interacting agents. In this article, we consider the history of Bitcoin, a novel digital currency system, for which the complete list of transactions is available for analysis. Using this dataset, we reconstruct the transaction network between users and analyze changes in the structure of the subgraph induced by the most active users. Our approach is based on the unsupervised identification of important features of the time variation of the network. Applying the widely used method of Principal Component Analysis to the matrix constructed from snapshots of the network at different times, we are able to show how structural changes in the network accompany significant changes in the exchange price of bitcoins.

  14. Marketing Youth Services.

    ERIC Educational Resources Information Center

    Dimick, Barbara

    1995-01-01

    Marketing techniques in youth services are useful for designing programs, collections, and services and for determining customer needs. The marketing mix--product, place, price, and practice--provides a framework for service analysis. (AEF)

  15. Supply chain network design problem for a new market opportunity in an agile manufacturing system

    NASA Astrophysics Data System (ADS)

    Babazadeh, Reza; Razmi, Jafar; Ghodsi, Reza

    2012-08-01

    The characteristics of today's competitive environment, such as the speed with which products are designed, manufactured, and distributed, and the need for higher responsiveness and lower operational cost, are forcing companies to search for innovative ways to do business. The concept of agile manufacturing has been proposed in response to these challenges for companies. This paper copes with the strategic and tactical level decisions in agile supply chain network design. An efficient mixed-integer linear programming model that is able to consider the key characteristics of agile supply chain such as direct shipments, outsourcing, different transportation modes, discount, alliance (process and information integration) between opened facilities, and maximum waiting time of customers for deliveries is developed. In addition, in the proposed model, the capacity of facilities is determined as decision variables, which are often assumed to be fixed. Computational results illustrate that the proposed model can be applied as a power tool in agile supply chain network design as well as in the integration of strategic decisions with tactical decisions.

  16. Effects of financial crisis on the industry sector of Chinese stock market — from a perspective of complex network

    NASA Astrophysics Data System (ADS)

    Yang, Chunxia; Chen, Yanhua; Hao, Weiwei; Shen, Ying; Tang, Minxuan; Niu, Lei

    2014-05-01

    In this paper, we use mutual information to measure the statistical interdependence between 23 industry sectors of Shanghai stock market and construct corresponding correlation network to analyze the shock of 2008 financial crisis on industry sectors. The obtained meaningful facts are as follows. First, such crisis has only a limited impact on leading industries such as Manufacturing, Commercial trade and Machinery & Equipment, which still play an important role in Chinese economy. Second, the crisis badly attacks China's export industries like Electronics, Wood & Furniture and Textile & Clothing. The damage further hurts other industries, and then export industries' influence becomes larger. Third, the crisis adversely impacts the import industries like Petrochemical, Metal & Nonmetal and Pharmaceutical Biotechnology. While due to the stimulation of macroeconomic policies, the influence of crisis on import industries is limited. Similarly, due to relatively strict capital control and the macroeconomic policies stimulating the domestic demand, those industries like Construction, Real Estate and Financial Services are slightly wounded. All these findings suggest that Chinese government should transform from the external demand to the domestic consumption to sustain economic growth.

  17. An Analytical Framework for Studying Small-Number Effects in Catalytic Reaction Networks: A Probability Generating Function Approach to Chemical Master Equations

    PubMed Central

    Nakagawa, Masaki; Togashi, Yuichi

    2016-01-01

    Cell activities primarily depend on chemical reactions, especially those mediated by enzymes, and this has led to these activities being modeled as catalytic reaction networks. Although deterministic ordinary differential equations of concentrations (rate equations) have been widely used for modeling purposes in the field of systems biology, it has been pointed out that these catalytic reaction networks may behave in a way that is qualitatively different from such deterministic representation when the number of molecules for certain chemical species in the system is small. Apart from this, representing these phenomena by simple binary (on/off) systems that omit the quantities would also not be feasible. As recent experiments have revealed the existence of rare chemical species in cells, the importance of being able to model potential small-number phenomena is being recognized. However, most preceding studies were based on numerical simulations, and theoretical frameworks to analyze these phenomena have not been sufficiently developed. Motivated by the small-number issue, this work aimed to develop an analytical framework for the chemical master equation describing the distributional behavior of catalytic reaction networks. For simplicity, we considered networks consisting of two-body catalytic reactions. We used the probability generating function method to obtain the steady-state solutions of the chemical master equation without specifying the parameters. We obtained the time evolution equations of the first- and second-order moments of concentrations, and the steady-state analytical solution of the chemical master equation under certain conditions. These results led to the rank conservation law, the connecting state to the winner-takes-all state, and analysis of 2-molecules M-species systems. A possible interpretation of the theoretical conclusion for actual biochemical pathways is also discussed. PMID:27047384

  18. An Analytical Framework for Studying Small-Number Effects in Catalytic Reaction Networks: A Probability Generating Function Approach to Chemical Master Equations.

    PubMed

    Nakagawa, Masaki; Togashi, Yuichi

    2016-01-01

    Cell activities primarily depend on chemical reactions, especially those mediated by enzymes, and this has led to these activities being modeled as catalytic reaction networks. Although deterministic ordinary differential equations of concentrations (rate equations) have been widely used for modeling purposes in the field of systems biology, it has been pointed out that these catalytic reaction networks may behave in a way that is qualitatively different from such deterministic representation when the number of molecules for certain chemical species in the system is small. Apart from this, representing these phenomena by simple binary (on/off) systems that omit the quantities would also not be feasible. As recent experiments have revealed the existence of rare chemical species in cells, the importance of being able to model potential small-number phenomena is being recognized. However, most preceding studies were based on numerical simulations, and theoretical frameworks to analyze these phenomena have not been sufficiently developed. Motivated by the small-number issue, this work aimed to develop an analytical framework for the chemical master equation describing the distributional behavior of catalytic reaction networks. For simplicity, we considered networks consisting of two-body catalytic reactions. We used the probability generating function method to obtain the steady-state solutions of the chemical master equation without specifying the parameters. We obtained the time evolution equations of the first- and second-order moments of concentrations, and the steady-state analytical solution of the chemical master equation under certain conditions. These results led to the rank conservation law, the connecting state to the winner-takes-all state, and analysis of 2-molecules M-species systems. A possible interpretation of the theoretical conclusion for actual biochemical pathways is also discussed. PMID:27047384

  19. Integrating a flexible modeling framework (FMF) with the network security assessment instrument to reduce software security risk

    NASA Technical Reports Server (NTRS)

    Gilliam, D. P.; Powell, J. D.

    2002-01-01

    This paper presents a portion of an overall research project on the generation of the network security assessment instrument to aid developers in assessing and assuring the security of software in the development and maintenance lifecycles.

  20. Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

    USGS Publications Warehouse

    Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

    2011-01-01

    Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

  1. Home and Clinical Cardiovascular Care Center (H4C): a Framework for Integrating Body Sensor Networks and QTRU Cryptography System

    PubMed Central

    Zakerolhosseini, Ali; Sokouti, Massoud; Pezeshkian, Massoud

    2013-01-01

    Quick responds to heart attack patients before arriving to hospital is a very important factor. In this paper, a combined model of Body Sensor Network and Personal Digital Access using QTRU cipher algorithm in Wifi networks is presented to efficiently overcome these life threatening attacks. The algorithm for optimizing the routing paths between sensor nodes and an algorithm for reducing the power consumption are also applied for achieving the best performance by this model. This system is consumes low power and has encrypting and decrypting processes. It also has an efficient routing path in a fast manner. PMID:24252988

  2. Home and Clinical Cardiovascular Care Center (H4C): a Framework for Integrating Body Sensor Networks and QTRU Cryptography System.

    PubMed

    Zakerolhosseini, Ali; Sokouti, Massoud; Pezeshkian, Massoud

    2013-01-01

    Quick responds to heart attack patients before arriving to hospital is a very important factor. In this paper, a combined model of Body Sensor Network and Personal Digital Access using QTRU cipher algorithm in Wifi networks is presented to efficiently overcome these life threatening attacks. The algorithm for optimizing the routing paths between sensor nodes and an algorithm for reducing the power consumption are also applied for achieving the best performance by this model. This system is consumes low power and has encrypting and decrypting processes. It also has an efficient routing path in a fast manner. PMID:24252988

  3. The study and implementation of the wireless network data security model

    NASA Astrophysics Data System (ADS)

    Lin, Haifeng

    2013-03-01

    In recent years, the rapid development of Internet technology and the advent of information age, people are increasing the strong demand for the information products and the market for information technology. Particularly, the network security requirements have become more sophisticated. This paper analyzes the wireless network in the data security vulnerabilities. And a list of wireless networks in the framework is the serious defects with the related problems. It has proposed the virtual private network technology and wireless network security defense structure; and it also given the wireless networks and related network intrusion detection model for the detection strategies.

  4. Networks.

    ERIC Educational Resources Information Center

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

    2001-01-01

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

  5. Optimization of Network Topology in Computer-Aided Detection Schemes Using Phased Searching with NEAT in a Time-Scaled Framework

    PubMed Central

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-01-01

    In the field of computer-aided mammographic mass detection, many different features and classifiers have been tested. Frequently, the relevant features and optimal topology for the artificial neural network (ANN)-based approaches at the classification stage are unknown, and thus determined by trial-and-error experiments. In this study, we analyzed a classifier that evolves ANNs using genetic algorithms (GAs), which combines feature selection with the learning task. The classifier named “Phased Searching with NEAT in a Time-Scaled Framework” was analyzed using a dataset with 800 malignant and 800 normal tissue regions in a 10-fold cross-validation framework. The classification performance measured by the area under a receiver operating characteristic (ROC) curve was 0.856 ± 0.029. The result was also compared with four other well-established classifiers that include fixed-topology ANNs, support vector machines (SVMs), linear discriminant analysis (LDA), and bagged decision trees. The results show that Phased Searching outperformed the LDA and bagged decision tree classifiers, and was only significantly outperformed by SVM. Furthermore, the Phased Searching method required fewer features and discarded superfluous structure or topology, thus incurring a lower feature computational and training and validation time requirement. Analyses performed on the network complexities evolved by Phased Searching indicate that it can evolve optimal network topologies based on its complexification and simplification parameter selection process. From the results, the study also concluded that the three classifiers – SVM, fixed-topology ANN, and Phased Searching with NeuroEvolution of Augmenting Topologies (NEAT) in a Time-Scaled Framework – are performing comparably well in our mammographic mass detection scheme. PMID:25392680

  6. Multi-agent framework for negotiation in a closed environment

    NASA Astrophysics Data System (ADS)

    Cretan, Adina; Coutinho, Carlos; Bratu, Ben; Jardim-Goncalves, Ricardo

    2013-10-01

    The goal of this paper is to offer support for small and medium enterprises which cannot or do not want to fulfill a big contract alone. Each organization has limited resources and in order to better accomplish a higher external demand, the managers are forced to outsource parts of their contracts even to concurrent organizations. In this concurrent environment each enterprise wants to preserve its decision autonomy and to disclose as little as possible from its business information. To describe this interaction, our approach is to define a framework for managing parallel and concurrent negotiations among independent organizations acting in the same industrial market. The complexity of our negotiation framework is done by the dynamic environment in which multi-attribute and multi-participant negotiations are racing over the same set of resources. Moreover, the proposed framework helps the organizations within the collaborative networked environment to augment their efficiency and ability to react to unforeseen situations, thus improving their market competitiveness.

  7. Host-guest architectures with a surface confined imine covalent organic framework as two-dimensional host networks.

    PubMed

    Sun, Jiang; Zhou, Xin; Lei, Shengbin

    2016-07-01

    A two-dimensional covalent organic framework (2D COF), synthesized on a highly oriented pyrolytic graphite (HOPG) surface with benzene-1,3,5-tricarbaldehyde and p-phenylenediamine as the precursors, is used as a host to accommodate three guest molecules, coronene, copper phthalocyanine (CuPc), and fluorine-substituted copper phthalocyanine (F16CuPc). The host-guest interaction and dynamic behavior were investigated by scanning tunneling microscopy and density functional theory. PMID:27333296

  8. Gene Networks Involved in Hormonal Control of Root Development in Arabidopsis thaliana: A Framework for Studying Its Disturbance by Metal Stress.

    PubMed

    De Smet, Stefanie; Cuypers, Ann; Vangronsveld, Jaco; Remans, Tony

    2015-01-01

    Plant survival under abiotic stress conditions requires morphological and physiological adaptations. Adverse soil conditions directly affect root development, although the underlying mechanisms remain largely to be discovered. Plant hormones regulate normal root growth and mediate root morphological responses to abiotic stress. Hormone synthesis, signal transduction, perception and cross-talk create a complex network in which metal stress can interfere, resulting in root growth alterations. We focus on Arabidopsis thaliana, for which gene networks in root development have been intensively studied, and supply essential terminology of anatomy and growth of roots. Knowledge of gene networks, mechanisms and interactions related to the role of plant hormones is reviewed. Most knowledge has been generated for auxin, the best-studied hormone with a pronounced primary role in root development. Furthermore, cytokinins, gibberellins, abscisic acid, ethylene, jasmonic acid, strigolactones, brassinosteroids and salicylic acid are discussed. Interactions between hormones that are of potential importance for root growth are described. This creates a framework that can be used for investigating the impact of abiotic stress factors on molecular mechanisms related to plant hormones, with the limited knowledge of the effects of the metals cadmium, copper and zinc on plant hormones and root development included as case example. PMID:26287175

  9. Gene Networks Involved in Hormonal Control of Root Development in Arabidopsis thaliana: A Framework for Studying Its Disturbance by Metal Stress

    PubMed Central

    De Smet, Stefanie; Cuypers, Ann; Vangronsveld, Jaco; Remans, Tony

    2015-01-01

    Plant survival under abiotic stress conditions requires morphological and physiological adaptations. Adverse soil conditions directly affect root development, although the underlying mechanisms remain largely to be discovered. Plant hormones regulate normal root growth and mediate root morphological responses to abiotic stress. Hormone synthesis, signal transduction, perception and cross-talk create a complex network in which metal stress can interfere, resulting in root growth alterations. We focus on Arabidopsis thaliana, for which gene networks in root development have been intensively studied, and supply essential terminology of anatomy and growth of roots. Knowledge of gene networks, mechanisms and interactions related to the role of plant hormones is reviewed. Most knowledge has been generated for auxin, the best-studied hormone with a pronounced primary role in root development. Furthermore, cytokinins, gibberellins, abscisic acid, ethylene, jasmonic acid, strigolactones, brassinosteroids and salicylic acid are discussed. Interactions between hormones that are of potential importance for root growth are described. This creates a framework that can be used for investigating the impact of abiotic stress factors on molecular mechanisms related to plant hormones, with the limited knowledge of the effects of the metals cadmium, copper and zinc on plant hormones and root development included as case example. PMID:26287175

  10. Generic Overlay Framework

    Energy Science and Technology Software Center (ESTSC)

    2005-09-01

    This software provides a framework for building application layter overlay networks. It includes example overlays that can be used without modification. Also provided are example multicast and routing protocols that can be used with the overlays.

  11. Integrated framework for retrievals in a networked radar environment: Application to the Mid-latitude Continental Convective Clouds Experiment

    NASA Astrophysics Data System (ADS)

    Hardin, J. C.; Chandrasekar, C. V.; Yoshikawa, E.; Ushio, T.

    2012-12-01

    The Mid-Latitude Continental Convective Clouds Experiment (MC3E), was a joint DOE Atmospheric Radiation Measurement (ARM) and NASA Global Precipitation Measurements (GPM) field campaign that took place from April - June 2011 in Central Oklahoma centered at the ARM Southern Great Plains site. The experiment was a collaborative effort between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission Ground Validation (GV) program. The field campaign involved a large suite of observing infrastructure currently available in the central United States, combined with an extensive sounding array, remote sensing and in situ aircraft observations, NASA GPM ground validation remote sensors, and new ARM instrumentation. The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available. The experiment consisted of a large number of ground radars, including NASA scanning dual-polarization radar systems (NPOL) at S-band, wind profilers, and a dense network of surface disdrometers. In addition to these special MC3E instruments, there were three networked scanning X-band radar systems, four wind profilers, a C-band scanning radar, a dual-wavelength (Ka/W) scanning cloud radar. There is extensive literature on the retrieval algorithms for precipitation and cloud parameters from single frequency, dual-polarization radar systems. With the cost of instruments such as radars becoming more affordable, multiple radar deployments are becoming more common in special programs, and the MC3E is a text book example of such a deployment. Networked deployments are becoming more common popularized by the

  12. Fluctuations in reactive networks subject to extrinsic noise studied in the framework of the chemical Langevin equation

    NASA Astrophysics Data System (ADS)

    Berthoumieux, H.

    2016-07-01

    Theoretical and experimental studies have shown that the fluctuations of in vivo systems break the fluctuation-dissipation theorem. One can thus ask what information is contained in the correlation functions of protein concentrations and how they relate to the response of the reactive network to a perturbation. Answers to these questions are of prime importance to extract meaningful parameters from the in vivo fluorescence correlation spectroscopy data. In this paper we study the fluctuations of the concentration of a reactive species involved in a cyclic network that is in a nonequilibrium steady state perturbed by a noisy force, taking into account both the breaking of detailed balance and extrinsic noises. Using a generic model for the network and the extrinsic noise, we derive a chemical Langevin equation that describes the dynamics of the system, we determine the expressions of the correlation functions of the concentrations, and we estimate the deviation of the fluctuation-dissipation theorem and the range of parameters in which an effective temperature can be defined.

  13. Fluctuations in reactive networks subject to extrinsic noise studied in the framework of the chemical Langevin equation.

    PubMed

    Berthoumieux, H

    2016-07-01

    Theoretical and experimental studies have shown that the fluctuations of in vivo systems break the fluctuation-dissipation theorem. One can thus ask what information is contained in the correlation functions of protein concentrations and how they relate to the response of the reactive network to a perturbation. Answers to these questions are of prime importance to extract meaningful parameters from the in vivo fluorescence correlation spectroscopy data. In this paper we study the fluctuations of the concentration of a reactive species involved in a cyclic network that is in a nonequilibrium steady state perturbed by a noisy force, taking into account both the breaking of detailed balance and extrinsic noises. Using a generic model for the network and the extrinsic noise, we derive a chemical Langevin equation that describes the dynamics of the system, we determine the expressions of the correlation functions of the concentrations, and we estimate the deviation of the fluctuation-dissipation theorem and the range of parameters in which an effective temperature can be defined. PMID:27575151

  14. SME 2.0: Roadmap towards Web 2.0-Based Open Innovation in SME-Networks - A Case Study Based Research Framework

    NASA Astrophysics Data System (ADS)

    Lindermann, Nadine; Valcárcel, Sylvia; Schaarschmidt, Mario; von Kortzfleisch, Harald

    Small- and medium sized enterprises (SMEs) are of high social and economic importance since they represent 99% of European enterprises. With regard to their restricted resources, SMEs are facing a limited capacity for innovation to compete with new challenges in a complex and dynamic competitive environment. Given this context, SMEs need to increasingly cooperate to generate innovations on an extended resource base. Our research project focuses on the aspect of open innovation in SME-networks enabled by Web 2.0 applications and referring to innovative solutions of non-competitive daily life problems. Examples are industrial safety, work-life balance issues or pollution control. The project raises the question whether the use of Web 2.0 applications can foster the exchange of creativity and innovative ideas within a network of SMEs and hence catalyze new forms of innovation processes among its participants. Using Web 2.0 applications within SMEs implies consequently breaking down innovation processes to employees’ level and thus systematically opening up a heterogeneous and broader knowledge base to idea generation. In this paper we address first steps on a roadmap towards Web 2.0-based open innovation processes within SME-networks. It presents a general framework for interaction activities leading to open innovation and recommends a regional marketplace as a viable, trust-building driver for further collaborative activities. These findings are based on field research within a specific SME-network in Rhineland-Palatinate Germany, the “WirtschaftsForum Neuwied e.V.”, which consists of roughly 100 heterogeneous SMEs employing about 8,000 workers.

  15. Functional paleoclimate networks of North Atlantic terrestrial proxies: A new tool for studying spatio-temporal climate variability within the Arctic 2k framework

    NASA Astrophysics Data System (ADS)

    Franke, Jasper G.; Donner, Reik V.

    2016-04-01

    The increasing availability of high-resolution paleoclimate proxies allows to not only study climate variations in time, but also temporal changes in spatial variability patterns. In this study we use the method of functional paleoclimate network analysis [1] to investigate changes in the statistical similarity patterns among ensembles of high-resolution terrestrial paleoclimate records from Northern Europe. The study region ranging from Southern Finland over Northern Fennoscandia to Iceland is of paramount importance for reconstructions of the climate of the last two millennia within the Arctic 2k framework, and understanding the associated spatial variability of regional paleoclimate is a key question for further regional reconstructions. The analysis reported here is based on an ensemble of 16 paleoclimate proxy records comprising tree ring data from the Scandinavian Peninsula, different lacustrine archives from Southern Finland and one lake sediment record cored on Iceland, having a common interpretation as proxies of (mainly summer) temperatures. Based on the mentioned selection of existing data sets, we construct complex networks capturing the mutual statistical similarity of the variability recorded by different archives furing different episodes in time. These ''functional'' networks are not restricted to capturing linear Pearson correlations, but can also be obtained based on nonlinear characteristics like mutual information. This allows for comparing non-normally distributed time series or data of different origin like tree ring and lake sediment records as considered in this study. Furthermore, the obtained functional paleoclimate networks are used to test if regional (gridded) proxy-based temperature reconstructions preserve the essential spatial correlation patterns of the underlying archives. Temporal changes in the network structure indicate changing dynamics in the regional climate system and enable us to distinguish different episodes with distinct

  16. Live bird markets characterization and trading network analysis in Mali: Implications for the surveillance and control of avian influenza and Newcastle disease.

    PubMed

    Molia, Sophie; Boly, Ismaël Ardho; Duboz, Raphaël; Coulibaly, Boubacar; Guitian, Javier; Grosbois, Vladimir; Fournié, Guillaume; Pfeiffer, Dirk Udo

    2016-03-01

    Live bird markets (LBMs) play an important role in the transmission of avian influenza (AI) and Newcastle disease (ND) viruses in poultry. Our study had two objectives: (1) characterizing LBMs in Mali with a focus on practices influencing the risk of transmission of AI and ND, and (2) identifying which LBMs should be targeted for surveillance and control based on properties of the live poultry trade network. Two surveys were conducted in 2009-2010: a descriptive study in all 96 LBMs of an area encompassing approximately 98% of the Malian poultry population and a network analysis study in Sikasso county, the main poultry supplying county for the capital city Bamako. Regarding LBMs' characteristics, risk factors for the presence of AI and ND viruses (being open every day, more than 2 days before a bird is sold, absence of zoning to segregate poultry-related work flow areas, waste removal or cleaning and disinfecting less frequently than on a daily basis, trash disposal of dead birds and absence of manure processing) were present in 80-100% of the LBMs. Furthermore, LBMs tended to have wide catchment areas because of consumers' preference for village poultry meat, thereby involving a large number of villages in their supply chain. In the poultry trade network from/to Sikasso county, 182 traders were involved and 685 links were recorded among 159 locations. The network had a heterogeneous degree distribution and four hubs were identified based on measures of in-degrees, out-degrees and betweenness: the markets of Medine and Wayerma and the fairs of Farakala and Niena. These results can be used to design biosecurity-improvement interventions and to optimize the prevention, surveillance and control of transmissible poultry diseases in Malian LBMs. Further studies should investigate potential drivers (seasonality, prices) of the poultry trade network and the acceptability of biosecurity and behavior-change recommendations in the Malian socio-cultural context. PMID

  17. Information security threats and an easy-to-implement attack detection framework for wireless sensor network-based smart grid applications

    NASA Astrophysics Data System (ADS)

    Tuna, G.; Örenbaş, H.; Daş, R.; Kogias, D.; Baykara, M.; K, K.

    2016-03-01

    Wireless Sensor Networks (WSNs) when combined with various energy harvesting solutions managing to prolong the overall lifetime of the system and enhanced capabilities of the communication protocols used by modern sensor nodes are efficiently used in are efficiently used in Smart Grid (SG), an evolutionary system for the modernization of existing power grids. However, wireless communication technology brings various types of security threats. In this study, firstly the use of WSNs for SG applications is presented. Second, the security related issues and challenges as well as the security threats are presented. In addition, proposed security mechanisms for WSN-based SG applications are discussed. Finally, an easy- to-implement and simple attack detection framework to prevent attacks directed to sink and gateway nodes with web interfaces is proposed and its efficiency is proved using a case study.

  18. Barriers and challenges of implementing tobacco control policies in hospitals: applying the institutional analysis and development framework to the Catalan Network of Smoke-Free Hospitals.

    PubMed

    Martinez, Cristina

    2009-08-01

    This article analyzes tobacco control policies in hospitals based on the experience of the Catalan Network of Smoke-Free Hospitals, Spain. The objective is to understand through this case study how tobacco policies are designed and implemented in health care organizations. Because tobacco control is a public health issue, governmental, institutional, and professional involvement is necessary. This article identifies and examines the structure and relationships among the different actors involved in the tobacco control policies in health care organizations using Ostrom's Institutional Analysis and Development framework.This theory helps one understand the policy failures and rethink the future challenges. Critical issues should be reviewed to enhance implementation of smoke-free hospitals-such as assuring the compliance of nonsmoking areas and introducing compulsory tobacco cessation activities that are promoted and monitored by the public administration. The author suggests that relying primarily on an organization's interpretation of rules leads to irregular implementation. PMID:19900946

  19. A Framework for Understanding the Emerging Role of Corticolimbic-Ventral Striatal Networks in OCD-Associated Repetitive Behaviors

    PubMed Central

    Wood, Jesse; Ahmari, Susanne E.

    2015-01-01

    Significant interest in the mechanistic underpinnings of obsessive-compulsive disorder (OCD) has fueled research on the neural origins of compulsive behaviors. Converging clinical and preclinical evidence suggests that abnormal repetitive behaviors are driven by dysfunction in cortico-striatal-thalamic-cortical (CSTC) circuits. These findings suggest that compulsive behaviors arise, in part, from aberrant communication between lateral orbitofrontal cortex (OFC) and dorsal striatum. An important body of work focused on the role of this network in OCD has been instrumental to progress in the field. Disease models focused primarily on these regions, however, fail to capture an important aspect of the disorder: affective dysregulation. High levels of anxiety are extremely prevalent in OCD, as is comorbidity with major depressive disorder. Furthermore, deficits in processing rewards and abnormalities in processing emotional stimuli are suggestive of aberrant encoding of affective information. Accordingly, OCD can be partially characterized as a disease in which behavioral selection is corrupted by exaggerated or dysregulated emotional states. This suggests that the networks producing OCD symptoms likely expand beyond traditional lateral OFC and dorsal striatum circuit models, and highlights the need to cast a wider net in our investigation of the circuits involved in generating and sustaining OCD symptoms. Here, we address the emerging role of medial OFC, amygdala, and ventral tegmental area projections to the ventral striatum (VS) in OCD pathophysiology. The VS receives strong innervation from these affect and reward processing regions, and is therefore poised to integrate information crucial to the generation of compulsive behaviors. Though it complements functions of dorsal striatum and lateral OFC, this corticolimbic-VS network is less commonly explored as a potential source of the pathology underlying OCD. In this review, we discuss this network’s potential role

  20. Strategy-aligned fuzzy approach for market segment evaluation and selection: a modular decision support system by dynamic network process (DNP)

    NASA Astrophysics Data System (ADS)

    Mohammadi Nasrabadi, Ali; Hosseinpour, Mohammad Hossein; Ebrahimnejad, Sadoullah

    2013-05-01

    In competitive markets, market segmentation is a critical point of business, and it can be used as a generic strategy. In each segment, strategies lead companies to their targets; thus, segment selection and the application of the appropriate strategies over time are very important to achieve successful business. This paper aims to model a strategy-aligned fuzzy approach to market segment evaluation and selection. A modular decision support system (DSS) is developed to select an optimum segment with its appropriate strategies. The suggested DSS has two main modules. The first one is SPACE matrix which indicates the risk of each segment. Also, it determines the long-term strategies. The second module finds the most preferred segment-strategies over time. Dynamic network process is applied to prioritize segment-strategies according to five competitive force factors. There is vagueness in pairwise comparisons, and this vagueness has been modeled using fuzzy concepts. To clarify, an example is illustrated by a case study in Iran's coffee market. The results show that success possibility of segments could be different, and choosing the best ones could help companies to be sure in developing their business. Moreover, changing the priority of strategies over time indicates the importance of long-term planning. This fact has been supported by a case study on strategic priority difference in short- and long-term consideration.

  1. Ionothermal synthesis of open-framework metal phosphates with a Kagome lattice network exhibiting canted anti-ferromagnetism

    SciTech Connect

    Wang, Guangmei; Valldor, Martin; Mallick, Bert; Mudring, Anja-Verena

    2014-01-01

    Four open-framework transition-metal phosphates; (NH4)2Co3(HPO4)2F4 (1), (NH4)Co3(HPO4)2(H2PO4)F2 (2), KCo3(HPO4)2(H2PO4)F2 (3), and KFe3(HPO4)2(H2PO4)F2 (4); are prepared by ionothermal synthesis using pyridinium hexafluorophosphate as the ionic liquid. Single-crystal X-ray diffraction analyses reveal that the four compounds contain cobalt/iron–oxygen/fluoride layers with Kagomé topology composed of interlinked face-sharing MO3F3/MO4F2 octahedra. PO3OH pseudo-tetrahedral groups augment the [M3O6F4] (1)/[M3O8F2] layers on both sides to give M3(HPO4)2F4 (1) and M3(HPO4)2F2 (2–4) layers. These layers are stacked along the a axis in a sequence AA…, resulting in the formation of a layer structure for (NH4)2Co3(HPO4)2F4(1). In NH4Co3(HPO4)2(H2PO4)F2 and KM3(HPO4)2(H2PO4)F2, the M3(HPO4)2F2 layers are stacked along the a axis in a sequence AAi… and are connected by [PO3(OH)] tetrahedra, giving rise to a 3-D open framework structure with 10-ring channels along the [001] direction. The negative charges of the inorganic framework are balanced by K+/NH4+ ions located within the channels. The magnetic transition metal cations themselves form layers with stair-case Kagomé topology. Magnetic susceptibility and magnetization measurements reveal that all four compounds exhibit a canted anti-ferromagnetic ground state (Tc = 10 or 13 K for Co and Tc = 27 K for Fe) with different canting angles. The full orbital moment is observed for both Co2+ and Fe2+.

  2. [Study on building index system of risk assessment of post-marketing Chinese patent medicine based on AHP-fuzzy neural network].

    PubMed

    Li, Yuanyuan; Xie, Yanming; Fu, Yingkun

    2011-10-01

    Currently massive researches have been launched about the safety, efficiency and economy of post-marketing Chinese patent medicine (CPM) proprietary Chinese medicine, but it was lack of a comprehensive interpretation. Establishing the risk evaluation index system and risk assessment model of CPM is the key to solve drug safety problems and protect people's health. The clinical risk factors of CPM exist similarities with the Western medicine, can draw lessons from foreign experience, but also have itself multi-factor multivariate multi-level complex features. Drug safety risk assessment for the uncertainty and complexity, using analytic hierarchy process (AHP) to empower the index weights, AHP-based fuzzy neural network to build post-marketing CPM risk evaluation index system and risk assessment model and constantly improving the application of traditional Chinese medicine characteristic is accord with the road and feasible beneficial exploration. PMID:22292377

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

    PubMed

    Hammoudeh, Mohammad; Newman, Robert; Dennett, Christopher; Mount, Sarah; Aldabbas, Omar

    2015-01-01

    This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service. PMID:26378539

  4. Map as a Service: A Framework for Visualising and Maximising Information Return from Multi-Modal Wireless Sensor Networks

    PubMed Central

    Hammoudeh, Mohammad; Newman, Robert; Dennett, Christopher; Mount, Sarah; Aldabbas, Omar

    2015-01-01

    This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service. PMID:26378539

  5. Networking.

    ERIC Educational Resources Information Center

    Duvall, Betty

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-12-01

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

  8. Electrospun carbon nanofibers reinforced 3D porous carbon polyhedra network derived from metal-organic frameworks for capacitive deionization

    PubMed Central

    Liu, Yong; Ma, Jiaqi; Lu, Ting; Pan, Likun

    2016-01-01

    Carbon nanofibers reinforced 3D porous carbon polyhedra network (e-CNF-PCP) was prepared through electrospinning and subsequent thermal treatment. The morphology, structure and electrochemical performance of the e-CNF-PCP were characterized using scanning electron microscopy, Raman spectra, nitrogen adsorption-desorption, cyclic voltammetry and electrochemical impedance spectroscopy, and their electrosorption performance in NaCl solution was studied. The results show that the e-CNF-PCP exhibits a high electrosorption capacity of 16.98 mg g−1 at 1.2 V in 500 mg l−1 NaCl solution, which shows great improvement compared with those of electrospun carbon nanofibers and porous carbon polyhedra. The e-CNF-PCP should be a very promising candidate as electrode material for CDI applications. PMID:27608826

  9. Electrospun carbon nanofibers reinforced 3D porous carbon polyhedra network derived from metal-organic frameworks for capacitive deionization.

    PubMed

    Liu, Yong; Ma, Jiaqi; Lu, Ting; Pan, Likun

    2016-01-01

    Carbon nanofibers reinforced 3D porous carbon polyhedra network (e-CNF-PCP) was prepared through electrospinning and subsequent thermal treatment. The morphology, structure and electrochemical performance of the e-CNF-PCP were characterized using scanning electron microscopy, Raman spectra, nitrogen adsorption-desorption, cyclic voltammetry and electrochemical impedance spectroscopy, and their electrosorption performance in NaCl solution was studied. The results show that the e-CNF-PCP exhibits a high electrosorption capacity of 16.98 mg g(-1) at 1.2 V in 500 mg l(-1) NaCl solution, which shows great improvement compared with those of electrospun carbon nanofibers and porous carbon polyhedra. The e-CNF-PCP should be a very promising candidate as electrode material for CDI applications. PMID:27608826

  10. Understanding Dynamics of Information Transmission in Drosophila melanogaster Using a Statistical Modeling Framework for Longitudinal Network Data (the RSiena Package)

    PubMed Central

    Pasquaretta, Cristian; Klenschi, Elizabeth; Pansanel, Jérôme; Battesti, Marine; Mery, Frederic; Sueur, Cédric

    2016-01-01

    Social learning – the transmission of behaviors through observation or interaction with conspecifics – can be viewed as a decision-making process driven by interactions among individuals. Animal group structures change over time and interactions among individuals occur in particular orders that may be repeated following specific patterns, change in their nature, or disappear completely. Here we used a stochastic actor-oriented model built using the RSiena package in R to estimate individual behaviors and their changes through time, by analyzing the dynamic of the interaction network of the fruit fly Drosophila melanogaster during social learning experiments. In particular, we re-analyzed an experimental dataset where uninformed flies, left free to interact with informed ones, acquired and later used information about oviposition site choice obtained by social interactions. We estimated the degree to which the uninformed flies had successfully acquired the information carried by informed individuals using the proportion of eggs laid by uninformed flies on the medium their conspecifics had been trained to favor. Regardless of the degree of information acquisition measured in uninformed individuals, they always received and started interactions more frequently than informed ones did. However, information was efficiently transmitted (i.e., uninformed flies predominantly laid eggs on the same medium informed ones had learn to prefer) only when the difference in contacts sent between the two fly types was small. Interestingly, we found that the degree of reciprocation, the tendency of individuals to form mutual connections between each other, strongly affected oviposition site choice in uninformed flies. This work highlights the great potential of RSiena and its utility in the studies of interaction networks among non-human animals. PMID:27148146

  11. Understanding Dynamics of Information Transmission in Drosophila melanogaster Using a Statistical Modeling Framework for Longitudinal Network Data (the RSiena Package).

    PubMed

    Pasquaretta, Cristian; Klenschi, Elizabeth; Pansanel, Jérôme; Battesti, Marine; Mery, Frederic; Sueur, Cédric

    2016-01-01

    Social learning - the transmission of behaviors through observation or interaction with conspecifics - can be viewed as a decision-making process driven by interactions among individuals. Animal group structures change over time and interactions among individuals occur in particular orders that may be repeated following specific patterns, change in their nature, or disappear completely. Here we used a stochastic actor-oriented model built using the RSiena package in R to estimate individual behaviors and their changes through time, by analyzing the dynamic of the interaction network of the fruit fly Drosophila melanogaster during social learning experiments. In particular, we re-analyzed an experimental dataset where uninformed flies, left free to interact with informed ones, acquired and later used information about oviposition site choice obtained by social interactions. We estimated the degree to which the uninformed flies had successfully acquired the information carried by informed individuals using the proportion of eggs laid by uninformed flies on the medium their conspecifics had been trained to favor. Regardless of the degree of information acquisition measured in uninformed individuals, they always received and started interactions more frequently than informed ones did. However, information was efficiently transmitted (i.e., uninformed flies predominantly laid eggs on the same medium informed ones had learn to prefer) only when the difference in contacts sent between the two fly types was small. Interestingly, we found that the degree of reciprocation, the tendency of individuals to form mutual connections between each other, strongly affected oviposition site choice in uninformed flies. This work highlights the great potential of RSiena and its utility in the studies of interaction networks among non-human animals. PMID:27148146

  12. Progress and hurdles to forecasting phenology: How networked experiments and a species' traits framework can improve predictions with climate change

    NASA Astrophysics Data System (ADS)

    Wolkovich, E. M.; Cook, B. I.

    2012-12-01

    Accurate predictions of the timing of plant leafing and flowering are critical to models of global carbon budgets and future ecosystem services under climate change scenarios. Yet useful predictions have proven difficult for all but a handful of well-studied tree and crop species; further, comparisons of predictions across methods have highlighted large inconsistencies, which suggest robust forecasting of future ecosystems' plant phenology is still not within reach. Here I highlight how new approaches in ecological research could rapidly contribute to improved understanding of plant phenology across species, growing seasons and ecosystems. I first show how re-designed warming experiments--including standardized methods and analyses--would allow more useful comparisons with other methods and improved opportunities to study non-linearities and phenological cues beyond temperature. I then highlight how a species trait framework is critical for predicting shifts across years and ecosystems. I show that invasive species are generally 20-40% more sensitive to temperature than native species in temperate ecosystems--with responses in summer drought systems more complex and soil moisture dependent. Additionally, I show that annual species are 20% more temperature sensitive than perennials. Such species' responses may be especially critical for predicting longer growing seasons and their related carbon balances in future systems. Combined with a returned focus to the physiology of phenology and standardized experimental approaches ecologically-focused climate change research can allow rapid progress in understanding plant phenology across species and ecosystems.

  13. SmartHome: a domotic framework based on smart sensing and actuator network to reduce energy wastes

    NASA Astrophysics Data System (ADS)

    Santamaria, Amilcare Francesco; De Rango, Floriano; Falbo, Domenico; Barletta, Domenico

    2014-05-01

    Domestic environment and human interaction with services supplied by domotic devices is going to be a very interesting application field. With a domotic system is possible to achieve great interaction between human beings, environments and smart devices. The enhancing of these interactions is the main goal of this work whose intent is to improve the classic concept of domotics. The framework we developed can be used for several application fields such as lighting, heating, conditioning or water management and energy consumption. In particular, the proposed system can optimize energy consumptions by rising awareness to users that have full control of their house and the possibility to save money and reduce the impact of the energetic consumes to the earth, matching the new "green" motto requirements. In this way, the overall system wants to match the central concept of Internet Of Things (IoT) as well. From this point of view a complex automation system with smart devices make possible a more efficient way to produce, follow and manage domotic policies. Following the spread of IoT, for this work we designed and implemented new plug-and-play and ready-to-use smart devices that are part of a complex automation system that offers a user-friendly web application and allows users to control and interact with different plans of their house in order to make life more comfortable and be aware of their energy consumptions. Control and awareness arc the two key points that led us to develop the proposed system.

  14. A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

    PubMed

    Hossain, Moinul; Muromachi, Yasunori

    2012-03-01

    The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. PMID:22269521

  15. Highly efficient nonprecious metal catalyst prepared with metal–organic framework in a continuous carbon nanofibrous network

    DOE PAGESBeta

    Shui, Jianglan; Chen, Chen; Grabstanowicz, Lauren; Zhao, Dan; Liu, Di -Jia

    2015-08-25

    Fuel cell vehicles, the only all-electric technology with a demonstrated >300 miles per fill travel range, use Pt as the electrode catalyst. The high price of Pt creates a major cost barrier for large-scale implementation of polymer electrolyte membrane fuel cells. Nonprecious metal catalysts (NPMCs) represent attractive low-cost alternatives. However, a significantly lower turnover frequency at the individual catalytic site renders the traditional carbon-supported NPMCs inadequate in reaching the desired performance afforded by Pt. Unconventional catalyst design aiming at maximizing the active site density at much improved mass and charge transports is essential for the next-generation NPMC. We report heremore » a method of preparing highly efficient, nanofibrous NPMC for cathodic oxygen reduction reaction by electrospinning a polymer solution containing ferrous organometallics and zeolitic imidazolate framework followed by thermal activation. The catalyst offers a carbon nanonetwork architecture made of microporous nanofibers decorated by uniformly distributed high-density active sites. In a single-cell test, the membrane electrode containing such a catalyst delivered unprecedented volumetric activities of 3.3 A∙cm-3 at 0.9 V or 450 A∙cm-3 extrapolated at 0.8 V, representing the highest reported value in the literature. Improved fuel cell durability was also observed.« less

  16. Highly efficient nonprecious metal catalyst prepared with metal–organic framework in a continuous carbon nanofibrous network

    SciTech Connect

    Shui, Jianglan; Chen, Chen; Grabstanowicz, Lauren; Zhao, Dan; Liu, Di -Jia

    2015-08-25

    Fuel cell vehicles, the only all-electric technology with a demonstrated >300 miles per fill travel range, use Pt as the electrode catalyst. The high price of Pt creates a major cost barrier for large-scale implementation of polymer electrolyte membrane fuel cells. Nonprecious metal catalysts (NPMCs) represent attractive low-cost alternatives. However, a significantly lower turnover frequency at the individual catalytic site renders the traditional carbon-supported NPMCs inadequate in reaching the desired performance afforded by Pt. Unconventional catalyst design aiming at maximizing the active site density at much improved mass and charge transports is essential for the next-generation NPMC. We report here a method of preparing highly efficient, nanofibrous NPMC for cathodic oxygen reduction reaction by electrospinning a polymer solution containing ferrous organometallics and zeolitic imidazolate framework followed by thermal activation. The catalyst offers a carbon nanonetwork architecture made of microporous nanofibers decorated by uniformly distributed high-density active sites. In a single-cell test, the membrane electrode containing such a catalyst delivered unprecedented volumetric activities of 3.3 A∙cm-3 at 0.9 V or 450 A∙cm-3 extrapolated at 0.8 V, representing the highest reported value in the literature. Improved fuel cell durability was also observed.

  17. Highly efficient nonprecious metal catalyst prepared with metal–organic framework in a continuous carbon nanofibrous network

    PubMed Central

    Shui, Jianglan; Chen, Chen; Grabstanowicz, Lauren; Zhao, Dan; Liu, Di-Jia

    2015-01-01

    Fuel cell vehicles, the only all-electric technology with a demonstrated >300 miles per fill travel range, use Pt as the electrode catalyst. The high price of Pt creates a major cost barrier for large-scale implementation of polymer electrolyte membrane fuel cells. Nonprecious metal catalysts (NPMCs) represent attractive low-cost alternatives. However, a significantly lower turnover frequency at the individual catalytic site renders the traditional carbon-supported NPMCs inadequate in reaching the desired performance afforded by Pt. Unconventional catalyst design aiming at maximizing the active site density at much improved mass and charge transports is essential for the next-generation NPMC. We report here a method of preparing highly efficient, nanofibrous NPMC for cathodic oxygen reduction reaction by electrospinning a polymer solution containing ferrous organometallics and zeolitic imidazolate framework followed by thermal activation. The catalyst offers a carbon nanonetwork architecture made of microporous nanofibers decorated by uniformly distributed high-density active sites. In a single-cell test, the membrane electrode containing such a catalyst delivered unprecedented volumetric activities of 3.3 A⋅cm−3 at 0.9 V or 450 A⋅cm−3 extrapolated at 0.8 V, representing the highest reported value in the literature. Improved fuel cell durability was also observed. PMID:26261338

  18. Signalling entropy: A novel network-theoretical framework for systems analysis and interpretation of functional omic data.

    PubMed

    Teschendorff, Andrew E; Sollich, Peter; Kuehn, Reimer

    2014-06-01

    A key challenge in systems biology is the elucidation of the underlying principles, or fundamental laws, which determine the cellular phenotype. Understanding how these fundamental principles are altered in diseases like cancer is important for translating basic scientific knowledge into clinical advances. While significant progress is being made, with the identification of novel drug targets and treatments by means of systems biological methods, our fundamental systems level understanding of why certain treatments succeed and others fail is still lacking. We here advocate a novel methodological framework for systems analysis and interpretation of molecular omic data, which is based on statistical mechanical principles. Specifically, we propose the notion of cellular signalling entropy (or uncertainty), as a novel means of analysing and interpreting omic data, and more fundamentally, as a means of elucidating systems-level principles underlying basic biology and disease. We describe the power of signalling entropy to discriminate cells according to differentiation potential and cancer status. We further argue the case for an empirical cellular entropy-robustness correlation theorem and demonstrate its existence in cancer cell line drug sensitivity data. Specifically, we find that high signalling entropy correlates with drug resistance and further describe how entropy could be used to identify the achilles heels of cancer cells. In summary, signalling entropy is a deep and powerful concept, based on rigorous statistical mechanical principles, which, with improved data quality and coverage, will allow a much deeper understanding of the systems biological principles underlying normal and disease physiology. PMID:24675401

  19. Highly efficient nonprecious metal catalyst prepared with metal-organic framework in a continuous carbon nanofibrous network.

    PubMed

    Shui, Jianglan; Chen, Chen; Grabstanowicz, Lauren; Zhao, Dan; Liu, Di-Jia

    2015-08-25

    Fuel cell vehicles, the only all-electric technology with a demonstrated >300 miles per fill travel range, use Pt as the electrode catalyst. The high price of Pt creates a major cost barrier for large-scale implementation of polymer electrolyte membrane fuel cells. Nonprecious metal catalysts (NPMCs) represent attractive low-cost alternatives. However, a significantly lower turnover frequency at the individual catalytic site renders the traditional carbon-supported NPMCs inadequate in reaching the desired performance afforded by Pt. Unconventional catalyst design aiming at maximizing the active site density at much improved mass and charge transports is essential for the next-generation NPMC. We report here a method of preparing highly efficient, nanofibrous NPMC for cathodic oxygen reduction reaction by electrospinning a polymer solution containing ferrous organometallics and zeolitic imidazolate framework followed by thermal activation. The catalyst offers a carbon nanonetwork architecture made of microporous nanofibers decorated by uniformly distributed high-density active sites. In a single-cell test, the membrane electrode containing such a catalyst delivered unprecedented volumetric activities of 3.3 A ⋅ cm(-3) at 0.9 V or 450 A ⋅ cm(-3) extrapolated at 0.8 V, representing the highest reported value in the literature. Improved fuel cell durability was also observed. PMID:26261338

  20. Marketing the nursing practice of obstetrics.

    PubMed

    Dill, P Z

    1991-01-01

    This article offers nurses a conceptual framework for marketing their skills and discusses how that framework can be applied to obstetric nursing practice. A thorough understanding of the framework presented will provide maternity nurses with the foundation they need to participate effectively in a marketing plan. Examples of the application of the framework to specific clinical situations are examined. PMID:1941295

  1. Towards a Software Framework to Support Deployment of Low Cost End-to-End Hydroclimatological Sensor Network

    NASA Astrophysics Data System (ADS)

    Celicourt, P.; Piasecki, M.

    2015-12-01

    Deployment of environmental sensors assemblies based on cheap platforms such as Raspberry Pi and Arduino have gained much attention over the past few years. While they are more attractive due to their ability to be controlled with a few programming language choices, the configuration task can become quite complex due to the need of having to learn several different proprietary data formats and protocols which constitute a bottleneck for the expansion of sensor network. In response to this rising complexity the Institute of Electrical and Electronics Engineers (IEEE) has sponsored the development of the IEEE 1451 standard in an attempt to introduce a common standard. The most innovative concept of the standard is the Transducer Electronic Data Sheet (TEDS) which enables transducers to self-identify, self-describe, self-calibrate, to exhibit plug-and-play functionality, etc. We used Python to develop an IEEE 1451.0 platform-independent graphical user interface to generate and provide sufficient information about almost ANY sensor and sensor platforms for sensor programming purposes, automatic calibration of sensors data, incorporation of back-end demands on data management in TEDS for automatic standard-based data storage, search and discovery purposes. These features are paramount to make data management much less onerous in large scale sensor network. Along with the TEDS Creator, we developed a tool namely HydroUnits for three specific purposes: encoding of physical units in the TEDS, dimensional analysis, and on-the-fly conversion of time series allowing users to retrieve data in a desired equivalent unit while accommodating unforeseen and user-defined units. In addition, our back-end data management comprises the Python/Django equivalent of the CUAHSI Observations Data Model (ODM) namely DjangODM that will be hosted by a MongoDB Database Server which offers more convenience for our application. We are also developing a data which will be paired with the data

  2. Structural changes in the minimal spanning tree and the hierarchical network in the Korean stock market around the global financial crisis

    NASA Astrophysics Data System (ADS)

    Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

    2015-04-01

    This paper considers stock prices in the Korean stock market during the 2008 global financial crisis by focusing on three time periods: before, during, and after the crisis. Complex networks are extracted from cross-correlation coefficients between the normalized logarithmic return of the stock price time series of firms. The minimal spanning trees (MSTs) and the hierarchical network (HN) are generated from cross-correlation coefficients. Before and after the crisis, securities firms are located at the center of the MST. During the crisis, however, the center of the MST changes to a firm in heavy industry and construction. During the crisis, the MST shrinks in comparison to that before and that after the crisis. This topological change in the MST during the crisis reflects a distinct effect of the global financial crisis. The cophenetic correlation coefficient increases during the crisis, indicating an increase in the hierarchical structure during in this period. When crisis hits the market, firms behave synchronously, and their correlations are higher than those during a normal period.

  3. Integration in primary community care networks (PCCNs): examination of governance, clinical, marketing, financial, and information infrastructures in a national demonstration project in Taiwan

    PubMed Central

    Lin, Blossom Yen-Ju

    2007-01-01

    Background Taiwan's primary community care network (PCCN) demonstration project, funded by the Bureau of National Health Insurance on March 2003, was established to discourage hospital shopping behavior of people and drive the traditional fragmented health care providers into cooperate care models. Between 2003 and 2005, 268 PCCNs were established. This study profiled the individual members in the PCCNs to study the nature and extent to which their network infrastructures have been integrated among the members (clinics and hospitals) within individual PCCNs. Methods The thorough questionnaire items, covering the network working infrastructures – governance, clinical, marketing, financial, and information integration in PCCNs, were developed with validity and reliability confirmed. One thousand five hundred and fifty-seven clinics that had belonged to PCCNs for more than one year, based on the 2003–2005 Taiwan Primary Community Care Network List, were surveyed by mail. Nine hundred and twenty-eight clinic members responded to the surveys giving a 59.6 % response rate. Results Overall, the PCCNs' members had higher involvement in the governance infrastructure, which was usually viewed as the most important for establishment of core values in PCCNs' organization design and management at the early integration stage. In addition, it found that there existed a higher extent of integration of clinical, marketing, and information infrastructures among the hospital-clinic member relationship than those among clinic members within individual PCCNs. The financial infrastructure was shown the least integrated relative to other functional infrastructures at the early stage of PCCN formation. Conclusion There was still room for better integrated partnerships, as evidenced by the great variety of relationships and differences in extent of integration in this study. In addition to provide how the network members have done for their initial work at the early stage of network

  4. An object-oriented modeling and simulation framework for bearings-only multi-target tracking using an unattended acoustic sensor network

    NASA Astrophysics Data System (ADS)

    Aslan, Murat Šamil

    2013-10-01

    Tracking ground targets using low cost ground-based sensors is a challenging field because of the limited capabilities of such sensors. Among the several candidates, including seismic and magnetic sensors, the acoustic sensors based on microphone arrays have a potential of being useful: They can provide a direction to the sound source, they can have a relatively better range, and the sound characteristics can provide a basis for target classification. However, there are still many problems. One of them is the difficulty to resolve multiple sound sources, another is that they do not provide distance, a third is the presence of background noise from wind, sea, rain, distant air and land traffic, people, etc., and a fourth is that the same target can sound very differently depending on factors like terrain type, topography, speed, gear, distance, etc. Use of sophisticated signal processing and data fusion algorithms is the key for compensating (to an extend) the limited capabilities and mentioned problems of these sensors. It is hard, if not impossible, to evaluate the performance of such complex algorithms analytically. For an effective evaluation, before performing expensive field trials, well-designed laboratory experiments and computer simulations are necessary. Along this line, in this paper, we present an object-oriented modeling and simulation framework which can be used to generate simulated data for the data fusion algorithms for tracking multiple on-road targets in an unattended acoustic sensor network. Each sensor node in the network is a circular microphone array which produces the direction of arrival (DOA) (or bearing) measurements of the targets and sends this information to a fusion center. We present the models for road networks, targets (motion and acoustic power) and acoustic sensors in an object-oriented fashion where different and possibly time-varying sampling periods for each sensor node is possible. Moreover, the sensor's signal processing and

  5. Characterizing Soil Hydraulic Parameter Heterogeneity Using Cokriging and Artificial Neural Network: A Framework of Integrating Hard and Soft Data

    NASA Astrophysics Data System (ADS)

    Ye, M.; Schaap, M. G.; Khaleel, R.; Zhu, J.

    2005-12-01

    Characterization of the heterogeneity of hydraulic parameters that control transport processes in the vadose zone is always difficult due to prohibitive investments involved with direct parameter measurements (so-called `hard' data). `Soft' data such as moisture content (θ) and results derived from geophysical measurements, however, carry significant information about media heterogeneity and should be included in site characterization, where possible. We developed a method to incorporate both `hard' and `soft' data using cokriging and artificial neural network (ANN) analyses to generate 3D spatially correlated structures of hydraulic parameters. This method was applied to a field injection experiment carried out in 2000 at the `Sisson and Lu' injection site at the U.S. Department of Energy's Hanford Site, WA. Available data included limited measurements of soil hydraulic parameters (i.e., saturated hydraulic conductivity and van Genuchten parameters, totaling 70 datasets) and soil characterization data (bulk density and percentages of gravel, coarse and fine sand, silt, and clay). A 3D initial θ field reflecting the geologic layering was available at 32 observation wells (1344 locations). We used variograms and cross-variograms to investigate the spatial correlation and cross-correlation of the initial θ measurements and soil characterization data variables. We used ANN-based pedotransfer functions to map soil characterization data to hydraulic parameters. Using initial θ as a secondary variable, we used a cokriging scheme to estimate 3D heterogeneous fields of the primary variables, the soil characterization data and, subsequently, 3D fields of the hydraulic parameters with the pedotransfer functions. These hydraulic parameter fields were then used to simulate the field injection experiment. The spatial moments of the measured and simulated θ were compared to evaluate the robustness of the developed method. The θ profiles at observation wells were

  6. Evaluating nonindigenous species management in a Bayesian networks derived relative risk framework for Padilla Bay, WA, USA.

    PubMed

    Herring, Carlie E; Stinson, Jonah; Landis, Wayne G

    2015-10-01

    Many coastal regions are encountering issues with the spread of nonindigenous species (NIS). In this study, we conducted a regional risk assessment using a Bayesian network relative risk model (BN-RRM) to analyze multiple vectors of NIS introductions to Padilla Bay, Washington, a National Estuarine Research Reserve. We had 3 objectives in this study. The 1st objective was to determine whether the BN-RRM could be used to calculate risk from NIS introductions for Padilla Bay. Our 2nd objective was to determine which regions and endpoints were at greatest risk from NIS introductions. Our 3rd objective was to incorporate a management option into the model and predict endpoint risk if it were to be implemented. Eradication can occur at different stages of NIS invasions, such as the elimination of these species before being introduced to the habitat or removal of the species after settlement. We incorporated the ballast water treatment management scenario into the model, observed the risk to the endpoints, and compared this risk with the initial risk estimates. The model results indicated that the southern portion of the bay was at greatest risk because of NIS. Changes in community composition, Dungeness crab, and eelgrass were the endpoints most at risk from NIS introductions. The currents node, which controls the exposure of NIS to the bay from the surrounding marine environment, was the parameter that had the greatest influence on risk. The ballast water management scenario displayed an approximate 1% reduction in risk in this Padilla Bay case study. The models we developed provide an adaptable template for decision makers interested in managing NIS in other coastal regions and large bodies of water. PMID:25845995

  7. A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

    PubMed

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

  8. A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

    PubMed Central

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

  9. Thermal transformation of a layered multifunctional network into a metal-organic framework based on a polymeric organic linker.

    PubMed

    Silva, Patrícia; Vieira, Fabiana; Gomes, Ana C; Ananias, Duarte; Fernandes, José A; Bruno, Sofia M; Soares, Rosário; Valente, Anabela A; Rocha, João; Paz, Filipe A Almeida

    2011-09-28

    The preparation of layered [La(H(3)nmp)] as microcrystalline powders from optimized microwave-assisted synthesis or dynamic hydrothermal synthesis (i.e., with constant rotation of the autoclaves) from the reaction of nitrilotris(methylenephosphonic acid) (H(6)nmp) with LaCl(3)·7H(2)O is reported. Thermogravimetry in conjunction with thermodiffractometry showed that the material undergoes a microcrystal-to-microcrystal phase transformation above 300 °C, being transformed into either a three-dimensional or a two-dimensional network (two models are proposed based on dislocation of molecular units) formulated as [La(L)] (where L(3-) = [-(PO(3)CH(2))(2)(NH)(CH(2)PO(2))O(1/2)-](n)(3n-)). The two crystal structures were solved from ab initio methods based on powder X-ray diffraction data in conjunction with structural information derived from (13)C and (31)P solid-state NMR, electron microscopy (SEM and EDS mapping), FT-IR spectroscopy, thermodiffractometry, and photoluminescence studies. It is shown that upon heating the coordinated H(3)nmp(3-) anionic organic ligand undergoes a polymerization (condensation) reaction to form in situ a novel and unprecedented one-dimensional polymeric organic ligand. The lanthanum oxide layers act, thus, simultaneously as insulating and templating two-dimensional scaffolds. A rationalization of the various steps involved in these transformations is provided for the two models. Photoluminescent materials, isotypical with both the as-prepared ([(La(0.95)Eu(0.05))(H(3)nmp)] and [(La(0.95)Tb(0.05))(H(3)nmp)]) and the calcined ([(La(0.95)Eu(0.05))(L)]) compounds and containing stoichiometric amounts of optically active lanthanide centers, have been prepared and their photoluminescent properties studied in detail. The lifetimes of Eu(3+) vary between 2.04 ± 0.01 and 2.31 ± 0.01 ms (considering both ambient and low-temperature studies). [La(H(3)nmp)] is shown to be an effective heterogeneous catalyst in the ring opening of styrene oxide with

  10. A framework for the establishment of a cnidarian gene regulatory network for "endomesoderm" specification: the inputs of ß-catenin/TCF signaling.

    PubMed

    Röttinger, Eric; Dahlin, Paul; Martindale, Mark Q

    2012-01-01

    Understanding the functional relationship between intracellular factors and extracellular signals is required for reconstructing gene regulatory networks (GRN) involved in complex biological processes. One of the best-studied bilaterian GRNs describes endomesoderm specification and predicts that both mesoderm and endoderm arose from a common GRN early in animal evolution. Compelling molecular, genomic, developmental, and evolutionary evidence supports the hypothesis that the bifunctional gastrodermis of the cnidarian-bilaterian ancestor is derived from the same evolutionary precursor of both endodermal and mesodermal germ layers in all other triploblastic bilaterian animals. We have begun to establish the framework of a provisional cnidarian "endomesodermal" gene regulatory network in the sea anemone, Nematostella vectensis, by using a genome-wide microarray analysis on embryos in which the canonical Wnt/ß-catenin pathway was ectopically targeted for activation by two distinct pharmaceutical agents (lithium chloride and 1-azakenpaullone) to identify potential targets of endomesoderm specification. We characterized 51 endomesodermally expressed transcription factors and signaling molecule genes (including 18 newly identified) with fine-scale temporal (qPCR) and spatial (in situ) analysis to define distinct co-expression domains within the animal plate of the embryo and clustered genes based on their earliest zygotic expression. Finally, we determined the input of the canonical Wnt/ß-catenin pathway into the cnidarian endomesodermal GRN using morpholino and mRNA overexpression experiments to show that NvTcf/canonical Wnt signaling is required to pattern both the future endomesodermal and ectodermal domains prior to gastrulation, and that both BMP and FGF (but not Notch) pathways play important roles in germ layer specification in this animal. We show both evolutionary conserved as well as profound differences in endomesodermal GRN structure compared to bilaterians

  11. Evolution of microbial markets

    PubMed Central

    Werner, Gijsbert D. A.; Strassmann, Joan E.; Ivens, Aniek B. F.; Engelmoer, Daniel J. P.; Verbruggen, Erik; Queller, David C.; Noë, Ronald; Johnson, Nancy Collins; Hammerstein, Peter; Kiers, E. Toby

    2014-01-01

    Biological market theory has been used successfully to explain cooperative behavior in many animal species. Microbes also engage in cooperative behaviors, both with hosts and other microbes, that can be described in economic terms. However, a market approach is not traditionally used to analyze these interactions. Here, we extend the biological market framework to ask whether this theory is of use to evolutionary biologists studying microbes. We consider six economic strategies used by microbes to optimize their success in markets. We argue that an economic market framework is a useful tool to generate specific and interesting predictions about microbial interactions, including the evolution of partner discrimination, hoarding strategies, specialized versus diversified mutualistic services, and the role of spatial structures, such as flocks and consortia. There is untapped potential for studying the evolutionary dynamics of microbial systems. Market theory can help structure this potential by characterizing strategic investment of microbes across a diversity of conditions. PMID:24474743

  12. Evolution of microbial markets.

    PubMed

    Werner, Gijsbert D A; Strassmann, Joan E; Ivens, Aniek B F; Engelmoer, Daniel J P; Verbruggen, Erik; Queller, David C; Noë, Ronald; Johnson, Nancy Collins; Hammerstein, Peter; Kiers, E Toby

    2014-01-28

    Biological market theory has been used successfully to explain cooperative behavior in many animal species. Microbes also engage in cooperative behaviors, both with hosts and other microbes, that can be described in economic terms. However, a market approach is not traditionally used to analyze these interactions. Here, we extend the biological market framework to ask whether this theory is of use to evolutionary biologists studying microbes. We consider six economic strategies used by microbes to optimize their success in markets. We argue that an economic market framework is a useful tool to generate specific and interesting predictions about microbial interactions, including the evolution of partner discrimination, hoarding strategies, specialized versus diversified mutualistic services, and the role of spatial structures, such as flocks and consortia. There is untapped potential for studying the evolutionary dynamics of microbial systems. Market theory can help structure this potential by characterizing strategic investment of microbes across a diversity of conditions. PMID:24474743

  13. Implementation of an active 'bryomonitoring' network for chemical status and temporal trend assessment under the Water Framework Directive in the Chiampo Valley's tannery district (NE Italy).

    PubMed

    Cesa, Mattia; Baldisseri, Andrea; Bertolini, Giovanni; Dainese, Ezio; Dal Col, Monia; Dalla Vecchia, Ugo; Marchesini, Paolo; Nimis, Pier Luigi

    2013-01-15

    An innovative network based on transplanted bryophytes providing a continuous monitoring of the priority substances Cd, Hg, Ni, and Pb and other trace elements (Co, Cr, Cu, Fe, Mn, Zn) was designed for the watercourses flowing across an industrial district of NE Italy where both permitted and illegal wastes cause sporadic, intermittent or chronic events of environmental alteration. During a two-year preliminary survey, over 300 biomonitoring actions ('moss bag' transplantation and recovery) were successfully carried out at 25 stations: 190 of them occurred under acceptable conditions and provided results suitable for comparisons. Five environmental priorities were assessed and characterized in space and time. For these situations local authorities drafted a protocol for data management, to plan official controls and dissuasive actions. The 'moss bag' technique allows a flexible approach for both surveillance monitoring (trend assessment) and investigations (point source detection) in compliance with the Water Framework Directive 2000/60/EC as suggested by the recent Guidance Document on chemical monitoring of sediment and biota. PMID:23182520

  14. Co3V2O8 Sponge Network Morphology Derived from Metal-Organic Framework as an Excellent Lithium Storage Anode Material.

    PubMed

    Soundharrajan, Vaiyapuri; Sambandam, Balaji; Song, Jinju; Kim, Sungjin; Jo, Jeonggeun; Kim, Seokhun; Lee, Seulgi; Mathew, Vinod; Kim, Jaekook

    2016-04-01

    Metal-organic framework (MOF)-based synthesis of battery electrodes has presntly become a topic of significant research interest. Considering the complications to prepare Co3V2O8 due to the criticality of its stoichiometric composition, we report on a simple MOF-based solvothermal synthesis of Co3V2O8 for use as potential anodes for lithium battery applications. Characterizations by X-ray diffraction, X-ray photoelectron spectroscopy, high resolution electron microscopy, and porous studies revealed that the phase pure Co3V2O8 nanoparticles are interconnected to form a sponge-like morphology with porous properties. Electrochemical measurements exposed the excellent lithium storage (∼1000 mAh g(-1) at 200 mA g(-1)) and retention properties (501 mAh g(-1) at 1000 mA g(-1) after 700 cycles) of the prepared Co3V2O8 electrode. A notable rate performance of 430 mAh g(-1) at 3200 mA g(-1) was also observed, and ex situ investigations confirmed the morphological and structural stability of this material. These results validate that the unique nanostructured morphology arising from the use of the ordered array of MOF networks is favorable for improving the cyclability and rate capability in battery electrodes. The synthetic strategy presented herein may provide solutions to develop phase pure mixed metal oxides for high-performance electrodes for useful energy storage applications. PMID:26983348

  15. Co-Creation of Value in Higher Education: Using Social Network Marketing in the Recruitment of Students

    ERIC Educational Resources Information Center

    Fagerstrom, Asle; Ghinea, Gheorghita

    2013-01-01

    A social network recruitment campaign was prepared where applicants for information technology bachelor studies at a Norwegian university college were invited to join a Facebook group related to the subject of interest. Each Facebook group was assigned a contact person who received training to facilitate activities and in answering questions from…

  16. State Action Plan for Iowa. "Marketing" Marketing Education.

    ERIC Educational Resources Information Center

    Omega Group, Inc., Haverford, PA.

    An Iowa project identified curriculum, program standards, and a framework for promoting marketing education programs. The mission for the state action plan for marketing education is to develop a strategy to revitalize Iowa's marketing education for the 21st century. Three goals support this mission: (1) create a community-wide awareness of the…

  17. The Online Social Networking of Cyberspace: A Study on the Development of an Online Social Network Project and the Sport Industry's Perception of Its Relative Advantage

    ERIC Educational Resources Information Center

    Liptrap, Timothy John

    2011-01-01

    This exploratory case study examined online social networking (OSN), and the perceptions of Sport Marketing students and sport industry professional as to the relative advantage of the OSN tools in the marketplace. The conceptual framework for this study was based on Boyer's (1990) concepts of Scholarship of Teaching and Learning (SoTL), and the…

  18. The National Network forTechnology Entrepreneurship and Commercialization (N2TEC): Bringing New Technologies to Market

    NASA Astrophysics Data System (ADS)

    Allen, Kathleen

    2003-03-01

    N2TEC, the National Network for Technology Entrepreneurship and Commercialization, is a National Science Foundation "Partnerships for Innovation" initiative designed to raise the level of innovation and technology commercialization in colleges, universities, and communities across the nation. N2TEC is creating a network of people and institutions, and a set of technology tools that will facilitate the pooling of resources and knowledge and enable faculty and students to share those resources and collaborate without regard to geographic boundaries. N2TEC will become the backbone by which educational institutions across the nation can move their technologies into new venture startups. The ultimate goal is to create new wealth and strengthen local, regional and national economies.

  19. Evaluating the ISDN Market.

    ERIC Educational Resources Information Center

    Liss, Alan

    1996-01-01

    Discusses bandwidth on demand technologies, including frame relay and ISDNs (integrated services digital networks). Topics include tariff policies; lack of standards; market conditions; growth in the Internet market and the World Wide Web; and the growing need for remote access. (LRW)

  20. Generation capacity expansion planning in deregulated electricity markets

    NASA Astrophysics Data System (ADS)

    Sharma, Deepak

    With increasing demand of electric power in the context of deregulated electricity markets, a good strategic planning for the growth of the power system is critical for our tomorrow. There is a need to build new resources in the form of generation plants and transmission lines while considering the effects of these new resources on power system operations, market economics and the long-term dynamics of the economy. In deregulation, the exercise of generation planning has undergone a paradigm shift. The first stage of generation planning is now undertaken by the individual investors. These investors see investments in generation capacity as an increasing business opportunity because of the increasing market prices. Therefore, the main objective of such a planning exercise, carried out by individual investors, is typically that of long-term profit maximization. This thesis presents some modeling frameworks for generation capacity expansion planning applicable to independent investor firms in the context of power industry deregulation. These modeling frameworks include various technical and financing issues within the process of power system planning. The proposed modeling frameworks consider the long-term decision making process of investor firms, the discrete nature of generation capacity addition and incorporates transmission network modeling. Studies have been carried out to examine the impact of the optimal investment plans on transmission network loadings in the long-run by integrating the generation capacity expansion planning framework within a modified IEEE 30-bus transmission system network. The work assesses the importance of arriving at an optimal IRR at which the firm's profit maximization objective attains an extremum value. The mathematical model is further improved to incorporate binary variables while considering discrete unit sizes, and subsequently to include the detailed transmission network representation. The proposed models are novel in the

  1. Cap-and-Trade Modeling and Analysis: Congested Electricity Market Equilibrium

    NASA Astrophysics Data System (ADS)

    Limpaitoon, Tanachai

    This dissertation presents an equilibrium framework for analyzing the impact of cap-and-trade regulation on transmission-constrained electricity market. The cap-and-trade regulation of greenhouse gas emissions has gained momentum in the past decade. The impact of the regulation and its efficacy in the electric power industry depend on interactions of demand elasticity, transmission network, market structure, and strategic behavior of firms. I develop an equilibrium model of an oligopoly electricity market in conjunction with a market for tradable emissions permits to study the implications of such interactions. My goal is to identify inefficiencies that may arise from policy design elements and to avoid any unintended adverse consequences on the electric power sector. I demonstrate this modeling framework with three case studies examining the impact of carbon cap-and-trade regulation. In the first case study, I study equilibrium results under various scenarios of resource ownership and emission targets using a 24-bus IEEE electric transmission system. The second and third case studies apply the equilibrium model to a realistic electricity market, Western Electricity Coordinating Council (WECC) 225-bus system with a detailed representation of the California market. In the first and second case studies, I examine oligopoly in electricity with perfect competition in the permit market. I find that under a stringent emission cap and a high degree of concentration of non-polluting firms, the electricity market is subject to potential abuses of market power. Also, market power can occur in the procurement of non-polluting energy through the permit market when non-polluting resources are geographically concentrated in a transmission-constrained market. In the third case study, I relax the competitive market structure assumption of the permit market by allowing oligopolistic competition in the market through a conjectural variation approach. A short-term equilibrium

  2. Mississippi Curriculum Framework for Computer Information Systems Technology. Computer Information Systems Technology (Program CIP: 52.1201--Management Information Systems & Business Data). Computer Programming (Program CIP: 52.1201). Network Support (Program CIP: 52.1290--Computer Network Support Technology). Postsecondary Programs.

    ERIC Educational Resources Information Center

    Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

    This document, which is intended for use by community and junior colleges throughout Mississippi, contains curriculum frameworks for two programs in the state's postsecondary-level computer information systems technology cluster: computer programming and network support. Presented in the introduction are program descriptions and suggested course…

  3. The Market for Vocational Education and Training.

    ERIC Educational Resources Information Center

    Robinson, Chris, Ed.; Kenyon, Richard, Ed.

    These 43 conference papers on vocational education and training (VET) markets are grouped under three broad themes describing them. Sixteen papers deal with the VET product and providers: "The VET Market" (Kemp); "Market Frameworks in VET" (FitzGerald); "The New Zealand Market Approach" (Barker); "An Economic Primer to Government's Role in VET"…

  4. Establishing a National Research Agenda for Marketing Education.

    ERIC Educational Resources Information Center

    Smith, Clifton L.

    1992-01-01

    A review of marketing education research 1936-91 illuminated areas of need for a research agenda in marketing education. A framework and proposal for future marketing education research were formulated. (JOW)

  5. Active safety monitoring of newly marketed medications in a distributed data network: application of a semi-automated monitoring system.

    PubMed

    Gagne, J J; Glynn, R J; Rassen, J A; Walker, A M; Daniel, G W; Sridhar, G; Schneeweiss, S

    2012-07-01

    We developed a semi-automated active monitoring system that uses sequential matched-cohort analyses to assess drug safety across a distributed network of longitudinal electronic health-care data. In a retrospective analysis, we show that the system would have identified cerivastatin-induced rhabdomyolysis. In this study, we evaluated whether the system would generate alerts for three drug-outcome pairs: rosuvastatin and rhabdomyolysis (known null association), rosuvastatin and diabetes mellitus, and telithromycin and hepatotoxicity (two examples for which alerting would be questionable). Over >5 years of monitoring, rate differences (RDs) in comparisons of rosuvastatin with atorvastatin were -0.1 cases of rhabdomyolysis per 1,000 person-years (95% confidence interval (CI): -0.4, 0.1) and -2.2 diabetes cases per 1,000 person-years (95% CI: -6.0, 1.6). The RD for hepatotoxicity comparing telithromycin with azithromycin was 0.3 cases per 1,000 person-years (95% CI: -0.5, 1.0). In a setting in which false positivity is a major concern, the system did not generate alerts for the three drug-outcome pairs. PMID:22588606

  6. Nurse education in competitive markets: the case for relationship marketing.

    PubMed

    Roberts, P M

    1998-10-01

    Since the National Health Service reforms of the late 1980s, nurse education has been increasingly subject to market forces. This new competitive environment presents not only threat, but also challenge and opportunity. Providers of nurse education who recognize the need for market orientation and develop responsive marketing strategies will maximize their potential for market retention and growth. Traditional marketing strategies have considerable limitations for public sector services. The new and growing field of relationship marketing offers nurse education an opportunity to retain and develop profitable relationships with both internal and external markets. This paper reviews the marketing arena in nurse education and proposes context-based qualitative research to ascertain definitive constructs of service quality. Such constructs might then be rooted in a theoretical framework of service quality measurement, and be measured within the disconfirmation paradigm of relationship marketing. PMID:9887753

  7. To Market, to Market

    ERIC Educational Resources Information Center

    Barden, Dennis M.

    2006-01-01

    The institution is part of a national market and its presidential options are dictated by that market, the reputation, the challenges of the position, and the relative compensation for the opportunity to lead the organization. Many in academe are uncomfortable with the idea that hiring in higher education should be governed by the laws of supply…

  8. Knowledge, Skills, and Dispositions: The Innovation Lab Network State Framework for College, Career, and Citizenship Readiness, and Implications for State Policy

    ERIC Educational Resources Information Center

    Council of Chief State School Officers, 2013

    2013-01-01

    In 2011, member states of the Innovation Lab Network (ILN or Network), facilitated by the Council of Chief State School Officers (CCSSO), agreed to work together under the shared belief that their states face a great opportunity to transform their education systems to new designs that prepare all students for postsecondary learning, work, and…

  9. Livestock Marketing.

    ERIC Educational Resources Information Center

    Futrell, Gene; And Others

    This marketing unit focuses on the seasonal and cyclical patterns of livestock markets. Cash marketing, forward contracting, hedging in the futures markets, and the options markets are examined. Examples illustrate how each marketing tool may be useful in gaining a profit on livestock and cutting risk exposure. The unit is organized in the…

  10. Beryllosilicate frameworks and zeolites.

    PubMed

    Armstrong, Jennifer A; Weller, Mark T

    2010-11-10

    Using inspiration derived from studying naturally occurring minerals, a series of framework beryllosilicates have been synthesized under hydrothermal conditions. These include two new zeolite topologies, a unique layered beryllosilicate, and beryllosilicate analogues of numerous aluminosilicate zeolites. Materials with the structure of the rare zeolite mineral nabesite have been synthesized for the first time, including both sodium and potassium derivatives. The structural chemistry of these beryllosilicates frameworks is discussed with reference to the networks of linked tetrahedra, which include the first instance of pentagonal, two-dimensional Cairo-tiling of silicate tetrahedra in one of the new zeolite topologies, their porosity, and their thermal stability. PMID:20949941

  11. Demonstrating marketing accountability.

    PubMed

    Gombeski, William R; Britt, Jason; Taylor, Jan; Riggs, Karen; Wray, Tanya; Adkins, Wanda; Springate, Suzanne

    2008-01-01

    Pressure on health care marketers to demonstrate effectiveness of their strategies and show their contribution to organizational goals is growing. A seven-tiered model based on the concepts of structure (having the right people, systems), process (doing the right things in the right way), and outcomes (results) is discussed. Examples of measures for each tier are provided and the benefits of using the model as a tool for measuring, organizing, tracking, and communicating appropriate information are provided. The model also provides a framework for helping management understand marketing's value and can serve as a vehicle for demonstrating marketing accountability. PMID:19064476

  12. Marketing Education Students' Perceptions toward Marketing Education Courses.

    ERIC Educational Resources Information Center

    Adams, Elaine; Womble, Myra N.; Jones, Karen H.

    2000-01-01

    Using National Board for Professional Teaching Standards propositions as a framework, attitudes of 354 secondary marketing students were examined. Their perception of marketing courses was based on personal relevance, educational value, and life skills. They felt teachers had sufficient knowledge and commitment and the course prepared them for…

  13. Innovation Networks

    NASA Astrophysics Data System (ADS)

    Pyka, Andreas; Scharnhorst, Andrea

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

  14. The 30/20 GHZ net market assessment

    NASA Technical Reports Server (NTRS)

    Rogers, J. C.; Reiner, P.

    1980-01-01

    By creating a number of market scenarios variations dealing with network types, network sizes, and service price levels were analyzed for their impact on market demand. Each market scenario represents a market demand forecast with results for voice, data, and video service traffic expressed in peak load megabits per second.

  15. Communication impacting financial markets

    NASA Astrophysics Data System (ADS)

    Vitting Andersen, Jørgen; Vrontos, Ioannis; Dellaportas, Petros; Galam, Serge

    2014-10-01

    Since the attribution of the Nobel prize in 2002 to Kahneman for prospect theory, behavioral finance has become an increasingly important subfield of finance. However the main parts of behavioral finance, prospect theory included, understand financial markets through individual investment behavior. Behavioral finance thereby ignores any interaction between participants. We introduce a socio-financial model (Vitting Andersen J. and Nowak A., An Introduction to Socio-Finance (Springer, Berlin) 2013) that studies the impact of communication on the pricing in financial markets. Considering the simplest possible case where each market participant has either a positive (bullish) or negative (bearish) sentiment with respect to the market, we model the evolution of the sentiment in the population due to communication in subgroups of different sizes. Nonlinear feedback effects between the market performance and changes in sentiments are taken into account by assuming that the market performance is dependent on changes in sentiments (e.g., a large sudden positive change in bullishness would lead to more buying). The market performance in turn has an impact on the sentiment through the transition probabilities to change an opinion in a group of a given size. The idea is that if for example the market has observed a recent downturn, it will be easier for even a bearish minority to convince a bullish majority to change opinion compared to the case where the meeting takes place in a bullish upturn of the market. Within the framework of our proposed model, financial markets stylized facts such as volatility clustering and extreme events may be perceived as arising due to abrupt sentiment changes via ongoing communication of the market participants. The model introduces a new volatility measure which is apt of capturing volatility clustering and from maximum-likelihood analysis we are able to apply the model to real data and give additional long term insight into where a market is

  16. Spatial coupled disease-behavior framework as a dynamic and adaptive system. Reply to comments on "Coupled disease-behavior dynamics on complex networks: A review"

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.

    2015-12-01

    We would like to begin this response by recognizing all the insightful and thought-provoking comments to our review "Coupled disease-behavior dynamics on complex networks" [1]. We find that, with their diverse expertise, all the commentators enrich the discussion on this topic, and also identify important, interesting questions [2-13], indicating how much space there still is for the development of the field. To give the readers a systematic understanding, these opinions and suggestions are roughly divided into two classes: (i) whether the coupled models could be closer to realistic observations, yet simpler [2-5,7-10,13]; and (ii) whether the hypothesis of network models could mimic the empirical networks more accurately [5-8,10-13].

  17. Value Co-creation and Co-innovation: Linking Networked Organisations and Customer Communities

    NASA Astrophysics Data System (ADS)

    Romero, David; Molina, Arturo

    Strategic networks such as Collaborative Networked Organisations (CNOs) and Virtual Customer Communities (VCCs) show a high potential as drivers of value co-creation and collaborative innovation in today’s Networking Era. Both look at the network structures as a source of jointly value creation and open innovation through access to new skills, knowledge, markets and technologies by sharing risk and integrating complementary competencies. This collaborative endeavour has proven to be able to enhance the adaptability and flexibility of CNOs and VCCs value creating systems in order to react in response to external drivers such as collaborative (business) opportunities. This paper presents a reference framework for creating interface networks, also known as ‘experience-centric networks’, as enablers for linking networked organisations and customer communities in order to support the establishment of user-driven and collaborative innovation networks.

  18. Network Controllability Is Determined by the Density of Low In-Degree and Out-Degree Nodes

    NASA Astrophysics Data System (ADS)

    Menichetti, Giulia; Dall'Asta, Luca; Bianconi, Ginestra

    2014-08-01

    The problem of controllability of the dynamical state of a network is central in network theory and has wide applications ranging from network medicine to financial markets. The driver nodes of the network are the nodes that can bring the network to the desired dynamical state if an external signal is applied to them. Using the framework of structural controllability, here, we show that the density of nodes with in degree and out degree equal to one and two determines the number of driver nodes in the network. Moreover, we show that random networks with minimum in degree and out degree greater than two, are always fully controllable by an infinitesimal fraction of driver nodes, regardless of the other properties of the degree distribution. Finally, based on these results, we propose an algorithm to improve the controllability of networks.

  19. An anionic zeolite-like metal-organic framework (AZMOF) with a Moravia network for organic dye absorption through cation-exchange.

    PubMed

    Shen, Yu; Fan, Cong-Cong; Wei, Yu-Zhen; Du, Jie; Zhu, Hai-Bin; Zhao, Yue

    2016-07-01

    An anionic zeolite-like metal-organic framework (AZMOF) with a twisted partially augmented the net, known as the "Moravia" net, [(CH3)2NH2]6[Sr13(O)3()8(OH)2(H2O)16]·xS (, where S represents non-coordinated solvent molecules, and is the abbreviation of benzo-(1,2;3,4;5,6)-tris-(thiophene-2'-carboxylic acid)), has been solvothermally synthesized and characterized, which possesses an anionic framework and nano-sized sodalite cage. Through cation-exchange, is capable of uptaking large organic cationic dyes including Rhodamine B (RB), Basic Red 2 (BR2), Crystal Violet (CV) and Methylene Blue (MB), amongst which the adsorption capability for RB (up to 545 mg g(-1)), and BR2 (up to 675 mg g(-1)) is the highest for reported absorbants to date. PMID:27301344

  20. Energy efficiency, market failures, and government policy

    SciTech Connect

    Levine, M.D.; Koomey, J.G.; McMahon, J.E.; Sanstad, A.H.; Hirst, E.

    1994-03-01

    This paper presents a framework for evaluating engineering-economic evidence on the diffusion of energy efficiency improvements. Four examples are evaluated within this framework. The analysis provides evidence of market failures related to energy efficiency. Specific market failures that may impede the adoption of cost-effective energy efficiency are discussed. Two programs that have had a major impact in overcoming these market failures, utility DSM programs and appliance standards, are described.

  1. MVC Framework

    SciTech Connect

    Benz, Zachary; McClain, Jonathan; Bauer, Travis; Titus, Brian

    2008-06-03

    Provides a reusable model-view-controller application programming interface (API) for use in the rapid development of graphical user interface applications in the .NET 2.0 framework. This includes a mechanism for adding new data stores, data sources, data analyses, and visualizations in the form of plugins.] The MVC Framework is implemented in C# as a .NET 2.0 framework that can then be built against when developing applications. The infrasturcture allows for presenting application specific views (visualizations) to the user to interact with. Based on the interactions the suer makes with a view, requests are generated which in turn are handled by the central controller facility. The controller handles the request in an application specific manner by routing the request to appropriate data stores, data accessors or data analyzers. Retrieved or processed data is published to subscribed components for further processing or for presentation to the user.

  2. MVC Framework

    Energy Science and Technology Software Center (ESTSC)

    2008-06-03

    Provides a reusable model-view-controller application programming interface (API) for use in the rapid development of graphical user interface applications in the .NET 2.0 framework. This includes a mechanism for adding new data stores, data sources, data analyses, and visualizations in the form of plugins.] The MVC Framework is implemented in C# as a .NET 2.0 framework that can then be built against when developing applications. The infrasturcture allows for presenting application specific views (visualizations) tomore » the user to interact with. Based on the interactions the suer makes with a view, requests are generated which in turn are handled by the central controller facility. The controller handles the request in an application specific manner by routing the request to appropriate data stores, data accessors or data analyzers. Retrieved or processed data is published to subscribed components for further processing or for presentation to the user.« less

  3. E-Commerce Marketing State Competency Profile.

    ERIC Educational Resources Information Center

    Ohio State Univ., Columbus. Tech Prep Curriculum Services.

    This profile provides the curricular framework for Ohio Tech Prep programs in e-commerce marketing beginning in high school and continuing through the end of the associate degree. It includes a comprehensive set of e-commerce marketing competencies that reflect job opportunities and skills required for e-commerce marketing professionals today and…

  4. Marketing Library Services: Strategy for Survival.

    ERIC Educational Resources Information Center

    Edinger, Joyce A.

    1980-01-01

    Discusses the conditions necessary for the success of marketing programs within libraries and methods of implementing a formal marketing program. The four factors of the marketing mix (product, place, price, promotion) are considered and administrative decisions are explored within the framework of these four factors. (Author)

  5. Market-Based Reforms in Urban Education.

    ERIC Educational Resources Information Center

    Ladd, Helen F.

    This paper is for policymakers, advocates, and analysts who understand that the issues surrounding the introduction of more market-based mechanisms into education are complex and who accept the view that evidence is useful in sorting out the issues. It uses the market framework of demand, supply, and market pricing to organize the extensive but…

  6. CRM Systems with Social Networking Capabilities: The Value of Incorporating a CRM 2.0 System in Sales/Marketing Education

    ERIC Educational Resources Information Center

    Wang, Xin; Dugan, Riley; Sojka, Jane

    2013-01-01

    Implementation of a customer relationship management (CRM) 2.0 system can provide both a valuable pedagogical tool and a needed skill set in a marketing and sales curriculum. A CRM 2.0 system incorporated in the sales and marketing curriculum can help manage relationships between students, practitioners, and faculty while teaching students a…

  7. Momentum: "Developing Masterful Marketing Plans."

    ERIC Educational Resources Information Center

    Meservey, Lynne D.

    1988-01-01

    Describes how directors can plan and develop a written marketing plan which can increase enrollment at child care centers. Components of successful marketing plans include parent retention; program merchandising; staff and director training; sales promotions; networking; and enrichment programs/fundraising. (NH)

  8. Language as a whole - A new framework for linguistic knowledge integration. Comment on "Approaching human language with complex networks" by Cong and Liu

    NASA Astrophysics Data System (ADS)

    Chen, Xinying

    2014-12-01

    Researchers have been talking about the language system theoretically for many years [1]. A well accepted assumption is that language is a complex adaptive system [2] which is hierarchical [3] and contains multiple levels along the meaning-form dimension [4]. Over the last decade or so, driven by the availability of digital language data and the popularity of statistical approach, many researchers interested in theoretical questions have started to try to quantitatively describe microscopic linguistic features in a certain level of a language system by using authentic language data. Despite the fruitful findings, one question remains unclear. That is, how does a whole language system look like? For answering this question, network approach, an analysis method emphasizes the macro features of structures, has been introduced into linguistic studies [5]. By analyzing the static and dynamic linguistics networks constructed from authentic language data, many macro and micro linguistic features, such as lexical, syntactic or semantic features have been discovered and successfully applied in linguistic typographical studies so that the huge potential of linguistic networks research has revealed [6].

  9. The SGML Standardization Framework and the Introduction of XML

    PubMed Central

    Grütter, Rolf

    2000-01-01

    Extensible Markup Language (XML) is on its way to becoming a global standard for the representation, exchange, and presentation of information on the World Wide Web (WWW). More than that, XML is creating a standardization framework, in terms of an open network of meta-standards and mediators that allows for the definition of further conventions and agreements in specific business domains. Such an approach is particularly needed in the healthcare domain; XML promises to especially suit the particularities of patient records and their lifelong storage, retrieval, and exchange. At a time when change rather than steadiness is becoming the faithful feature of our society, standardization frameworks which support a diversified growth of specifications that are appropriate to the actual needs of the users are becoming more and more important; and efforts should be made to encourage this new attempt at standardization to grow in a fruitful direction. Thus, the introduction of XML reflects a standardization process which is neither exclusively based on an acknowledged standardization authority, nor a pure market standard. Instead, a consortium of companies, academic institutions, and public bodies has agreed on a common recommendation based on an existing standardization framework. The consortium's process of agreeing to a standardization framework will doubtlessly be successful in the case of XML, and it is suggested that it should be considered as a generic model for standardization processes in the future. PMID:11720931

  10. The SGML standardization framework and the introduction of XML.

    PubMed

    Fierz, W; Grütter, R

    2000-01-01

    Extensible Markup Language (XML) is on its way to becoming a global standard for the representation, exchange, and presentation of information on the World Wide Web (WWW). More than that, XML is creating a standardization framework, in terms of an open network of meta-standards and mediators that allows for the definition of further conventions and agreements in specific business domains. Such an approach is particularly needed in the healthcare domain; XML promises to especially suit the particularities of patient records and their lifelong storage, retrieval, and exchange. At a time when change rather than steadiness is becoming the faithful feature of our society, standardization frameworks which support a diversified growth of specifications that are appropriate to the actual needs of the users are becoming more and more important; and efforts should be made to encourage this new attempt at standardization to grow in a fruitful direction. Thus, the introduction of XML reflects a standardization process which is neither exclusively based on an acknowledged standardization authority, nor a pure market standard. Instead, a consortium of companies, academic institutions, and public bodies has agreed on a common recommendation based on an existing standardization framework. The consortium's process of agreeing to a standardization framework will doubtlessly be successful in the case of XML, and it is suggested that it should be considered as a generic model for standardization processes in the future. PMID:11720931

  11. Micro-economic analysis of the physical constrained markets: game theory application to competitive electricity markets

    NASA Astrophysics Data System (ADS)

    Bompard, E.; Ma, Y. C.; Ragazzi, E.

    2006-03-01

    Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower price, leading to higher market efficiency. Electricity markets are pretty different from other commodities mainly due to the physical constraints related to the network structure that may impact the market performance. The network structure of the system on which the economic transactions need to be undertaken poses strict physical and operational constraints. Strategic interactions among producers that game the market with the objective of maximizing their producer surplus must be taken into account when modeling competitive electricity markets. The physical constraints, specific of the electricity markets, provide additional opportunity of gaming to the market players. Game theory provides a tool to model such a context. This paper discussed the application of game theory to physical constrained electricity markets with the goal of providing tools for assessing the market performance and pinpointing the critical network constraints that may impact the market efficiency. The basic models of game theory specifically designed to represent the electricity markets will be presented. IEEE30 bus test system of the constrained electricity market will be discussed to show the network impacts on the market performances in presence of strategic bidding behavior of the producers.

  12. Learning in innovation networks: Some simulation experiments

    NASA Astrophysics Data System (ADS)

    Gilbert, Nigel; Ahrweiler, Petra; Pyka, Andreas

    2007-05-01

    According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning.

  13. Models for electricity market efficiency and bidding strategy analysis

    NASA Astrophysics Data System (ADS)

    Niu, Hui

    This dissertation studies models for the analysis of market efficiency and bidding behaviors of market participants in electricity markets. Simulation models are developed to estimate how transmission and operational constraints affect the competitive benchmark and market prices based on submitted bids. This research contributes to the literature in three aspects. First, transmission and operational constraints, which have been neglected in most empirical literature, are considered in the competitive benchmark estimation model. Second, the effects of operational and transmission constraints on market prices are estimated through two models based on the submitted bids of market participants. Third, these models are applied to analyze the efficiency of the Electric Reliability Council Of Texas (ERCOT) real-time energy market by simulating its operations for the time period from January 2002 to April 2003. The characteristics and available information for the ERCOT market are considered. In electricity markets, electric firms compete through both spot market bidding and bilateral contract trading. A linear asymmetric supply function equilibrium (SFE) model with transmission constraints is proposed in this dissertation to analyze the bidding strategies with forward contracts. The research contributes to the literature in several aspects. First, we combine forward contracts, transmission constraints, and multi-period strategy (an obligation for firms to bid consistently over an extended time horizon such as a day or an hour) into the linear asymmetric supply function equilibrium framework. As an ex-ante model, it can provide qualitative insights into firms' behaviors. Second, the bidding strategies related to Transmission Congestion Rights (TCRs) are discussed by interpreting TCRs as linear combination of forwards. Third, the model is a general one in the sense that there is no limitation on the number of firms and scale of the transmission network, which can have

  14. Temperature dependent structural variation from 2D supramolecular network to 3D interpenetrated metal–organic framework: In situ cleavage of S–S and C–S bonds

    SciTech Connect

    Ugale, Bharat; Singh, Divyendu; Nagaraja, C.M.

    2015-03-15

    Two new Zn(II)–organic compounds, [Zn(muco)(dbds){sub 2}(H{sub 2}O){sub 2}] (1) and [Zn(muco)(dbs)] (2) (where, muco=trans, trans-muconate dianion, dbds=4,4′-dipyridyldisulfide and dbs=4,4′-dipyridylsulfide) have been synthesized from same precursors but at two different temperatures. Both the compounds have been characterized by single-crystal X-ray diffraction, powder X-ray diffraction, elemental analysis, IR spectroscopy, thermal analysis and photoluminescence studies. Compound 1 prepared at room temperature possesses a molecular structure extended to 2D supramolecular network through (H–O…H) hydrogen-bonding interactions. Compound 2, obtained at high temperature (100 °C) shows a 3-fold interpenetrating 3D framework constituted by an in situ generated dbs linker by the cleavage of S–S and C–S bonds of dbds linker. Thus, the influence of reaction temperature on the formation of two structural phases has been demonstrated. Both 1 and 2 exhibit ligand based luminescence emission owing to n→π⁎ and π→π⁎ transitions and also high thermal stabilities. - Graphical abstract: The influence of temperature on the formation of two structural phases, a 2D supramolecular network and a 3D 3-fold interpenetrating framework has been demonstrated and their luminescence emission is measured. - Highlights: • Two new Zn(II)–organic compounds were synthesized by tuning reaction temperatures. • Temperature induced in situ generation of dbs linker has been observed. • The compounds exhibit high thermal stability and luminescence emission properties. • The effect of temperature on structure, dimension and topology has been presented.

  15. Canadian drug regulatory framework.

    PubMed

    Kelly, L; Lazzaro, M; Petersen, C

    2007-03-01

    The role of regulatory drug submission evaluators in Canada is to critically assess both the data submitted and the sponsor's interpretation of the data in order to reach an evidence-, and context-based recommendation as to the potential benefits and potential harms (i.e., risks) associated with taking the drug under the proposed conditions of use. The purpose of this document is to outline the regulatory framework in which this assessment occurs, including: defining what "authorization to market a drug in Canada" means, in terms of the role of the sponsor, the responsibility of Health Canada in applying the Food and Drugs Act prior to and after marketing authorization, and the distinction between regulatory authorization versus physician authorization; highlighting organizational, process and legal factors within Health Canada related to authorization of clinical trials and authorization to market a drug; considerations during the review process, such as regulatory and scientific issues related to the drug, patient populations and trial designs; application of international guidelines, and decisions from other jurisdictions; regulatory realities regarding drug authorization, including the requirement for wording in the Product Monograph to accurately reflect the information currently available on the safe and effective use of a drug, and that hypothesis-confirming studies are essential to regulatory endorsement; current issues related to the review of therapies for dementia, such as assessing preventative treatments, and therapies that have symptomatic versus disease-modifying effects, statistical issues regarding missing data, and trial design issues. PMID:17469674

  16. Transportation and dynamic networks: Models, theory, and applications to supply chains, electric power, and financial networks

    NASA Astrophysics Data System (ADS)

    Liu, Zugang

    Network systems, including transportation and logistic systems, electric power generation and distribution networks as well as financial networks, provide the critical infrastructure for the functioning of our societies and economies. The understanding of the dynamic behavior of such systems is also crucial to national security and prosperity. The identification of new connections between distinct network systems is the inspiration for the research in this dissertation. In particular, I answer two questions raised by Beckmann, McGuire, and Winsten (1956) and Copeland (1952) over half a century ago, which are, respectively, how are electric power flows related to transportation flows and does money flow like water or electricity? In addition, in this dissertation, I achieve the following: (1) I establish the relationships between transportation networks and three other classes of complex network systems: supply chain networks, electric power generation and transmission networks, and financial networks with intermediation. The establishment of such connections provides novel theoretical insights as well as new pricing mechanisms, and efficient computational methods. (2) I develop new modeling frameworks based on evolutionary variational inequality theory that capture the dynamics of such network systems in terms of the time-varying flows and incurred costs, prices, and, where applicable, profits. This dissertation studies the dynamics of such network systems by addressing both internal competition and/or cooperation, and external changes, such as varying costs and demands. (3) I focus, in depth, on electric power supply chains. By exploiting the relationships between transportation networks and electric power supply chains, I develop a large-scale network model that integrates electric power supply chains and fuel supply markets. The model captures both the economic transactions as well as the physical transmission constraints. The model is then applied to the New

  17. Establishing a framework for the Ad/abaxial regulatory network of Arabidopsis: ascertaining targets of class III homeodomain leucine zipper and KANADI regulation.

    PubMed

    Reinhart, Brenda J; Liu, Tie; Newell, Nicole R; Magnani, Enrico; Huang, Tengbo; Kerstetter, Randall; Michaels, Scott; Barton, M Kathryn

    2013-09-01

    The broadly conserved Class III homeodomain leucine zipper (HD-ZIPIII) and KANADI transcription factors have opposing and transformational effects on polarity and growth in all tissues and stages of the plant's life. To obtain a comprehensive understanding of how these factors work, we have identified transcripts that change in response to induced HD-ZIPIII or KANADI function. Additional criteria used to identify high-confidence targets among this set were presence of an adjacent HD-ZIPIII binding site, expression enriched within a subdomain of the shoot apical meristem, mutant phenotype showing defect in polar leaf and/or meristem development, physical interaction between target gene product and HD-ZIPIII protein, opposite regulation by HD-ZIPIII and KANADI, and evolutionary conservation of the regulator-target relationship. We find that HD-ZIPIII and KANADI regulate tissue-specific transcription factors involved in subsidiary developmental decisions, nearly all major hormone pathways, and new actors (such as indeterminate domain4) in the ad/abaxial regulatory network. Multiple feedback loops regulating HD-ZIPIII and KANADI are identified, as are mechanisms through which HD-ZIPIII and KANADI oppose each other. This work lays the foundation needed to understand the components, structure, and workings of the ad/abaxial regulatory network directing basic plant growth and development. PMID:24076978

  18. Establishing a Framework for the Ad/Abaxial Regulatory Network of Arabidopsis: Ascertaining Targets of Class III HOMEODOMAIN LEUCINE ZIPPER and KANADI Regulation[W

    PubMed Central

    Reinhart, Brenda J.; Liu, Tie; Newell, Nicole R.; Magnani, Enrico; Huang, Tengbo; Kerstetter, Randall; Michaels, Scott; Barton, M. Kathryn

    2013-01-01

    The broadly conserved Class III HOMEODOMAIN LEUCINE ZIPPER (HD-ZIPIII) and KANADI transcription factors have opposing and transformational effects on polarity and growth in all tissues and stages of the plant's life. To obtain a comprehensive understanding of how these factors work, we have identified transcripts that change in response to induced HD-ZIPIII or KANADI function. Additional criteria used to identify high-confidence targets among this set were presence of an adjacent HD-ZIPIII binding site, expression enriched within a subdomain of the shoot apical meristem, mutant phenotype showing defect in polar leaf and/or meristem development, physical interaction between target gene product and HD-ZIPIII protein, opposite regulation by HD-ZIPIII and KANADI, and evolutionary conservation of the regulator–target relationship. We find that HD-ZIPIII and KANADI regulate tissue-specific transcription factors involved in subsidiary developmental decisions, nearly all major hormone pathways, and new actors (such as INDETERMINATE DOMAIN4) in the ad/abaxial regulatory network. Multiple feedback loops regulating HD-ZIPIII and KANADI are identified, as are mechanisms through which HD-ZIPIII and KANADI oppose each other. This work lays the foundation needed to understand the components, structure, and workings of the ad/abaxial regulatory network directing basic plant growth and development. PMID:24076978

  19. Transaction-Based Building Controls Framework, Volume 1: Reference Guide

    SciTech Connect

    Somasundaram, Sriram; Pratt, Robert G.; Akyol, Bora A.; Fernandez, Nicholas; Foster, Nikolas AF; Katipamula, Srinivas; Mayhorn, Ebony T.; Somani, Abhishek; Steckley, Andrew C.; Taylor, Zachary T.

    2014-04-28

    This document proposes a framework concept to achieve the objectives of raising buildings’ efficiency and energy savings potential benefitting building owners and operators. We call it a transaction-based framework, wherein mutually-beneficial and cost-effective market-based transactions can be enabled between multiple players across different domains. Transaction-based building controls are one part of the transactional energy framework. While these controls realize benefits by enabling automatic, market-based intra-building efficiency optimizations, the transactional energy framework provides similar benefits using the same market -based structure, yet on a larger scale and beyond just buildings, to the society at large.

  20. Marketing fundamentals.

    PubMed

    Redmond, W H

    2001-01-01

    This chapter outlines current marketing practice from a managerial perspective. The role of marketing within an organization is discussed in relation to efficiency and adaptation to changing environments. Fundamental terms and concepts are presented in an applied context. The implementation of marketing plans is organized around the four P's of marketing: product (or service), promotion (including advertising), place of delivery, and pricing. These are the tools with which marketers seek to better serve their clients and form the basis for competing with other organizations. Basic concepts of strategic relationship management are outlined. Lastly, alternate viewpoints on the role of advertising in healthcare markets are examined. PMID:11401791

  1. Multivariate Spatio-Temporal Clustering: A Framework for Integrating Disparate Data to Understand Network Representativeness and Scaling Up Sparse Ecosystem Measurements

    NASA Astrophysics Data System (ADS)

    Hoffman, F. M.; Kumar, J.; Maddalena, D. M.; Langford, Z.; Hargrove, W. W.

    2014-12-01

    Disparate in situ and remote sensing time series data are being collected to understand the structure and function of ecosystems and how they may be affected by climate change. However, resource and logistical constraints limit the frequency and extent of observations, particularly in the harsh environments of the arctic and the tropics, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent variability at desired scales. These regions host large areas of potentially vulnerable ecosystems that are poorly represented in Earth system models (ESMs), motivating two new field campaigns, called Next Generation Ecosystem Experiments (NGEE) for the Arctic and Tropics, funded by the U.S. Department of Energy. Multivariate Spatio-Temporal Clustering (MSTC) provides a quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks. We applied MSTC to down-scaled general circulation model results and data for the State of Alaska at a 4 km2 resolution to define maps of ecoregions for the present (2000-2009) and future (2090-2099), showing how combinations of 37 bioclimatic characteristics are distributed and how they may shift in the future. Optimal representative sampling locations were identified on present and future ecoregion maps, and representativeness maps for candidate sampling locations were produced. We also applied MSTC to remotely sensed LiDAR measurements and multi-spectral imagery from the WorldView-2 satellite at a resolution of about 5 m2 within the Barrow Environmental Observatory (BEO) in Alaska. At this resolution, polygonal ground features—such as centers, edges, rims, and troughs—can be distinguished. Using these remote sensing data, we up-scaled vegetation distribution data collected on these polygonal ground features to a large area of the BEO to provide distributions of plant functional types that can

  2. Understanding the China energy market: trends and opportunities 2006

    SciTech Connect

    Barbara Drazga

    2005-05-15

    The report is broken up into 4 Sections: Section I - Overview of China Energy Market (historical background, market value, consumption, production, reserves, export and import, market segmentation, market forecast); Section II - Market Analysis (PEST analysis, Porter's five forces analysis, socio-economic trends, consumption trends); Section III - Market Segments (electricity, oil, natural gas, liquefied natural gas, liquid petroleum gas, nuclear power, coal, renewables, photovoltaics, wind power, hydroelectric power. Each market segment details current and planned projects, and lists participants in that sector); and Section IV - Breaking Into the Market (regulatory framework, methods of market entry, foreign investment, challenges, government agencies).

  3. Effectively executing a comprehensive marketing communication strategy.

    PubMed

    Gombeski, William R; Taylor, Jan; Piccirilli, Ami; Cundiff, Lee; Britt, Jason

    2007-01-01

    Marketers are under increasing scrutiny from their management to demonstrate accountability for the resources they receive. Three models are presented to help marketers execute their customer communication activities more effectively. Benefits of using the "Identification of Strategic Communication Elements," "Business Communication" and "Communications Management Process" models include (1) more effective upfront strategic and tactical planning, (2) ensuring key communication principles are addressed, (3) easier communication program communication, (4) provides a framework for program evaluation and market research and (5) increases the creative thinking marketers need when addressing the major marketing challenges. The ultimate benefit is the greater likelihood of more positive marketing results. PMID:19042530

  4. The topology of the federal funds market

    NASA Astrophysics Data System (ADS)

    Bech, Morten L.; Atalay, Enghin

    2010-11-01

    We explore the network topology of the federal funds market. This market is important for distributing liquidity throughout the financial system and for the implementation of monetary policy. The recent turmoil in global financial markets underscores its importance. We find that the network is sparse, exhibits the small-world phenomenon, and is disassortative. Centrality measures are useful predictors of the interest rate of a loan.

  5. Providing the Framework for Earthquake and Tsunami Early Warning in British Columbia, Canada: WARN, the Web-enabled Awareness Research Network

    NASA Astrophysics Data System (ADS)

    Pirenne, B.; Rosenberger, A.; Crosby, R.; MacArthur, M.; Allen, N.; Bayaki, M.

    2015-12-01

    The main seismic hazard in western Canada is associated with the subduction of the Juan de Fuca plate under the North American continent. It threatens the major population centres of Vancouver and Victoria but also communities along the west coast of Vancouver Island, which face an additional threat from any earthquake-generated tsunami. WARN is a project of Ocean Networks Canada (ONC), a not-for-profit organization that manages several ocean observatories on behalf of the University of Victoria. WARN integrates an array of off-shore and on-shore sensors, both strong motion seismometers and ocean bottom pressure recorders, into a real-time network that is capable of detecting and classifying the early phases of an earthquake rupture as well as waves generated by a local or distant tsunami source. All of WARN's instruments perform complex signal processing tasks on site, on-line and in real time. For earthquakes, WARN's software receives event reports and waveform parameters from off-shore and on-shore strong motion seismometers and associates them with an epicentre and an average magnitude based on their respective empirical relationships. A client application computes the local impact time and expected severity in terms of Modified Mercalli Intensity from its own location in relation the reported epicentre, origin time and magnitude. Event reports from ocean bottom pressure recorders together with earthquake parameters are used to select precomputed scenarios from a tsunami propagation model and to forecast arrival times and inundation at specific points along the West coast of Vancouver Island. WARN's architecture is extremely flexible and can incorporate high rate GNSS based observations.

  6. A Model Philosophy and Curriculum for Postsecondary Marketing Education Programs in Missouri.

    ERIC Educational Resources Information Center

    Smith, Clifton L.

    1992-01-01

    Consensus building with 22 (of 26) postsecondary marketing educators established a core curriculum, mission statement, and articulation framework. Core marketing courses included principles of marketing, sales promotion, salesmanship, and management. (SK)

  7. Barriers to healthcare coordination in market-based and decentralized public health systems: a qualitative study in healthcare networks of Colombia and Brazil

    PubMed Central

    Vargas, Ingrid; Mogollón-Pérez, Amparo Susana; De Paepe, Pierre; Ferreira da Silva, Maria Rejane; Unger, Jean-Pierre; Vázquez, María-Luisa

    2016-01-01

    Although integrated healthcare networks (IHNs) are promoted in Latin America in response to health system fragmentation, few analyses on the coordination of care across levels in these networks have been conducted in the region. The aim is to analyse the existence of healthcare coordination across levels of care and the factors influencing it from the health personnel’ perspective in healthcare networks of two countries with different health systems: Colombia, with a social security system based on managed competition and Brazil, with a decentralized national health system. A qualitative, exploratory and descriptive–interpretative study was conducted, based on a case study of healthcare networks in four municipalities. Individual semi-structured interviews were conducted with a three stage theoretical sample of (a) health (112) and administrative (66) professionals of different care levels, and (b) managers of providers (42) and insurers (14). A thematic content analysis was conducted, segmented by cases, informant groups and themes. The results reveal poor clinical information transfer between healthcare levels in all networks analysed, with added deficiencies in Brazil in the coordination of access and clinical management. The obstacles to care coordination are related to the organization of both the health system and the healthcare networks. In the health system, there is the existence of economic incentives to compete (exacerbated in Brazil by partisan political interests), the fragmentation and instability of networks in Colombia and weak planning and evaluation in Brazil. In the healthcare networks, there are inadequate working conditions (temporary and/or part-time contracts) which hinder the use of coordination mechanisms, and inadequate professional training for implementing a healthcare model in which primary care should act as coordinator in patient care. Reforms are needed in these health systems and networks in order to modify incentives

  8. Barriers to healthcare coordination in market-based and decentralized public health systems: a qualitative study in healthcare networks of Colombia and Brazil.

    PubMed

    Vargas, Ingrid; Mogollón-Pérez, Amparo Susana; De Paepe, Pierre; Ferreira da Silva, Maria Rejane; Unger, Jean-Pierre; Vázquez, María-Luisa

    2016-07-01

    Although integrated healthcare networks (IHNs) are promoted in Latin America in response to health system fragmentation, few analyses on the coordination of care across levels in these networks have been conducted in the region. The aim is to analyse the existence of healthcare coordination across levels of care and the factors influencing it from the health personnel' perspective in healthcare networks of two countries with different health systems: Colombia, with a social security system based on managed competition and Brazil, with a decentralized national health system. A qualitative, exploratory and descriptive-interpretative study was conducted, based on a case study of healthcare networks in four municipalities. Individual semi-structured interviews were conducted with a three stage theoretical sample of (a) health (112) and administrative (66) professionals of different care levels, and (b) managers of providers (42) and insurers (14). A thematic content analysis was conducted, segmented by cases, informant groups and themes. The results reveal poor clinical information transfer between healthcare levels in all networks analysed, with added deficiencies in Brazil in the coordination of access and clinical management. The obstacles to care coordination are related to the organization of both the health system and the healthcare networks. In the health system, there is the existence of economic incentives to compete (exacerbated in Brazil by partisan political interests), the fragmentation and instability of networks in Colombia and weak planning and evaluation in Brazil. In the healthcare networks, there are inadequate working conditions (temporary and/or part-time contracts) which hinder the use of coordination mechanisms, and inadequate professional training for implementing a healthcare model in which primary care should act as coordinator in patient care. Reforms are needed in these health systems and networks in order to modify incentives, strengthen

  9. Marketing 101.

    ERIC Educational Resources Information Center

    Henderson, Karla A.

    1997-01-01

    A marketing model for camps includes a mix of services, presentation, and communication elements that promote the virtues of camp, convince potential campers and their families of the benefits of camp, and successfully distinguish the camp from others. Includes resources related to marketing strategies, theme merchandise, and market trends…

  10. Essays on microgrids, asymmetric pricing and market power in electricity markets

    NASA Astrophysics Data System (ADS)

    Lo Prete, Chiara

    This dissertation presents four studies of the electricity industry. The first and second essays use economic-engineering models to assess different aspects of microgrid penetration in regional electricity markets, while the last two studies contain empirical analyses aimed at evaluating the performance of wholesale electricity markets. Chapter 2 develops a framework to quantify economic, environmental, efficiency and reliability impacts of different power production scenarios in a regional system, focusing on the interaction of microgrids with the existing transmission and distribution grid. The setting is the regional network formed by Belgium, France, Germany and the Netherlands. The study presents simulations of power market outcomes under various policies and levels of microgrid penetration, and evaluates them using a diverse set of metrics. Chapter 3 studies the interaction between a microgrid and a regulated electric utility in a regional electricity market. I consider the interaction among the utility, the microgrid developer and consumers in the framework of cooperative game theory (assuming exchangeable utility), and use regional market models to simulate scenarios in which microgrid introduction may or may not be socially beneficial. Under the assumptions of this chapter, customer participation is essential to the development of socially beneficial microgrids, while the utility has little or no gain from it. Discussed incentives to avoid that utilities block microgrid entry include additional revenue drivers related to microgrid connection, decoupling and performance-based mechanisms targeted at service quality. When prices are below marginal costs of utility provided power, microgrid development may be socially beneficial, but unprofitable for microgrid customers and its developer. By imposing lower charges and higher remuneration for its services, the regulator could ensure that microgrid value is positive, without adversely impacting the utility

  11. Integrated Framework for Assessing Impacts of CO₂ Leakage on Groundwater Quality and Monitoring-Network Efficiency: Case Study at a CO₂ Enhanced Oil Recovery Site.

    PubMed

    Yang, Changbing; Hovorka, Susan D; Treviño, Ramón H; Delgado-Alonso, Jesus

    2015-07-21

    This study presents a combined use of site characterization, laboratory experiments, single-well push-pull tests (PPTs), and reactive transport modeling to assess potential impacts of CO2 leakage on groundwater quality and leakage-detection ability of a groundwater monitoring network (GMN) in a potable aquifer at a CO2 enhanced oil recovery (CO2 EOR) site. Site characterization indicates that failures of plugged and abandoned wells are possible CO2 leakage pathways. Groundwater chemistry in the shallow aquifer is dominated mainly by silicate mineral weathering, and no CO2 leakage signals have been detected in the shallow aquifer. Results of the laboratory experiments and the field test show no obvious damage to groundwater chemistry should CO2 leakage occur and further were confirmed with a regional-scale reactive transport model (RSRTM) that was built upon the batch experiments and validated with the single-well PPT. Results of the RSRTM indicate that dissolved CO2 as an indicator for CO2 leakage detection works better than dissolved inorganic carbon, pH, and alkalinity at the CO2 EOR site. The detection ability of a GMN was assessed with monitoring efficiency, depending on various factors, including the natural hydraulic gradient, the leakage rate, the number of monitoring wells, the aquifer heterogeneity, and the time for a CO2 plume traveling to the monitoring well. PMID:26052928

  12. A new watershed assessment framework for Nova Scotia: A high-level, integrated approach for regions without a dense network of monitoring stations

    NASA Astrophysics Data System (ADS)

    Sterling, Shannon M.; Garroway, Kevin; Guan, Yue; Ambrose, Sarah M.; Horne, Peter; Kennedy, Gavin W.

    2014-11-01

    High-level, integrated watershed assessments are a basic requirement for freshwater planning, as they create regional summaries of multiple environmental stressors for the prioritization of watershed conservation, restoration, monitoring, and mitigation. There is a heightened need for a high-level, integrated watershed assessment in Nova Scotia as it faces pressing watershed issues relating to acidification, soil erosion, acid rock drainage, eutrophication, and water withdrawals related to potential shale gas development. But because of the relative sparseness of the on-the-ground effects-based data, for example on water quality or fish assemblages, previously created approaches for integrated watershed assessment cannot be used. In a government/university collaboration, we developed a new approach that relies solely on easier-to-collect and more available exposure-based variables to perform the first high-level watershed assessment in Nova Scotia. In this assessment, a total of 295 watershed units were studied. We used Geographic Information Systems (GIS) to map and analyze 13 stressor variables that represent risks to aquatic environment (e.g., road/stream crossing density, acid rock drainage risk, surface water withdrawals, human land use, and dam density). We developed a model to link stressors with impacts to aquatic systems to serve as a basis for a watershed threat ranking system. Resource management activities performed by government and other stakeholders were also included in this analysis. Our assessment identifies the most threatened watersheds, enables informed comparisons among watersheds, and indicates where to focus resource management and monitoring efforts. Stakeholder communication tools produced by the NSWAP include a watershed atlas to communicate the assessment results to a broader audience, including policy makers and public stakeholders. This new framework for high-level watershed assessments provides a resource for other regions that also

  13. Channel Networks

    NASA Astrophysics Data System (ADS)

    Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio; Rigon, Riccardo

    This review proceeds from Luna Leopold's and Ronald Shreve's lasting accomplishments dealing with the study of random-walk and topologically random channel networks. According to the random perspective, which has had a profound influence on the interpretation of natural landforms, nature's resiliency in producing recurrent networks and landforms was interpreted to be the consequence of chance. In fact, central to models of topologically random networks is the assumption of equal likelihood of any tree-like configuration. However, a general framework of analysis exists that argues that all possible network configurations draining a fixed area are not necessarily equally likely. Rather, a probability P(s) is assigned to a particular spanning tree configuration, say s, which can be generally assumed to obey a Boltzmann distribution: P(s) % e^-H(s)/T, where T is a parameter and H(s) is a global property of the network configuration s related to energetic characters, i.e. its Hamiltonian. One extreme case is the random topology model where all trees are equally likely, i.e. the limit case for T6 4 . The other extreme case is T 6 0, and this corresponds to network configurations that tend to minimize their total energy dissipation to improve their likelihood. Networks obtained in this manner are termed optimal channel networks (OCNs). Observational evidence suggests that the characters of real river networks are reproduced extremely well by OCNs. Scaling properties of energy and entropy of OCNs suggest that large network development is likely to effectively occur at zero temperature (i.e. minimizing its Hamiltonian). We suggest a corollary of dynamic accessibility of a network configuration and speculate towards a thermodynamics of critical self-organization. We thus conclude that both chance and necessity are equally important ingredients for the dynamic origin of channel networks---and perhaps of the geometry of nature.

  14. Capacity Markets and Market Stability

    SciTech Connect

    Stauffer, Hoff

    2006-04-15

    The good news is that market stability can be achieved through a combination of longer-term contracts, auctions for far enough in the future to permit new entry, a capacity management system, and a demand curve. The bad news is that if and when stable capacity markets are designed, the markets may seem to be relatively close to where we started - with integrated resource planning. Market ideologues will find this anathema. (author)

  15. The scale-free topology of market investments

    NASA Astrophysics Data System (ADS)

    Garlaschelli, Diego; Battiston, Stefano; Castri, Maurizio; Servedio, Vito D. P.; Caldarelli, Guido

    2005-05-01

    We propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings. In this framework, the in-degree ( kin) and the sum of incoming link weights ( v) of an investor correspond to the number of assets held ( portfolio diversification) and to the invested wealth ( portfolio volume), respectively. An empirical analysis of three different real markets reveals that the distributions of both kin and v display power-law tails with exponents γ and α. Moreover, we find that kin scales as a power-law function of v with an exponent β. Remarkably, despite the values of α, β and γ differ across the three markets, they are always governed by the scaling relation β=(1-α)/(1-γ). We show that these empirical findings can be reproduced by a recent model relating the emergence of scale-free networks to an underlying Paretian distribution of ‘hidden’ vertex properties.

  16. Framework faults

    NASA Astrophysics Data System (ADS)

    Vierkorn-Rudolph, Beatrix

    2009-02-01

    Your news story "Carbon-capture and gamma-ray labs top Euro wish list" (January p6) states that the European Strategy Forum for Research Infrastructures (ESFRI) has a budget of €1.7bn and is "part of the European Union's Seventh Framework Programme (FP7)". Neither of these statements is true. In fact, as vice-chair of the ESFRI, I should point out that it is an independent strategic forum where delegates (nominated and mandated by the research ministers of the member states and associated states of the European Community) jointly reflect on the development of strategic policies for pan-European research infrastructures. As the forum is an informal body, it does not have any funds.

  17. Robustness of a Network of Networks

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

  18. Analysis in correlation for the Korean stock market

    NASA Astrophysics Data System (ADS)

    Jung, Woo-Sung; Chae, Seungbyung; Yang, Jae-Suk; Kwon, Okyu; Moon, Hie-Tae

    2005-05-01

    The correlation between stock price changes is useful information. Through the correlation matrix, we construct a portfolio with its minimum spanning tree. We make the minimum spanning tree of the Korean stock market, a representative emerging market, which is different from that of the mature market. It is due to the emerging market's less abundant liquidity than the mature market. And we find the distribution of the correlation coefficient is different for several periods. As the market is developing, many changes from inside and outside the market occurs, and several parameters of the stock market network are changed. The Korean stock market is under an evolution.

  19. Network planning under uncertainties

    NASA Astrophysics Data System (ADS)

    Ho, Kwok Shing; Cheung, Kwok Wai

    2008-11-01

    One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a

  20. Interdependent networks - Topological percolation research and application in finance

    NASA Astrophysics Data System (ADS)

    Zhou, Di

    This dissertation covers the two major parts of my Ph.D. research: i) developing a theoretical framework of complex networks and applying simulation and numerical methods to study the robustness of the network system, and ii) applying statistical physics concepts and methods to quantitatively analyze complex systems and applying the theoretical framework to study real-world systems. In part I, we focus on developing theories of interdependent networks as well as building computer simulation models, which includes three parts: 1) We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the networks significantly changes the critical density of failures, which can trigger the total disruption of the two-network system. Specifically, we find that the assortativity within a single network decreases the robustness of the entire system. 2) We study the percolation behavior of two interdependent scale-free (SF) networks under random failure of 1-p fraction of nodes. We find that as the coupling strength q between the two networks reduces from 1 (fully coupled) to 0 (no coupling), there exist two critical coupling strengths q1 and q2 , which separate the behaviors of the giant component as a function of p into three different regions, and for q2 < q < q 1 , we observe a hybrid order phase transition phenomenon. 3) We study the robustness of n interdependent networks with partially support-dependent relationship both analytically and numerically. We study a starlike network of n Erdos-Renyi (ER), SF networks and a looplike network of n ER networks, and we find for starlike networks, their phase transition regions change with n, but for looplike networks the phase regions change with average degree k . In part II, we apply concepts and methods developed in statistical physics to study economic systems. We analyze stock market indices and foreign exchange