Science.gov

Sample records for cobden-chevalier network 1860-1875

  1. 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)

  2. 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…

  3. A network of networks.

    PubMed

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

    2017-04-10

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

  4. Network cosmology.

    PubMed

    Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

    2012-01-01

    Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

  5. Network Cosmology

    PubMed Central

    Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

    2012-01-01

    Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

  6. Network Solutions.

    ERIC Educational Resources Information Center

    Vietzke, Robert; And Others

    1996-01-01

    This special section explains the latest developments in networking technologies, profiles school districts benefiting from successful implementations, and reviews new products for building networks. Highlights include ATM (asynchronous transfer mode), cable modems, networking switches, Internet screening software, file servers, network management…

  7. Network Kits.

    ERIC Educational Resources Information Center

    Falk, Howard

    1999-01-01

    Describes interconnection methods, speed, and comparative equipment costs of networking starter kits. These kits supply network-connection devices that plug into or connect to each computer that is part of a network; they may also provide interconnection cables and installation software needed to set up a network. Reviews 20 kits that use a…

  8. Networking standards

    NASA Technical Reports Server (NTRS)

    Davies, Mark

    1991-01-01

    The enterprise network is currently a multivendor environment consisting of many defacto and proprietary standards. During the 1990s, these networks will evolve towards networks which are based on international standards in both Local Area Network (LAN) and Wide Area Network (WAN) space. Also, you can expect to see the higher level functions and applications begin the same transition. Additional information is given in viewgraph form.

  9. Semantic Networks and Social Networks

    ERIC Educational Resources Information Center

    Downes, Stephen

    2005-01-01

    Purpose: To illustrate the need for social network metadata within semantic metadata. Design/methodology/approach: Surveys properties of social networks and the semantic web, suggests that social network analysis applies to semantic content, argues that semantic content is more searchable if social network metadata is merged with semantic web…

  10. Semantic Networks and Social Networks

    ERIC Educational Resources Information Center

    Downes, Stephen

    2005-01-01

    Purpose: To illustrate the need for social network metadata within semantic metadata. Design/methodology/approach: Surveys properties of social networks and the semantic web, suggests that social network analysis applies to semantic content, argues that semantic content is more searchable if social network metadata is merged with semantic web…

  11. Network neuroscience

    PubMed Central

    Bassett, Danielle S; Sporns, Olaf

    2017-01-01

    Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system. PMID:28230844

  12. Network Basics.

    ERIC Educational Resources Information Center

    Tennant, Roy

    1992-01-01

    Explains how users can find and access information resources available on the Internet. Highlights include network information centers (NICs); lists, both formal and informal; computer networking protocols, including international standards; electronic mail; remote log-in; and file transfer. (LRW)

  13. Network Basics.

    ERIC Educational Resources Information Center

    Tennant, Roy

    1992-01-01

    Explains how users can find and access information resources available on the Internet. Highlights include network information centers (NICs); lists, both formal and informal; computer networking protocols, including international standards; electronic mail; remote log-in; and file transfer. (LRW)

  14. Network neuroscience.

    PubMed

    Bassett, Danielle S; Sporns, Olaf

    2017-02-23

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

  15. Network science.

    PubMed

    Barabási, Albert-László

    2013-03-28

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

  16. Integrated Networks.

    ERIC Educational Resources Information Center

    Robinovitz, Stewart

    1987-01-01

    A strategy for integrated data and voice networks implemented at the University of Michigan is described. These networks often use multi-technologies, multi-vendors, and multi-transmission media that will be fused into a single integrated network. Transmission media include twisted-pair wire, coaxial cable, fiber optics, and microwave. (Author/MLW)

  17. Integrated Networks.

    ERIC Educational Resources Information Center

    Robinovitz, Stewart

    1987-01-01

    A strategy for integrated data and voice networks implemented at the University of Michigan is described. These networks often use multi-technologies, multi-vendors, and multi-transmission media that will be fused into a single integrated network. Transmission media include twisted-pair wire, coaxial cable, fiber optics, and microwave. (Author/MLW)

  18. Superelastic networks

    SciTech Connect

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

    1993-12-31

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

  19. Networking computers.

    PubMed

    McBride, D C

    1997-03-01

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

  20. Vulnerability of network of networks

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  1. Neural Networks

    DTIC Science & Technology

    1990-01-01

    FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO. ACCESSION NO 11 TITLE (Include Security Classification) NEURAL NETWORKS 12. PERSONAL...SUB-GROUP Neural Networks Optical Architectures Nonlinear Optics Adaptation 19. ABSTRACT (Continue on reverse if necessary and identify by block number...341i Y C-odes , lo iii/(iv blank) 1. INTRODUCTION Neural networks are a type of distributed processing system [1

  2. Network reliability

    NASA Technical Reports Server (NTRS)

    Johnson, Marjory J.

    1985-01-01

    Network control (or network management) functions are essential for efficient and reliable operation of a network. Some control functions are currently included as part of the Open System Interconnection model. For local area networks, it is widely recognized that there is a need for additional control functions, including fault isolation functions, monitoring functions, and configuration functions. These functions can be implemented in either a central or distributed manner. The Fiber Distributed Data Interface Medium Access Control and Station Management protocols provide an example of distributed implementation. Relative information is presented here in outline form.

  3. Innovation Networks

    NASA Astrophysics Data System (ADS)

    Pyka, Andreas; Scharnhorst, Andrea

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

  4. Cognitive Networks

    DTIC Science & Technology

    2007-06-15

    networks have the potential to change this trend by adding intelligence to the network. This work introduces the concept and provides a foundation for future ...of Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 7.2 Future Work...CRs) could interact within the system-level scope of a CN. Saracco [9] refers to CNs in his investigation into the future of information technology

  5. Network Flows

    DTIC Science & Technology

    1988-12-01

    Researchers have suggested other solution strategies, using ideas from nonlinear progamming for solving this general separable convex cost flow problems. Some...plane methods and branch and bound procedures of integer programming, primal-dual methods of linear and nonlinear programming, and polyhedral methods...Combinatorial Optimization: Networks and Matroids), Bazaraa and Jarvis [1978] (Linear Programming and Network Flows), Minieka [1978] (Optimization Algorithms for

  6. Temporal networks

    NASA Astrophysics Data System (ADS)

    Holme, Petter; Saramäki, Jari

    2012-10-01

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

  7. Technological Networks

    NASA Astrophysics Data System (ADS)

    Mitra, Bivas

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

  8. Innovation network

    PubMed Central

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

    2016-01-01

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

  9. Innovation network.

    PubMed

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

    2016-10-11

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

  10. Sentinel Network

    Cancer.gov

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

  11. Exchange Network

    EPA Pesticide Factsheets

    The Environmental Information Exchange Network (EIEN) is an Internet-based system used by state, tribal and territorial partners to securely share environmental and health information with one another and EPA.

  12. Developer Network

    SciTech Connect

    2012-08-21

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

  13. Sentient networks

    SciTech Connect

    Chapline, G.

    1998-03-01

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

  14. Neural Networks

    SciTech Connect

    Smith, Patrick I.

    2003-09-23

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  15. Network motif identification in stochastic networks

    NASA Astrophysics Data System (ADS)

    Jiang, Rui; Tu, Zhidong; Chen, Ting; Sun, Fengzhu

    2006-06-01

    Network motifs have been identified in a wide range of networks across many scientific disciplines and are suggested to be the basic building blocks of most complex networks. Nonetheless, many networks come with intrinsic and/or experimental uncertainties and should be treated as stochastic networks. The building blocks in these networks thus may also have stochastic properties. In this article, we study stochastic network motifs derived from families of mutually similar but not necessarily identical patterns of interconnections. We establish a finite mixture model for stochastic networks and develop an expectation-maximization algorithm for identifying stochastic network motifs. We apply this approach to the transcriptional regulatory networks of Escherichia coli and Saccharomyces cerevisiae, as well as the protein-protein interaction networks of seven species, and identify several stochastic network motifs that are consistent with current biological knowledge. expectation-maximization algorithm | mixture model | transcriptional regulatory network | protein-protein interaction network

  16. Metabolic Networks

    NASA Astrophysics Data System (ADS)

    Palumbo, Maria Concetta; Farina, Lorenzo; Colosimo, Alfredo; Giuliani, Alessandro

    The use of the term `network' is more and more widespread in all fields of biology. It evokes a systemic approach to biological problems able to overcome the evident limitations of the strict reductionism of the past twenty years. The expectations produced by taking into considerations not only the single elements but even the intermingled `web' of links connecting different parts of biological entities, are huge. Nevertheless, we believe that the lack of consciousness that networks, beside their biological `likelihood', are modeling tools and not real entities, could be detrimental to the exploitation of the full potential of this paradigm. Like any modeling tool the network paradigm has a range of application going from situations in which it is particularly fit to situations in which its application can be largely misleading. In this chapter we deal with an aspect of biological entities that is particularly fit for the network approach: the intermediate metabolism. This fit derives both from the existence of a privileged formalization in which the relative role of nodes (metabolites) and arches (enzymes) is immediately suggested by the system architecture. Here we will discuss some applications of both graph theory based analysis and multidimensional statistics method to metabolic network studies with the emphasis on the derivation of biologically meaningful information.

  17. Computer networks.

    PubMed

    Wear, L L; Pinkert, J R

    1993-10-01

    We have looked at several aspects of networks in this article. As you read about networks, and use them, we hope our discussions will help you understand some of the associated concepts and terms. For instance, suppose someone describes an Ethernet installation as a bus topology LAN using the 1-persistent CSMA/CD protocol with horizontal cables on each floor connected by repeaters to a vertical cable backbone running from the basement to the roof. You now have seen what that description implies. To close this article, we ask you to refer back to Figure 1. Our sample network transfer from Marie to Lars was described as being accomplished through a number of layers or steps, most of which were transparent to the users. Building upon the material presented in this article, we can now give you a more detailed illustration of those layers. Figure 13 shows the seven layers in network model defined by the International Standards Organization, ISO: application, presentation, session, transport, network, data link, and physical. We do not have space here to discuss each layer in detail, but Figure 13 does give a typical operation that is done in each layer.

  18. Network dismantling

    PubMed Central

    Braunstein, Alfredo; Dall’Asta, Luca; Semerjian, Guilhem; Zdeborová, Lenka

    2016-01-01

    We study the network dismantling problem, which consists of determining a minimal set of vertices in which removal leaves the network broken into connected components of subextensive size. For a large class of random graphs, this problem is tightly connected to the decycling problem (the removal of vertices, leaving the graph acyclic). Exploiting this connection and recent works on epidemic spreading, we present precise predictions for the minimal size of a dismantling set in a large random graph with a prescribed (light-tailed) degree distribution. Building on the statistical mechanics perspective, we propose a three-stage Min-Sum algorithm for efficiently dismantling networks, including heavy-tailed ones for which the dismantling and decycling problems are not equivalent. We also provide additional insights into the dismantling problem, concluding that it is an intrinsically collective problem and that optimal dismantling sets cannot be viewed as a collection of individually well-performing nodes. PMID:27791075

  19. Nuclear networking.

    PubMed

    Xie, Wei; Burke, Brian

    2017-07-04

    Nuclear lamins are intermediate filament proteins that represent important structural components of metazoan nuclear envelopes (NEs). By combining proteomics and superresolution microscopy, we recently reported that both A- and B-type nuclear lamins form spatially distinct filament networks at the nuclear periphery of mouse fibroblasts. In particular, A-type lamins exhibit differential association with nuclear pore complexes (NPCs). Our studies reveal that the nuclear lamina network in mammalian somatic cells is less ordered and more complex than that of amphibian oocytes, the only other system in which the lamina has been visualized at high resolution. In addition, the NPC component Tpr likely links NPCs to the A-type lamin network, an association that appears to be regulated by C-terminal modification of various A-type lamin isoforms. Many questions remain, however, concerning the structure and assembly of lamin filaments, as well as with their mode of association with other nuclear components such as peripheral chromatin.

  20. Rapid Network Design

    DTIC Science & Technology

    2013-09-01

    packet- switched networks are extremely prone to human design faults, which can adversely affect the reliability of the network. This thesis proposes an...network devices and create a functioning packet- switch network. network design , network topology, packet- switching networks, routing protocols, data... switched networks are extremely prone to human design faults, which can adversely affect the reliability of the network. This thesis proposes an

  1. Network Physiology: Mapping Interactions Between Networks of Physiologic Networks

    NASA Astrophysics Data System (ADS)

    Ivanov, Plamen Ch.; Bartsch, Ronny P.

    The human organism is an integrated network of interconnected and interacting organ systems, each representing a separate regulatory network. The behavior of one physiological system (network) may affect the dynamics of all other systems in the network of physiologic networks. Due to these interactions, failure of one system can trigger a cascade of failures throughout the entire network. We introduce a systematic method to identify a network of interactions between diverse physiologic organ systems, to quantify the hierarchical structure and dynamics of this network, and to track its evolution under different physiologic states. We find a robust relation between network structure and physiologic states: every state is characterized by specific network topology, node connectivity and links strength. Further, we find that transitions from one physiologic state to another trigger a markedly fast reorganization in the network of physiologic interactions on time scales of just a few minutes, indicating high network flexibility in response to perturbations. This reorganization in network topology occurs simultaneously and globally in the entire network as well as at the level of individual physiological systems, while preserving a hierarchical order in the strength of network links. Our findings highlight the need of an integrated network approach to understand physiologic function, since the framework we develop provides new information which can not be obtained by studying individual systems. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.

  2. Network Views

    ERIC Educational Resources Information Center

    Alexander, Louis

    2010-01-01

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

  3. Beyond Networking.

    ERIC Educational Resources Information Center

    Carmel, Michael

    1981-01-01

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

  4. Networked Resources.

    ERIC Educational Resources Information Center

    Nickerson, Gord

    1992-01-01

    The LISTSERV program on the BITNET computer network started as a simple mailing list program for electronic group communication. A revised version of LISTSERV now offers sophisticated new functions and help for users, including file-server functions. Problems with the revised version are noted, and computer commands are provided. (six references)…

  5. Resistive Networks.

    ERIC Educational Resources Information Center

    Balabanian, Norman

    This programed text on resistive networks was developed under contract with the United States Office of Education as part of a series of materials for use in an electrical engineering sequence. It is to be used in conjunction with other materials and with other short texts in the series, this one being Number 3. (DH)

  6. Knowledge Networks

    ERIC Educational Resources Information Center

    McLeod, Scott

    2008-01-01

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

  7. Gradient networks

    NASA Astrophysics Data System (ADS)

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

    2008-04-01

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

  8. Network Views

    ERIC Educational Resources Information Center

    Alexander, Louis

    2010-01-01

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

  9. Global Networking.

    ERIC Educational Resources Information Center

    Lynch, Clifford

    1997-01-01

    Discusses the state of the Internet. Highlights include the magnitude of the infrastructure, costs, its increasing pace, constraints in international links, provision of network capacity to homes and small businesses, cable television modems, political and cultural problems, the digital library concept, search engines, the failure of personal…

  10. Neural Networks

    NASA Astrophysics Data System (ADS)

    Schwindling, Jerome

    2010-04-01

    This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p.) corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  11. Network gravity

    NASA Astrophysics Data System (ADS)

    Lombard, John

    2017-01-01

    We introduce the construction of a new framework for probing discrete emergent geometry and boundary-boundary observables based on a fundamentally a-dimensional underlying network structure. Using a gravitationally motivated action with Forman weighted combinatorial curvatures and simplicial volumes relying on a decomposition of an abstract simplicial complex into realized embeddings of proper skeletons, we demonstrate properties such as a minimal volume-scale cutoff, the necessity of a term playing the role of a positive definite cosmological constant as a regulator for nondegenerate geometries, and naturally emergent simplicial structures from Metropolis network evolution simulations with no restrictions on attachment rules or regular building blocks. We see emergent properties which echo results from both the spinfoam formalism and causal dynamical triangulations in quantum gravity, and provide analytical and numerical results to support the analogy. We conclude with a summary of open questions and intent for future work in developing the program.

  12. Modeling the citation network by network cosmology.

    PubMed

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

    2015-01-01

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

  13. Modeling the Citation Network by Network Cosmology

    PubMed Central

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

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well. PMID:25807397

  14. NASA Network

    NASA Technical Reports Server (NTRS)

    Carter, David; Wetzel, Scott

    2000-01-01

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

  15. NASA Network

    NASA Technical Reports Server (NTRS)

    Carter, David; Wetzel, Scott

    2000-01-01

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

  16. Why Network? Theoretical Perspectives on Networking

    ERIC Educational Resources Information Center

    Muijs, Daniel; West, Mel; Ainscow, Mel

    2010-01-01

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

  17. Why Network? Theoretical Perspectives on Networking

    ERIC Educational Resources Information Center

    Muijs, Daniel; West, Mel; Ainscow, Mel

    2010-01-01

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

  18. Communications Network

    NASA Technical Reports Server (NTRS)

    1990-01-01

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

  19. Neural Network Function Classifier

    DTIC Science & Technology

    2003-02-07

    neural network sets. Each of the neural networks in a particular set is trained to recognize a particular data set type. The best function representation of the data set is determined from the neural network output. The system comprises sets of trained neural networks having neural networks trained to identify different types of data. The number of neural networks within each neural network set will depend on the number of function types that are represented. The system further comprises

  20. [Networks in cognitive research].

    PubMed

    Pléh, Csaba

    2012-01-01

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

  1. Robustness of a Network of Networks

    NASA Astrophysics Data System (ADS)

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

    2012-02-01

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

  2. TELECOM 1 multiservices network

    NASA Astrophysics Data System (ADS)

    Lombard, D.; Ramat, P.; Rancy, F.

    The main objectives of the TELECOM 1 French domestic satellite project are to set up a business communication network which is to carry a wide range of digital services including data, voice, and pictures between a number of small earth stations located on the subscribers' premises. The parallel development of terrestrial specialized services networks has enabled the fitting of the TELECOM 1 network with high interworking capabilities with these networks. It has also allowed TELECOM 1 to be designed as the basis of the Future Integrated Services Digital Network. The TELECOM 1 network consists of the terrestrial network, the satellite network, and the maintenance network. Various elements which include the terrestrial network; the satellite network, and its modulation, TDMA frame and terminals; the System Management Center; the signalling system; and the demand assignment operation which are involved in the operation of the multiservices network are presented. The TELECOM 1 network evolution until 1990 through the rapid development of the ISDN is discussed.

  3. Interconnection networks

    DOEpatents

    Faber, V.; Moore, J.W.

    1988-06-20

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

  4. Hormone Health Network

    MedlinePlus

    ... 3D Patient Education mobile app The Hormone Health Network helps you and your health care provider have ... Copyright Endocrine Society. All rights reserved. Terms & Policies Network Partners The Hormone Health Network partners with other ...

  5. Air Traffic Network Project

    NASA Technical Reports Server (NTRS)

    1997-01-01

    The high level requirement of the Air Traffic Network (ATN) project is to provide a mechanism for evaluating the impact of router scheduling modifications on a networks efficiency, without implementing the modifications in the live network.

  6. Animal transportation networks

    PubMed Central

    Perna, Andrea; Latty, Tanya

    2014-01-01

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

  7. Integrated network management of hybrid networks

    NASA Astrophysics Data System (ADS)

    Baras, John S.; Ball, Mike; Karne, Ramesh K.; Kelley, Steve; Jang, Kap D.; Plaisant, Catherine; Roussopoulos, Nick; Stathatos, Kostas; Vakhutinsky, Andrew; Jaibharat, Valluri; Whitefield, David

    1996-03-01

    We describe our collaborative efforts towards the design and implementation of a next generation integrated network management system for hybrid networks (INMS/HN). We describe the overall software architecture of the system at its current stage of development. This network management system is specifically designed to address issues relevant for complex heterogeneous networks consisting of seamlessly interoperable terrestrial and satellite networks. Network management systems are a key element for interoperability in such networks. We describe the integration of configuration management and performance management. The next step in this integration is fault management. In particular we describe the object model, issues of the Graphical User Interface (GUI), browsing tools and performance data graphical widget displays, management information database (MIB) organization issues. Several components of the system are being commercialized by Hughes Network Systems.

  8. The deep space network

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Summaries are given of Deep Space Network progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations.

  9. The deep space network

    NASA Technical Reports Server (NTRS)

    1977-01-01

    Presented is Deep Space Network (DSN) progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations.

  10. Computer Networks and Networking: A Primer.

    ERIC Educational Resources Information Center

    Collins, Mauri P.

    1993-01-01

    Provides a basic introduction to computer networks and networking terminology. Topics addressed include modems; the Internet; TCP/IP (Transmission Control Protocol/Internet Protocol); transmission lines; Internet Protocol numbers; network traffic; Fidonet; file transfer protocol (FTP); TELNET; electronic mail; discussion groups; LISTSERV; USENET;…

  11. Computer Networks and Networking: A Primer.

    ERIC Educational Resources Information Center

    Collins, Mauri P.

    1993-01-01

    Provides a basic introduction to computer networks and networking terminology. Topics addressed include modems; the Internet; TCP/IP (Transmission Control Protocol/Internet Protocol); transmission lines; Internet Protocol numbers; network traffic; Fidonet; file transfer protocol (FTP); TELNET; electronic mail; discussion groups; LISTSERV; USENET;…

  12. Identity and Professional Networking.

    PubMed

    Raj, Medha; Fast, Nathanael J; Fisher, Oliver

    2017-06-01

    Despite evidence that large professional networks afford a host of financial and professional benefits, people vary in how motivated they are to build such networks. To help explain this variance, the present article moves beyond a rational self-interest account to examine the possibility that identity shapes individuals' intentions to network. Study 1 established a positive association between viewing professional networking as identity-congruent and the tendency to prioritize strengthening and expanding one's professional network. Study 2 revealed that manipulating the salience of the self affects networking intentions, but only among those high in networking identity-congruence. Study 3 further established causality by experimentally manipulating identity-congruence to increase networking intentions. Study 4 examined whether identity or self-interest is a better predictor of networking intentions, providing support for the former. These findings indicate that identity influences the networks people develop. Implications for research on the self, identity-based motivation, and professional networking are discussed.

  13. Network Plus

    NASA Astrophysics Data System (ADS)

    Bender, Walter; Chesnais, Pascal

    1988-05-01

    Over the past several years, the Electronic Publishing Group at the MIT Media Laboratory has been conducting a family of media experiments which explore a new kind of broadcast: the distribution of data and computer programs rather than pre-packaged material. This broadcast is not directed to a human recipient, but to a local computational agent acting on his behalf. In response to instructions from both the broadcaster and the reader, this agent selects from the incoming data and presents it in a manner suggestive of traditional media. The embodiment of these media experiments is a news retrieval system where the news editor has been replaced by the personal computer. A variety of both local and remote databases which operate passively as well as interac-tively are accessed by "reporters." These "reporters" are actually software interfaces, which are programmed to gather news. Ideally, they are "broadcatching" that is to say, watching all broadcast television channels, listening to all radio transmissions, and reading all newspapers, magazines, and journals. 1 A possible consequence of the synthesis of media through active processing is the merger of newspapers and television (figure 1). The result is either a newspaper with illustrations which move 2 or, conversely, print as television output. The latter is the theme of Network Plus.

  14. Robustness of Interdependent Networks

    NASA Astrophysics Data System (ADS)

    Havlin, Shlomo

    2011-03-01

    In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of many interdependent networks. We will present a framework for understanding the robustness of interacting networks subject to such cascading failures and provide a basic analytic approach that may be useful in future studies. We present exact analytical solutions for the critical fraction of nodes that upon removal will lead to a failure cascade and to a complete fragmentation of two interdependent networks in a first order transition. Surprisingly, analyzing complex systems as a set of interdependent networks may alter a basic assumption that network theory has relied on: while for a single network a broader degree distribution of the network nodes results in the network being more robust to random failures, for interdependent networks, the broader the distribution is, the more vulnerable the networks become to random failure. We also show that reducing the coupling between the networks leads to a change from a first order percolation phase transition to a second order percolation transition at a critical point. These findings pose a significant challenge to the future design of robust networks that need to consider the unique properties of interdependent networks.

  15. Data center networks and network architecture

    NASA Astrophysics Data System (ADS)

    Esaki, Hiroshi

    2014-02-01

    This paper discusses and proposes the architectural framework, which is for data center networks. The data center networks require new technical challenges, and it would be good opportunity to change the functions, which are not need in current and future networks. Based on the observation and consideration on data center networks, this paper proposes; (i) Broadcast-free layer 2 network (i.e., emulation of broadcast at the end-node), (ii) Full-mesh point-to-point pipes, and (iii) IRIDES (Invitation Routing aDvertisement for path Engineering System).

  16. Network epidemiology and plant trade networks

    PubMed Central

    Pautasso, Marco; Jeger, Mike J.

    2014-01-01

    Models of epidemics in complex networks are improving our predictive understanding of infectious disease outbreaks. Nonetheless, applying network theory to plant pathology is still a challenge. This overview summarizes some key developments in network epidemiology that are likely to facilitate its application in the study and management of plant diseases. Recent surveys have provided much-needed datasets on contact patterns and human mobility in social networks, but plant trade networks are still understudied. Human (and plant) mobility levels across the planet are unprecedented—there is thus much potential in the use of network theory by plant health authorities and researchers. Given the directed and hierarchical nature of plant trade networks, there is a need for plant epidemiologists to further develop models based on undirected and homogeneous networks. More realistic plant health scenarios would also be obtained by developing epidemic models in dynamic, rather than static, networks. For plant diseases spread by the horticultural and ornamental trade, there is the challenge of developing spatio-temporal epidemic simulations integrating network data. The use of network theory in plant epidemiology is a promising avenue and could contribute to anticipating and preventing plant health emergencies such as European ash dieback. PMID:24790128

  17. Engineering technology for networks

    NASA Technical Reports Server (NTRS)

    Paul, Arthur S.; Benjamin, Norman

    1991-01-01

    Space Network (SN) modeling and evaluation are presented. The following tasks are included: Network Modeling (developing measures and metrics for SN, modeling of the Network Control Center (NCC), using knowledge acquired from the NCC to model the SNC, and modeling the SN); and Space Network Resource scheduling.

  18. Damselfly Network Simulator

    SciTech Connect

    2014-04-01

    Damselfly is a model-based parallel network simulator. It can simulate communication patterns of High Performance Computing applications on different network topologies. It outputs steady-state network traffic for a communication pattern, which can help in studying network congestion and its impact on performance.

  19. Network Visualization Project (NVP)

    DTIC Science & Technology

    2016-07-01

    network visualization, network traffic analysis, network forensics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF...shell, is a command-line framework used for network forensic analysis. Dshell processes existing pcap files and filters output information based on

  20. Neural Network Studies

    DTIC Science & Technology

    1993-07-01

    basic useful theorems and general rules which apply to neural networks (in ’Overview of Neural Network Theory’), studies of training time as the...The Neural Network , Bayes- Gaussian, and k-Nearest Neighbor Classifiers’), an analysis of fuzzy logic and its relationship to neural network (in ’Fuzzy

  1. Coupled adaptive complex networks

    NASA Astrophysics Data System (ADS)

    Shai, S.; Dobson, S.

    2013-04-01

    Adaptive networks, which combine topological evolution of the network with dynamics on the network, are ubiquitous across disciplines. Examples include technical distribution networks such as road networks and the internet, natural and biological networks, and social science networks. These networks often interact with or depend upon other networks, resulting in coupled adaptive networks. In this paper we study susceptible-infected-susceptible (SIS) epidemic dynamics on coupled adaptive networks, where susceptible nodes are able to avoid contact with infected nodes by rewiring their intranetwork connections. However, infected nodes can pass the disease through internetwork connections, which do not change with time: The dependencies between the coupled networks remain constant. We develop an analytical formalism for these systems and validate it using extensive numerical simulation. We find that stability is increased by increasing the number of internetwork links, in the sense that the range of parameters over which both endemic and healthy states coexist (both states are reachable depending on the initial conditions) becomes smaller. Finally, we find a new stable state that does not appear in the case of a single adaptive network but only in the case of weakly coupled networks, in which the infection is endemic in one network but neither becomes endemic nor dies out in the other. Instead, it persists only at the nodes that are coupled to nodes in the other network through internetwork links. We speculate on the implications of these findings.

  2. Building Air Monitoring Networks

    ERIC Educational Resources Information Center

    Environmental Science and Technology, 1977

    1977-01-01

    The different components of air monitoring networks, the status of air monitoring in the United States, and the services and activities of the three major American network builders are detailed. International air monitoring networks and alert systems are identified, with emphasis on the Dutch air monitoring network. (BT)

  3. Designing Secure Library Networks.

    ERIC Educational Resources Information Center

    Breeding, Michael

    1997-01-01

    Focuses on designing a library network to maximize security. Discusses UNIX and file servers; connectivity to campus, corporate networks and the Internet; separation of staff from public servers; controlling traffic; the threat of network sniffers; hubs that eliminate eavesdropping; dividing the network into subnets; Switched Ethernet;…

  4. Energy Efficient Digital Networks

    SciTech Connect

    Lanzisera, Steven; Brown, Richard

    2013-01-01

    Digital networks are the foundation of the information services, and play an expanding and indispensable role in our lives, via the Internet, email, mobile phones, etc. However, these networks consume energy, both through the direct energy use of the network interfaces and equipment that comprise the network, and in the effect they have on the operating patterns of devices connected to the network. The purpose of this research was to investigate a variety of technology and policy issues related to the energy use caused by digital networks, and to further develop several energy-efficiency technologies targeted at networks.

  5. Networks in Cell Biology

    NASA Astrophysics Data System (ADS)

    Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, Michele

    2010-05-01

    Introduction; 1. Network views of the cell Paolo De Los Rios and Michele Vendruscolo; 2. Transcriptional regulatory networks Sarath Chandra Janga and M. Madan Babu; 3. Transcription factors and gene regulatory networks Matteo Brilli, Elissa Calistri and Pietro Lió; 4. Experimental methods for protein interaction identification Peter Uetz, Björn Titz, Seesandra V. Rajagopala and Gerard Cagney; 5. Modeling protein interaction networks Francesco Rao; 6. Dynamics and evolution of metabolic networks Daniel Segré; 7. Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan; 8. Signalling networks Gian Paolo Rossini; Appendix 1. Complex networks: from local to global properties D. Garlaschelli and G. Caldarelli; Appendix 2. Modelling the local structure of networks D. Garlaschelli and G. Caldarelli; Appendix 3. Higher-order topological properties S. Ahnert, T. Fink and G. Caldarelli; Appendix 4. Elementary mathematical concepts A. Gabrielli and G. Caldarelli; References.

  6. Epidemics on interconnected networks

    NASA Astrophysics Data System (ADS)

    Dickison, Mark; Havlin, S.; Stanley, H. E.

    2012-06-01

    Populations are seldom completely isolated from their environment. Individuals in a particular geographic or social region may be considered a distinct network due to strong local ties but will also interact with individuals in other networks. We study the susceptible-infected-recovered process on interconnected network systems and find two distinct regimes. In strongly coupled network systems, epidemics occur simultaneously across the entire system at a critical infection strength βc, below which the disease does not spread. In contrast, in weakly coupled network systems, a mixed phase exists below βc of the coupled network system, where an epidemic occurs in one network but does not spread to the coupled network. We derive an expression for the network and disease parameters that allow this mixed phase and verify it numerically. Public health implications of communities comprising these two classes of network systems are also mentioned.

  7. Electronic Neural Networks

    NASA Technical Reports Server (NTRS)

    Thakoor, Anil

    1990-01-01

    Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

  8. Percolation of a general network of networks.

    PubMed

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

    2013-12-01

    Percolation theory is an approach to study the vulnerability of a system. We develop an analytical framework and analyze the percolation properties of a network composed of interdependent networks (NetONet). Typically, percolation of a single network shows that the damage in the network due to a failure is a continuous function of the size of the failure, i.e., the fraction of failed nodes. In sharp contrast, in NetONet, due to the cascading failures, the percolation transition may be discontinuous and even a single node failure may lead to an abrupt collapse of the system. We demonstrate our general framework for a NetONet composed of n classic Erdős-Rényi (ER) networks, where each network depends on the same number m of other networks, i.e., for a random regular network (RR) formed of interdependent ER networks. The dependency between nodes of different networks is taken as one-to-one correspondence, i.e., a node in one network can depend only on one node in the other network (no-feedback condition). In contrast to a treelike NetONet in which the size of the largest connected cluster (mutual component) depends on n, the loops in the RR NetONet cause the largest connected cluster to depend only on m and the topology of each network but not on n. We also analyzed the extremely vulnerable feedback condition of coupling, where the coupling between nodes of different networks is not one-to-one correspondence. In the case of NetONet formed of ER networks, percolation only exhibits two phases, a second order phase transition and collapse, and no first order percolation transition regime is found in the case of the no-feedback condition. In the case of NetONet composed of RR networks, there exists a first order phase transition when the coupling strength q (fraction of interdependency links) is large and a second order phase transition when q is small. Our insight on the resilience of coupled networks might help in designing robust interdependent systems.

  9. Percolation of a general network of networks

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Percolation theory is an approach to study the vulnerability of a system. We develop an analytical framework and analyze the percolation properties of a network composed of interdependent networks (NetONet). Typically, percolation of a single network shows that the damage in the network due to a failure is a continuous function of the size of the failure, i.e., the fraction of failed nodes. In sharp contrast, in NetONet, due to the cascading failures, the percolation transition may be discontinuous and even a single node failure may lead to an abrupt collapse of the system. We demonstrate our general framework for a NetONet composed of n classic Erdős-Rényi (ER) networks, where each network depends on the same number m of other networks, i.e., for a random regular network (RR) formed of interdependent ER networks. The dependency between nodes of different networks is taken as one-to-one correspondence, i.e., a node in one network can depend only on one node in the other network (no-feedback condition). In contrast to a treelike NetONet in which the size of the largest connected cluster (mutual component) depends on n, the loops in the RR NetONet cause the largest connected cluster to depend only on m and the topology of each network but not on n. We also analyzed the extremely vulnerable feedback condition of coupling, where the coupling between nodes of different networks is not one-to-one correspondence. In the case of NetONet formed of ER networks, percolation only exhibits two phases, a second order phase transition and collapse, and no first order percolation transition regime is found in the case of the no-feedback condition. In the case of NetONet composed of RR networks, there exists a first order phase transition when the coupling strength q (fraction of interdependency links) is large and a second order phase transition when q is small. Our insight on the resilience of coupled networks might help in designing robust interdependent systems.

  10. Minimal Increase Network Coding for Dynamic Networks

    PubMed Central

    Wu, Yanxia

    2016-01-01

    Because of the mobility, computing power and changeable topology of dynamic networks, it is difficult for random linear network coding (RLNC) in static networks to satisfy the requirements of dynamic networks. To alleviate this problem, a minimal increase network coding (MINC) algorithm is proposed. By identifying the nonzero elements of an encoding vector, it selects blocks to be encoded on the basis of relationship between the nonzero elements that the controls changes in the degrees of the blocks; then, the encoding time is shortened in a dynamic network. The results of simulations show that, compared with existing encoding algorithms, the MINC algorithm provides reduced computational complexity of encoding and an increased probability of delivery. PMID:26867211

  11. Minimal Increase Network Coding for Dynamic Networks.

    PubMed

    Zhang, Guoyin; Fan, Xu; Wu, Yanxia

    2016-01-01

    Because of the mobility, computing power and changeable topology of dynamic networks, it is difficult for random linear network coding (RLNC) in static networks to satisfy the requirements of dynamic networks. To alleviate this problem, a minimal increase network coding (MINC) algorithm is proposed. By identifying the nonzero elements of an encoding vector, it selects blocks to be encoded on the basis of relationship between the nonzero elements that the controls changes in the degrees of the blocks; then, the encoding time is shortened in a dynamic network. The results of simulations show that, compared with existing encoding algorithms, the MINC algorithm provides reduced computational complexity of encoding and an increased probability of delivery.

  12. Networking: challenges for network centric operations

    NASA Astrophysics Data System (ADS)

    Stotts, Larry B.; Allen, John G.

    2004-11-01

    This paper examines some of the challenges facing the community in providing radio communications to enable information systems for military operations. We believe that much of the on-going/completed work is necessary, but not sufficient, to provide the military Network Centric Operations, which integrates military"s network centric enterprise with network centric warfare. Additional issues need to be addressed to better support battle commanders as well as decider-sensor-effecter linkages. We discuss a possible way ahead.

  13. Robustness of a Network of Networks

    NASA Astrophysics Data System (ADS)

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

    2011-11-01

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

  14. Improving network utilization over heterogeneous airborne networks

    NASA Astrophysics Data System (ADS)

    Griffin, Peter H.; Rickenbach, Brent L.; Rush, Jason A.

    2011-06-01

    Existing and future military networks vary widely in bandwidth and other network characteristics, potentially challenging deployment of services and applications across heterogeneous data links. To address this challenge, General Dynamics and Naval Research Laboratory created network services to allow applications to use wireless data links more efficiently. The basis for the network services are hooks into the data links and transport protocols providing status about the airborne networking environment. The network service can monitor heterogeneous data links on a platform and report on link availability and parameters such as latency and bandwidth. The network service then presents the network characteristics to other services and applications. These services and applications are then able to tune parameters and content based on network parameters. The technology has been demonstrated in several live-flight experiments sponsored by the United States Air Force and United States Navy. The technology was housed on several aircraft with a variety of data links ranging from directional, high-bandwidth systems to omnidirectional, medium-bandwidth systems to stable but low-bandwidth satellite systems. In each of these experiments, image and video data was successfully delivered over tactical data links that varied greatly in bandwidth and delay.

  15. Weighted projected networks: Mapping hypergraphs to networks

    NASA Astrophysics Data System (ADS)

    López, Eduardo

    2013-05-01

    Many natural, technological, and social systems incorporate multiway interactions, yet are characterized and measured on the basis of weighted pairwise interactions. In this article, I propose a family of models in which pairwise interactions originate from multiway interactions, by starting from ensembles of hypergraphs and applying projections that generate ensembles of weighted projected networks. I calculate analytically the statistical properties of weighted projected networks, and suggest ways these could be used beyond theoretical studies. Weighted projected networks typically exhibit weight disorder along links even for very simple generating hypergraph ensembles. Also, as the size of a hypergraph changes, a signature of multiway interaction emerges on the link weights of weighted projected networks that distinguishes them from fundamentally weighted pairwise networks. This signature could be used to search for hidden multiway interactions in weighted network data. I find the percolation threshold and size of the largest component for hypergraphs of arbitrary uniform rank, translate the results into projected networks, and show that the transition is second order. This general approach to network formation has the potential to shed new light on our understanding of weighted networks.

  16. Computer network defense system

    DOEpatents

    Urias, Vincent; Stout, William M. S.; Loverro, Caleb

    2017-08-22

    A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves network connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.

  17. Translated chemical reaction networks.

    PubMed

    Johnston, Matthew D

    2014-05-01

    Many biochemical and industrial applications involve complicated networks of simultaneously occurring chemical reactions. Under the assumption of mass action kinetics, the dynamics of these chemical reaction networks are governed by systems of polynomial ordinary differential equations. The steady states of these mass action systems have been analyzed via a variety of techniques, including stoichiometric network analysis, deficiency theory, and algebraic techniques (e.g., Gröbner bases). In this paper, we present a novel method for characterizing the steady states of mass action systems. Our method explicitly links a network's capacity to permit a particular class of steady states, called toric steady states, to topological properties of a generalized network called a translated chemical reaction network. These networks share their reaction vectors with their source network but are permitted to have different complex stoichiometries and different network topologies. We apply the results to examples drawn from the biochemical literature.

  18. Wayfinding in Social Networks

    NASA Astrophysics Data System (ADS)

    Liben-Nowell, David

    With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.

  19. Network connectivity value.

    PubMed

    Dragicevic, Arnaud; Boulanger, Vincent; Bruciamacchie, Max; Chauchard, Sandrine; Dupouey, Jean-Luc; Stenger, Anne

    2017-02-23

    In order to unveil the value of network connectivity, we formalize the construction of ecological networks in forest environments as an optimal control dynamic graph-theoretic problem. The network is based on a set of bioreserves and patches linked by ecological corridors. The node dynamics, built upon the consensus protocol, form a time evolutive Mahalanobis distance weighted by the opportunity costs of timber production. We consider a case of complete graph, where the ecological network is fully connected, and a case of incomplete graph, where the ecological network is partially connected. The results show that the network equilibrium depends on the size of the reception zone, while the network connectivity depends on the environmental compatibility between the ecological areas. Through shadow prices, we find that securing connectivity in partially connected networks is more expensive than in fully connected networks, but should be undertaken when the opportunity costs are significant.

  20. Satellite networks for education

    NASA Technical Reports Server (NTRS)

    Singh, J. P.; Morgan, R. P.; Rosenbaum, F. J.

    1972-01-01

    Satellite based educational networking is discussed with particular attention given to the potential uses of communications satellites to help meet educational needs in the United states. Four major subject areas were covered; (1) characteristics and structure of networks, (2) definition of pressures within educational establishment that provide motivation for various types of networks, (3) examination of current educational networking status for educational radio and television, instructional television fixed services, inter- and intra-state educational communication networks, computer networks, and cable television for education, and (4) identification of possible satellite based educational telecommunication services and three alternatives for implementing educational satellite systems.

  1. Network observability transitions.

    PubMed

    Yang, Yang; Wang, Jianhui; Motter, Adilson E

    2012-12-21

    In the modeling, monitoring, and control of complex networks, a fundamental problem concerns the comprehensive determination of the state of the system from limited measurements. Using power grids as example networks, we show that this problem leads to a new type of percolation transition, here termed a network observability transition, which we solve analytically for the configuration model. We also demonstrate a dual role of the network's community structure, which both facilitates optimal measurement placement and renders the networks substantially more sensitive to "observability attacks." Aside from their immediate implications for the development of smart grids, these results provide insights into decentralized biological, social, and technological networks.

  2. The International Trade Network

    NASA Astrophysics Data System (ADS)

    Bhattacharya, K.; Mukherjee, G.; Manna, S. S.

    Bilateral trade relationships in the international level between pairs of countries in the world give rise to the notion of the International Trade Network (ITN). This network has attracted the attention of network researchers as it serves as an excellent example of the weighted networks, the link weight being defined as a measure of the volume of trade between two countries. In this paper we analyzed the international trade data for 53 years and studied in detail the variations of different network related quantities associated with the ITN. Our observation is that the ITN has also a scale invariant structure like many other real-world networks.

  3. Local area networking: Ames centerwide network

    NASA Technical Reports Server (NTRS)

    Price, Edwin

    1988-01-01

    A computer network can benefit the user by making his/her work quicker and easier. A computer network is made up of seven different layers with the lowest being the hardware, the top being the user, and the middle being the software. These layers are discussed.

  4. Parental Social Network and Child's Friendship Network.

    ERIC Educational Resources Information Center

    Uhlendorff, Harald; Oswald, Hans

    This study analyzed the relation between the friendship networks of parents and the peer networks of their children. Subjects were 255 second- through fifth-grade children of an inner-city primary school in the western part of Berlin, Germany, who were interviewed about friends. In the interview, children were asked to name other children with…

  5. Reciprocity of weighted networks.

    PubMed

    Squartini, Tiziano; Picciolo, Francesco; Ruzzenenti, Franco; Garlaschelli, Diego

    2013-01-01

    In directed networks, reciprocal links have dramatic effects on dynamical processes, network growth, and higher-order structures such as motifs and communities. While the reciprocity of binary networks has been extensively studied, that of weighted networks is still poorly understood, implying an ever-increasing gap between the availability of weighted network data and our understanding of their dyadic properties. Here we introduce a general approach to the reciprocity of weighted networks, and define quantities and null models that consistently capture empirical reciprocity patterns at different structural levels. We show that, counter-intuitively, previous reciprocity measures based on the similarity of mutual weights are uninformative. By contrast, our measures allow to consistently classify different weighted networks according to their reciprocity, track the evolution of a network's reciprocity over time, identify patterns at the level of dyads and vertices, and distinguish the effects of flux (im)balances or other (a)symmetries from a true tendency towards (anti-)reciprocation.

  6. The deep space network

    NASA Technical Reports Server (NTRS)

    1979-01-01

    Progress is reported in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. The functions and facilities of the Deep Space Network are emphasized.

  7. The deep space network

    NASA Technical Reports Server (NTRS)

    1979-01-01

    A report is given of the Deep Space Networks progress in (1) flight project support, (2) tracking and data acquisition research and technology, (3) network engineering, (4) hardware and software implementation, and (5) operations.

  8. Bladder Cancer Advocacy Network

    MedlinePlus

    ... Grants Bladder Cancer Think Tank Bladder Cancer Research Network Bladder Cancer Genomics Consortium Get Involved Ways to ... RESEARCHERS Research Grants Bladder Cancer Think Tank Research Network Explore all research programs View all stories NEWSLETTER ...

  9. Join the Network

    EPA Pesticide Factsheets

    As a CMOP Network Member you will automatically receive our periodic news announcements and can add your organization and your contact information to our Network Contacts list, which is featured on the CMOP website.

  10. National Lymphedema Network

    MedlinePlus

    ... 11-14 NLN Lymphedema Awareness Month National Lymphedema Network Lymphedema Overview Start Here! Get an overview of ... activities and goings-on. Follow the National Lymphedema Network newsfeed below. Also, see the following links for ...

  11. Class network routing

    DOEpatents

    Bhanot, Gyan [Princeton, NJ; Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

    2009-09-08

    Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

  12. Dynamic Constraints Networks

    DTIC Science & Technology

    1989-10-31

    static approach to constrained networks has been used to develop a dynamic theory of constraint networks for problem solving. The scientific results of this development resulted in six scientific publications . (KT)

  13. The deep space network

    NASA Technical Reports Server (NTRS)

    1977-01-01

    A Deep Space Network progress report is presented dealing with in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations.

  14. The deep space network

    NASA Technical Reports Server (NTRS)

    1980-01-01

    The functions and facilities of the Deep Space Network are considered. Progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations is reported.

  15. The Merit Computer Network

    ERIC Educational Resources Information Center

    Aupperle, Eric M.; Davis, Donna L.

    1978-01-01

    The successful Merit Computer Network is examined in terms of both technology and operational management. The network is fully operational and has a significant and rapidly increasing usage, with three major institutions currently sharing computer resources. (Author/CMV)

  16. Lymphatic Education & Research Network

    MedlinePlus

    Lymphatic Education & Research Network Donate Now Become a Supporting Member X Living with LYMPHEDEMA AND Lymphatic Disease FAQs About ... 261 Madison Avenue, New York, NY 10016 | Lymphatic Education & Research Network is a 501(c)(3) under ...

  17. The deep space network

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The facilities, programming system, and monitor and control system for the deep space network are described. Ongoing planetary and interplanetary flight projects are reviewed, along with tracking and ground-based navigation, communications, and network and facility engineering.

  18. Networking and Institutional Planning.

    ERIC Educational Resources Information Center

    Riggs, Donald E.

    1987-01-01

    Explores the impact of networks and shared library resources on the library planning process. Environmental scanning techniques, the need for cooperative planning, and the formulation of strategies to achieve networking goals are discussed. (CLB)

  19. Virtualized Network Control (VNC)

    SciTech Connect

    Lehman, Thomas; Guok, Chin; Ghani, Nasir

    2013-01-31

    The focus of this project was on the development of a "Network Service Plane" as an abstraction model for the control and provisioning of multi-layer networks. The primary motivation for this work were the requirements of next generation networked applications which will need to access advanced networking as a first class resource at the same level as compute and storage resources. A new class of "Intelligent Network Services" were defined in order to facilitate the integration of advanced network services into application specific workflows. This new class of network services are intended to enable real-time interaction between the application co-scheduling algorithms and the network for the purposes of workflow planning, real-time resource availability identification, scheduling, and provisioning actions.

  20. Wireless Mesh Networks

    NASA Astrophysics Data System (ADS)

    Ishmael, Johnathan; Race, Nicholas

    Wireless Mesh Networks have emerged as an important technology in building next-generation networks. They are seen to have a range of benefits over traditional wired and wireless networks including low deployment costs, high scalability and resiliency to faults. Moreover, Wireless Mesh Networks (WMNs) are often described as being autonomic with self-* (healing and configuration) properties and their popularity has grown both as a research platform and as a commercially exploitable technology.

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

    PubMed

    Yoshihara, Chika; Shimizu, Shinji

    2005-10-01

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

  2. Automatic Microwave Network Analysis.

    DTIC Science & Technology

    A program and procedure are developed for the automatic measurement of microwave networks using a Hewlett-Packard network analyzer and programmable calculator . The program and procedure are used in the measurement of a simple microwave two port network. These measurements are evaluated by comparing with measurements on the same network using other techniques. The programs...in the programmable calculator are listed in Appendix 1. The step by step procedure used is listed in Appendix 2. (Author)

  3. TENET: Texas Education Network.

    ERIC Educational Resources Information Center

    Stout, Connie

    The Texas Education Agency sought to create an enhanced electronic communications network (TENET) capable of transmitting information among and between the members of the public education system in Texas. They contracted with the Texas Higher Education Network (THEnet), an existing distributed network which is an NSF (National Science Foundation)…

  4. Emergent Network Defense

    ERIC Educational Resources Information Center

    Crane, Earl Newell

    2013-01-01

    The research problem that inspired this effort is the challenge of managing the security of systems in large-scale heterogeneous networked environments. Human intervention is slow and limited: humans operate at much slower speeds than networked computer communications and there are few humans associated with each network. Enabling each node in the…

  5. Information network architectures

    NASA Technical Reports Server (NTRS)

    Murray, N. D.

    1985-01-01

    Graphs, charts, diagrams and outlines of information relative to information network architectures for advanced aerospace missions, such as the Space Station, are presented. Local area information networks are considered a likely technology solution. The principle needs for the network are listed.

  6. Networking Brown University.

    ERIC Educational Resources Information Center

    Beckham, Bonnie

    1989-01-01

    Assesses BRUNET, a campuswide network that links more than 100 academic and administrative buildings and 40 dormitories. Notes a key element is hierarchical network management and support. Discusses the deployment, security, and use of four networking spheres in the system. (MVL)

  7. Metallic nanowire networks

    DOEpatents

    Song, Yujiang; Shelnutt, John A.

    2012-11-06

    A metallic nanowire network synthesized using chemical reduction of a metal ion source by a reducing agent in the presence of a soft template comprising a tubular inverse micellar network. The network of interconnected polycrystalline nanowires has a very high surface-area/volume ratio, which makes it highly suitable for use in catalytic applications.

  8. Advanced Network Security Project

    DTIC Science & Technology

    2005-12-01

    network. The network observed was the Abilene network of the University Consortium for Advanced Internet Development (UCAID), often known as “ Internet2 ...for Advanced Internet Development (UCAID), often known as “ Internet2 .” This contract was heavily operational in nature, as opposed to a contract

  9. Real Time Network Assessment

    DTIC Science & Technology

    2013-07-12

    Demonstrate a simple system Conduct a feasibility assessment of data storage, maintenance, and integration requirements Test a web-based data feed...Real Time Network Assessment Prototype We demonstrated the feasibility of linking near real time network analytics to mashups and web- based...combining similar concepts into single node) Stemmers Thesauri application Network position Statistical common patterns Pronoun identification

  10. OSI Network Management.

    ERIC Educational Resources Information Center

    Harris, Ethan

    1990-01-01

    Management of heterogeneous networks is complicated by the persistence of proprietary management schemes. The need for integration of network management capabilities is pressing. The International Organization for Standardization is developing standards for managing networks as part of the Open Systems Interconnection (OSI) effort. OSI management…

  11. Spanish Museum Libraries Network.

    ERIC Educational Resources Information Center

    Lopez de Prado, Rosario

    This paper describes the creation of an automated network of museum libraries in Spain. The only way in which the specialized libraries in the world today can continue to be active and to offer valid information is to automate the service they offer, and create network libraries with cooperative plans. The network can be configured with different…

  12. Social Networks and Adaptation.

    ERIC Educational Resources Information Center

    Cohen, Carl I.; And Others

    In a longitudinal study of the network characteristics that assist elderly individuals to meet their needs, as well as the effects of change in four categories of social network dimensions (social interaction, network structure, member attribute, environmental attribute), 133 elderly residents of 18 midtown Manhattan single room occupancy (SRO)…

  13. Emergent Network Defense

    ERIC Educational Resources Information Center

    Crane, Earl Newell

    2013-01-01

    The research problem that inspired this effort is the challenge of managing the security of systems in large-scale heterogeneous networked environments. Human intervention is slow and limited: humans operate at much slower speeds than networked computer communications and there are few humans associated with each network. Enabling each node in the…

  14. Calorimetry Network Program

    SciTech Connect

    Brown, C.

    1998-01-30

    This is a Windows NT based program to run the SRTC designed calorimeters. The network version can communicate near real time data and final data values over the network. This version, due to network specifics, can function in a stand-alone operation also.

  15. Generalized classifier neural network.

    PubMed

    Ozyildirim, Buse Melis; Avci, Mutlu

    2013-03-01

    In this work a new radial basis function based classification neural network named as generalized classifier neural network, is proposed. The proposed generalized classifier neural network has five layers, unlike other radial basis function based neural networks such as generalized regression neural network and probabilistic neural network. They are input, pattern, summation, normalization and output layers. In addition to topological difference, the proposed neural network has gradient descent based optimization of smoothing parameter approach and diverge effect term added calculation improvements. Diverge effect term is an improvement on summation layer calculation to supply additional separation ability and flexibility. Performance of generalized classifier neural network is compared with that of the probabilistic neural network, multilayer perceptron algorithm and radial basis function neural network on 9 different data sets and with that of generalized regression neural network on 3 different data sets include only two classes in MATLAB environment. Better classification performance up to %89 is observed. Improved classification performances proved the effectivity of the proposed neural network.

  16. Security of Complex Networks

    DTIC Science & Technology

    2010-02-18

    social network (DS), (8) network of American football games among colleges (AFC), (9) social network of friendships of a karate club (FKC), (10...Ax2 = 12 book karate football ’•■ electronic circuit dolphins a C. Elegans 102 Figure 8: For Universal scaling law for six real-world

  17. Satellite Networks for Education.

    ERIC Educational Resources Information Center

    Singh, J. P.; And Others

    The paper has four main sections. The first is concerned with the characteristics and structure of satellite networks. The second discusses pressures within education that are causing the development of various types of networks and also identifies studies in which networking needs for educational sectors and services are defined. The third…

  18. OSI Network Management.

    ERIC Educational Resources Information Center

    Harris, Ethan

    1990-01-01

    Management of heterogeneous networks is complicated by the persistence of proprietary management schemes. The need for integration of network management capabilities is pressing. The International Organization for Standardization is developing standards for managing networks as part of the Open Systems Interconnection (OSI) effort. OSI management…

  19. Electronic Networking. ERIC Digest.

    ERIC Educational Resources Information Center

    Tucker, Susan

    This digest discusses several aspects of electronic networking, including network functions, implementation, and applications in education. Electronic networking is defined as including the four basic services of electronic mail (E-mail), electronic "bulletin boards," teleconferencing, and online databases, and an overview of these four…

  20. CD-ROM Networking.

    ERIC Educational Resources Information Center

    Akeroyd, John

    1992-01-01

    Provides an overview of CD-ROM networks. Highlights include network technology, including local area networks; an example of an installation at the South Bank Polytechnic (United Kingdom) library; interface issues, including standardization; possible future developments; licensing arrangements; and acquiring data in formats other than CD-ROM.…

  1. Computer Networking for Educators.

    ERIC Educational Resources Information Center

    McCain, Ted D. E.; Ekelund, Mark

    This book is intended to introduce the basic concepts of connecting computers together and to equip individuals with the technical background necessary to begin constructing small networks. For those already experienced with creating and maintaining computer networks, the book can help in considering the creation of a schoolwide network. The book…

  2. Probabilistic Analysis of Neural Networks

    DTIC Science & Technology

    1990-11-26

    provide an understanding of the basic mechanisms of learning and recognition in neural networks . The main areas of progress were analysis of neural ... networks models, study of network connectivity, and investigation of computer network theory.

  3. Directed network discovery with dynamic network modelling.

    PubMed

    Anzellotti, Stefano; Kliemann, Dorit; Jacoby, Nir; Saxe, Rebecca

    2017-05-01

    Cognitive tasks recruit multiple brain regions. Understanding how these regions influence each other (the network structure) is an important step to characterize the neural basis of cognitive processes. Often, limited evidence is available to restrict the range of hypotheses a priori, and techniques that sift efficiently through a large number of possible network structures are needed (network discovery). This article introduces a novel modelling technique for network discovery (Dynamic Network Modelling or DNM) that builds on ideas from Granger Causality and Dynamic Causal Modelling introducing three key changes: (1) efficient network discovery is implemented with statistical tests on the consistency of model parameters across participants, (2) the tests take into account the magnitude and sign of each influence, and (3) variance explained in independent data is used as an absolute (rather than relative) measure of the quality of the network model. In this article, we outline the functioning of DNM, we validate DNM in simulated data for which the ground truth is known, and we report an example of its application to the investigation of influences between regions during emotion recognition, revealing top-down influences from brain regions encoding abstract representations of emotions (medial prefrontal cortex and superior temporal sulcus) onto regions engaged in the perceptual analysis of facial expressions (occipital face area and fusiform face area) when participants are asked to switch between reporting the emotional valence and the age of a face. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Characteristics on hub networks of urban rail transit networks

    NASA Astrophysics Data System (ADS)

    Zhang, Jianhua; Wang, Shuliang; Zhang, Zhaojun; Zou, Kuansheng; Shu, Zhan

    2016-04-01

    This paper proposes an approach to extract the hub networks from urban rail transit networks, and analyzes the characteristics of the hub networks. Minsk metro and Shanghai metro networks are given to illustrate the feasibility and effectiveness of the presented method in this paper. By simulations, we discover that the hub networks of urban rail transit networks possess small-world property and scale-free property. Meanwhile, this paper shows that the hub networks are completely different from the corresponding metro networks. Moreover, we find that the hub network is a hierarchical network, and the root of hub network corresponds to the transfer station of metro network which is passed by the most lines in metro network, and the root controls the main characteristics of hub network. In other words, the transfer station corresponding to this root plays the most important role in the urban rail transit networks.

  5. Groundwater data network interoperability

    USGS Publications Warehouse

    Brodaric, Boyan; Booth, Nathaniel; Boisvert, Eric; Lucido, Jessica M.

    2016-01-01

    Water data networks are increasingly being integrated to answer complex scientific questions that often span large geographical areas and cross political borders. Data heterogeneity is a major obstacle that impedes interoperability within and between such networks. It is resolved here for groundwater data at five levels of interoperability, within a Spatial Data Infrastructure architecture. The result is a pair of distinct national groundwater data networks for the United States and Canada, and a combined data network in which they are interoperable. This combined data network enables, for the first time, transparent public access to harmonized groundwater data from both sides of the shared international border.

  6. Networks Technology Conference

    NASA Technical Reports Server (NTRS)

    Tasaki, Keiji K. (Editor)

    1993-01-01

    The papers included in these proceedings represent the most interesting and current topics being pursued by personnel at GSFC's Networks Division and supporting contractors involved in Space, Ground, and Deep Space Network (DSN) technical work. Although 29 papers are represented in the proceedings, only 12 were presented at the conference because of space and time limitations. The proceedings are organized according to five principal technical areas of interest to the Networks Division: Project Management; Network Operations; Network Control, Scheduling, and Monitoring; Modeling and Simulation; and Telecommunications Engineering.

  7. NASA's unique networking environment

    NASA Technical Reports Server (NTRS)

    Johnson, Marjory J.

    1988-01-01

    Networking is an infrastructure technology; it is a tool for NASA to support its space and aeronautics missions. Some of NASA's networking problems are shared by the commercial and/or military communities, and can be solved by working with these communities. However, some of NASA's networking problems are unique and will not be addressed by these other communities. Individual characteristics of NASA's space-mission networking enviroment are examined, the combination of all these characteristics that distinguish NASA's networking systems from either commercial or military systems is explained, and some research areas that are important for NASA to pursue are outlined.

  8. Network structure of production

    PubMed Central

    Atalay, Enghin; Hortaçsu, Ali; Roberts, James; Syverson, Chad

    2011-01-01

    Complex social networks have received increasing attention from researchers. Recent work has focused on mechanisms that produce scale-free networks. We theoretically and empirically characterize the buyer–supplier network of the US economy and find that purely scale-free models have trouble matching key attributes of the network. We construct an alternative model that incorporates realistic features of firms’ buyer–supplier relationships and estimate the model’s parameters using microdata on firms’ self-reported customers. This alternative framework is better able to match the attributes of the actual economic network and aids in further understanding several important economic phenomena. PMID:21402924

  9. Studies in Neural Networks

    DTIC Science & Technology

    1991-01-01

    N00014-87-K-0377 TITLE: "Studies in Neural Networks " fl.U Q l~~izie JUL 021991 "" " F.: L9’CO37 "I! c-1(.d Contract No.: N00014-87-K-0377 Final...34) have been very useful, both in understanding the dynamics of neural networks and in engineering networks to perform particular tasks. We have noted...understanding more complex network computation. Interest in applying ideas from biological neural networks to real problems of engineering raises the issues of

  10. Network Characterization Service (NCS)

    SciTech Connect

    Jin, Guojun; Yang, George; Crowley, Brian; Agarwal, Deborah

    2001-06-06

    Distributed applications require information to effectively utilize the network. Some of the information they require is the current and maximum bandwidth, current and minimum latency, bottlenecks, burst frequency, and congestion extent. This type of information allows applications to determine parameters like optimal TCP buffer size. In this paper, we present a cooperative information-gathering tool called the network characterization service (NCS). NCS runs in user space and is used to acquire network information. Its protocol is designed for scalable and distributed deployment, similar to DNS. Its algorithms provide efficient, speedy and accurate detection of bottlenecks, especially dynamic bottlenecks. On current and future networks, dynamic bottlenecks do and will affect network performance dramatically.

  11. Packet transport network in metro

    NASA Astrophysics Data System (ADS)

    Huang, Feng; Yi, Xiaobo; Zhang, Hanzheng; Gong, Ping

    2008-11-01

    IP packet based services such as high speed internet, IP voice and IP video will be widely deployed in telecom network, which make transport network evolution to packet transport network. Characteristics of transport network and requirements of packet transport network are analyzed, T-MPLS/MPLS-TP based PTN technology is given and it will be used in metro (access, aggregation and core) network.

  12. Cheaters in mutualism networks.

    PubMed

    Genini, Julieta; Morellato, L Patrícia C; Guimarães, Paulo R; Olesen, Jens M

    2010-08-23

    Mutualism-network studies assume that all interacting species are mutualistic partners and consider that all links are of one kind. However, the influence of different types of links, such as cheating links, on network organization remains unexplored. We studied two flower-visitation networks (Malpighiaceae and Bignoniaceae and their flower visitors), and divide the types of link into cheaters (i.e. robbers and thieves of flower rewards) and effective pollinators. We investigated if there were topological differences among networks with and without cheaters, especially with respect to nestedness and modularity. The Malpighiaceae network was nested, but not modular, and it was dominated by pollinators and had much fewer cheater species than Bignoniaceae network (28% versus 75%). The Bignoniaceae network was mainly a plant-cheater network, being modular because of the presence of pollen robbers and showing no nestedness. In the Malpighiaceae network, removal of cheaters had no major consequences for topology. In contrast, removal of cheaters broke down the modularity of the Bignoniaceae network. As cheaters are ubiquitous in all mutualisms, the results presented here show that they have a strong impact upon network topology.

  13. Cheaters in mutualism networks

    PubMed Central

    Genini, Julieta; Morellato, L. Patrícia C.; Guimarães, Paulo R.; Olesen, Jens M.

    2010-01-01

    Mutualism-network studies assume that all interacting species are mutualistic partners and consider that all links are of one kind. However, the influence of different types of links, such as cheating links, on network organization remains unexplored. We studied two flower-visitation networks (Malpighiaceae and Bignoniaceae and their flower visitors), and divide the types of link into cheaters (i.e. robbers and thieves of flower rewards) and effective pollinators. We investigated if there were topological differences among networks with and without cheaters, especially with respect to nestedness and modularity. The Malpighiaceae network was nested, but not modular, and it was dominated by pollinators and had much fewer cheater species than Bignoniaceae network (28% versus 75%). The Bignoniaceae network was mainly a plant–cheater network, being modular because of the presence of pollen robbers and showing no nestedness. In the Malpighiaceae network, removal of cheaters had no major consequences for topology. In contrast, removal of cheaters broke down the modularity of the Bignoniaceae network. As cheaters are ubiquitous in all mutualisms, the results presented here show that they have a strong impact upon network topology. PMID:20089538

  14. Emergent Complex Network Geometry

    PubMed Central

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

    2015-01-01

    Networks are mathematical structures that are universally used to describe a large variety of complex systems such as the brain or the Internet. Characterizing the geometrical properties of these networks has become increasingly relevant for routing problems, inference and data mining. In real growing networks, topological, structural and geometrical properties emerge spontaneously from their dynamical rules. Nevertheless we still miss a model in which networks develop an emergent complex geometry. Here we show that a single two parameter network model, the growing geometrical network, can generate complex network geometries with non-trivial distribution of curvatures, combining exponential growth and small-world properties with finite spectral dimensionality. In one limit, the non-equilibrium dynamical rules of these networks can generate scale-free networks with clustering and communities, in another limit planar random geometries with non-trivial modularity. Finally we find that these properties of the geometrical growing networks are present in a large set of real networks describing biological, social and technological systems. PMID:25985280

  15. Internet protocol network mapper

    SciTech Connect

    Youd, David W.; Colon III, Domingo R.; Seidl, Edward T.

    2016-02-23

    A network mapper for performing tasks on targets is provided. The mapper generates a map of a network that specifies the overall configuration of the network. The mapper inputs a procedure that defines how the network is to be mapped. The procedure specifies what, when, and in what order the tasks are to be performed. Each task specifies processing that is to be performed for a target to produce results. The procedure may also specify input parameters for a task. The mapper inputs initial targets that specify a range of network addresses to be mapped. The mapper maps the network by, for each target, executing the procedure to perform the tasks on the target. The results of the tasks represent the mapping of the network defined by the initial targets.

  16. Network topology analysis.

    SciTech Connect

    Kalb, Jeffrey L.; Lee, David S.

    2008-01-01

    Emerging high-bandwidth, low-latency network technology has made network-based architectures both feasible and potentially desirable for use in satellite payload architectures. The selection of network topology is a critical component when developing these multi-node or multi-point architectures. This study examines network topologies and their effect on overall network performance. Numerous topologies were reviewed against a number of performance, reliability, and cost metrics. This document identifies a handful of good network topologies for satellite applications and the metrics used to justify them as such. Since often multiple topologies will meet the requirements of the satellite payload architecture under development, the choice of network topology is not easy, and in the end the choice of topology is influenced by both the design characteristics and requirements of the overall system and the experience of the developer.

  17. Satellite networks for education.

    NASA Technical Reports Server (NTRS)

    Singh, J. P.; Morgan, R. P.; Rosenbaum, F. J.

    1972-01-01

    Consideration of satellite-based educational networking. The characteristics and structure of networks are reviewed, and pressures within the educational establishment that are providing motivation for various types of networks are discussed. A number of studies are cited in which networking needs for educational sectors and services are defined. The current status of educational networking for educational radio and television, instructional television fixed services, inter- and intrastate educational communication networks, computer networks, cable television for education, and continuing and proposed educational experiments using NASA's Applications Technology Satellites is reviewed. Possible satellite-based educational telecommunication services and three alternatives for implementing educational satellite systems are described. Some remarks are made concerning public policy aspects of future educational satellite system development.

  18. Satellite networks for education.

    NASA Technical Reports Server (NTRS)

    Singh, J. P.; Morgan, R. P.; Rosenbaum, F. J.

    1972-01-01

    Consideration of satellite-based educational networking. The characteristics and structure of networks are reviewed, and pressures within the educational establishment that are providing motivation for various types of networks are discussed. A number of studies are cited in which networking needs for educational sectors and services are defined. The current status of educational networking for educational radio and television, instructional television fixed services, inter- and intrastate educational communication networks, computer networks, cable television for education, and continuing and proposed educational experiments using NASA's Applications Technology Satellites is reviewed. Possible satellite-based educational telecommunication services and three alternatives for implementing educational satellite systems are described. Some remarks are made concerning public policy aspects of future educational satellite system development.

  19. Percolation on Sparse Networks

    NASA Astrophysics Data System (ADS)

    Karrer, Brian; Newman, M. E. J.; Zdeborová, Lenka

    2014-11-01

    We study percolation on networks, which is used as a model of the resilience of networked systems such as the Internet to attack or failure and as a simple model of the spread of disease over human contact networks. We reformulate percolation as a message passing process and demonstrate how the resulting equations can be used to calculate, among other things, the size of the percolating cluster and the average cluster size. The calculations are exact for sparse networks when the number of short loops in the network is small, but even on networks with many short loops we find them to be highly accurate when compared with direct numerical simulations. By considering the fixed points of the message passing process, we also show that the percolation threshold on a network with few loops is given by the inverse of the leading eigenvalue of the so-called nonbacktracking matrix.

  20. Organization of complex networks

    NASA Astrophysics Data System (ADS)

    Kitsak, Maksim

    Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how

  1. Network planning under uncertainties

    NASA Astrophysics Data System (ADS)

    Ho, Kwok Shing; Cheung, Kwok Wai

    2008-11-01

    One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a

  2. A Networking Protocol for Underwater Acoustic Networks

    DTIC Science & Technology

    2000-12-01

    acoustic networks. [Ramanathan 1996, Broch 1999, Perkins 2000, Boukerche 2000] Two key characteristics bear consideration- when routes are determined...Master Thesis, Department of Computer Science, Naval Postgraduate School, June 2000. 2. Broch , Josh, D. A. Maltz, D. B. Johnson, Y. Hu, and J...Networking, October 1998. 3. Broch , Josh, D. B. Johnson, and D. A. Maltz. �The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks�, IETF

  3. Network Management of the SPLICE Computer Network.

    DTIC Science & Technology

    1982-12-01

    user. We now submit what we feel is a responsible and complete lefinition of network management. Our definition includes: collecti:n of measurements...it’s limited ability to detect the stimulus for the set of signals it is monitDring. 2. SqtSL phd12 Although various definitions exist, a software...the network possess a greater than normal degree sf intelligence, ilen-. ion and ma’ntenance tend to oe nore : osty than centralized mon itoring. 5

  4. Patterns in randomly evolving networks: Idiotypic networks

    NASA Astrophysics Data System (ADS)

    Brede, Markus; Behn, Ulrich

    2003-03-01

    We present a model for the evolution of networks of occupied sites on undirected regular graphs. At every iteration step in a parallel update, I randomly chosen empty sites are occupied and occupied sites having occupied neighbor degree outside of a given interval (tl,tu) are set empty. Depending on the influx I and the values of both lower threshold and upper threshold of the occupied neighbor degree, different kinds of behavior can be observed. In certain regimes stable long-living patterns appear. We distinguish two types of patterns: static patterns arising on graphs with low connectivity and dynamic patterns found on high connectivity graphs. Increasing I patterns become unstable and transitions between almost stable patterns, interrupted by disordered phases, occur. For still larger I the lifetime of occupied sites becomes very small and network structures are dominated by randomness. We develop methods to analyze the nature and dynamics of these network patterns, give a statistical description of defects and fluctuations around them, and elucidate the transitions between different patterns. Results and methods presented can be applied to a variety of problems in different fields and a broad class of graphs. Aiming chiefly at the modeling of functional networks of interacting antibodies and B cells of the immune system (idiotypic networks), we focus on a class of graphs constructed by bit chains. The biological relevance of the patterns and possible operational modes of idiotypic networks are discussed.

  5. Optical Access Networks

    NASA Astrophysics Data System (ADS)

    Zheng, Jun; Ansari, Nirwan

    2005-05-01

    Call for Papers: Optical Access Networks With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the economic viability of many potential high-bandwidth applications. In recent years, optical access networks have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or

  6. Optical Access Networks

    NASA Astrophysics Data System (ADS)

    Zheng, Jun; Ansari, Nirwan; Jersey Inst Ansari, New; Jersey Inst, New

    2005-04-01

    Call for Papers: Optical Access Networks With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the economic viability of many potential high-bandwidth applications. In recent years, optical access networks have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or

  7. Optical Access Networks

    NASA Astrophysics Data System (ADS)

    Zheng, Jun; Ansari, Nirwan

    2005-06-01

    Call for Papers: Optical Access Networks With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the economic viability of many potential high-bandwidth applications. In recent years, optical access networks have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or

  8. Cognitive Network Neuroscience

    PubMed Central

    Medaglia, John D.; Lynall, Mary-Ellen; Bassett, Danielle S.

    2016-01-01

    Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience. PMID:25803596

  9. Cognitive network neuroscience.

    PubMed

    Medaglia, John D; Lynall, Mary-Ellen; Bassett, Danielle S

    2015-08-01

    Network science provides theoretical, computational, and empirical tools that can be used to understand the structure and function of the human brain in novel ways using simple concepts and mathematical representations. Network neuroscience is a rapidly growing field that is providing considerable insight into human structural connectivity, functional connectivity while at rest, changes in functional networks over time (dynamics), and how these properties differ in clinical populations. In addition, a number of studies have begun to quantify network characteristics in a variety of cognitive processes and provide a context for understanding cognition from a network perspective. In this review, we outline the contributions of network science to cognitive neuroscience. We describe the methodology of network science as applied to the particular case of neuroimaging data and review its uses in investigating a range of cognitive functions including sensory processing, language, emotion, attention, cognitive control, learning, and memory. In conclusion, we discuss current frontiers and the specific challenges that must be overcome to integrate these complementary disciplines of network science and cognitive neuroscience. Increased communication between cognitive neuroscientists and network scientists could lead to significant discoveries under an emerging scientific intersection known as cognitive network neuroscience.

  10. Serial Network Flow Monitor

    NASA Technical Reports Server (NTRS)

    Robinson, Julie A.; Tate-Brown, Judy M.

    2009-01-01

    Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

  11. Computer network programming

    SciTech Connect

    Hsu, J.Y.

    1996-12-31

    The programs running on a computer network can be divided into two parts, the Network Operating System and the user applications. Any high level language translator, such as C, JAVA, BASIC, FORTRAN, or COBOL, runs under NOS as a programming tool to produce network application programs or software. Each application program while running on the network provides the human user with network application services, such as remote data base search, retrieval, etc. The Network Operating System should provide a simple and elegant system interface to all the network application programs. This programming interface may request the Transport layer services on behalf of a network application program. The primary goals are to achieve programming convenience, and to avoid complexity. In a 5-layer network model, the system interface is comprised of a group of system calls which are collectively known as the session layer with its own Session Protocol Data Units. This is a position paper discussing the basic system primitives which reside between a network application program and the Transport layer, and a programming example of using such primitives.

  12. Weighted multiplex networks.

    PubMed

    Menichetti, Giulia; Remondini, Daniel; Panzarasa, Pietro; Mondragón, Raúl J; Bianconi, Ginestra

    2014-01-01

    One of the most important challenges in network science is to quantify the information encoded in complex network structures. Disentangling randomness from organizational principles is even more demanding when networks have a multiplex nature. Multiplex networks are multilayer systems of [Formula: see text] nodes that can be linked in multiple interacting and co-evolving layers. In these networks, relevant information might not be captured if the single layers were analyzed separately. Here we demonstrate that such partial analysis of layers fails to capture significant correlations between weights and topology of complex multiplex networks. To this end, we study two weighted multiplex co-authorship and citation networks involving the authors included in the American Physical Society. We show that in these networks weights are strongly correlated with multiplex structure, and provide empirical evidence in favor of the advantage of studying weighted measures of multiplex networks, such as multistrength and the inverse multiparticipation ratio. Finally, we introduce a theoretical framework based on the entropy of multiplex ensembles to quantify the information stored in multiplex networks that would remain undetected if the single layers were analyzed in isolation.

  13. Branching toughens fibrous networks.

    PubMed

    Koh, C T; Oyen, M L

    2012-08-01

    Fibrous collagenous networks are not only stiff but also tough, due to their complex microstructures. This stiff yet tough behavior is desirable for both medical and military applications but it is difficult to reproduce in engineering materials. While the nonlinear hyperelastic behavior of fibrous networks has been extensively studied, the understanding of toughness is still incomplete. Here, we identify a microstructure mimicking the branched bundles of a natural type I collagen network, in which partially cross-linked long fibers give rise to novel combinations of stiffness and toughness. Finite element analysis shows that the stiffness of fully cross-linked fibrous networks is amplified by increasing the fibril length and cross-link density. However, a trade-off of such stiff networks is reduced toughness. By having partially cross-linked networks with long fibrils, the networks have comparable stiffness and improved toughness as compared to the fully cross-linked networks. Further, the partially cross-linked networks avoid the formation of kinks, which cause fibril rupture during deformation. As a result, the branching allows the networks to have stiff yet tough behavior.

  14. Weighted Multiplex Networks

    PubMed Central

    Menichetti, Giulia; Remondini, Daniel; Panzarasa, Pietro; Mondragón, Raúl J.; Bianconi, Ginestra

    2014-01-01

    One of the most important challenges in network science is to quantify the information encoded in complex network structures. Disentangling randomness from organizational principles is even more demanding when networks have a multiplex nature. Multiplex networks are multilayer systems of nodes that can be linked in multiple interacting and co-evolving layers. In these networks, relevant information might not be captured if the single layers were analyzed separately. Here we demonstrate that such partial analysis of layers fails to capture significant correlations between weights and topology of complex multiplex networks. To this end, we study two weighted multiplex co-authorship and citation networks involving the authors included in the American Physical Society. We show that in these networks weights are strongly correlated with multiplex structure, and provide empirical evidence in favor of the advantage of studying weighted measures of multiplex networks, such as multistrength and the inverse multiparticipation ratio. Finally, we introduce a theoretical framework based on the entropy of multiplex ensembles to quantify the information stored in multiplex networks that would remain undetected if the single layers were analyzed in isolation. PMID:24906003

  15. A network security monitor

    SciTech Connect

    Heberlein, L.T.; Dias, G.V.; Levitt, K.N.; Mukherjee, B.; Wood, J.; Wolber, D. . Dept. of Electrical Engineering and Computer Science)

    1989-11-01

    The study of security in computer networks is a rapidly growing area of interest because of the proliferation of networks and the paucity of security measures in most current networks. Since most networks consist of a collection of inter-connected local area networks (LANs), this paper concentrates on the security-related issues in a single broadcast LAN such as Ethernet. Specifically, we formalize various possible network attacks and outline methods of detecting them. Our basic strategy is to develop profiles of usage of network resources and then compare current usage patterns with the historical profile to determine possible security violations. Thus, our work is similar to the host-based intrusion-detection systems such as SRI's IDES. Different from such systems, however, is our use of a hierarchical model to refine the focus of the intrusion-detection mechanism. We also report on the development of our experimental LAN monitor currently under implementation. Several network attacks have been simulated and results on how the monitor has been able to detect these attacks are also analyzed. Initial results demonstrate that many network attacks are detectable with our monitor, although it can surely be defeated. Current work is focusing on the integration of network monitoring with host-based techniques. 20 refs., 2 figs.

  16. Collaborative learning in networks.

    PubMed

    Mason, Winter; Watts, Duncan J

    2012-01-17

    Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions.

  17. Compressive Network Analysis

    PubMed Central

    Jiang, Xiaoye; Yao, Yuan; Liu, Han; Guibas, Leonidas

    2014-01-01

    Modern data acquisition routinely produces massive amounts of network data. Though many methods and models have been proposed to analyze such data, the research of network data is largely disconnected with the classical theory of statistical learning and signal processing. In this paper, we present a new framework for modeling network data, which connects two seemingly different areas: network data analysis and compressed sensing. From a nonparametric perspective, we model an observed network using a large dictionary. In particular, we consider the network clique detection problem and show connections between our formulation with a new algebraic tool, namely Randon basis pursuit in homogeneous spaces. Such a connection allows us to identify rigorous recovery conditions for clique detection problems. Though this paper is mainly conceptual, we also develop practical approximation algorithms for solving empirical problems and demonstrate their usefulness on real-world datasets. PMID:25620806

  18. NASA Communications Augmentation network

    NASA Technical Reports Server (NTRS)

    Omidyar, Guy C.; Butler, Thomas E.; Laios, Straton C.

    1990-01-01

    The NASA Communications (Nascom) Division of the Mission Operations and Data Systems Directorate (MO&DSD) is to undertake a major initiative to develop the Nascom Augmentation (NAUG) network to achieve its long-range service objectives for operational data transport to support the Space Station Freedom Program, the Earth Observing System (EOS), and other projects. The NAUG is the Nascom ground communications network being developed to accommodate the operational traffic of the mid-1990s and beyond. The NAUG network development will be based on the Open Systems Interconnection Reference Model (OSI-RM). This paper describes the NAUG network architecture, subsystems, topology, and services; addresses issues of internetworking the Nascom network with other elements of the Space Station Information System (SSIS); discusses the operations environment. This paper also notes the areas of related research and presents the current conception of how the network will provide broadband services in 1998.

  19. Reconfigureable network node

    DOEpatents

    Vanderveen, Keith B.; Talbot, Edward B.; Mayer, Laurence E.

    2008-04-08

    Nodes in a network having a plurality of nodes establish communication links with other nodes using available transmission media, as the ability to establish such links becomes available and desirable. The nodes predict when existing communications links will fail, become overloaded or otherwise degrade network effectiveness and act to establish substitute or additional links before the node's ability to communicate with the other nodes on the network is adversely affected. A node stores network topology information and programmed link establishment rules and criteria. The node evaluates characteristics that predict existing links with other nodes becoming unavailable or degraded. The node then determines whether it can form a communication link with a substitute node, in order to maintain connectivity with the network. When changing its communication links, a node broadcasts that information to the network. Other nodes update their stored topology information and consider the updated topology when establishing new communications links for themselves.

  20. Compressive Network Analysis.

    PubMed

    Jiang, Xiaoye; Yao, Yuan; Liu, Han; Guibas, Leonidas

    2014-11-01

    Modern data acquisition routinely produces massive amounts of network data. Though many methods and models have been proposed to analyze such data, the research of network data is largely disconnected with the classical theory of statistical learning and signal processing. In this paper, we present a new framework for modeling network data, which connects two seemingly different areas: network data analysis and compressed sensing. From a nonparametric perspective, we model an observed network using a large dictionary. In particular, we consider the network clique detection problem and show connections between our formulation with a new algebraic tool, namely Randon basis pursuit in homogeneous spaces. Such a connection allows us to identify rigorous recovery conditions for clique detection problems. Though this paper is mainly conceptual, we also develop practical approximation algorithms for solving empirical problems and demonstrate their usefulness on real-world datasets.

  1. MSAT network architecture

    NASA Technical Reports Server (NTRS)

    Davies, N. G.; Skerry, B.

    1990-01-01

    The Mobile Satellite (MSAT) communications system will support mobile voice and data services using circuit switched and packet switched facilities with interconnection to the public switched telephone network and private networks. Control of the satellite network will reside in a Network Control System (NCS) which is being designed to be extremely flexible to provide for the operation of the system initially with one multi-beam satellite, but with capability to add additional satellites which may have other beam configurations. The architecture of the NCS is described. The signalling system must be capable of supporting the protocols for the assignment of circuits for mobile public telephone and private network calls as well as identifying packet data networks. The structure of a straw-man signalling system is discussed.

  2. Distributed network scheduling

    NASA Technical Reports Server (NTRS)

    Clement, Bradley J.; Schaffer, Steven R.

    2004-01-01

    Distributed Network Scheduling is the scheduling of future communications of a network by nodes in the network. This report details software for doing this onboard spacecraft in a remote network. While prior work on distributed scheduling has been applied to remote spacecraft networks, the software reported here focuses on modeling communication activities in greater detail and including quality of service constraints. Our main results are based on a Mars network of spacecraft and include identifying a maximum opportunity of improving traverse exploration rate a factor of three; a simulation showing reduction in one-way delivery times from a rover to Earth from as much as 5 to 1.5 hours; simulated response to unexpected events averaging under an hour onboard; and ground schedule generation ranging from seconds to 50 minutes for 15 to 100 communication goals.

  3. Expert networks in CLIPS

    NASA Technical Reports Server (NTRS)

    Hruska, S. I.; Dalke, A.; Ferguson, J. J.; Lacher, R. C.

    1991-01-01

    Rule-based expert systems may be structurally and functionally mapped onto a special class of neural networks called expert networks. This mapping lends itself to adaptation of connectionist learning strategies for the expert networks. A parsing algorithm to translate C Language Integrated Production System (CLIPS) rules into a network of interconnected assertion and operation nodes has been developed. The translation of CLIPS rules to an expert network and back again is illustrated. Measures of uncertainty similar to those rules in MYCIN-like systems are introduced into the CLIPS system and techniques for combining and hiring nodes in the network based on rule-firing with these certainty factors in the expert system are presented. Several learning algorithms are under study which automate the process of attaching certainty factors to rules.

  4. Immunization of complex networks

    NASA Astrophysics Data System (ADS)

    Pastor-Satorras, Romualdo; Vespignani, Alessandro

    2002-03-01

    Complex networks such as the sexual partnership web or the Internet often show a high degree of redundancy and heterogeneity in their connectivity properties. This peculiar connectivity provides an ideal environment for the spreading of infective agents. Here we show that the random uniform immunization of individuals does not lead to the eradication of infections in all complex networks. Namely, networks with scale-free properties do not acquire global immunity from major epidemic outbreaks even in the presence of unrealistically high densities of randomly immunized individuals. The absence of any critical immunization threshold is due to the unbounded connectivity fluctuations of scale-free networks. Successful immunization strategies can be developed only by taking into account the inhomogeneous connectivity properties of scale-free networks. In particular, targeted immunization schemes, based on the nodes' connectivity hierarchy, sharply lower the network's vulnerability to epidemic attacks.

  5. Seven Deadliest Network Attacks

    SciTech Connect

    Prowell, Stacy J; Borkin, Michael; Kraus, Robert

    2010-05-01

    Do you need to keep up with the latest hacks, attacks, and exploits effecting networks? Then you need "Seven Deadliest Network Attacks". This book pinpoints the most dangerous hacks and exploits specific to networks, laying out the anatomy of these attacks including how to make your system more secure. You will discover the best ways to defend against these vicious hacks with step-by-step instruction and learn techniques to make your computer and network impenetrable. Attacks detailed in this book include: Denial of Service; War Dialing; Penetration 'Testing'; Protocol Tunneling; Spanning Tree Attacks; Man-in-the-Middle; and, Password Replay. Knowledge is power, find out about the most dominant attacks currently waging war on computers and networks globally. Discover the best ways to defend against these vicious attacks; step-by-step instruction shows you how. Institute countermeasures, don't be caught defenseless again, learn techniques to make your computer and network impenetrable.

  6. Professional social networking.

    PubMed

    Rowley, Robert D

    2014-12-01

    We review the current state of social communication between healthcare professionals, the role of consumer social networking, and some emerging technologies to address the gaps. In particular, the review covers (1) the current state of loose social networking for continuing medical education (CME) and other broadcast information dissemination; (2) social networking for business promotion; (3) social networking for peer collaboration, including simple communication as well as more robust data-centered collaboration around patient care; and (4) engaging patients on social platforms, including integrating consumer-originated data into the mix of healthcare data. We will see how, as the nature of healthcare delivery moves from the institution-centric way of tradition to a more social and networked ambulatory pattern that we see emerging today, the nature of health IT has also moved from enterprise-centric systems to more socially networked, cloud-based options.

  7. Oscillations of complex networks

    NASA Astrophysics Data System (ADS)

    Wang, Xingang; Lai, Ying-Cheng; Lai, Choy Heng

    2006-12-01

    A complex network processing information or physical flows is usually characterized by a number of macroscopic quantities such as the diameter and the betweenness centrality. An issue of significant theoretical and practical interest is how such quantities respond to sudden changes caused by attacks or disturbances in recoverable networks, i.e., functions of the affected nodes are only temporarily disabled or partially limited. By introducing a model to address this issue, we find that, for a finite-capacity network, perturbations can cause the network to oscillate persistently in the sense that the characterizing quantities vary periodically or randomly with time. We provide a theoretical estimate of the critical capacity-parameter value for the onset of the network oscillation. The finding is expected to have broad implications as it suggests that complex networks may be structurally highly dynamic.

  8. The optimation of random network coding in wireless MESH networks

    NASA Astrophysics Data System (ADS)

    Pang, Chunjiang; Pan, Xikun

    2013-03-01

    In order to improve the efficiency of wireless mesh network transmission, this paper focused on the network coding technology. Using network coding can significantly increase the wireless mesh network's throughput, but it will inevitably increase the computational complexity to the network, and the traditional linear network coding algorithm requires the aware of the whole network topology, which is impossible in the ever-changing topology of wireless mesh networks. In this paper, we use a distributed network coding strategy: random network coding, which don't need to know the whole topology of the network. In order to decrease the computation complexity, this paper suggests an improved strategy for random network coding: Do not code the packets which bring no good to the whole transmission. In this paper, we list several situations which coding is not necessary. Simulation results show that applying these strategies can improve the efficiency of wireless mesh network transmission.

  9. The Unesco/UIE Literacy Network: A Network of Networks.

    ERIC Educational Resources Information Center

    Giere, Ursula

    In order to achieve significant results, crucial criteria for stabilizing a network's capacity for dialog are high levels of commitment to offer high quality knowledge, two-way translation from research knowledge to practitioners and from practice to researchers, a maximum size, face-to-face communication, infrastructure, and funds for…

  10. Tomography using neural networks

    NASA Astrophysics Data System (ADS)

    Demeter, G.

    1997-03-01

    We have utilized neural networks for fast evaluation of tomographic data on the MT-1M tokamak. The networks have proven useful in providing the parameters of a nonlinear fit to experimental data, producing results in a fraction of the time required for performing the nonlinear fit. Time required for training the networks makes the method worth applying only if a substantial amount of data are to be evaluated.

  11. NASA Integrated Network COOP

    NASA Technical Reports Server (NTRS)

    Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

    2012-01-01

    Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

  12. The deep space network

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The objectives, functions, and organization of the Deep Space Network are summarized along with deep space station, ground communication, and network operations control capabilities. Mission support of ongoing planetary/interplanetary flight projects is discussed with emphasis on Viking orbiter radio frequency compatibility tests, the Pioneer Venus orbiter mission, and Helios-1 mission status and operations. Progress is also reported in tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations.

  13. The Deep Space Network

    NASA Technical Reports Server (NTRS)

    1974-01-01

    The objectives, functions, and organization, of the Deep Space Network are summarized. Deep Space stations, ground communications, and network operations control capabilities are described. The network is designed for two-way communications with unmanned spacecraft traveling approximately 1600 km from earth to the farthest planets in the solar system. It has provided tracking and data acquisition support for the following projects: Ranger, Surveyor, Mariner, Pioneer, Apollo, Helios, Viking, and the Lunar Orbiter.

  14. Disrupting Syrian Economic Networks

    DTIC Science & Technology

    2015-10-28

    Privileged Networks, which support regime survival, and the War Economy , which sustains both sides of the Civil War as well as the Islamic State of...Iraq and the Levant (ISIL). Methods of attacking these networks utilizing concepts from the information economy such as Disruptive Innovation...Syrian and regional economies . 15. SUBJECT TERMS Syria, Economy , Civil War, Privileged Network, War Economy , Islamic State, Disruptive Innovation

  15. Network problem threshold

    NASA Technical Reports Server (NTRS)

    Gejji, Raghvendra, R.

    1992-01-01

    Network transmission errors such as collisions, CRC errors, misalignment, etc. are statistical in nature. Although errors can vary randomly, a high level of errors does indicate specific network problems, e.g. equipment failure. In this project, we have studied the random nature of collisions theoretically as well as by gathering statistics, and established a numerical threshold above which a network problem is indicated with high probability.

  16. NASA Integrated Network COOP

    NASA Technical Reports Server (NTRS)

    Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

    2012-01-01

    Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

  17. Network operating system

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Long-term and short-term objectives for the development of a network operating system for the Space Station are stated. The short-term objective is to develop a prototype network operating system for a 100 megabit/second fiber optic data bus. The long-term objective is to establish guidelines for writing a detailed specification for a Space Station network operating system. Major milestones are noted. Information is given in outline form.

  18. Nonlinear Neural Network Oscillator.

    DTIC Science & Technology

    A nonlinear oscillator (10) includes a neural network (12) having at least one output (12a) for outputting a one dimensional vector. The neural ... neural network and the input of the input layer for modifying a magnitude and/or a polarity of the one dimensional output vector prior to the sample of...first or a second direction. Connection weights of the neural network are trained on a deterministic sequence of data from a chaotic source or may be a

  19. Neural Network Hurricane Tracker

    DTIC Science & Technology

    1998-05-27

    data about the hurricane and supplying the data to a trained neural network for yielding a predicted path for the hurricane. The system further includes...a device for displaying the predicted path of the hurricane. A method for using and training the neural network in the system is described. In the...method, the neural network is trained using information about hurricanes in a specific geographical area maintained in a database. The training involves

  20. Networks of Markovian Queues.

    DTIC Science & Technology

    1987-05-01

    8217There is a recognized need to make the subject of queueing network theory less esoteric.’ The engineer who is faced with an application often does not...112 5.3.2 Local Balance ..... a. ................................ 114 5.3.3 An Application of an Open Queueing Network ...Rate Case ....................... 125 5.3.2 Closed Networks ...................................... 127 * 5.4.3 An Application of Closed Queueing

  1. Exploring neural network technology

    SciTech Connect

    Naser, J.; Maulbetsch, J.

    1992-12-01

    EPRI is funding several projects to explore neural network technology, a form of artificial intelligence that some believe may mimic the way the human brain processes information. This research seeks to provide a better understanding of fundamental neural network characteristics and to identify promising utility industry applications. Results to date indicate that the unique attributes of neural networks could lead to improved monitoring, diagnostic, and control capabilities for a variety of complex utility operations. 2 figs.

  2. Albuquerque Basin seismic network

    USGS Publications Warehouse

    Jaksha, Lawrence H.; Locke, Jerry; Thompson, J.B.; Garcia, Alvin

    1977-01-01

    The U.S. Geological Survey has recently completed the installation of a seismic network around the Albuquerque Basin in New Mexico. The network consists of two seismometer arrays, a thirteen-station array monitoring an area of approximately 28,000 km 2 and an eight-element array monitoring the area immediately adjacent to the Albuquerque Seismological Laboratory. This report describes the instrumentation deployed in the network.

  3. Modelling dendritic ecological networks in space: An integrated network perspective

    Treesearch

    Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

    2013-01-01

    Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

  4. Network of Networks and the Climate System

    NASA Astrophysics Data System (ADS)

    Kurths, Jürgen; Boers, Niklas; Bookhagen, Bodo; Donges, Jonathan; Donner, Reik; Malik, Nishant; Marwan, Norbert; Stolbova, Veronika

    2013-04-01

    Network of networks is a new direction in complex systems science. One can find such networks in various fields, such as infrastructure (power grids etc.), human brain or Earth system. Basic properties and new characteristics, such as cross-degree, or cross-betweenness will be discussed. This allows us to quantify the structural role of single vertices or whole sub-networks with respect to the interaction of a pair of subnetworks on local, mesoscopic, and global topological scales. Next, we consider an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This technique is then applied to 3-dimensional data of the climate system. We interpret different heights in the atmosphere as different networks and the whole as a network of networks. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. The global scale view on climate networks offers promising new perspectives for detecting dynamical structures based on nonlinear physical processes in the climate system. This concept is applied to Indian Monsoon data in order to characterize the regional occurrence of strong rain events and its impact on predictability. References: Arenas, A., A. Diaz-Guilera, J. Kurths, Y. Moreno, and C. Zhou, Phys. Reports 2008, 469, 93. Donges, J., Y. Zou, N. Marwan, and J. Kurths, Europhys. Lett. 2009, 87, 48007. Donner, R., Y. Zou, J. Donges, N. Marwan, and J. Kurths, Phys. Rev. E 2010, 81, 015101(R ). Mokhov, I. I., D. A. Smirnov, P. I. Nakonechny, S. S. Kozlenko, E. P. Seleznev, and J. Kurths, Geophys. Res. Lett. 2011, 38, L00F04. Malik, N., B. Bookhagen, N. Marwan, and J. Kurths, Climate Dynamics, 2012, 39, 971. Donges, J., H. Schultz, N. Marwan, Y. Zou, J. Kurths, Eur. J. Phys. B 2011, 84, 635-651. Donges, J., R. Donner, M. Trauth, N. Marwan, H.J. Schellnhuber, and J. Kurths

  5. Effective professional networking.

    PubMed

    Goolsby, Mary Jo; Knestrick, Joyce M

    2017-08-01

    The reasons for nurse practitioners to develop a professional network are boundless and are likely to change over time. Networking opens doors and creates relationships that support new opportunities, personal development, collaborative research, policy activism, evidence-based practice, and more. Successful professional networking involves shared, mutually beneficial interactions between individuals and/or individuals and groups, regardless of whether it occurs face to face or electronically. This article combines nuggets from the literature with guidance based on the authors' combined experience in networking activities at the local, national, and international levels. ©2017 American Association of Nurse Practitioners.

  6. Mission Critical Networking

    SciTech Connect

    Eltoweissy, Mohamed Y.; Du, David H.C.; Gerla, Mario; Giordano, Silvia; Gouda, Mohamed; Schulzrinne, Henning; Youssef, Moustafa

    2010-06-01

    Mission-Critical Networking (MCN) refers to networking for application domains where life or livelihood may be at risk. Typical application domains for MCN include critical infrastructure protection and operation, emergency and crisis intervention, healthcare services, and military operations. Such networking is essential for safety, security and economic vitality in our complex world characterized by uncertainty, heterogeneity, emergent behaviors, and the need for reliable and timely response. MCN comprise networking technology, infrastructures and services that may alleviate the risk and directly enable and enhance connectivity for mission-critical information exchange among diverse, widely dispersed, mobile users.

  7. Power-functional network

    NASA Astrophysics Data System (ADS)

    Sun, Yong; Kurths, Jürgen; Zhan, Meng

    2017-08-01

    Power grids and their properties have been studied broadly in many aspects. In this paper, we propose a novel concept, power-flow-based power grid, as a typical power-functional network, based on the calculation of power flow distribution from power electrical engineering. We compare it with structural networks based on the shortest path length and effective networks based on the effective electrical distance and study the relationship among these three kinds of networks. We find that they have roughly positive correlations with each other, indicating that in general any close nodes in the topological structure are actually connected in function. However, we do observe some counter-examples that two close nodes in a structural network can have a long distance in a power-functional network, namely, two physically connected nodes can actually be separated in function. In addition, we find that power grids in the structural network tend to be heterogeneous, whereas those in the effective and power-functional networks tend to be homogeneous. These findings are expected to be significant not only for power grids but also for various other complex networks.

  8. Mobile Virtual Private Networking

    NASA Astrophysics Data System (ADS)

    Pulkkis, Göran; Grahn, Kaj; Mårtens, Mathias; Mattsson, Jonny

    Mobile Virtual Private Networking (VPN) solutions based on the Internet Security Protocol (IPSec), Transport Layer Security/Secure Socket Layer (SSL/TLS), Secure Shell (SSH), 3G/GPRS cellular networks, Mobile IP, and the presently experimental Host Identity Protocol (HIP) are described, compared and evaluated. Mobile VPN solutions based on HIP are recommended for future networking because of superior processing efficiency and network capacity demand features. Mobile VPN implementation issues associated with the IP protocol versions IPv4 and IPv6 are also evaluated. Mobile VPN implementation experiences are presented and discussed.

  9. Celestial data routing network

    NASA Astrophysics Data System (ADS)

    Bordetsky, Alex

    2000-11-01

    Imagine that information processing human-machine network is threatened in a particular part of the world. Suppose that an anticipated threat of physical attacks could lead to disruption of telecommunications network management infrastructure and access capabilities for small geographically distributed groups engaged in collaborative operations. Suppose that small group of astronauts are exploring the solar planet and need to quickly configure orbital information network to support their collaborative work and local communications. The critical need in both scenarios would be a set of low-cost means of small team celestial networking. To the geographically distributed mobile collaborating groups such means would allow to maintain collaborative multipoint work, set up orbital local area network, and provide orbital intranet communications. This would be accomplished by dynamically assembling the network enabling infrastructure of the small satellite based router, satellite based Codec, and set of satellite based intelligent management agents. Cooperating single function pico satellites, acting as agents and personal switching devices together would represent self-organizing intelligent orbital network of cooperating mobile management nodes. Cooperative behavior of the pico satellite based agents would be achieved by comprising a small orbital artificial neural network capable of learning and restructing the networking resources in response to the anticipated threat.

  10. Optical network democratization.

    PubMed

    Nejabati, Reza; Peng, Shuping; Simeonidou, Dimitra

    2016-03-06

    The current Internet infrastructure is not able to support independent evolution and innovation at physical and network layer functionalities, protocols and services, while at same time supporting the increasing bandwidth demands of evolving and heterogeneous applications. This paper addresses this problem by proposing a completely democratized optical network infrastructure. It introduces the novel concepts of the optical white box and bare metal optical switch as key technology enablers for democratizing optical networks. These are programmable optical switches whose hardware is loosely connected internally and is completely separated from their control software. To alleviate their complexity, a multi-dimensional abstraction mechanism using software-defined network technology is proposed. It creates a universal model of the proposed switches without exposing their technological details. It also enables a conventional network programmer to develop network applications for control of the optical network without specific technical knowledge of the physical layer. Furthermore, a novel optical network virtualization mechanism is proposed, enabling the composition and operation of multiple coexisting and application-specific virtual optical networks sharing the same physical infrastructure. Finally, the optical white box and the abstraction mechanism are experimentally evaluated, while the virtualization mechanism is evaluated with simulation.

  11. Generalized Communities in Networks

    NASA Astrophysics Data System (ADS)

    Newman, M. E. J.; Peixoto, Tiago P.

    2015-08-01

    A substantial volume of research is devoted to studies of community structure in networks, but communities are not the only possible form of large-scale network structure. Here, we describe a broad extension of community structure that encompasses traditional communities but includes a wide range of generalized structural patterns as well. We describe a principled method for detecting this generalized structure in empirical network data and demonstrate with real-world examples how it can be used to learn new things about the shape and meaning of networks.

  12. Mixing navigation on networks

    NASA Astrophysics Data System (ADS)

    Zhou, Tao

    2008-05-01

    In this article, we propose a mixing navigation mechanism, which interpolates between random-walk and shortest-path protocol. The navigation efficiency can be remarkably enhanced via a few routers. Some advanced strategies are also designed: For non-geographical scale-free networks, the targeted strategy with a tiny fraction of routers can guarantee an efficient navigation with low and stable delivery time almost independent of network size. For geographical localized networks, the clustering strategy can simultaneously increase efficiency and reduce the communication cost. The present mixing navigation mechanism is of significance especially for information organization of wireless sensor networks and distributed autonomous robotic systems.

  13. Future Optical Networks

    NASA Astrophysics Data System (ADS)

    O'Mahony, Michael J.; Politi, Christina; Klonidis, Dimitrios; Nejabati, Reza; Simeonidou, Dimitra

    2006-12-01

    This paper presents views on the future of optical networking. A historical look at the emergence of optical networking is first taken, followed by a discussion on the drivers pushing for a new and pervasive network, which is based on photonics and can satisfy the needs of a broadening base of residential, business, and scientific users. Regional plans and targets for optical networking are reviewed to understand which current approaches are judged important. Today, two thrusts are driving separate optical network infrastructure models, namely 1) the need by nations to provide a ubiquitous network infrastructure to support all the future services and telecommunication needs of residential and business users and 2) increasing demands by the scientific community for networks to support their requirements with respect to large-scale data transport and processing. This paper discusses these network models together with the key enabling technologies currently being considered for future implementation, including optical circuit, burst and packet switching, and optical code-division multiplexing. Critical subsystem functionalities are also reviewed. The discussion considers how these separate models might eventually merge to form a global optical network infrastructure.

  14. Telestroke network fundamentals.

    PubMed

    Meyer, Brett C; Demaerschalk, Bart M

    2012-10-01

    The objectives of this manuscript are to identify key components to maintaining the logistic and/or operational sustainability of a telestroke network, to identify best practices to be considered for assessment and management of acute stroke when planning for and developing a telestroke network, to show practical steps to enable progress toward implementing a telestroke solution for optimizing acute stroke care, to incorporate evidence-based practice guidelines and care pathways into a telestroke network, to emphasize technology variables and options, and to propose metrics to use when determining the performance, outcomes, and quality of a telestroke network. Copyright © 2012 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  15. Competing edge networks

    NASA Astrophysics Data System (ADS)

    Parsons, Mark; Grindrod, Peter

    2012-06-01

    We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, subject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other's growth and encourage the other's demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails.

  16. Entangled networks, synchronization, and optimal network topology.

    PubMed

    Donetti, Luca; Hurtado, Pablo I; Muñoz, Miguel A

    2005-10-28

    A new family of graphs, entangled networks, with optimal properties in many respects, is introduced. By definition, their topology is such that it optimizes synchronizability for many dynamical processes. These networks are shown to have an extremely homogeneous structure: degree, node distance, betweenness, and loop distributions are all very narrow. Also, they are characterized by a very interwoven (entangled) structure with short average distances, large loops, and no well-defined community structure. This family of nets exhibits an excellent performance with respect to other flow properties such as robustness against errors and attacks, minimal first-passage time of random walks, efficient communication, etc. These remarkable features convert entangled networks in a useful concept, optimal or almost optimal in many senses, and with plenty of potential applications in computer science or neuroscience.

  17. Better sales networks.

    PubMed

    Ustüner, Tuba; Godes, David

    2006-01-01

    Anyone in sales will tell you that social networks are critical. The more contacts you have, the more leads you'll generate, and, ultimately, the more sales you'll make. But that's a vast oversimplification. Different configurations of networks produce different results, and the salesperson who develops a nuanced understanding of social networks will outshine competitors. The salesperson's job changes over the course of the selling process. Different abilities are required in each stage of the sale: identifying prospects, gaining buy-in from potential customers, creating solutions, and closing the deal. Success in the first stage, for instance, depends on the salesperson acquiring precise and timely information about opportunities from contacts in the marketplace. Closing the deal requires the salesperson to mobilize contacts from prior sales to act as references. Managers often view sales networks only in terms of direct contacts. But someone who knows lots of people doesn't necessarily have an effective network because networks often pay off most handsomely through indirect contacts. Moreover, the density of the connections in a network is important. Do a salesperson's contacts know all the same people, or are their associates widely dispersed? Sparse networks are better, for example, at generating unique information. Managers can use three levers--sales force structure, compensation, and skills development--to encourage salespeople to adopt a network-based view and make the best possible use of social webs. For example, the sales force can be restructured to decouple lead generation from other tasks because some people are very good at building diverse ties but not so good at maintaining other kinds of networks. Companies that take steps of this kind to help their sales teams build better networks will reap tremendous advantages.

  18. Local Area Networks: Part II.

    ERIC Educational Resources Information Center

    Dessy, Raymond E., Ed.

    1982-01-01

    Discusses five approaches used by industry/colleges to provide local area network (LAN) capabilities in the analytical laboratory: (1) mixed baseband bus network coupled to a star net; (2) broadband bus network; (3) ring network; (4) star network coupled to broadband net; and (5) simple multiprocessor center. Part I (September issue) focused on…

  19. The Benefits of Grid Networks

    ERIC Educational Resources Information Center

    Tennant, Roy

    2005-01-01

    In the article, the author talks about the benefits of grid networks. In speaking of grid networks the author is referring to both networks of computers and networks of humans connected together in a grid topology. Examples are provided of how grid networks are beneficial today and the ways in which they have been used.

  20. Chaotic Neural Networks and Beyond

    NASA Astrophysics Data System (ADS)

    Aihara, Kazuyuki; Yamada, Taiji; Oku, Makito

    2013-01-01

    A chaotic neuron model which is closely related to deterministic chaos observed experimentally with squid giant axons is explained, and used to construct a chaotic neural network model. Further, such a chaotic neural network is extended to different chaotic models such as a largescale memory relation network, a locally connected network, a vector-valued network, and a quaternionic-valued neuron.

  1. Straight Talk About Local Networks.

    ERIC Educational Resources Information Center

    Green, John O.

    1984-01-01

    Networks confined to one classroom or several classrooms in one building are called local networks. The nature and uses of these networks, software needed to run a network, software problems, and potential problems are discussed. Information on commercially available networks (including source, cost, hardware/software provided, features, and…

  2. The Benefits of Grid Networks

    ERIC Educational Resources Information Center

    Tennant, Roy

    2005-01-01

    In the article, the author talks about the benefits of grid networks. In speaking of grid networks the author is referring to both networks of computers and networks of humans connected together in a grid topology. Examples are provided of how grid networks are beneficial today and the ways in which they have been used.

  3. Internationalisation Network: A Finnish Experience

    ERIC Educational Resources Information Center

    Kantola, Mauri; Hautala, Jouni

    2008-01-01

    One of the main issues of internationalisation is networking. The network way of action within higher education institutions (HEIs) represents new modes of the information work. Networks are worth evaluating more precisely in the future, and social network analysis (SNA) is a useful tool for this evaluation. This article describes the network of…

  4. Cascading Failures and Recovery in Networks of Networks

    NASA Astrophysics Data System (ADS)

    Havlin, Shlomo

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

  5. An approach for modeling vulnerability of the network of networks

    NASA Astrophysics Data System (ADS)

    Zhang, Jianhua; Song, Bo; Zhang, Zhaojun; Liu, Haikuan

    2014-10-01

    In this paper, a framework is given to model the network of networks and to investigate the vulnerability of the network of networks subjected to failures. Because there are several redundant systems in infrastructure systems, the dependent intensity between two networks is introduced and adopted to discuss the vulnerability of the interdependent infrastructure networks subjected to failures. Shanghai electrified rail transit network is used to illustrate the feasibility and effectiveness of the proposed framework. Because the rail network is dependent on the power grid and communication network, the corresponding power grid and communication network are also included in this system. Meanwhile the failures to the power grid and communication network are utilized to investigate the vulnerability of the rail network. The results show that the rail network strongly depends on the power grid and weakly depends on the communication network, and the transport functionality loss of the rail network increases with the increase of dependent intensity. Meanwhile the highest betweenness node-based attack to the power grid and the largest degree node-based attack to the communication network can result in the most functionality losses to the rail network. Moreover, the functionality loss of the rail network has the smallest value when the tolerance parameter of the power grid equals 0.75 and the critical nodes of the power grid and communication network can be obtained by simulations.

  6. Identification of Topological Network Modules in Perturbed Protein Interaction Networks.

    PubMed

    Sardiu, Mihaela E; Gilmore, Joshua M; Groppe, Brad; Florens, Laurence; Washburn, Michael P

    2017-03-08

    Biological networks consist of functional modules, however detecting and characterizing such modules in networks remains challenging. Perturbing networks is one strategy for identifying modules. Here we used an advanced mathematical approach named topological data analysis (TDA) to interrogate two perturbed networks. In one, we disrupted the S. cerevisiae INO80 protein interaction network by isolating complexes after protein complex components were deleted from the genome. In the second, we reanalyzed previously published data demonstrating the disruption of the human Sin3 network with a histone deacetylase inhibitor. Here we show that disrupted networks contained topological network modules (TNMs) with shared properties that mapped onto distinct locations in networks. We define TMNs as proteins that occupy close network positions depending on their coordinates in a topological space. TNMs provide new insight into networks by capturing proteins from different categories including proteins within a complex, proteins with shared biological functions, and proteins disrupted across networks.

  7. Identification of Topological Network Modules in Perturbed Protein Interaction Networks

    PubMed Central

    Sardiu, Mihaela E.; Gilmore, Joshua M.; Groppe, Brad; Florens, Laurence; Washburn, Michael P.

    2017-01-01

    Biological networks consist of functional modules, however detecting and characterizing such modules in networks remains challenging. Perturbing networks is one strategy for identifying modules. Here we used an advanced mathematical approach named topological data analysis (TDA) to interrogate two perturbed networks. In one, we disrupted the S. cerevisiae INO80 protein interaction network by isolating complexes after protein complex components were deleted from the genome. In the second, we reanalyzed previously published data demonstrating the disruption of the human Sin3 network with a histone deacetylase inhibitor. Here we show that disrupted networks contained topological network modules (TNMs) with shared properties that mapped onto distinct locations in networks. We define TMNs as proteins that occupy close network positions depending on their coordinates in a topological space. TNMs provide new insight into networks by capturing proteins from different categories including proteins within a complex, proteins with shared biological functions, and proteins disrupted across networks. PMID:28272416

  8. Wireless Sensor Networks Approach

    NASA Technical Reports Server (NTRS)

    Perotti, Jose M.

    2003-01-01

    This viewgraph presentation provides information on hardware and software configurations for a network architecture for sensors. The hardware configuration uses a central station and remote stations. The software configuration uses the 'lost station' software algorithm. The presentation profiles a couple current examples of this network architecture in use.

  9. Wireless Sensors Network (Sensornet)

    NASA Technical Reports Server (NTRS)

    Perotti, J.

    2003-01-01

    The Wireless Sensor Network System presented in this paper provides a flexible reconfigurable architecture that could be used in a broad range of applications. It also provides a sensor network with increased reliability; decreased maintainability costs, and assured data availability by autonomously and automatically reconfiguring to overcome communication interferences.

  10. Reciprocity of weighted networks

    PubMed Central

    Squartini, Tiziano; Picciolo, Francesco; Ruzzenenti, Franco; Garlaschelli, Diego

    2013-01-01

    In directed networks, reciprocal links have dramatic effects on dynamical processes, network growth, and higher-order structures such as motifs and communities. While the reciprocity of binary networks has been extensively studied, that of weighted networks is still poorly understood, implying an ever-increasing gap between the availability of weighted network data and our understanding of their dyadic properties. Here we introduce a general approach to the reciprocity of weighted networks, and define quantities and null models that consistently capture empirical reciprocity patterns at different structural levels. We show that, counter-intuitively, previous reciprocity measures based on the similarity of mutual weights are uninformative. By contrast, our measures allow to consistently classify different weighted networks according to their reciprocity, track the evolution of a network's reciprocity over time, identify patterns at the level of dyads and vertices, and distinguish the effects of flux (im)balances or other (a)symmetries from a true tendency towards (anti-)reciprocation. PMID:24056721

  11. Local Area Networks.

    ERIC Educational Resources Information Center

    Bullard, David

    1983-01-01

    The proliferation of word processors, micro- and minicomputer systems, and other digital office equipment is causing major design changes in existing networks. Local Area Networks (LANs) which have adequately served terminal users in the past must now be redesigned. Implementation at Clemson is described. (MLW)

  12. Local Area Networks.

    ERIC Educational Resources Information Center

    Marks, Kenneth E.; Nielsen, Steven

    1991-01-01

    Discusses cabling that is needed in local area networks (LANs). Types of cables that may be selected are described, including twisted pair, coaxial cables (or ethernet), and fiber optics; network topologies, the manner in which the cables are laid out, are considered; and cable installation issues are discussed. (LRW)

  13. Making friends versus networking

    NASA Astrophysics Data System (ADS)

    Williams, Heather

    2013-03-01

    Marc Kuchner's article on the importance to one's career of making friends, rather than merely "networking" (February pp44-45) said more about a rather strange form of networking - based on collecting signatures from strangers at a conference - than it did about how best to develop professional relationships.

  14. The deep space network

    NASA Technical Reports Server (NTRS)

    1974-01-01

    The progress is reported of Deep Space Network (DSN) research in the following areas: (1) flight project support, (2) spacecraft/ground communications, (3) station control and operations technology, (4) network control and processing, and (5) deep space stations. A description of the DSN functions and facilities is included.

  15. Teacher Networks Companion Piece

    ERIC Educational Resources Information Center

    Hopkins, Ami Patel; Rulli, Carolyn; Schiff, Daniel; Fradera, Marina

    2015-01-01

    Network building vitally impacts career development, but in few professions does it impact daily practice more than in teaching. Teacher networks, known as professional learning communities, communities of practice, peer learning circles, virtual professional communities, as well as other names, play a unique and powerful role in education. In…

  16. Networked Teaching and Learning.

    ERIC Educational Resources Information Center

    Benson, Chris, Ed.

    2002-01-01

    This theme issue on networked teaching and learning contains 11 articles written by teachers of English and language arts in Bread Loaf's primarily rural, teacher networks. Most of these narratives describe how teachers have taught writing and literature using online exchanges or teleconferencing involving students in different locations and grade…

  17. The Deep Space Network

    NASA Technical Reports Server (NTRS)

    1979-01-01

    Deep Space Network progress in flight project support, tracking and data acquisition, research and technology, network engineering, hardware and software implementation, and operations is cited. Topics covered include: tracking and ground based navigation; spacecraft/ground communication; station control and operations technology; ground communications; and deep space stations.

  18. Hanford Seismic Network

    SciTech Connect

    Reidel, S.P.; Hartshorn, D.C.

    1997-05-01

    This report describes the Hanford Seismic Network. The network consists of two instrument arrays: seismometers and strong motion accelerometers. The seismometers determine the location and magnitude of earthquakes, and the strong motion accelerometers determine ground motion. Together these instruments arrays comply with the intent of DOE Order 5480.20, Natural Phenomena Hazards Mitigation.

  19. Community Wireless Networks

    ERIC Educational Resources Information Center

    Feld, Harold

    2005-01-01

    With increasing frequency, communities are seeing the arrival of a new class of noncommercial broadband providers: community wireless networks (CWNs). Utilizing the same wireless technologies that many colleges and universities have used to create wireless networks on campus, CWNs are creating broadband access for free or at costs well below…

  20. Academe's New Girl Network

    ERIC Educational Resources Information Center

    Stent, Angela

    1978-01-01

    A "networking" processing pioneered by the Committee for the Concerns of Women in New England Colleges and Universities, which is establishing a New Girl network to compete with and eventually mesh with the Old Boy system, is described. Lobbying and conference efforts of HERS (Higher Education Resource Services) are reported. (LBH)

  1. Telecommunications network optimization

    NASA Technical Reports Server (NTRS)

    Lee, J.

    1979-01-01

    Analysis discusses STACOM (state criminal justic communication) network topology program used to design and evaluate digital telecommunications networks STACOM employs ESAU-WILLIAMS technique to search for direct links between system terminations and regional switching center. Inputs include traffic data, terminal locations, and functional requirements.

  2. CAISSON: Interconnect Network Simulator

    NASA Technical Reports Server (NTRS)

    Springer, Paul L.

    2006-01-01

    Cray response to HPCS initiative. Model future petaflop computer interconnect. Parallel discrete event simulation techniques for large scale network simulation. Built on WarpIV engine. Run on laptop and Altix 3000. Can be sized up to 1000 simulated nodes per host node. Good parallel scaling characteristics. Flexible: multiple injectors, arbitration strategies, queue iterators, network topologies.

  3. A Balanced Memory Network

    PubMed Central

    Roudi, Yasser; Latham, Peter E

    2007-01-01

    A fundamental problem in neuroscience is understanding how working memory—the ability to store information at intermediate timescales, like tens of seconds—is implemented in realistic neuronal networks. The most likely candidate mechanism is the attractor network, and a great deal of effort has gone toward investigating it theoretically. Yet, despite almost a quarter century of intense work, attractor networks are not fully understood. In particular, there are still two unanswered questions. First, how is it that attractor networks exhibit irregular firing, as is observed experimentally during working memory tasks? And second, how many memories can be stored under biologically realistic conditions? Here we answer both questions by studying an attractor neural network in which inhibition and excitation balance each other. Using mean-field analysis, we derive a three-variable description of attractor networks. From this description it follows that irregular firing can exist only if the number of neurons involved in a memory is large. The same mean-field analysis also shows that the number of memories that can be stored in a network scales with the number of excitatory connections, a result that has been suggested for simple models but never shown for realistic ones. Both of these predictions are verified using simulations with large networks of spiking neurons. PMID:17845070

  4. Security of Sensor Networks

    DTIC Science & Technology

    2006-06-01

    8 2. Message Confidentiality ........................................................................8 3. Message Integrity...SUMMARY Security in sensor networks is an active but wide-open research field. Past experiences with other wireless technologies have shown that...layer security because, like other wireless networking technologies , the threat of interception by an adversary is always present. The security

  5. The Deep Space Network

    NASA Technical Reports Server (NTRS)

    1988-01-01

    The Deep Space Network (DSN) is the largest and most sensitive scientific telecommunications and radio navigation network in the world. Its principal responsibilities are to support unmanned interplanetary spacecraft missions and to support radio and radar astronomy observations in the exploration of the solar system and the universe. The DSN facilities and capabilities as of January 1988 are described.

  6. Classroom Computer Network.

    ERIC Educational Resources Information Center

    Lent, John

    1984-01-01

    This article describes a computer network system that connects several microcomputers to a single disk drive and one copy of software. Many schools are switching to networks as a cheaper and more efficient means of computer instruction. Teachers may be faced with copywriting problems when reproducing programs. (DF)

  7. The Community Networking Handbook.

    ERIC Educational Resources Information Center

    Bajjaly, Stephen T.

    This publication outlines the complete community networking process: planning, developing partnerships, funding, marketing, content, public access, and evaluation, and discusses the variety of roles that the local public library can play in this process. Chapter One, "The Importance of Community Networking," describes the importance of community…

  8. Hubless satellite communications networks

    NASA Technical Reports Server (NTRS)

    Robinson, Peter Alan

    1994-01-01

    Frequency Comb Multiple Access (FCMA) is a new combined modulation and multiple access method which will allow cheap hubless Very Small Aperture Terminal (VSAT) networks to be constructed. Theoretical results show bandwidth efficiency and power efficiency improvements over other modulation and multiple access methods. Costs of the VSAT network are reduced dramatically since a hub station is not required.

  9. Community Wireless Networks

    ERIC Educational Resources Information Center

    Feld, Harold

    2005-01-01

    With increasing frequency, communities are seeing the arrival of a new class of noncommercial broadband providers: community wireless networks (CWNs). Utilizing the same wireless technologies that many colleges and universities have used to create wireless networks on campus, CWNs are creating broadband access for free or at costs well below…

  10. Electrical Networks: An Introduction

    NASA Astrophysics Data System (ADS)

    Pahwa, S.; Youssef, M.; Scoglio, C.

    A world without electricity is beyond our imagination. Starting from the prehistoric times, man has made much progress in every walk of life. We have become accustomed to getting everything at the flick of a switch, touch of a button, or turn of a knob. While we have become so used to enjoying the benefits of electricity, it is not easy to imagine how electricity travels from its source to our homes and offices. It sometimes has to cover large distances through a complex network of transmission lines and power substations to provide us the facilities and entertainment that we take for granted. This network which transports electricity from the source to the consumers is called the electrical network. The electrical network is a collective term for different components such as transformers, transmission lines, substations, and different stages and sub-networks devoted to generation, transmission, and distribution. Sometimes, there may be sub-transmission and secondary distribution networks too. A simple schematic of an electric network is shown in Fig. 8.1. In the past decade, analysis of the electrical power system as a complex network has been an evolving and challenging topic of research.

  11. The protein folding network

    NASA Astrophysics Data System (ADS)

    Rao, Francesco; Caflisch, Amedeo

    2004-03-01

    Networks are everywhere. The conformation space of a 20-residue antiparallel beta-sheet peptide [1], sampled by molecular dynamics simulations, is mapped to a network. Conformations are nodes of the network, and the transitions between them are links. As previously found for the World-Wide Web as well as for social and biological networks , the conformation space contains highly connected hubs like the native state which is the most populated free energy basin. Furthermore, the network shows a hierarchical modularity [2] which is consistent with the funnel mechanism of folding [3] and is not observed for a random heteropolymer lacking a native state. Here we show that the conformation space network describes the free energy landscape without requiring projections into arbitrarily chosen reaction coordinates. The network analysis provides a basis for understanding the heterogeneity of the folding transition state and the existence of multiple pathways. [1] P. Ferrara and A. Caflisch, Folding simulations of a three-stranded antiparallel beta-sheet peptide, PNAS 97, 10780-10785 (2000). [2] Ravasz, E. and Barabási, A. L. Hierarchical organization in complex networks. Phys. Rev. E 67, 026112 (2003). [3] Dill, K. and Chan, H From Levinthal to pathways to funnels. Nature Struct. Biol. 4, 10-19 (1997)

  12. Information Networks in Biomedicine

    ERIC Educational Resources Information Center

    Millard, William L.

    1975-01-01

    Describes current biomedical information networks, focusing on those with an educational function, and elaborates on the problems encountered in planning, implementing, utilizing and evaluating such networks. Journal of Biocommunication, T. Banks, Educ. TV-431N, U. of Calif., San Francisco 94143. Subscription Rates: individuals and libraries,…

  13. Rural Information Network.

    ERIC Educational Resources Information Center

    National Public Telecomputing Network, Cleveland, OH.

    This report describes the National Public Telecomputing Network's (NPTN) development of free, public-access, community computer systems throughout the United States. It also provides information on how to initiate a "Free-Net" through the Rural Information Network. Free-Nets are multi-user systems with some of the power and…

  14. Network Difficulties: Stand By.

    ERIC Educational Resources Information Center

    Oborn, Richard L.

    This document traces the development of Federal Communications Commission (FCC) network regulations from their beginning in 1941 with the "Report on Chain Broadcasting." The eight rules defined by the report were aimed at correcting network abuses and were intended to maintain community broadcasting in the public interest. The document…

  15. Programming neural networks

    SciTech Connect

    Anderson, J.A.; Markman, A.B.; Viscuso, S.R.; Wisniewski, E.J.

    1988-09-01

    Neural networks ''compute'' though not in the way that traditional computers do. One must accept their weaknesses to use their strengths. The authors present several applications of a particular non-linear network (the BSB model) to illustrate some of the peculiarities inherent in this architecture.

  16. Optimal Phase Oscillatory Network

    NASA Astrophysics Data System (ADS)

    Follmann, Rosangela

    2013-03-01

    Important topics as preventive detection of epidemics, collective self-organization, information flow and systemic robustness in clusters are typical examples of processes that can be studied in the context of the theory of complex networks. It is an emerging theory in a field, which has recently attracted much interest, involving the synchronization of dynamical systems associated to nodes, or vertices, of the network. Studies have shown that synchronization in oscillatory networks depends not only on the individual dynamics of each element, but also on the combination of the topology of the connections as well as on the properties of the interactions of these elements. Moreover, the response of the network to small damages, caused at strategic points, can enhance the global performance of the whole network. In this presentation we explore an optimal phase oscillatory network altered by an additional term in the coupling function. The application to associative-memory network shows improvement on the correct information retrieval as well as increase of the storage capacity. The inclusion of some small deviations on the nodes, when solutions are attracted to a false state, results in additional enhancement of the performance of the associative-memory network. Supported by FAPESP - Sao Paulo Research Foundation, grant number 2012/12555-4

  17. Telecommunications network optimization

    NASA Technical Reports Server (NTRS)

    Lee, J.

    1979-01-01

    Analysis discusses STACOM (state criminal justic communication) network topology program used to design and evaluate digital telecommunications networks STACOM employs ESAU-WILLIAMS technique to search for direct links between system terminations and regional switching center. Inputs include traffic data, terminal locations, and functional requirements.

  18. Multimedia Networks: Mission Impossible?

    ERIC Educational Resources Information Center

    Weiss, Andrew M.

    1996-01-01

    Running multimedia on a network, often difficult because of the memory and processing power required, is becoming easier thanks to new protocols and products. Those developing network design criteria may wish to consider making use of Fast Ethernet, Asynchronous Transfer Method (ATM), switches, "fat pipes", additional network…

  19. The Ontario CAI Network.

    ERIC Educational Resources Information Center

    Olivier, W. P.

    The evolution and current operation of the Ontario Computer Assisted Instruction (CAI) Network are described. Sponsored by the Ontario Institute for Studies in Education and including 11 community colleges in Ontario, the network has computer installations and access devices throughout the province. Initial development work was done using a…

  20. A balanced memory network.

    PubMed

    Roudi, Yasser; Latham, Peter E

    2007-09-01

    A fundamental problem in neuroscience is understanding how working memory--the ability to store information at intermediate timescales, like tens of seconds--is implemented in realistic neuronal networks. The most likely candidate mechanism is the attractor network, and a great deal of effort has gone toward investigating it theoretically. Yet, despite almost a quarter century of intense work, attractor networks are not fully understood. In particular, there are still two unanswered questions. First, how is it that attractor networks exhibit irregular firing, as is observed experimentally during working memory tasks? And second, how many memories can be stored under biologically realistic conditions? Here we answer both questions by studying an attractor neural network in which inhibition and excitation balance each other. Using mean-field analysis, we derive a three-variable description of attractor networks. From this description it follows that irregular firing can exist only if the number of neurons involved in a memory is large. The same mean-field analysis also shows that the number of memories that can be stored in a network scales with the number of excitatory connections, a result that has been suggested for simple models but never shown for realistic ones. Both of these predictions are verified using simulations with large networks of spiking neurons.

  1. Multimedia Networks: Mission Impossible?

    ERIC Educational Resources Information Center

    Weiss, Andrew M.

    1996-01-01

    Running multimedia on a network, often difficult because of the memory and processing power required, is becoming easier thanks to new protocols and products. Those developing network design criteria may wish to consider making use of Fast Ethernet, Asynchronous Transfer Method (ATM), switches, "fat pipes", additional network…

  2. Networking: OFFLU example

    USDA-ARS?s Scientific Manuscript database

    World Organization for Animal Health (OIE) and Food and Agriculture Organization (FAO) for the United Nations Influenza Network (OFFLU) is the joint OIE-FAO global network of expertise on animal influenzas: equine, swine, poultry and wild birds. OFFLU aims to reduce negative impacts of animal influ...

  3. Local Area Networks.

    ERIC Educational Resources Information Center

    Marks, Kenneth E.; Nielsen, Steven

    1991-01-01

    Discusses cabling that is needed in local area networks (LANs). Types of cables that may be selected are described, including twisted pair, coaxial cables (or ethernet), and fiber optics; network topologies, the manner in which the cables are laid out, are considered; and cable installation issues are discussed. (LRW)

  4. Networking Systems and Equipment.

    ERIC Educational Resources Information Center

    Kranz, Maciej

    2002-01-01

    Describes how high-bandwidth networks are delivering new educational and administrative opportunities for K-12 school districts. Addresses implementing the new network, upgrading to a switched environment, adding intelligent switches, IP telephony, and wireless technology. Describes deployment and benefits of broadband in the Denver public schools…

  5. The Community Networking Handbook.

    ERIC Educational Resources Information Center

    Bajjaly, Stephen T.

    This publication outlines the complete community networking process: planning, developing partnerships, funding, marketing, content, public access, and evaluation, and discusses the variety of roles that the local public library can play in this process. Chapter One, "The Importance of Community Networking," describes the importance of community…

  6. Networked Innovation in Innovation Networks: A Home Appliances Case Study

    NASA Astrophysics Data System (ADS)

    Berasategi, Luis; Arana, Joseba; Castellano, Eduardo

    Amongst different types of Collaborative Networked Organizations it is possible to highlight those created to develop and market product, process or business model innovation. In this type of innovation network, which has special characteristics, the challenge is to introduce effective networked innovation in the very same innovation network. This paper presents the main features of TALAI-SAREA © methodology that includes a reference model, a set of analysis tools and a method for implementing networked innovation in innovation networks.

  7. Optical Access Networks

    NASA Astrophysics Data System (ADS)

    Zheng, Jun; Ansari, Nirwan

    2005-03-01

    Call for Papers: Optical Access Networks With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the economic viability of many potential high-bandwidth applications. In recent years, optical access networks have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or

  8. Information theoretic description of networks

    NASA Astrophysics Data System (ADS)

    Wilhelm, Thomas; Hollunder, Jens

    2007-11-01

    We present a new information theoretic approach for network characterizations. It is developed to describe the general type of networks with n nodes and L directed and weighted links, i.e., it also works for the simpler undirected and unweighted networks. The new information theoretic measures for network characterizations are based on a transmitter-receiver analogy of effluxes and influxes. Based on these measures, we classify networks as either complex or non-complex and as either democracy or dictatorship networks. Directed networks, in particular, are furthermore classified as either information spreading and information collecting networks. The complexity classification is based on the information theoretic network complexity measure medium articulation (MA). It is proven that special networks with a medium number of links ( L∼n1.5) show the theoretical maximum complexity MA=(log n)2/2. A network is complex if its MA is larger than the average MA of appropriately randomized networks: MA>MAr. A network is of the democracy type if its redundancy Rnetwork. In democracy networks all nodes are, on average, of similar importance, whereas in dictatorship networks some nodes play distinguished roles in network functioning. In other words, democracy networks are characterized by cycling of information (or mass, or energy), while in dictatorship networks there is a straight through-flow from sources to sinks. The classification of directed networks into information spreading and information collecting networks is based on the conditional entropies of the considered networks ( H(A/B)=uncertainty of sender node if receiver node is known, H(B/A)=uncertainty of receiver node if sender node is known): if H(A/B)>H(B/A), it is an information collecting network, otherwise an information spreading network. Finally, different real networks (directed and undirected, weighted and unweighted) are classified according to our general scheme.

  9. The INGV tectonomagnetic network

    NASA Astrophysics Data System (ADS)

    Masci, F.; Palangio, P.; di Persio, M.

    2008-01-01

    The Italian Istituto Nazionale di Geofisica e Vulcanologia (INGV) tectonomagnetic network was installed in Central Italy since the middle of 1989 to investigate possible magnetic anomalies related to earthquakes. The network is part of the INGV L'Aquila Geomagnetic Observatory and is located in an area extending approximately in latitude range [41.6°-42.8°] N and longitude range [13.0°-14.3°] E. Actually the network consists of four stations where the total magnetic field intensity data are collected using proton precession magnetometers. New stations will be added to the network starting from the end of 2007. Here we are reporting the whole data set of the network's stations for the period 2004-2006. No significant anomaly in the local geomagnetic field correlated to the seismic activity has been found. Some considerations about misleading structures present in the data sets are reported.

  10. Modular Brain Networks

    PubMed Central

    Sporns, Olaf; Betzel, Richard F.

    2016-01-01

    The development of new technologies for mapping structural and functional brain connectivity has led to the creation of comprehensive network maps of neuronal circuits and systems. The architecture of these brain networks can be examined and analyzed with a large variety of graph theory tools. Methods for detecting modules, or network communities, are of particular interest because they uncover major building blocks or subnetworks that are particularly densely connected, often corresponding to specialized functional components. A large number of methods for community detection have become available and are now widely applied in network neuroscience. This article first surveys a number of these methods, with an emphasis on their advantages and shortcomings; then it summarizes major findings on the existence of modules in both structural and functional brain networks and briefly considers their potential functional roles in brain evolution, wiring minimization, and the emergence of functional specialization and complex dynamics. PMID:26393868

  11. Collective network routing

    DOEpatents

    Hoenicke, Dirk

    2014-12-02

    Disclosed are a unified method and apparatus to classify, route, and process injected data packets into a network so as to belong to a plurality of logical networks, each implementing a specific flow of data on top of a common physical network. The method allows to locally identify collectives of packets for local processing, such as the computation of the sum, difference, maximum, minimum, or other logical operations among the identified packet collective. Packets are injected together with a class-attribute and an opcode attribute. Network routers, employing the described method, use the packet attributes to look-up the class-specific route information from a local route table, which contains the local incoming and outgoing directions as part of the specifically implemented global data flow of the particular virtual network.

  12. Semaphore network encryption report

    NASA Astrophysics Data System (ADS)

    Johnson, Karen L.

    1994-03-01

    This paper documents the results of a preliminary assessment performed on the commercial off-the-shelf (COTS) Semaphore Communications Corporation (SCC) Network Security System (NSS). The Semaphore NSS is a family of products designed to address important network security concerns, such as network source address authentication and data privacy. The assessment was performed in the INFOSEC Core Integration Laboratory, and its scope was product usability focusing on interoperability and system performance in an existing operational network. Included in this paper are preliminary findings. Fundamental features and functionality of the Semaphore NSS are identified, followed by details of the assessment, including test descriptions and results. A summary of test results and future plans are also included. These findings will be useful to those investigating the use of commercially available solutions to network authentication and data privacy.

  13. Optical Access Networks

    NASA Astrophysics Data System (ADS)

    Zheng, Jun; Ansari, Nirwan

    2005-01-01

    Call for Papers: Optical Access Networks

    Guest Editors Jun Zheng, University of Ottawa Nirwan Ansari, New Jersey Institute of Technology

    Submission Deadline: 1 June 2005

    Background

    With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the

  14. Concordant Chemical Reaction Networks

    PubMed Central

    Shinar, Guy; Feinberg, Martin

    2015-01-01

    We describe a large class of chemical reaction networks, those endowed with a subtle structural property called concordance. We show that the class of concordant networks coincides precisely with the class of networks which, when taken with any weakly monotonic kinetics, invariably give rise to kinetic systems that are injective — a quality that, among other things, precludes the possibility of switch-like transitions between distinct positive steady states. We also provide persistence characteristics of concordant networks, instability implications of discordance, and consequences of stronger variants of concordance. Some of our results are in the spirit of recent ones by Banaji and Craciun, but here we do not require that every species suffer a degradation reaction. This is especially important in studying biochemical networks, for which it is rare to have all species degrade. PMID:22659063

  15. Online social support networks.

    PubMed

    Mehta, Neil; Atreja, Ashish

    2015-04-01

    Peer support groups have a long history and have been shown to improve health outcomes. With the increasing familiarity with online social networks like Facebook and ubiquitous access to the Internet, online social support networks are becoming popular. While studies have shown the benefit of these networks in providing emotional support or meeting informational needs, robust data on improving outcomes such as a decrease in health services utilization or reduction in adverse outcomes is lacking. These networks also pose unique challenges in the areas of patient privacy, funding models, quality of content, and research agendas. Addressing these concerns while creating patient-centred, patient-powered online support networks will help leverage these platforms to complement traditional healthcare delivery models in the current environment of value-based care.

  16. Community structure in networks

    NASA Astrophysics Data System (ADS)

    Newman, Mark

    2004-03-01

    Many networked systems, including physical, biological, social, and technological networks, appear to contain ``communities'' -- groups of nodes within which connections are dense, but between which they are sparser. The ability to find such communities in an automated fashion could be of considerable use. Communities in a web graph for instance might correspond to sets of web sites dealing with related topics, while communities in a biochemical network or an electronic circuit might correspond to functional units of some kind. We present a number of new methods for community discovery, including methods based on ``betweenness'' measures and methods based on modularity optimization. We also give examples of applications of these methods to both computer-generated and real-world network data, and show how our techniques can be used to shed light on the sometimes dauntingly complex structure of networked systems.

  17. Self Evolving Modular Network

    NASA Astrophysics Data System (ADS)

    Tokunaga, Kazuhiro; Kawabata, Nobuyuki; Furukawa, Tetsuo

    We propose a novel modular network called the Self-Evolving Modular Network (SEEM). The SEEM has a modular network architecture with a graph structure and these following advantages: (1) new modules are added incrementally to allow the network to adapt in a self-organizing manner, and (2) graph's paths are formed based on the relationships between the models represented by modules. The SEEM is expected to be applicable to evolving functions of an autonomous robot in a self-organizing manner through interaction with the robot's environment and categorizing large-scale information. This paper presents the architecture and an algorithm for the SEEM. Moreover, performance characteristic and effectiveness of the network are shown by simulations using cubic functions and a set of 3D-objects.

  18. Network Detection Theory

    NASA Astrophysics Data System (ADS)

    Ferry, James P.; Lo, Darren; Ahearn, Stephen T.; Phillips, Aaron M.

    Despite the breadth of modern network theory, it can be difficult to apply its results to the task of uncovering terrorist networks: the most useful network analyses are often low-tech, link-following approaches. In the traditional military domain, detection theory has a long history of finding stealthy targets such as submarines. We demonstrate how the detection theory framework leads to a variety of network analysis questions. Some solutions to these leverage existing theory; others require novel techniques - but in each case the solutions contribute to a principled methodology for solving network detection problems. This endeavor is difficult, and the work here represents only a beginning. However, the required mathematics is interesting, being the synthesis of two fields with little common history.

  19. Network of Interdependent Networks: Overview of Theory and Applications

    NASA Astrophysics Data System (ADS)

    Kenett, Dror Y.; Gao, Jianxi; Huang, Xuqing; Shao, Shuai; Vodenska, Irena; Buldyrev, Sergey V.; Paul, Gerald; Stanley, H. Eugene; Havlin, Shlomo

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

  20. Network Class Superposition Analyses

    PubMed Central

    Pearson, Carl A. B.; Zeng, Chen; Simha, Rahul

    2013-01-01

    Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., for the yeast cell cycle process [1]), considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix , which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for derived from Boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with . We show how to generate Derrida plots based on . We show that -based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on . We motivate all of these results in terms of a popular molecular biology Boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for , for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses. PMID:23565141

  1. Network class superposition analyses.

    PubMed

    Pearson, Carl A B; Zeng, Chen; Simha, Rahul

    2013-01-01

    Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30) for the yeast cell cycle process), considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.

  2. Improved Autoassociative Neural Networks

    NASA Technical Reports Server (NTRS)

    Hand, Charles

    2003-01-01

    Improved autoassociative neural networks, denoted nexi, have been proposed for use in controlling autonomous robots, including mobile exploratory robots of the biomorphic type. In comparison with conventional autoassociative neural networks, nexi would be more complex but more capable in that they could be trained to do more complex tasks. A nexus would use bit weights and simple arithmetic in a manner that would enable training and operation without a central processing unit, programs, weight registers, or large amounts of memory. Only a relatively small amount of memory (to hold the bit weights) and a simple logic application- specific integrated circuit would be needed. A description of autoassociative neural networks is prerequisite to a meaningful description of a nexus. An autoassociative network is a set of neurons that are completely connected in the sense that each neuron receives input from, and sends output to, all the other neurons. (In some instantiations, a neuron could also send output back to its own input terminal.) The state of a neuron is completely determined by the inner product of its inputs with weights associated with its input channel. Setting the weights sets the behavior of the network. The neurons of an autoassociative network are usually regarded as comprising a row or vector. Time is a quantized phenomenon for most autoassociative networks in the sense that time proceeds in discrete steps. At each time step, the row of neurons forms a pattern: some neurons are firing, some are not. Hence, the current state of an autoassociative network can be described with a single binary vector. As time goes by, the network changes the vector. Autoassociative networks move vectors over hyperspace landscapes of possibilities.

  3. Network of networks in Linux operating system

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  4. Tinnitus: network pathophysiology-network pharmacology

    PubMed Central

    Elgoyhen, Ana B.; Langguth, Berthold; Vanneste, Sven; De Ridder, Dirk

    2012-01-01

    Tinnitus, the phantom perception of sound, is a prevalent disorder. One in 10 adults has clinically significant subjective tinnitus, and for one in 100, tinnitus severely affects their quality of life. Despite the significant unmet clinical need for a safe and effective drug targeting tinnitus relief, there is currently not a single Food and Drug Administration (FDA)-approved drug on the market. The search for drugs that target tinnitus is hampered by the lack of a deep knowledge of the underlying neural substrates of this pathology. Recent studies are increasingly demonstrating that, as described for other central nervous system (CNS) disorders, tinnitus is a pathology of brain networks. The application of graph theoretical analysis to brain networks has recently provided new information concerning their topology, their robustness and their vulnerability to attacks. Moreover, the philosophy behind drug design and pharmacotherapy in CNS pathologies is changing from that of “magic bullets” that target individual chemoreceptors or “disease-causing genes” into that of “magic shotguns,” “promiscuous” or “dirty drugs” that target “disease-causing networks,” also known as network pharmacology. In the present work we provide some insight into how this knowledge could be applied to tinnitus pathophysiology and pharmacotherapy. PMID:22291622

  5. Articulation points in complex networks

    NASA Astrophysics Data System (ADS)

    Tian, Liang; Bashan, Amir; Shi, Da-Ning; Liu, Yang-Yu

    2017-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, such as the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a different perspective on the organizational principles of complex networks. Moreover, this process results in a rich phase diagram with two fundamentally different types of percolation transitions. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks.

  6. Extracting information from multiplex networks

    NASA Astrophysics Data System (ADS)

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  7. Articulation points in complex networks

    PubMed Central

    Tian, Liang; Bashan, Amir; Shi, Da-Ning; Liu, Yang-Yu

    2017-01-01

    An articulation point in a network is a node whose removal disconnects the network. Those nodes play key roles in ensuring connectivity of many real-world networks, from infrastructure networks to protein interaction networks and terrorist communication networks. Despite their fundamental importance, a general framework of studying articulation points in complex networks is lacking. Here we develop analytical tools to study key issues pertinent to articulation points, such as the expected number of them and the network vulnerability against their removal, in an arbitrary complex network. We find that a greedy articulation point removal process provides us a different perspective on the organizational principles of complex networks. Moreover, this process results in a rich phase diagram with two fundamentally different types of percolation transitions. Our results shed light on the design of more resilient infrastructure networks and the effective destruction of terrorist communication networks. PMID:28139697

  8. Extracting information from multiplex networks.

    PubMed

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ̃(S) for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  9. Neural networks for aircraft control

    NASA Technical Reports Server (NTRS)

    Linse, Dennis

    1990-01-01

    Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

  10. National Network for Immunization Information

    MedlinePlus

    ... American College of Obstetricians and Gynecologists . © Copyright National Network for Immunization Information. The information contained in the National Network for Immunization Information Web site should not be ...

  11. Correlation dimension of complex networks.

    PubMed

    Lacasa, Lucas; Gómez-Gardeñes, Jesús

    2013-04-19

    We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of complex networks. The method is validated with reliable results for both synthetic networks and real-world networks such as the world air-transportation network or urban networks, and provides a computationally fast way for estimating the dimensionality of networks which only relies on the local information provided by the walkers.

  12. Robustness of airline route networks

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Yang, Qiang; Wu, Chunming; Zhang, Min

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

  14. Optical Network Testbeds Workshop

    SciTech Connect

    Joe Mambretti

    2007-06-01

    This is the summary report of the third annual Optical Networking Testbed Workshop (ONT3), which brought together leading members of the international advanced research community to address major challenges in creating next generation communication services and technologies. Networking research and development (R&D) communities throughout the world continue to discover new methods and technologies that are enabling breakthroughs in advanced communications. These discoveries are keystones for building the foundation of the future economy, which requires the sophisticated management of extremely large qualities of digital information through high performance communications. This innovation is made possible by basic research and experiments within laboratories and on specialized testbeds. Initial network research and development initiatives are driven by diverse motives, including attempts to solve existing complex problems, the desire to create powerful new technologies that do not exist using traditional methods, and the need to create tools to address specific challenges, including those mandated by large scale science or government agency mission agendas. Many new discoveries related to communications technologies transition to wide-spread deployment through standards organizations and commercialization. These transition paths allow for new communications capabilities that drive many sectors of the digital economy. In the last few years, networking R&D has increasingly focused on advancing multiple new capabilities enabled by next generation optical networking. Both US Federal networking R&D and other national R&D initiatives, such as those organized by the National Institute of Information and Communications Technology (NICT) of Japan are creating optical networking technologies that allow for new, powerful communication services. Among the most promising services are those based on new types of multi-service or hybrid networks, which use new optical networking

  15. Neural networks in psychiatry.

    PubMed

    Hulshoff Pol, Hilleke; Bullmore, Edward

    2013-01-01

    Over the past three decades numerous imaging studies have revealed structural and functional brain abnormalities in patients with neuropsychiatric diseases. These structural and functional brain changes are frequently found in multiple, discrete brain areas and may include frontal, temporal, parietal and occipital cortices as well as subcortical brain areas. However, while the structural and functional brain changes in patients are found in anatomically separated areas, these are connected through (long distance) fibers, together forming networks. Thus, instead of representing separate (patho)-physiological entities, these local changes in the brains of patients with psychiatric disorders may in fact represent different parts of the same 'elephant', i.e., the (altered) brain network. Recent developments in quantitative analysis of complex networks, based largely on graph theory, have revealed that the brain's structure and functions have features of complex networks. Here we briefly introduce several recent developments in neural network studies relevant for psychiatry, including from the 2013 special issue on Neural Networks in Psychiatry in European Neuropsychopharmacology. We conclude that new insights will be revealed from the neural network approaches to brain imaging in psychiatry that hold the potential to find causes for psychiatric disorders and (preventive) treatments in the future.

  16. Neural networks counting chimes.

    PubMed Central

    Amit, D J

    1988-01-01

    It is shown that the ideas that led to neural networks capable of recalling associatively and asynchronously temporal sequences of patterns can be extended to produce a neural network that automatically counts the cardinal number in a sequence of identical external stimuli. The network is explicitly constructed, analyzed, and simulated. Such a network may account for the cognitive effect of the automatic counting of chimes to tell the hour. A more general implication is that different electrophysiological responses to identical stimuli, at certain stages of cortical processing, do not necessarily imply synaptic modification, a la Hebb. Such differences may arise from the fact that consecutive identical inputs find the network in different stages of an active temporal sequence of cognitive states. These types of networks are then situated within a program for the study of cognition, which assigns the detection of meaning as the primary role of attractor neural networks rather than computation, in contrast to the parallel distributed processing attitude to the connectionist project. This interpretation is free of homunculus, as well as from the criticism raised against the cognitive model of symbol manipulation. Computation is then identified as the syntax of temporal sequences of quasi-attractors. PMID:3353371

  17. Complex Semantic Networks

    NASA Astrophysics Data System (ADS)

    Teixeira, G. M.; Aguiar, M. S. F.; Carvalho, C. F.; Dantas, D. R.; Cunha, M. V.; Morais, J. H. M.; Pereira, H. B. B.; Miranda, J. G. V.

    Verbal language is a dynamic mental process. Ideas emerge by means of the selection of words from subjective and individual characteristics throughout the oral discourse. The goal of this work is to characterize the complex network of word associations that emerge from an oral discourse from a discourse topic. Because of that, concepts of associative incidence and fidelity have been elaborated and represented the probability of occurrence of pairs of words in the same sentence in the whole oral discourse. Semantic network of words associations were constructed, where the words are represented as nodes and the edges are created when the incidence-fidelity index between pairs of words exceeds a numerical limit (0.001). Twelve oral discourses were studied. The networks generated from these oral discourses present a typical behavior of complex networks and their indices were calculated and their topologies characterized. The indices of these networks obtained from each incidence-fidelity limit exhibit a critical value in which the semantic network has maximum conceptual information and minimum residual associations. Semantic networks generated by this incidence-fidelity limit depict a pattern of hierarchical classes that represent the different contexts used in the oral discourse.

  18. Network aware distributed applications

    SciTech Connect

    Agarwal, Deborah; Tierney, Brian L.; Gunter, Dan; Lee, Jason; Johnston, William

    2001-02-04

    Most distributed applications today manage to utilize only a small percentage of the needed and available network bandwidth. Often application developers are not aware of the potential bandwidth of the network, and therefore do not know what to expect. Even when application developers are aware of the specifications of the machines and network links, they have few resources that can help determine why the expected performance was not achieved. What is needed is a ubiquitous and easy-to-use service that provides reliable, accurate, secure, and timely estimates of dynamic network properties. This service will help advise applications on how to make use of the network's increasing bandwidth and capabilities for traffic shaping and engineering. When fully implemented, this service will make building currently unrealizable levels of network awareness into distributed applications a relatively mundane task. For example, a remote data visualization application could choose between sending a wireframe, a pre-rendered image, or a 3-D representation, based on forecasts of CPU availability and power, compression options, and available bandwidth. The same service will provide on-demand performance information so that applications can compare predicted with actual results, and allow detailed queries about the end-to-end path for application and network tuning and debugging.

  19. Simulated Associating Polymer Networks

    NASA Astrophysics Data System (ADS)

    Billen, Joris

    Telechelic associating polymer networks consist of polymer chains terminated by endgroups that have a different chemical composition than the polymer backbone. When dissolved in a solution, the endgroups cluster together to form aggregates. At low temperature, a strongly connected reversible network is formed and the system behaves like a gel. Telechelic networks are of interest since they are representative for biopolymer networks (e.g. F-actin) and are widely used in medical applications (e.g. hydrogels for tissue engineering, wound dressings) and consumer products (e.g. contact lenses, paint thickeners). In this thesis such systems are studied by means of a molecular dynamics/Monte Carlo simulation. At first, the system in rest is studied by means of graph theory. The changes in network topology upon cooling to the gel state, are characterized. Hereto an extensive study of the eigenvalue spectrum of the gel network is performed. As a result, an in-depth investigation of the eigenvalue spectra for spatial ER, scale-free, and small-world networks is carried out. Next, the gel under the application of a constant shear is studied, with a focus on shear banding and the changes in topology under shear. Finally, the relation between the gel transition and percolation is discussed.

  20. Networked Microgrids Scoping Study

    SciTech Connect

    Backhaus, Scott N.; Dobriansky, Larisa; Glover, Steve; Liu, Chen-Ching; Looney, Patrick; Mashayekh, Salman; Pratt, Annabelle; Schneider, Kevin; Stadler, Michael; Starke, Michael; Wang, Jianhui; Yue, Meng

    2016-12-05

    Much like individual microgrids, the range of opportunities and potential architectures of networked microgrids is very diverse. The goals of this scoping study are to provide an early assessment of research and development needs by examining the benefits of, risks created by, and risks to networked microgrids. At this time there are very few, if any, examples of deployed microgrid networks. In addition, there are very few tools to simulate or otherwise analyze the behavior of networked microgrids. In this setting, it is very difficult to evaluate networked microgrids systematically or quantitatively. At this early stage, this study is relying on inputs, estimations, and literature reviews by subject matter experts who are engaged in individual microgrid research and development projects, i.e., the authors of this study The initial step of the study gathered input about the potential opportunities provided by networked microgrids from these subject matter experts. These opportunities were divided between the subject matter experts for further review. Part 2 of this study is comprised of these reviews. Part 1 of this study is a summary of the benefits and risks identified in the reviews in Part 2 and synthesis of the research needs required to enable networked microgrids.

  1. Balanced Centrality of Networks.

    PubMed

    Debono, Mark; Lauri, Josef; Sciriha, Irene

    2014-01-01

    There is an age-old question in all branches of network analysis. What makes an actor in a network important, courted, or sought? Both Crossley and Bonacich contend that rather than its intrinsic wealth or value, an actor's status lies in the structures of its interactions with other actors. Since pairwise relation data in a network can be stored in a two-dimensional array or matrix, graph theory and linear algebra lend themselves as great tools to gauge the centrality (interpreted as importance, power, or popularity, depending on the purpose of the network) of each actor. We express known and new centralities in terms of only two matrices associated with the network. We show that derivations of these expressions can be handled exclusively through the main eigenvectors (not orthogonal to the all-one vector) associated with the adjacency matrix. We also propose a centrality vector (SWIPD) which is a linear combination of the square, walk, power, and degree centrality vectors with weightings of the various centralities depending on the purpose of the network. By comparing actors' scores for various weightings, a clear understanding of which actors are most central is obtained. Moreover, for threshold networks, the (SWIPD) measure turns out to be independent of the weightings.

  2. Endogenous Cooperation Network Formation

    NASA Astrophysics Data System (ADS)

    Angus, S.

    This paper employs insights from Complex Systems literature to develop a computational model of endogenous strategic network formation. Artificial Adaptive Agents (AAAs), implemented as finite state automata, play a modified two-player Iterated Prisoner's Dilemma game with an option to further develop the interaction space as part of their strategy. Several insights result from this relatively minor modification: first, I find that network formation is a necessary condition for cooperation to be sustainable but that both the frequency of interaction and the degree to which edge formation impacts agent mixing are both necessary conditions for cooperative networks. Second, within the FSA-modified IPD frame-work, a rich ecology of agents and network topologies is observed, with consequent payoff symmetry and network 'purity' seen to be further contributors to robust cooperative networks. Third, the dynamics of the strategic system under network formation show that initially simple dynamics with small interaction length between agents gives way to complex, a-periodic dynamics when interaction lengths are increased by a single step.

  3. Endogenous Cooperation Network Formation

    NASA Astrophysics Data System (ADS)

    Angus, S.

    This paper employs insights from Complex Systems literature to develop a computational model of endogenous strategic network formation. Artificial Adaptive Agents (AAAs), implemented as finite state automata, play a modified two-player Iterated Prisoner's Dilemma game with an option to further develop the interaction space as part of their strategy. Several insights result from this relatively minor modification: first, I find that network formation is a necessary condition for cooperation to be sustainable but that both the frequency of interaction and the degree to which edge formation impacts agent mixing are both necessary conditions for cooperative networks. Second, within the FSA-modified IPD frame-work, a rich ecology of agents and network topologies is observed, with consequent payoff symmetry and network `purity' seen to be further contributors to robust cooperative networks. Third, the dynamics of the strategic system under network formation show that initially simple dynamics with small interaction length between agents gives way to complex, a-periodic dynamics when interaction lengths are increased by a single step.

  4. Deblurring Signal Network Dynamics.

    PubMed

    Kamps, Dominic; Dehmelt, Leif

    2017-09-15

    To orchestrate the function and development of multicellular organisms, cells integrate intra- and extracellular information. This information is processed via signal networks in space and time, steering dynamic changes in cellular structure and function. Defects in those signal networks can lead to developmental disorders or cancer. However, experimental analysis of signal networks is challenging as their state changes dynamically and differs between individual cells. Thus, causal relationships between network components are blurred if lysates from large cell populations are analyzed. To directly study causal relationships, perturbations that target specific components have to be combined with measurements of cellular responses within individual cells. However, using standard single-cell techniques, the number of signal activities that can be monitored simultaneously is limited. Furthermore, diffusion of signal network components limits the spatial precision of perturbations, which blurs the analysis of spatiotemporal processing in signal networks. Hybrid strategies based on optogenetics, surface patterning, chemical tools, and protein design can overcome those limitations and thereby sharpen our view into the dynamic spatiotemporal state of signal networks and enable unique insights into the mechanisms that control cellular function in space and time.

  5. Launch Control Network Engineer

    NASA Technical Reports Server (NTRS)

    Medeiros, Samantha

    2017-01-01

    The Spaceport Command and Control System (SCCS) is being built at the Kennedy Space Center in order to successfully launch NASA’s revolutionary vehicle that allows humans to explore further into space than ever before. During my internship, I worked with the Network, Firewall, and Hardware teams that are all contributing to the huge SCCS network project effort. I learned the SCCS network design and the several concepts that are running in the background. I also updated and designed documentation for physical networks that are part of SCCS. This includes being able to assist and build physical installations as well as configurations. I worked with the network design for vehicle telemetry interfaces to the Launch Control System (LCS); this allows the interface to interact with other systems at other NASA locations. This network design includes the Space Launch System (SLS), Interim Cryogenic Propulsion Stage (ICPS), and the Orion Multipurpose Crew Vehicle (MPCV). I worked on the network design and implementation in the Customer Avionics Interface Development and Analysis (CAIDA) lab.

  6. 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.

  7. Toward Optimal Transport Networks

    NASA Technical Reports Server (NTRS)

    Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

    2008-01-01

    Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

  8. Attractor Metabolic Networks

    PubMed Central

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

    2013-01-01

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

  9. Small-world networks

    NASA Astrophysics Data System (ADS)

    Strogatz, Steven

    Everyone is familiar with the small-world phenomenon: soon after meeting a stranger, we are often suprised to discover that we have a mutual friend, or that we are somehow linked by a short chain of friends. In this talk, I'll present evidence that the small-world phenomenon is more than a curiosity of social networks — it is actually a general property of large, sparse networks whose topology is neither completely regular nor completely random. To check this idea, Duncan Watts and I have analyzed three networks of scientific interest: the neural network of the nematode worm C. elegans, the electrical power grid of the western United States, and the collaboration graph of actors in feature films. All three are small worlds, in the sense that the average number of "handshakes" separating any two members is extremely small (close to the theoretical lower limit set by a random graph). Yet at the same time, all three networks exhibit much more local clustering than a random net, demonstrating that they are not random. I'll also discuss a class of model networks that interpolate between regular lattices and random graphs. Previous theoretical research on complex systems in a wide range of disciplines has focused almost exclusively on networks that are either regular or random. Real networks often lie somewhere in between. Our mathematical model shows that networks in this middle ground tend to exhibit the small-world phenomenon, thanks to the presence of a few long-range edges that link parts of the graph that would otherwise be far apart. Furthermore, we find that when various dynamical systems are coupled in a small-world fashion, they exhibit much greater propagation speed, computational power, and synchronizability than their locally connected, regular counterparts. We explore the implications of these results for simple models of disease spreading, global computation in cellular automata, and collective locking of biological oscillators.

  10. Functional Molecular Ecological Networks

    PubMed Central

    Zhou, Jizhong; Deng, Ye; Luo, Feng; He, Zhili; Tu, Qichao; Zhi, Xiaoyang

    2010-01-01

    Biodiversity and its responses to environmental changes are central issues in ecology and for society. Almost all microbial biodiversity research focuses on “species” richness and abundance but not on their interactions. Although a network approach is powerful in describing ecological interactions among species, defining the network structure in a microbial community is a great challenge. Also, although the stimulating effects of elevated CO2 (eCO2) on plant growth and primary productivity are well established, its influences on belowground microbial communities, especially microbial interactions, are poorly understood. Here, a random matrix theory (RMT)-based conceptual framework for identifying functional molecular ecological networks was developed with the high-throughput functional gene array hybridization data of soil microbial communities in a long-term grassland FACE (free air, CO2 enrichment) experiment. Our results indicate that RMT is powerful in identifying functional molecular ecological networks in microbial communities. Both functional molecular ecological networks under eCO2 and ambient CO2 (aCO2) possessed the general characteristics of complex systems such as scale free, small world, modular, and hierarchical. However, the topological structures of the functional molecular ecological networks are distinctly different between eCO2 and aCO2, at the levels of the entire communities, individual functional gene categories/groups, and functional genes/sequences, suggesting that eCO2 dramatically altered the network interactions among different microbial functional genes/populations. Such a shift in network structure is also significantly correlated with soil geochemical variables. In short, elucidating network interactions in microbial communities and their responses to environmental changes is fundamentally important for research in microbial ecology, systems microbiology, and global change. PMID:20941329

  11. Dim Networks: The Utility of Social Network Analysis for Illuminating Partner Security Force Networks

    DTIC Science & Technology

    2015-12-01

    UTILITY OF SOCIAL NETWORK ANALYSIS FOR ILLUMINATING PARTNER SECURITY FORCE NETWORKS by Antione C. Fernandes Travis J. Taylor December 2015...REPORT DATE December 2015 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE DIM NETWORKS: THE UTILITY OF SOCIAL NETWORK ANALYSIS...use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations and selectively target key elements

  12. Embedded Sensor Networks

    NASA Astrophysics Data System (ADS)

    Iyengar, Sitharama S.

    Embedded sensor networks are distributed systems for sensing and in situ processing of spatially and temporally dense data from resource-limited and harsh environments such as seismic zones, ecological contamination sites are battle fields. From an application point of view, many interesting questions arise from sensor network technology that go far beyond the networking/computing aspects of the embedded system. This talk presents an overview of various open problems that are both of mathematical and engineering interests. These problems include sensor-centric quality of routing/energy optimization among other graph theoretic problems.

  13. BES Science Network Requirements

    SciTech Connect

    Biocca, Alan; Carlson, Rich; Chen, Jackie; Cotter, Steve; Tierney, Brian; Dattoria, Vince; Davenport, Jim; Gaenko, Alexander; Kent, Paul; Lamm, Monica; Miller, Stephen; Mundy, Chris; Ndousse, Thomas; Pederson, Mark; Perazzo, Amedeo; Popescu, Razvan; Rouson, Damian; Sekine, Yukiko; Sumpter, Bobby; Dart, Eli; Wang, Cai-Zhuang -Z; Whitelam, Steve; Zurawski, Jason

    2011-02-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivityfor the US Department of Energy Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of the Office ofScience programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years.

  14. Social Networks and Health.

    PubMed

    Perdiaris, Christos; Chardalias, Konstantinos; Magita, Andrianna; Mechili, Aggelos E; Diomidous, Marianna

    2015-01-01

    Nowadays the social networks have been developed into an advanced communications tool, which is important for all people to contact each other. These specific networks do offer lots of options as well as plenty of advantages and disadvantages. The social websites are many in number and titles, such as the facebook, the twitter, the bandoo etc. One of the most important function-mechanisms for the social network websites, are the marketing tools. The future goal is suggested to be the evolution of these programs. The development of these applications, which is going to lead into a new era for the social digital communication between the internet users, all around the globe.

  15. Broadband network selection issues

    NASA Astrophysics Data System (ADS)

    Leimer, Michael E.

    1996-01-01

    Selecting the best network for a given cable or telephone company provider is not as obvious as it appears. The cost and performance trades between Hybrid Fiber Coax (HFC), Fiber to the Curb (FTTC) and Asymmetric Digital Subscriber Line networks lead to very different choices based on the existing plant and the expected interactive subscriber usage model. This paper presents some of the issues and trades that drive network selection. The majority of the Interactive Television trials currently underway or planned are based on HFC networks. As a throw away market trial or a short term strategic incursion into a cable market, HFC may make sense. In the long run, if interactive services see high demand, HFC costs per node and an ever shrinking neighborhood node size to service large numbers of subscribers make FTTC appear attractive. For example, thirty-three 64-QAM modulators are required to fill the 550 MHz to 750 MHz spectrum with compressed video streams in 6 MHz channels. This large amount of hardware at each node drives not only initial build-out costs, but operations and maintenance costs as well. FTTC, with its potential for digitally switching large amounts of bandwidth to an given home, offers the potential to grow with the interactive subscriber base with less downstream cost. Integrated telephony on these networks is an issue that appears to be an afterthought for most of the networks being selected at the present time. The major players seem to be videocentric and include telephony as a simple add-on later. This may be a reasonable view point for the telephone companies that plan to leave their existing phone networks untouched. However, a phone company planning a network upgrade or a cable company jumping into the telephony business needs to carefully weigh the cost and performance issues of the various network choices. Each network type provides varying capability in both upstream and downstream bandwidth for voice channels. The noise characteristics

  16. Learning In networks

    NASA Technical Reports Server (NTRS)

    Buntine, Wray L.

    1995-01-01

    Intelligent systems require software incorporating probabilistic reasoning, and often times learning. Networks provide a framework and methodology for creating this kind of software. This paper introduces network models based on chain graphs with deterministic nodes. Chain graphs are defined as a hierarchical combination of Bayesian and Markov networks. To model learning, plates on chain graphs are introduced to model independent samples. The paper concludes by discussing various operations that can be performed on chain graphs with plates as a simplification process or to generate learning algorithms.

  17. The Space Mobile Network

    NASA Technical Reports Server (NTRS)

    Israel, David

    2017-01-01

    The definition and development of the next generation space communications and navigation architecture is underway. The primary goals are to remove communications and navigations constraints from missions and to enable increased autonomy. The Space Mobile Network (SMN) is an architectural concept that includes new technology and operations that will provide flight systems with an similar user experience to terrestrial wireless mobile networks. This talk will describe the SMN and its proposed new features, such as Disruption Tolerant Networking (DTN), optical communications, and User Initiated Services (UIS).

  18. Comparative analysis of collaboration networks

    SciTech Connect

    Progulova, Tatiana; Gadjiev, Bahruz

    2011-03-14

    In this paper we carry out a comparative analysis of the word network as the collaboration network based on the novel by M. Bulgakov 'Master and Margarita', the synonym network of the Russian language as well as the Russian movie actor network. We have constructed one-mode projections of these networks, defined degree distributions for them and have calculated main characteristics. In the paper a generation algorithm of collaboration networks has been offered which allows one to generate networks statistically equivalent to the studied ones. It lets us reveal a structural correlation between word network, synonym network and movie actor network. We show that the degree distributions of all analyzable networks are described by the distribution of q-type.

  19. Comparative analysis of collaboration networks

    NASA Astrophysics Data System (ADS)

    Progulova, Tatiana; Gadjiev, Bahruz

    2011-03-01

    In this paper we carry out a comparative analysis of the word network as the collaboration network based on the novel by M. Bulgakov "Master and Margarita", the synonym network of the Russian language as well as the Russian movie actor network. We have constructed one-mode projections of these networks, defined degree distributions for them and have calculated main characteristics. In the paper a generation algorithm of collaboration networks has been offered which allows one to generate networks statistically equivalent to the studied ones. It lets us reveal a structural correlation between word network, synonym network and movie actor network. We show that the degree distributions of all analyzable networks are described by the distribution of q-type.

  20. The Analysis of Social Networks.

    PubMed

    O'Malley, A James; Marsden, Peter V

    2008-12-01

    Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them to network data. This article reviews fundamentals of, and recent innovations in, social network analysis using a physician influence network as an example. After introducing forms of network data, basic network statistics, and common descriptive measures, it describes two distinct types of statistical models for network data: individual-outcome models in which networks enter the construction of explanatory variables, and relational models in which the network itself is a multivariate dependent variable. Complexities in estimating both types of models arise due to the complex correlation structures among outcome measures.

  1. Quantifying randomness in real networks

    NASA Astrophysics Data System (ADS)

    Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-10-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

  2. Quantifying randomness in real networks.

    PubMed

    Orsini, Chiara; Dankulov, Marija M; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-10-20

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

  3. Network Routing Using the Network Tasking Order, a Chron Approach

    DTIC Science & Technology

    2015-03-26

    some advanced prediction techniques that are utilized for traffic routing and management as well as some synchronization techniques are presented...NETWORK ROUTING USING THE NETWORK TASKING ORDER, A CHRON APPROACH THESIS Nicholas J. Paltzer...MS-15-M-059 NETWORK ROUTING USING THE NETWORK TASKING ORDER, A CHRON APPROACH THESIS Presented to the Faculty Department of Electrical

  4. The Deep Space Network

    NASA Technical Reports Server (NTRS)

    1979-01-01

    Progress on the Deep Space Network (DSN) supporting research and technology, advanced development, engineering and implementation, and DSN operations is presented. The functions and facilities of the DSN are described.

  5. Environmental Response Laboratory Network

    EPA Pesticide Factsheets

    The ERLN as a national network of laboratories that can be ramped up as needed to support large scale environmental responses. It integrates capabilities of existing public and private sector labs, providing consistent capacity and quality data.

  6. NP Science Network Requirements

    SciTech Connect

    Dart, Eli; Rotman, Lauren; Tierney, Brian

    2011-08-26

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. To support SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In August 2011, ESnet and the Office of Nuclear Physics (NP), of the DOE SC, organized a workshop to characterize the networking requirements of the programs funded by NP. The requirements identified at the workshop are summarized in the Findings section, and are described in more detail in the body of the report.

  7. CRCHD Integrated Networks

    Cancer.gov

    INB supports the National Outreach Network, the Geographic Management of Cancer Health Disparities Program, and advises on women’s health and sexual and gender minority opportunities within and across NCI.

  8. Learning network representations

    NASA Astrophysics Data System (ADS)

    Moyano, Luis G.

    2017-02-01

    In this review I present several representation learning methods, and discuss the latest advancements with emphasis in applications to network science. Representation learning is a set of techniques that has the goal of efficiently mapping data structures into convenient latent spaces. Either for dimensionality reduction or for gaining semantic content, this type of feature embeddings has demonstrated to be useful, for example, for node classification or link prediction tasks, among many other relevant applications to networks. I provide a description of the state-of-the-art of network representation learning as well as a detailed account of the connections with other fields of study such as continuous word embeddings and deep learning architectures. Finally, I provide a broad view of several applications of these techniques to networks in various domains.

  9. The Deep Space Network

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The various systems and subsystems are discussed for the Deep Space Network (DSN). A description of the DSN is presented along with mission support, program planning, facility engineering, implementation and operations.

  10. Dynamics in scheduled networks

    NASA Astrophysics Data System (ADS)

    Zanin, Massimiliano; Lacasa, Lucas; Cea, Miguel

    2009-06-01

    When studying real or virtual systems through complex networks theories, usually time restrictions are neglected, and a static structure is defined to characterize which node is connected to which other. However, this approach is oversimplified, as real networks are indeed dynamically modified by external mechanisms. In order to bridge the gap, in this work we present a scheduled network formalism, which takes into account such dynamical modifications by including generic time restrictions in the structure of an extended adjacency matrix. We present some of its properties and apply this formalism to the specific case of the air transportation network in order to analyze its efficiency. Real data are used at this point. We finally discuss on the applicability of this formalism to other complex systems.

  11. Compressively sensed complex networks.

    SciTech Connect

    Dunlavy, Daniel M.; Ray, Jaideep; Pinar, Ali

    2010-07-01

    The aim of this project is to develop low dimension parametric (deterministic) models of complex networks, to use compressive sensing (CS) and multiscale analysis to do so and to exploit the structure of complex networks (some are self-similar under coarsening). CS provides a new way of sampling and reconstructing networks. The approach is based on multiresolution decomposition of the adjacency matrix and its efficient sampling. It requires preprocessing of the adjacency matrix to make it 'blocky' which is the biggest (combinatorial) algorithm challenge. Current CS reconstruction algorithm makes no use of the structure of a graph, its very general (and so not very efficient/customized). Other model-based CS techniques exist, but not yet adapted to networks. Obvious starting point for future work is to increase the efficiency of reconstruction.

  12. Network science: Destruction perfected

    NASA Astrophysics Data System (ADS)

    Kovács, István A.; Barabási, Albert-László

    2015-08-01

    Pinpointing the nodes whose removal most effectively disrupts a network has become a lot easier with the development of an efficient algorithm. Potential applications might include cybersecurity and disease control. See Letter p.65

  13. Actively stressed marginal networks.

    PubMed

    Sheinman, M; Broedersz, C P; MacKintosh, F C

    2012-12-07

    We study the effects of motor-generated stresses in disordered three-dimensional fiber networks using a combination of a mean-field theory, scaling analysis, and a computational model. We find that motor activity controls the elasticity in an anomalous fashion close to the point of marginal stability by coupling to critical network fluctuations. We also show that motor stresses can stabilize initially floppy networks, extending the range of critical behavior to a broad regime of network connectivities below the marginal point. Away from this regime, or at high stress, motors give rise to a linear increase in stiffness with stress. Finally, we demonstrate that our results are captured by a simple, constitutive scaling relation highlighting the important role of nonaffine strain fluctuations as a susceptibility to motor stress.

  14. Growing networks with superjoiners.

    PubMed

    Jabr-Hamdan, Ameerah; Sun, Jie; Ben-Avraham, Daniel

    2014-11-01

    We study the Krapivsky-Redner (KR) network growth model, but where new nodes can connect to any number of existing nodes, m, picked from a power-law distribution p(m)∼m^{-α}. Each of the m new connections is still carried out as in the KR model with probability redirection r (corresponding to degree exponent γ_{KR}=1+1/r in the original KR model). The possibility to connect to any number of nodes resembles a more realistic type of growth in several settings, such as social networks, routers networks, and networks of citations. Here we focus on the in-, out-, and total-degree distributions and on the potential tension between the degree exponent α, characterizing new connections (outgoing links), and the degree exponent γ_{KR}(r) dictated by the redirection mechanism.

  15. Growing networks with superjoiners

    NASA Astrophysics Data System (ADS)

    Jabr-Hamdan, Ameerah; Sun, Jie; ben-Avraham, Daniel

    2014-11-01

    We study the Krapivsky-Redner (KR) network growth model, but where new nodes can connect to any number of existing nodes, m , picked from a power-law distribution p (m ) ˜m-α . Each of the m new connections is still carried out as in the KR model with probability redirection r (corresponding to degree exponent γKR=1 +1 /r in the original KR model). The possibility to connect to any number of nodes resembles a more realistic type of growth in several settings, such as social networks, routers networks, and networks of citations. Here we focus on the in-, out-, and total-degree distributions and on the potential tension between the degree exponent α , characterizing new connections (outgoing links), and the degree exponent γKR(r ) dictated by the redirection mechanism.

  16. Netiquettes for Networkers.

    ERIC Educational Resources Information Center

    McMurdo, George

    1995-01-01

    Presents 20 networking etiquette guidelines taken from electronic and print sources. Highlights include focusing on one subject, condensing messages, editing quotes, spelling and grammar, typography, mistakes, acronyms, humor, researching discussion groups, intellectual property and copyright, manners, ethics, and damage. (AEF)

  17. Dynamics of fractal networks

    NASA Astrophysics Data System (ADS)

    Orbach, R.

    1986-02-01

    Random structures often exhibit fractal geometry, defined in terms of the mass scaling exponent, D, the fractal dimension. The vibrational dynamics of fractal networks are expressed in terms of the exponent d double bar, the fracton dimensionality. The eigenstates on a fractal network are spatially localized for d double bar less than or equal to 2. The implications of fractal geometry are discussed for thermal transport on fractal networks. The electron-fracton interaction is developed, with a brief outline given for the time dependence of the electronic relaxation on fractal networks. It is suggested that amorphous or glassy materials may exhibit fractal properties at short length scales or, equivalently, at high energies. The calculations of physical properties can be used to test the fractal character of the vibrational excitations in these materials.

  18. Networks Around the World.

    ERIC Educational Resources Information Center

    Online & CD-ROM Review, 1997

    1997-01-01

    Examines the topic of networked information. Discusses the possibility of a global stock exchange, the utility of environmental information on the Internet, the Internet in India, and Internet user types and habits according to a survey conducted in Denmark. (AEF)

  19. Divers Alert Network

    MedlinePlus

    ... Network, the diving industry’s largest association dedicated to scuba diving safety. Serving scuba divers for more than 30 ... to help cover the cost of treatment for scuba diving injuries. DAN fulfilled that need by developing diving’s ...

  20. Multimedia wireless networking

    NASA Astrophysics Data System (ADS)

    Jain, Rajeev; Alwan, Abeer; Gerla, Mario; Kleinrock, Leonard; Villasenor, John D.; Belzer, Ben; Boring, Walter; Molloy, Stephen; Nazareth, Sean; Siqueira, Marcio; Short, Joel; Tsai, Jack

    1996-03-01

    Current wireless network systems (e.g. metropolitan cellular) are constrained by fixed bandwidth allocations and support only a narrow range of services (voice and low bit-rate data). To overcome these constraints and advance the state of the art in wireless multimedia communications, we are developing variable-rate video and speech compression algorithms, and wireless node architectures that will enable peer-to-peer multimedia networking even with very low bandwidth. To support this objective, each wireless node must support new applications (for multimedia), advances in networking and source coding to support multimedia under limited bandwidth conditions (wireless), advances in physical layer design to support robust, low power, high packet throughput links, low power DSP for multimedia compression, and an architectural strategy to integrate these components into an efficient node. The algorithms and architectures to support this functionality are presented here, together with some preliminary results on network performance.

  1. NSIUWG: Science networking retreat

    NASA Technical Reports Server (NTRS)

    Hart, Jim

    1991-01-01

    The purpose of this session was to study and identify alternatives to be recommended for the science networking areas of vision; roles and responsibilities; and technical approach and transition. This presentation is represented by charts and viewgraphs only.

  2. Netiquettes for Networkers.

    ERIC Educational Resources Information Center

    McMurdo, George

    1995-01-01

    Presents 20 networking etiquette guidelines taken from electronic and print sources. Highlights include focusing on one subject, condensing messages, editing quotes, spelling and grammar, typography, mistakes, acronyms, humor, researching discussion groups, intellectual property and copyright, manners, ethics, and damage. (AEF)

  3. Congenital Heart Information Network

    MedlinePlus

    ... Baemayr for The Congenital Heart Information Network Exempt organization under Section 501(c)3. Copyright ©1996 - 2016 C.H.I.N. All rights reserved TX4-390-685 Original site design and HTML by Panoptic Communications

  4. Multitasking Associative Networks

    NASA Astrophysics Data System (ADS)

    Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Moauro, Francesco

    2012-12-01

    We introduce a bipartite, diluted and frustrated, network as a sparse restricted Boltzmann machine and we show its thermodynamical equivalence to an associative working memory able to retrieve several patterns in parallel without falling into spurious states typical of classical neural networks. We focus on systems processing in parallel a finite (up to logarithmic growth in the volume) amount of patterns, mirroring the low-level storage of standard Amit-Gutfreund-Sompolinsky theory. Results obtained through statistical mechanics, the signal-to-noise technique, and Monte Carlo simulations are overall in perfect agreement and carry interesting biological insights. Indeed, these associative networks pave new perspectives in the understanding of multitasking features expressed by complex systems, e.g., neural and immune networks.

  5. Actively Stressed Marginal Networks

    NASA Astrophysics Data System (ADS)

    Sheinman, M.; Broedersz, C. P.; MacKintosh, F. C.

    2012-12-01

    We study the effects of motor-generated stresses in disordered three-dimensional fiber networks using a combination of a mean-field theory, scaling analysis, and a computational model. We find that motor activity controls the elasticity in an anomalous fashion close to the point of marginal stability by coupling to critical network fluctuations. We also show that motor stresses can stabilize initially floppy networks, extending the range of critical behavior to a broad regime of network connectivities below the marginal point. Away from this regime, or at high stress, motors give rise to a linear increase in stiffness with stress. Finally, we demonstrate that our results are captured by a simple, constitutive scaling relation highlighting the important role of nonaffine strain fluctuations as a susceptibility to motor stress.

  6. LINCS: Livermore's network architecture. [Octopus computing network

    SciTech Connect

    Fletcher, J.G.

    1982-01-01

    Octopus, a local computing network that has been evolving at the Lawrence Livermore National Laboratory for over fifteen years, is currently undergoing a major revision. The primary purpose of the revision is to consolidate and redefine the variety of conventions and formats, which have grown up over the years, into a single standard family of protocols, the Livermore Interactive Network Communication Standard (LINCS). This standard treats the entire network as a single distributed operating system such that access to a computing resource is obtained in a single way, whether that resource is local (on the same computer as the accessing process) or remote (on another computer). LINCS encompasses not only communication but also such issues as the relationship of customer to server processes and the structure, naming, and protection of resources. The discussion includes: an overview of the Livermore user community and computing hardware, the functions and structure of each of the seven layers of LINCS protocol, the reasons why we have designed our own protocols and why we are dissatisfied by the directions that current protocol standards are taking.

  7. Emergence of robustness in networks of networks

    NASA Astrophysics Data System (ADS)

    Roth, Kevin; Morone, Flaviano; Min, Byungjoon; Makse, Hernán A.

    2017-06-01

    A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017), 10.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.

  8. Network vulnerability assessment using Bayesian networks

    NASA Astrophysics Data System (ADS)

    Liu, Yu; Man, Hong

    2005-03-01

    While computer vulnerabilities have been continually reported in laundry-list format by most commercial scanners, a comprehensive network vulnerability assessment has been an increasing challenge to security analysts. Researchers have proposed a variety of methods to build attack trees with chains of exploits, based on which post-graph vulnerability analysis can be performed. The most recent approaches attempt to build attack trees by enumerating all potential attack paths, which are space consuming and result in poor scalability. This paper presents an approach to use Bayesian network to model potential attack paths. We call such graph as "Bayesian attack graph". It provides a more compact representation of attack paths than conventional methods. Bayesian inference methods can be conveniently used for probabilistic analysis. In particular, we use the Bucket Elimination algorithm for belief updating, and we use Maximum Probability Explanation algorithm to compute an optimal subset of attack paths relative to prior knowledge on attackers and attack mechanisms. We tested our model on an experimental network. Test results demonstrate the effectiveness of our approach.

  9. Convolution in Convolution for Network in Network.

    PubMed

    Pang, Yanwei; Sun, Manli; Jiang, Xiaoheng; Li, Xuelong

    2017-03-16

    Network in network (NiN) is an effective instance and an important extension of deep convolutional neural network consisting of alternating convolutional layers and pooling layers. Instead of using a linear filter for convolution, NiN utilizes shallow multilayer perceptron (MLP), a nonlinear function, to replace the linear filter. Because of the powerfulness of MLP and 1 x 1 convolutions in spatial domain, NiN has stronger ability of feature representation and hence results in better recognition performance. However, MLP itself consists of fully connected layers that give rise to a large number of parameters. In this paper, we propose to replace dense shallow MLP with sparse shallow MLP. One or more layers of the sparse shallow MLP are sparely connected in the channel dimension or channel-spatial domain. The proposed method is implemented by applying unshared convolution across the channel dimension and applying shared convolution across the spatial dimension in some computational layers. The proposed method is called convolution in convolution (CiC). The experimental results on the CIFAR10 data set, augmented CIFAR10 data set, and CIFAR100 data set demonstrate the effectiveness of the proposed CiC method.

  10. Optical Access Networks

    NASA Astrophysics Data System (ADS)

    Zheng, Jun; Ansari, Nirwan

    2005-02-01

    Call for Papers: Optical Access Networks With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the economic viability of many potential high-bandwidth applications. In recent years, optical access networks have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or

  11. The Colombia Seismological Network

    NASA Astrophysics Data System (ADS)

    Blanco Chia, J. F.; Poveda, E.; Pedraza, P.

    2013-05-01

    The latest seismological equipment and data processing instrumentation installed at the Colombia Seismological Network (RSNC) are described. System configuration, network operation, and data management are discussed. The data quality and the new seismological products are analyzed. The main purpose of the network is to monitor local seismicity with a special emphasis on seismic activity surrounding the Colombian Pacific and Caribbean oceans, for early warning in case a Tsunami is produced by an earthquake. The Colombian territory is located at the South America northwestern corner, here three tectonic plates converge: Nazca, Caribbean and the South American. The dynamics of these plates, when resulting in earthquakes, is continuously monitored by the network. In 2012, the RSNC registered in 2012 an average of 67 events per day; from this number, a mean of 36 earthquakes were possible to be located well. In 2010 the network was also able to register an average of 67 events, but it was only possible to locate a mean of 28 earthquakes daily. This difference is due to the expansion of the network. The network is made up of 84 stations equipped with different kind of broadband 40s, 120s seismometers, accelerometers and short period 1s sensors. The signal is transmitted continuously in real-time to the Central Recording Center located at Bogotá, using satellite, telemetry, and Internet. Moreover, there are some other stations which are required to collect the information in situ. Data is recorded and processed digitally using two different systems, EARTHWORM and SEISAN, which are able to process and share the information between them. The RSNC has designed and implemented a web system to share the seismological data. This innovative system uses tools like Java Script, Oracle and programming languages like PHP to allow the users to access the seismicity registered by the network almost in real time as well as to download the waveform and technical details. The coverage

  12. Network Profiling Using Flow

    DTIC Science & Technology

    2012-08-01

    the name of the server (all externally facing SMTP servers will have a DNS record and associated IP address). Telnetting to each IP address at port...38 5.6 Remote Services This section discusses how to profile three remote service protocols: Telnet , SSH, and FTP. Telnet is an older protocol...show, the sample network has two potential FTP servers, three potential SSH servers, and no Telnet servers. 2. To find clients on the network

  13. Introduction: optimization in networks.

    PubMed

    Motter, Adilson E; Toroczkai, Zoltan

    2007-06-01

    The recent surge in the network modeling of complex systems has set the stage for a new era in the study of fundamental and applied aspects of optimization in collective behavior. This Focus Issue presents an extended view of the state of the art in this field and includes articles from a large variety of domains in which optimization manifests itself, including physical, biological, social, and technological networked systems.

  14. Neural Networks: A Primer

    DTIC Science & Technology

    1991-05-01

    capture underlying relationships directly from observed behavior is one of the primary capabilities of neural networks. 29 Back P’ropagation Approximailon...model complex behavior patterns. Particularly in areas traditionally addressed by regression and other functional based techniques, neural networks...to.be determined directly from the observed behavior of a system or sample of individuals. This ability should prove important in personnel analysis and

  15. Networks of Human Culture

    NASA Astrophysics Data System (ADS)

    Csermely, Peter

    Now that you are back from the zoo, where you tried in vain to shake the six hands of all the ants for several hours,1 it is time to start our fifth trip into Netland. Let us go and see what those macroscopic ants known as human beings can achieve. I will show you what type of networks we have figured out to support the last variety of social networks from the previous chapter.

  16. Network Security Guideline

    DTIC Science & Technology

    1993-06-01

    employing and used for data communications and data processing; variable and continuous waveforms to represent ASCII allows compatibility among data... modulated as an analog carrier frequency; in modulation , the frequency band occupied by the aggregate C of the transmitted signals when first used to modulate ...number assigned to public data line digital service offered intraLATA by BOCs (Bell networks and to specific services within those networks. Operated

  17. Joint Tactical Networks (JTN)

    DTIC Science & Technology

    2013-12-01

    BY - Base Year DAMIR - Defense Acquisition Management Information Retrieval Dev Est - Development Estimate DoD - Department of Defense DSN - Defense...the Handheld, Manpack and Small Form Fit (HMS) Rifleman Radio Initial Operational Test & Evaluation ( IOT &E) conducted at Network Integration...scheduled IOT &E of the Mid-Tier Networking Vehicular Radio (MNVR) in November 2015 and fielding to the Brigade Combat Teams (BCT) beginning in September

  18. Fixed Access Network Sharing

    NASA Astrophysics Data System (ADS)

    Cornaglia, Bruno; Young, Gavin; Marchetta, Antonio

    2015-12-01

    Fixed broadband network deployments are moving inexorably to the use of Next Generation Access (NGA) technologies and architectures. These NGA deployments involve building fiber infrastructure increasingly closer to the customer in order to increase the proportion of fiber on the customer's access connection (Fibre-To-The-Home/Building/Door/Cabinet… i.e. FTTx). This increases the speed of services that can be sold and will be increasingly required to meet the demands of new generations of video services as we evolve from HDTV to "Ultra-HD TV" with 4k and 8k lines of video resolution. However, building fiber access networks is a costly endeavor. It requires significant capital in order to cover any significant geographic coverage. Hence many companies are forming partnerships and joint-ventures in order to share the NGA network construction costs. One form of such a partnership involves two companies agreeing to each build to cover a certain geographic area and then "cross-selling" NGA products to each other in order to access customers within their partner's footprint (NGA coverage area). This is tantamount to a bi-lateral wholesale partnership. The concept of Fixed Access Network Sharing (FANS) is to address the possibility of sharing infrastructure with a high degree of flexibility for all network operators involved. By providing greater configuration control over the NGA network infrastructure, the service provider has a greater ability to define the network and hence to define their product capabilities at the active layer. This gives the service provider partners greater product development autonomy plus the ability to differentiate from each other at the active network layer.

  19. OPTIMAL NETWORK TOPOLOGY DESIGN

    NASA Technical Reports Server (NTRS)

    Yuen, J. H.

    1994-01-01

    This program was developed as part of a research study on the topology design and performance analysis for the Space Station Information System (SSIS) network. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. It is intended that this new design technique consider all important performance measures explicitly and take into account the constraints due to various technical feasibilities. In the current program, technical constraints are taken care of by the user properly forming the starting set of candidate components (e.g. nonfeasible links are not included). As subsets are generated, they are tested to see if they form an acceptable network by checking that all requirements are satisfied. Thus the first acceptable subset encountered gives the cost-optimal topology satisfying all given constraints. The user must sort the set of "feasible" link elements in increasing order of their costs. The program prompts the user for the following information for each link: 1) cost, 2) connectivity (number of stations connected by the link), and 3) the stations connected by that link. Unless instructed to stop, the program generates all possible acceptable networks in increasing order of their total costs. The program is written only to generate topologies that are simply connected. Tests on reliability, delay, and other performance measures are discussed in the documentation, but have not been incorporated into the program. This program is written in PASCAL for interactive execution and has been implemented on an IBM PC series computer operating under PC DOS. The disk contains source code only. This program was developed in 1985.

  20. Applied Learning Networks (ALN)

    DTIC Science & Technology

    2007-01-01

    AFRL-IF-RS-TR-2007-7 Final Technical Report January 2007 APPLIED LEARNING NETWORKS (ALN) University of Southern California...any other person or corporation; or convey any rights or permission to manufacture, use, or sell any patented invention that may relate to them...1-0051 4. TITLE AND SUBTITLE APPLIED LEARNING NETWORKS (ALN) 5c. PROGRAM ELEMENT NUMBER 62301E 5d. PROJECT NUMBER T981 5e. TASK NUMBER US

  1. Causal networks in EIA

    SciTech Connect

    Perdicoulis, Anastassios . E-mail: tasso@utad.pt; Glasson, John . E-mail: jglasson@brookes.ac.uk

    2006-08-15

    Causal networks have been used in Environmental Impact Assessment (EIA) since its early days, but they appear to have a minimal use in modern practice. This article reviews the typology of causal networks in EIA as well as in other academic and professional fields, verifies their contribution to EIA against the principles and requirements of the process, and discusses alternative scenarios for their future in EIA.

  2. Modeling Network Interdiction Tasks

    DTIC Science & Technology

    2015-09-17

    they may attack the flaw to cause widespread chaos. Attacks such as these are considered a form of network interdiction. Assessing the networks over...and forms a foundation for the techniques of the measures and models approaches of the research framework, which is depicted in Figure 2. The...ensures the distance of the shortest (i, j) path is computed. This insight is attributed to Warshall [62]. The algorithm’s present form is attributed

  3. Emergent Hyperbolic Network Geometry

    NASA Astrophysics Data System (ADS)

    Bianconi, Ginestra; Rahmede, Christoph

    2017-02-01

    A large variety of interacting complex systems are characterized by interactions occurring between more than two nodes. These systems are described by simplicial complexes. Simplicial complexes are formed by simplices (nodes, links, triangles, tetrahedra etc.) that have a natural geometric interpretation. As such simplicial complexes are widely used in quantum gravity approaches that involve a discretization of spacetime. Here, by extending our knowledge of growing complex networks to growing simplicial complexes we investigate the nature of the emergent geometry of complex networks and explore whether this geometry is hyperbolic. Specifically we show that an hyperbolic network geometry emerges spontaneously from models of growing simplicial complexes that are purely combinatorial. The statistical and geometrical properties of the growing simplicial complexes strongly depend on their dimensionality and display the major universal properties of real complex networks (scale-free degree distribution, small-world and communities) at the same time. Interestingly, when the network dynamics includes an heterogeneous fitness of the faces, the growing simplicial complex can undergo phase transitions that are reflected by relevant changes in the network geometry.

  4. Coupled biopolymer networks

    NASA Astrophysics Data System (ADS)

    Schwarz, J. M.; Zhang, Tao

    2015-03-01

    The actin cytoskeleton provides the cell with structural integrity and allows it to change shape to crawl along a surface, for example. The actin cytoskeleton can be modeled as a semiflexible biopolymer network that modifies its morphology in response to both external and internal stimuli. Just inside the inner nuclear membrane of a cell exists a network of filamentous lamin that presumably protects the heart of the cell nucleus--the DNA. Lamins are intermediate filaments that can also be modeled as semiflexible biopolymers. It turns out that the actin cytoskeletal biopolymer network and the lamin biopolymer network are coupled via a sequence of proteins that bridge the outer and inner nuclear membranes. We, therefore, probe the consequences of such a coupling via numerical simulations to understand the resulting deformations in the lamin network in response to perturbations in the cytoskeletal network. Such study could have implications for mechanical mechanisms of the regulation of transcription, since DNA--yet another semiflexible polymer--contains lamin-binding domains, and, thus, widen the field of epigenetics.

  5. Emergent Hyperbolic Network Geometry.

    PubMed

    Bianconi, Ginestra; Rahmede, Christoph

    2017-02-07

    A large variety of interacting complex systems are characterized by interactions occurring between more than two nodes. These systems are described by simplicial complexes. Simplicial complexes are formed by simplices (nodes, links, triangles, tetrahedra etc.) that have a natural geometric interpretation. As such simplicial complexes are widely used in quantum gravity approaches that involve a discretization of spacetime. Here, by extending our knowledge of growing complex networks to growing simplicial complexes we investigate the nature of the emergent geometry of complex networks and explore whether this geometry is hyperbolic. Specifically we show that an hyperbolic network geometry emerges spontaneously from models of growing simplicial complexes that are purely combinatorial. The statistical and geometrical properties of the growing simplicial complexes strongly depend on their dimensionality and display the major universal properties of real complex networks (scale-free degree distribution, small-world and communities) at the same time. Interestingly, when the network dynamics includes an heterogeneous fitness of the faces, the growing simplicial complex can undergo phase transitions that are reflected by relevant changes in the network geometry.

  6. Stochastic pooling networks

    NASA Astrophysics Data System (ADS)

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

    2009-01-01

    We introduce and define the concept of a stochastic pooling network (SPN), as a model for sensor systems where redundancy and two forms of 'noise'—lossy compression and randomness—interact in surprising ways. Our approach to analysing SPNs is information theoretic. We define an SPN as a network with multiple nodes that each produce noisy and compressed measurements of the same information. An SPN must combine all these measurements into a single further compressed network output, in a way dictated solely by naturally occurring physical properties—i.e. pooling—and yet cause no (or negligible) reduction in mutual information. This means that SPNs exhibit redundancy reduction as an emergent property of pooling. The SPN concept is applicable to examples in biological neural coding, nanoelectronics, distributed sensor networks, digital beamforming arrays, image processing, multiaccess communication networks and social networks. In most cases the randomness is assumed to be unavoidably present rather than deliberately introduced. We illustrate the central properties of SPNs for several case studies, where pooling occurs by summation, including nodes that are noisy scalar quantizers, and nodes with conditionally Poisson statistics. Other emergent properties of SPNs and some unsolved problems are also briefly discussed.

  7. Emergent Hyperbolic Network Geometry

    PubMed Central

    Bianconi, Ginestra; Rahmede, Christoph

    2017-01-01

    A large variety of interacting complex systems are characterized by interactions occurring between more than two nodes. These systems are described by simplicial complexes. Simplicial complexes are formed by simplices (nodes, links, triangles, tetrahedra etc.) that have a natural geometric interpretation. As such simplicial complexes are widely used in quantum gravity approaches that involve a discretization of spacetime. Here, by extending our knowledge of growing complex networks to growing simplicial complexes we investigate the nature of the emergent geometry of complex networks and explore whether this geometry is hyperbolic. Specifically we show that an hyperbolic network geometry emerges spontaneously from models of growing simplicial complexes that are purely combinatorial. The statistical and geometrical properties of the growing simplicial complexes strongly depend on their dimensionality and display the major universal properties of real complex networks (scale-free degree distribution, small-world and communities) at the same time. Interestingly, when the network dynamics includes an heterogeneous fitness of the faces, the growing simplicial complex can undergo phase transitions that are reflected by relevant changes in the network geometry. PMID:28167818

  8. Scaling in Transportation Networks

    PubMed Central

    Louf, Rémi; Roth, Camille; Barthelemy, Marc

    2014-01-01

    Subway systems span most large cities, and railway networks most countries in the world. These networks are fundamental in the development of countries and their cities, and it is therefore crucial to understand their formation and evolution. However, if the topological properties of these networks are fairly well understood, how they relate to population and socio-economical properties remains an open question. We propose here a general coarse-grained approach, based on a cost-benefit analysis that accounts for the scaling properties of the main quantities characterizing these systems (the number of stations, the total length, and the ridership) with the substrate's population, area and wealth. More precisely, we show that the length, number of stations and ridership of subways and rail networks can be estimated knowing the area, population and wealth of the underlying region. These predictions are in good agreement with data gathered for about subway systems and more than railway networks in the world. We also show that train networks and subway systems can be described within the same framework, but with a fundamental difference: while the interstation distance seems to be constant and determined by the typical walking distance for subways, the interstation distance for railways scales with the number of stations. PMID:25029528

  9. Networks of strong ties

    NASA Astrophysics Data System (ADS)

    Shi, Xiaolin; Adamic, Lada A.; Strauss, Martin J.

    2007-05-01

    Social networks transmitting covert or sensitive information cannot use all ties for this purpose. Rather, they can only use a subset of ties that are strong enough to be “trusted”. This paper addresses whether it is still possible, under this restriction, for information to be transmitted widely and rapidly in social networks. We use transitivity as evidence of strong ties, requiring one or more shared contacts in order to count an edge as strong. We examine the effect of removing all non-transitive ties in two real social network data sets, imposing varying thresholds in the number of shared contacts. We observe that transitive ties occupy a large portion of the network and that removing all other ties, while causing some individuals to become disconnected, preserves the majority of the giant connected component. Furthermore, the average shortest path, important for the rapid diffusion of information, increases only slightly relative to the original network. We also evaluate the cost of forming transitive ties by modeling a random graph composed entirely of closed triads and comparing its connectivity and average shortest path with the equivalent Erdös-Renyi random graph. Both the empirical study and random model point to a robustness of strong ties with respect to the connectivity and small world property of social networks.

  10. 78 FR 775 - Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division Alpharetta, GA...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-04

    ... Employment and Training Administration Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division Alpharetta, GA; Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division Hunt Valley, MD; Goodman Networks, Inc. Core Network Engineering (Deployment Engineering) Division...

  11. Neural Network Development Tool (NETS)

    NASA Technical Reports Server (NTRS)

    Baffes, Paul T.

    1990-01-01

    Artificial neural networks formed from hundreds or thousands of simulated neurons, connected in manner similar to that in human brain. Such network models learning behavior. Using NETS involves translating problem to be solved into input/output pairs, designing network configuration, and training network. Written in C.

  12. Assessing the Academic Networked Environment.

    ERIC Educational Resources Information Center

    Lippincott, Joan K.

    1999-01-01

    Describes a project of the Coalition for Networked Information, founded in 1990 to advance scholarship interest in the networked-computer environment. The project coordinated work of seven higher education institutions in conducting assessments of their campus networks. Topics discussed include the networking climate on campuses, why assessment is…

  13. The Adaptive Kernel Neural Network

    DTIC Science & Technology

    1989-10-01

    A neural network architecture for clustering and classification is described. The Adaptive Kernel Neural Network (AKNN) is a density estimation...classification layer. The AKNN retains the inherent parallelism common in neural network models. Its relationship to the kernel estimator allows the network to

  14. Renormalization group for evolving networks.

    PubMed

    Dorogovtsev, S N

    2003-04-01

    We propose a renormalization group treatment of stochastically growing networks. As an example, we study percolation on growing scale-free networks in the framework of a real-space renormalization group approach. As a result, we find that the critical behavior of percolation on the growing networks differs from that in uncorrelated networks.

  15. Network Leadership: An Emerging Practice

    ERIC Educational Resources Information Center

    Tremblay, Christopher W.

    2012-01-01

    Network leadership is an emerging approach that can have an impact on change in education and in society. According to Merriam-Webster (2011), a network is "an interconnected or interrelated chain, group, or system." Intentional interconnectedness is what separates network leadership from other leadership theories. Network leadership has the…

  16. From network structure to network reorganization: implications for adult neurogenesis

    NASA Astrophysics Data System (ADS)

    Schneider-Mizell, Casey M.; Parent, Jack M.; Ben-Jacob, Eshel; Zochowski, Michal R.; Sander, Leonard M.

    2010-12-01

    Networks can be dynamical systems that undergo functional and structural reorganization. One example of such a process is adult hippocampal neurogenesis, in which new cells are continuously born and incorporate into the existing network of the dentate gyrus region of the hippocampus. Many of these introduced cells mature and become indistinguishable from established neurons, joining the existing network. Activity in the network environment is known to promote birth, survival and incorporation of new cells. However, after epileptogenic injury, changes to the connectivity structure around the neurogenic niche are known to correlate with aberrant neurogenesis. The possible role of network-level changes in the development of epilepsy is not well understood. In this paper, we use a computational model to investigate how the structural and functional outcomes of network reorganization, driven by addition of new cells during neurogenesis, depend on the original network structure. We find that there is a stable network topology that allows the network to incorporate new neurons in a manner that enhances activity of the persistently active region, but maintains global network properties. In networks having other connectivity structures, new cells can greatly alter the distribution of firing activity and destroy the initial activity patterns. We thus find that new cells are able to provide focused enhancement of network only for small-world networks with sufficient inhibition. Network-level deviations from this topology, such as those caused by epileptogenic injury, can set the network down a path that develops toward pathological dynamics and aberrant structural integration of new cells.

  17. Program Helps Simulate Neural Networks

    NASA Technical Reports Server (NTRS)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  18. Neural networks in seismic discrimination

    SciTech Connect

    Dowla, F.U.

    1995-01-01

    Neural networks are powerful and elegant computational tools that can be used in the analysis of geophysical signals. At Lawrence Livermore National Laboratory, we have developed neural networks to solve problems in seismic discrimination, event classification, and seismic and hydrodynamic yield estimation. Other researchers have used neural networks for seismic phase identification. We are currently developing neural networks to estimate depths of seismic events using regional seismograms. In this paper different types of network architecture and representation techniques are discussed. We address the important problem of designing neural networks with good generalization capabilities. Examples of neural networks for treaty verification applications are also described.

  19. Quantifying randomness in real networks

    PubMed Central

    Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

    2015-01-01

    Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks—the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain—and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs. PMID:26482121

  20. Local-Area-Network Simulator

    NASA Technical Reports Server (NTRS)

    Gibson, Jim; Jordan, Joe; Grant, Terry

    1990-01-01

    Local Area Network Extensible Simulator (LANES) computer program provides method for simulating performance of high-speed local-area-network (LAN) technology. Developed as design and analysis software tool for networking computers on board proposed Space Station. Load, network, link, and physical layers of layered network architecture all modeled. Mathematically models according to different lower-layer protocols: Fiber Distributed Data Interface (FDDI) and Star*Bus. Written in FORTRAN 77.

  1. Interactome Networks and Human Disease

    PubMed Central

    Vidal, Marc; Cusick, Michael E.; Barabási, Albert-László

    2011-01-01

    Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease. PMID:21414488

  2. Computing preimages of Boolean networks

    PubMed Central

    2013-01-01

    In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network. Our probabilistic method runs in linear time with respect to the number of nodes in the network. We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases. PMID:24267277

  3. Computer and information networks.

    PubMed

    Greenberger, M; Aronofsky, J; McKenney, J L; Massy, W F

    1973-10-05

    The most basic conclusion coming out of the EDUCOM seminars is that computer networking must be acknowledged as an important new mode for obtaining information and computation (15). It is a real alternative that needs to be given serious attention in current planning and decision-making. Yet the fact is that many institutions are not taking account of networks when they confer on whether or how to replace their main computer. Articulation of the possibilities of computer networks goes back to the early 1960's and before, and working networks have been in evidence for several years now, both commercially and in universities. What is new, however, is the unmistakable recognition-bordering on a sense of the inevitable-that networks are finally practical and here to stay. The visionary and promotional phases of computer networks are over. It is time for hard-nosed comparative analysis (16). Another conclusion of the seminars has to do with the factors that hinder the fuller development of networking. The major problems to be overcome in applying networks to research and education are political, organizational, and economic in nature rather than technological. This is not to say that the hardware and software problems of linking computers and information systems are completely solved, but they are not the big bottlenecks at present. Research and educational institutions must find ways to organize themselves as well as their computers to work together for greater resource sharing. The coming of age of networks takes on special significance as a result of widespread dissatisfactions expressed with the present computing situation. There is a feeling that the current mode of autonomous, self-sufficient operation in the provision of computing and information services is frequently wasteful, deficient, and unresponsive to users' needs because of duplication of effort from one installation to another, incompatibilities, and inadequate documentation, program support, and user

  4. Mobile infostation network technology

    NASA Astrophysics Data System (ADS)

    Rajappan, Gowri; Acharya, Joydeep; Liu, Hongbo; Mandayam, Narayan; Seskar, Ivan; Yates, Roy

    2006-05-01

    Inefficient use of network resources on the battlefield is a serious liability: if an asset communicates with the network command for data-a terrain map, for instance-it ties up the end-to-end network resources. When many such assets contend for data simultaneously, traffic is limited by the slowest link along the path from the network command to the asset. A better approach is for a local server, known as an infostation, to download data on an anticipated-need basis when the network load is low. The infostation can then dump data when needed to the assets over a high-speed wireless connection. The infostation serves the local assets over an OFDM-based wireless data link that has MIMO enhancements for high data rate and robustness. We aim for data rate in excess of 100 Mbps, spectral efficiency in excess of 5 bits/sec/Hz, and robustness to poor channel conditions and jammers. We propose an adaptive physical layer that determines power levels, modulation schemes, and the MIMO enhancements to use based on the channel state and the level of interference in the system. We also incorporate the idea of superuser: a user who is allowed preferential use of the high data rate link. We propose a MAC that allows for this priority-based bandwidth allocation scheme. The proposed infostation MAC is integrated tightly with the physical layer through a cross-layer design. We call the proposed infostation PHY, MAC, and network technology, collectively, as the Mobile Infostation Network Technology (MINT).

  5. Exploring network operations for data and information networks

    NASA Astrophysics Data System (ADS)

    Yao, Bing; Su, Jing; Ma, Fei; Wang, Xiaomin; Zhao, Xiyang; Yao, Ming

    2017-01-01

    Barabási and Albert, in 1999, formulated scale-free models based on some real networks: World-Wide Web, Internet, metabolic and protein networks, language or sexual networks. Scale-free networks not only appear around us, but also have high qualities in the world. As known, high quality information networks can transfer feasibly and efficiently data, clearly, their topological structures are very important for data safety. We build up network operations for constructing large scale of dynamic networks from smaller scale of network models having good property and high quality. We focus on the simplest operators to formulate complex operations, and are interesting on the closeness of operations to desired network properties.

  6. Survivability of public transit network based on network structure entropy

    NASA Astrophysics Data System (ADS)

    Fu, Bai-Bai; Zhang, Lin; Li, Shu-Bin; Li, Yun-Xuan

    2015-01-01

    In this work, we have collected 195 bus routes and 1433 bus stations of Jinan city as sample date to build up the public transit geospatial network model by applying space L method, until May 2014. Then, by analyzing the topological properties of public transit geospatial network model, which include degree and degree distribution, average shortest path length, clustering coefficient and betweenness, we get the conclusion that public transit network is a typical complex network with scale-free and small-world characteristics. Furthermore, in order to analyze the survivability of public transit network, we define new network structure entropy based on betweenness importance, and prove its correctness by giving that the new network structure entropy has the same statistical characteristics with network efficiency. Finally, the "inflexion zone" is discovered, which can be taken as the momentous indicator to determine the public transit network failure.

  7. Network Motifs: Simple Building Blocks of Complex Networks

    NASA Astrophysics Data System (ADS)

    Milo, R.; Shen-Orr, S.; Itzkovitz, S.; Kashtan, N.; Chklovskii, D.; Alon, U.

    2002-10-01

    Complex networks are studied across many fields of science. To uncover their structural design principles, we defined ``network motifs,'' patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This approach may uncover the basic building blocks of most networks.

  8. Gradient networks on uncorrelated random scale-free networks

    NASA Astrophysics Data System (ADS)

    Pan, Gui-Jun; Yan, Xiao-Qing; Huang, Zhong-Bing; Ma, Wei-Chuan

    2011-03-01

    Uncorrelated random scale-free (URSF) networks are useful null models for checking the effects of scale-free topology on network-based dynamical processes. Here, we present a comparative study of the jamming level of gradient networks based on URSF networks and Erdős-Rényi (ER) random networks. We find that the URSF networks are less congested than ER random networks for the average degree langkrang>kc (kc ≈ 2 denotes a critical connectivity). In addition, by investigating the topological properties of the two kinds of gradient networks, we discuss the relations between the topological structure and the transport efficiency of the gradient networks. These findings show that the uncorrelated scale-free structure might allow more efficient transport than the random structure.

  9. Fluvial network organization imprints on microbial co-occurrence networks

    PubMed Central

    Widder, Stefanie; Besemer, Katharina; Singer, Gabriel A.; Ceola, Serena; Bertuzzo, Enrico; Quince, Christopher; Sloan, William T.; Rinaldo, Andrea; Battin, Tom J.

    2014-01-01

    Recent studies highlight linkages among the architecture of ecological networks, their persistence facing environmental disturbance, and the related patterns of biodiversity. A hitherto unresolved question is whether the structure of the landscape inhabited by organisms leaves an imprint on their ecological networks. We analyzed, based on pyrosequencing profiling of the biofilm communities in 114 streams, how features inherent to fluvial networks affect the co-occurrence networks that the microorganisms form in these biofilms. Our findings suggest that hydrology and metacommunity dynamics, both changing predictably across fluvial networks, affect the fragmentation of the microbial co-occurrence networks throughout the fluvial network. The loss of taxa from co-occurrence networks demonstrates that the removal of gatekeepers disproportionately contributed to network fragmentation, which has potential implications for the functions biofilms fulfill in stream ecosystems. Our findings are critical because of increased anthropogenic pressures deteriorating stream ecosystem integrity and biodiversity. PMID:25136087

  10. Fluvial network organization imprints on microbial co-occurrence networks.

    PubMed

    Widder, Stefanie; Besemer, Katharina; Singer, Gabriel A; Ceola, Serena; Bertuzzo, Enrico; Quince, Christopher; Sloan, William T; Rinaldo, Andrea; Battin, Tom J

    2014-09-02

    Recent studies highlight linkages among the architecture of ecological networks, their persistence facing environmental disturbance, and the related patterns of biodiversity. A hitherto unresolved question is whether the structure of the landscape inhabited by organisms leaves an imprint on their ecological networks. We analyzed, based on pyrosequencing profiling of the biofilm communities in 114 streams, how features inherent to fluvial networks affect the co-occurrence networks that the microorganisms form in these biofilms. Our findings suggest that hydrology and metacommunity dynamics, both changing predictably across fluvial networks, affect the fragmentation of the microbial co-occurrence networks throughout the fluvial network. The loss of taxa from co-occurrence networks demonstrates that the removal of gatekeepers disproportionately contributed to network fragmentation, which has potential implications for the functions biofilms fulfill in stream ecosystems. Our findings are critical because of increased anthropogenic pressures deteriorating stream ecosystem integrity and biodiversity.

  11. Network fingerprint: a knowledge-based characterization of biomedical networks

    PubMed Central

    Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen

    2015-01-01

    It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246

  12. French fireball network FRIPON

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

    FRIPON (Fireball Recovery and Interplanetary Observation Network) was recently founded by ANR (Agence Nationale de la Recherche), its aim being to connect meteoritical science with asteroidal and cometary sciences, in order to better understand our solar system formation and evolution. The main idea is to cover all the French territory to collect a large number of meteorites (one or two per year) with an accurate orbit determination, allowing to pinpoint possible parent bodies. 100 all-sky cameras will be installed at the end of 2015, creating a dense network with an average distance of 100 km between the stations. To maximize the accuracy of the orbit determination, we will mix our optical data with radar data from the GRAVES transmitter received by 25 stations (Rault et al., 2015). As the network installation and the creation of research teams for meteorites involves many persons, at least many more than our small team of professionals, we will develop a participative science network for amateurs called Vigie-Ciel (Zanda et al., 2015). It will be possible to simply use our data, participate in research campaigns or even add cameras to the FRIPON network.

  13. Yugoslav strong motion network

    NASA Astrophysics Data System (ADS)

    Mihailov, Vladimir

    1985-04-01

    Data concerning ground motion and the response of structures during strong earthquakes are necessary for seismic hazard evaluation and the definition of design criteria for structures to be constructed in seismically active zones. The only way to obtain such data is the installation of a strong-motion instrument network. The Yugoslav strong-motion programme was created in 1972 to recover strong-motion response data used by the structural engineering community in developing earthquake resistant design. Instruments, accelerographs SMA-1 and seismoscopes WM-1, were installed in free-field stations and on structures (high-rise buildings, dams, bridges, etc.). A total number of 176 accelerographs and 137 seismoscopes have been installed and are operating in Yugoslavia. The strong-motion programme in Yugoslavia consists of five subactivities: network design, network operation, data processing, network management and research as well as application. All these activities are under the responsibility of IZIIS in cooperation with the Yugoslav Association of Seismology. By 1975 in the realisation of this project participated the CALTECH as cooperative institution in the joint American-Yugoslav cooperative project. The results obtained which are presented in this paper, and their application in the aseismic design justify the necessity for the existence of such a network in Yugoslavia.

  14. Social Network Infiltration

    NASA Astrophysics Data System (ADS)

    Plait, Philip

    2008-05-01

    Social networks are websites (or software that distributes media online) where users can distribute content to either a list of friends on that site or to anyone who surfs onto their page, and where those friends can interact and discuss the content. By linking to friends online, the users’ personal content (pictures, songs, favorite movies, diaries, websites, and so on) is dynamically distributed, and can "become viral", that is, get spread rapidly as more people see it and spread it themselves. Social networks are immensely popular around the planet, especially with younger users. The biggest social networks are Facebook and MySpace; an IYA2009 user already exists on Facebook, and one will be created for MySpace (in fact, several NASA satellites such as GLAST and Swift already have successful MySpace pages). Twitter is another network where data distribution is more limited; it is more like a mini-blog, but is very popular. IYA2009 already has a Twitter page, and will be updated more often with relevant information. In this talk I will review the existing social networks, show people how and why they are useful, and give them the tools they need to contribute meaningfully to IYA's online reach.

  15. Network Consistent Data Association.

    PubMed

    Chakraborty, Anirban; Das, Abir; Roy-Chowdhury, Amit K

    2016-09-01

    Existing data association techniques mostly focus on matching pairs of data-point sets and then repeating this process along space-time to achieve long term correspondences. However, in many problems such as person re-identification, a set of data-points may be observed at multiple spatio-temporal locations and/or by multiple agents in a network and simply combining the local pairwise association results between sets of data-points often leads to inconsistencies over the global space-time horizons. In this paper, we propose a Novel Network Consistent Data Association (NCDA) framework formulated as an optimization problem that not only maintains consistency in association results across the network, but also improves the pairwise data association accuracies. The proposed NCDA can be solved as a binary integer program leading to a globally optimal solution and is capable of handling the challenging data-association scenario where the number of data-points varies across different sets of instances in the network. We also present an online implementation of NCDA method that can dynamically associate new observations to already observed data-points in an iterative fashion, while maintaining network consistency. We have tested both the batch and the online NCDA in two application areas-person re-identification and spatio-temporal cell tracking and observed consistent and highly accurate data association results in all the cases.

  16. Network-Friendly Gossiping

    NASA Astrophysics Data System (ADS)

    Serbu, Sabina; Rivière, Étienne; Felber, Pascal

    The emergence of large-scale distributed applications based on many-to-many communication models, e.g., broadcast and decentralized group communication, has an important impact on the underlying layers, notably the Internet routing infrastructure. To make an effective use of network resources, protocols should both limit the stress (amount of messages) on each infrastructure entity like routers and links, and balance as much as possible the load in the network. Most protocols use application-level metrics such as delays to improve efficiency of content dissemination or routing, but the extend to which such application-centric optimizations help reduce and balance the load imposed to the infrastructure is unclear. In this paper, we elaborate on the design of such network-friendly protocols and associated metrics. More specifically, we investigate random-based gossip dissemination. We propose and evaluate different ways of making this representative protocol network-friendly while keeping its desirable properties (robustness and low delays). Simulations of the proposed methods using synthetic and real network topologies convey and compare their abilities to reduce and balance the load while keeping good performance.

  17. Bimodality in Network Control

    NASA Astrophysics Data System (ADS)

    Jia, Tao; Liu, Yang-Yu; Posfai, Marton; Slotine, Jean-Jacques; Barabasi, Albert-Laszlo

    2013-03-01

    Controlling complex systems is a fundamental challenge of network science. Recent tools enable us to identify the minimum driver nodes, from which we can control a system. They also indicate a multiplicity of minimum driver node sets (MDS's): multiple combinations of the same number of nodes can achieve control over the system. This multiplicity allows us to classify individual nodes as critical if they are involved in all control configurations, intermittent if they occasionally act as driver nodes and redundant if they do not play any role in control. We develop computational and analytical framework analyzing nodes in each category in both model and real networks. We find that networks with identical degree distribution can be in two distinct control modes, ``centralized'' or ``distributed'', with drastic change on the role of each node in maintaining the controllability and orders of magnitude difference in the number of MDS's. In analyzing both model and real networks, we find that the two modes can be inferred directly from the network's degree distribution. Finally we show that the two control modes can be switched by small structural perturbations, leading to potential applications of control theory in real systems.

  18. The ANTARES observation network

    NASA Astrophysics Data System (ADS)

    Dogliotti, Ana I.; Ulloa, Osvaldo; Muller-Karger, Frank; Hu, Chuanmin; Murch, Brock; Taylor, Charles; Yuras, Gabriel; Kampel, Milton; Lutz, Vivian; Gaeta, Salvador; Gagliardini, Domingo A.; Garcia, Carlos A. E.; Klein, Eduardo; Helbling, Walter; Varela, Ramon; Barbieri, Elena; Negri, Ruben; Frouin, Robert; Sathyendranath, Shubha; Platt, Trevor

    2005-08-01

    The ANTARES network seeks to understand the variability of the coastal environment on a continental scale and the local, regional, and global factors and processes that effect this change. The focus are coastal zones of South America and the Caribbean Sea. The initial approach includes developing time series of in situ and satellite-based environmental observations in coastal and oceanic regions. The network is constituted by experts that seek to exchange ideas, develop an infrastructure for mutual logistical and knowledge support, and link in situ time series of observations located around the Americas with real-time and historical satellite-derived time series of relevant products. A major objective is to generate information that will be distributed publicly and openly in the service of coastal ocean research, resource management, science-based policy making and education in the Americas. As a first stage, the network has linked oceanographic time series located in Argentina, Brazil, Chile and Venezuela. The group has also developed an online tool to examine satellite data collected with sensors such as NASA's MODIS. Specifically, continental-scale high-resolution (1 km) maps of chlorophyll and of sea surface temperature are generated and served daily over the web according to specifications of users within the ANTARES network. Other satellite-derived variables will be added as support for the network is solidified. ANTARES serves data and offers simple analysis tools that anyone can use with the ultimate goal of improving coastal assessments, management and policies.

  19. Networks of Emotion Concepts

    PubMed Central

    Toivonen, Riitta; Kivelä, Mikko; Saramäki, Jari; Viinikainen, Mikko; Vanhatalo, Maija; Sams, Mikko

    2012-01-01

    The aim of this work was to study the similarity network and hierarchical clustering of Finnish emotion concepts. Native speakers of Finnish evaluated similarity between the 50 most frequently used Finnish words describing emotional experiences. We hypothesized that methods developed within network theory, such as identifying clusters and specific local network structures, can reveal structures that would be difficult to discover using traditional methods such as multidimensional scaling (MDS) and ordinary cluster analysis. The concepts divided into three main clusters, which can be described as negative, positive, and surprise. Negative and positive clusters divided further into meaningful sub-clusters, corresponding to those found in previous studies. Importantly, this method allowed the same concept to be a member in more than one cluster. Our results suggest that studying particular network structures that do not fit into a low-dimensional description can shed additional light on why subjects evaluate certain concepts as similar. To encourage the use of network methods in analyzing similarity data, we provide the analysis software for free use (http://www.becs.tkk.fi/similaritynets/). PMID:22276099

  20. Optimal synchronizability of networks

    NASA Astrophysics Data System (ADS)

    Wang, B.; Zhou, T.; Xiu, Z. L.; Kim, B. J.

    2007-11-01

    We numerically investigate how to enhance synchronizability of coupled identical oscillators in complex networks with research focus on the roles of the high level of clustering for a given heterogeneity in the degree distribution. By using the edge-exchange method with the fixed degree sequence, we first directly maximize synchronizability measured by the eigenratio of the coupling matrix, through the use of the so-called memory tabu search algorithm developed in applied mathematics. The resulting optimal network, which turns out to be weakly disassortative, is observed to exhibit a small modularity. More importantly, it is clearly revealed that the optimally synchronizable network for a given degree sequence shows a very low level of clustering, containing much fewer small-size loops than the original network. We then use the clustering coefficient as an object function to be reduced during the edge exchanges, and find it a very efficient way to enhance synchronizability. We thus conclude that under the condition of a given degree heterogeneity, the clustering plays a very important role in the network synchronization.

  1. Network testbed creation and validation

    DOEpatents

    Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.; Watts, Kristopher K.; Sweeney, Andrew John

    2017-03-21

    Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices, embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.

  2. Structure of brain functional networks.

    PubMed

    Kuchaiev, Oleksii; Wang, Po T; Nenadic, Zoran; Przulj, Natasa

    2009-01-01

    Brain is a complex network optimized both for segregated and distributed information processing. To perform cognitive tasks, different areas of the brain must "cooperate," thereby forming complex networks of interactions also known as brain functional networks. Previous studies have shown that these networks exhibit "small-world" characteristics. Small-world topology, however, is a general property of all brain functional networks and does not capture structural changes in these networks in response to different stimuli or cognitive tasks. Here we show how novel graph theoretic techniques can be utilized for precise analysis of brain functional networks. These techniques allow us to detect structural changes in brain functional networks in response to different stimuli or cognitive tasks. For certain types of cognitive tasks we have found that these networks exhibit geometric structure in addition to the small-world topology. The method has been applied to the electrocorticographic signals of six epileptic patients.

  3. Graph distance for complex networks

    NASA Astrophysics Data System (ADS)

    Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

    2016-10-01

    Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions.

  4. Network testbed creation and validation

    DOEpatents

    Thai, Tan Q.; Urias, Vincent; Van Leeuwen, Brian P.; Watts, Kristopher K.; Sweeney, Andrew John

    2017-04-18

    Embodiments of network testbed creation and validation processes are described herein. A "network testbed" is a replicated environment used to validate a target network or an aspect of its design. Embodiments describe a network testbed that comprises virtual testbed nodes executed via a plurality of physical infrastructure nodes. The virtual testbed nodes utilize these hardware resources as a network "fabric," thereby enabling rapid configuration and reconfiguration of the virtual testbed nodes without requiring reconfiguration of the physical infrastructure nodes. Thus, in contrast to prior art solutions which require a tester manually build an emulated environment of physically connected network devices, embodiments receive or derive a target network description and build out a replica of this description using virtual testbed nodes executed via the physical infrastructure nodes. This process allows for the creation of very large (e.g., tens of thousands of network elements) and/or very topologically complex test networks.

  5. Social Network Visualization in Epidemiology

    PubMed Central

    Christakis, Nicholas A.; Fowler, James H.

    2010-01-01

    Epidemiological investigations and interventions are increasingly focusing on social networks. Two aspects of social networks are relevant in this regard: the structure of networks and the function of networks. A better understanding of the processes that determine how networks form and how they operate with respect to the spread of behavior holds promise for improving public health. Visualizing social networks is a key to both research and interventions. Network images supplement statistical analyses and allow the identification of groups of people for targeting, the identification of central and peripheral individuals, and the clarification of the macro-structure of the network in a way that should affect public health interventions. People are inter-connected and so their health is inter-connected. Inter-personal health effects in social networks provide a new foundation for public health. PMID:22544996

  6. Forman curvature for complex networks

    NASA Astrophysics Data System (ADS)

    Sreejith, R. P.; Mohanraj, Karthikeyan; Jost, Jürgen; Saucan, Emil; Samal, Areejit

    2016-06-01

    We adapt Forman’s discretization of Ricci curvature to the case of undirected networks, both weighted and unweighted, and investigate the measure in a variety of model and real-world networks. We find that most nodes and edges in model and real networks have a negative curvature. Furthermore, the distribution of Forman curvature of nodes and edges is narrow in random and small-world networks, while the distribution is broad in scale-free and real-world networks. In most networks, Forman curvature is found to display significant negative correlation with degree and centrality measures. However, Forman curvature is uncorrelated with clustering coefficient in most networks. Importantly, we find that both model and real networks are vulnerable to targeted deletion of nodes with highly negative Forman curvature. Our results suggest that Forman curvature can be employed to gain novel insights on the organization of complex networks.

  7. Graph distance for complex networks

    PubMed Central

    Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

    2016-01-01

    Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions. PMID:27725690

  8. Cyclic networks of quantum gates

    NASA Astrophysics Data System (ADS)

    Cabauy, Peter

    In this thesis we first give an introduction to the basic aspects of quantum computation followed by an analysis of networks of quantum logic gates where the qubit lines are loops (cyclic). Thus far, investigations into cyclic networks of quantum logic gates have not been examined (as far as we know) by the quantum information community. In our investigations of cyclic quantum networks we have studied simple, one and two qubit systems. The analysis includes: classifying networks into groups, the dynamics of the qubits in a cyclic quantum network, and the perturbation effects of an external qubit acting on a cyclic quantum network. The analysis will be followed by a discussion on quantum algorithms and quantum information processing with cyclic quantum networks, a novel implementation of a cyclic network quantum memory and a discussion of quantum sensors via cyclic quantum networks.

  9. Whether information network supplements friendship network

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  10. Applications of Social Network Analysis

    NASA Astrophysics Data System (ADS)

    Thilagam, P. Santhi

    A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

  11. FRIPON network status

    NASA Astrophysics Data System (ADS)

    Colas, F.; Zanda, B.; Bouley, S.; Vaubaillon, J.; Marmo, C.; Audureau, Y.; Kwon, M.-K.; Rault, J.-L.; Vernazza, P.; Gattacceca, J.; Caminade, S.; Birlan, M.; Maquet, L.; Egal, A.; Rotaru, M.; Jorda, L.; Birnbaum, C.; Blanpain, C.; Malgoyre, A.; Lecubin, J.; Cellino, A.; Gardiol, D.; Di Martino, M.; Nitschelm, C.; Camargo, J.; Valenzuela, M.; Ferrière, L.; Popescu, M.; Loizeau, D.

    2016-01-01

    The FRIPON network (Fireball Recovery and Interplanetary observation Network) will be fully operational in 2016 (www.fripon.org). This "open source" project includes several new features that will be described in detail. We also discuss the opportunities for expansion outside France. The main innovation is the connectivity of cameras enabling better efficiency for meteors detection, and the possibility of computing orbits in real time to organize an observation campaign within 24 hours. Another innovation is the ability to daytime detections. Statistics show that there are more meteorites in late afternoon than during the rest of the day because of their low speed. As the project has been designed from the start to handle a large number of cameras it is easy to extend it to increase its effectiveness. I will show the next extension of the network and its operation.

  12. Neighborhood Environmental Watch Network

    SciTech Connect

    Sanders, L.D.

    1993-10-01

    The Neighborhood Environmental Watch Network (NEWNET) is a regional network of environmental monitoring stations and a data archival center that supports collaboration between communities, industry, and government agencies to solve environmental problems. The stations provide local displays of measurements for the public and transmit measurements via satellite to a central site for archival and analysis. Station managers are selected from the local community and trained to support the stations. Archived data and analysis tools are available to researchers, educational institutions, industrial collaborators, and the public across the nation through a communications network. Los Alamos National Laboratory and the Environmental Protection Agency have developed a NEWNET pilot program for the Department of Energy. The pilot program supports monitoring stations in Nevada, Arizona, Utah, Wyoming, and California. Additional stations are being placed in Colorado and New Mexico. Pilot stations take radiological and meteorological measurements. Other measurements are possible by exchanging sensors.

  13. Network acceleration techniques

    NASA Technical Reports Server (NTRS)

    Crowley, Patricia (Inventor); Awrach, James Michael (Inventor); Maccabe, Arthur Barney (Inventor)

    2012-01-01

    Splintered offloading techniques with receive batch processing are described for network acceleration. Such techniques offload specific functionality to a NIC while maintaining the bulk of the protocol processing in the host operating system ("OS"). The resulting protocol implementation allows the application to bypass the protocol processing of the received data. Such can be accomplished this by moving data from the NIC directly to the application through direct memory access ("DMA") and batch processing the receive headers in the host OS when the host OS is interrupted to perform other work. Batch processing receive headers allows the data path to be separated from the control path. Unlike operating system bypass, however, the operating system still fully manages the network resource and has relevant feedback about traffic and flows. Embodiments of the present disclosure can therefore address the challenges of networks with extreme bandwidth delay products (BWDP).

  14. Network topology mapper

    DOEpatents

    Quist, Daniel A.; Gavrilov, Eugene M.; Fisk, Michael E.

    2008-01-15

    A method enables the topology of an acyclic fully propagated network to be discovered. A list of switches that comprise the network is formed and the MAC address cache for each one of the switches is determined. For each pair of switches, from the MAC address caches the remaining switches that see the pair of switches are located. For each pair of switches the remaining switches are determined that see one of the pair of switches on a first port and the second one of the pair of switches on a second port. A list of insiders is formed for every pair of switches. It is determined whether the insider for each pair of switches is a graph edge and adjacent ones of the graph edges are determined. A symmetric adjacency matrix is formed from the graph edges to represent the topology of the data link network.

  15. Hyperswitch Communication Network Computer

    NASA Technical Reports Server (NTRS)

    Peterson, John C.; Chow, Edward T.; Priel, Moshe; Upchurch, Edwin T.

    1993-01-01

    Hyperswitch Communications Network (HCN) computer is prototype multiple-processor computer being developed. Incorporates improved version of hyperswitch communication network described in "Hyperswitch Network For Hypercube Computer" (NPO-16905). Designed to support high-level software and expansion of itself. HCN computer is message-passing, multiple-instruction/multiple-data computer offering significant advantages over older single-processor and bus-based multiple-processor computers, with respect to price/performance ratio, reliability, availability, and manufacturing. Design of HCN operating-system software provides flexible computing environment accommodating both parallel and distributed processing. Also achieves balance among following competing factors; performance in processing and communications, ease of use, and tolerance of (and recovery from) faults.

  16. Neural network technologies

    NASA Technical Reports Server (NTRS)

    Villarreal, James A.

    1991-01-01

    A whole new arena of computer technologies is now beginning to form. Still in its infancy, neural network technology is a biologically inspired methodology which draws on nature's own cognitive processes. The Software Technology Branch has provided a software tool, Neural Execution and Training System (NETS), to industry, government, and academia to facilitate and expedite the use of this technology. NETS is written in the C programming language and can be executed on a variety of machines. Once a network has been debugged, NETS can produce a C source code which implements the network. This code can then be incorporated into other software systems. Described here are various software projects currently under development with NETS and the anticipated future enhancements to NETS and the technology.

  17. Worldwide standardized seismograph network

    USGS Publications Warehouse

    Peterson, J.

    1977-01-01

    A global network of seismographs is as indispensable to seismologists as telescopes are to astronomers. The network is used to catalog the thousands of earthquakes that occur each year and to provide the data needed for detailed studies of earthquake mechanisms, deep Earth structure, and tectonic processes. Like astronomy, seismology is an observational science, and most of the scientific advances have been preceded by improvements in instrument technology. To be useful for seismic studies, new technology must be applied on a global scale. During the past two decades, there has been notable success in meeting this objective. The network that exists today (fig. 1) is a vital scientific resource. Continued innovations and improvements are needed to insure that its keeps pace with the data needs of the seismological community. 

  18. Robust distribution network reconfiguration

    SciTech Connect

    Lee, Changhyeok; Liu, Cong; Mehrotra, Sanjay; Bie, Zhaohong

    2015-03-01

    We propose a two-stage robust optimization model for the distribution network reconfiguration problem with load uncertainty. The first-stage decision is to configure the radial distribution network and the second-stage decision is to find the optimal a/c power flow of the reconfigured network for given demand realization. We solve the two-stage robust model by using a column-and-constraint generation algorithm, where the master problem and subproblem are formulated as mixed-integer second-order cone programs. Computational results for 16, 33, 70, and 94-bus test cases are reported. We find that the configuration from the robust model does not compromise much the power loss under the nominal load scenario compared to the configuration from the deterministic model, yet it provides the reliability of the distribution system for all scenarios in the uncertainty set.

  19. Controllability analysis of networks

    NASA Astrophysics Data System (ADS)

    Lombardi, Anna; Hörnquist, Michael

    2007-05-01

    The concept of controllability of linear systems from control theory is applied to networks inspired by biology. A node is in this context controllable if an external signal can be applied which can adjust the level (e.g., protein concentration) of the node in a finite time to an arbitrary value, regardless of the levels of the other nodes. The property of being downstream of the node to which the input is applied turns out to be a necessary but not a sufficient condition for being controllable. An interpretation of the controllability matrix, when applied to networks, is also given. Finally, two case studies are provided in order to better explain the concepts, as well as some results for a gene regulatory network of fission yeast.

  20. High speed optical networks

    NASA Astrophysics Data System (ADS)

    Frankel, Michael Y.; Livas, Jeff

    2005-02-01

    This overview will discuss core network technology and cost trade-offs inherent in choosing between "analog" architectures with high optical transparency, and ones heavily dependent on frequent "digital" signal regeneration. The exact balance will be related to the specific technology choices in each area outlined above, as well as the network needs such as node geographic spread, physical connectivity patterns, and demand loading. Over the course of a decade, optical networks have evolved from simple single-channel SONET regenerator-based links to multi-span multi-channel optically amplified ultra-long haul systems, fueled by high demand for bandwidth at reduced cost. In general, the cost of a well-designed high capacity system is dominated by the number of optical to electrical (OE) and electrical to optical (EO) conversions required. As the reach and channel capacity of the transport systems continued to increase, it became necessary to improve the granularity of the demand connections by introducing (optical add/drop multiplexers) OADMs. Thus, if a node requires only small demand connectivity, most of the optical channels are expressed through without regeneration (OEO). The network costs are correspondingly reduced, partially balanced by the increased cost of the OADM nodes. Lately, the industry has been aggressively pursuing a natural extension of this philosophy towards all-optical "analog" core networks, with each demand touching electrical digital circuitry only at the in/egress nodes. This is expected to produce a substantial elimination of OEO costs, increase in network capacity, and a notionally simpler operation and service turn-up. At the same time, such optical "analog" network requires a large amount of complicated hardware and software for monitoring and manipulating high bit rate optical signals. New and more complex modulation formats that provide resiliency to both optical noise and nonlinear propagation effects are important for extended

  1. Multilayer Optical Learning Networks

    NASA Astrophysics Data System (ADS)

    Wagner, Kelvin; Psaltis, Demetri

    1987-08-01

    In this paper we present a new approach to learning in a multilayer optical neural network which is based on holographically interconnected nonlinear Fabry-Perot etalons. The network can learn the interconnections that form a distributed representation of a desired pattern transformation operation. The interconnections are formed in an adaptive and self aligning fashion, as volume holographic gratings in photorefractive crystals. Parallel arrays of globally space integrated inner products diffracted by the interconnecting hologram illuminate arrays of nonlinear Fabry-Perot etalons for fast thresholding of the transformed patterns. A phase conjugated reference wave interferes with a backwards propagating error signal to form holographic interference patterns which are time integrated in the volume of the photorefractive crystal in order to slowly modify and learn the appropriate self aligning interconnections. A holographic implementation of a single layer perceptron learning procedure is presented that can be extendept ,to a multilayer learning network through an optical implementation of the backward error propagation (BEP) algorithm.

  2. Hyperbolic Hopfield neural networks.

    PubMed

    Kobayashi, M

    2013-02-01

    In recent years, several neural networks using Clifford algebra have been studied. Clifford algebra is also called geometric algebra. Complex-valued Hopfield neural networks (CHNNs) are the most popular neural networks using Clifford algebra. The aim of this brief is to construct hyperbolic HNNs (HHNNs) as an analog of CHNNs. Hyperbolic algebra is a Clifford algebra based on Lorentzian geometry. In this brief, a hyperbolic neuron is defined in a manner analogous to a phasor neuron, which is a typical complex-valued neuron model. HHNNs share common concepts with CHNNs, such as the angle and energy. However, HHNNs and CHNNs are different in several aspects. The states of hyperbolic neurons do not form a circle, and, therefore, the start and end states are not identical. In the quantized version, unlike complex-valued neurons, hyperbolic neurons have an infinite number of states.

  3. The Social Network Classroom

    NASA Astrophysics Data System (ADS)

    Bunus, Peter

    Online social networking is an important part in the everyday life of college students. Despite the increasing popularity of online social networking among students and faculty members, its educational benefits are largely untested. This paper presents our experience in using social networking applications and video content distribution websites as a complement of traditional classroom education. In particular, the solution has been based on effective adaptation, extension and integration of Facebook, Twitter, Blogger YouTube and iTunes services for delivering educational material to students on mobile platforms like iPods and 3 rd generation mobile phones. The goals of the proposed educational platform, described in this paper, are to make the learning experience more engaging, to encourage collaborative work and knowledge sharing among students, and to provide an interactive platform for the educators to reach students and deliver lecture material in a totally new way.

  4. Semilocal cosmic string networks

    SciTech Connect

    Achucarro, Ana; Salmi, Petja; Urrestilla, Jon

    2007-06-15

    We report on a large-scale numerical study of networks of semilocal cosmic strings in flat space in the parameter regime in which they are perturbatively stable. We find a population of segments with an exponential length distribution and indications of a scaling network without significant loop formation. Very deep in the stability regime strings of superhorizon size grow rapidly and ''percolate'' through the box. We believe these should lead at late times to a population of infinite strings similar to topologically stable strings. However, the strings are very light; scalar gradients dominate the energy density, and the network has thus a global texturelike signature. As a result, the observational constraints, at least from the temperature power spectrum of the cosmic microwave background, on models predicting semilocal strings should be closer to those on global textures or monopoles, rather than on topologically stable gauged cosmic strings.

  5. Synchronization in complex networks

    SciTech Connect

    Arenas, A.; Diaz-Guilera, A.; Moreno, Y.; Zhou, C.; Kurths, J.

    2007-12-12

    Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.

  6. Flows in Polymer Networks

    NASA Astrophysics Data System (ADS)

    Tanaka, Fumihiko

    A simple transient network model is introduced to describe creation and annihilation of junctions in the networks of associating polymers. Stationary non-linear viscosity is calculated by the theory and by Monte Carlo simulation to study shear thickening. The dynamic mechanical moduli are calculated as functions of the frequency and the chain disengagement rate. From the peak of the loss modulus, the lifetime τx of the junction is estimated, and from the high frequency plateau of the storage modulus, the number of elastically effective chains in the network is found. Transient phenomena such as stress relaxation and stress overshoot are also theoretically studied. Results are compared with the recent experimental reports on the rheological study of hydrophobically modified water-soluble polymeters.

  7. Universality in network dynamics

    PubMed Central

    Barzel, Baruch; Barabási, Albert-László

    2013-01-01

    Despite significant advances in characterizing the structural properties of complex networks, a mathematical framework that uncovers the universal properties of the interplay between the topology and the dynamics of complex systems continues to elude us. Here we develop a self-consistent theory of dynamical perturbations in complex systems, allowing us to systematically separate the contribution of the network topology and dynamics. The formalism covers a broad range of steady-state dynamical processes and offers testable predictions regarding the system's response to perturbations and the development of correlations. It predicts several distinct universality classes whose characteristics can be derived directly from the continuum equation governing the system's dynamics and which are validated on several canonical network-based dynamical systems, from biochemical dynamics to epidemic spreading. Finally, we collect experimental data pertaining to social and biological systems, demonstrating that we can accurately uncover their universality class even in the absence of an appropriate continuum theory that governs the system's dynamics. PMID:24319492

  8. LCOGT network observatory operations

    NASA Astrophysics Data System (ADS)

    Pickles, Andrew; Hjelstrom, Annie; Boroson, Todd; Burleson, Ben; Conway, Patrick; De Vera, Jon; Elphick, Mark; Haworth, Brian; Rosing, Wayne; Saunders, Eric; Thomas, Doug; White, Gary; Willis, Mark; Walker, Zach

    2014-08-01

    We describe the operational capabilities of the Las Cumbres Observatory Global Telescope Network. We summarize our hardware and software for maintaining and monitoring network health. We focus on methodologies to utilize the automated system to monitor availability of sites, instruments and telescopes, to monitor performance, permit automatic recovery, and provide automatic error reporting. The same jTCS control system is used on telescopes of apertures 0.4m, 0.8m, 1m and 2m, and for multiple instruments on each. We describe our network operational model, including workloads, and illustrate our current tools, and operational performance indicators, including telemetry and metrics reporting from on-site reductions. The system was conceived and designed to establish effective, reliable autonomous operations, with automatic monitoring and recovery - minimizing human intervention while maintaining quality. We illustrate how far we have been able to achieve that.

  9. [Health care networks].

    PubMed

    Mendes, Eugênio Vilaça

    2010-08-01

    The demographic and epidemiologic transition resulting from aging and the increase of life expectation means an increment related to chronic conditions. The healthcare systems contemporary crisis is characterized by the organization of the focus on fragmented systems turned to the acute conditions care, in spite of the chronic conditions prevalence, and by the hierarchical structure without communication flow among the different health care levels. Brazil health care situation profile is now presenting a triple burden of diseases, due to the concomitant presence of infectious diseases, external causes and chronic diseases. The solution is to restore the consistence between the triple burden of diseases on the health situation and the current system of healthcare practice, with the implantation of health care networks. The conclusion is that there are evidences in the international literature on health care networks that these networks may improve the clinical quality, the sanitation results and the user's satisfaction and the reduction of healthcare systems costs.

  10. Shareholding Networks in Japan

    NASA Astrophysics Data System (ADS)

    Souma, Wataru; Fujiwara, Yoshi; Aoyama, Hideaki

    2005-06-01

    The Japanese shareholding network existing at the end of March 2002 is studied empirically. The network is constructed from 2,303 listed companies and 53 non-listed financial institutions. We consider this network as a directed graph by drawing edges from shareholders to stock corporations. The lengths of the shareholder lists vary with the companies, and the most comprehensive lists contain the top 30 shareholders. Consequently, the distribution of incoming edges has an upper bound, while that of outgoing edges has no bound. The distribution of outgoing degrees is well explained by the power law function with an exponential tail. The exponent in the power law range is γ = 1.7. To understand these features from the viewpoint of a company's growth, we consider the correlations between the outgoing degree and the company's age, profit, and total assets.

  11. Programmable multimode quantum networks

    PubMed Central

    Armstrong, Seiji; Morizur, Jean-François; Janousek, Jiri; Hage, Boris; Treps, Nicolas; Lam, Ping Koy; Bachor, Hans-A.

    2012-01-01

    Entanglement between large numbers of quantum modes is the quintessential resource for future technologies such as the quantum internet. Conventionally, the generation of multimode entanglement in optics requires complex layouts of beamsplitters and phase shifters in order to transform the input modes into entangled modes. Here we report the highly versatile and efficient generation of various multimode entangled states with the ability to switch between different linear optics networks in real time. By defining our modes to be combinations of different spatial regions of one beam, we may use just one pair of multi-pixel detectors in order to measure multiple entangled modes. We programme virtual networks that are fully equivalent to the physical linear optics networks they are emulating. We present results for N=2 up to N=8 entangled modes here, including N=2, 3, 4 cluster states. Our approach introduces the highly sought after attributes of flexibility and scalability to multimode entanglement. PMID:22929783

  12. Hyperswitch Communication Network Computer

    NASA Technical Reports Server (NTRS)

    Peterson, John C.; Chow, Edward T.; Priel, Moshe; Upchurch, Edwin T.

    1993-01-01

    Hyperswitch Communications Network (HCN) computer is prototype multiple-processor computer being developed. Incorporates improved version of hyperswitch communication network described in "Hyperswitch Network For Hypercube Computer" (NPO-16905). Designed to support high-level software and expansion of itself. HCN computer is message-passing, multiple-instruction/multiple-data computer offering significant advantages over older single-processor and bus-based multiple-processor computers, with respect to price/performance ratio, reliability, availability, and manufacturing. Design of HCN operating-system software provides flexible computing environment accommodating both parallel and distributed processing. Also achieves balance among following competing factors; performance in processing and communications, ease of use, and tolerance of (and recovery from) faults.

  13. Synchronization On Hanoi Networks

    NASA Astrophysics Data System (ADS)

    Li, Shanshan; Boettcher, Stefan

    2015-03-01

    Synchronization of coupled oscillators has been intensively studied on a variety of structures. It is believed that the dynamics is deeply associated with its structure. To explore this relation, we study the synchronization of coupled oscillators on Hanoi networks. We analyze the evolution of coupled units over time, and characterized the convergence to the global synchronized state. For this state, the results show a close connection to the spectrum of connectivity matrix. Inspired by this connection, we try to show a dynamical pattern that describes the entire synchronization process from the onset to the final state. This may unveil the unique hierarchical structure of these self-similar Hanoi networks. Our goal is to map the dynamics to the spectrum of the connectivity matrix that encodes significant information about the structure of the underlying system. This exploration may have implications on designing networks that synchronizes coupled units efficiently. Supported through NSF Grant DMR-1207431.

  14. Network systems security analysis

    NASA Astrophysics Data System (ADS)

    Yilmaz, Ä.°smail

    2015-05-01

    Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.

  15. Excitable scale free networks

    NASA Astrophysics Data System (ADS)

    Copelli, M.; Campos, P. R. A.

    2007-04-01

    When a simple excitable system is continuously stimulated by a Poissonian external source, the response function (mean activity versus stimulus rate) generally shows a linear saturating shape. This is experimentally verified in some classes of sensory neurons, which accordingly present a small dynamic range (defined as the interval of stimulus intensity which can be appropriately coded by the mean activity of the excitable element), usually about one or two decades only. The brain, on the other hand, can handle a significantly broader range of stimulus intensity, and a collective phenomenon involving the interaction among excitable neurons has been suggested to account for the enhancement of the dynamic range. Since the role of the pattern of such interactions is still unclear, here we investigate the performance of a scale-free (SF) network topology in this dynamic range problem. Specifically, we study the transfer function of disordered SF networks of excitable Greenberg-Hastings cellular automata. We observe that the dynamic range is maximum when the coupling among the elements is critical, corroborating a general reasoning recently proposed. Although the maximum dynamic range yielded by general SF networks is slightly worse than that of random networks, for special SF networks which lack loops the enhancement of the dynamic range can be dramatic, reaching nearly five decades. In order to understand the role of loops on the transfer function we propose a simple model in which the density of loops in the network can be gradually increased, and show that this is accompanied by a gradual decrease of dynamic range.

  16. Community Seismic Network (CSN)

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    The CSN is a network of low-cost accelerometers deployed in the Pasadena, CA region. It is a prototype network with the goal of demonstrating the importance of dense measurements in determining the rapid lateral variations in ground motion due to earthquakes. The main product of the CSN is a map of peak ground produced within seconds of significant local earthquakes that can be used as a proxy for damage. Examples of this are shown using data from a temporary network in Long Beach, CA. Dense measurements in buildings are also being used to determine the state of health of structures. In addition to fixed sensors, portable sensors such as smart phones are also used in the network. The CSN has necessitated several changes in the standard design of a seismic network. The first is that the data collection and processing is done in the "cloud" (Google cloud in this case) for robustness and the ability to handle large impulsive loads (earthquakes). Second, the database is highly de-normalized (i.e. station locations are part of waveform and event-detection meta data) because of the mobile nature of the sensors. Third, since the sensors are hosted and/or owned by individuals, the privacy of the data is very important. The location of fixed sensors is displayed on maps as sensor counts in block-wide cells, and mobile sensors are shown in a similar way, with the additional requirement to inhibit tracking that at least two must be present in a particular cell before any are shown. The raw waveform data are only released to users outside of the network after a felt earthquake.

  17. Analysis of network statistics

    NASA Astrophysics Data System (ADS)

    Cottrell, R. L. A.

    1987-08-01

    This talk discusses the types and sources of data obtainable from networks of computer systems and terminals connected by communications paths. These paths often utilize mixtures of protocols and devices (such as modems, multiplexors, switches and front-ends) from multiple vendors. The talk describes how the data can be gathered from these devices and protocol layers, consolidated, stored, and analyzed. The analysis typically includes merging information from data bases describing the network topology, components, etc. Examples of reports and displays of the information gleaned are shown, together with illustrations of how the information may be useful for troubleshooting, performance measurement, auditing, accounting, and trend prediction.

  18. Networks of Memories

    DTIC Science & Technology

    2013-03-01

    2000). The construction of  autobiographical   memories in the self­memory system. Psychological Review, 107(2), 261­288. Dennis, S., & Chapman, A. (2010...AFRL-OSR-VA-TR-2013-0131 Networks of Memories Simon Dennis, Mikhail Belkin Ohio State University March 2013 Final...Back (Rev. 8/98) 1 Networks of  Memories FA9550­09­1­0614 Professor Jay Myung PI: Simon Dennis Ohio State University February 15, 2013 2 Introduction

  19. Nested neural networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1988-01-01

    Nested neural networks, consisting of small interconnected subnetworks, allow for the storage and retrieval of neural state patterns of different sizes. The subnetworks are naturally categorized by layers of corresponding to spatial frequencies in the pattern field. The storage capacity and the error correction capability of the subnetworks generally increase with the degree of connectivity between layers (the nesting degree). Storage of only few subpatterns in each subnetworks results in a vast storage capacity of patterns and subpatterns in the nested network, maintaining high stability and error correction capability.

  20. Synthetic biological networks

    NASA Astrophysics Data System (ADS)

    Archer, Eric; Süel, Gürol M.

    2013-09-01

    Despite their obvious relationship and overlap, the field of physics is blessed with many insightful laws, while such laws are sadly absent in biology. Here we aim to discuss how the rise of a more recent field known as synthetic biology may allow us to more directly test hypotheses regarding the possible design principles of natural biological networks and systems. In particular, this review focuses on synthetic gene regulatory networks engineered to perform specific functions or exhibit particular dynamic behaviors. Advances in synthetic biology may set the stage to uncover the relationship of potential biological principles to those developed in physics.

  1. Babylonian resistor networks

    NASA Astrophysics Data System (ADS)

    Mungan, Carl E.; Lipscombe, Trevor C.

    2012-05-01

    The ancient Babylonians had an iterative technique for numerically approximating the values of square roots. Their method can be physically implemented using series and parallel resistor networks. A recursive formula for the equivalent resistance Req is developed and converted into a nonrecursive solution for circuits using geometrically increasing numbers of identical resistors. As an example, 24 resistors R are assembled into a second-order network and Req/R is measured to equal \\sqrt 2 to better than 0.2%, as could be done in an introductory physics laboratory.

  2. Reciprocity in directed networks

    NASA Astrophysics Data System (ADS)

    Yin, Mei; Zhu, Lingjiong

    2016-04-01

    Reciprocity is an important characteristic of directed networks and has been widely used in the modeling of World Wide Web, email, social, and other complex networks. In this paper, we take a statistical physics point of view and study the limiting entropy and free energy densities from the microcanonical ensemble, the canonical ensemble, and the grand canonical ensemble whose sufficient statistics are given by edge and reciprocal densities. The sparse case is also studied for the grand canonical ensemble. Extensions to more general reciprocal models including reciprocal triangle and star densities will likewise be discussed.

  3. Adaptive network countermeasures.

    SciTech Connect

    McClelland-Bane, Randy; Van Randwyk, Jamie A.; Carathimas, Anthony G.; Thomas, Eric D.

    2003-10-01

    This report describes the results of a two-year LDRD funded by the Differentiating Technologies investment area. The project investigated the use of countermeasures in protecting computer networks as well as how current countermeasures could be changed in order to adapt with both evolving networks and evolving attackers. The work involved collaboration between Sandia employees and students in the Sandia - California Center for Cyber Defenders (CCD) program. We include an explanation of the need for adaptive countermeasures, a description of the architecture we designed to provide adaptive countermeasures, and evaluations of the system.

  4. Generalized Network Implementations,

    DTIC Science & Technology

    1986-01-01

    nodes are either suppliers or users. In fact, this network Is a transportation network (see Bazaraa and Jarvis [11). 2) many of the multipliers are one. 3...optimization model in operations research. Bazaraa and Jarvis (1] provide an excellent introduction to this field. The linear programming model employs the i...ET AL 1986 PDRC-86-03 I UNCLASSIFIED NB84-85-C-797 F/G 5/1 NL EE JI2 ilU41 A 12 NATIONA &MNAU OF S %gSOY IO" TISI p REFERENCES [1] Bazaraa , M.S. and

  5. ADE spectral networks

    NASA Astrophysics Data System (ADS)

    Longhi, Pietro; Park, Chan Y.

    2016-08-01

    We introduce a new perspective and a generalization of spectral networks for 4d {N} = 2 theories of class S associated to Lie algebras {g} = A n , D n , E6, and E7. Spectral networks directly compute the BPS spectra of 2d theories on surface defects coupled to the 4d theories. A Lie algebraic interpretation of these spectra emerges naturally from our construction, leading to a new description of 2d-4d wall-crossing phenomena. Our construction also provides an efficient framework for the study of BPS spectra of the 4d theories. In addition, we consider novel types of surface defects associated with minuscule ccrepresentations of {g}.

  6. Social networking and adolescents.

    PubMed

    Fuld, Gilbert L

    2009-04-01

    Online social networking is a 21st century innovation increasingly embraced by today's young people. It provides new opportunities for communication that expand an adolescent's world. Yet adults, often suspicious of new trends and technologies initially embraced by youth, often see these new environments as perilous places to visit. These fears have been accentuated by media hype, especially about sexual predators. How dangerous are they? Because the rush to go on these sites is a new phenomenon, research is as yet scant. This review explores current beliefs and knowledge about the dangers of social networking sites.

  7. The ribonucleoprotein Csr network.

    PubMed

    Seyll, Ethel; Van Melderen, Laurence

    2013-11-08

    Ribonucleoprotein complexes are essential regulatory components in bacteria. In this review, we focus on the carbon storage regulator (Csr) network, which is well conserved in the bacterial world. This regulatory network is composed of the CsrA master regulator, its targets and regulators. CsrA binds to mRNA targets and regulates translation either negatively or positively. Binding to small non-coding RNAs controls activity of this protein. Expression of these regulators is tightly regulated at the level of transcription and stability by various global regulators (RNAses, two-component systems, alarmone). We discuss the implications of these complex regulations in bacterial adaptation.

  8. Optimal covariant quantum networks

    NASA Astrophysics Data System (ADS)

    Chiribella, Giulio; D'Ariano, Giacomo Mauro; Perinotti, Paolo

    2009-04-01

    A sequential network of quantum operations is efficiently described by its quantum comb [1], a non-negative operator with suitable normalization constraints. Here we analyze the case of networks enjoying symmetry with respect to the action of a given group of physical transformations, introducing the notion of covariant combs and testers, and proving the basic structure theorems for these objects. As an application, we discuss the optimal alignment of reference frames (without pre-established common references) with multiple rounds of quantum communication, showing that i) allowing an arbitrary amount of classical communication does not improve the alignment, and ii) a single round of quantum communication is sufficient.

  9. The Ribonucleoprotein Csr Network

    PubMed Central

    Seyll, Ethel; Van Melderen, Laurence

    2013-01-01

    Ribonucleoprotein complexes are essential regulatory components in bacteria. In this review, we focus on the carbon storage regulator (Csr) network, which is well conserved in the bacterial world. This regulatory network is composed of the CsrA master regulator, its targets and regulators. CsrA binds to mRNA targets and regulates translation either negatively or positively. Binding to small non-coding RNAs controls activity of this protein. Expression of these regulators is tightly regulated at the level of transcription and stability by various global regulators (RNAses, two-component systems, alarmone). We discuss the implications of these complex regulations in bacterial adaptation. PMID:24217225

  10. On IPTV network design

    NASA Astrophysics Data System (ADS)

    Li, Guangzhi; Wang, Dongmei

    2007-11-01

    With more service providers making considerable investments to roll out multimedia services using IP technology, multimedia distribution, especially broadcast TV distribution over an IP network, the so called IPTV, is expected to grow impressively over coming years. However, there are confusing concepts and claims for this new technology: What is IPTV? Why do we need IPTV? How does it work? What are the requirements to design an efficient IPTV network? Are there any research problems? What are the solutions? In this paper, we will try to provide initial answers to all those questions based on our understanding and research work.

  11. A networked world

    NASA Astrophysics Data System (ADS)

    Buchanan, Mark; Caldarelli, Guido

    2010-02-01

    Just over a decade ago, in June 1998, a curious three-page paper appeared in Nature. In it, the authors - two applied mathematicians - reported a link between the structure of the US electrical grid and the wiring of a nematode worm's neural system. They also noted that these patterns were strikingly similar in their structure to the social networks of Hollywood actors, one of the few such networks for which the authors could find extensive data. It is hard to imagine a more bizarre melding of topics in one study.

  12. [Social networks and medicine].

    PubMed

    Bastardot, F; Vollenweider, P; Marques-Vidal, P

    2015-11-04

    Social networks (social media or #SoMe) have entered medical practice within the last few years. These new media--like Twitter or Skype--enrich interactions among physicians (telemedicine), among physicians and patients (virtual consultations) and change the way of teaching medicine. They also entail new ethical, deontological and legal issues: the extension of the consultation area beyond the medical office and the access of information by third parties were recently debated. We develop here a review of some social networks with their characteristics, applications for medicine and limitations, and we offer some recommendations of good practice.

  13. Communications network analysis tool

    NASA Astrophysics Data System (ADS)

    Phillips, Wayne; Dunn, Gary

    1989-11-01

    The Communications Network Analysis Tool (CNAT) is a set of computer programs that aids in the performance evaluation of a communication system in a real-world scenario. Communication network protocols can be modeled and battle group connectivity can be analyzed in the presence of jamming and the benefit of relay platforms can be studied. The Joint Tactical Information Distribution System (JTIDS) Communication system architecture is currently being modeled; however, the computer software is modular enough to allow substitution of a new code representative of prospective communication protocols.

  14. Adaptive parallel logic networks

    NASA Technical Reports Server (NTRS)

    Martinez, Tony R.; Vidal, Jacques J.

    1988-01-01

    Adaptive, self-organizing concurrent systems (ASOCS) that combine self-organization with massive parallelism for such applications as adaptive logic devices, robotics, process control, and system malfunction management, are presently discussed. In ASOCS, an adaptive network composed of many simple computing elements operating in combinational and asynchronous fashion is used and problems are specified by presenting if-then rules to the system in the form of Boolean conjunctions. During data processing, which is a different operational phase from adaptation, the network acts as a parallel hardware circuit.

  15. Self-Configuring Network Monitor

    SciTech Connect

    Goujun, Jin; Berket, Karlo; Lee, Jason; Leres, Craig

    2004-05-01

    Self-Configuring Network Monitor (SCNM) is a passive monitoring that can collect packet headers from any point in a network path. SCNM uses special activation packets to automatically activate monitors deployed at the layer three ingress and egress routers of the wide-area network, and at critical points within the site networks. Monitoring output data is sent back to the application data source or destination host. No modifications are required to the application or network routing infrastructure in order to activate monitoring of traffic for an application. This ensures that the monitoring operation does not add a burden to the networks administrator.

  16. Layer Communities in Multiplex Networks

    NASA Astrophysics Data System (ADS)

    Kao, Ta-Chu; Porter, Mason A.

    2017-08-01

    Multiplex networks are a type of multilayer network in which entities are connected to each other via multiple types of connections. We propose a method, based on computing pairwise similarities between layers and then doing community detection, for grouping structurally similar layers in multiplex networks. We illustrate our approach using both synthetic and empirical networks, and we are able to find meaningful groups of layers in both cases. For example, we find that airlines that are based in similar geographic locations tend to be grouped together in a multiplex airline network and that related research areas in physics tend to be grouped together in a multiplex collaboration network.

  17. Hidden variables in bipartite networks.

    PubMed

    Kitsak, Maksim; Krioukov, Dmitri

    2011-08-01

    We introduce and study random bipartite networks with hidden variables. Nodes in these networks are characterized by hidden variables that control the appearance of links between node pairs. We derive analytic expressions for the degree distribution, degree correlations, the distribution of the number of common neighbors, and the bipartite clustering coefficient in these networks. We also establish the relationship between degrees of nodes in original bipartite networks and in their unipartite projections. We further demonstrate how hidden variable formalism can be applied to analyze topological properties of networks in certain bipartite network models, and verify our analytical results in numerical simulations.

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

    NASA Astrophysics Data System (ADS)

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

    2017-09-01

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

  19. Network Adaptive Deadband: NCS Data Flow Control for Shared Networks

    PubMed Central

    Díaz-Cacho, Miguel; Delgado, Emma; Prieto, José A. G.; López, Joaquín

    2012-01-01

    This paper proposes a new middleware solution called Network Adaptive Deadband (NAD) for long time operation of Networked Control Systems (NCS) through the Internet or any shared network based on IP technology. The proposed middleware takes into account the network status and the NCS status, to improve the global system performance and to share more effectively the network by several NCS and sensor/actuator data flows. Relationship between network status and NCS status is solved with a TCP-friendly transport flow control protocol and the deadband concept, relating deadband value and transmission throughput. This creates a deadband-based flow control solution. Simulation and experiments in shared networks show that the implemented network adaptive deadband has better performance than an optimal constant deadband solution in the same circumstances. PMID:23208556

  20. Dynamic network management and service integration for airborne network

    NASA Astrophysics Data System (ADS)

    Pan, Wei; Li, Weihua

    2009-12-01

    The development of airborne network is conducive to resource sharing, flight management and interoperability in civilian and military aviation fields. To enhance the integrated ability of airborne network, the paper focuses on dynamic network management and service integration architecture for airborne network (DNMSIAN). Adaptive routing based on the mapping mechanism between connection identification and routing identification can provide diversified network access, and ensure the credibility and mobility of the aviation information exchange. Dynamic network management based on trustworthy cluster can ensure dynamic airborne network controllable and safe. Service integration based on semantic web and ontology can meet the customized and diversified needs for aviation information services. The DNMSIAN simulation platform demonstrates that our proposed methods can effectively perform dynamic network management and service integration.

  1. ASCR Science Network Requirements

    SciTech Connect

    Dart, Eli; Tierney, Brian

    2009-08-24

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

  2. Survivable virtual optical network embedding with probabilistic network-element failures in elastic optical networks

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Cheng, Lei; Luo, Guangjun; Zhang, Jie; Zhao, Yongli; Ding, Huixia; Zhou, Jing; Wang, Yang

    2015-06-01

    The elastic optical networks can elastically allocate spectrum tailored for various bandwidth requirements. In addition, different virtual optical networks (VONs) formed by different applications or service providers need to be embedded on the common physical optical network, it brings virtual optical network embedding (VONE) problem. There is no precise standard to measure the survivability of VON from the failure probability view and take minimum VON failure probability as an objective in a VONE problem. In this paper, we investigate a survivable VONE problem from a new perspective. Considering probabilistic physical network-element failures, a novel metric, named virtual optical network failure probability (VON-FP), is introduced to evaluate the survivability of VONs in elastic optical networks. Moreover, a failure-probability-aware virtual optical network embedding (FPA-VONE) algorithm is proposed to deploy VONs on the physical network elements with small failure probability, and finally to decrease the VON-FP and enhance the spectrum utilization effectively.

  3. Thermodynamic Constraints Improve Metabolic Networks.

    PubMed

    Krumholz, Elias W; Libourel, Igor G L

    2017-08-08

    In pursuit of establishing a realistic metabolic phenotypic space, the reversibility of reactions is thermodynamically constrained in modern metabolic networks. The reversibility constraints follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite concentration ranges into account. Because constraints reduce the feasible space, draft metabolic network reconstructions may need more extensive reconciliation, and a larger number of genes may become essential. Notwithstanding ubiquitous application, the effect of reversibility constraints on the predictive capabilities of metabolic networks has not been investigated in detail. Instead, work has focused on the implementation and validation of the thermodynamic poise calculation itself. With the advance of fast linear programming-based network reconciliation, the effects of reversibility constraints on network reconciliation and gene essentiality predictions have become feasible and are the subject of this study. Networks with thermodynamically informed reversibility constraints outperformed gene essentiality predictions compared to networks that were constrained with randomly shuffled constraints. Unconstrained networks predicted gene essentiality as accurately as thermodynamically constrained networks, but predicted substantially fewer essential genes. Networks that were reconciled with sequence similarity data and strongly enforced reversibility constraints outperformed all other networks. We conclude that metabolic network analysis confirmed the validity of the thermodynamic constraints, and that thermodynamic poise information is actionable during network reconciliation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  4. Generative model for feedback networks

    NASA Astrophysics Data System (ADS)

    White, Douglas R.; Kejžar, Nataša; Tsallis, Constantino; Farmer, Doyne; White, Scott

    2006-01-01

    We propose a model for network formation and study some of its statistical properties. The motivation for the model comes from the growth of several kinds of real networks (i.e., kinship and trading networks, networks of corporate alliances, networks of autocatalytic chemical reactions). These networks grow either by establishing closer connections by adding links in the existing network or by adding new nodes. A node in these networks lacks the information of the entire network. In order to establish a closer connection to other nodes it starts a search in the neighboring part of the network and waits for a possible feedback from a distant node that received the “searching signal.” Our model imitates this behavior by growing the network via the addition of a link that creates a cycle in the network or via the addition of a new node with a link to the network. The forming of a cycle creates feedback between the two ending nodes. After choosing a starting node, a search is made for another node at a suitable distance; if such a node is found, a link is established between this and the starting node, otherwise (such a node cannot be found) a new node is added and is linked to the starting node. We simulate this algorithm and find that we cannot reject the hypothesis that the empirical degree distribution is a q -exponential function, which has been used to model long-range processes in nonequilibrium statistical mechanics.

  5. Investigating the validity of current network analysis on static conglomerate networks by protein network stratification.

    PubMed

    Zhang, Minlu; Lu, Long J

    2010-09-16

    A molecular network perspective forms the foundation of systems biology. A common practice in analyzing protein-protein interaction (PPI) networks is to perform network analysis on a conglomerate network that is an assembly of all available binary interactions in a given organism from diverse data sources. Recent studies on network dynamics suggested that this approach might have ignored the dynamic nature of context-dependent molecular systems. In this study, we employed a network stratification strategy to investigate the validity of the current network analysis on conglomerate PPI networks. Using the genome-scale tissue- and condition-specific proteomics data in Arabidopsis thaliana, we present here the first systematic investigation into this question. We stratified a conglomerate A. thaliana PPI network into three levels of context-dependent subnetworks. We then focused on three types of most commonly conducted network analyses, i.e., topological, functional and modular analyses, and compared the results from these network analyses on the conglomerate network and five stratified context-dependent subnetworks corresponding to specific tissues. We found that the results based on the conglomerate PPI network are often significantly different from those of context-dependent subnetworks corresponding to specific tissues or conditions. This conclusion depends neither on relatively arbitrary cutoffs (such as those defining network hubs or bottlenecks), nor on specific network clustering algorithms for module extraction, nor on the possible high false positive rates of binary interactions in PPI networks. We also found that our conclusions are likely to be valid in human PPI networks. Furthermore, network stratification may help resolve many controversies in current research of systems biology.

  6. Investigating the validity of current network analysis on static conglomerate networks by protein network stratification

    PubMed Central

    2010-01-01

    Background A molecular network perspective forms the foundation of systems biology. A common practice in analyzing protein-protein interaction (PPI) networks is to perform network analysis on a conglomerate network that is an assembly of all available binary interactions in a given organism from diverse data sources. Recent studies on network dynamics suggested that this approach might have ignored the dynamic nature of context-dependent molecular systems. Results In this study, we employed a network stratification strategy to investigate the validity of the current network analysis on conglomerate PPI networks. Using the genome-scale tissue- and condition-specific proteomics data in Arabidopsis thaliana, we present here the first systematic investigation into this question. We stratified a conglomerate A. thaliana PPI network into three levels of context-dependent subnetworks. We then focused on three types of most commonly conducted network analyses, i.e., topological, functional and modular analyses, and compared the results from these network analyses on the conglomerate network and five stratified context-dependent subnetworks corresponding to specific tissues. Conclusions We found that the results based on the conglomerate PPI network are often significantly different from those of context-dependent subnetworks corresponding to specific tissues or conditions. This conclusion depends neither on relatively arbitrary cutoffs (such as those defining network hubs or bottlenecks), nor on specific network clustering algorithms for module extraction, nor on the possible high false positive rates of binary interactions in PPI networks. We also found that our conclusions are likely to be valid in human PPI networks. Furthermore, network stratification may help resolve many controversies in current research of systems biology. PMID:20846443

  7. Network growth models and genetic regulatory networks

    NASA Astrophysics Data System (ADS)

    Foster, D. V.; Kauffman, S. A.; Socolar, J. E. S.

    2006-03-01

    We study a class of growth algorithms for directed graphs that are candidate models for the evolution of genetic regulatory networks. The algorithms involve partial duplication of nodes and their links, together with the innovation of new links, allowing for the possibility that input and output links from a newly created node may have different probabilities of survival. We find some counterintuitive trends as the parameters are varied, including the broadening of the in-degree distribution when the probability for retaining input links is decreased. We also find that both the scaling of transcription factors with genome size and the measured degree distributions for genes in yeast can be reproduced by the growth algorithm if and only if a special seed is used to initiate the process.

  8. Network growth models and genetic regulatory networks

    NASA Astrophysics Data System (ADS)

    Socolar, Joshua; Foster, David; Kauffman, Stuart

    2006-03-01

    We study a class of growth algorithms for directed graphs that are candidate models for the evolution of genetic regulatory networks. The algorithms involve partial duplication of nodes and their links, together with innovation of new links, allowing for the possibility that input and output links from a newly created node may have different probabilities of survival. We find some counterintuitive trends as parameters are varied, including the broadening of indegree distribution when the probability for retaining input links is decreased. We also find that both the scaling of transcription factors with genome size and the measured degree distributions for genes in yeast can be reproduced by the growth algorithm if and only if a special seed is used to initiate the process.

  9. The Community Science Workshop Network Story: Becoming a Networked Organization

    ERIC Educational Resources Information Center

    St. John, Mark

    2014-01-01

    The Community Science Workshops (CSWs)--with funding from the S.D. Bechtel, Jr. Foundation, and the Gordon and Betty Moore Foundation--created a network among the CSW sites in California. The goals of the CSW Network project have been to improve programs, build capacity throughout the Network, and establish new sites. Inverness Research has been…

  10. Spectral Analysis of Rich Network Topology in Social Networks

    ERIC Educational Resources Information Center

    Wu, Leting

    2013-01-01

    Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

  11. The Community Science Workshop Network Story: Becoming a Networked Organization

    ERIC Educational Resources Information Center

    St. John, Mark

    2014-01-01

    The Community Science Workshops (CSWs)--with funding from the S.D. Bechtel, Jr. Foundation, and the Gordon and Betty Moore Foundation--created a network among the CSW sites in California. The goals of the CSW Network project have been to improve programs, build capacity throughout the Network, and establish new sites. Inverness Research has been…

  12. LTAR linkages with other research networks: Capitalizing on network interconnections

    USDA-ARS?s Scientific Manuscript database

    The USDA ARS Research Unit based at the Jornada Experimental Range outside of Las Cruces, NM, is a member of the USDA’s Long Term Agro-ecosystem Research (LTAR) Network, the National Science Foundation’s Long Term Ecological Research (LTER) Network, the National Ecological Observation Network (NEON)...

  13. Promoting Social Network Awareness: A Social Network Monitoring System

    ERIC Educational Resources Information Center

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  14. Do You Lock Your Network Doors? Some Network Management Precautions.

    ERIC Educational Resources Information Center

    Neray, Phil

    1997-01-01

    Discusses security problems and solutions for networked organizations with Internet connections. Topics include access to private networks from electronic mail information; computer viruses; computer software; corporate espionage; firewalls, that is computers that stand between a local network and the Internet; passwords; and physical security.…

  15. Promoting Social Network Awareness: A Social Network Monitoring System

    ERIC Educational Resources Information Center

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  16. Spectral Analysis of Rich Network Topology in Social Networks

    ERIC Educational Resources Information Center

    Wu, Leting

    2013-01-01

    Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

  17. Validating Large Scale Networks Using Temporary Local Scale Networks

    USDA-ARS?s Scientific Manuscript database

    The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

  18. Do You Lock Your Network Doors? Some Network Management Precautions.

    ERIC Educational Resources Information Center

    Neray, Phil

    1997-01-01

    Discusses security problems and solutions for networked organizations with Internet connections. Topics include access to private networks from electronic mail information; computer viruses; computer software; corporate espionage; firewalls, that is computers that stand between a local network and the Internet; passwords; and physical security.…

  19. Architecting the Network

    ERIC Educational Resources Information Center

    Chretien, Wendy

    2007-01-01

    The word "architect" calls to mind a designer of buildings. An architect's job is to develop a structure to fit the client's needs, some of which are conflicting (or seem to be). When it comes to designing a campus network, IT infrastructure architects have a similar function. Like a building architect, an IT architect must develop a…

  20. Diffusion in random networks

    DOE PAGES

    Zhang, Duan Z.; Padrino, Juan C.

    2017-06-01

    The ensemble averaging technique is applied to model mass transport by diffusion in random networks. The system consists of an ensemble of random networks, where each network is made of pockets connected by tortuous channels. Inside a channel, fluid transport is assumed to be governed by the one-dimensional diffusion equation. Mass balance leads to an integro-differential equation for the pocket mass density. The so-called dual-porosity model is found to be equivalent to the leading order approximation of the integration kernel when the diffusion time scale inside the channels is small compared to the macroscopic time scale. As a test problem,more » we consider the one-dimensional mass diffusion in a semi-infinite domain. Because of the required time to establish the linear concentration profile inside a channel, for early times the similarity variable is xt$-$1/4 rather than xt$-$1/2 as in the traditional theory. We found this early time similarity can be explained by random walk theory through the network.« less

  1. The European VLBI network

    NASA Technical Reports Server (NTRS)

    Schilizzi, R. T.

    1980-01-01

    The capabilities of the European very long baseline interferometry (VLBI) network are summarized. The range of baseline parameters, sensitivities, and recording and other equipment available are included. Plans for upgrading the recording facilities and the use of geostationary satellites for signal transfer and clock synchronization are discussed.

  2. NASA Engineering Network (NEN)

    NASA Technical Reports Server (NTRS)

    Topousis, Daria; Trevarthen, Ellie; Yew, Manson

    2008-01-01

    This slide presentation reviews the NASA Engineering Network (NEN). NEN is designed to search documents over multiple repositories, submit and browse NASA Lessons Learned, collaborate and share ideas with other engineers via communities of practice, access resources from one portal, and find subject matter experts via the People, Organizations, Projects, Skills (POPS) locator.

  3. Recovery of Interdependent Networks

    NASA Astrophysics Data System (ADS)

    di Muro, M. A.; La Rocca, C. E.; Stanley, H. E.; Havlin, S.; Braunstein, L. A.

    2016-03-01

    Recent network research has focused on the cascading failures in a system of interdependent networks and the necessary preconditions for system collapse. An important question that has not been addressed is how to repair a failing system before it suffers total breakdown. Here we introduce a recovery strategy for nodes and develop an analytic and numerical framework for studying the concurrent failure and recovery of a system of interdependent networks based on an efficient and practically reasonable strategy. Our strategy consists of repairing a fraction of failed nodes, with probability of recovery γ, that are neighbors of the largest connected component of each constituent network. We find that, for a given initial failure of a fraction 1 ‑ p of nodes, there is a critical probability of recovery above which the cascade is halted and the system fully restores to its initial state and below which the system abruptly collapses. As a consequence we find in the plane γ ‑ p of the phase diagram three distinct phases. A phase in which the system never collapses without being restored, another phase in which the recovery strategy avoids the breakdown, and a phase in which even the repairing process cannot prevent system collapse.

  4. Recovery of Interdependent Networks.

    PubMed

    Di Muro, M A; La Rocca, C E; Stanley, H E; Havlin, S; Braunstein, L A

    2016-03-09

    Recent network research has focused on the cascading failures in a system of interdependent networks and the necessary preconditions for system collapse. An important question that has not been addressed is how to repair a failing system before it suffers total breakdown. Here we introduce a recovery strategy for nodes and develop an analytic and numerical framework for studying the concurrent failure and recovery of a system of interdependent networks based on an efficient and practically reasonable strategy. Our strategy consists of repairing a fraction of failed nodes, with probability of recovery γ, that are neighbors of the largest connected component of each constituent network. We find that, for a given initial failure of a fraction 1 - p of nodes, there is a critical probability of recovery above which the cascade is halted and the system fully restores to its initial state and below which the system abruptly collapses. As a consequence we find in the plane γ - p of the phase diagram three distinct phases. A phase in which the system never collapses without being restored, another phase in which the recovery strategy avoids the breakdown, and a phase in which even the repairing process cannot prevent system collapse.

  5. Recovery of Interdependent Networks

    PubMed Central

    Di Muro, M. A.; La Rocca, C. E.; Stanley, H. E.; Havlin, S.; Braunstein, L. A.

    2016-01-01

    Recent network research has focused on the cascading failures in a system of interdependent networks and the necessary preconditions for system collapse. An important question that has not been addressed is how to repair a failing system before it suffers total breakdown. Here we introduce a recovery strategy for nodes and develop an analytic and numerical framework for studying the concurrent failure and recovery of a system of interdependent networks based on an efficient and practically reasonable strategy. Our strategy consists of repairing a fraction of failed nodes, with probability of recovery γ, that are neighbors of the largest connected component of each constituent network. We find that, for a given initial failure of a fraction 1 − p of nodes, there is a critical probability of recovery above which the cascade is halted and the system fully restores to its initial state and below which the system abruptly collapses. As a consequence we find in the plane γ − p of the phase diagram three distinct phases. A phase in which the system never collapses without being restored, another phase in which the recovery strategy avoids the breakdown, and a phase in which even the repairing process cannot prevent system collapse. PMID:26956773

  6. The network queueing system

    NASA Technical Reports Server (NTRS)

    Kingsbury, Brent K.

    1986-01-01

    Described is the implementation of a networked, UNIX based queueing system developed on contract for NASA. The system discussed supports both batch and device requests, and provides the facilities of remote queueing, request routing, remote status, queue access controls, batch request resource quota limits, and remote output return.

  7. Local Area Networks.

    ERIC Educational Resources Information Center

    Nasatir, Marilyn; And Others

    1990-01-01

    Four papers discuss LANs (local area networks) and library applications: (1) "Institute for Electrical and Electronic Engineers Standards..." (Charles D. Brown); (2) "Facilities Planning for LANs..." (Gail Persky); (3) "Growing up with the Alumni Library: LAN..." (Russell Buchanan); and (4) "Implementing a LAN...at the Health Sciences Library"…

  8. Networking for Remote Benefits.

    ERIC Educational Resources Information Center

    Farmer, Lesley S. J.

    1998-01-01

    Describes local networking approaches that encourage student interaction and better information access for the school community, while maintaining security measures. Discusses computer-supported collaborative work, simultaneous online discussion, educator support and curriculum development, courses on the Internet, and implementation. (AEF)

  9. Babylonian Resistor Networks

    ERIC Educational Resources Information Center

    Mungan, Carl E.; Lipscombe, Trevor C.

    2012-01-01

    The ancient Babylonians had an iterative technique for numerically approximating the values of square roots. Their method can be physically implemented using series and parallel resistor networks. A recursive formula for the equivalent resistance R[subscript eq] is developed and converted into a nonrecursive solution for circuits using…

  10. The Deep Space Network

    NASA Technical Reports Server (NTRS)

    1975-01-01

    Work accomplished on the Deep Space Network (DSN) was described, including the following topics: supporting research and technology, advanced development and engineering, system implementation, and DSN operations pertaining to mission-independent or multiple-mission development as well as to support of flight projects.

  11. Florida Information Resource Network.

    ERIC Educational Resources Information Center

    Watson, Francis C.

    1986-01-01

    The Florida Information Resource Network (FIRN) is an effort by the Florida education community and the Florida Legislature to provide an electronic link among all agencies, institutions, and schools in the public education system. The communications link, perhaps one of the most advanced in the nation, has three purposes: (1) to provide equal…

  12. Scientific networking in disciplines

    NASA Astrophysics Data System (ADS)

    Chang, Ching-Ray; Marks, Ann; Dawson, Silvina Ponce

    2013-03-01

    Scientific networking occurs at various levels. There are regional and worldwide professional organizations that link together national physical societies (IUPAP, EPS, AAPPS, FeLaSoFi), providing a platform to exchange ideas and advance common agendas. National and international agencies have special lines of funding for scientific collaboration between groups of various countries. Some of these lines are targeted at improving science education at all levels. There are then personal networks that link people with common interests or who know each other for any reason. The International Conferences on Women in Physics have provided a unique opportunity for female physicists from all over the world to start a network of interactions that can involve all sorts of collaborative efforts. In the three-session workshop organized at ICWIP11, we discussed these various issues that the worldwide scientific community faces. In this paper we summarize the main ideas that surged during the meeting and provide the list of recommendations that were to start and keep an active network of female physicists and to foster scientific collaboration regionally and internationally.

  13. Social Networking Technologies

    DTIC Science & Technology

    2015-01-01

    pushed the communist party from power in Moldova in 2009. Many have also argued that social networking technology played a vital role in the Arab Spring...Constant Connection. New York, NY: HarperCollins, 2015. Cross-References: Arab Spring Barack Obama Facebook Katz v. United States MySpace

  14. Computers, Networks and Education.

    ERIC Educational Resources Information Center

    Kay, Alan C.

    1991-01-01

    Discussed is how globally networked, easy-to-use computers can enhance learning only within an educational environment that encourages students to question "facts" and seek challenges. The strengths and weaknesses of computers used as amplifiers for learning are described. (KR)

  15. Neuromorphic atomic switch networks.

    PubMed

    Avizienis, Audrius V; Sillin, Henry O; Martin-Olmos, Cristina; Shieh, Hsien Hang; Aono, Masakazu; Stieg, Adam Z; Gimzewski, James K

    2012-01-01

    Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate structures with the highly complex interconnectivity found in biological neuronal networks. Here we demonstrate the physical realization of a self-assembled neuromorphic device which implements basic concepts of systems neuroscience through a hardware-based platform comprised of over a billion interconnected atomic-switch inorganic synapses embedded in a complex network of silver nanowires. Observations of network activation and passive harmonic generation demonstrate a collective response to input stimulus in agreement with recent theoretical predictions. Further, emergent behaviors unique to the complex network of atomic switches and akin to brain function are observed, namely spatially distributed memory, recurrent dynamics and the activation of feedforward subnetworks. These devices display the functional characteristics required for implementing unconventional, biologically and neurally inspired computational methodologies in a synthetic experimental system.

  16. Diversity Networking Reception

    NASA Astrophysics Data System (ADS)

    2014-03-01

    Join us at the APS Diversity Reception to relax, network with colleagues, and learn about programs and initiatives for women, underrepresented minorities, and LGBT physicists. You'll have a great time meeting friends in a supportive environment and making connections.

  17. Networking among Chevron Libraries.

    ERIC Educational Resources Information Center

    Linden, Margaret J.

    1989-01-01

    Describes the process by which librarians at the Chevron and Gulf Oil Corporations managed the merger of corporation libraries and developed a framework for a company-wide library network. The discussion covers corporate policies for information exchange, shared resources, and cost control, and examines factors that led to the success of the…

  18. The drug cocktail network

    PubMed Central

    2012-01-01

    Background Combination of different agents is widely used in clinic to combat complex diseases with improved therapy and reduced side effects. However, the identification of effective drug combinations remains a challenging task due to the huge number of possible combinations among candidate drugs that makes it impractical to screen putative combinations. Results In this work, we construct a 'drug cocktail network' using all the known effective drug combinations extracted from the Drug Combination Database (DCDB), and propose a network-based approach to investigate drug combinations. Our results show that the agents in an effective combination tend to have more similar therapeutic effects and share more interaction partners. Based on our observations, we further develop a statistical approach termed as DCPred (Drug Combination Predictor) to predict possible drug combinations by exploiting the topological features of the drug cocktail network. Validating on the known drug combinations, DCPred achieves the overall AUC (Area Under the receiver operating characteristic Curve) score of 0.92, indicating the predictive power of our proposed approach. Conclusions The drug cocktail network constructed in this work provides useful insights into the underlying rules of effective drug combinations and offer important clues to accelerate the future discovery of new drug combinations. PMID:23046711

  19. Accessibility in complex networks

    NASA Astrophysics Data System (ADS)

    Travençolo, B. A. N.; da F. Costa, L.

    2008-12-01

    This Letter describes a method for the quantification of the diversity of non-linear dynamics in complex networks as a consequence of self-avoiding random walks. The methodology is analyzed in the context of theoretical models and illustrated with respect to the characterization of the accessibility in urban streets.

  20. Communicability across evolving networks.

    PubMed

    Grindrod, Peter; Parsons, Mark C; Higham, Desmond J; Estrada, Ernesto

    2011-04-01

    Many natural and technological applications generate time-ordered sequences of networks, defined over a fixed set of nodes; for example, time-stamped information about "who phoned who" or "who came into contact with who" arise naturally in studies of communication and the spread of disease. Concepts and algorithms for static networks do not immediately carry through to this dynamic setting. For example, suppose A and B interact in the morning, and then B and C interact in the afternoon. Information, or disease, may then pass from A to C, but not vice versa. This subtlety is lost if we simply summarize using the daily aggregate network given by the chain A-B-C. However, using a natural definition of a walk on an evolving network, we show that classic centrality measures from the static setting can be extended in a computationally convenient manner. In particular, communicability indices can be computed to summarize the ability of each node to broadcast and receive information. The computations involve basic operations in linear algebra, and the asymmetry caused by time's arrow is captured naturally through the noncommutativity of matrix-matrix multiplication. Illustrative examples are given for both synthetic and real-world communication data sets. We also discuss the use of the new centrality measures for real-time monitoring and prediction.