Science.gov

Sample records for market network framework

  1. 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.

  2. MarketBayes: A distributed, market-based Bayesian network

    SciTech Connect

    Pennock, D.M.

    1996-12-31

    This paper presents initial work on a system called MarketBayes, a computational market economy where distributed agents trade in uncertain propositions. For any Bayesian network, we have defined a corresponding economy of goods, consumers and producers that essentially {open_quotes}computes{close_quotes} the same information. Although our research thus far has only verified the existence of a market structure capable of Bayesian calculations, our hope is that such a system may address a variety of interesting problems of distributed uncertain reasoning. For example, the economic framework should be well suited for belief aggregation, since the bids of numerous agents with varying beliefs, confidence levels and wealth are concisely {open_quotes}summarized{close_quotes} in the going prices of goods.

  3. 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.

  4. Marketing Network Centric Warfare

    DTIC Science & Technology

    2007-11-02

    must transition from a Navy concept to a joint product. NCW advocates can effect this transition by using basic business principles to market NCW...They can tailor a solid mix of product, price, place, and promotion to target and win over operational commanders. This is the first and vital step to successfully introduce NCW as the way of the future.

  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. A dynamic network model for interbank market

    NASA Astrophysics Data System (ADS)

    Xu, Tao; He, Jianmin; Li, Shouwei

    2016-12-01

    In this paper, a dynamic network model based on agent behavior is introduced to explain the formation mechanism of interbank market network. We investigate the impact of credit lending preference on interbank market network topology, the evolution of interbank market network and stability of interbank market. Experimental results demonstrate that interbank market network is a small-world network and cumulative degree follows the power-law distribution. We find that the interbank network structure keeps dynamic stability in the network evolution process. With the increase of bank credit lending preference, network clustering coefficient increases and average shortest path length decreases monotonously, which improves the stability of the network structure. External shocks are main threats for the interbank market and the reduction of bank external investment yield rate and deposits fluctuations contribute to improve the resilience of the banking system.

  7. Developing Functional Networks of Frontier Capital Markets

    DTIC Science & Technology

    2011-10-01

    ABSTRACT Examining the structure , dynamics, and unique characteristics of a capital market network in which it operates is vital to understanding...opportunities. Examining the structure , dynamics, and unique characteristics of the capital market network in which they operate is vital to...behavior and economics. The individual motivations, information availability, transaction systems , and cultural realities in these markets provide a rich

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

    EPA Pesticide Factsheets

    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.

  9. Tactical Network Integration Test Framework

    DTIC Science & Technology

    2011-05-16

    Wood Street, Lexington, MA 02420 Patrick Boehm ( OPNET ), Edward Kuczynski (DAG), John Cain (Akibia) Thomas Mak (PM WIN-T, US Army) Abstract- Mobile...tier" of the network is a Wideband Networking Waveform (WNW) cloud that is represented in an OPNET model. The difference between the three test...with an OPNET model that is representative of a higher tier backbone network. In the high fidelity emulation environment, a smaD number of upper

  10. [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.

  11. 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…

  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. 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.

  14. The stability of financial market networks

    NASA Astrophysics Data System (ADS)

    Yan, Xin-Guo; Xie, Chi; Wang, Gang-Jin

    2014-08-01

    We investigate the stability of a financial market network by measuring its topological robustness, namely the ability of the network to resist structural or topological changes. The closing prices of 710 stocks in the Shanghai Stock Exchange (SSE) from 2005 to 2011 are chosen as the empirical data. We divide the period into three sub-periods: before, during, and after the US sub-prime crisis. By monitoring the size of the clusters which fall apart from the network after removing the nodes (i.e., the listed companies in the SSE), we find that: i) the SSE network is sensitive to the nodes' failure, which implies that the network is unstable. ii) the SSE network before the financial crisis has the strongest robustness against the intentional topological damage; iii) the hubs (i.e., highly connected nodes) connect with each other directly and play a vital important role in maintaining SSE network's stability.

  15. 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.

  16. A network model of the interbank market

    NASA Astrophysics Data System (ADS)

    Li, Shouwei; He, Jianmin; Zhuang, Yaming

    2010-12-01

    This work introduces a network model of an interbank market based on interbank credit lending relationships. It generates some network features identified through empirical analysis. The critical issue to construct an interbank network is to decide the edges among banks, which is realized in this paper based on the interbank’s degree of trust. Through simulation analysis of the interbank network model, some typical structural features are identified in our interbank network, which are also proved to exist in real interbank networks. They are namely, a low clustering coefficient and a relatively short average path length, community structures, and a two-power-law distribution of out-degree and in-degree.

  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. 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.

  19. A General Framework of Human Trust in Networks

    DTIC Science & Technology

    2009-06-01

    information dominance and complete mission objectives. Soldiers must possess a sufficient amount of trust in networks for adequate mission performance. We are investigating human trust in tactical networks by establishing a theoretical framework for analysis and an approach for validation of the framework. We identify reliability and availability as network parameters that define the relationship between quality of service performance and human trust in networks. A general framework is being developed for human trust in networks, which combines singular elements of trust

  20. Contagions across networks: colds and markets

    NASA Astrophysics Data System (ADS)

    Berryman, Matthew J.; Johnson, Neil F.; Abbott, Derek

    2005-12-01

    We explore a variety of network models describing transmission across a network. In particular we focus on transmission across composite networks, or "networks of networks", in which a finite number of networked objects are then themselves connected together into a network. In a disease context we introduce two interrelated viruses to hosts on a network, to model the infection of hosts in a classroom situation, with high rates of infection within a classroom, and lower rates of infection between classrooms. The hosts can be either susceptible to infection, infected, or recovering from each virus. During the infection stage and recovery stage there is some level of cross-immunity to related viruses. We explore the effects of immunizing sections of the community on transmission through social networks. In a stock market context we introduce memes, or virus-like ideas into a virtual agent-based model of a stock exchange. By varying the parameters of the individual traders and the way in which they are connected we are able to show emergent behaviour, including boom and bust cycles.

  1. 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

  2. Network Centric Operations Conceptual Framework Version 1.0

    DTIC Science & Technology

    2003-11-01

    Network Centric Operations Conceptual Framework Version 1.0 Prepared for: John Garstka Office of Force Transformation Prepared by...COVERED 00-11-2003 to 00-11-2003 4. TITLE AND SUBTITLE Network Centric Operations Conceptual Framework Version 1.0 5a. CONTRACT NUMBER 5b. GRANT... Conceptual Framework Version 1.0 Table of Contents 1.0 Introduction and Background

  3. A Framework for State-Level Renewable Energy Market Potential Studies

    EPA Pesticide Factsheets

    This document provides a framework/next steps for state officials who require estimates of renewable energy market potential, shows how to conduct a market potential study, and distinguishes between goal-oriented studies and other types of studies.

  4. 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.

  5. An Evolutionary Optimization Framework for Neural Networks and Neuromorphic Architectures

    SciTech Connect

    Schuman, Catherine D; Plank, James; Disney, Adam; Reynolds, John

    2016-01-01

    As new neural network and neuromorphic architectures are being developed, new training methods that operate within the constraints of the new architectures are required. Evolutionary optimization (EO) is a convenient training method for new architectures. In this work, we review a spiking neural network architecture and a neuromorphic architecture, and we describe an EO training framework for these architectures. We present the results of this training framework on four classification data sets and compare those results to other neural network and neuromorphic implementations. We also discuss how this EO framework may be extended to other architectures.

  6. 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).

  7. Multiple crossbar network: Integrated supercomputing framework

    SciTech Connect

    Hoebelheinrich, R. )

    1989-01-01

    At Los Alamos National Laboratory, site of one of the world's most powerful scientific supercomputing facilities, a prototype network for an environment that links supercomputers and workstations is being developed. Driven by a need to provide graphics data at movie rates across a network from a Cray supercomputer to a Sun scientific workstation, the network is called the Multiple Crossbar Network (MCN). It is intended to be coarsely grained, loosely coupled, general-purpose interconnection network that will vastly increase the speed at which supercomputers communicate with each other in large networks. The components of the network are described, as well as work done in collaboration with vendors who are interested in providing commercial products. 9 refs.

  8. 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

  9. 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.

  10. Design framework for entanglement-distribution switching networks

    NASA Astrophysics Data System (ADS)

    Drost, Robert J.; Brodsky, Michael

    2016-09-01

    The distribution of quantum entanglement appears to be an important component of applications of quantum communications and networks. The ability to centralize the sourcing of entanglement in a quantum network can provide for improved efficiency and enable a variety of network structures. A necessary feature of an entanglement-sourcing network node comprising several sources of entangled photons is the ability to reconfigurably route the generated pairs of photons to network neighbors depending on the desired entanglement sharing of the network users at a given time. One approach to such routing is the use of a photonic switching network. The requirements for an entanglement distribution switching network are less restrictive than for typical conventional applications, leading to design freedom that can be leveraged to optimize additional criteria. In this paper, we present a mathematical framework defining the requirements of an entanglement-distribution switching network. We then consider the design of such a switching network using a number of 2 × 2 crossbar switches, addressing the interconnection of these switches and efficient routing algorithms. In particular, we define a worst-case loss metric and consider 6 × 6, 8 × 8, and 10 × 10 network designs that optimize both this metric and the number of crossbar switches composing the network. We pay particular attention to the 10 × 10 network, detailing novel results proving the optimality of the proposed design. These optimized network designs have great potential for use in practical quantum networks, thus advancing the concept of quantum networks toward reality.

  11. 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…

  12. Agent-Based Framework for Personalized Service Provisioning in Converged IP Networks

    NASA Astrophysics Data System (ADS)

    Podobnik, Vedran; Matijasevic, Maja; Lovrek, Ignac; Skorin-Kapov, Lea; Desic, Sasa

    In a global multi-service and multi-provider market, the Internet Service Providers will increasingly need to differentiate in the service quality they offer and base their operation on new, consumer-centric business models. In this paper, we propose an agent-based framework for the Business-to-Consumer (B2C) electronic market, comprising the Consumer Agents, Broker Agents and Content Agents, which enable Internet consumers to select a content provider in an automated manner. We also discuss how to dynamically allocate network resources to provide end-to-end Quality of Service (QoS) for a given consumer and content provider.

  13. 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.

  14. Establishing a Network Framework for TRADOC Scenarios

    DTIC Science & Technology

    2010-09-30

    Optimized Network Evaluation Tool ( OPNET ), Net Warfare Simulation (NETWARS) and the Joint...Electronic Maintenance Training Department OFF officer OneSAF One Semi Automated Force OPCON operational control OPLAN operational plan OPNET Optimized

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Conceptual Framework for Curriculum Decisions in Education for Marketing and Distribution Careers.

    ERIC Educational Resources Information Center

    Gordon, Alice K.; And Others

    Developed to provide bases for curriculum decisions in education for marketing and distribution careers, the conceptual framework presented here contains the following elements: Identification of social, economic and educational trends which affect employment and education in marketing and distribution; an assessment of current education practice;…

  5. 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.

  6. 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.

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

    PubMed

    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.

  8. 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.

  9. 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.

  10. A Framework for Event Prioritization in Cyber Network Defense

    DTIC Science & Technology

    2014-07-15

    myong H. KAng Jim Z. Luo ALex VeLAZqueZ Center for High Assurance Computer Systems Information Technology Division July 15, 2014 Approved for public...OF ABSTRACT A Framework for Event Prioritization in Cyber Network Defense Anya Kim, Myong H. Kang, Jim Z. Luo, and Alex Velazquez Naval Research

  11. Framework for adaptive content delivery in heterogeneous network environments

    NASA Astrophysics Data System (ADS)

    Ma, Wei-Ying; Bedner, Ilja; Chang, Grace; Kuchinsky, Allan; Zhang, HongJiang

    1999-12-01

    The explosive growth of the Internet has come with increasing diversity and heterogeneity in terms of client device capability, network bandwidth, and user preferences. To date, most Web content has been designed with desktop computers in mind, and often contains rich media such as images, audio, and video. In many cases, this content is not suitable for devices like netTVs, handheld computers, personal digital assistants, and smart phones with relatively limited display capability, storage, processing power, and network access. Thus, Internet access is still constrained on these devices and there is a need to develop alternative approaches for information delivery. In this paper, we propose a framework for adaptive content delivery in heterogeneous environments. The goal is to improve content accessibility and perceived quality of service for information access under changing network and viewer conditions. The framework includes content adaptation algorithms, client capability and network bandwidth discovery methods, and a Decision Engine for determining when and how to adapt content. We describe this framework, initial system implementations based upon this framework, and the issues associated with the deployment of such systems based on different architectures.

  12. SERA Scenarios of Early Market Fuel Cell Electric Vehicle Introductions: Modeling Framework, Regional Markets, and Station Clustering

    SciTech Connect

    Bush, B.; Melaina, M.; Penev, M.; Daniel, W.

    2013-09-01

    This report describes the development and analysis of detailed temporal and spatial scenarios for early market hydrogen fueling infrastructure clustering and fuel cell electric vehicle rollout using the Scenario Evaluation, Regionalization and Analysis (SERA) model. The report provides an overview of the SERA scenario development framework and discusses the approach used to develop the nationwidescenario.

  13. A framework for analyzing contagion in assortative banking networks

    PubMed Central

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

    2017-01-01

    We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk. PMID:28231324

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Pythoscape: a framework for generation of large protein similarity networks.

    PubMed

    Barber, Alan E; Babbitt, Patricia C

    2012-11-01

    Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.

  19. Social Network Analysis in Frontier Capital Markets

    DTIC Science & Technology

    2012-06-01

    generate results efficiently. References [Bor03] Stephen Borgatti . The key player problem. In Dynamic Social Network Modeling and Analysis: workshop...form of the equation for determining the centralization of a network is given by CX = ∑N i=1[CX( p ∗)− CX(pi)] max ∑N i=1[CX( p ∗)− CX(pi)] , (6) the...following equation: CD = ∑N i=1[CD( p ∗)− CD(pi)] (N − 1)(N − 2) . Here the maximum possible sum of differences in the denominator in (6) is given by

  20. 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

  1. Topological isomorphisms of human brain and financial market networks.

    PubMed

    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.

  2. A network analysis of the Chinese stock market

    NASA Astrophysics Data System (ADS)

    Huang, Wei-Qiang; Zhuang, Xin-Tian; Yao, Shuang

    2009-07-01

    In many practical important cases, a massive dataset can be represented as a very large network with certain attributes associated with its vertices and edges. Stock markets generate huge amounts of data, which can be use for constructing the network reflecting the market’s behavior. In this paper, we use a threshold method to construct China’s stock correlation network and then study the network’s structural properties and topological stability. We conduct a statistical analysis of this network and show that it follows a power-law model. We also detect components, cliques and independent sets in this network. These analyses allows one to apply a new data mining technique of classifying financial instruments based on stock price data, which provides a deeper insight into the internal structure of the stock market. Moreover, we test the topological stability of this network and find that it displays a topological robustness against random vertex failures, but it is also fragile to intentional attacks. Such a network stability property would be also useful for portfolio investment and risk management.

  3. 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

  4. Introducing FNCS: Framework for Network Co-Simulation

    ScienceCinema

    None

    2016-07-12

    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.

  5. 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.

  6. 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.

  7. Organizing product innovation: hierarchy, market or triple-helix networks?

    PubMed

    Fitjar, Rune Dahl; Gjelsvik, Martin; Rodríguez-Pose, Andrés

    This paper assesses the extent to which the organization of the innovation effort in firms, as well as the geographical scale at which this effort is pursued, affects the capacity to benefit from product innovations. Three alternative modes of organization are studied: hierarchy, market and triple-helix-type networks. Furthermore, we consider triple-helix networks at three geographical scales: local, national and international. These relationships are tested on a random sample of 763 firms located in five urban regions of Norway which reported having introduced new products or services during the preceding 3 years. The analysis shows that firms exploiting internal hierarchy or triple-helix networks with a wide range of partners managed to derive a significantly higher share of their income from new products, compared to those that mainly relied on outsourcing within the market. In addition, the analysis shows that the geographical scale of cooperation in networks, as well as the type of partner used, matters for the capacity of firms to benefit from product innovation. In particular, firms that collaborate in international triple-helix-type networks involving suppliers, customers and R&D institutions extract a higher share of their income from product innovations, regardless of whether they organize the processes internally or through the network.

  8. A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics

    PubMed Central

    Yuan, Kai; Liu, Jian; Liu, Kaipei; Tan, Tianyuan

    2015-01-01

    Background Evaluations of electric power distribution network risks must address the problems of incomplete information and changing dynamics. A risk evaluation framework should be adaptable to a specific situation and an evolving understanding of risk. Methods This study investigates the use of symbolic dynamics to abstract raw data. After introducing symbolic dynamics operators, Kolmogorov-Sinai entropy and Kullback-Leibler relative entropy are used to quantitatively evaluate relationships between risk sub-factors and main factors. For layered risk indicators, where the factors are categorized into four main factors – device, structure, load and special operation – a merging algorithm using operators to calculate the risk factors is discussed. Finally, an example from the Sanya Power Company is given to demonstrate the feasibility of the proposed method. Conclusion Distribution networks are exposed and can be affected by many things. The topology and the operating mode of a distribution network are dynamic, so the faults and their consequences are probabilistic. PMID:25789859

  9. Developing a marketing function in public healthcare systems: a framework for action.

    PubMed

    Lega, Federico

    2006-10-01

    The scope of this paper is to analyse the contribution that a marketing function can bring to the wide variety of healthcare organizations operating in public health systems (PHSs). While extensive research on marketing applied to healthcare services has been elaborated in competitive and managed care contexts, marketing is a rather new issue in PHSs and little research has been conducted to assess its relevance and benefits in these environments. This study tackles that gap and is based on a review of the current literature in order to provide answers to the following points: - definition of the scopes of marketing and of the elements that affect its incorporation in the healthcare sector; - conceptualization of the possible approaches to marketing by health organizations operating in PHSs; - discussion of the resulting framework for action.

  10. Analytical framework for recurrence network analysis of time series.

    PubMed

    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.

  11. A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

    NASA Astrophysics Data System (ADS)

    Opadiji, Jayeola Femi; Kaihara, Toshiya

    We present a market-based decentralized approach which uses a market-oriented programming algorithm to obtain Pareto-optimal allocation of resources traded among agents which represent enterprise units in a supply network. The proposed method divides the network into a series of Walrsian markets in order to obtain procurement budgets for enterprises in the network. An interaction protocol based on market value propagation is constructed to coordinate the flow of resources across the network layers. The method mitigates the effect of product complementarity in convergent network by allowing for enterprises to hold private valuations of resources in the markets.

  12. 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.

  13. 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.

  14. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection.

    PubMed

    Delaney, Declan T; O'Hare, Gregory M P

    2016-12-01

    No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks.

  15. A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection †

    PubMed Central

    Delaney, Declan T.; O’Hare, Gregory M. P.

    2016-01-01

    No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks. PMID:27916929

  16. 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

  17. Movie Piracy Networks at Alaba International Market, Lagos, Nigeria.

    PubMed

    Tade, Oludayo; Mmahi, Okoro Paul

    2017-02-01

    This study examined the veiled chain of film piracy, a major crime in the Nigeria entertainment industry. Studies on film piracy in Nigeria have focused on its economic implications, both on the copyright owners and on the Nigerian economy. The organization of the activities of the film pirates has, however, been neglected. Narratives were extracted through in-depth interviews with pirates, "marketers," and "producers." Data indicated that pirates were insiders in the film marketing industry and included importers of foreign movies, registered and nonregistered retailers of Nigerian films, as well as marketers appointed by copyright owners to distribute their films. With the connivance of sales girls working with the copyright owners and dubbing companies, original copies of films (white face) are "procured." Pirates distributed pirated copies, also secretly known as "green face," without issuing receipts or putting the logo of the company on it. For security reasons, pirated films are sold only to buyers introduced by a member in the piracy network. Efforts aimed at fighting piracy must take into account this veiled network to effectively combat intellectual theft via aggressive ban on the public sale of such products.

  18. 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…

  19. A rigorous framework for multiscale simulation of stochastic cellular networks

    PubMed Central

    Chevalier, Michael W.; El-Samad, Hana

    2009-01-01

    Noise and stochasticity are fundamental to biology and derive from the very nature of biochemical reactions where thermal motion of molecules translates into randomness in the sequence and timing of reactions. This randomness leads to cell-cell variability even in clonal populations. Stochastic biochemical networks are modeled as continuous time discrete state Markov processes whose probability density functions evolve according to a chemical master equation (CME). The CME is not solvable but for the simplest cases, and one has to resort to kinetic Monte Carlo techniques to simulate the stochastic trajectories of the biochemical network under study. A commonly used such algorithm is the stochastic simulation algorithm (SSA). Because it tracks every biochemical reaction that occurs in a given system, the SSA presents computational difficulties especially when there is a vast disparity in the timescales of the reactions or in the number of molecules involved in these reactions. This is common in cellular networks, and many approximation algorithms have evolved to alleviate the computational burdens of the SSA. Here, we present a rigorously derived modified CME framework based on the partition of a biochemically reacting system into restricted and unrestricted reactions. Although this modified CME decomposition is as analytically difficult as the original CME, it can be naturally used to generate a hierarchy of approximations at different levels of accuracy. Most importantly, some previously derived algorithms are demonstrated to be limiting cases of our formulation. We apply our methods to biologically relevant test systems to demonstrate their accuracy and efficiency. PMID:19673546

  20. Functional Network Analysis: A New Way to Compare Frontier and Emerging Markets

    DTIC Science & Technology

    2012-06-01

    intersection of human behavior and economics. The individual motivations, information availability, transaction systems , and cultural realities in...and information flows between people, organizations, and functions enabling us to describe capital market structure and function in innovative ways...This study involves developing methodologies to classify capital market networks by comparing the capital markets in three frontier markets ( Ghana

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

    DOE PAGES

    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

  2. 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

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

    PubMed

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

    2013-01-18

    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.

  4. Social Marketing as a Framework for Recruitment: Illustrations From the REACH Study

    PubMed Central

    Nichols, Linda; Martindale-Adams, Jennifer; Burns, Robert; Coon, David; Ory, Marcia; Tarlow, Diane Mahoney Barbara; Burgio, Louis; Gallagher-Thompson, Dolores; Guy, Delois; Arguelles, Trinidad; Winter, Laraine

    2008-01-01

    Objectives Recruitment is often the most challenging aspect of research with older persons. Social marketing—applying marketing techniques to influence the behavior of target audiences to improve their welfare—can help researchers identify factors Methods Illustrations of social marketing principles are provided from the Resources for Enhancing Alzheimer’s Caregiver Health project, a national Alzheimer’s caregivers study that targeted ethnic and racial minorities. Results Social marketing principles—the six Ps of participants, product, price, place, promotion, and partners—provide a theoretical framework for organizing and planning recruitment activities, including developing varying strategies to define the target audience (participants), develop the intervention (product), manage time and trouble (price), target the audience, improve accessibility (place), promote the study, and develop and work with partners. Discussion Strategies to enhance recruitment are often undertaken without a comprehensive plan. A social marketing plan provides a framework to map out the steps in recruitment that will be needed and to plan for allocations of time, staff, and resources. PMID:15448292

  5. A Framework of Hyperspectral Image Compression using Neural Networks

    SciTech Connect

    Masalmah, Yahya M.; Martínez Nieves, Christian; Rivera Soto, Rafael; Velez, Carlos; Gonzalez, Jenipher

    2015-01-01

    Hyperspectral image analysis has gained great attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows us to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. Lastly, this paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.

  6. 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.

  7. A Framework of Hyperspectral Image Compression using Neural Networks

    DOE PAGES

    Masalmah, Yahya M.; Martínez Nieves, Christian; Rivera Soto, Rafael; ...

    2015-01-01

    Hyperspectral image analysis has gained great attention due to its wide range of applications. Hyperspectral images provide a vast amount of information about underlying objects in an image by using a large range of the electromagnetic spectrum for each pixel. However, since the same image is taken multiple times using distinct electromagnetic bands, the size of such images tend to be significant, which leads to greater processing requirements. The aim of this paper is to present a proposed framework for image compression and to study the possible effects of spatial compression on quality of unmixing results. Image compression allows usmore » to reduce the dimensionality of an image while still preserving most of the original information, which could lead to faster image processing. Lastly, this paper presents preliminary results of different training techniques used in Artificial Neural Network (ANN) based compression algorithm.« less

  8. 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.

  9. 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.

  10. A computational molecular design framework for crosslinked polymer networks

    PubMed Central

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

    2013-01-01

    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

  11. An Integrated Dynamic Online Management Framework for QoS-Sensitive Multimedia Overlay Networks

    NASA Astrophysics Data System (ADS)

    Kim, Sungwook; Choi, Myungwhan; Kim, Sungchun

    New multimedia services over cellular/WLAN overlay networks require different Quality of Service (QoS) levels. Therefore, an efficient network management system is necessary in order to realize QoS sensitive multimedia services while enhancing network performance. In this paper, we propose a new online network management framework for overlay networks. Our online approach to network management exhibits dynamic adaptability, flexibility, and responsiveness to the traffic conditions in multimedia networks. Simulation results indicate that our proposed framework can strike the appropriate balance between performance criteria under widely varying diverse traffic loads.

  12. 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

  13. 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.

  14. A Semiquantitative Framework for Gene Regulatory Networks: Increasing the Time and Quantitative Resolution of Boolean Networks

    PubMed Central

    Kerkhofs, Johan; Geris, Liesbet

    2015-01-01

    Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a basic quantitative and a limited time resolution to a discrete (Boolean) framework. Quantitative resolution is improved through the employ of normalized variables in unison with an additive approach. Increased time resolution stems from the introduction of two distinct priority classes. Through the implementation of a previously published chondrocyte network and T helper cell network, we show that this addition of quantitative and time resolution broadens the scope of biological behaviour that can be captured by the models. Specifically, the quantitative resolution readily allows models to discern qualitative differences in dosage response to growth factors. The limited time resolution, in turn, can influence the reachability of attractors, delineating the likely long term system behaviour. Importantly, the information required for implementation of these features, such as the nature of an interaction, is typically obtainable from the literature. Nonetheless, a trade-off is always present between additional computational cost of this approach and the likelihood of extending the model’s scope. Indeed, in some cases the inclusion of these features does not yield additional insight. This framework, incorporating increased and readily available time and semi-quantitative resolution, can help in substantiating the litmus test of dynamics for gene networks, firstly by excluding unlikely dynamics and secondly by refining falsifiable predictions on qualitative behaviour. PMID:26067297

  15. Global regulatory framework for production and marketing of crops biofortified with vitamins and minerals.

    PubMed

    Mejia, Luis A; Dary, Omar; Boukerdenna, Hala

    2017-02-01

    Biofortification of crops is being introduced in several countries as a strategy to reduce micronutrient deficiencies. Biofortified products, with increased contents of micronutrients, are currently produced by conventional plant breeding, genetic modification, or nutrient-enhanced fertilization. Corn, rice, wheat, beans, pearl millet, sweet potato, and cassava have been biofortified with increased contents of provitamin A carotenoids, iron, or zinc. However, regulatory considerations are rare or nonexistent. The objective of this paper is to review the regulatory framework for production and marketing of biofortified crops in countries that have adopted this strategy. The information was identified using Internet search engines and websites of health and nutrition organizations and nongovernmental organizations and by consulting scientists and government authorities. Thus far, biofortified products introduced in Latin America, Africa, and Asia have been produced only by conventional breeding. Cultivars using other techniques are still under testing. The production and marketing of these products have been conducted without regulatory framework and under limited government control or regulatory guidance. Nevertheless, some countries have integrated biofortified crops into their nutrition agendas. Although improvements by conventional breeding have not been subject to regulations, when biofortification becomes expanded by including other techniques, an appropriate regulatory framework will be necessary.

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

    PubMed

    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.

  17. 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

  18. 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.

  19. 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.

  20. Network Centric Operations Conceptual Framework Air-to-Ground Case Study

    DTIC Science & Technology

    2004-06-01

    Network Centric Operations Conceptual Framework Air-to-Ground Case Study Final Brief 17 June 2004 Prepared by SAIC for: Evidence Based Research...JUN 2004 2. REPORT TYPE 3. DATES COVERED 00-00-2004 to 00-00-2004 4. TITLE AND SUBTITLE Network Centric Operations Conceptual Framework Air-to... conceptual framework which drove approach Cognitive Social Interviews to provide insights into cognitive process Assumptions OEF and OIF would

  1. Fluvial networks of the Iberian Peninsula: a chronological framework

    NASA Astrophysics Data System (ADS)

    Santisteban, Juan I.; Schulte, Lothar

    2007-11-01

    Knowledge of the evolution of Spanish fluvial networks has improved during recent years as more river systems have been studied and more geochronological data has become available. However, the chronological framework is a major issue as the range of applications is limited by methodological constraints and spatial coverage is sparse. Integration of 'absolute' dating methods with biostratigraphy and palaeomagnetism permits the recent evolution of these river systems to be reviewed. The timing of incision from the Late Neogene to the present varies between the major Iberian fluvial systems, depending on the substrata and tectonic settings. Early Pleistocene and older fluvial sequences in the core areas of the Iberian Peninsula provide a more extensive record of fluvial evolution and are better preserved than the terrace flights in the coastal lowlands. Middle Pleistocene sequences are well developed in most of the major river systems in Iberia, particularly those of the Tajo, Guadalquivir and Aguas River, and frequently represent the principal climatic cycles of that period, although tectonic and sea-level effects can also be seen. For Late Pleistocene to Holocene times, the scheme becomes more complex. Our review suggests that each river system has responded differently to local and regional climate control, glacial and periglacial processes in headwaters in high mountain areas, glacio-eustatic sea-level changes and local and regional tectonic patterns.

  2. A Modified Artifitial Neural Network Ensemble Framework for Drought Estimation

    NASA Astrophysics Data System (ADS)

    Alobaidi, M. H.; Marpu, P. R.; Ouarda, T.

    2014-12-01

    Drought estimation at ungauged sites is a difficult task due to various challenges such as scale and limited availability and information about hydrologic neighborhoods. Ensemble regression has been recently utilized in modeling various hydrologic systems and showed advantage over classical regression approaches to such studies. A challenging task in ensemble modeling is the proper training of the ensemble's individual learners and the ensemble combiners. In this work, an ensemble framework is proposed to enhance the generalization ability of the sub-ensemble models and its combiner. Information mixtures between the subsamples are introduced. Such measure is dedicated to the ensemble members and ensemble combiners. Controlled homogeneity magnitudes are then stimulated and induced in the proposed model via a two-stage resampling algorithm. Artificial neural networks (ANNs) were used as ensemble members in addition to different ensemble integration plans. The model provided superior results when compared to previous models applied to the case study in this work. The root mean squared error (RMSE) in the testing phase for the drought quantiles improved by 67% - 76%. The bias error (BIAS) also showed 61% - 95% improvement.

  3. NetSim-Steer: A Runtime Steering Framework for Network Simulators

    SciTech Connect

    Ciraci, Selim; Akyol, Bora A.

    2012-08-07

    This paper presents NetSim-Steer, a runtime steering framework for network simulators. With this framework, users can specify execution constraints for the network protocols and network models. In addition to this, users can implement steering rules to be executed when a constraint is violated. These rules allows users to alter the parameters of the protocols/models during the simulation so that they stay within the boundaries of the constraints.

  4. NetSim Steer: A Runtime Steering Framework for Network Simulators

    SciTech Connect

    Ciraci, Selim; Akyol, Bora A.

    2012-08-09

    This paper presents NetSim-Steer, a runtime steering framework for network simulators. With this framework, users can specify execution constraints for the network protocols and network models. In addition to this, users can implement steering rules to be executed when a constraint is violated. These rules allows users to alter the parameters of the protocols/models during the simulation so that they stay within the boundaries of the constraints.

  5. 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.

  6. Sustainability for behaviour change in the fight against antibiotic resistance: a social marketing framework.

    PubMed

    Edgar, Timothy; Boyd, Stephanie D; Palamé, Megan J

    2009-02-01

    Antibiotic resistance is one of today's most urgent public health problems, threatening to undermine the effectiveness of infectious disease treatment in every country of the world. Specific individual behaviours such as not taking the entire antibiotic regimen and skipping doses contribute to resistance development as does the taking of antibiotics for colds and other illnesses that antibiotics cannot treat. Antibiotic resistance is as much a societal problem as it is an individual one; if mass behaviour change across the population does not occur, the problem of resistance cannot be mitigated at community levels. The problem is one that potentially can be solved if both providers and patients become sufficiently aware of the issue and if they engage in appropriate behaviours. Although a number of initiatives have been implemented in various parts of the world to elicit behaviour change, results have been mixed, and there is little evidence that trial programmes with positive outcomes serve as models of sustainability. In recent years, several scholars have suggested social marketing as the framework for behaviour change that has the greatest chance of sustained success, but the antibiotic resistance literature provides no specifics for how the principles of social marketing should be applied. This paper provides an overview of previous communication-based initiatives and offers a detailed approach to social marketing to guide future efforts.

  7. Characterizing emerging European stock markets through complex networks: From local properties to self-similar characteristics

    NASA Astrophysics Data System (ADS)

    Caraiani, Petre

    2012-07-01

    We investigate the properties of the returns of the main emerging stock markets from Europe by means of complex networks. We transform the series of daily returns into complex networks, and analyze the local properties of these networks with respect to degree distributions, clustering, or average line length. We further use the clustering coefficients as quantities describing the local structure of the network, and approach them by using multifractal analysis. We find evidence of scale-free networks and multifractality of clustering coefficients.

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

    PubMed

    Laubichler, Manfred D; Renn, Jürgen

    2015-11-01

    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.

  9. 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…

  10. Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

    NASA Astrophysics Data System (ADS)

    Hou, Rui; Wu, Jiawen; Du, Helen S.

    2017-03-01

    To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

  11. New Frameworks for Detecting and Minimizing Information Leakage in Anonymized Network Data

    DTIC Science & Technology

    2011-10-01

    FORCE RESEARCH LABORATORY INFORMATION DIRECTORATE NEW FRAMEWORKS FOR DETECTING AND MINIMIZING INFORMATION LEAKAGE IN ANONYMIZED NETWORK...FRAMEWORKS FOR DETECTING AND MINIMIZING INFORMATION LEAKAGE IN ANONYMIZED NETWORK DATA 5a. CONTRACT NUMBER FA8750-08-2-0147 5b. GRANT NUMBER N/A...risk, high-value data is that of trace anonymization - a process of sanitizing data before release so that information of concern cannot be extracted

  12. Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective

    NASA Astrophysics Data System (ADS)

    Wen, Shaobo; An, Haizhong; Chen, Zhihua; Liu, Xueyong

    2017-08-01

    In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government's policy mix.

  13. 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.

  14. A modelling and reasoning framework for social networks policies

    NASA Astrophysics Data System (ADS)

    Governatori, Guido; Iannella, Renato

    2011-02-01

    Policy languages (such as privacy and rights) have had little impact on the wider community. Now that social networks have taken off, the need to revisit policy languages and realign them towards social networks requirements has become more apparent. One such language is explored as to its applicability to the social networks masses. We also argue that policy languages alone are not sufficient and thus they should be paired with reasoning mechanisms to provide precise and unambiguous execution models of the policies. To this end, we propose a computationally oriented model to represent, reason with and execute policies for social networks.

  15. Internationalization, Globalization and Relationship Networks as an Epistemological Framework Based on Comparative Studies in Education

    ERIC Educational Resources Information Center

    García, Amelia Molina; Lara, José Luis Horacio Andrade

    2016-01-01

    In this paper we present some thoughts on the epistemological framework of comparative studies in education. We present some concepts on the internationalization, globalization and inter-relation networks, based on Jürgen Schriewer, Immanuel Wallerstein, and Norbert Elias's theoretical concepts. These reflections were built within the framework of…

  16. Network of listed companies based on common shareholders and the prediction of market volatility

    NASA Astrophysics Data System (ADS)

    Li, Jie; Ren, Da; Feng, Xu; Zhang, Yongjie

    2016-11-01

    In this paper, we build a network of listed companies in the Chinese stock market based on common shareholding data from 2003 to 2013. We analyze the evolution of topological characteristics of the network (e.g., average degree, diameter, average path length and clustering coefficient) with respect to the time sequence. Additionally, we consider the economic implications of topological characteristic changes on market volatility and use them to make future predictions. Our study finds that the network diameter significantly predicts volatility. After adding control variables used in traditional financial studies (volume, turnover and previous volatility), network topology still significantly influences volatility and improves the predictive ability of the model.

  17. 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…

  18. 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…

  19. Implementation of a Framework for Collaborative Social Networks in E-Learning

    ERIC Educational Resources Information Center

    Maglajlic, Seid

    2016-01-01

    This paper describes the implementation of a framework for the construction and utilization of social networks in ELearning. These social networks aim to enhance collaboration between all E-Learning participants (i.e. both traineeto-trainee and trainee-to-tutor communication are targeted). E-Learning systems that include a so-called "social…

  20. 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.

  1. 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.

  2. Forecasting of Market Clearing Price by Using GA Based Neural Network

    NASA Astrophysics Data System (ADS)

    Yang, Bo; Chen, Yun-Ping; Zhao, Zun-Lian; Han, Qi-Ye

    Forecasting of Market Clearing Price (MCP) is important to economic benefits of electricity market participants. To accurately forecast MCP, a novel two-stage GA-based neural network model (GA-NN) is proposed. In the first stage, GA chromosome is designed into two parts: boolean coding part for neural network topology and real coding part for connection weights. By hybrid genetic operation of selection, crossover and mutation under the criterion of error minimization between the actual output and the desired output, optimal architecture of neural network is obtained. In the second stage, gradient learning algorithm with momentum rate is imposed on neural network with optimal architecture. After learning process, optimal connection weights are obtained. The proposed model is tested on MCP forecasting in California electricity market. The test results show that GA-NN has self-adaptive ability in its topology and connection weights and can obtain more accurate MCP forecasting values than BP neural network.

  3. A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network

    PubMed Central

    Jadamba, Erkhembayar

    2016-01-01

    Drug repositioning offers new clinical indications for old drugs. Recently, many computational approaches have been developed to repurpose marketed drugs in human diseases by mining various of biological data including disease expression profiles, pathways, drug phenotype expression profiles, and chemical structure data. However, despite encouraging results, a comprehensive and efficient computational drug repositioning approach is needed that includes the high-level integration of available resources. In this study, we propose a systematic framework employing experimental genomic knowledge and pharmaceutical knowledge to reposition drugs for a specific disease. Specifically, we first obtain experimental genomic knowledge from disease gene expression profiles and pharmaceutical knowledge from drug phenotype expression profiles and construct a pathway-drug network representing a priori known associations between drugs and pathways. To discover promising candidates for drug repositioning, we initialize node labels for the pathway-drug network using identified disease pathways and known drugs associated with the phenotype of interest and perform network propagation in a semisupervised manner. To evaluate our method, we conducted some experiments to reposition 1309 drugs based on four different breast cancer datasets and verified the results of promising candidate drugs for breast cancer by a two-step validation procedure. Consequently, our experimental results showed that the proposed framework is quite useful approach to discover promising candidates for breast cancer treatment. PMID:28127549

  4. 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,…

  5. 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…

  6. 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.

  7. The use of social network methodological framework in nursing care to breastfeeding women.

    PubMed

    Souza, Maria Helena do Nascimento; Souza, Ivis Emília de Oliveira; Tocantins, Florence Romijn

    2009-01-01

    This study aimed to discuss the contribution of the social network methodological framework in nursing care delivered to women who breastfeed their children up to six months of age. This qualitative study aimed to elaborate the social network map of 20 women through tape-recorded interview. Social network analysis evidenced a 'strong' bond between these women and members from their primary network, especially friends, neighbors, mothers or with the child's father, who were reported as the people most involved in the breastfeeding period. The contribution of this framework to nursing practice is discussed, especially in care and research processes. We believe that nurses' appropriation of this framework can be an important support for efficacious actions, as well as to favor a broader perspective on the social context people experience.

  8. A Unifying Mathematical Framework for Genetic Robustness, Environmental Robustness, Network Robustness and their Tradeoff on Phenotype Robustness in Biological Networks Part II: Ecological Networks.

    PubMed

    Chen, Bor-Sen; Lin, Ying-Po

    2013-01-01

    In ecological networks, network robustness should be large enough to confer intrinsic robustness for tolerating intrinsic parameter fluctuations, as well as environmental robustness for resisting environmental disturbances, so that the phenotype stability of ecological networks can be maintained, thus guaranteeing phenotype robustness. However, it is difficult to analyze the network robustness of ecological systems because they are complex nonlinear partial differential stochastic systems. This paper develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance sensitivity in ecological networks. We found that the phenotype robustness criterion for ecological networks is that if intrinsic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations and environmental disturbances. These results in robust ecological networks are similar to that in robust gene regulatory networks and evolutionary networks even they have different spatial-time scales.

  9. 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.

  10. Automated iterative reclustering framework for determining hierarchical functional networks in resting state fMRI.

    PubMed

    Shams, Seyed-Mohammad; Afshin-Pour, Babak; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali; Strother, Stephen C

    2015-09-01

    To spatially cluster resting state-functional magnetic resonance imaging (rs-fMRI) data into potential networks, there are only a few general approaches that determine the number of networks/clusters, despite a wide variety of techniques proposed for clustering. For individual subjects, extraction of a large number of spatially disjoint clusters results in multiple small networks that are spatio-temporally homogeneous but irreproducible across subjects. Alternatively, extraction of a small number of clusters creates spatially large networks that are temporally heterogeneous but spatially reproducible across subjects. We propose a fully automatic, iterative reclustering framework in which a small number of spatially large, heterogeneous networks are initially extracted to maximize spatial reproducibility. Subsequently, the large networks are iteratively subdivided to create spatially reproducible subnetworks until the overall within-network homogeneity does not increase substantially. The proposed approach discovers a rich network hierarchy in the brain while simultaneously optimizing spatial reproducibility of networks across subjects and individual network homogeneity. We also propose a novel metric to measure the connectivity of brain regions, and in a simulation study show that our connectivity metric and framework perform well in the face of low signal to noise and initial segmentation errors. Experimental results generated using real fMRI data show that the proposed metric improves stability of network clusters across subjects, and generates a meaningful pattern for spatially hierarchical structure of the brain.

  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. 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.

  14. Visibility graph network analysis of natural gas price: The case of North American market

    NASA Astrophysics Data System (ADS)

    Sun, Mei; Wang, Yaqi; Gao, Cuixia

    2016-11-01

    Fluctuations in prices of natural gas significantly affect global economy. Therefore, the research on the characteristics of natural gas price fluctuations, turning points and its influencing cycle on the subsequent price series is of great significance. Global natural gas trade concentrates on three regional markets: the North American market, the European market and the Asia-Pacific market, with North America having the most developed natural gas financial market. In addition, perfect legal supervision and coordinated regulations make the North American market more open and more competitive. This paper focuses on the North American natural gas market specifically. The Henry Hub natural gas spot price time series is converted to a visibility graph network which provides a new direction for macro analysis of time series, and several indicators are investigated: degree and degree distribution, the average shortest path length and community structure. The internal mechanisms underlying price fluctuations are explored through the indicators. The results show that the natural gas prices visibility graph network (NGP-VGN) is of small-world and scale-free properties simultaneously. After random rearrangement of original price time series, the degree distribution of network becomes exponential distribution, different from the original ones. This means that, the original price time series is of long-range negative correlation fractal characteristic. In addition, nodes with large degree correspond to significant geopolitical or economic events. Communities correspond to time cycles in visibility graph network. The cycles of time series and the impact scope of hubs can be found by community structure partition.

  15. 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.

  16. Network Community Detection based on the Physarum-inspired Computational Framework.

    PubMed

    Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili

    2016-12-13

    Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.

  17. Social Networking Framework for Universities in Saudi Arabia

    ERIC Educational Resources Information Center

    Alqahtani, Sulaiman

    2016-01-01

    The interactive capacities of social networking instruments have unleashed a number of possibilities for enhancing teaching and learning in the higher education sector and many universities are engaged in harnessing the capabilities of these tools. While much valuable research has been conducted on this theme, scholarship has tended to be oriented…

  18. Towards a matrix mechanics framework for dynamic protein network

    PubMed Central

    2010-01-01

    Protein–protein interaction networks are currently visualized by software generated interaction webs based upon static experimental data. Current state is limited to static, mostly non-compartmental network and non time resolved protein interactions. A satisfactory mathematical foundation for particle interactions within a viscous liquid state (situation within the cytoplasm) does not exist nor do current computer programs enable building dynamic interaction networks for time resolved interactions. Building mathematical foundation for intracellular protein interactions can be achieved in two increments (a) trigger and capture the dynamic molecular changes for a select subset of proteins using several model systems and high throughput time resolved proteomics and, (b) use this information to build the mathematical foundation and computational algorithm for a compartmentalized and dynamic protein interaction network. Such a foundation is expected to provide benefit in at least two spheres: (a) understanding physiology enabling explanation of phenomenon such as incomplete penetrance in genetic disorders and (b) enabling several fold increase in biopharmaceutical production using impure starting materials. PMID:20805933

  19. The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

    NASA Astrophysics Data System (ADS)

    Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

    Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

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

    NASA Astrophysics Data System (ADS)

    Cao, Hongduo; Li, Ying

    2014-03-01

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

    PubMed

    Cao, Hongduo; Li, Ying

    2014-03-01

    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.

  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. Quantitative social science. A network framework of cultural history.

    PubMed

    Schich, Maximilian; Song, Chaoming; Ahn, Yong-Yeol; Mirsky, Alexander; Martino, Mauro; Barabási, Albert-László; Helbing, Dirk

    2014-08-01

    The emergent processes driving cultural history are a product of complex interactions among large numbers of individuals, determined by difficult-to-quantify historical conditions. To characterize these processes, we have reconstructed aggregate intellectual mobility over two millennia through the birth and death locations of more than 150,000 notable individuals. The tools of network and complexity theory were then used to identify characteristic statistical patterns and determine the cultural and historical relevance of deviations. The resulting network of locations provides a macroscopic perspective of cultural history, which helps us to retrace cultural narratives of Europe and North America using large-scale visualization and quantitative dynamical tools and to derive historical trends of cultural centers beyond the scope of specific events or narrow time intervals.

  4. Wireless industrial sensor networks: framework for QoS assessment and QoS management.

    PubMed

    Howitt, Ivan; Manges, Wayne W; Kuruganti, Phani Teja; Allgood, Glenn; Gutierrez, José A; Conrad, James M

    2006-07-01

    This paper presents a framework that addresses Quality of Service (QoS) for industrial wireless sensor networks as a real-time measurable set of parameters within the context of feedback control, thereby facilitating QoS management. This framework is based on examining the interaction between the industrial control processes and the wireless network. Control theory is used to evaluate the impact of the control/communication interaction, providing a methodology for defining, measuring, and quantifying QoS requirements. An example is presented illustrating the wireless industrial sensor network (WISN) QoS management framework for providing dynamic QoS control within WISN. The example focuses on WISN operating in a time-varying RF interference environment in order to manage application-driven QoS latency constraints.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. Development of a Neural Network-Based Renewable Energy Forecasting Framework for Process Industries

    SciTech Connect

    Lee, Soobin; Ryu, Jun-Hyung; Hodge, Bri-Mathias; Lee, In-Beum

    2016-06-25

    This paper presents a neural network-based forecasting framework for photovoltaic power (PV) generation as a decision-supporting tool to employ renewable energies in the process industry. The applicability of the proposed framework is illustrated by comparing its performance against other methodologies such as linear and nonlinear time series modelling approaches. A case study of an actual PV power plant in South Korea is presented.

  10. Stock market networks: The dynamic conditional correlation approach

    NASA Astrophysics Data System (ADS)

    Lyócsa, Štefan; Výrost, Tomáš; Baumöhl, Eduard

    2012-08-01

    We demonstrate the economic relevance of minimum spanning trees (MSTs) constructed from dynamic conditional correlations (DCC) for a sample of S&P 100 constituents. An empirical comparison of MST properties shows that using the standard approach of rolling (or sliding-window) correlations yields trees that are more robust, have higher densities and exhibit higher industry clustering than MSTs based on DCC. Our results suggest that these properties are achieved at the expense of the smoothing of market dynamics, which is better preserved by DCC. The DCC approach offers a new perspective for the analysis of complex systems such as stock markets.

  11. 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.

  12. 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.

  13. The discipline of hospital development: a conceptual framework incorporating marketing, managerial, consumer behavior, and adult learning theories.

    PubMed

    Shirley, S; Stampfl, R

    1997-12-01

    The purpose of this explanatory and prescriptive article is to identify interdisciplinary theories used by hospital development to direct its practice. The article explores, explains, and applies theories and principles from behavioral, social, and managerial disciplines. Learning, motivational, organizational, marketing, and attitudinal theories are incorporated and transformed into the fundamental components of a conceptual framework that provides an overview of the practice of hospital development. How this discipline incorporates these theories to design, explain, and prescribe the focus of its own practice is demonstrated. This interdisciplinary approach results in a framework for practice that is adaptable to changing social, cultural, economic, political, and technological environments.

  14. Modeling dynamics of adaptive complex systems: From gene regulatory networks to financial markets

    NASA Astrophysics Data System (ADS)

    Liu, Min

    This dissertation aims to model the dynamics of two types of adaptive complex systems: gene regulatory networks and financial markets. In modeling gene regulatory networks, a dynamics-driven rewiring mechanism is introduced to Boolean networks and it is found that a critical state emerges spontaneously resulting from the interplay between topology and dynamics during evolution. For biologically realized network sizes, significant finite-size effects are observed. In networks of competing Boolean nodes, we find that in small networks, the evolutionary dynamics selects for input inverting functions rather than canalizing functions in infinitely large networks. It is found that finite sizes can cause symmetry breaking in the evolutionary dynamics. Using the Polya theorem, we show the number of the function classes increases to 46, in contrast to 14 in infinitely large networks, due to the reduced symmetry which matches our simulation results well. In addition, we find that an optimum amount of stochastic noise in the signals exchanged between nodes can result in maximum excess canalization. In modeling financial markets, we simulate a double-auction virtual market by utilizing reaction-diffusion processes to describe the dynamics of limit orders. We find that the log-returns produced have a dynamical scaling exponent of 1/4 and nonstationary, negatively autocorrelated increments. By investigating the microstructure of the virtual market, we find that the mean interarrival time between transactions satisfies an increasing power-law function of time. We propose an inhomogeneous compound Poisson process with a decreasing power-law intensity rate function and demonstrate that this purely jump process captures the essential macroscopic dynamics of the virtual market.

  15. 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.

  16. Network structure of cross-correlations among the world market indices

    NASA Astrophysics Data System (ADS)

    Eryiğit, Mehmet; Eryiğit, Resul

    2009-09-01

    We report the results of an investigation of the properties of the networks formed by the cross-correlations of the daily and weekly index changes of 143 stock market indices from 59 different countries. Analysis of the asset graphs, minimum spanning trees (MST) and planar maximally filtered graphs (PMFG) of the afermentioned networks confirms that globalization has been increasing in recent years. North American and European markets are observed to be much more strongly connected among themselves compared to the integration with the other geographical regions. Surprisingly, the integration of East Asian markets among themselves as well as to the Western markets is found to be rather weak. MST and PMFG of both daily and weekly return correlations indicates that the clustering of the indices is mostly geographical. The French fsbf250 index is found to be most important node of the MST and PMFG based on several graph centrality measures.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

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

    PubMed Central

    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

    2016-01-01

    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

  3. Theoretical framework for the histone modification network: modifications in the unstructured histone tails form a robust scale-free network.

    PubMed

    Hayashi, Yohei; Senda, Toshiya; Sano, Norihiko; Horikoshi, Masami

    2009-07-01

    A rapid increase in research on the relationship between histone modifications and their subsequent reactions in the nucleus has revealed that the histone modification system is complex, and robust against point mutations. The prevailing theoretical framework (the histone code hypothesis) is inadequate to explain either the complexity or robustness, making the formulation of a new theoretical framework both necessary and desirable. Here, we develop a model of the regulatory network of histone modifications in which we encode histone modifications as nodes and regulatory interactions between histone modifications as links. This network has scale-free properties and subnetworks with a pseudo-mirror symmetry structure, which supports the robustness of the histone modification network. In addition, we show that the unstructured tail regions of histones are suitable for the acquisition of this scale-free property. Our model and related insights provide the first framework for an overall architecture of a histone modification network system, particularly with regard to the structural and functional roles of the unstructured histone tail region. In general, the post-translational "modification webs" of natively unfolded regions (proteins) may function as signal routers for the robust processing of the large amounts of signaling information.

  4. 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

  5. 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

  6. 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...

  7. 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:…

  8. 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.

  9. Microbiome Networks: A Systems Framework for Identifying Candidate Microbial Assemblages for Disease Management.

    PubMed

    Poudel, R; Jumpponen, A; Schlatter, D C; Paulitz, T C; Gardener, B B McSpadden; Kinkel, L L; Garrett, K A

    2016-10-01

    Network models of soil and plant microbiomes provide new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how observed network structures can be used to generate testable hypotheses about candidate microbes affecting plant health. The framework includes four types of network analyses. "General network analysis" identifies candidate taxa for maintaining an existing microbial community. "Host-focused analysis" includes a node representing a plant response such as yield, identifying taxa with direct or indirect associations with that node. "Pathogen-focused analysis" identifies taxa with direct or indirect associations with taxa known a priori as pathogens. "Disease-focused analysis" identifies taxa associated with disease. Positive direct or indirect associations with desirable outcomes, or negative associations with undesirable outcomes, indicate candidate taxa. Network analysis provides characterization not only of taxa with direct associations with important outcomes such as disease suppression, biofertilization, or expression of plant host resistance, but also taxa with indirect associations via their association with other key taxa. We illustrate the interpretation of network structure with analyses of microbiomes in the oak phyllosphere, and in wheat rhizosphere and bulk soil associated with the presence or absence of infection by Rhizoctonia solani.

  10. Development of Network Interface Cards for TRIDAQ systems with the NaNet framework

    NASA Astrophysics Data System (ADS)

    Ammendola, R.; Biagioni, A.; Cretaro, P.; Di Lorenzo, S.; Fiorini, M.; Frezza, O.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Valente, P.; Vicini, P.

    2017-03-01

    NaNet is a framework for the development of FPGA-based PCI Express (PCIe) Network Interface Cards (NICs) with real-time data transport architecture that can be effectively employed in TRIDAQ systems. Key features of the architecture are the flexibility in the configuration of the number and kind of the I/O channels, the hardware offloading of the network protocol stack, the stream processing capability, and the zero-copy CPU and GPU Remote Direct Memory Access (RDMA). Three NIC designs have been developed with the NaNet framework: NaNet-1 and NaNet-10 for the CERN NA62 low level trigger and NaNet3 for the KM3NeT-IT underwater neutrino telescope DAQ system. We will focus our description on the NaNet-10 design, as it is the most complete of the three in terms of capabilities and integrated IPs of the framework.

  11. 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.

  12. A biologically inspired sensor network framework for autonomous structural health monitoring

    NASA Astrophysics Data System (ADS)

    Chen, Bo

    2009-03-01

    This paper presents a biologically inspired sensor network framework for autonomous structural health monitoring (SHM). The presented sensor network framework transforms desirable characteristics and effective defense mechanisms of the natural immune system to wireless sensor networks for SHM. The autonomous structural health monitoring is achieved through an integrated sensor network framework consisting of high computational power sensors, a mobileagent- based sensor network middleware, and artificial immune pattern recognition (AIPR) methodology for structure damage detection and classification. An AIPR-based structure damage classifier (AIPR-SDC) has been developed, which incorporates several novel characteristics of the natural immune system. The performance of the AIPR-SDC has been validated using a benchmark structure proposed by the IASC-ASCE (International Association for Structural Control - American Society of Civil Engineers) SHM Task Group. The validation results show a better classification success rate comparing to some of other classification algorithms. The further study of unsupervised structure damage classification is also conducted by integrating data clustering techniques and the AIPR method.

  13. A comprehensive review on adaptability of network forensics frameworks for mobile cloud computing.

    PubMed

    Khan, Suleman; Shiraz, Muhammad; Wahab, Ainuddin Wahid Abdul; Gani, Abdullah; Han, Qi; Rahman, Zulkanain Bin Abdul

    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.

  14. 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

  15. 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.

  16. 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.

  17. Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data.

    PubMed

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor-McCourt, Maureen

    2015-02-01

    Tumor genome sequencing leads to documenting thousands of DNA mutations and other genomic alterations. At present, these data cannot be analyzed adequately to aid in the understanding of tumorigenesis and its evolution. Moreover, we have little insight into how to use these data to predict clinical phenotypes and tumor progression to better design patient treatment. To meet these challenges, we discuss a cancer hallmark network framework for modeling genome sequencing data to predict cancer clonal evolution and associated clinical phenotypes. The framework includes: (1) cancer hallmarks that can be represented by a few molecular/signaling networks. 'Network operational signatures' which represent gene regulatory logics/strengths enable to quantify state transitions and measures of hallmark traits. Thus, sets of genomic alterations which are associated with network operational signatures could be linked to the state/measure of hallmark traits. The network operational signature transforms genotypic data (i.e., genomic alterations) to regulatory phenotypic profiles (i.e., regulatory logics/strengths), to cellular phenotypic profiles (i.e., hallmark traits) which lead to clinical phenotypic profiles (i.e., a collection of hallmark traits). Furthermore, the framework considers regulatory logics of the hallmark networks under tumor evolutionary dynamics and therefore also includes: (2) a self-promoting positive feedback loop that is dominated by a genomic instability network and a cell survival/proliferation network is the main driver of tumor clonal evolution. Surrounding tumor stroma and its host immune systems shape the evolutionary paths; (3) cell motility initiating metastasis is a byproduct of the above self-promoting loop activity during tumorigenesis; (4) an emerging hallmark network which triggers genome duplication dominates a feed-forward loop which in turn could act as a rate-limiting step for tumor formation; (5) mutations and other genomic alterations have

  18. 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.

  19. 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

  20. 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.

  1. Toward a management framework for networks of protected areas in the face of climate change.

    PubMed

    Hole, David G; Huntley, Brian; Arinaitwe, Julius; Butchart, Stuart H M; Collingham, Yvonne C; Fishpool, Lincoln D C; Pain, Deborah J; Willis, Stephen G

    2011-04-01

    Networks of sites of high importance for conservation of biological diversity are a cornerstone of current conservation strategies but are fixed in space and time. As climate change progresses, substantial shifts in species' ranges may transform the ecological community that can be supported at a given site. Thus, some species in an existing network may not be protected in the future or may be protected only if they can move to sites that in future provide suitable conditions. We developed an approach to determine appropriate climate-change adaptation strategies for individual sites within a network that was based on projections of future changes in the relative proportions of emigrants (species for which a site becomes climatically unsuitable), colonists (species for which a site becomes climatically suitable), and persistent species (species able to remain within a site despite the climatic change). Our approach also identifies key regions where additions to a network could enhance its future effectiveness. Using the sub-Saharan African Important Bird Area (IBA) network as a case study, we found that appropriate conservation strategies for individual sites varied widely across sub-Saharan Africa, and key regions where new sites could help increase network robustness varied in space and time. Although these results highlight the potential difficulties within any planning framework that seeks to address climate-change adaptation needs, they demonstrate that such planning frameworks are necessary, if current conservation strategies are to be adapted effectively, and feasible, if applied judiciously.

  2. 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

    2014-02-11

    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.

  3. 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

  4. Emerging markets in the global economic network: Real(ly) decoupling?

    NASA Astrophysics Data System (ADS)

    Trancoso, Tiago

    2014-02-01

    We evaluate the degree of business cycle interdependence in the global economic network, focusing on the hypothesis that emergent market (EM) economies have decoupled from advanced economies in the recent period of globalization. We employ a novel methodological approach to the study of business cycles synchronization that combines network analysis and dynamic correlations. We find a process of increasing transnational interdependence within and across all economic development groups. Our results suggest that EM do not form a cohesive group and support the view of an increasingly multipolar and interdependent global economic network.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Artefacts in statistical analyses of network motifs: general framework and application to metabolic networks.

    PubMed

    Beber, Moritz Emanuel; Fretter, Christoph; Jain, Shubham; Sonnenschein, Nikolaus; Müller-Hannemann, Matthias; Hütt, Marc-Thorsten

    2012-12-07

    Few-node subgraphs are the smallest collective units in a network that can be investigated. They are beyond the scale of individual nodes but more local than, for example, communities. When statistically over- or under-represented, they are called network motifs. Network motifs have been interpreted as building blocks that shape the dynamic behaviour of networks. It is this promise of potentially explaining emergent properties of complex systems with relatively simple structures that led to an interest in network motifs in an ever-growing number of studies and across disciplines. Here, we discuss artefacts in the analysis of network motifs arising from discrepancies between the network under investigation and the pool of random graphs serving as a null model. Our aim was to provide a clear and accessible catalogue of such incongruities and their effect on the motif signature. As a case study, we explore the metabolic network of Escherichia coli and show that only by excluding ever more artefacts from the motif signature a strong and plausible correlation with the essentiality profile of metabolic reactions emerges.

  11. Artefacts in statistical analyses of network motifs: general framework and application to metabolic networks

    PubMed Central

    Beber, Moritz Emanuel; Fretter, Christoph; Jain, Shubham; Sonnenschein, Nikolaus; Müller-Hannemann, Matthias; Hütt, Marc-Thorsten

    2012-01-01

    Few-node subgraphs are the smallest collective units in a network that can be investigated. They are beyond the scale of individual nodes but more local than, for example, communities. When statistically over- or under-represented, they are called network motifs. Network motifs have been interpreted as building blocks that shape the dynamic behaviour of networks. It is this promise of potentially explaining emergent properties of complex systems with relatively simple structures that led to an interest in network motifs in an ever-growing number of studies and across disciplines. Here, we discuss artefacts in the analysis of network motifs arising from discrepancies between the network under investigation and the pool of random graphs serving as a null model. Our aim was to provide a clear and accessible catalogue of such incongruities and their effect on the motif signature. As a case study, we explore the metabolic network of Escherichia coli and show that only by excluding ever more artefacts from the motif signature a strong and plausible correlation with the essentiality profile of metabolic reactions emerges. PMID:22896565

  12. A uniform instrumentation, event, and adaptation framework for network-aware middleware and advanced network applications

    SciTech Connect

    Reed, Daniel A.

    2003-03-14

    Developers of advanced network applications such as remote instrument control, distributed data management, tele-immersion and collaboration, and distributed computing face a daunting challenge: sustaining robust application performance despite time-varying resource demands and dynamically changing resource availability. It is widely recognized that network-aware middleware is key to achieving performance robustness.

  13. 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.

  14. Comparing administered and market-based water allocation systems through a consistent agent-based modeling framework.

    PubMed

    Zhao, Jianshi; Cai, Ximing; Wang, Zhongjing

    2013-07-15

    Water allocation can be undertaken through administered systems (AS), market-based systems (MS), or a combination of the two. The debate on the performance of the two systems has lasted for decades but still calls for attention in both research and practice. This paper compares water users' behavior under AS and MS through a consistent agent-based modeling framework for water allocation analysis that incorporates variables particular to both MS (e.g., water trade and trading prices) and AS (water use violations and penalties/subsidies). Analogous to the economic theory of water markets under MS, the theory of rational violation justifies the exchange of entitled water under AS through the use of cross-subsidies. Under water stress conditions, a unique water allocation equilibrium can be achieved by following a simple bargaining rule that does not depend upon initial market prices under MS, or initial economic incentives under AS. The modeling analysis shows that the behavior of water users (agents) depends on transaction, or administrative, costs, as well as their autonomy. Reducing transaction costs under MS or administrative costs under AS will mitigate the effect that equity constraints (originating with primary water allocation) have on the system's total net economic benefits. Moreover, hydrologic uncertainty is shown to increase market prices under MS and penalties/subsidies under AS and, in most cases, also increases transaction, or administrative, costs.

  15. Chemical structure, network topology, and porosity effects on the mechanical properties of Zeolitic Imidazolate Frameworks

    PubMed Central

    Tan, Jin Chong; Bennett, Thomas D.; Cheetham, Anthony K.

    2010-01-01

    The mechanical properties of seven zeolitic imidazolate frameworks (ZIFs) based on five unique network topologies have been systematically characterized by single-crystal nanoindentation studies. We demonstrate that the elastic properties of ZIF crystal structures are strongly correlated to the framework density and the underlying porosity. For the systems considered here, the elastic modulus was found to range from 3 to 10 GPa, whereas the hardness property lies between 300 MPa and 1.1 GPa. Notably, these properties are superior to those of other metal–organic frameworks (MOFs), such as MOF-5. In substituted imidazolate frameworks, our results show that their mechanical properties are mainly governed by the rigidity and bulkiness of the substituted organic linkages. The framework topology and the intricate pore morphology can also influence the degree of mechanical anisotropy. Our findings present the previously undescribed structure-mechanical property relationships pertaining to hybrid open frameworks that are important for the design and application of new MOF materials. PMID:20479264

  16. 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

  17. 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.

  18. Strategic planning for health care markets: a framework and case study in analyzing diagnosis related groups.

    PubMed

    Wood, V R; Singh, J

    1986-09-01

    The sweeping changes in the health care industry, of which implementation of the prospective payment system (PPS) is one, put heavy demands on hospital administrators to "manage" their portfolio of health care products and services. The authors discuss the implications of PPS and other changes in the industry for strategic planning and present a framework based on an efficiency/profitability matrix. The framework can assist hospital managers in gaining strategic insight into their current portfolio and can guide their efforts in determining future product/service portfolios. A case study demonstrates the application of the proposed framework.

  19. 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…

  20. Spatiotemporal Dynamics and Fitness Analysis of Global Oil Market: Based on Complex Network

    PubMed Central

    Wang, Minggang; Fang, Guochang; Shao, Shuai

    2016-01-01

    We study the overall topological structure properties of global oil trade network, such as degree, strength, cumulative distribution, information entropy and weight clustering. The structural evolution of the network is investigated as well. We find the global oil import and export networks do not show typical scale-free distribution, but display disassortative property. Furthermore, based on the monthly data of oil import values during 2005.01–2014.12, by applying random matrix theory, we investigate the complex spatiotemporal dynamic from the country level and fitness evolution of the global oil market from a demand-side analysis. Abundant information about global oil market can be obtained from deviating eigenvalues. The result shows that the oil market has experienced five different periods, which is consistent with the evolution of country clusters. Moreover, we find the changing trend of fitness function agrees with that of gross domestic product (GDP), and suggest that the fitness evolution of oil market can be predicted by forecasting GDP values. To conclude, some suggestions are provided according to the results. PMID:27706147

  1. Spatiotemporal Dynamics and Fitness Analysis of Global Oil Market: Based on Complex Network.

    PubMed

    Du, Ruijin; Dong, Gaogao; Tian, Lixin; Wang, Minggang; Fang, Guochang; Shao, Shuai

    2016-01-01

    We study the overall topological structure properties of global oil trade network, such as degree, strength, cumulative distribution, information entropy and weight clustering. The structural evolution of the network is investigated as well. We find the global oil import and export networks do not show typical scale-free distribution, but display disassortative property. Furthermore, based on the monthly data of oil import values during 2005.01-2014.12, by applying random matrix theory, we investigate the complex spatiotemporal dynamic from the country level and fitness evolution of the global oil market from a demand-side analysis. Abundant information about global oil market can be obtained from deviating eigenvalues. The result shows that the oil market has experienced five different periods, which is consistent with the evolution of country clusters. Moreover, we find the changing trend of fitness function agrees with that of gross domestic product (GDP), and suggest that the fitness evolution of oil market can be predicted by forecasting GDP values. To conclude, some suggestions are provided according to the results.

  2. 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.

  3. Marketing for health-care organizations: an introduction to network management.

    PubMed

    Boonekamp, L C

    1994-01-01

    The introduction of regulated competition in health care in several Western countries confronts health care providing organizations with changing relationships, with their environment and a need for knowledge and skills to analyse and improve their market position. Marketing receives more and more attention, as recent developments in this field of study provide a specific perspective on the relationships between an organization and external and internal parties. In doing so, a basis is offered for network management. A problem is that the existing marketing literature is not entirely appropriate for the specific characteristics of health care. After a description of the developments in marketing and its most recent key concepts, the applicability of these concepts in health-care organizations is discussed. States that for the health-care sector, dominated by complex networks of interorganizational relationships, the strategic marketing vision on relationships can be very useful. At the same time however, the operationalization of these concepts requires special attention and a distinct role of the management of health-care organizations, because of the characteristics of such organizations and the specific type of their service delivery.

  4. Marketing.

    PubMed

    Chambers, David W

    2010-01-01

    There is not enough marketing of dentistry; but there certainly is too much selling of poor quality service that is being passed off as dentistry. The marketing concept makes the patient and the patients' needs the ultimate criteria of marketing efforts. Myths and good practices for effective marketing that will promote oral health are described under the traditional four "Ps" categories of "product" (best dental care), "place" (availability), "promotion" (advertising and other forms of making patients aware of available services and how to use them), and "price" (the total cost to patients of receiving care).

  5. Stress Averaging for a Beam Network for Use in a Hierarchical Multiscale Framework

    DTIC Science & Technology

    2015-03-01

    5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Richard Becker and Adam Sokolow 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7...14. ABSTRACT An efficient procedure for obtaining the average stress within a representative volume element (RVE) composed of beam elements is...developed and validated. A model composed of a network of elastic beam elements is taken as the lower length scale in a hierarchical modeling framework

  6. A Self-Adaptive Energy-Efficient Framework for Large Unattended Wireless Sensor Networks

    DTIC Science & Technology

    2014-11-06

    Report 15-May-2009- 15-Aug-2014 4. 1ITLE AND SUBTITLE 5a CONTRACT NUMBER Final Report: A Self-Adaptive Energy- Efficient Framework for W911NF-09-l-0154...unless so designated by other documentation. 14. ABSTRACT The objective of this research is to study energy efficient self-adaptive schemes for...1. ~~·· -~1....:1~ 15. SUBJECT TERMS wireless sensor networks, energy efficiency , adptive, data gathering, mobility, multiple-input

  7. A unified framework for chaotic neural-network approaches to combinatorial optimization.

    PubMed

    Kwok, T; Smith, K A

    1999-01-01

    As an attempt to provide an organized way to study the chaotic structures and their effects in solving combinatorial optimization with chaotic neural networks (CNN's), a unifying framework is proposed to serve as a basis where the existing CNN models can be placed and compared. The key of this proposed framework is the introduction of an extra energy term into the computational energy of the Hopfield model, which takes on different forms for different CNN models, and modifies the original Hopfield energy landscape in various manners. Three CNN models, namely the Chen and Aihara model with self-feedback chaotic simulated annealing (CSA), the Wang and Smith model with timestep CSA, and the chaotic noise model, are chosen as examples to show how they can be classified and compared within the proposed framework.

  8. A perimotor framework reveals functional segmentation in the motoneuronal network controlling locomotion in Caenorhabditis elegans.

    PubMed

    Haspel, Gal; O'Donovan, Michael J

    2011-10-12

    The neuronal connectivity dataset of the nematode Caenorhabditis elegans attracts wide attention from computational neuroscientists and experimentalists. However, the dataset is incomplete. The ventral and dorsal nerve cords of a single nematode were reconstructed halfway along the body and the posterior data are missing, leaving 21 of 75 motoneurons of the locomotor network with partial or no connectivity data. Using a new framework for network analysis, the perimotor space, we identified rules of connectivity that allowed us to approximate the missing data by extrapolation. Motoneurons were mapped into perimotor space in which each motoneuron is located according to the muscle cells it innervates. In this framework, a pattern of iterative connections emerges which includes most (0.90) of the connections. We identified a repeating unit consisting of 12 motoneurons and 12 muscle cells. The cell bodies of the motoneurons of such a unit are not necessarily anatomical neighbors and there is no obvious anatomical segmentation. A connectivity model, composed of six repeating units, is a description of the network that is both simplified (modular and without noniterative connections) and more complete (includes the posterior part) than the original dataset. The perimotor framework of observed connectivity and the segmented connectivity model give insights and advance the study of the neuronal infrastructure underlying locomotion in C. elegans. Furthermore, we suggest that the tools used herein may be useful to interpret, simplify, and represent connectivity data of other motor systems.

  9. 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

  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. Marketing.

    ERIC Educational Resources Information Center

    Maust, Robert N.

    1985-01-01

    Although college administrators may be committed to the concept and need for institutional marketing, even a well-developed marketing plan may not work if it is not clearly organized to address special needs. This article reviews management fads, how to make jargon operational, organizational dynamics, and monitoring fads. (MSE)

  12. 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.

  13. 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.

  14. 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

  15. 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

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

    PubMed

    Kafetzoglou, Stella; Aristomenopoulos, Giorgos; Papavassiliou, Symeon

    2015-08-11

    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.

  17. 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.

  18. A Bayesian Framework for Combining Protein and Network Topology Information for Predicting Protein-Protein Interactions.

    PubMed

    Birlutiu, Adriana; d'Alché-Buc, Florence; Heskes, Tom

    2015-01-01

    Computational methods for predicting protein-protein interactions are important tools that can complement high-throughput technologies and guide biologists in designing new laboratory experiments. The proteins and the interactions between them can be described by a network which is characterized by several topological properties. Information about proteins and interactions between them, in combination with knowledge about topological properties of the network, can be used for developing computational methods that can accurately predict unknown protein-protein interactions. This paper presents a supervised learning framework based on Bayesian inference for combining two types of information: i) network topology information, and ii) information related to proteins and the interactions between them. The motivation of our model is that by combining these two types of information one can achieve a better accuracy in predicting protein-protein interactions, than by using models constructed from these two types of information independently.

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

    PubMed

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

    2016-03-15

    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.

  20. 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.

  1. 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…

  2. Using a two-phase evolutionary framework to select multiple network spreaders based on community structure

    NASA Astrophysics Data System (ADS)

    Fu, Yu-Hsiang; Huang, Chung-Yuan; Sun, Chuen-Tsai

    2016-11-01

    Using network community structures to identify multiple influential spreaders is an appropriate method for analyzing the dissemination of information, ideas and infectious diseases. For example, data on spreaders selected from groups of customers who make similar purchases may be used to advertise products and to optimize limited resource allocation. Other examples include community detection approaches aimed at identifying structures and groups in social or complex networks. However, determining the number of communities in a network remains a challenge. In this paper we describe our proposal for a two-phase evolutionary framework (TPEF) for determining community numbers and maximizing community modularity. Lancichinetti-Fortunato-Radicchi benchmark networks were used to test our proposed method and to analyze execution time, community structure quality, convergence, and the network spreading effect. Results indicate that our proposed TPEF generates satisfactory levels of community quality and convergence. They also suggest a need for an index, mechanism or sampling technique to determine whether a community detection approach should be used for selecting multiple network spreaders.

  3. 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

  4. 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

    2016-07-02

    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.

  5. 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.

  6. 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

  7. 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.

  8. 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)

  9. 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.

  10. 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.

  11. Disruptive innovation, labor markets, and Big Valley STEM School: network analysis in STEM education

    NASA Astrophysics Data System (ADS)

    Ellison, Scott; Allen, Ben

    2016-11-01

    A defining characteristic of contemporary trends in global education policy is the promotion of STEM learning in the primary, secondary, and tertiary sectors of education as a means to generate innovation and prosperity in the economy. Intertwined with common sensical assumptions about future labor markets and the transformative potential of technology in education, STEM has become a hegemonic discourse informing policy formation and educational practice. In Gramscian terms, the struggle over STEM as a discursive practice, between proponents of instrumental learning of marketable economic skills and those of education towards humanistic goals, reveals insights about the ideological characteristics of the push for STEM learning. This article explores the power dynamics behind the push for STEM learning as an ideological discourse propagated by global networks of elite policy actors and enacted by non-elite policy actors at the school level. The findings point toward a disjuncture between the discourse of elite policy actors in the US, the realities of STEM labor markets, and the actualization of this policy discourse into classroom practice. The implications of this study indicate that analyses of vertical power relations in network governance in STEM education should attend to the semiotics, materiality, and mutability of networked spaces.

  12. ENcentive: A Framework for Intelligent Marketing in Mobile Peer-To-Peer Environments

    DTIC Science & Technology

    2005-01-01

    circulation since businesses that originally created the promotions re- ward the active distributors with additional promotions and other compensations...trade and commu- nication strategies, mobile electronic marketing, intelligent agents, collaborative eCommerce 1. INTRODUCTION With the explosion of...gadgets, applications and services, comes a set of new business models that address the needs of such mobile users. Mobile commerce is a new way to do

  13. 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.

  14. 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.

  15. 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

  16. 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.

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

    PubMed

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

    2016-01-21

    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. 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.

  19. [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.

  20. Forecasting the portuguese stock market time series by using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Isfan, Monica; Menezes, Rui; Mendes, Diana A.

    2010-04-01

    In this paper, we show that neural networks can be used to uncover the non-linearity that exists in the financial data. First, we follow a traditional approach by analysing the deterministic/stochastic characteristics of the Portuguese stock market data and some typical features are studied, like the Hurst exponents, among others. We also simulate a BDS test to investigate nonlinearities and the results are as expected: the financial time series do not exhibit linear dependence. Secondly, we trained four types of neural networks for the stock markets and used the models to make forecasts. The artificial neural networks were obtained using a three-layer feed-forward topology and the back-propagation learning algorithm. The quite large number of parameters that must be selected to develop a neural network forecasting model involves some trial and as a consequence the error is not small enough. In order to improve this we use a nonlinear optimization algorithm to minimize the error. Finally, the output of the 4 models is quite similar, leading to a qualitative forecast that we compare with the results of the application of k-nearest-neighbor for the same time series.

  1. 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

  2. An informatics framework for the standardized collection and analysis of medication data in networked research.

    PubMed

    Richesson, Rachel L

    2014-12-01

    Medication exposure is an important variable in virtually all clinical research, yet there is great variation in how the data are collected, coded, and analyzed. Coding and classification systems for medication data are heterogeneous in structure, and there is little guidance for implementing them, especially in large research networks and multi-site trials. Current practices for handling medication data in clinical trials have emerged from the requirements and limitations of paper-based data collection, but there are now many electronic tools to enable the collection and analysis of medication data. This paper reviews approaches to coding medication data in multi-site research contexts, and proposes a framework for the classification, reporting, and analysis of medication data. The framework can be used to develop tools for classifying medications in coded data sets to support context appropriate, explicit, and reproducible data analyses by researchers and secondary users in virtually all clinical research domains.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Understanding cancer complexome using networks, spectral graph theory and multilayer framework

    PubMed Central

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K.; Chowdhury, Rajdeep; Jalan, Sarika

    2017-01-01

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine. PMID:28155908

  10. Understanding cancer complexome using networks, spectral graph theory and multilayer framework

    NASA Astrophysics Data System (ADS)

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K.; Chowdhury, Rajdeep; Jalan, Sarika

    2017-02-01

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

  11. A network approach for the scientific collaboration in the European Framework Programs

    NASA Astrophysics Data System (ADS)

    Garas, A.; Argyrakis, P.

    2008-12-01

    We construct the networks of collaboration between partners for projects carried out with the support of European Commission Framework Programs FP5 and FP6. We analyze in detail these networks, not only in terms of total number of projects, but also for the different tools employed, the different geographical partitions, and the different thematic areas. For all cases we find a scale-free behavior, as expected for such social networks, and also reported in the literature. In comparing FP5 to FP6, we show that, despite a decrease in the number of signed contracts, and the total number of unique partners, there is an increase in the average number of collaborative partners per institution. Furthermore, we establish a measure for the central role (hub) for each country, by using the Minimum Spanning Tree (MST), which we construct in detail for each thematic area (e.g. Informatics, Nanoscience, Life Sciences, etc.). The importance of these network hubs is highlighted, as this information can be used by policy planners in designing future research plans regarding the distribution of available funds.

  12. Understanding cancer complexome using networks, spectral graph theory and multilayer framework.

    PubMed

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K; Chowdhury, Rajdeep; Jalan, Sarika

    2017-02-03

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

  13. On Governance, Embedding and Marketing: Reflections on the Construction of Alternative Sustainable Food Networks.

    PubMed

    Roep, Dirk; Wiskerke, Johannes S C

    Based on the reconstruction of the development of 14 food supply chain initiatives in 7 European countries, we developed a conceptual framework that demonstrates that the process of increasing the sustainability of food supply chains is rooted in strategic choices regarding governance, embedding, and marketing and in the coordination of these three dimensions that are inextricably interrelated. The framework also shows that when seeking to further develop an initiative (e.g., through scaling up or product diversification) these interrelations need continuous rebalancing. We argue that the framework can serve different purposes: it can be used as an analytical tool by researchers studying food supply chain dynamics, as a policy tool by policymakers that want to support the development of sustainable food supply chains, and as a reflexive tool by practitioners and their advisors to help them to position themselves, develop a clear strategy, find the right allies, develop their skills, and build the capacities that they need. In this paper, we elaborate upon the latter function of the framework and illustrate this briefly with empirical evidence from three of the initiatives that we studied.

  14. 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.

  15. How can the regulator show evidence of (no) risk selection in health insurance markets? Conceptual framework and empirical evidence.

    PubMed

    van de Ven, Wynand P M M; van Vliet, René C J A; van Kleef, Richard C

    2017-03-01

    If consumers have a choice of health plan, risk selection is often a serious problem (e.g., as in Germany, Israel, the Netherlands, the United States of America, and Switzerland). Risk selection may threaten the quality of care for chronically ill people, and may reduce the affordability and efficiency of healthcare. Therefore, an important question is: how can the regulator show evidence of (no) risk selection? Although this seems easy, showing such evidence is not straightforward. The novelty of this paper is two-fold. First, we provide a conceptual framework for showing evidence of risk selection in competitive health insurance markets. It is not easy to disentangle risk selection and the insurers' efficiency. We suggest two methods to measure risk selection that are not biased by the insurers' efficiency. Because these measures underestimate the true risk selection, we also provide a list of signals of selection that can be measured and that, in particular in combination, can show evidence of risk selection. It is impossible to show the absence of risk selection. Second, we empirically measure risk selection among the switchers, taking into account the insurers' efficiency. Based on 2-year administrative data on healthcare expenses and risk characteristics of nearly all individuals with basic health insurance in the Netherlands (N > 16 million) we find significant risk selection for most health insurers. This is the first publication of hard empirical evidence of risk selection in the Dutch health insurance market.

  16. 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...

  17. A hybrid framework for reservoir characterization using fuzzy ranking and an artificial neural network

    NASA Astrophysics Data System (ADS)

    Wang, Baijie; Wang, Xin; Chen, Zhangxin

    2013-08-01

    Reservoir characterization refers to the process of quantitatively assigning reservoir properties using all available field data. Artificial neural networks (ANN) have recently been introduced to solve reservoir characterization problems dealing with the complex underlying relationships inherent in well log data. Despite the utility of ANNs, the current limitation is that most existing applications simply focus on directly implementing existing ANN models instead of improving/customizing them to fit the specific reservoir characterization tasks at hand. In this paper, we propose a novel intelligent framework that integrates fuzzy ranking (FR) and multilayer perceptron (MLP) neural networks for reservoir characterization. FR can automatically identify a minimum subset of well log data as neural inputs, and the MLP is trained to learn the complex correlations from the selected well log data to a target reservoir property. FR guarantees the selection of the optimal subset of representative data from the overall well log data set for the characterization of a specific reservoir property; and, this implicitly improves the modeling and predication accuracy of the MLP. In addition, a growing number of industrial agencies are implementing geographic information systems (GIS) in field data management; and, we have designed the GFAR solution (GIS-based FR ANN Reservoir characterization solution) system, which integrates the proposed framework into a GIS system that provides an efficient characterization solution. Three separate petroleum wells from southwestern Alberta, Canada, were used in the presented case study of reservoir porosity characterization. Our experiments demonstrate that our method can generate reliable results.

  18. Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning.

    PubMed

    Zhang, Yue; Song, Bin; Zhang, Ying; Du, Xiaojiang; Guizani, Mohsen

    2016-11-29

    Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users' patterns. Reinforcement learning methods are introduced to estimate users' patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management.

  19. Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

    PubMed Central

    Zhang, Yue; Song, Bin; Zhang, Ying; Du, Xiaojiang; Guizani, Mohsen

    2016-01-01

    Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management. PMID:27916841

  20. Study of a market model with conservative exchanges on complex networks

    NASA Astrophysics Data System (ADS)

    Braunstein, Lidia A.; Macri, Pablo A.; Iglesias, J. R.

    2013-04-01

    Many models of market dynamics make use of the idea of conservative wealth exchanges among economic agents. A few years ago an exchange model using extremal dynamics was developed and a very interesting result was obtained: a self-generated minimum wealth or poverty line. On the other hand, the wealth distribution exhibited an exponential shape as a function of the square of the wealth. These results have been obtained both considering exchanges between nearest neighbors or in a mean field scheme. In the present paper we study the effect of distributing the agents on a complex network. We have considered archetypical complex networks: Erdös-Rényi random networks and scale-free networks. The presence of a poverty line with finite wealth is preserved but spatial correlations are important, particularly between the degree of the node and the wealth. We present a detailed study of the correlations, as well as the changes in the Gini coefficient, that measures the inequality, as a function of the type and average degree of the considered networks.

  1. 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.

  2. Systemic risk in a unifying framework for cascading processes on networks

    NASA Astrophysics Data System (ADS)

    Lorenz, J.; Battiston, S.; Schweitzer, F.

    2009-10-01

    We introduce a general framework for models of cascade and contagion processes on networks, to identify their commonalities and differences. In particular, models of social and financial cascades, as well as the fiber bundle model, the voter model, and models of epidemic spreading are recovered as special cases. To unify their description, we define the net fragility of a node, which is the difference between its fragility and the threshold that determines its failure. Nodes fail if their net fragility grows above zero and their failure increases the fragility of neighbouring nodes, thus possibly triggering a cascade. In this framework, we identify three classes depending on the way the fragility of a node is increased by the failure of a neighbour. At the microscopic level, we illustrate with specific examples how the failure spreading pattern varies with the node triggering the cascade, depending on its position in the network and its degree. At the macroscopic level, systemic risk is measured as the final fraction of failed nodes, X*, and for each of the three classes we derive a recursive equation to compute its value. The phase diagram of X* as a function of the initial conditions, thus allows for a prediction of the systemic risk as well as a comparison of the three different model classes. We could identify which model class leads to a first-order phase transition in systemic risk, i.e. situations where small changes in the initial conditions determine a global failure. Eventually, we generalize our framework to encompass stochastic contagion models. This indicates the potential for further generalizations.

  3. Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study

    PubMed Central

    Acharjee, Animesh

    2016-01-01

    The socio-economic systems today possess high levels of both interconnectedness and interdependencies, and such system-level relationships behave very dynamically. In such situations, it is all around perceived that influence is a perplexing power that has an overseeing part in affecting the dynamics and behaviours of involved ones. As a result of the force & direction of influence, the transformative change of one entity has a cogent aftereffect on the other entities in the system. The current study employs directed weighted networks for investigating the influential relationship patterns existent in a typical equity market as an outcome of inter-stock interactions happening at the market level, the sectorial level and the industrial level. The study dataset is derived from 335 constituent stocks of ‘Standard & Poor Bombay Stock Exchange 500 index’ and study period is 1st June 2005 to 30th June 2015. The study identifies the set of most dynamically influential stocks & their respective temporal pattern at three hierarchical levels: the complete equity market, different sectors, and constituting industry segments of those sectors. A detailed influence relationship analysis is performed for the sectorial level network of the construction sector, and it was found that stocks belonging to the cement industry possessed high influence within this sector. Also, the detailed network analysis of construction sector revealed that it follows scale-free characteristics and power law distribution. In the industry specific influence relationship analysis for cement industry, methods based on threshold filtering and minimum spanning tree were employed to derive a set of sub-graphs having temporally stable high-correlation structure over this ten years period. PMID:27846251

  4. Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study.

    PubMed

    Bhattacharjee, Biplab; Shafi, Muhammad; Acharjee, Animesh

    2016-01-01

    The socio-economic systems today possess high levels of both interconnectedness and interdependencies, and such system-level relationships behave very dynamically. In such situations, it is all around perceived that influence is a perplexing power that has an overseeing part in affecting the dynamics and behaviours of involved ones. As a result of the force & direction of influence, the transformative change of one entity has a cogent aftereffect on the other entities in the system. The current study employs directed weighted networks for investigating the influential relationship patterns existent in a typical equity market as an outcome of inter-stock interactions happening at the market level, the sectorial level and the industrial level. The study dataset is derived from 335 constituent stocks of 'Standard & Poor Bombay Stock Exchange 500 index' and study period is 1st June 2005 to 30th June 2015. The study identifies the set of most dynamically influential stocks & their respective temporal pattern at three hierarchical levels: the complete equity market, different sectors, and constituting industry segments of those sectors. A detailed influence relationship analysis is performed for the sectorial level network of the construction sector, and it was found that stocks belonging to the cement industry possessed high influence within this sector. Also, the detailed network analysis of construction sector revealed that it follows scale-free characteristics and power law distribution. In the industry specific influence relationship analysis for cement industry, methods based on threshold filtering and minimum spanning tree were employed to derive a set of sub-graphs having temporally stable high-correlation structure over this ten years period.

  5. 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.

  6. 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.

  7. A model framework for the enhancement of community detection in complex networks

    NASA Astrophysics Data System (ADS)

    He, Dongxiao; Wang, Hongcui; Jin, Di; Liu, Baolin

    2016-11-01

    Community detection is an important data analysis problem in many different areas, and how to enhance the quality of community detection in complicated real applications is still a challenge. Current community detection enhancement methods often take the enhancement as a preprocess of community detection. They mainly focus on how to design the suitable topological similarity of nodes to adjust the original network, but did not consider how to make use of this topological similarity more effectively. In order to better utilize the similarity information, we propose a model framework which integrates the enhancement into the whole community detection procedure. First, we calculate the structural similarity of nodes based on network topology. Second, we present a stochastic model to describe the community memberships of nodes; we then model the strong constraint based on structural similarity, i.e., we make each node have the same community membership distribution with its most similar neighbors; and then we model the weak constraint, i.e., if two nodes have a high similarity we will make their community membership distributions close, otherwise we will make them not close. Finally, we present a nonnegative matrix factorization approach to learn the model parameters. We evaluate our method on both synthetic and real-world networks with ground-truths, and compare it with five comparable methods. The experimental results demonstrate the superior performance of our new method over the competing ones for community detection and enhancement.

  8. 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

  9. 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

  10. Conceptual framework for assessing the response of delta channel networks to Holocene sea level rise

    NASA Astrophysics Data System (ADS)

    Jerolmack, Douglas J.

    2009-08-01

    Recent research has identified two fundamental unit processes that build delta distributary channels. The first is mouth-bar deposition at the shoreline and subsequent channel bifurcation, which is driven by progradation of the shoreline; the second is avulsion to a new channel, a result of aggradation of the delta topset. The former creates relatively small, branching networks such as Wax Lake Delta; the latter generates relatively few, long distributaries such as the Mississippi and Atchafalaya channels on the Mississippi Delta. The relative rate of progradation to aggradation, and hence the creation of accommodation space, emerges as a controlling parameter on channel network form. Field and experimental research has identified sea level as the dominant control on Holocene delta growth worldwide, and has empirically linked channel network changes to changes in the rate of sea level rise. Here I outline a simple modeling framework for distributary network evolution, and use this to explore large-scale changes in Holocene channel pattern that have been observed in deltas such as the Rhine-Meuse and Mississippi. Rapid early- to mid-Holocene sea level rise forced many deltas into an aggradational mode, where I hypothesize that avulsion and the generation of large-scale branches should dominate. Slowing of sea level rise in the last ˜6000 yr allowed partitioning of sediment into progradation, facilitating the growth of smaller-scale distributary trees at the shorelines of some deltas, and a reduction in the number of large-scale branches. Significant antecedent topography modulates delta response; the filling of large incised valleys, for example, caused many deltas to bypass the aggradational phase. Human effects on deltas can be cast in terms of geologic controls affecting accommodation: constriction of channels forces rapid local progradation and mouth-bar bifurcation, while accelerated sea level rise increases aggradation and induces more frequent channel

  11. 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

  12. Adding Abstraction and Reuse to a Network Modelling Tool Using the Reuseware Composition Framework

    NASA Astrophysics Data System (ADS)

    Johannes, Jendrik; Fernández, Miguel A.

    Domain-specific modelling (DSM) environments enable experts in a certain domain to actively participate in model-driven development. Developing DSM environments need to be cost-efficient, since they are only used by a limited group of domain experts. Different model-driven technologies promise to allow this cost-efficient development. [1] presented experiences in developing a DSM environment for telecommunication network modelling. There, challenges were identified that need to be addressed by other new modelling technologies. In this paper, we now present the results of addressing one of theses challenges - abstraction and reuse support - with the Reuseware Composition Framework. We show how we identified the abstraction and reuse features required in the telecommunication DSM environment in a case study and extended the existing environment with these features using Reuseware. We discuss the advantages of using this technology and propose a process for further improving the abstraction and reuse capabilities of the DSM environment in the future.

  13. An automatic fall detection framework using data fusion of Doppler radar and motion sensor network.

    PubMed

    Liu, Liang; Popescu, Mihail; Skubic, Marjorie; Rantz, Marilyn

    2014-01-01

    This paper describes the ongoing work of detecting falls in independent living senior apartments. We have developed a fall detection system with Doppler radar sensor and implemented ceiling radar in real senior apartments. However, the detection accuracy on real world data is affected by false alarms inherent in the real living environment, such as motions from visitors. To solve this issue, this paper proposes an improved framework by fusing the Doppler radar sensor result with a motion sensor network. As a result, performance is significantly improved after the data fusion by discarding the false alarms generated by visitors. The improvement of this new method is tested on one week of continuous data from an actual elderly person who frequently falls while living in her senior home.

  14. 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.

  15. 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.

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

    PubMed

    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.

  17. 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.

  18. 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.

  19. A mathematical framework for agent based models of complex biological networks.

    PubMed

    Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

    2011-07-01

    Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

  20. A remote quantitative Fugl-Meyer assessment framework for stroke patients based on wearable sensor networks.

    PubMed

    Yu, Lei; Xiong, Daxi; Guo, Liquan; Wang, Jiping

    2016-05-01

    To extend the use of wearable sensor networks for stroke patients training and assessment in non-clinical settings, this paper proposes a novel remote quantitative Fugl-Meyer assessment (FMA) framework, in which two accelerometer and seven flex sensors were used to monitoring the movement function of upper limb, wrist and fingers. The extreme learning machine based ensemble regression model was established to map the sensor data to clinical FMA scores while the RRelief algorithm was applied to find the optimal features subset. Considering the FMA scale is time-consuming and complicated, seven training exercises were designed to replace the upper limb related 33 items in FMA scale. 24 stroke inpatients participated in the experiments in clinical settings and 5 of them were involved in the experiments in home settings after they left the hospital. Both the experimental results in clinical and home settings showed that the proposed quantitative FMA model can precisely predict the FMA scores based on wearable sensor data, the coefficient of determination can reach as high as 0.917. It also indicated that the proposed framework can provide a potential approach to the remote quantitative rehabilitation training and evaluation.

  1. Product Design Network Self-contextualization: Enterprise Knowledge-Based Approach and Agent-Based Technological Framework

    NASA Astrophysics Data System (ADS)

    Levashova, Tatiana; Sandkuhl, Kurt; Shilov, Nikolay; Smirnov, Alexander; Tarasov, Vladimir

    The paper introduces self-contextualization in a service infrastructure for product design networks as novel application field for multi-agent technology. The main contributions of this paper are (1) identification of requirements from product design networks to the supporting service infrastructure, (2) the use of enterprise knowledge modelling techniques for the representation of computable context models, (3) a technological framework based on agent technology for self-contextualization based on enterprise knowledge models.

  2. 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.

  3. 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

  4. Mathematical framework for large-scale brain network modeling in The Virtual Brain.

    PubMed

    Sanz-Leon, Paula; Knock, Stuart A; Spiegler, Andreas; Jirsa, Viktor K

    2015-05-01

    In this article, we describe the mathematical framework of the computational model at the core of the tool The Virtual Brain (TVB), designed to simulate collective whole brain dynamics by virtualizing brain structure and function, allowing simultaneous outputs of a number of experimental modalities such as electro- and magnetoencephalography (EEG, MEG) and functional Magnetic Resonance Imaging (fMRI). The implementation allows for a systematic exploration and manipulation of every underlying component of a large-scale brain network model (BNM), such as the neural mass model governing the local dynamics or the structural connectivity constraining the space time structure of the network couplings. Here, a consistent notation for the generalized BNM is given, so that in this form the equations represent a direct link between the mathematical description of BNMs and the components of the numerical implementation in TVB. Finally, we made a summary of the forward models implemented for mapping simulated neural activity (EEG, MEG, sterotactic electroencephalogram (sEEG), fMRI), identifying their advantages and limitations.

  5. 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.

  6. AlleleSeq: analysis of allele-specific expression and binding in a network framework.

    PubMed

    Rozowsky, Joel; Abyzov, Alexej; Wang, Jing; Alves, Pedro; Raha, Debasish; Harmanci, Arif; Leng, Jing; Bjornson, Robert; Kong, Yong; Kitabayashi, Naoki; Bhardwaj, Nitin; Rubin, Mark; Snyder, Michael; Gerstein, Mark

    2011-08-02

    To study allele-specific expression (ASE) and binding (ASB), that is, differences between the maternally and paternally derived alleles, we have developed a computational pipeline (AlleleSeq). Our pipeline initially constructs a diploid personal genome sequence (and corresponding personalized gene annotation) using genomic sequence variants (SNPs, indels, and structural variants), and then identifies allele-specific events with significant differences in the number of mapped reads between maternal and paternal alleles. There are many technical challenges in the construction and alignment of reads to a personal diploid genome sequence that we address, for example, bias of reads mapping to the reference allele. We have applied AlleleSeq to variation data for NA12878 from the 1000 Genomes Project as well as matched, deeply sequenced RNA-Seq and ChIP-Seq data sets generated for this purpose. In addition to observing fairly widespread allele-specific behavior within individual functional genomic data sets (including results consistent with X-chromosome inactivation), we can study the interaction between ASE and ASB. Furthermore, we investigate the coordination between ASE and ASB from multiple transcription factors events using a regulatory network framework. Correlation analyses and network motifs show mostly coordinated ASB and ASE.

  7. Determinants of hospital choice of rural hospital patients: the impact of networks, service scopes, and market competition.

    PubMed

    Roh, Chul-Young; Lee, Keon-Hyung; Fottler, Myron D

    2008-08-01

    Among 10,384 rural Colorado female patients who received MDC 14 (obstetric services) from 2000 to 2003, 6,615 (63.7%) were admitted to their local rural hospitals; 1,654 (15.9%) were admitted to other rural hospitals; and 2,115 (20.4%) traveled to urban hospitals for inpatient services. This study is to examine how network participation, service scopes, and market competition influences rural women's choice of hospital for their obstetric care. A conditional logistic regression analysis was used. The network participation (p < 0.01), the number of services offered (p < 0.05), and the hospital market competition had a positive and significant relationship with patients' choice to receive obstetric care. That is, rural patients prefer to receive care from a hospital that participates in a network, that provides more number of services, and that has a greater market share (i.e., a lower level of market competition) in their locality. Rural hospitals could actively increase their competitiveness and market share by increasing the number of health care services provided and seeking to network with other hospitals.

  8. Networking activities and perceptions of HIV risk among male migrant market vendors in China.

    PubMed

    Wang, Wenqing; Muessig, Kathryn E; Li, Mingqiang; Zhang, Ying-Xia; Zhang, Yingxia

    2014-02-01

    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 22-56, 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.

  9. 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

  10. Hospital marketing.

    PubMed

    Carter, Tony

    2003-01-01

    This article looks at a prescribed academic framework for various criteria that serve as a checklist for marketing performance that can be applied to hospital marketing organizations. These guidelines are drawn from some of Dr. Noel Capon of Columbia University's book Marketing Management in the 21st Century and applied to actual practices of hospital marketing organizations. In many ways this checklist can act as a "marketing" balanced scorecard to verify performance effectiveness and develop opportunities for innovation.

  11. Social network analysis of the movement of poultry to and from live bird markets in Bali and Lombok, Indonesia.

    PubMed

    Kurscheid, J; Stevenson, M; Durr, P A; Toribio, J-A L M L; Kurscheid, S; Ambarawati, I G A A; Abdurrahman, M; Fenwick, S

    2017-02-04

    Highly pathogenic avian influenza H5N1 has resulted in large losses to the Indonesian poultry sector. Evidence suggests that live bird markets (LBMs) play an important role in the epidemiology of the disease. Knowledge of the frequency and type of contact between the various poultry market players should allow animal health authorities to develop a better understanding of factors influencing virus transmission between Indonesian villages. A questionnaire-based cross-sectional survey was conducted in 17 LBMs on the neighbouring Indonesian islands of Bali and Lombok to investigate the movement patterns of poultry to and from markets. Using social network analyses, a network of contacts was created for each island from a total of 413 live poultry traders and 134 customers. Individual nodes with high degree and/or betweenness were identified in each network. The Lombok network was more dense and connected than the Bali network indicating that disease transmission would be more efficient in the Lombok network. Our findings indicate that whilst live poultry are typically transported over relatively short distances of approximately 10 km, it is not uncommon for traders and customers to travel in excess of 100 km to buy or sell poultry, which may facilitate the spread of disease over a large geographical area. This study highlights the different roles markets play in poultry movement networks and their potential for disease dissemination. The identification of highly influential market nodes allows authorities to target HPAI surveillance activities to locations where disease is more likely to be present, which is crucial in low-resource settings.

  12. Topological Characteristics of the Hong Kong Stock Market: A Test-based P-threshold Approach to Understanding Network Complexity

    NASA Astrophysics Data System (ADS)

    Xu, Ronghua; Wong, Wing-Keung; Chen, Guanrong; Huang, Shuo

    2017-02-01

    In this paper, we analyze the relationship among stock networks by focusing on the statistically reliable connectivity between financial time series, which accurately reflects the underlying pure stock structure. To do so, we firstly filter out the effect of market index on the correlations between paired stocks, and then take a t-test based P-threshold approach to lessening the complexity of the stock network based on the P values. We demonstrate the superiority of its performance in understanding network complexity by examining the Hong Kong stock market. By comparing with other filtering methods, we find that the P-threshold approach extracts purely and significantly correlated stock pairs, which reflect the well-defined hierarchical structure of the market. In analyzing the dynamic stock networks with fixed-size moving windows, our results show that three global financial crises, covered by the long-range time series, can be distinguishingly indicated from the network topological and evolutionary perspectives. In addition, we find that the assortativity coefficient can manifest the financial crises and therefore can serve as a good indicator of the financial market development.

  13. Topological Characteristics of the Hong Kong Stock Market: A Test-based P-threshold Approach to Understanding Network Complexity

    PubMed Central

    Xu, Ronghua; Wong, Wing-Keung; Chen, Guanrong; Huang, Shuo

    2017-01-01

    In this paper, we analyze the relationship among stock networks by focusing on the statistically reliable connectivity between financial time series, which accurately reflects the underlying pure stock structure. To do so, we firstly filter out the effect of market index on the correlations between paired stocks, and then take a t-test based P-threshold approach to lessening the complexity of the stock network based on the P values. We demonstrate the superiority of its performance in understanding network complexity by examining the Hong Kong stock market. By comparing with other filtering methods, we find that the P-threshold approach extracts purely and significantly correlated stock pairs, which reflect the well-defined hierarchical structure of the market. In analyzing the dynamic stock networks with fixed-size moving windows, our results show that three global financial crises, covered by the long-range time series, can be distinguishingly indicated from the network topological and evolutionary perspectives. In addition, we find that the assortativity coefficient can manifest the financial crises and therefore can serve as a good indicator of the financial market development. PMID:28145494

  14. Topological Characteristics of the Hong Kong Stock Market: A Test-based P-threshold Approach to Understanding Network Complexity.

    PubMed

    Xu, Ronghua; Wong, Wing-Keung; Chen, Guanrong; Huang, Shuo

    2017-02-01

    In this paper, we analyze the relationship among stock networks by focusing on the statistically reliable connectivity between financial time series, which accurately reflects the underlying pure stock structure. To do so, we firstly filter out the effect of market index on the correlations between paired stocks, and then take a t-test based P-threshold approach to lessening the complexity of the stock network based on the P values. We demonstrate the superiority of its performance in understanding network complexity by examining the Hong Kong stock market. By comparing with other filtering methods, we find that the P-threshold approach extracts purely and significantly correlated stock pairs, which reflect the well-defined hierarchical structure of the market. In analyzing the dynamic stock networks with fixed-size moving windows, our results show that three global financial crises, covered by the long-range time series, can be distinguishingly indicated from the network topological and evolutionary perspectives. In addition, we find that the assortativity coefficient can manifest the financial crises and therefore can serve as a good indicator of the financial market development.

  15. National Development Education Network: Framework Plan for the Period from 1 August 1986 to 1 August 1991.

    ERIC Educational Resources Information Center

    Hooghoff, Hans

    In 1982 the Netherlands National Institute for Curriculum Development (SLO), with the support of Parliament, devised the framework for the Development Education Project (EPOS). This project concerns a national development education network, which is to be supported for a new period, 1986 to 1991. EPOS is comprised of national organizations,…

  16. The use of dynamical networks to detect the hierarchical organization of financial market sectors

    NASA Astrophysics Data System (ADS)

    Di Matteo, T.; Pozzi, F.; Aste, T.

    2010-01-01

    Two kinds of filtered networks: minimum spanning trees (MSTs) and planar maximally filtered graphs (PMFGs) are constructed from dynamical correlations computed over a moving window. We study the evolution over time of both hierarchical and topological properties of these graphs in relation to market fluctuations. We verify that the dynamical PMFG preserves the same hierarchical structure as the dynamical MST, providing in addition a more significant and richer structure, a stronger robustness and dynamical stability. Central and peripheral stocks are differentiated by using a combination of different topological measures. We find stocks well connected and central; stocks well connected but peripheral; stocks poorly connected but central; stocks poorly connected and peripheral. It results that the Financial sector plays a central role in the entire system. The robustness, stability and persistence of these findings are verified by changing the time window and by performing the computations on different time periods. We discuss these results and the economic meaning of this hierarchical positioning.

  17. Networked Virtual Organizations: A Chance for Small and Medium Sized Enterprises on Global Markets

    NASA Astrophysics Data System (ADS)

    Cellary, Wojciech

    Networked Virtual Organizations (NVOs) are a right answer to challenges of globalized, diversified, and dynamic contemporary economy. NVOs need more than e-trade and outsourcing, namely, they need out-tasking and e-collaboration. To out-task, but retain control on the way a task is performed by an external partner, two integrations are required: (1) integration of computer management systems of enterprises cooperating within an NVO; and (2) integration of cooperating representatives of NVO member enterprises into a virtual team. NVOs provide a particular chance to Small and Medium size Enterprises (SMEs) to find their place on global markets and to play a significant role on them. Requirements for SMEs to be able to successfully join an NVO are analyzed in the paper.

  18. Three-dimensional conductive networks based on stacked SiO2@graphene frameworks for enhanced gas sensing.

    PubMed

    Huang, Da; Yang, Zhi; Li, Xiaolin; Zhang, Liling; Hu, Jing; Su, Yanjie; Hu, Nantao; Yin, Guilin; He, Dannong; Zhang, Yafei

    2017-01-07

    Graphene is an ideal candidate for gas sensing due to its excellent conductivity and large specific surface areas. However, it usually suffers from sheet stacking, which seriously debilitates its sensing performance. Herein, we demonstrate a three-dimensional conductive network based on stacked SiO2@graphene core-shell hybrid frameworks for enhanced gas sensing. SiO2 spheres are uniformly encapsulated by graphene oxide (GO) through an electrostatic self-assembly approach to form SiO2@GO core-shell hybrid frameworks, which are reduced through thermal annealing to establish three-dimensional (3D) conductive sensing networks. The SiO2 supported 3D conductive graphene frameworks reveal superior sensing performance to bare reduced graphene oxide (RGO) films, which can be attributed to their less agglomeration and larger surface area. The response value of the 3D framework based sensor for 50 ppm NH3 and 50 ppm NO2 increased 8 times and 5 times, respectively. Additionally, the sensing performance degradation caused by the stacking of the sensing materials is significantly suppressed because the graphene layers are separated by the SiO2 spheres. The sensing performance decays by 92% for the bare RGO films when the concentration of the sensing material increases 8 times, while there is only a decay of 25% for that of the SiO2@graphene core-shell hybrid frameworks. This work provides an insight into 3D frameworks of hybrid materials for effectively improving gas sensing performance.

  19. 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.

  20. 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

  1. A collaborative computing framework of cloud network and WBSN applied to fall detection and 3-D motion reconstruction.

    PubMed

    Lai, Chin-Feng; Chen, Min; Pan, Jeng-Shyang; Youn, Chan-Hyun; Chao, Han-Chieh

    2014-03-01

    As cloud computing and wireless body sensor network technologies become gradually developed, ubiquitous healthcare services prevent accidents instantly and effectively, as well as provides relevant information to reduce related processing time and cost. This study proposes a co-processing intermediary framework integrated cloud and wireless body sensor networks, which is mainly applied to fall detection and 3-D motion reconstruction. In this study, the main focuses includes distributed computing and resource allocation of processing sensing data over the computing architecture, network conditions and performance evaluation. Through this framework, the transmissions and computing time of sensing data are reduced to enhance overall performance for the services of fall events detection and 3-D motion reconstruction.

  2. A decision-making framework to model environmental flow requirements in oasis areas using Bayesian networks

    NASA Astrophysics Data System (ADS)

    Xue, Jie; Gui, Dongwei; Zhao, Ying; Lei, Jiaqiang; Zeng, Fanjiang; Feng, Xinlong; Mao, Donglei; Shareef, Muhammad

    2016-09-01

    The competition for water resources between agricultural and natural oasis ecosystems has become an increasingly serious problem in oasis areas worldwide. Recently, the intensive extension of oasis farmland has led to excessive exploitation of water discharge, and consequently has resulted in a lack of water supply in natural oasis. To coordinate the conflicts, this paper provides a decision-making framework for modeling environmental flows in oasis areas using Bayesian networks (BNs). Three components are included in the framework: (1) assessment of agricultural economic loss due to meeting environmental flow requirements; (2) decision-making analysis using BNs; and (3) environmental flow decision-making under different water management scenarios. The decision-making criterion is determined based on intersection point analysis between the probability of large-level total agro-economic loss and the ratio of total to maximum agro-economic output by satisfying environmental flows. An application in the Qira oasis area of the Tarim Basin, Northwest China indicates that BNs can model environmental flow decision-making associated with agricultural economic loss effectively, as a powerful tool to coordinate water-use conflicts. In the case study, the environmental flow requirement is determined as 50.24%, 49.71% and 48.73% of the natural river flow in wet, normal and dry years, respectively. Without further agricultural economic loss, 1.93%, 0.66% and 0.43% of more river discharge can be allocated to eco-environmental water demands under the combined strategy in wet, normal and dry years, respectively. This work provides a valuable reference for environmental flow decision-making in any oasis area worldwide.

  3. 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

  4. 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

    2015-06-12

    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.

  5. Sensor network based solar forecasting using a local vector autoregressive ridge framework

    SciTech Connect

    Xu, J.; Yoo, S.; Heiser, J.; Kalb, P.

    2016-04-04

    The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations due to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.

  6. 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.

  7. 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.

  8. 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

    2016-03-04

    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.

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

    NASA Astrophysics Data System (ADS)

    Grunberg, Marc; Lambotte, Sophie; Engels, Fabien; Dretzen, Remi; Hernandez, Alain

    2014-05-01

    In the framework of the RESIF (Réseau Sismologique et géodésique Français) project, a new information system is being setting up, allowing the improvement of the management and the distribution of high quality data from the different elements of RESIF and the associated networks. 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) in order 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 first 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 subprocesses to check the consistency of the whole system and process from the stations to the data center. This allows us to verify that instruments and data transmission are operating correctly. Moreover analysis of the ambient noise helps to characterize intrinsic seismic quality of the stations and to identify other kind of disturbances. The deployed Quality Control consist in a pipeline that starts with low-level procedures : check the real-time miniseed data file (file naming convention, data integrity), check for inconsistencies between waveform and meta-data (channel name, sample rate, etc.), compute waveform statistics (data availability, gap/overlap, mean, rms, time quality, spike). It is followed by some high-level procedures such as : power spectral density computation (PSD), STA/LTA computation to be correlated to the seismicity, phases picking and stations magnitudes

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

    NASA Astrophysics Data System (ADS)

    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.

  11. 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.

  12. 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.

  13. The DELTA Network Study of Distributed Automated Post-Market Cardiovascular Device Safety Surveillance

    PubMed Central

    Kumar, Amit; Matheny, Michael E.; Ho, Kalon K.L.; Yeh, Robert W.; Piemonte, Thomas C.; Waldman, Howard; Shah, Pinak B.; Cope, Richard; Normand, Sharon-Lise; Donnelly, Sharon; Robbins, Susan; Resnic, Frederic S.

    2016-01-01

    Background Current approaches for post-market medical device safety surveillance are limited in their ability to produce timely and accurate assessments of adverse event rates. Methods and Results The DELTA (Data Extraction and Longitudinal Trend Analysis) network study was a multicenter prospective observational study designed to evaluate the safety of devices used during percutaneous coronary interventions (PCI). All adult patients undergoing PCI from January 2008 through December 2012 at five participating Massachusetts sites were included. A safety alert was triggered if the cumulative observed adverse event rates for the study device exceeded the upper 95% confidence interval of the event rates of propensity-matched control cohort. Pre-specified sensitivity analyses were developed to validate any identified safety signal. A total of 23,805 consecutive PCI procedures were evaluated. Two out of 24 safety analyses triggered safety alerts. Patients receiving Perclose vascular closure device (VCD) experienced an increased risk of minor vascular complications (relative risk [RR] 4.14; p <0.01) and any vascular complication (RR: 2.06; p = 0.01) as compared with propensity-matched patients receiving alternative VCD; a result primarily driven by relatively high event rates at one participating center. Sensitivity analyses based on alternative risk adjustment methods confirmed the a pattern of increased rate of complications at one of the five participating sites in their use of Perclose VCD. Conclusions The DELTA network study demonstrates that distributed automated prospective safety surveillance has the potential of providing near real-time assessment of safety risks of newly approved medical devices. PMID:25491915

  14. A peri-motor framework reveals functional segmentation in the motoneuronal network controlling locomotion in Caenorhabditis elegans

    PubMed Central

    Haspel, Gal; O'Donovan, Michael J

    2011-01-01

    The neuronal connectivity dataset of the nematode Caenorhabditis elegans attracts wide attention from computational neuroscientists and experimentalists. However, the dataset is incomplete. The ventral and dorsal nerve cords of a single nematode were reconstructed halfway along the body and the posterior data is missing, leaving 21 of 75 motoneurons of the locomotor network with partial or no connectivity data. Using a new framework for network analysis, the peri-motor space, we identified rules of connectivity that allowed us to approximate the missing data by extrapolation. Motoneurons were mapped into peri-motor space in which each motoneuron is located according to the muscle cells it innervates. In this framework, a pattern of iterative connections emerges which includes most (0.90) of the connections. We identified a repeating unit consisting of 12 motoneurons and 12 muscle cells. The cell bodies of the motoneurons of such a unit are not necessarily anatomical neighbors and there is no obvious anatomical segmentation. A connectivity model, comprised of six repeating units, is a description of the network that is both simplified (modular and without non-iterative connections) and more complete (includes the posterior part) than the original dataset. The peri-motor framework of observed connectivity and the segmented connectivity model give insights and advance the study of the neuronal infrastructure underlying locomotion in C. elegans. Furthermore, we suggest that the tools used herein may be useful to interpret, simplify and represent connectivity data of other motor systems. PMID:21994377

  15. 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

  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. 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…

  18. A Framework for the Management of Evolving Requirements in Software Systems Supporting Network-Centric Warfare

    DTIC Science & Technology

    2006-06-01

    NCW environment must be supported by new, innovative networked communication technologies. There are many sources of requirements for these software...support network-centric operations (NCO) in the NCW environment must be supported by new, innovative networked communication technologies. There... communication technologies. These technologies may be modifications to fully developed legacy software systems that are programs of record (POR). They

  19. 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…

  20. 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

  1. A theoretical framework for understanding river networks: Connecting process, geometry and topology across many scales

    NASA Astrophysics Data System (ADS)

    Veitzer, Seth Andrew

    A new class of models with statistically self-similar network topology is proposed for the modeling of river networks. The network construction process exhibits both topological variability and scale invariance in a statistical sense. The network construction model allows for a derivation of generalized Horton laws in terms of simple scaling of probability distributions in the limit of large Strahler order, representing a reformulation of traditional Horton laws which are defined only in terms of averages. Properties of networks constructed by the random self-similar model are evaluated. An analytic algorithm is introduced which generates width functions, an important network property that connects network structure to hydrologic basin response, based on a new procedure called braided convolution in the deterministic limit. The braided convolution algorithm is a powerful tool, in that it can recursively generate both smooth and multifractal width functions, and may have wider applications in the fields of data analysis, turbulence, and signal processing. Tests are made to determine the possible multifractal nature of both simulated and real width functions. Increasing and decreasing trends inherent to width functions mask any underlying singularity structure, producing inconclusive results using the standard tools of multifractal analysis. Scaling properties of the maximum of the width function are calculated in terms of the braided convolution algorithm for deterministically generated networks, and by ensemble simulation for random networks. The scaling properties of the maximum of the width function compare favorably to real networks for a large variety of parameterizations, both for topological and psuedo-geometric width functions. In addition distributions of the maximum of the width function as indexed by Strahler order are shown to exhibit generalized Horton laws both in simulation and in data. This represents a fundamentally new way to think about the

  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.

  3. System, environmental, and policy changes: using the social-ecological model as a framework for evaluating nutrition education and social marketing programs with low-income audiences.

    PubMed

    Gregson, J; Foerster, S B; Orr, R; Jones, L; Benedict, J; Clarke, B; Hersey, J; Lewis, J; Zotz, A K

    2001-01-01

    A variety of nutrition education interventions and social marketing initiatives are being used by the Food Stamp Program to improve food resource management, food safety, dietary quality, and food security for low-income households. The Social-Ecological Model is proposed as a theory-based framework to characterize the nature and results of interventions conducted through large public/private partnerships with the Food Stamp Program. In particular, this article suggests indicators and measures that lend themselves to the pooling of data across counties and states, with special emphasis on systems, environment, and public policy change within organizations at the community and state levels.

  4. Optimising value and quality in general practice within the primary health care sector through relationship marketing: a conceptual framework.

    PubMed

    Bansal, Manjit K

    2004-01-01

    Discusses the rationale of applying relationship marketing and service quality concepts within the primary health care sector. The use of relational strategies in general practice, by modelling the relationships between practitioners and patients from a marketing perspective, could potentially lead to sustained high quality service being provided, and to more efficient use of resources. This essentially conceptually focused paper addresses an area that has not yet been researched in detail, and furthers understanding of the relationships that facilitate exchange within general practice and service delivery in non-profit, resource-constrained conditions. Deeper understanding of the needs and expectations of patients and the way these can be delivered by general practice can only lead to improvements for all parties involved. The relationship marketing paradigm presents itself as a potentially exciting way of addressing issues associated with ensuring that the highest level of quality is delivered in this area of the UK National Health Service.

  5. Dynamic spanning trees in stock market networks: The case of Asia-Pacific

    NASA Astrophysics Data System (ADS)

    Sensoy, Ahmet; Tabak, Benjamin M.

    2014-11-01

    This article proposes a new procedure to evaluate Asia Pacific stock market interconnections using a dynamic setting. Dynamic spanning trees (DST) are constructed using an ARMA-FIEGARCH-cDCC process. The main results show that: 1. the DST significantly shrinks over time; 2. Hong Kong is found to be the key financial market; 3. the DST has a significantly increased stability in the last few years; 4. the removal of the key player has two effects: there is no clear key market any longer and the stability of the DST significantly decreases. These results are important for the design of policies that help develop stock markets and for academics and practitioners.

  6. 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.

  7. 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…

  8. "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…

  9. 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…

  10. 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…

  11. 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…

  12. Using Natural Language Processing and Network Analysis to Develop a Conceptual Framework for Medication Therapy Management Research.

    PubMed

    Ogallo, William; Kanter, Andrew S

    2016-01-01

    This paper describes a theory derivation process used to develop a conceptual framework for medication therapy management (MTM) research. The MTM service model and chronic care model were selected as parent theories. Review article abstracts targeting medication therapy management in chronic disease care were retrieved from Ovid Medline (2000-2016). Unique concepts in each abstract were extracted using MetaMap and their pairwise cooccurrence determined. The information was used to construct a network graph of concept co-occurrence that was analyzed to identify content for the new conceptual model. 142 abstracts were analyzed. Medication adherence is the most studied drug therapy problem and co-occurred with concepts related to patient-centered interventions targeting self-management. The enhanced model consists of 65 concepts clustered into 14 constructs. The framework requires additional refinement and evaluation to determine its relevance and applicability across a broad audience including underserved settings.

  13. Using Natural Language Processing and Network Analysis to Develop a Conceptual Framework for Medication Therapy Management Research

    PubMed Central

    Ogallo, William; Kanter, Andrew S.

    2016-01-01

    This paper describes a theory derivation process used to develop a conceptual framework for medication therapy management (MTM) research. The MTM service model and chronic care model were selected as parent theories. Review article abstracts targeting medication therapy management in chronic disease care were retrieved from Ovid Medline (2000-2016). Unique concepts in each abstract were extracted using MetaMap and their pairwise cooccurrence determined. The information was used to construct a network graph of concept co-occurrence that was analyzed to identify content for the new conceptual model. 142 abstracts were analyzed. Medication adherence is the most studied drug therapy problem and co-occurred with concepts related to patient-centered interventions targeting self-management. The enhanced model consists of 65 concepts clustered into 14 constructs. The framework requires additional refinement and evaluation to determine its relevance and applicability across a broad audience including underserved settings. PMID:28269895

  14. Quincy Market. [A Product of] the Regional Math Network: A Teacher Invigoration and Curriculum Development Project.

    ERIC Educational Resources Information Center

    Harvard Univ., Cambridge, MA. Graduate School of Education.

    In this middle school mathematics unit two imaginary characters, Horatio and Portia, decide to make their fortune in Quincy Market (Boston, Massachusetts) running a Bull Market cart. In order to solve the problems that they encounter, they need to learn ratio and proportion, map reading, estimation, area and perimeter, population sampling, problem…

  15. Increasing revenue through idea generation at University Health Network.

    PubMed

    Alcia, Lisa

    2013-01-01

    To enhance products and services provided to researchers and generate external revenue, research operations at the University Health Network implemented an ideation revenue generation framework for evaluation of product ideas for launch to external market. The framework consists of coordinated cross-functional teamwork in idea development and formal evaluation by research operations senior management based on standard criteria. The framework accelerates launch to market of products and services, facilitates due diligence review, increases staff competencies and engagement, and helps foster innovative thinking.

  16. A new optimization framework using genetic algorithm and artificial neural network to reduce uncertainties in petroleum reservoir models

    NASA Astrophysics Data System (ADS)

    Maschio, Célio; José Schiozer, Denis

    2015-01-01

    In this article, a new optimization framework to reduce uncertainties in petroleum reservoir attributes using artificial intelligence techniques (neural network and genetic algorithm) is proposed. Instead of using the deterministic values of the reservoir properties, as in a conventional process, the parameters of the probability density function of each uncertain attribute are set as design variables in an optimization process using a genetic algorithm. The objective function (OF) is based on the misfit of a set of models, sampled from the probability density function, and a symmetry factor (which represents the distribution of curves around the history) is used as weight in the OF. Artificial neural networks are trained to represent the production curves of each well and the proxy models generated are used to evaluate the OF in the optimization process. The proposed method was applied to a reservoir with 16 uncertain attributes and promising results were obtained.

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

    DOE PAGES

    Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

    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

  18. 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.

  19. Environmental technologies industry and global markets. A supplement to environmental technologies export: Strategic framework for US leadership. Export trade information

    SciTech Connect

    Not Available

    1994-04-01

    The present report outlines the background and issues supporting the national strategy which was developed to deploy U.S. Government resources most effectively to increase environmental technologies exports and to enhance the trade competitiveness of the U.S. environmental technologies sector. The document is a supplement to the strategic framework.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. NUDTSNA at TREC 2015 Microblog Track: A Live Retrieval System Framework for Social Network based on Semantic Expansion and Quality Model

    DTIC Science & Technology

    2015-11-20

    NUDTSNA at TREC 2015 Microblog Track: A Live Retrieval System Framework for Social Network based on Semantic Expansion and Quality Model Xiang Zhu...attracted increasing attention with develop- ment of social network services. To explore user’s interests and boost retrieval and recommendation...classified into a topic are ranked by our key word bool logistic model. 1. Introduction Information retrieval and recommendation in online so- cial network has

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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…

  10. CGLX: a scalable, high-performance visualization framework for networked display environments.

    PubMed

    Doerr, Kai-Uwe; Kuester, Falko

    2011-03-01

    The Cross Platform Cluster Graphics Library (CGLX) is a flexible and transparent OpenGL-based graphics framework for distributed, high-performance visualization systems. CGLX allows OpenGL based applications to utilize massively scalable visualization clusters such as multiprojector or high-resolution tiled display environments and to maximize the achievable performance and resolution. The framework features a programming interface for hardware-accelerated rendering of OpenGL applications on visualization clusters, mimicking a GLUT-like (OpenGL-Utility-Toolkit) interface to enable smooth translation of single-node applications to distributed parallel rendering applications. CGLX provides a unified, scalable, distributed OpenGL context to the user by intercepting and manipulating certain OpenGL directives. CGLX's interception mechanism, in combination with the core functionality for users to register callbacks, enables this framework to manage a visualization grid without additional implementation requirements to the user. Although CGLX grants access to its core engine, allowing users to change its default behavior, general development can occur in the context of a standalone desktop. The framework provides an easy-to-use graphical user interface (GUI) and tools to test, setup, and configure a visualization cluster. This paper describes CGLX's architecture, tools, and systems components. We present performance and scalability tests with different types of applications, and we compare the results with a Chromium-based approach.

  11. 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…

  12. 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…

  13. Development of an evaluation framework for publicly funded R&D projects: The case of Korea's Next Generation Network.

    PubMed

    Kim, Eungdo; Kim, Soyoung; Kim, Hongbum

    2017-02-28

    For decades, efforts have been made globally to measure the performance of large-scale public projects and to develop a framework to perform such measurements due to the complexity and dynamics of R&D and stakeholder interests. Still, limitations such as the use of a simply modified model and the lack of a comprehensive viewpoint are prevalent in existing approaches. In light of these research gaps, this study suggests a practical model to evaluate the performance of large-scale and publicly funded projects. The proposed model suggests a standard matrix framework of indices that evaluates the performance of particular elements in an industrial ecosystem in vertical categories and the economic and technological outcomes of those elements in horizontal categories. Based on the application of a balanced scorecard, this study uses mixed methodologies such as social network analysis, inter-industry analysis, and the analytic hierarchy process. Finally, the model evaluates the performance of Korea's Next Generation Network project as a case study.

  14. 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.

  15. Markov Task Network: A Framework for Service Composition under Uncertainty in Cyber-Physical Systems.

    PubMed

    Mohammed, Abdul-Wahid; Xu, Yang; Hu, Haixiao; Agyemang, Brighter

    2016-09-21

    In novel collaborative systems, cooperative entities collaborate services to achieve local and global objectives. With the growing pervasiveness of cyber-physical systems, however, such collaboration is hampered by differences in the operations of the cyber and physical objects, and the need for the dynamic formation of collaborative functionality given high-level system goals has become practical. In this paper, we propose a cross-layer automation and management model for cyber-physical systems. This models the dynamic formation of collaborative services pursuing laid-down system goals as an ontology-oriented hierarchical task network. Ontological intelligence provides the semantic technology of this model, and through semantic reasoning, primitive tasks can be dynamically composed from high-level system goals. In dealing with uncertainty, we further propose a novel bridge between hierarchical task networks and Markov logic networks, called the Markov task network. This leverages the efficient inference algorithms of Markov logic networks to reduce both computational and inferential loads in task decomposition. From the results of our experiments, high-precision service composition under uncertainty can be achieved using this approach.

  16. Geophysical monitoring of a complex geologic framework: the multi-disciplinary sensor networks in Sicily (Italy)

    NASA Astrophysics Data System (ADS)

    Cantarero, M.; Di Prima, S.; Mattia, M.; Patanè, D.; Rossi, M.

    2012-04-01

    Since 2004 the Osservatorio Etneo INGV has begun a new approach to the geophysical monitoring of volcanic and seismic areas of Sicily (Italy) where the core is a new type of remote infrastructure able to efficiently accommodate different kinds of sensor. In particular our multi-parametric network is mainly focused on the monitoring of different geophysical parameters (seismic ground velocity and acceleration, infrasound and ground deformation GPS).The whole seismic network consists of 66 broad band digital stations, 19 analog stations, 13 accelerometric stations and 12 infrasonic stations, for a total of 110 stations while the Continuous GPS network consist of 80 stations. Every station is equipped with solar panels in order to satisfy the power requirements of the instruments and with satellite-based communication systems. In this work we show both the technical solutions of this integrated network and its main advantages, if compared with older kinds of remote stations. Moreover we show some examples of the more interesting scientific results achieved thank to this technologically advanced network.

  17. Markov Task Network: A Framework for Service Composition under Uncertainty in Cyber-Physical Systems

    PubMed Central

    Mohammed, Abdul-Wahid; Xu, Yang; Hu, Haixiao; Agyemang, Brighter

    2016-01-01

    In novel collaborative systems, cooperative entities collaborate services to achieve local and global objectives. With the growing pervasiveness of cyber-physical systems, however, such collaboration is hampered by differences in the operations of the cyber and physical objects, and the need for the dynamic formation of collaborative functionality given high-level system goals has become practical. In this paper, we propose a cross-layer automation and management model for cyber-physical systems. This models the dynamic formation of collaborative services pursuing laid-down system goals as an ontology-oriented hierarchical task network. Ontological intelligence provides the semantic technology of this model, and through semantic reasoning, primitive tasks can be dynamically composed from high-level system goals. In dealing with uncertainty, we further propose a novel bridge between hierarchical task networks and Markov logic networks, called the Markov task network. This leverages the efficient inference algorithms of Markov logic networks to reduce both computational and inferential loads in task decomposition. From the results of our experiments, high-precision service composition under uncertainty can be achieved using this approach. PMID:27657084

  18. Molecular tectonics of metal-organic frameworks (MOFs): a rational design strategy for unusual mixed-connected network topologies.

    PubMed

    Du, Miao; Zhang, Zhi-Hui; Tang, Liang-Fu; Wang, Xiu-Guang; Zhao, Xiao-Jun; Batten, Stuart R

    2007-01-01

    To systematically explore the higher-dimensional network structures with mixed connectivity, a series of two-dimensional (2D) and three-dimensional (3D) metal-organic frameworks (MOFs) with unusual (3,6)-connected net topologies are presented. These crystalline materials include [{[Mn(btza)2(H2O)2].2 H2O}n] (1), [{[Zn(btza)2(H2O)2].2 H2O}n] (2), [{[Cu(btza)2].H2O}n] (3), and [{[Cd(btza)2].3 H2O}n] (4), which have been successfully assembled through a predesigned three-connected organic component bis(1,2,4-triazol-1-yl)acetate (btza) with a variety of octahedral metal cores based on the modular synthetic methodology. The topological paradigms shown in this work cover the 2D CdCl2, 3D (4(2).6)2(4(4).6(2).8(7).10(2)), and pyrite (pyr) types. That is, when properly treated with the familiar first-row divalent metal ions, btza may perfectly furnish the coordination spheres for effective connectivity to result in diverse (3,6)-connected nets. Beyond this, a detailed analysis of network topology for all known 3D (3,6)-connected frameworks in both inorganic and inorganic-organic hybrid materials is described. Specific network connectivity of these MOFs indicates that the metal centers represent the most significant and alterable factor in structural assembly, although they show reliable and similar geometries. In this context, the combination of the distinct d10 AgI ion with btza in different solvents affords two isomorphous MOFs [{[Ag(btza)].glycol}n] (5) and [{[Ag(btza)]CH3OH}n] (6) with a binodal 4-connected 3D SrAl2 (sra) topology. The network structures of MOFs 1-3 and 5 turn out to be more complicated and interesting if one considers the hydrogen bonding between the host coordination frameworks and the intercalated solvent molecules. Furthermore, the role of the included solvents in the generation and stabilization of MOFs 1-6 is also investigated.

  19. 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

  20. 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.

  1. 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

  2. The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

    DOE PAGES

    Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

    2016-11-12

    Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operatemore » the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.« less

  3. The microeconomics of residential photovoltaics: Tariffs, network operation and maintenance, and ancillary services in distribution-level electricity markets

    SciTech Connect

    Boero, Riccardo; Backhaus, Scott N.; Edwards, Brian K.

    2016-11-12

    Here, we develop a microeconomic model of a distribution-level electricity market that takes explicit account of residential photovoltaics (PV) adoption. The model allows us to study the consequences of most tariffs on PV adoption and the consequences of increased residential PV adoption under the assumption of economic sustainability for electric utilities. We also validated the model using U.S. data and extend it to consider different pricing schemes for operation and maintenance costs of the distribution network and for ancillary services. Results show that net metering promotes more environmental benefits and social welfare than other tariffs. But, if costs to operate the distribution network increase, net metering will amplify the unequal distribution of surplus among households. In conclusion, maintaining the economic sustainability of electric utilities under net metering may become extremely difficult unless the uneven distribution of surplus is legitimated by environmental benefits.

  4. 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

  5. A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks.

    PubMed

    Lin, Yun; Wang, Chao; Wang, Jiaxing; Dou, Zheng

    2016-10-12

    Cognitive radio sensor networks are one of the kinds of application where cognitive techniques can be adopted and have many potential applications, challenges and future research trends. According to the research surveys, dynamic spectrum access is an important and necessary technology for future cognitive sensor networks. Traditional methods of dynamic spectrum access are based on spectrum holes and they have some drawbacks, such as low accessibility and high interruptibility, which negatively affect the transmission performance of the sensor networks. To address this problem, in this paper a new initialization mechanism is proposed to establish a communication link and set up a sensor network without adopting spectrum holes to convey control information. Specifically, firstly a transmission channel model for analyzing the maximum accessible capacity for three different polices in a fading environment is discussed. Secondly, a hybrid spectrum access algorithm based on a reinforcement learning model is proposed for the power allocation problem of both the transmission channel and the control channel. Finally, extensive simulations have been conducted and simulation results show that this new algorithm provides a significant improvement in terms of the tradeoff between the control channel reliability and the efficiency of the transmission channel.

  6. A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks

    PubMed Central

    Lin, Yun; Wang, Chao; Wang, Jiaxing; Dou, Zheng

    2016-01-01

    Cognitive radio sensor networks are one of the kinds of application where cognitive techniques can be adopted and have many potential applications, challenges and future research trends. According to the research surveys, dynamic spectrum access is an important and necessary technology for future cognitive sensor networks. Traditional methods of dynamic spectrum access are based on spectrum holes and they have some drawbacks, such as low accessibility and high interruptibility, which negatively affect the transmission performance of the sensor networks. To address this problem, in this paper a new initialization mechanism is proposed to establish a communication link and set up a sensor network without adopting spectrum holes to convey control information. Specifically, firstly a transmission channel model for analyzing the maximum accessible capacity for three different polices in a fading environment is discussed. Secondly, a hybrid spectrum access algorithm based on a reinforcement learning model is proposed for the power allocation problem of both the transmission channel and the control channel. Finally, extensive simulations have been conducted and simulation results show that this new algorithm provides a significant improvement in terms of the tradeoff between the control channel reliability and the efficiency of the transmission channel. PMID:27754316

  7. 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.

  8. A Decision Framework for Enhancing Mobile Ad Hoc Network Stability and Security

    DTIC Science & Technology

    2008-06-01

    views expressed in this thesis are those of the author and do not reflect the official policy or position of the Department of Defense or the U.S... THESIS STATEMENT...................................................................................5 D. CONTRIBUTIONS OF THIS RESEARCH...C. THESIS STATEMENT A MANET management process based on an ontological organization of network decision factors and device security characteristics

  9. "Living" Theory: A Pedagogical Framework for Process Support in Networked Learning

    ERIC Educational Resources Information Center

    Levy, Philipa

    2006-01-01

    This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the…

  10. 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 ...

  11. 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.

  12. Atmospheric mercury concentrations observed at ground-based monitoring sites globally distributed in the framework of the GMOS network

    NASA Astrophysics Data System (ADS)

    Sprovieri, Francesca; Pirrone, Nicola; Bencardino, Mariantonia; D'Amore, Francesco; Carbone, Francesco; Cinnirella, Sergio; Mannarino, Valentino; Landis, Matthew; Ebinghaus, Ralf; Weigelt, Andreas; Brunke, Ernst-Günther; Labuschagne, Casper; Martin, Lynwill; Munthe, John; Wängberg, Ingvar; Artaxo, Paulo; Morais, Fernando; Barbosa, Henrique de Melo Jorge; Brito, Joel; Cairns, Warren; Barbante, Carlo; Diéguez, María del Carmen; Garcia, Patricia Elizabeth; Dommergue, Aurélien; Angot, Helene; Magand, Olivier; Skov, Henrik; Horvat, Milena; Kotnik, Jože; Read, Katie Alana; Mendes Neves, Luis; Gawlik, Bernd Manfred; Sena, Fabrizio; Mashyanov, Nikolay; Obolkin, Vladimir; Wip, Dennis; Feng, Xin Bin; Zhang, Hui; Fu, Xuewu; Ramachandran, Ramesh; Cossa, Daniel; Knoery, Joël; Marusczak, Nicolas; Nerentorp, Michelle; Norstrom, Claus

    2016-09-01

    Long-term monitoring of data of ambient mercury (Hg) on a global scale to assess its emission, transport, atmospheric chemistry, and deposition processes is vital to understanding the impact of Hg pollution on the environment. The Global Mercury Observation System (GMOS) project was funded by the European Commission (http://www.gmos.eu) and started in November 2010 with the overall goal to develop a coordinated global observing system to monitor Hg on a global scale, including a large network of ground-based monitoring stations, ad hoc periodic oceanographic cruises and measurement flights in the lower and upper troposphere as well as in the lower stratosphere. To date, more than 40 ground-based monitoring sites constitute the global network covering many regions where little to no observational data were available before GMOS. This work presents atmospheric Hg concentrations recorded worldwide in the framework of the GMOS project (2010-2015), analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. Major findings highlighted in this paper include a clear gradient of Hg concentrations between the Northern and Southern hemispheres, confirming that the gradient observed is mostly driven by local and regional sources, which can be anthropogenic, natural or a combination of both.

  13. Building a multi-FPGA-based emulation framework to support networks-on-chip design and verification

    NASA Astrophysics Data System (ADS)

    Liu, Yangfan; Liu, Peng; Jiang, Yingtao; Yang, Mei; Wu, Kejun; Wang, Weidong; Yao, Qingdong

    2010-10-01

    In this article, we present a highly scalable, flexible hardware-based network-on-chip (NoC) emulation framework, through which NoCs built upon various types of network topologies, routing algorithms, switching protocols and flow control schemes can be explored, compared, and validated with injected or self-generated traffic from both real-life and synthetic applications. This high degree of scalability and flexibility is achieved due to the field programmable gate array (FPGA) design choices made at both functional and physical levels. At the functional level, a NoC system to be emulated can be partitioned into two parts: (i) the processing cores and (ii) the network. Each part is mapped onto a different FPGA so that when there is any change to be made to any one of these parts, only the corresponding FPGA needs to be reconfigured and the rest of the FPGAs will be left untouched. At the physical level, two levels of interconnects are adopted to mimic NoC on-chip communications: high bandwidth and low latency parallel on-board wires, and high-speed serial multigigabit transceivers available in FPGAs. The latter is particularly important as it helps the proposed NoC emulation platform scale well with the size increase of the NoCs.

  14. 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.

  15. The application of a marketing systems planning framework to design a ground-air medical transport service.

    PubMed

    Chasin, S; Schlacter, J; Shirley, C

    1986-01-01

    This article has examined the application of a marketing and community planning process to the development of a regional, complete patient transportation system. The model is designed to interface with a region whose existing Emergency Medical Service System is operating at the advanced Life Support (usually paramedic) level. It is suitable for regions whose existing ambulance (ground and air) services are in need of improvement and/or coordination, and specifically utilizes the concept of ownership and management by a hospital consortium. The model, as described, is sufficiently flexible to be usable in a variety of local and regional environments, where changes in the patient transportation system can enhance the quality and operations of emergency medical services.

  16. 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.

  17. A unified framework for the pareto law and Matthew effect using scale-free networks

    NASA Astrophysics Data System (ADS)

    Hu, M.-B.; Wang, W.-X.; Jiang, R.; Wu, Q.-S.; Wang, B.-H.; Wu, Y.-H.

    2006-09-01

    We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth P(m)˜m-(v+1) with 1.6 < v <2.0 (which is in agreement with that of U.S. or Japan). Particularly, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.

  18. A Matched Field Processing Framework for Coherent Detection Over Local and Regional Networks

    DTIC Science & Technology

    2011-06-01

    Northern Finland Seismological Network, FN) and to the University of Helsinki for data from the VRF and HEF stations (part of the Finnish seismograph...could contribute to a slight worsening of performance:  Whereas the ARCES array has central timing, the ARA0, HEF , VRF, and RNF stations are part of...various sites as could be included following the P-arrival at HEF (the closest station). No alignment of the waveforms was attempted and no tapering of

  19. Mapping, Awareness, and Virtualization Network Administrator Training Tool (MAVNATT) Architecture and Framework

    DTIC Science & Technology

    2015-06-01

    than Angry IP Scanner. Nmap is a command line tool, although a graphical user interface called Zenmap is available to simplify Nmap usability. Figure...instead of creating a full- fledged virtual machine. These containers do not have the overhead of a regular type-II hypervisor and are therefore extremely...because they closely relate to two MAVNATT functional areas -- mapping and virtualization. Network simulators can use both GUI and command line

  20. 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.

  1. A Framework for Understanding Collective Leadership: The Selective Utilization of Leader and Team Expertise within Networks

    DTIC Science & Technology

    2011-05-01

    sharing,  conflict  mgmt)  Leader Network    (e.g., connections  between actors, centrality,  boundary spanning)  Communication  (e.g., consultation...differences in relationships among team members, it can result in negative team outcomes such as team conflict , and decreased satisfaction and...group members indicates that it is positively related to group performance and may even reduce task and interpersonal conflict (Moye & Langfred

  2. A Framework for Network Visualisation (Un Cadre Pour la Visualisation des Reseaux)

    DTIC Science & Technology

    2010-02-01

    0945 Round Robin Introductions 1000 Vincent Taylor RTG-025 and the N/X 1015 Zack Jacobson Workshop Introduction – Social Network Analysis for...0930 Round Robin Introductions 0945 Vincent Taylor RTG025 and the N/X 1000 Zack Jacobson, Margaret Varga Workshop Introduction 1015 Coffee Break...1030 Information on local arrangements 1035 Round Robin Introductions 1055 Vincent Taylor Introduction to NATO IST-059 and the N/X 1105 Zack

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

    DOE PAGES

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; ...

    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

  4. 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.

  5. 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.

  6. Controlling market power and price spikes in electricity networks: Demand-side bidding

    PubMed Central

    Rassenti, Stephen J.; Smith, Vernon L.; Wilson, Bart J.

    2003-01-01

    In this article we report an experiment that examines how demand-side bidding can discipline generators in a market for electric power. First we develop a treatment without demand-side bidding; two large firms are allocated baseload and intermediate cost generators such that either firm might unilaterally withhold the capacity of its intermediate cost generators from the market to benefit from the supracompetitive prices that would result from only selling its baseload units. In a converse treatment, ownership of some of the intermediate cost generators is transferred from each of these firms to two other firms such that no one firm could unilaterally restrict output to spawn supracompetitive prices. Having established a well controlled data set with price spikes paralleling those observed in the naturally occurring economy, we also extend the design to include demand-side bidding. We find that demand-side bidding completely neutralizes the exercise of market power and eliminates price spikes even in the presence of structural market power. PMID:16576750

  7. Controlling market power and price spikes in electricity networks: Demand-side bidding.

    PubMed

    Rassenti, Stephen J; Smith, Vernon L; Wilson, Bart J

    2003-03-04

    In this article we report an experiment that examines how demand-side bidding can discipline generators in a market for electric power. First we develop a treatment without demand-side bidding; two large firms are allocated baseload and intermediate cost generators such that either firm might unilaterally withhold the capacity of its intermediate cost generators from the market to benefit from the supracompetitive prices that would result from only selling its baseload units. In a converse treatment, ownership of some of the intermediate cost generators is transferred from each of these firms to two other firms such that no one firm could unilaterally restrict output to spawn supracompetitive prices. Having established a well controlled data set with price spikes paralleling those observed in the naturally occurring economy, we also extend the design to include demand-side bidding. We find that demand-side bidding completely neutralizes the exercise of market power and eliminates price spikes even in the presence of structural market power.

  8. 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)

  9. 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

  10. 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

  11. A low-complexity medium access control framework for body sensor networks.

    PubMed

    Wang, Bo; Wang, Lei; Huang, Bang-Yu; Wu, Dan; Lin, Shao-Jie; Gu, Jia; Zhang, Yuan-Ting; Chen, Wei

    2009-01-01

    This paper proposed a low-complexity medium access control (MAC) protocol tailored for body sensor networks (BSN) applications. The MAC protocol was designated to handle collision avoidance by reducing the numbers of the overhead packets for handshake control within the BSN. We also suggested a novel message recovery mechanism for getting back the lost physiological information. The adaptive synchronization scheme we have implemented exploited the features of multiple data-rate and adjustable precision design to support differentiated healthcare applications. The MAC protocol was fully implemented using our BSN development platform. The experimental results suggested the improved MAC design was compact and energy-efficient.

  12. 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

  13. A computational framework to characterize and compare the geometry of coronary networks.

    PubMed

    Bulant, C A; Blanco, P J; Lima, T P; Assunção, A N; Liberato, G; Parga, J R; Ávila, L F R; Pereira, A C; Feijóo, R A; Lemos, P A

    2017-03-01

    This work presents a computational framework to perform a systematic and comprehensive assessment of the morphometry of coronary arteries from in vivo medical images. The methodology embraces image segmentation, arterial vessel representation, characterization and comparison, data storage, and finally analysis. Validation is performed using a sample of 48 patients. Data mining of morphometric information of several coronary arteries is presented. Results agree to medical reports in terms of basic geometric and anatomical variables. Concerning geometric descriptors, inter-artery and intra-artery correlations are studied. Data reported here can be useful for the construction and setup of blood flow models of the coronary circulation. Finally, as an application example, similarity criterion to assess vasculature likelihood based on geometric features is presented and used to test geometric similarity among sibling patients. Results indicate that likelihood, measured through geometric descriptors, is stronger between siblings compared with non-relative patients. Copyright © 2016 John Wiley & Sons, Ltd.

  14. An integrated mass spectrometric and computational framework for the analysis of protein interaction networks.

    PubMed

    Rinner, Oliver; Mueller, Lukas N; Hubálek, Martin; Müller, Markus; Gstaiger, Matthias; Aebersold, Ruedi

    2007-03-01

    Biological systems are controlled by protein complexes that associate into dynamic protein interaction networks. We describe a strategy that analyzes protein complexes through the integration of label-free, quantitative mass spectrometry and computational analysis. By evaluating peptide intensity profiles throughout the sequential dilution of samples, the MasterMap system identifies specific interaction partners, detects changes in the composition of protein complexes and reveals variations in the phosphorylation states of components of protein complexes. We use the complexes containing the human forkhead transcription factor FoxO3A to demonstrate the validity and performance of this technology. Our analysis identifies previously known and unknown interactions of FoxO3A with 14-3-3 proteins, in addition to identifying FoxO3A phosphorylation sites and detecting reduced 14-3-3 binding following inhibition of phosphoinositide-3 kinase. By improving specificity and sensitivity of interaction networks, assessing post-translational modifications and providing dynamic interaction profiles, the MasterMap system addresses several limitations of current approaches for protein complexes.

  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.

  16. A framework for UWB-based communication and location tracking systems for wireless sensor networks.

    PubMed

    Chóliz, Juan; Hernández, Angela; Valdovinos, Antonio

    2011-01-01

    Ultra wideband (UWB) radio technology is nowadays one of the most promising technologies for medium-short range communications. It has a wide range of applications including wireless sensor networks (WSN) with simultaneous data transmission and location tracking. The combination of location and data transmission is important in order to increase flexibility and reduce the cost and complexity of the system deployment. In this scenario, accuracy is not the only evaluation criteria, but also the amount of resources associated to the location service, as it has an impact not only on the location capacity of the system but also on the sensor data transmission capacity. Although several studies can be found in the literature addressing UWB-based localization, these studies mainly focus on distance estimation and position calculation algorithms. Practical aspects such as the design of the functional architecture, the procedure for the transmission of the associated information between the different elements of the system, and the need of tracking multiple terminals simultaneously in various application scenarios, are generally omitted. This paper provides a complete system level evaluation of a UWB-based communication and location system for Wireless Sensor Networks, including aspects such as UWB-based ranging, tracking algorithms, latency, target mobility and MAC layer design. With this purpose, a custom simulator has been developed, and results with real UWB equipment are presented too.

  17. 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

    2016-06-06

    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.

  18. 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.

  19. 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.

  20. Generic Learning-Based Ensemble Framework for Small Sample Size Face Recognition in Multi-Camera Networks.

    PubMed

    Zhang, Cuicui; Liang, Xuefeng; Matsuyama, Takashi

    2014-12-08

    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.

  1. 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.

  2. 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.

  3. To Supplement or Not to Supplement: A Metabolic Network Framework for Human Nutritional Supplements

    PubMed Central

    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

  4. Marketing in nursing organizations.

    PubMed

    Chambers, S B

    1989-05-01

    The purpose of chapter 3 is to provide a conceptual framework for understanding marketing. Although it is often considered to be, marketing is not really a new activity for nursing organizations. What is perhaps new to most nursing organizations is the conduct of marketing activities as a series of interrelated events that are part of a strategic marketing process. The increasingly volatile nursing environment requires a comprehensive approach to marketing. This chapter presents definitions of marketing, the marketing mix, the characteristics of nonprofit marketing, the relationship of strategic planning and strategic marketing, portfolio analysis, and a detailed description of the strategic marketing process. While this chapter focuses on marketing concepts, essential components, and presentation of the strategic marketing process, chapter 4 presents specific methods and techniques for implementing the strategic marketing process.

  5. 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…

  6. 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.

  7. Tle and Heet Research in South America in the Framework of Leona Collaborative Network

    NASA Astrophysics Data System (ADS)

    Sao Sabbas, F.

    2013-12-01

    South America is one of the most active thunderstorm regions of the world. About 20 years ago, it was discovered that thunderstorm electrical activity, in the form of lightning discharges, can excite Transient Luminous Events - TLEs in the upper atmosphere directly above it. More recently, measurements of High Energy Emissions from Thunderstorms - HEET from space revealed that they also produce high energy emissions. Up to date, six different field campaigns, between 2002 and 2012 have been successfully performed in Brazil to make TLE observations. More than 700 events, mainly sprites, have been recorded over thunderstorms in different places in South America during these campaigns. Given the high thunderstorm electrical activity in our region, it is expected to have an extremely high TLE occurrence rate as well as intense emission of TGFs, high energy electron beams, neutron beam, X-Rays, i.e. HEET in general. This paper will review the main results of the different TLE observations performed from Brazil up to date and the research on TLEs and HEET performed by the Atmospheric and Space Electrodynamical Coupling - ACATMOS group at INPE. It will introduce the LEONA: Transient Luminous Event and Thunderstorm High Energy Emission Collaborative Network in Latin America. The team unites scientists of research institutions from several countries to investigate TLEs, HEET and related phenomena. It will present the collaborative network of cameras that are already been installed in Brazil, Peru and Argentina for continuous remote observation of TLE, and the prospective installation of 21 optical observation sites in other locations in South America, as well as a neutron detector in southern Brazil. The LEONA project has been recently approved by the Brazilian research funding agency FAPESP. The Argentina sites will allow for combined collaborative studies of TLEs and HEET produced by thunderstorms in the Pampas region, where the most several thunderstorms in South America

  8. 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

  9. 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.

  10. A Framework for Fracture Network Formation in Overpressurised Impermeable Shale: Deformability Versus Diagenesis

    NASA Astrophysics Data System (ADS)

    Alevizos, Sotiris; Poulet, Thomas; Sari, Mustafa; Lesueur, Martin; Regenauer-Lieb, Klaus; Veveakis, Manolis

    2017-03-01

    Understanding the formation, geometry and fluid connectivity of nominally impermeable unconventional shale gas and oil reservoirs is crucial for safe unlocking of these vast energy resources. We present a recent discovery of volumetric instabilities of ductile materials that may explain why impermeable formations become permeable. Here, we present the fundamental mechanisms, the critical parameters and the applicability of the novel theory to unconventional reservoirs. We show that for a reservoir under compaction, there exist certain ambient and permeability conditions at which diagenetic (fluid-release) reactions may provoke channelling localisation instabilities. These channels are periodically interspersed in the matrix and represent areas where the excess fluid from the reaction is segregated at high velocity. We find that channelling instabilities are favoured from pore collapse features for extremely low-permeability formations and fluid-release diagenetic reactions, therefore providing a natural, periodic network of efficient fluid pathways in an otherwise impermeable matrix (i.e. fractures). Such an outcome is of extreme importance the for exploration and extraction phases of unconventional reservoirs.

  11. 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.

  12. Using multi-criteria analysis to explore non-market monetary values of water quality changes in the context of the Water Framework Directive.

    PubMed

    Martin-Ortega, Julia; Berbel, Julio

    2010-09-01

    The EU Water Framework Directive represents a major change in the management of water resources and sets ambitious ecological objectives for all European waters. In the Directive, the economic assessment of the non-market environmental benefits of water quality improvements plays a crucial role. Studies valuing these benefits are now appearing in the literature, applying stated preference valuation techniques. However, these techniques are often criticized for providing only narrow mono-criterion information to the decision-making process. The research presented here builds on a recent line of investigation that combines monetary stated preference tools, in this case a choice experiment, with multi-criteria analysis, in this case the Analytical Hierarchy Process (AHP). We argue that the AHP can contribute to a better understanding and interpretation of the choice experiment results by exploring the criteria involved in respondents' trade-off between the attributes. The AHP provides relevant insights for the application of use-based water quality ladders in the valuation of environmental benefits in the context of the WFD. Results also show the importance of the spatial dimension of preferences for water quality.

  13. Gray marketing of pharmaceuticals.

    PubMed

    Chaudhry, P E; Walsh, M G

    1995-01-01

    Pharmaceutical marketers in the European Union are constrained by regulated prices, opening up opportunities for gray marketers. The authors investigate the legal framework that regulates gray markets by summarizing and analyzing relevant European Court of Justice decisions that favor gray marketers and actually foster parallel trade. Before marketing managers can develop effective strategies in this marketplace, they must first understand the precedents of the legal system in which they will be operating.

  14. 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

    2016-04-21

    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.

  15. 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.

  16. 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.

  17. Acid-doped polymer nanofiber framework: Three-dimensional proton conductive network for high-performance fuel cells

    NASA Astrophysics Data System (ADS)

    Tanaka, Manabu; Takeda, Yasushi; Wakiya, Takeru; Wakamoto, Yuta; Harigaya, Kaori; Ito, Tatsunori; Tarao, Takashi; Kawakami, Hiroyoshi

    2017-02-01

    High-performance polymer electrolyte membranes (PEMs) with excellent proton conductivity, gas barrier property, and membrane stability are desired for future fuel cells. Here we report the development of PEMs based on our proposed new concept ;Nanofiber Framework (NfF).; The NfF composite membranes composed of phytic acid-doped polybenzimidazole nanofibers (PBINf) and Nafion matrix show higher proton conductivity than the recast-Nafion membrane without nanofibers. A series of analyses reveal the formation of three-dimensional network nanostructures to conduct protons and water effectively through acid-condensed layers at the interface of PBINf and Nafion matrix. In addition, the NfF composite membrane achieves high gas barrier property and distinguished membrane stability. The fuel cell performance by the NfF composite membrane, which enables ultra-thin membranes with their thickness less than 5 μm, is superior to that by the recast-Nafion membrane, especially at low relative humidity. Such NfF-based high-performance PEM will be accomplished not only by the Nafion matrix used in this study but also by other polymer electrolyte matrices for future PEFCs.

  18. 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.

  19. 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

  20. 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…

  1. Pharmaceutical Pricing and Market Access Outlook Europe 2010-HealthNetwork Communications' fourth annual conference. 24-25 March 2010, London, UK.

    PubMed

    Ogbighele, Erhimuvi

    2010-05-01

    The HealthNetwork Communications' Fourth Annual Conference on Pharmaceutical Pricing and Market Access Outlook Europe 2010, held in London, included topics covering the challenges facing the pharmaceutical industry, specifically related to pricing and reimbursement, and demonstrating the value of a pharmaceutical. This conference report highlights selected presentations on a global perspective on pricing and reimbursement, with an analysis of the specific, unique challenges in the six major markets, Europe, the US, Canada, Germany, the UK and Japan, and a discussion of the benefits of risk-sharing schemes.

  2. 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.

  3. The development of Sustainability Graduate Community (SGC) as a learning pathway for sustainability education - a framework for engineering programmes in Malaysia Technical Universities Network (MTUN)

    NASA Astrophysics Data System (ADS)

    Johan, Kartina; Mohd Turan, Faiz

    2016-11-01

    ‘Environmental and sustainability’ is one of the Program Outcome (PO) designated by the Board of Engineers Malaysia (BEM) as one of the accreditation program requirement. However, to-date the implementation of sustainability elements in engineering programme in the technical universities in Malaysia is within individual faculty's curriculum plan and lack of university-level structured learning pathway, which enable all students to have access to an education in sustainability across all disciplines. Sustainability Graduate Community (SGC) is a framework designed to provide a learning pathway in the curriculum of engineering programs to inculcate sustainability education among engineering graduates. This paper aims to study the required attributes in Sustainability Graduate Community (SGC) framework to produce graduates who are not just engineers but also skilful in sustainability competencies using Global Project Management (GPM) P5 Standard for Sustainability. The development of the conceptual framework is to provide a constructive teaching and learning plan for educators and policy makers to work on together in developing the Sustainability Graduates (SG), the new kind of graduates from Malaysia Technical Universities Network (MTUN) in Malaysia who are literate in sustainability practices. The framework also support the call for developing holistic students based on Malaysian Education Blueprint (Higher Education) and address the gap between the statuses of engineering qualification to the expected competencies from industries in Malaysia in particular by achieving the SG attributes outlined in the framework

  4. A Marketing Plan for Schools.

    ERIC Educational Resources Information Center

    Dembowski, Frederick; Biros, Janice

    1984-01-01

    A marketing model is described as a framework for applying major marketing management principles to public school business management and is illustrated with the case of a hypothetical district's use of the plan. (MJL)

  5. Internet marketing 401.

    PubMed

    Miller, Ryan J

    2010-11-01

    For facial plastic surgeons who are already realizing increased patient consultation requests from their online marketing efforts, the primary concern often becomes implementing additional tactics and strategies that can keep their online marketing fresh, relevant, and effective. This article creates a framework for evaluating advanced online marketing opportunities by analyzing each opportunity according to the variables of possible return, average cost to implement, probability of success, and implementation time. Within this framework, 11 distinct tactics are discussed, with special emphasis on the most common marketing needs and challenges of facial plastic surgery practices.

  6. Optimization of Network Topology in Computer-Aided Detection Schemes Using Phased Searching with NEAT in a Time-Scaled Framework.

    PubMed

    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.

  7. 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.

  8. Framework for waveband switching in multigranular optical networks: part I-multigranular cross-connect architectures [Invited

    NASA Astrophysics Data System (ADS)

    Cao, Xiaojun; Anand, Vishal; Qiao, Chunming

    2006-12-01

    Optical networks using wavelength-division multiplexing (WDM) are the foremost solution to the ever-increasing traffic in the Internet backbone. Rapid advances in WDM technology will enable each fiber to carry hundreds or even a thousand wavelengths (using dense-WDM, or DWDM, and ultra-DWDM) of traffic. This, coupled with worldwide fiber deployment, will bring about a tremendous increase in the size of the optical cross-connects, i.e., the number of ports of the wavelength switching elements. Waveband switching (WBS), wherein wavelengths are grouped into bands and switched as a single entity, can reduce the cost and control complexity of switching nodes by minimizing the port count. This paper presents a detailed study on recent advances and open research issues in WBS networks. In this study, we investigate in detail the architecture for various WBS cross-connects and compare them in terms of the number of ports and complexity and also in terms of how flexible they are in adjusting to dynamic traffic. We outline various techniques for grouping wavelengths into bands for the purpose of WBS and show how traditional wavelength routing is different from waveband routing and why techniques developed for wavelength-routed networks (WRNs) cannot be simply applied to WBS networks. We also outline how traffic grooming of subwavelength traffic can be done in WBS networks. In part II of this study [Cao , submitted to J. Opt. Netw.], we study the effect of wavelength conversion on the performance of WBS networks with reconfigurable MG-OXCs. We present an algorithm for waveband grouping in wavelength-convertible networks and evaluate its performance. We also investigate issues related to survivability in WBS networks and show how waveband and wavelength conversion can be used to recover from failures in WBS networks.

  9. 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.

  10. 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.

  11. Risk-based surveillance for avian influenza control along poultry market chains in South China: The value of social network analysis.

    PubMed

    Martin, Vincent; Zhou, Xiaoyan; Marshall, Edith; Jia, Beibei; Fusheng, Guo; FrancoDixon, Mary Ann; DeHaan, Nicoline; Pfeiffer, Dirk U; Soares Magalhães, Ricardo J; Gilbert, Marius

    2011-12-01

    Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.

  12. 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.

  13. 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

  14. [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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Supporting Multidisciplinary Networks through Relationality and a Critical Sense of Belonging: Three "Gardening Tools" and the "Relational Agency Framework"

    ERIC Educational Resources Information Center

    Duhn, Iris; Fleer, Marilyn; Harrison, Linda

    2016-01-01

    This article focuses on the "Relational Agency Framework" (RAF), an analytical tool developed for an Australian review and evaluation study of an early years' policy initiative. We explore Anne Edward's concepts of "relational expertise", "building common knowledge" and "relational agency" to explore how…

  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. The Development of an Instructional Model for a Basic Marketing Course, Using Jerome S. Bruner's Theory of Instruction as the Framework.

    ERIC Educational Resources Information Center

    Unger, Melvin J.

    1980-01-01

    A project was conducted to develop an instructional model for a course in basic marketing. Topics for the course were identified, a literature review was performed, and a strategy was developed. It was concluded that such a model would improve methods of teaching and curricular design. (CT)

  2. The development, design, testing, refinement, simulation and application of an evaluation framework for communities of practice and social-professional networks

    PubMed Central

    Braithwaite, Jeffrey; Westbrook, Johanna I; Ranmuthugala, Geetha; Cunningham, Frances; Plumb, Jennifer; Wiley, Janice; Ball, Dianne; Huckson, Sue; Hughes, Cliff; Johnston, Brian; Callen, Joanne; Creswick, Nerida; Georgiou, Andrew; Betbeder-Matibet, Luc; Debono, Deborah

    2009-01-01

    Background Communities of practice and social-professional networks are generally considered to enhance workplace experience and enable organizational success. However, despite the remarkable growth in interest in the role of collaborating structures in a range of industries, there is a paucity of empirical research to support this view. Nor is there a convincing model for their systematic evaluation, despite the significant potential benefits in answering the core question: how well do groups of professionals work together and how could they be organised to work together more effectively? This research project will produce a rigorous evaluation methodology and deliver supporting tools for the benefit of researchers, policymakers, practitioners and consumers within the health system and other sectors. Given the prevalence and importance of communities of practice and social networks, and the extent of investments in them, this project represents a scientific innovation of national and international significance. Methods and design Working in four conceptual phases the project will employ a combination of qualitative and quantitative methods to develop, design, field-test, refine and finalise an evaluation framework. Once available the framework will be used to evaluate simulated, and then later existing, health care communities of practice and social-professional networks to assess their effectiveness in achieving desired outcomes. Peak stakeholder groups have agreed to involve a wide range of members and participant organisations, and will facilitate access to various policy, managerial and clinical networks. Discussion Given its scope and size, the project represents a valuable opportunity to achieve breakthroughs at two levels; firstly, by introducing novel and innovative aims and methods into the social research process and, secondly, through the resulting evaluation framework and tools. We anticipate valuable outcomes in the improved understanding of

  3. 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.

  4. 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

  5. Design and implementation of a QoS measurement and monitoring framework for Diff-Serv network

    NASA Astrophysics Data System (ADS)

    Ge, Fei; Cao, Yang

    2004-04-01

    The QoS measurement and monitoring framework proposed for Diff-Serv consists of three conceptual modules, the QoS data acquisition agent, the Qos data correlating agent and the QoS data analysis agent. The Common Object Request Broker Architecture (CORBA) is used when implementing the frame. The constructing of the measurement package, the transmitting rule of active measurement packages and path measurement is studied. A abbreviated QoS data correlating and analyzing is introduced.

  6. Host-guest architectures with a surface confined imine covalent organic framework as two-dimensional host networks.

    PubMed

    Sun, Jiang; Zhou, Xin; Lei, Shengbin

    2016-07-05

    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.

  7. 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…

  8. 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

  9. Extensible Systems Dynamics Framework

    DTIC Science & Technology

    2008-04-01

    pedigree information across communities-of-interest and across network boundaries. 15. SUBJECT TERMS Ptolemy II, Systems Dynamics, PMESII, National...3 4.2 ADAPT THE PTOLEMY II FRAMEWORK TO ENSURE A WELL-SUITED MODELING...report of activities in the Extensible Systems Dynamics Framework project performed by the Ptolemy Project, University of California, Berkeley for

  10. Adaptive optimization as a design and management methodology for coal-mining enterprise in uncertain and volatile market environment - the conceptual framework

    NASA Astrophysics Data System (ADS)

    Mikhalchenko, V. V.; Rubanik, Yu T.

    2016-10-01

    The work is devoted to the problem of cost-effective adaptation of coal mines to the volatile and uncertain market conditions. Conceptually it can be achieved through alignment of the dynamic characteristics of the coal mining system and power spectrum of market demand for coal product. In practical terms, this ensures the viability and competitiveness of coal mines. Transformation of dynamic characteristics is to be done by changing the structure of production system as well as corporate, logistics and management processes. The proposed methods and algorithms of control are aimed at the development of the theoretical foundations of adaptive optimization as basic methodology for coal mine enterprise management in conditions of high variability and uncertainty of economic and natural environment. Implementation of the proposed methodology requires a revision of the basic principles of open coal mining enterprises design.

  11. 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.

  12. 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

  13. 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.

  14. Cluster behavior of a simple model in financial markets

    NASA Astrophysics Data System (ADS)

    Jiang, J.; Li, W.; Cai, X.

    2008-01-01

    We investigate the cluster behavior of financial markets within the framework of a model based on a scale-free network. In this model, a cluster is formed by connected agents that are in the same state. The cumulative distribution of clusters is found to be a power-law. We find that the probability distribution of the liquidity parameter, which measures the financial markets’ energy, is rather robust. Furthermore, the time series of the liquidity parameter have the characteristics of 1/f noise, which may indicate the fractal geometry of financial markets.

  15. 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

  16. From microporous regular frameworks to mesoporous materials with ultrahigh surface area: dynamic reorganization of porous polymer networks.

    PubMed

    Kuhn, Pierre; Forget, Aurélien; Su, Dangsheng; Thomas, Arne; Antonietti, Markus

    2008-10-08

    High surface area organic materials featuring both micro- and mesopores were synthesized under ionothermal conditions via the formation of polyaryltriazine networks. While the polytrimerization of nitriles in zinc chloride at 400 degrees C produces microporous polymers, higher reaction temperatures induce the formation of additional spherical mesopores with a narrow dispersity. The nitrogen-rich carbonaceous polymer materials thus obtained present surface areas and porosities up to 3300 m(2) g(-1) and 2.4 cm(3) g(-1), respectively. The key point of this synthesis relies on the occurrence of several high temperature polymerization reactions, where irreversible carbonization reactions coupled with the reversible trimerization of nitriles allow the reorganization of the dynamic triazine network. The ZnCl2 molten salt fulfills the requirement of a high temperature solvent, but is also required as catalyst. Thus, this dynamic polymerization system provides not only highly micro- and mesoporous materials, but also allows controlling the pore structure in amorphous organic materials.

  17. 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

  18. 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.

  19. 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.

  20. 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)

  1. Using Social Marketing Theory as a Framework for Understanding and Increasing HPV Vaccine Series Completion Among Hispanic Adolescents: A Qualitative Study.

    PubMed

    Roncancio, Angelica M; Ward, Kristy K; Carmack, Chakema C; Muñoz, Becky T; Cano, Miguel A; Cribbs, Felicity

    2017-02-01

    HPV vaccine series completion rates among adolescent Hispanic females and males (~39 and 21 %, respectively) are far below the Healthy People 80 % coverage goal. Completion of the 3-dose vaccine series is critical to reducing the incidence of HPV-associated cancers. This formative study applies social marketing theory to assess the needs and preferences of Hispanic mothers in order to guide the development of interventions to increase HPV vaccine completion. We conducted 51 in-depth interviews with Hispanic mothers of adolescents to identify the key concepts of social marketing theory (i.e., the four P's: product, price, place and promotion). Results suggest that a desire complete the vaccine series, vaccine reminders and preventing illnesses and protecting their children against illnesses and HPV all influence vaccination (product). The majority of Completed mothers did not experience barriers that prevented vaccine series completion and Initiated mothers perceived a lack of health insurance and the cost of the vaccine as potential barriers. Informational barriers were prevalent across both market segments (price). Clinics are important locations for deciding to complete the vaccine series (place). They are the preferred sources to obtain information about the HPV vaccine thus making them ideal locations to deliver intervention messages, followed by television, the child's school and brochures (promotion). Increasing HPV vaccine coverage among Hispanic adolescents will reduce the rates of HPV-associated cancers and the cervical cancer health disparity among Hispanic women. This research can inform the development of an intervention to increase HPV vaccine series completion in this population.

  2. 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

  3. 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.

  4. 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+.

  5. 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

  6. Global sensitivity analysis approach for input selection and system identification purposes--a new framework for feedforward neural networks.

    PubMed

    Fock, Eric

    2014-08-01

    A new algorithm for the selection of input variables of neural network is proposed. This new method, applied after the training stage, ranks the inputs according to their importance in the variance of the model output. The use of a global sensitivity analysis technique, extended Fourier amplitude sensitivity test, gives the total sensitivity index for each variable, which allows for the ranking and the removal of the less relevant inputs. Applied to some benchmarking problems in the field of features selection, the proposed approach shows good agreement in keeping the relevant variables. This new method is a useful tool for removing superfluous inputs and for system identification.

  7. Ensuring Support for Research and Quality Improvement (QI) Networks: Four Pillars of Sustainability-An Emerging Framework.

    PubMed

    Holve, Erin

    2013-01-01

    Multi-institutional research and quality improvement (QI) projects using electronic clinical data (ECD) hold great promise for improving quality of care and patient outcomes but typically require significant infrastructure investments both to initiate and maintain the project over its duration. Consequently, it is important for these projects to think holistically about sustainability to ensure their long-term success. Four "pillars" of sustainability are discussed based on the experiences of EDM Forum grantees and other research and QI networks. These include trust and value, governance, management, and financial and administrative support. Two "foundational considerations," adaptive capacity and policy levers, are also discussed.

  8. First steps in adaptation of an evidential network for data fusion in the framework of medical remote monitoring.

    PubMed

    Cavalcante, P A; Sehili, M A; Herbin, M; Istrate, D; Blanchard, F; Boudy, J; Dorizzi, B

    2012-01-01

    This paper presents a medical remote monitoring application which aims at detecting falls. The detection system is based on three modalities: a wearable sensor, infrared sensors and a sound analysis module. The sound analysis is presented briefly. The multimodal fusion is made using the Dempster Schaffer theory through Evidential Network. A first evaluation of the use of data mining techniques in order to extract blindly data representatives is proposed. These representatives are used to continuously increase the system performances. The system is evaluated on a local recorded data base.

  9. 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

    2013-11-27

    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.

  10. 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

  11. 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

  12. 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

  13. Marketing telehealth to align with strategy.

    PubMed

    Dansky, Kathryn H; Ajello, Jeffrey

    2005-01-01

    Telehealth is a twenty-first century solution to an old problem-how to deliver quality health services with shrinking resources. Telehealth enables healthcare providers to interact with and monitor patients remotely, thus adding value to service delivery models. On occasion, telehealth can substitute for live encounters, saving time and resources. Furthermore, as the geriatric population increases, telehealth will support independent living by supplementing the existing network of care. To be used most effectively, however, telehealth services must be carefully planned and executed. This study investigated management practices used to promote telehealth services, focusing on strategic goals for adopting telehealth. Interviews with senior managers from 19 home health agencies identified three strategic goals for adopting telehealth: (1) clinical excellence, (2) technological preeminence, and (3) cost containment. Organizational documents were analyzed to determine the extent to which the telehealth program was featured in marketing materials. Documents included the organization's brochure, newspaper ads and articles, and each home health agency's web site. Results showed that marketing practices vary widely but are correlated with motivations to adopt telehealth. The organizations with the highest marketing scores emphasize clinical excellence as a major reason for using telehealth, whereas those with the lowest marketing scores tend to focus on cost containment. Although this study focused on management practices in home health agencies, results are applicable to hospital and outpatient services as well as to other community-based programs. Using a strategic management framework, the authors offer recommendations to help organizations develop effective marketing approaches for telehealth programs.

  14. 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

  15. 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

  16. 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

  17. 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…

  18. 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.

  19. 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

  20. 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.

  1. Highly efficient nonprecious metal catalyst prepared with metal–organic framework in a continuous carbon nanofibrous network

    DOE PAGES

    Shui, Jianglan; Chen, Chen; Grabstanowicz, Lauren; ...

    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

  2. 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.

  3. 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.

  4. 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…

  5. 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

  6. 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…

  7. 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…

  8. 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.

  9. 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…

  10. 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.

  11. Distribution characteristics of stock market liquidity

    NASA Astrophysics Data System (ADS)

    Luo, Jiawen; Chen, Langnan; Liu, Hao

    2013-12-01

    We examine the distribution characteristics of stock market liquidity by employing the generalized additive models for location, scale and shape (GAMLSS) model and three-minute frequency data from Chinese stock markets. We find that the BCPE distribution within the GAMLSS framework fits the distributions of stock market liquidity well with the diagnosis test. We also find that the stock market index exhibits a significant impact on the distributions of stock market liquidity. The stock market liquidity usually exhibits a positive skewness, but a normal distribution at a low level of stock market index and a high-peak and fat-tail shape at a high level of stock market index.

  12. Localization and diagnosis framework for pediatric cataracts based on slit-lamp images using deep features of a convolutional neural network

    PubMed Central

    Zhang, Kai; Long, Erping; Cui, Jiangtao; Zhu, Mingmin; An, Yingying; Zhang, Jia; Liu, Zhenzhen; Lin, Zhuoling; Li, Xiaoyan; Chen, Jingjing; Cao, Qianzhong; Li, Jing; Wu, Xiaohang; Wang, Dongni

    2017-01-01

    Slit-lamp images play an essential role for diagnosis of pediatric cataracts. We present a computer vision-based framework for the automatic localization and diagnosis of slit-lamp images by identifying the lens region of interest (ROI) and employing a deep learning convolutional neural network (CNN). First, three grading degrees for slit-lamp images are proposed in conjunction with three leading ophthalmologists. The lens ROI is located in an automated manner in the original image using two successive applications of Candy detection and the Hough transform, which are cropped, resized to a fixed size and used to form pediatric cataract datasets. These datasets are fed into the CNN to extract high-level features and implement automatic classification and grading. To demonstrate the performance and effectiveness of the deep features extracted in the CNN, we investigate the features combined with support vector machine (SVM) and softmax classifier and compare these with the traditional representative methods. The qualitative and quantitative experimental results demonstrate that our proposed method offers exceptional mean accuracy, sensitivity and specificity: classification (97.07%, 97.28%, and 96.83%) and a three-degree grading area (89.02%, 86.63%, and 90.75%), density (92.68%, 91.05%, and 93.94%) and location (89.28%, 82.70%, and 93.08%). Finally, we developed and deployed a potential automatic diagnostic software for ophthalmologists and patients in clinical applications to implement the validated model. PMID:28306716

  13. A California generation capacity market

    SciTech Connect

    Conkling, R.L.

    1998-10-01

    California, overconfident with its new Power Exchange spot market, seems unaware that it could be afflicted by the same turmoil that bludgeoned the Midwest in June. An electricity capacity market should be put in place before crisis strikes. This article outlines a framework for adding an electricity capacity market in California. The new market would not create a new bureaucracy but would function within the state`s now operational PX and independent system operator (ISO) mechanisms. It would be an open market, in which capacity would be traded transparently, with freedom of entree for all willing sellers and all willing buyers.

  14. 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

  15. Dropped out or pushed out? Insurance market exit and provider market power in Medicare Advantage.

    PubMed

    Pelech, Daria

    2017-01-01

    This paper explores how provider and insurer market power affect which markets an insurer chooses to operate in. A 2011 policy change required that certain private insurance plans in Medicare form provider networks de novo; in response, insurers cancelled two-thirds of the affected plans. Using detailed data on pre-policy provider and insurer market structure, I compare markets where insurers built networks to those they exited. Overall, insurers in the most concentrated hospital and physician markets were 9 and 13 percentage points more likely to exit, respectively, than those in the least concentrated markets. Conversely, insurers with more market power were less likely to exit than those with less, and an insurer's market power had the largest effect on exit in concentrated hospital markets. These findings suggest that concentrated provider markets contribute to insurer exit and that insurers with less market power have more difficulty surviving in concentrated provider markets.

  16. Silver(I) nitrate complexes of three tetra­kis-thio­ether-substituted pyrazine ligands: metal–organic chain, network and framework structures

    PubMed Central

    Assoumatine, Tokouré; Stoeckli-Evans, Helen

    2017-01-01

    The reaction of the ligand 2,3,5,6-tetra­kis­[(methyl­sulfanyl)­meth­yl]pyrazine (L1) with silver(I) nitrate led to {[Ag(C12H20N2S4)](NO3)}n, (I), catena-poly[[silver(I)-μ-2,3,5,6-tetra­kis­[(methyl­sulfan­yl)meth­yl]pyrazine] nitrate], a compound with a metal–organic chain structure. The asymmetric unit is composed of two half ligands, located about inversion centres, with one ligand coordinating to the silver atoms in a bis-tridentate manner and the other in a bis-bidentate manner. The charge on the metal atom is compensated for by a free nitrate anion. Hence, the silver atom has a fivefold S3N2 coordination sphere. The reaction of the ligand 2,3,5,6-tetra­kis­[(phenyl­sulfanyl)­meth­yl]pyrazine (L2) with silver(I) nitrate, led to [Ag2(NO3)2(C32H28N2S4)]n, (II), poly[di-μ-nitrato-bis­{μ-2,3,5,6-tetra­kis­[(phenyl­sulfan­yl)meth­yl]pyrazine}disilver], a compound with a metal–organic network structure. The asymmetric unit is composed of half a ligand, located about an inversion centre, that coordinates to the silver atoms in a bis-tridentate manner. The nitrate anion coordinates to the silver atom in a bidentate/monodentate manner, bridging the silver atoms, which therefore have a sixfold S2NO3 coordination sphere. The reaction of the ligand 2,3,5,6-tetra­kis­[(pyridin-2-yl­sulfanyl)­meth­yl]pyrazine (L3) with silver(I) nitrate led to [Ag3(NO3)3(C28H24N6S4)]n, (III), poly[trinitrato{μ 6-2,3,5,6-tetra­kis[(pyri­din-2-ylsulfan­yl)meth­yl]pyrazine}­trisilver(I)], a compound with a metal–organic framework structure. The asymmetric unit is composed of half a ligand, located about an inversion centre, that coordinates to the silver atoms in a bis-tridentate manner. One pyridine N atom bridges the monomeric units, so forming a chain structure. Two nitrate O atoms also coordinate to this silver atom, hence it has a sixfold S2N2O2 coordination sphere. The chains are linked via a second silver atom, located on a twofold rotation axis

  17. Silver(I) nitrate complexes of three tetra-kis-thio-ether-substituted pyrazine ligands: metal-organic chain, network and framework structures.

    PubMed

    Assoumatine, Tokouré; Stoeckli-Evans, Helen

    2017-03-01

    The reaction of the ligand 2,3,5,6-tetra-kis-[(methyl-sulfanyl)-meth-yl]pyrazine (L1) with silver(I) nitrate led to {[Ag(C12H20N2S4)](NO3)} n , (I), catena-poly[[silver(I)-μ-2,3,5,6-tetra-kis-[(methyl-sulfan-yl)meth-yl]pyrazine] nitrate], a compound with a metal-organic chain structure. The asymmetric unit is composed of two half ligands, located about inversion centres, with one ligand coordinating to the silver atoms in a bis-tridentate manner and the other in a bis-bidentate manner. The charge on the metal atom is compensated for by a free nitrate anion. Hence, the silver atom has a fivefold S3N2 coordination sphere. The reaction of the ligand 2,3,5,6-tetra-kis-[(phenyl-sulfanyl)-meth-yl]pyrazine (L2) with silver(I) nitrate, led to [Ag2(NO3)2(C32H28N2S4)] n , (II), poly[di-μ-nitrato-bis-{μ-2,3,5,6-tetra-kis-[(phenyl-sulfan-yl)meth-yl]pyrazine}disilver], a compound with a metal-organic network structure. The asymmetric unit is composed of half a ligand, located about an inversion centre, that coordinates to the silver atoms in a bis-tridentate manner. The nitrate anion coordinates to the silver atom in a bidentate/monodentate manner, bridging the silver atoms, which therefore have a sixfold S2NO3 coordination sphere. The reaction of the ligand 2,3,5,6-tetra-kis-[(pyridin-2-yl-sulfanyl)-meth-yl]pyrazine (L3) with silver(I) nitrate led to [Ag3(NO3)3(C28H24N6S4)] n , (III), poly[trinitrato{μ6-2,3,5,6-tetra-kis[(pyri-din-2-ylsulfan-yl)meth-yl]pyrazine}-trisilver(I)], a compound with a metal-organic framework structure. The asymmetric unit is composed of half a ligand, located about an inversion centre, that coordinates to the silver atoms in a bis-tridentate manner. One pyridine N atom bridges the monomeric units, so forming a chain structure. Two nitrate O atoms also coordinate to this silver atom, hence it has a sixfold S2N2O2 coordination sphere. The chains are linked via a second silver atom, located on a twofold rotation axis, coordinated by the second

  18. How Philip Morris unlocked the Japanese cigarette market: lessons for global tobacco control

    PubMed Central

    Lambert, A; Sargent, J; Glantz, S; Ling, P

    2004-01-01

    Background: The Framework Convention on Tobacco Control includes tobacco advertising restrictions that are strongly opposed by the tobacco industry. Marketing strategies used by transnational tobacco companies to open the Japanese market in the absence of such restrictions are described. Methods: Analysis of internal company documents. Findings: Between 1982 and 1987 transnational tobacco companies influenced the Japanese government through the US Trade Representative to open distribution networks and eliminate advertising restrictions. US cigarette exports to Japan increased 10-fold between 1985 and 1996. Television advertising was central to opening the market by projecting a popular image (despite a small actual market share) to attract existing smokers, combined with hero-centred advertisements to attract new smokers. Philip Morris's campaigns featured Hollywood movie personalities popular with young men, including James Coburn, Pierce Brosnan, Roger Moore, and Charlie Sheen. Event sponsorships allowed television access despite restrictions. When reinstatement of television restrictions was threatened in the late 1980s, Philip Morris more than doubled its television advertising budget and increased sponsorship of televised events. By adopting voluntary advertising standards, transnational companies delayed a television advertising ban for over a decade. Conclusions: Television image advertising was important to establish a market, and it has been enhanced using Hollywood personalities. Television advertising bans are essential measures to prevent industry penetration of new markets, and are less effective without concurrent limits on sponsorship and promotion. Comprehensive advertising restrictions, as included in the Framework Convention for Tobacco Control, are vital for countries where transnational tobacco companies have yet to penetrate the market. PMID:15564622

  19. 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.

  20. 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…