Science.gov

Sample records for cobden-chevalier network 1860-1875

  1. Networks.

    ERIC Educational Resources Information Center

    Cerf, Vinton G.

    1991-01-01

    The demands placed on the networks transporting the information and knowledge generated by the increased diversity and sophistication of computational machinery are described. What is needed to support this increased flow, the structures already in place, and what must be built are topics of discussion. (KR)

  2. 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

  3. 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.

  4. 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…

  5. 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…

  6. Fermionic networks

    NASA Astrophysics Data System (ADS)

    Javarone, Marco Alberto

    2016-08-01

    We study the structure of fermionic networks, i.e. a model of networks based on the behavior of fermionic gases, and we analyze dynamical processes over them. In this model, particle dynamics have been mapped to the domain of networks, hence a parameter representing the temperature controls the evolution of the system. In doing so, it is possible to generate adaptive networks, i.e. networks whose structure varies over time. As shown in previous works, networks generated by quantum statistics can undergo critical phenomena as phase transitions and, moreover, they can be considered as thermodynamic systems. In this study, we analyze fermionic networks and opinion dynamics processes over them, framing this network model as a computational model useful to represent complex and adaptive systems. Results highlight that a strong relation holds between the gas temperature and the structure of the achieved networks. Notably, both the degree distribution and the assortativity vary as the temperature varies, hence we can state that fermionic networks behave as adaptive networks. On the other hand, it is worth to highlight that we did not finding relation between outcomes of opinion dynamics processes and the gas temperature. Therefore, although the latter plays a fundamental role in gas dynamics, on the network domain, its importance is related only to structural properties of fermionic networks.

  7. 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)

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Computer Networks As Social Networks

    NASA Astrophysics Data System (ADS)

    Wellman, Barry

    2001-09-01

    Computer networks are inherently social networks, linking people, organizations, and knowledge. They are social institutions that should not be studied in isolation but as integrated into everyday lives. The proliferation of computer networks has facilitated a deemphasis on group solidarities at work and in the community and afforded a turn to networked societies that are loosely bounded and sparsely knit. The Internet increases people's social capital, increasing contact with friends and relatives who live nearby and far away. New tools must be developed to help people navigate and find knowledge in complex, fragmented, networked societies.

  13. Innovation Networks

    NASA Astrophysics Data System (ADS)

    Pyka, Andreas; Scharnhorst, Andrea

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

  14. Network Directory.

    ERIC Educational Resources Information Center

    Butler, Jocelyn A.; Batey, Anne

    This Network Directory is part of the effort by the Northwest Regional Educational Laboratory (NWREL) School Improvement Program to promote communication among educational professionals about school improvement. Specifically, the directory is designed to provide information for networking among schools involved in systematic, long-term…

  15. Diabetes network.

    PubMed

    2016-07-01

    Diabetes UK has launched a network of information and support for commissioning and improvement in diabetes care. The network is free to join and offers monthly updates on good practice from around the UK, a forum for sharing ideas and learning, and access to Diabetes UK resources. PMID:27369708

  16. 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

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. Workshop on neural networks

    SciTech Connect

    Uhrig, R.E.; Emrich, M.L.

    1990-01-01

    The topics covered in this report are: Learning, Memory, and Artificial Neural Systems; Emerging Neural Network Technology; Neural Networks; Digital Signal Processing and Neural Networks; Application of Neural Networks to In-Core Fuel Management; Neural Networks in Process Control; Neural Network Applications in Image Processing; Neural Networks for Multi-Sensor Information Fusion; Neural Network Research in Instruments Controls Division; Neural Networks Research in the ORNL Engineering Physics and Mathematics Division; Neural Network Applications for Linear Programming; Neural Network Applications to Signal Processing and Diagnostics; Neural Networks in Filtering and Control; Neural Network Research at Tennessee Technological University; and Global Minima within the Hopfield Hypercube.

  4. 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…

  5. Network opportunity

    NASA Astrophysics Data System (ADS)

    Catanzaro, Michele; Buchanan, Mark

    2013-03-01

    Our developing scientific understanding of complex networks is being usefully applied in a wide set of financial systems. What we've learned from the 2008 crisis could be the basis of better management of the economy -- and a means to avert future disaster.

  6. 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).

  7. 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…

  8. 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)

  9. Chemical networks

    NASA Astrophysics Data System (ADS)

    Thi, Wing-Fai

    2015-09-01

    This chapter discusses the fundamental ideas of how chemical networks are build, their strengths and limitations. The chemical reactions that occur in disks combine the cold phase reactions used to model cold molecular clouds with the hot chemistry applied to planetary atmosphere models. With a general understanding of the different types of reactions that can occur, one can proceed in building a network of chemical reactions and use it to explain the abundance of species seen in disks. One on-going research subject is finding new paths to synthesize species either in the gas-phase or on grain surfaces. Specific formation routes for water or carbon monoxide are discussed in more details. 13th Lecture of the Summer School "Protoplanetary Disks: Theory and Modelling Meet Observations"

  10. 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.

  11. 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.

  12. 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…

  13. 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.

  14. [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.

  15. 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.

  16. Subgraphs and network motifs in geometric networks

    NASA Astrophysics Data System (ADS)

    Itzkovitz, Shalev; Alon, Uri

    2005-02-01

    Many real-world networks describe systems in which interactions decay with the distance between nodes. Examples include systems constrained in real space such as transportation and communication networks, as well as systems constrained in abstract spaces such as multivariate biological or economic data sets and models of social networks. These networks often display network motifs: subgraphs that recur in the network much more often than in randomized networks. To understand the origin of the network motifs in these networks, it is important to study the subgraphs and network motifs that arise solely from geometric constraints. To address this, we analyze geometric network models, in which nodes are arranged on a lattice and edges are formed with a probability that decays with the distance between nodes. We present analytical solutions for the numbers of all three- and four-node subgraphs, in both directed and nondirected geometric networks. We also analyze geometric networks with arbitrary degree sequences and models with a bias for directed edges in one direction. Scaling rules for scaling of subgraph numbers with system size, lattice dimension, and interaction range are given. Several invariant measures are found, such as the ratio of feedback and feed-forward loops, which do not depend on system size, dimension, or connectivity function. We find that network motifs in many real-world networks, including social networks and neuronal networks, are not captured solely by these geometric models. This is in line with recent evidence that biological network motifs were selected as basic circuit elements with defined information-processing functions.

  17. Nested Neural Networks

    NASA Technical Reports Server (NTRS)

    Baram, Yoram

    1992-01-01

    Report presents analysis of nested neural networks, consisting of interconnected subnetworks. Analysis based on simplified mathematical models more appropriate for artificial electronic neural networks, partly applicable to biological neural networks. Nested structure allows for retrieval of individual subpatterns. Requires fewer wires and connection devices than fully connected networks, and allows for local reconstruction of damaged subnetworks without rewiring entire network.

  18. 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.

  19. Robustness of networks of networks with degree-degree correlation

    NASA Astrophysics Data System (ADS)

    Min, Byungjoon; Canals, Santiago; Makse, Hernan

    Many real-world complex systems ranging from critical infrastructure and transportation networks to living systems including brain and cellular networks are not formed by an isolated network but by a network of networks. Randomly coupled networks with interdependency between different networks may easily result in abrupt collapse. Here, we seek a possible explanation of stable functioning in natural networks of networks including functional brain networks. Specifically, we analyze the robustness of networks of networks focused on one-to-many interconnections between different networks and degree-degree correlation. Implication of the network robustness on functional brain networks of rats is also discussed.

  20. Animal transportation networks.

    PubMed

    Perna, Andrea; Latty, Tanya

    2014-11-01

    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.

  1. 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

  2. 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.

  3. 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.

  4. 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;…

  5. [Neuronal network].

    PubMed

    Langmeier, M; Maresová, D

    2005-01-01

    Function of the central nervous system is based on mutual relations among the nerve cells. Description of nerve cells and their processes, including their contacts was enabled by improvement of optical features of the microscope and by the development of impregnation techniques. It is associated with the name of Antoni van Leeuwenhoek (1632-1723), J. Ev. Purkyne (1787-1869), Camillo Golgi (1843-1926), and Ramón y Cajal (1852-1934). Principal units of the neuronal network are the synapses. The term synapse was introduced into neurophysiology by Charles Scott Sherrington (1857-1952). Majority of the interactions between nerve cells is mediated by neurotransmitters acting at the receptors of the postsynaptic membrane or at the autoreceptors of the presynaptic part of the synapse. Attachment of the vesicles to the presynaptic membrane and the release of the neurotransmitter into the synaptic cleft depend on the intracellular calcium concentration and on the presence of several proteins in the presynaptic element.

  6. 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).

  7. 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

  8. Network epidemiology and plant trade networks.

    PubMed

    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.

  9. 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.

  10. Networked Resources: Usenet.

    ERIC Educational Resources Information Center

    Nickerson, Gord

    1992-01-01

    Describes the development of Usenet, the User's Network, a computer network that distributes group discussions (newsgroups) on different topics. Network News software is described, the rapid growth in popularity and heavy network traffic is discussed, and a hierarchical classification scheme to limit the amount of information for users is…

  11. 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.

  12. Coupled adaptive complex networks.

    PubMed

    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. PMID:23679478

  13. 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.

  14. Networking the Classroom.

    ERIC Educational Resources Information Center

    Stencel, Sandra, Ed.; And Others

    1995-01-01

    This issue of "CQ Researcher" examines the theme of computer networking in the classroom and discusses uses past and present. It begins with an essay by Christopher Conte that discusses: "Does computer networking really enhance learning? Are teachers adequately prepared to take advantage of computer networking? Will computer networking promote…

  15. Special Section on Networking.

    ERIC Educational Resources Information Center

    McInnis, Noel; And Others

    1984-01-01

    Examines how networking can be used to manage a changing world, how computer networking alleviates many problems encountered in more traditional communications forums, what a networking group can accomplish, and the potential of learning networks to become a nationwide movement, offering high-quality education at no charge. (RM)

  16. 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;…

  17. 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.

  18. Control of Multilayer Networks

    PubMed Central

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

    2016-01-01

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

  19. 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.

  20. 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. PMID:26867211

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. Parallel Consensual Neural Networks

    NASA Technical Reports Server (NTRS)

    Benediktsson, J. A.; Sveinsson, J. R.; Ersoy, O. K.; Swain, P. H.

    1993-01-01

    A new neural network architecture is proposed and applied in classification of remote sensing/geographic data from multiple sources. The new architecture is called the parallel consensual neural network and its relation to hierarchical and ensemble neural networks is discussed. The parallel consensual neural network architecture is based on statistical consensus theory. The input data are transformed several times and the different transformed data are applied as if they were independent inputs and are classified using stage neural networks. Finally, the outputs from the stage networks are then weighted and combined to make a decision. Experimental results based on remote sensing data and geographic data are given. The performance of the consensual neural network architecture is compared to that of a two-layer (one hidden layer) conjugate-gradient backpropagation neural network. The results with the proposed neural network architecture compare favorably in terms of classification accuracy to the backpropagation method.

  6. 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.

  7. 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.

  8. 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.

  9. Network II Database

    1994-11-07

    The Oak Ridge National Laboratory (ORNL) Rail and Barge Network II Database is a representation of the rail and barge system of the United States. The network is derived from the Federal Rail Administration (FRA) rail database.

  10. Integrated digital networks

    NASA Astrophysics Data System (ADS)

    Schwartz, M.; Stern, T.; Lazar, A.

    1984-09-01

    The basic problem described in this document is that of transmitting mixtures of traffic of disparate types over a variety of communication networks. Typical examples include the transmission of interactive data, long streams of data (e.g., file transfers), voice, video, and facsimile in an integrated fashion. Network types include local area networks, metropolitan area networks, large geographically-dispersed terrestrial networks, and satellite networks. Ongoing standards work in the C CITT, supported by telephone administrations worldwide, has focused on the concept of Integrated Services Digital Networks (ISDN) toward which worldwide telecommunications will be moving. Computer manufacturers with a great deal of interest in communications (IBM is a prominent example) have begun to devote considerable effort as well to the concept of traffic integration over networks.

  11. Social networks and schizophrenia.

    PubMed

    Beels, C C

    1979-01-01

    This artical begins with an introduction to social networks research and its practical importance in the understanding and treatment of schizophrenia, and concludes with a consideration of the experience, the phenomenology, of schizophrenia, from a social network point of view.

  12. The Networked Classroom

    ERIC Educational Resources Information Center

    Roschelle, Jeremy; Penuel, William R.; Abrahamson, Louis

    2004-01-01

    Classroom network requires every student to think actively, which enhances student participation in mathematics and science. Classroom-specific networks use software designed to enhance communication between teacher and students.

  13. Bladder Cancer Advocacy Network

    MedlinePlus

    ... future bladder cancer research through the Patient Survey Network. Read More... The JPB Foundation 2016 Bladder Cancer ... 2016 Young Investigator Awardees The Bladder Cancer Advocacy Network (BCAN) has announced the recipients of the 2016 ...

  14. 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)

  15. 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.

  16. 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.

  17. Class network routing

    DOEpatents

    Bhanot, Gyan; Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard D.; Takken, Todd E.; Vranas, Pavlos M.

    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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Local network assessment

    NASA Astrophysics Data System (ADS)

    Glen, D. V.

    1985-04-01

    Local networks, related standards activities of the Institute of Electrical and Electronics Engineers the American National Standards Institute and other elements are presented. These elements include: (1) technology choices such as topology, transmission media, and access protocols; (2) descriptions of standards for the 802 local area networks (LAN's); high speed local networks (HSLN's) and military specification local networks; and (3) intra- and internetworking using bridges and gateways with protocols Interconnection (OSI) reference model. The convergence of LAN/PBX technology is also described.

  3. 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 functions…

  4. 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…

  5. 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 segmentation, and…

  6. The Network Classroom.

    ERIC Educational Resources Information Center

    Maule, R. William

    1993-01-01

    Discussion of the role of new computer communications technologies in education focuses on modern networking systems, including fiber distributed data interface and Integrated Services Digital Network; strategies for implementing networked-based communication; and public online information resources for the classroom, including Bitnet, Internet,…

  7. Equilibrium games in networks

    NASA Astrophysics Data System (ADS)

    Li, Angsheng; Zhang, Xiaohui; Pan, Yicheng; Peng, Pan

    2014-12-01

    It seems a universal phenomenon of networks that the attacks on a small number of nodes by an adversary player Alice may generate a global cascading failure of the networks. It has been shown (Li et al., 2013) that classic scale-free networks (Barabási and Albert, 1999, Barabási, 2009) are insecure against attacks of as small as O(logn) many nodes. This poses a natural and fundamental question: Can we introduce a second player Bob to prevent Alice from global cascading failure of the networks? We proposed a game in networks. We say that a network has an equilibrium game if the second player Bob has a strategy to balance the cascading influence of attacks by the adversary player Alice. It was shown that networks of the preferential attachment model (Barabási and Albert, 1999) fail to have equilibrium games, that random graphs of the Erdös-Rényi model (Erdös and Rényi, 1959, Erdös and Rényi, 1960) have, for which randomness is the mechanism, and that homophyly networks (Li et al., 2013) have equilibrium games, for which homophyly and preferential attachment are the underlying mechanisms. We found that some real networks have equilibrium games, but most real networks fail to have. We anticipate that our results lead to an interesting new direction of network theory, that is, equilibrium games in networks.

  8. 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)

  9. Flexible embedding of networks

    NASA Astrophysics Data System (ADS)

    Fernandez-Gracia, Juan; Buckee, Caroline; Onnela, Jukka-Pekka

    We introduce a model for embedding one network into another, focusing on the case where network A is much bigger than network B. Nodes from network A are assigned to the nodes in network B using an algorithm where we control the extent of localization of node placement in network B using a single parameter. Starting from an unassigned node in network A, called the source node, we first map this node to a randomly chosen node in network B, called the target node. We then assign the neighbors of the source node to the neighborhood of the target node using a random walk based approach. To assign each neighbor of the source node to one of the nodes in network B, we perform a random walk starting from the target node with stopping probability α. We repeat this process until all nodes in network A have been mapped to the nodes of network B. The simplicity of the model allows us to calculate key quantities of interest in closed form. By varying the parameter α, we are able to produce embeddings from very local (α = 1) to very global (α --> 0). We show how our calculations fit the simulated results, and we apply the model to study how social networks are embedded in geography and how the neurons of C. Elegans are embedded in the surrounding volume.

  10. Networks of Schools.

    ERIC Educational Resources Information Center

    McMeekin, Robert W.

    2003-01-01

    Suggests that networks of schools help improve school performance, and that one reason some networks are successful is that they promote the creation of sound institutional environments in member schools. Describes three such networks: the Matte Schools of Santiago, Chile; the Fe y Alegria schools in Latin American countries; and the Accelerated…

  11. 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.

  12. Foundations of neural networks

    SciTech Connect

    Simpson, P.K.

    1994-12-31

    Building intelligent systems that can model human behavior has captured the attention of the world for years. So, it is not surprising that a technology such as neural networks has generated great interest. This paper will provide an evolutionary introduction to neural networks by beginning with the key elements and terminology of neural networks, and developing the topologies, learning laws, and recall dynamics from this infrastructure. The perspective taken in this paper is largely that of an engineer, emphasizing the application potential of neural networks and drawing comparisons with other techniques that have similar motivations. As such, mathematics will be relied upon in many of the discussions to make points as precise as possible. The paper begins with a review of what neural networks are and why they are so appealing. A typical neural network is immediately introduced to illustrate several of the key features. With this network as a reference, the evolutionary introduction to neural networks is then pursued. The fundamental elements of a neural network, such as input and output patterns, processing element, connections, and threshold operations, are described, followed by descriptions of neural network topologies, learning algorithms, and recall dynamics. A taxonomy of neural networks is presented that uses two of the key characteristics of learning and recall. Finally, a comparison of neural networks and similar nonneural information processing methods is presented.

  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. Spatially embedded random networks.

    PubMed

    Barnett, L; Di Paolo, E; Bullock, S

    2007-11-01

    Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the spatial element is mostly ignored and, in particular, its relation to network structure disregarded. In this paper we introduce a model framework to analyze the mediation of network structure by spatial embedding; specifically, we model connectivity as dependent on the distance between network nodes. Our spatially embedded random networks construction is not primarily intended as an accurate model of any specific class of real-world networks, but rather to gain intuition for the effects of spatial embedding on network structure; nevertheless we are able to demonstrate, in a quite general setting, some constraints of spatial embedding on connectivity such as the effects of spatial symmetry, conditions for scale free degree distributions and the existence of small-world spatial networks. We also derive some standard structural statistics for spatially embedded networks and illustrate the application of our model framework with concrete examples. PMID:18233726

  15. Spatially embedded random networks

    NASA Astrophysics Data System (ADS)

    Barnett, L.; di Paolo, E.; Bullock, S.

    2007-11-01

    Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the spatial element is mostly ignored and, in particular, its relation to network structure disregarded. In this paper we introduce a model framework to analyze the mediation of network structure by spatial embedding; specifically, we model connectivity as dependent on the distance between network nodes. Our spatially embedded random networks construction is not primarily intended as an accurate model of any specific class of real-world networks, but rather to gain intuition for the effects of spatial embedding on network structure; nevertheless we are able to demonstrate, in a quite general setting, some constraints of spatial embedding on connectivity such as the effects of spatial symmetry, conditions for scale free degree distributions and the existence of small-world spatial networks. We also derive some standard structural statistics for spatially embedded networks and illustrate the application of our model framework with concrete examples.

  16. Calorimetry Network Program

    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.

  17. Managing Knowledge Networks.

    ERIC Educational Resources Information Center

    Contractor, Noshir S.; Monge, Peter R.

    2002-01-01

    Describes a multitheoretical, multilevel (MTML) model to study the management of knowledge networks. Considers theoretical mechanisms for emergence of knowledge networks and presents empirical findings about the emergence of knowledge networks. Concludes that it is necessary to utilize MTML models to integrate multiple social and communication…

  18. Electronic neural networks

    SciTech Connect

    Howard, R.E.; Jackel, L.D.; Graf, H.P.

    1988-02-01

    The use of electronic neural networks to handle some complex computing problems is discussed. A simple neural model is shown and discussed in terms of its computational aspects. The use of electronic neural networks in machine pattern recognition and classification and in machine learning is examined. CMOS programmable networks are discussed. 15 references.

  19. Dominating Biological Networks

    PubMed Central

    Milenković, Tijana; Memišević, Vesna; Bonato, Anthony; Pržulj, Nataša

    2011-01-01

    Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI) networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of “biologically central (BC)” genes (i.e., their protein products), such as those involved in aging, cancer, infectious diseases, or signaling and drug-targeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network. To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC) role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs) in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its “spine” that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks. PMID:21887225

  20. 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.

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

    PubMed

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

    2015-08-26

    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.

  2. A consensual neural network

    NASA Technical Reports Server (NTRS)

    Benediktsson, J. A.; Ersoy, O. K.; Swain, P. H.

    1991-01-01

    A neural network architecture called a consensual neural network (CNN) is proposed for the classification of data from multiple sources. Its relation to hierarchical and ensemble neural networks is discussed. CNN is based on the statistical consensus theory and uses nonlinearly transformed input data. The input data are transformed several times, and the different transformed data are applied as if they were independent inputs. The independent inputs are classified using stage neural networks and outputs from the stage networks are then weighted and combined to make a decision. Experimental results based on remote-sensing data and geographic data are given.

  3. 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

  4. 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.

  5. Networks in cognitive science.

    PubMed

    Baronchelli, Andrea; Ferrer-i-Cancho, Ramon; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H

    2013-07-01

    Networks of interconnected nodes have long played a key role in Cognitive Science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions, and collaborations among scientists. Today, the inclusion of network theory into Cognitive Sciences, and the expansion of complex-systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the Cognitive Sciences.

  6. 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.

  7. Neural-Network Simulator

    NASA Technical Reports Server (NTRS)

    Mitchell, Paul H.

    1991-01-01

    F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

  8. 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.

  9. Emergent Complex Network Geometry

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    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.

  10. 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.

  11. 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.

  12. Internet protocol network mapper

    DOEpatents

    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.

  13. 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

  14. 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.

  15. 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.

  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. PMID:22184216

  17. 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.

  18. 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

  19. 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.

  20. Visualizing Social Networks

    NASA Astrophysics Data System (ADS)

    Correa, Carlos D.; Ma, Kwan-Liu

    With today‘s ubiquity and popularity of social network applications, the ability to analyze and understand large networks in an efficient manner becomes critically important. However, as networks become larger and more complex, reasoning about social dynamics via simple statistics is not a feasible option. To overcome these limitations, we can rely on visual metaphors. Visualization nowadays is no longer a passive process that produces images from a set of numbers. Recent years have witnessed a convergence of social network analytics and visualization, coupled with interaction, that is changing the way analysts understand and characterize social networks. In this chapter, we discuss the main goal of visualization and how different metaphors are aimed towards elucidating different aspects of social networks, such as structure and semantics. We also describe a number of methods where analytics and visualization are interwoven towards providing a better comprehension of social structure and dynamics.

  1. 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.

  2. 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.

  3. Computer networking at FERMILAB

    SciTech Connect

    Chartrand, G.

    1986-05-01

    Management aspects of data communications facilities at Fermilab are described. Local area networks include Ferminet, a broadband CATV system which serves as a backbone-type carrier for high-speed data traffic between major network nodes; micom network, four Micom Micro-600/2A port selectors via private twisted pair cables, dedicated telephone circuits, or Micom 800/2 statistical multiplexors; and Decnet/Ethernet, several small local area networks which provide host-to-host communications for about 35 VAX computers systems. Wide area (off site) computer networking includes an off site Micom network which provides access to all of Fermilab's computer systems for 10 universities via leased lines or modem; Tymnet, used by many European and Japanese collaborations: Physnet, used for shared data processing task communications by large collaborations of universities; Bitnet, used for file transfer, electronic mail, and communications with CERN; and Mfenet, for access to supercomputers. Plans to participate in Hepnet are also addressed. 3 figs. (DWL)

  4. NASA Communications Augmentation network

    NASA Astrophysics Data System (ADS)

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

    1990-09-01

    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.

  5. 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

  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. 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. PMID:25308391

  8. National Highway Planning Network

    1992-02-02

    NHPN, the National Highway Planning Network, is a database of major highways in the continental United States that is used for national-level analyses of highway transportation issues that require use of a network, such as studies of highway performance, network design, social and environmental impacts of transportation, vehicle routing and scheduling, and mapping. The network is based on a set of roadways digitized by the U. S. Geological Survey (USGS) from the 1980 National Atlasmore » and has been enhanced with additional roads, attribute detail, and topological error corrections to produce a true analytic network. All data have been derived from or checked against information obtained from state and Federal governmental agencies. Two files comprise this network: one describing links and the other nodes. This release, NHPN1.0, contains 44,960 links and 28,512 nodes representing approximately 380,000 miles of roadway.« less

  9. Mutually connected component of networks of networks with replica nodes

    NASA Astrophysics Data System (ADS)

    Bianconi, Ginestra; Dorogovtsev, Sergey N.; Mendes, José F. F.

    2015-01-01

    We describe the emergence of the giant mutually connected component in networks of networks in which each node has a single replica node in any layer and can be interdependent only on its replica nodes in the interdependent layers. We prove that if, in these networks, all the nodes of one network (layer) are interdependent on the nodes of the same other interconnected layer, then, remarkably, the mutually connected component does not depend on the topology of the network of networks. This component coincides with the mutual component of the fully connected network of networks constructed from the same set of layers, i.e., a multiplex network.

  10. 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…

  11. 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.

  12. 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.

  13. 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.

  14. Affinity driven social networks

    NASA Astrophysics Data System (ADS)

    Ruyú, B.; Kuperman, M. N.

    2007-04-01

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

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Network discovery with DCM

    PubMed Central

    Friston, Karl J.; Li, Baojuan; Daunizeau, Jean; Stephan, Klaas E.

    2011-01-01

    This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a graph that best explains observed time-series. The implicit adjacency matrix specifies the form of the network (e.g., cyclic or acyclic) and its graph-theoretical attributes (e.g., degree distribution). The scheme is illustrated using functional magnetic resonance imaging (fMRI) time series to discover functional brain networks. Crucially, it can be applied to experimentally evoked responses (activation studies) or endogenous activity in task-free (resting state) fMRI studies. Unlike conventional approaches to network discovery, DCM permits the analysis of directed and cyclic graphs. Furthermore, it eschews (implausible) Markovian assumptions about the serial independence of random fluctuations. The scheme furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks. The networks are characterised in terms of their connectivity or adjacency matrices and conditional distributions over the directed (and reciprocal) effective connectivity between connected nodes or regions. We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies. PMID:21182971

  20. Exploring complex networks

    NASA Astrophysics Data System (ADS)

    Strogatz, Steven H.

    2001-03-01

    The study of networks pervades all of science, from neurobiology to statistical physics. The most basic issues are structural: how does one characterize the wiring diagram of a food web or the Internet or the metabolic network of the bacterium Escherichia coli? Are there any unifying principles underlying their topology? From the perspective of nonlinear dynamics, we would also like to understand how an enormous network of interacting dynamical systems - be they neurons, power stations or lasers - will behave collectively, given their individual dynamics and coupling architecture. Researchers are only now beginning to unravel the structure and dynamics of complex networks.

  1. Heterogeneous broadband network

    NASA Astrophysics Data System (ADS)

    Dittmann, Lars

    1995-11-01

    Although the vision for the future Integrated Broadband Communication Network (IBCN) is an all optical network, it is certain that for a long period to come, the network will remain very heterogeneous, with a mixture of different physical media (fiber, coax and twisted pair), transmission systems (PDH, SDH, ADSL) and transport protocols (TCP/IP, AAL/ATM, frame relay). In the current work towards the IBCN, the ATM concept is considered the generic network protocol for both public and private network, with the ability to use different underlying transmission protocols and, through adaptation protocols, provide the appropriate services (old as well as new) to the customer. One of the major difficulties of heterogeneous network is the restriction that is usually given by the lowest common denominator, e.g. in terms of single channel capacity. A possible way to overcome these limitations is by extending the ATM concept with a multilink capability, that allows us to use separate resources as one common. The improved flexibility obtained by this protocol extension further allows a real time optimization of network and call configuration, without any impact on the quality of service seen from the user. This paper describes an example of an ATM based multilink protocol that has been experimentally implemented within the RACE project 'STRATOSPHERIC'. The paper outlines the complexity of introducing an extra network functionality compared with the added value, such as an improved ability to recover an error due to a malfunctioning network component.

  2. 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.

  3. 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.

  4. Composite Random Fiber Networks

    NASA Astrophysics Data System (ADS)

    Picu, Catalin; Shahsavari, Ali

    2013-03-01

    Systems made from fibers are common in the biological and engineering worlds. In many instances, as for example in skin, where elastin and collagen fibers are present, the fiber network is composite, in the sense that it contains fibers of very different properties. The relationship between microstructural parameters and the elastic moduli of random fiber networks containing a single type of fiber is understood. In this work we address a similar target for the composite networks. We show that linear superposition of the contributions to stiffness of individual sub-networks does not apply and interesting non-linear effects are observed. A physical basis of these effects is proposed.

  5. 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.

  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. 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.

  8. 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.

  9. 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.

  10. 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. PMID:16846193

  11. 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.

  12. Gateways among Academic Computer Networks.

    ERIC Educational Resources Information Center

    McCredie, John W.

    National intercampus computer networks are discussed, along with six illustrative networks. Attention is focused on computer networks with significant academic usage through which special software is available to manage resources in the network. It is noted that computer networks have widespread use among academics for communication in the form of…

  13. 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…

  14. 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.

  15. 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…

  16. 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.

  17. 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.

  18. FTS2000 network architecture

    NASA Technical Reports Server (NTRS)

    Klenart, John

    1991-01-01

    The network architecture of FTS2000 is graphically depicted. A map of network A topology is provided, with interservice nodes. Next, the four basic element of the architecture is laid out. Then, the FTS2000 time line is reproduced. A list of equipment supporting FTS2000 dedicated transmissions is given. Finally, access alternatives are shown.

  19. 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,…

  20. 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)

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Networks; Who, Why, How?

    ERIC Educational Resources Information Center

    Wisconsin Library Bulletin, 1975

    1975-01-01

    The May-June, 1975, issue of Wisconsin Library Bulletin contains articles about library cooperative programs and networks. Subjects covered include: library network planning and definitions of terms; views on the National Commission on Libraries and Information Science program by school, public, academic, and state librarians; the Midwest Library…

  7. 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

  8. 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.

  9. 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…

  10. 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)

  11. Language Teaching and Networking.

    ERIC Educational Resources Information Center

    Peterson, Mark

    1997-01-01

    Discusses the impact of computer networking on foreign language teaching and focuses on the competing claims made regarding the value of network-based language learning activity. A description of how internet-based activities operate in the classroom is included. (24 references) (Author/CK)

  12. Network Collaboration with UNIX.

    ERIC Educational Resources Information Center

    Horn, Wm. Dennis

    1993-01-01

    Discusses networking as a collaboration tool in the teaching of technical writing. Argues that some degree of collaboration is innate to all writing, that word processing already facilitates that collaboration, and that networking is the next enhancement to the collaborative process. (RS)

  13. Communication Network Analysis Methods.

    ERIC Educational Resources Information Center

    Farace, Richard V.; Mabee, Timothy

    This paper reviews a variety of analytic procedures that can be applied to network data, discussing the assumptions and usefulness of each procedure when applied to the complexity of human communication. Special attention is paid to the network properties measured or implied by each procedure. Factor analysis and multidimensional scaling are among…

  14. 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)

  15. 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.

  16. 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…

  17. Networking Hawaii's School Libraries.

    ERIC Educational Resources Information Center

    Hawaii State Dept. of Education, Honolulu. Office of Instructional Services.

    This guide is designed to assist school librarians in becoming part of the planned statewide school library network in Hawaii. Approaches to the guide for librarians at all stages of planning are suggested, and an overview of the benefits, goals, steps, and historical development are provided together with a model of the networking plan. The steps…

  18. UNESCO as a Network

    ERIC Educational Resources Information Center

    Omolewa, Michael

    2007-01-01

    This study attempts to draw attention to the hitherto neglected, but important, subject of how the United Nations Educational, Scientific, and Cultural Organization (UNESCO), as a network and promoter of other networks, has sought to foster the spirit of cooperation, understanding and partnership among its various Member States through…

  19. 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…

  20. On Heterogeneous Covert Networks

    NASA Astrophysics Data System (ADS)

    Lindelauf, Roy; Borm, Peter; Hamers, Herbert

    Covert organizations are constantly faced with a tradeoff between secrecy and operational efficiency. Lindelauf, Borm and Hamers [13] developed a theoretical framework to determine optimal homogeneous networks taking the above mentioned considerations explicitly into account. In this paper this framework is put to the test by applying it to the 2002 Jemaah Islamiyah Bali bombing. It is found that most aspects of this covert network can be explained by the theoretical framework. Some interactions however provide a higher risk to the network than others. The theoretical framework on covert networks is extended to accommodate for such heterogeneous interactions. Given a network structure the optimal location of one risky interaction is established. It is shown that the pair of individuals in the organization that should conduct the interaction that presents the highest risk to the organization, is the pair that is the least connected to the remainder of the network. Furthermore, optimal networks given a single risky interaction are approximated and compared. When choosing among a path, star and ring graph it is found that for low order graphs the path graph is best. When increasing the order of graphs under consideration a transition occurs such that the star graph becomes best. It is found that the higher the risk a single interaction presents to the covert network the later this transition from path to star graph occurs.

  1. 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.

  2. 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…

  3. K-12 Computer Networking.

    ERIC Educational Resources Information Center

    ERIC Review, 1993

    1993-01-01

    The "ERIC Review" is published three times a year and announces research results, publications, and new programs relevant to each issue's theme topic. This issue explores computer networking in elementary and secondary schools via two principal articles: "Plugging into the 'Net'" (Michael B. Eisenberg and Donald P. Ely); and "Computer Networks for…

  4. 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)

  5. Networking: OFFLU example

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  6. 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.

  7. 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

  8. Easily repairable networks

    NASA Astrophysics Data System (ADS)

    Fink, Thomas

    2015-03-01

    We introduce a simple class of distribution networks which withstand damage by being repairable instead of redundant. Instead of asking how hard it is to disconnect nodes through damage, we ask how easy it is to reconnect nodes after damage. We prove that optimal networks on regular lattices have an expected cost of reconnection proportional to the lattice length, and that such networks have exactly three levels of structural hierarchy. We extend our results to networks subject to repeated attacks, in which the repairs themselves must be repairable. We find that, in exchange for a modest increase in repair cost, such networks are able to withstand any number of attacks. We acknowledge support from the Defense Threat Reduction Agency, BCG and EU FP7 (Growthcom).

  9. 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

  10. Collective network routing

    SciTech Connect

    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.

  11. 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

  12. Motifs in brain networks.

    PubMed

    Sporns, Olaf; Kötter, Rolf

    2004-11-01

    Complex brains have evolved a highly efficient network architecture whose structural connectivity is capable of generating a large repertoire of functional states. We detect characteristic network building blocks (structural and functional motifs) in neuroanatomical data sets and identify a small set of structural motifs that occur in significantly increased numbers. Our analysis suggests the hypothesis that brain networks maximize both the number and the diversity of functional motifs, while the repertoire of structural motifs remains small. Using functional motif number as a cost function in an optimization algorithm, we obtain network topologies that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. These results are consistent with the hypothesis that highly evolved neural architectures are organized to maximize functional repertoires and to support highly efficient integration of information.

  13. Motifs in Brain Networks

    PubMed Central

    2004-01-01

    Complex brains have evolved a highly efficient network architecture whose structural connectivity is capable of generating a large repertoire of functional states. We detect characteristic network building blocks (structural and functional motifs) in neuroanatomical data sets and identify a small set of structural motifs that occur in significantly increased numbers. Our analysis suggests the hypothesis that brain networks maximize both the number and the diversity of functional motifs, while the repertoire of structural motifs remains small. Using functional motif number as a cost function in an optimization algorithm, we obtain network topologies that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. These results are consistent with the hypothesis that highly evolved neural architectures are organized to maximize functional repertoires and to support highly efficient integration of information. PMID:15510229

  14. Deterministic hierarchical networks

    NASA Astrophysics Data System (ADS)

    Barrière, L.; Comellas, F.; Dalfó, C.; Fiol, M. A.

    2016-06-01

    It has been shown that many networks associated with complex systems are small-world (they have both a large local clustering coefficient and a small diameter) and also scale-free (the degrees are distributed according to a power law). Moreover, these networks are very often hierarchical, as they describe the modularity of the systems that are modeled. Most of the studies for complex networks are based on stochastic methods. However, a deterministic method, with an exact determination of the main relevant parameters of the networks, has proven useful. Indeed, this approach complements and enhances the probabilistic and simulation techniques and, therefore, it provides a better understanding of the modeled systems. In this paper we find the radius, diameter, clustering coefficient and degree distribution of a generic family of deterministic hierarchical small-world scale-free networks that has been considered for modeling real-life complex systems.

  15. Modeling semiflexible polymer networks

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

    This is an overview of theoretical approaches to semiflexible polymers and their networks. Such semiflexible polymers have large bending rigidities that can compete with the entropic tendency of a chain to crumple up into a random coil. Many studies on semiflexible polymers and their assemblies have been motivated by their importance in biology. Indeed, cross-linked networks of semiflexible polymers form a major structural component of tissue and living cells. Reconstituted networks of such biopolymers have emerged as a new class of biological soft matter systems with remarkable material properties, which have spurred many of the theoretical developments discussed here. Starting from the mechanics and dynamics of individual semiflexible polymers, the physics of semiflexible bundles, entangled solutions, and disordered cross-linked networks are reviewed. Finally, recent developments on marginally stable fibrous networks, which exhibit critical behavior similar to other marginal systems such as jammed soft matter, are discussed.

  16. Controllability of complex networks.

    PubMed

    Liu, Yang-Yu; Slotine, Jean-Jacques; Barabási, Albert-László

    2011-05-12

    The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems towards a desired state, a framework to control complex self-organized systems is lacking. Here we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system's entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network's degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.

  17. 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

  18. 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. PMID:23565141

  19. 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.

  20. 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.

  1. 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

  2. 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. PMID:27368796

  3. 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.

  4. 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.

  5. Closeness Possible through Computer Networking.

    ERIC Educational Resources Information Center

    Dodd, Julie E.

    1989-01-01

    Points out the benefits of computer networking for scholastic journalism. Discusses three systems currently offering networking possibilities for publications: the Student Press Information Network; the Youth Communication Service; and the Dow Jones Newspaper Fund's electronic mail system. (MS)

  6. 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.

  7. 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.

  8. 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.

  9. A Network Synthesis Model for Generating Protein Interaction Network Families

    PubMed Central

    Sahraeian, Sayed Mohammad Ebrahim; Yoon, Byung-Jun

    2012-01-01

    In this work, we introduce a novel network synthesis model that can generate families of evolutionarily related synthetic protein–protein interaction (PPI) networks. Given an ancestral network, the proposed model generates the network family according to a hypothetical phylogenetic tree, where the descendant networks are obtained through duplication and divergence of their ancestors, followed by network growth using network evolution models. We demonstrate that this network synthesis model can effectively create synthetic networks whose internal and cross-network properties closely resemble those of real PPI networks. The proposed model can serve as an effective framework for generating comprehensive benchmark datasets that can be used for reliable performance assessment of comparative network analysis algorithms. Using this model, we constructed a large-scale network alignment benchmark, called NAPAbench, and evaluated the performance of several representative network alignment algorithms. Our analysis clearly shows the relative performance of the leading network algorithms, with their respective advantages and disadvantages. The algorithm and source code of the network synthesis model and the network alignment benchmark NAPAbench are publicly available at http://www.ece.tamu.edu/bjyoon/NAPAbench/. PMID:22912671

  10. 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.

  11. 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

  12. A quantum access network.

    PubMed

    Fröhlich, Bernd; Dynes, James F; Lucamarini, Marco; Sharpe, Andrew W; Yuan, Zhiliang; Shields, Andrew J

    2013-09-01

    The theoretically proven security of quantum key distribution (QKD) could revolutionize the way in which information exchange is protected in the future. Several field tests of QKD have proven it to be a reliable technology for cryptographic key exchange and have demonstrated nodal networks of point-to-point links. However, until now no convincing answer has been given to the question of how to extend the scope of QKD beyond niche applications in dedicated high security networks. Here we introduce and experimentally demonstrate the concept of a 'quantum access network': based on simple and cost-effective telecommunication technologies, the scheme can greatly expand the number of users in quantum networks and therefore vastly broaden their appeal. We show that a high-speed single-photon detector positioned at a network node can be shared between up to 64 users for exchanging secret keys with the node, thereby significantly reducing the hardware requirements for each user added to the network. This point-to-multipoint architecture removes one of the main obstacles restricting the widespread application of QKD. It presents a viable method for realizing multi-user QKD networks with efficient use of resources, and brings QKD closer to becoming a widespread technology. PMID:24005413

  13. Interictal networks in magnetoencephalography.

    PubMed

    Malinowska, Urszula; Badier, Jean-Michel; Gavaret, Martine; Bartolomei, Fabrice; Chauvel, Patrick; Bénar, Christian-George

    2014-06-01

    Epileptic networks involve complex relationships across several brain areas. Such networks have been shown on intracerebral EEG (stereotaxic EEG, SEEG), an invasive technique. Magnetoencephalography (MEG) is a noninvasive tool, which was recently proven to be efficient for localizing the generators of epileptiform discharges. However, despite the importance of characterizing non-invasively network aspects in partial epilepsies, only few studies have attempted to retrieve fine spatiotemporal dynamics of interictal discharges with MEG. Our goal was to assess the relevance of magnetoencephalography for detecting and characterizing the brain networks involved in interictal epileptic discharges. We propose here a semi-automatic method based on independent component analysis (ICA) and on co-occurrence of events across components. The method was evaluated in a series of seven patients by comparing its results with networks identified in SEEG. On both MEG and SEEG, we found that interictal discharges can involve remote regions which are acting in synchrony. More regions were identified in SEEG (38 in total) than in MEG (20). All MEG regions were confirmed by SEEG when an electrode was present in the vicinity. In all patients, at least one region could be identified as leading according to our criteria. A majority (71%) of MEG leaders were confirmed by SEEG. We have therefore shown that MEG measurements can extract a significant proportion of the networks visible in SEEG. This suggests that MEG can be a useful tool for defining noninvasively interictal epileptic networks, in terms of regions and patterns of connectivity, in search for a "primary irritative zone".

  14. 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.

  15. 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.

  16. 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. PMID:27437494

  17. Balanced Centrality of Networks

    PubMed Central

    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. PMID:27437494

  18. Stochastically evolving networks

    NASA Astrophysics Data System (ADS)

    Chan, Derek Y.; Hughes, Barry D.; Leong, Alex S.; Reed, William J.

    2003-12-01

    We discuss a class of models for the evolution of networks in which new nodes are recruited into the network at random times, and links between existing nodes that are not yet directly connected may also form at random times. The class contains both models that produce “small-world” networks and less tightly linked models. We produce both trees, appropriate in certain biological applications, and networks in which closed loops can appear, which model communication networks and networks of human sexual interactions. One of our models is closely related to random recursive trees, and some exact results known in that context can be exploited. The other models are more subtle and difficult to analyze. Our analysis includes a number of exact results for moments, correlations, and distributions of coordination number and network size. We report simulations and also discuss some mean-field approximations. If the system has evolved for a long time and the state of a random node (which thus has a random age) is observed, power-law distributions for properties of the system arise in some of these models.

  19. Neural network machine vision

    SciTech Connect

    Fox, R.O.; Czerniejewski, F.; Fluet, F.; Mitchell, E.

    1988-09-01

    Gould, Inc. and Nestor, Inc. cooperated on a joint development project to combine machine vision technology with neural network technology. The result is a machine vision system which can be trained by an inexperienced operator to perform qualitative classification. The hardware preprocessor reduces the information in the 2D camera image from 122,880 (i.e. 512 x 240) bytes to several hundred bytes in 64 milliseconds. The output of the preprocessor, which is in the format of connected lines, is fed to the first neural network. This neural network performs feature recognition. The output of the first neural network is a probability map. This map is fed to the input of the second neural network which performs object verification. The output of the second neural network is the object location and classification in the field of view. This information can optionally be fed into a third neural network which analyzes spatial relationships of objects in the field of view. The final output is a classification, by quality level, or by style. The system has been tested on applications ranging from the grading of plywood and the grading of paper to the sorting of fabricated metal parts. Specific application examples are presented.

  20. Wireless mesh networks.

    PubMed

    Wang, Xinheng

    2008-01-01

    Wireless telemedicine using GSM and GPRS technologies can only provide low bandwidth connections, which makes it difficult to transmit images and video. Satellite or 3G wireless transmission provides greater bandwidth, but the running costs are high. Wireless networks (WLANs) appear promising, since they can supply high bandwidth at low cost. However, the WLAN technology has limitations, such as coverage. A new wireless networking technology named the wireless mesh network (WMN) overcomes some of the limitations of the WLAN. A WMN combines the characteristics of both a WLAN and ad hoc networks, thus forming an intelligent, large scale and broadband wireless network. These features are attractive for telemedicine and telecare because of the ability to provide data, voice and video communications over a large area. One successful wireless telemedicine project which uses wireless mesh technology is the Emergency Room Link (ER-LINK) in Tucson, Arizona, USA. There are three key characteristics of a WMN: self-organization, including self-management and self-healing; dynamic changes in network topology; and scalability. What we may now see is a shift from mobile communication and satellite systems for wireless telemedicine to the use of wireless networks based on mesh technology, since the latter are very attractive in terms of cost, reliability and speed.

  1. 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.

  2. 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

  3. 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

  4. Building new access network using reconfigurable optical grid network and wireless network

    NASA Astrophysics Data System (ADS)

    Qiu, Yinghui; Wu, Runze; Ji, Yuefeng; Xu, Daxiong

    2007-11-01

    Recently wireless mesh network has been gaining increasing attention and early versions are being deployed as municipal access solutions to eliminate the wired drop to every wireless router at customer premise. In this paper, we propose a novel access network using reconfigurable optical burst switching grid network and wireless mesh network. The proposed access network architecture saves network deployment cost because fiber need not penetrate to each end user. We also propose a hierarchical routing protocol to enhance the routing efficiency.

  5. 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.

  6. Advanced Optical Network

    NASA Astrophysics Data System (ADS)

    Braun, Steve; Michael, Xuejun

    The following article describes an advanced dense wavelength division multiplexing (DWDM) Optical Network developed by L-3 Photonics. The network, configured as an amplified optical bus, carries traffic simultaneously in both directions, using multiple wavelengths. As a result, data distribution is of the form peer-to-multi-peer, it is protocol independent, and it is scalable. The network leverages the rapid growth in commercial optical technologies, including wavelength division multiplexing (WDM), and when applied to military and commercial platforms such as aircraft, ships, unmanned and other vehicles, provides a cost-effective, low-weight, high-speed, and high noise-immune data distribution system.

  7. 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

  8. NIRVANA network requirements

    SciTech Connect

    Wood, B.J.

    1990-08-01

    NIRVANA is an effort to standardize electrical computer-aided design workstations at Sandia National Laboratories in Albuquerque, New Mexico. The early effect of this project will be the introduction of at least 60 new engineering workstations at Sandia National Laboratories. Albuquerque, and at Allied Signal, Kansas City Division. These workstations are expected to begin arriving in September 1990. This paper proposes a design and outlines the requirements for a network to support the NIRVANA project. The author proposes a near-term network design, describes the security profile and caveats of this design, and proposes a long-term networking strategy for NIRVANA. 6 refs., 7 figs.

  9. 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.

  10. Modeling worldwide highway networks

    NASA Astrophysics Data System (ADS)

    Villas Boas, Paulino R.; Rodrigues, Francisco A.; da F. Costa, Luciano

    2009-12-01

    This Letter addresses the problem of modeling the highway systems of different countries by using complex networks formalism. More specifically, we compare two traditional geographical models with a modified geometrical network model where paths, rather than edges, are incorporated at each step between the origin and the destination vertices. Optimal configurations of parameters are obtained for each model and used for the comparison. The highway networks of Australia, Brazil, India, and Romania are considered and shown to be properly modeled by the modified geographical model.

  11. 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.

  12. Multiuser quantum communication networks

    SciTech Connect

    Wojcik, Antoni; Kurzynski, Pawel; Grudka, Andrzej; Luczak, Tomasz; Gdala, Tomasz; Bednarska, Malgorzata

    2007-02-15

    We study a quantum state transfer between spins interacting with an arbitrary network of spins coupled by uniform XX interactions. It is shown that in such a system under fairly general conditions, we can expect a nearly perfect transfer of states. Then we analyze a generalization of this model to the case of many network users, where the sender can choose which party he wants to communicate with by appropriately tuning his local magnetic field. We also remark that a similar idea can be used to create an entanglement between several spins coupled to the network.

  13. 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.

  14. 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.

  15. 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.

  16. Effects of network structure and routing strategy on network capacity

    NASA Astrophysics Data System (ADS)

    Chen, Zhen Yi; Wang, Xiao Fan

    2006-03-01

    The capacity of maximum end-to-end traffic flow the network is able to handle without overloading is an important index for network performance in real communication systems. In this paper, we estimate the variations of network capacity under different routing strategies for three different topologies. Simulation results reveal that the capacity depends on the underlying network structure and the capacity increases as the network becomes more homogeneous. It is also observed that the network capacity is greatly enhanced when the new traffic awareness routing strategy is adopted in each network structure.

  17. 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 ...

  18. Autocatalysis in reaction networks.

    PubMed

    Deshpande, Abhishek; Gopalkrishnan, Manoj

    2014-10-01

    The persistence conjecture is a long-standing open problem in chemical reaction network theory. It concerns the behavior of solutions to coupled ODE systems that arise from applying mass-action kinetics to a network of chemical reactions. The idea is that if all reactions are reversible in a weak sense, then no species can go extinct. A notion that has been found useful in thinking about persistence is that of "critical siphon." We explore the combinatorics of critical siphons, with a view toward the persistence conjecture. We introduce the notions of "drainable" and "self-replicable" (or autocatalytic) siphons. We show that: Every minimal critical siphon is either drainable or self-replicable; reaction networks without drainable siphons are persistent; and nonautocatalytic weakly reversible networks are persistent. Our results clarify that the difficulties in proving the persistence conjecture are essentially due to competition between drainable and self-replicable siphons. PMID:25245394

  19. Multitasking associative networks.

    PubMed

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

    2012-12-28

    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.

  20. 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

  1. Autocatalysis in reaction networks.

    PubMed

    Deshpande, Abhishek; Gopalkrishnan, Manoj

    2014-10-01

    The persistence conjecture is a long-standing open problem in chemical reaction network theory. It concerns the behavior of solutions to coupled ODE systems that arise from applying mass-action kinetics to a network of chemical reactions. The idea is that if all reactions are reversible in a weak sense, then no species can go extinct. A notion that has been found useful in thinking about persistence is that of "critical siphon." We explore the combinatorics of critical siphons, with a view toward the persistence conjecture. We introduce the notions of "drainable" and "self-replicable" (or autocatalytic) siphons. We show that: Every minimal critical siphon is either drainable or self-replicable; reaction networks without drainable siphons are persistent; and nonautocatalytic weakly reversible networks are persistent. Our results clarify that the difficulties in proving the persistence conjecture are essentially due to competition between drainable and self-replicable siphons.

  2. 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.

  3. 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.

  4. 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.

  5. 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)

  6. ESNET (Energy Sciences Network)

    SciTech Connect

    Not Available

    1987-06-01

    This document describes the Energy Sciences Network (ESNET) project which was undertaken by the Scientific Computing Staff during fiscal year (FY) 1986 at the direction of the Director, Office of Energy Research (ER). This document serves as the program plan for the ESNET project and is the result of the effort of the cross program Energy Sciences Network Steering Committee. The ESNET Steering Committee has been charged to codify the overall ER computer network requirements, to document and set priorities for computer networking requirements including performance objectives. Further, this committee has been asked to identify future ESNET functional characteristics, to identify research and development needs for the ESNET, to establish ESNET performance objectives and to define the intrastructure necessary to manage and operate the ESNET facilities.

  7. 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.

  8. Computers, Networks and Work.

    ERIC Educational Resources Information Center

    Sproull, Lee; Kiesler, Sara

    1991-01-01

    Discussed are how computer networks can affect the nature of work and the relationships between managers and employees. The differences between face-to-face exchanges and electronic interactions are described. (KR)

  9. The network takeover

    NASA Astrophysics Data System (ADS)

    Barabási, Albert-László

    2012-01-01

    Reductionism, as a paradigm, is expired, and complexity, as a field, is tired. Data-based mathematical models of complex systems are offering a fresh perspective, rapidly developing into a new discipline: network science.

  10. 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)

  11. Integrated Networks Branch

    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.

  12. Collaborative Electronic Network Building.

    ERIC Educational Resources Information Center

    DiMauro, Vanessa; Jacobs, Gloria

    1995-01-01

    Addresses research questions related to purposeful collaboration as a mechanism for successful teacher professional development in the process of designing a telecommunications network with users. (19 references) (Author/MKR)

  13. 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.

  14. Evolution of document networks.

    PubMed

    Menczer, Filippo

    2004-04-01

    How does a network of documents grow without centralized control? This question is becoming crucial as we try to explain the emergent scale-free topology of the World Wide Web and use link analysis to identify important information resources. Existing models of growing information networks have focused on the structure of links but neglected the content of nodes. Here I show that the current models fail to reproduce a critical characteristic of information networks, namely the distribution of textual similarity among linked documents. I propose a more realistic model that generates links by using both popularity and content. This model yields remarkably accurate predictions of both degree and similarity distributions in networks of web pages and scientific literature.

  15. 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.

  16. 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

  17. Homogeneous complex networks

    NASA Astrophysics Data System (ADS)

    Bogacz, Leszek; Burda, Zdzisław; Wacław, Bartłomiej

    2006-07-01

    We discuss various ensembles of homogeneous complex networks and a Monte-Carlo method of generating graphs from these ensembles. The method is quite general and can be applied to simulate micro-canonical, canonical or grand-canonical ensembles for systems with various statistical weights. It can be used to construct homogeneous networks with desired properties, or to construct a non-trivial scoring function for problems of advanced motif searching.

  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. VOIP over Space Networks

    NASA Technical Reports Server (NTRS)

    Okino, C.; Kwong, W.; Pang, Jackson; Gao, Jerry; Clare, L.

    2006-01-01

    This viewgraph presentation reviews Voice over Internet Protocol (VOIP) over a space networking environment. The topics include: 1) Drivers for VOIP in Space; 2) Challenges in the Space Networking Environment: Long Latencies, Path errors, Simplex paths, Asymmetric paths, QoS requirements, Team-based operations, and Overhead concerns; 3) Possible VOIPOSN approaches; 4) Study of BER, code type and voice frame length on PESQ-MOS; 5) Codec Latency Trade Space; and 6) Testbed.

  20. 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.

  1. Nanostructured cellular networks.

    PubMed

    Moriarty, P; Taylor, M D R; Brust, M

    2002-12-01

    Au nanocrystals spin-coated onto silicon from toluene form cellular networks. A quantitative statistical crystallography analysis shows that intercellular correlations drive the networks far from statistical equilibrium. Spin-coating from hexane does not produce cellular structure, yet a strong correlation is retained in the positions of nanocrystal aggregates. Mechanisms based on Marangoni convection alone cannot account for the variety of patterns observed, and we argue that spinodal decomposition plays an important role in foam formation.

  2. Electronic Neural Networks

    NASA Technical Reports Server (NTRS)

    Lambe, John; Moopen, Alexander; Thakoor, Anilkumar P.

    1988-01-01

    Memory based on neural network models content-addressable and fault-tolerant. System includes electronic equivalent of synaptic network; particular, matrix of programmable binary switching elements over which data distributed. Switches programmed in parallel by outputs of serial-input/parallel-output shift registers. Input and output terminals of bank of high-gain nonlinear amplifiers connected in nonlinear-feedback configuration by switches and by memory-prompting shift registers.

  3. High performance satellite networks

    NASA Astrophysics Data System (ADS)

    Helm, Neil R.; Edelson, Burton I.

    1997-06-01

    The high performance satellite communications networks of the future will have to be interoperable with terrestrial fiber cables. These satellite networks will evolve from narrowband analogue formats to broadband digital transmission schemes, with protocols, algorithms and transmission architectures that will segment the data into uniform cells and frames, and then transmit these data via larger and more efficient synchronous optional (SONET) and asynchronous transfer mode (ATM) networks that are being developed for the information "superhighway". These high performance satellite communications and information networks are required for modern applications, such as electronic commerce, digital libraries, medical imaging, distance learning, and the distribution of science data. In order for satellites to participate in these information superhighway networks, it is essential that they demonstrate their ability to: (1) operate seamlessly with heterogeneous architectures and applications, (2) carry data at SONET rates with the same quality of service as optical fibers, (3) qualify transmission delay as a parameter not a problem, and (4) show that satellites have several performance and economic advantages over fiber cable networks.

  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. 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

  6. 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)...

  7. 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.

  8. Campus Networking Strategies: An Introduction.

    ERIC Educational Resources Information Center

    Roberts, Michael M.

    1988-01-01

    This article is adapted from the introduction to EDUCOM's forthcoming book, Campus Networking Strategies, which includes 10 case study chapters detailing academic experiences with computer networking. Topics discussed in the introduction include network issues for management, networking economics, engineering and telecommunications issues, and…

  9. 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…

  10. 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.

  11. 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.

  12. Statistical mechanics of complex networks

    NASA Astrophysics Data System (ADS)

    Albert, Réka; Barabási, Albert-László

    2002-01-01

    Complex networks describe a wide range of systems in nature and society. Frequently cited examples include the cell, a network of chemicals linked by chemical reactions, and the Internet, a network of routers and computers connected by physical links. While traditionally these systems have been modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks are governed by robust organizing principles. This article reviews the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, the authors discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, the emerging theory of evolving networks, and the interplay between topology and the network's robustness against failures and attacks.

  13. 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

  14. Computing preimages of Boolean networks.

    PubMed

    Klotz, Johannes; Bossert, Martin; Schober, Steffen

    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

  15. Computer and information networks.

    PubMed

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

    1973-10-01

    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

  16. Computer and information networks.

    PubMed

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

    1973-10-01

    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

  17. 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).

  18. Network motifs: simple building blocks of complex networks.

    PubMed

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

    2002-10-25

    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. PMID:12399590

  19. 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

  20. 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.

  1. 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

    2014-09-01

    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

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

    PubMed

    Chen, Shi; Lanzas, Cristina

    2016-09-01

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

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

    PubMed

    Chen, Shi; Lanzas, Cristina

    2016-09-01

    In this paper we discuss the distinction and connection between three closely related networks in animal ecology and epidemiology studies: the contact, social, and disease transmission networks. We provide a robust theoretical definition and interpretation of these three networks, demonstrate that social and disease transmission networks can be derived as spanning subgraphs of contact network, and show examples based on real-world high-resolution cattle contact structure data. Furthermore, we establish a modeling framework to track potential disease transmission dynamics and construct transmission network based on the observed animal contact network. PMID:27544246

  4. HIV / AIDS Network.

    PubMed

    1995-01-01

    The HIV/AIDS Network and the Philippines Department of Health (DOH) collaborated to produce the AIDS Candlelight Memorial at the Philippine International Convention Center (PICC), May 1995, and World AIDS Day activities on December 1, 1995. After the memorial, a fashion show, "Body Shots," provided a channel for information on acquired immunodeficiency syndrome (AIDS). On World AIDS Day, at the request of DOH, the Network provided speakers who lectured on human immunodeficiency virus (HIV) and AIDS in different government offices. Prior to World AIDS Day, the Network focused on strengthening its cohesiveness and building the capabilities of its member organizations through lectures and symposia during November. Network activities were coordinated by the Remedios AIDS Foundation with support from the other members of the Coordinating Council: Health Action Information Network (HAIN); Caritas; Kabalikat, Stop Trafficking of Pilopinos Foundation, Inc. (STOP);and the Library Foundation (TLF). The Coordinating Council elected for 1996 includes the Remedios AIDS Foundation, HAIN, Caritas, TLF, STOP, the Foundation for Adolescent Development (FAD), and the Salvation Army. PMID:12291699

  5. Viscoelastic Properties of Networks

    NASA Astrophysics Data System (ADS)

    Gündüz, Güngör

    A network was characterized by its viscoelastic properties. The viscoelastic property indicates the deformations or changes in the shape and in the internal structure during the evolution of a network. The change in the direction of motion was taken as elastic deformation and the change in the vertical direction as viscous deformation. These deformations were related to the change of geometry of internal structure and of shape. Thus it was possible to characterize a network by its storage and loss moduli. The change of the structure of a network during its evolution changes also its entropy. However entropy depends on the number of microstates of an already existing framework. As examples, two different systems (i) New York Stock Exchange and (ii) a melody were studied for their viscoelastic properties. The change of viscous property was compared with the change of different types of entropies such as configurational entropy, crossing entropy, and topological entropy. This last entropy was introduced and explained in the text. It was found out that there is no direct correspondence between the increase of entropy and the increase of viscous property of a network although they sometimes correlate with each other.

  6. 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.

  7. 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

  8. Network modularity promotes cooperation.

    PubMed

    Marcoux, Marianne; Lusseau, David

    2013-05-01

    Cooperation in animals and humans is widely observed even if evolutionary biology theories predict the evolution of selfish individuals. Previous game theory models have shown that cooperation can evolve when the game takes place in a structured population such as a social network because it limits interactions between individuals. Modularity, the natural division of a network into groups, is a key characteristic of all social networks but the influence of this crucial social feature on the evolution of cooperation has never been investigated. Here, we provide novel pieces of evidence that network modularity promotes the evolution of cooperation in 2-person prisoner's dilemma games. By simulating games on social networks of different structures, we show that modularity shapes interactions between individuals favouring the evolution of cooperation. Modularity provides a simple mechanism for the evolution of cooperation without having to invoke complicated mechanisms such as reputation or punishment, or requiring genetic similarity among individuals. Thus, cooperation can evolve over wider social contexts than previously reported.

  9. 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.

  10. 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.

  11. Quartets and unrooted phylogenetic networks.

    PubMed

    Gambette, Philippe; Berry, Vincent; Paul, Christophe

    2012-08-01

    Phylogenetic networks were introduced to describe evolution in the presence of exchanges of genetic material between coexisting species or individuals. Split networks in particular were introduced as a special kind of abstract network to visualize conflicts between phylogenetic trees which may correspond to such exchanges. More recently, methods were designed to reconstruct explicit phylogenetic networks (whose vertices can be interpreted as biological events) from triplet data. In this article, we link abstract and explicit networks through their combinatorial properties, by introducing the unrooted analog of level-k networks. In particular, we give an equivalence theorem between circular split systems and unrooted level-1 networks. We also show how to adapt to quartets some existing results on triplets, in order to reconstruct unrooted level-k phylogenetic networks. These results give an interesting perspective on the combinatorics of phylogenetic networks and also raise algorithmic and combinatorial questions.

  12. 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

  13. 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.

  14. Quartets and unrooted phylogenetic networks.

    PubMed

    Gambette, Philippe; Berry, Vincent; Paul, Christophe

    2012-08-01

    Phylogenetic networks were introduced to describe evolution in the presence of exchanges of genetic material between coexisting species or individuals. Split networks in particular were introduced as a special kind of abstract network to visualize conflicts between phylogenetic trees which may correspond to such exchanges. More recently, methods were designed to reconstruct explicit phylogenetic networks (whose vertices can be interpreted as biological events) from triplet data. In this article, we link abstract and explicit networks through their combinatorial properties, by introducing the unrooted analog of level-k networks. In particular, we give an equivalence theorem between circular split systems and unrooted level-1 networks. We also show how to adapt to quartets some existing results on triplets, in order to reconstruct unrooted level-k phylogenetic networks. These results give an interesting perspective on the combinatorics of phylogenetic networks and also raise algorithmic and combinatorial questions. PMID:22809417

  15. 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

  16. Attack vulnerability of complex networks

    NASA Astrophysics Data System (ADS)

    Holme, Petter; Kim, Beom Jun; Yoon, Chang No; Han, Seung Kee

    2002-05-01

    We study the response of complex networks subject to attacks on vertices and edges. Several existing complex network models as well as real-world networks of scientific collaborations and Internet traffic are numerically investigated, and the network performance is quantitatively measured by the average inverse geodesic length and the size of the largest connected subgraph. For each case of attacks on vertices and edges, four different attacking strategies are used: removals by the descending order of the degree and the betweenness centrality, calculated for either the initial network or the current network during the removal procedure. It is found that the removals by the recalculated degrees and betweenness centralities are often more harmful than the attack strategies based on the initial network, suggesting that the network structure changes as important vertices or edges are removed. Furthermore, the correlation between the betweenness centrality and the degree in complex networks is studied.

  17. 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.

  18. 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. PMID:26153011

  19. 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.

  20. 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).

  1. 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. 

  2. 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.

  3. 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.

  4. Practical emotional neural networks.

    PubMed

    Lotfi, Ehsan; Akbarzadeh-T, M-R

    2014-11-01

    In this paper, we propose a limbic-based artificial emotional neural network (LiAENN) for a pattern recognition problem. LiAENN is a novel computational neural model of the emotional brain that models emotional situations such as anxiety and confidence in the learning process, the short paths, the forgetting processes, and inhibitory mechanisms of the emotional brain. In the model, the learning weights are adjusted by the proposed anxious confident decayed brain emotional learning rules (ACDBEL). In engineering applications, LiAENN is utilized in facial detection, and emotion recognition. According to the comparative results on ORL and Yale datasets, LiAENN shows a higher accuracy than other applied emotional networks such as brain emotional learning (BEL) and emotional back propagation (EmBP) based networks.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Spectral tripartitioning of networks

    NASA Astrophysics Data System (ADS)

    Richardson, Thomas; Mucha, Peter J.; Porter, Mason A.

    2009-09-01

    We formulate a spectral graph-partitioning algorithm that uses the two leading eigenvectors of the matrix corresponding to a selected quality function to split a network into three communities in a single step. In so doing, we extend the recursive bipartitioning methods developed by Newman [M. E. J. Newman, Proc. Natl. Acad. Sci. U.S.A. 103, 8577 (2006); Phys. Rev. E 74, 036104 (2006)] to allow one to consider the best available two-way and three-way divisions at each recursive step. We illustrate the method using simple “bucket brigade” examples and then apply the algorithm to examine the community structures of the coauthorship graph of network scientists and of U. S. Congressional networks inferred from roll call voting similarities.

  13. 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.

  14. 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

  15. Ramification of stream networks.

    PubMed

    Devauchelle, Olivier; Petroff, Alexander P; Seybold, Hansjörg F; Rothman, Daniel H

    2012-12-18

    The geometric complexity of stream networks has been a source of fascination for centuries. However, a comprehensive understanding of ramification--the mechanism of branching by which such networks grow--remains elusive. Here we show that streams incised by groundwater seepage branch at a characteristic angle of 2π/5 = 72°. Our theory represents streams as a collection of paths growing and bifurcating in a diffusing field. Our observations of nearly 5,000 bifurcated streams growing in a 100 km(2) groundwater field on the Florida Panhandle yield a mean bifurcation angle of 71.9° ± 0.8°. This good accord between theory and observation suggests that the network geometry is determined by the external flow field but not, as classical theories imply, by the flow within the streams themselves.

  16. 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.

  17. Network design tool for EHF satellite communications networks

    NASA Astrophysics Data System (ADS)

    Norvell, S.; Brown, G. J.

    1983-06-01

    This document describes the design concept of the network design tool. The network design tool (NDT) is a collection of analytical techniques, algorithms and simulation methods that may be used to characterize the performance of a computer communication network. Much work has been done over the past several years in network performance analysis and many techniques have been developed or proposed. Each of these methods applies to a particular aspect of the network design and is based on a particular modeling point of view. We define the computer communication network and then describe the different ways the network may be modeled. Each network model is related to the particular design problem being addressed. The various analytical approaches are briefly described and their relationship to the network models discussed. Chapter 2 is a survey of the major approaches to specific network design problems while chapters 3 and 4 discuss two fairly well defined areas of network analysis: topological design/optimization and protocol validation. Chapter 5 is a survey of network design tools presently available locally or on the advanced research projects agency network (ARPANET). Finally, chapter 6 presents an outline of the NDT specification.

  18. 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.

  19. Adaptive Transfer Function Networks

    SciTech Connect

    Goulding, J.R. |

    1993-06-01

    Real-time pattern classification and time-series forecasting applications continue to drive artificial neural network (ANN) technology. As ANNs increase in complexity, the throughput of digital computer simulations decreases. A novel ANN, the Adaptive Transfer Function Network (ATF-Net), directly addresses the issue of throughput. ATF-Nets are global mapping equations generated by the superposition of ensembles of neurodes having arbitrary continuous functions receiving encoded input data. ATF-Nets may be implemented on parallel digital computers. An example is presented which illustrates a four-fold increase in computational throughput.

  20. Adaptive Transfer Function Networks

    SciTech Connect

    Goulding, J.R. Portland State Univ., OR . Dept. of Electrical Engineering)

    1993-01-01

    Real-time pattern classification and time-series forecasting applications continue to drive artificial neural network (ANN) technology. As ANNs increase in complexity, the throughput of digital computer simulations decreases. A novel ANN, the Adaptive Transfer Function Network (ATF-Net), directly addresses the issue of throughput. ATF-Nets are global mapping equations generated by the superposition of ensembles of neurodes having arbitrary continuous functions receiving encoded input data. ATF-Nets may be implemented on parallel digital computers. An example is presented which illustrates a four-fold increase in computational throughput.

  1. 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.

  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. Energy Sciences Network

    SciTech Connect

    2010-01-01

    ESnet is a high-speed network serving thousands of Department of Energy scientists at over 40 institutions, as well as connecting to more than 100 other networks. ESnet is a pioneer in providing high-bandwidth, reliable connections that link researchers at national laboratories, universities and other research institutions, enabling them to collaborate on some of the world's most important scientific research challenges including energy, climate science, and the origins of the universe. Funded by the DOE Office of Science, and managed and operated by the ESnet team at Lawrence Berkeley National Laboratory, ESnet provides scientists access to unique DOE research facilities and computing resources.

  4. Networking with China

    SciTech Connect

    Cottrell, R.L.A.; Granieri, C.; Fan, Lan; Xu, Rongsheng; Karita, Yukio

    1994-12-31

    This paper presents the history and current status of computer networking between IHEP in Beijing, China and the rest of the world, starting with no links at the beginning of 1987 through X.25 public networks and dial up links, to the installing, in March 1993, of one of the first dedicated 64 kbps satellite computer links between China and the outside world. In May 1994, IHEP became the first operational worldwide Internet connection. Experience with this dedicated link between SLAC and IHEP will be presented together with future plans to add a land line between KEK and IHEP and to extend the links within China.

  5. 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.

  6. Women's network in Afghanistan.

    PubMed

    1997-01-01

    Violence and discrimination against women have been part of the Afghan culture for thousands of years, but recently this situation has grown worse. In response, Afghan women have recently formed the Afghan Women's Network. The main objective of this organization is to work for peace and human rights in Afghanistan where the Taliban sect has been especially oppressive of women's rights. In a declaration issued late last year, the Network, which includes women in Pakistan as well as Afghanistan, requested international support for their work to guarantee the right of women to work outside the home, as well as their right to education and personal safety. PMID:12179739

  7. Hybrid network intrusion detection

    NASA Astrophysics Data System (ADS)

    Tahmoush, David

    2014-05-01

    We report on a machine learning classifier that can be used to discover the patterns hidden within large networking data flows. It utilizes an existing intrusion detection system (IDS) as an oracle to learn a faster, less resource intensive normalcy classifier as a front-end to a hybrid network IDS. This system has the capability to recognize new attacks that are similar to known attack signatures. It is also more highly scalable and distributable than the signature-based IDS. The new hybrid design also allows distributed updates and retraining of the normalcy classifier to stay up-to-date with current threats.

  8. Building interconnected membrane networks.

    PubMed

    Holden, Matthew A

    2015-01-01

    Reconstituted replica cell membranes are easily created by contacting two lipid-monolayer-encased aqueous droplets under an oil phase. Called the droplet interface bilayer (DIB), this technique has been used to study a wide range of membrane processes. Importantly, this method is compatible with electrical measurements, meaning that membrane protein activities are easily observed in DIBs. By positioning droplets in two- and three-dimensional networks, sophisticated interconnected systems can be created that possess collective properties. The methods described here summarize the approaches used to create DIB networks and how to operate the devices that have been constructed so far.

  9. [Social networks and medicine].

    PubMed

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

    2015-11-01

    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. PMID:26685647

  10. 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.

  11. 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}.

  12. 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

  13. Random walks on networks

    NASA Astrophysics Data System (ADS)

    Donnelly, Isaac

    Random walks on lattices are a well used model for diffusion on continuum. They have been to model subdiffusive systems, systems with forcing and reactions as well as a combination of the three. We extend the traditional random walk framework to the network to obtain novel results. As an example due to the small graph diameter, the early time behaviour of subdiffusive dynamics dominates the observed system which has implications for models of the brain or airline networks. I would like to thank the Australian American Fulbright Association.

  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. 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.

  16. 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.

  17. Self-Configuring Network Monitor

    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 infrastructuremore » 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.« less

  18. The robustness of complex networks

    NASA Astrophysics Data System (ADS)

    Albert, Reka

    2002-03-01

    Many complex networks display a surprising degree of tolerance against errors. For example, organisms and ecosystems exhibit remarkable robustness to large variations in temperature, moisture, and nutrients, and communication networks continue to function despite local failures. This presentation will explore the effects of the network topology on its robust functioning. First, we will consider the topological integrity of several networks under node disruption. Then we will focus on the functional robustness of biological signaling networks, and the decisive role played by the network topology in this robustness.

  19. The robustness and restoration of a network of ecological networks.

    PubMed

    Pocock, Michael J O; Evans, Darren M; Memmott, Jane

    2012-02-24

    Understanding species' interactions and the robustness of interaction networks to species loss is essential to understand the effects of species' declines and extinctions. In most studies, different types of networks (such as food webs, parasitoid webs, seed dispersal networks, and pollination networks) have been studied separately. We sampled such multiple networks simultaneously in an agroecosystem. We show that the networks varied in their robustness; networks including pollinators appeared to be particularly fragile. We show that, overall, networks did not strongly covary in their robustness, which suggests that ecological restoration (for example, through agri-environment schemes) benefitting one functional group will not inevitably benefit others. Some individual plant species were disproportionately well linked to many other species. This type of information can be used in restoration management, because it identifies the plant taxa that can potentially lead to disproportionate gains in biodiversity.

  20. A Network Primer: Full-Fledged Educational Networks.

    ERIC Educational Resources Information Center

    Lehrer, Ariella

    1988-01-01

    Discusses some of the factors included in choosing appropriate computer networks for the classroom. Describes such networks as those produced by Apple Computer, Corvus Systems, Velan, Berkeley Softworks, Tandy, LAN-TECH, Unisys, and International Business Machines (IBM). (TW)

  1. 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

  2. Network Analysis Tools: from biological networks to clusters and pathways.

    PubMed

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

    2008-01-01

    Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

  3. 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

  4. Thermodynamics of random reaction networks.

    PubMed

    Fischer, Jakob; Kleidon, Axel; Dittrich, Peter

    2015-01-01

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

  5. Thermodynamics of random reaction networks.

    PubMed

    Fischer, Jakob; Kleidon, Axel; Dittrich, Peter

    2015-01-01

    Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha) and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with Watts-Strogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa -1.5 for linear and -1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks. PMID:25723751

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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)...

  7. 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…

  8. Validating Large Scale Networks Using Temporary Local Scale Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  9. Robustness of a partially interdependent network formed of clustered networks

    NASA Astrophysics Data System (ADS)

    Shao, Shuai; Huang, Xuqing; Stanley, H. Eugene; Havlin, Shlomo

    2014-03-01

    Clustering, or transitivity, a behavior observed in real-world networks, affects network structure and function. This property has been studied extensively, but most of this research has been limited to clustering in single networks. The effect of clustering on the robustness of coupled networks, on the other hand, has received much less attention. Only the case of a pair of fully coupled networks with clustering has recently received study. Here we generalize the study of clustering of a fully coupled pair of networks and apply it to a partially interdependent network of networks with clustering within the network components. We show, both analytically and numerically, how clustering within networks affects the percolation properties of interdependent networks, including the percolation threshold, the size of the giant component, and the critical coupling point at which the first-order phase transition changes to a second-order phase transition as the coupling between the networks is reduced. We study two types of clustering, one proposed by Newman [Phys. Rev. Lett. 103, 058701 (2009), 10.1103/PhysRevLett.103.058701] in which the average degree is kept constant while the clustering is changed, and the other by Hackett et al. [Phys. Rev. E 83, 056107 (2011), 10.1103/PhysRevE.83.056107] in which the degree distribution is kept constant. The first type of clustering is studied both analytically and numerically, and the second is studied numerically.

  10. 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.…

  11. 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…

  12. 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…

  13. 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.

  14. Collaboration in social networks

    PubMed Central

    Dall’Asta, Luca; Marsili, Matteo; Pin, Paolo

    2012-01-01

    The very notion of social network implies that linked individuals interact repeatedly with each other. This notion allows them not only to learn successful strategies and adapt to them, but also to condition their own behavior on the behavior of others, in a strategic forward looking manner. Game theory of repeated games shows that these circumstances are conducive to the emergence of collaboration in simple games of two players. We investigate the extension of this concept to the case where players are engaged in a local contribution game and show that rationality and credibility of threats identify a class of Nash equilibria—that we call “collaborative equilibria”—that have a precise interpretation in terms of subgraphs of the social network. For large network games, the number of such equilibria is exponentially large in the number of players. When incentives to defect are small, equilibria are supported by local structures whereas when incentives exceed a threshold they acquire a nonlocal nature, which requires a “critical mass” of more than a given fraction of the players to collaborate. Therefore, when incentives are high, an individual deviation typically causes the collapse of collaboration across the whole system. At the same time, higher incentives to defect typically support equilibria with a higher density of collaborators. The resulting picture conforms with several results in sociology and in the experimental literature on game theory, such as the prevalence of collaboration in denser groups and in the structural hubs of sparse networks. PMID:22383559

  15. 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…

  16. 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.

  17. Programming Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Lopes, Luís; Martins, Francisco; Barros, João

    Sensor networks can be viewed as a collection of tiny, low-cost devices programmed to sense the physical world and that communicate over radio links [12]. The devices are commonly called motes or smart dust [676], in allusion to their computational and sensing capabilities, as well as their increasingly small size.

  18. 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…

  19. 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.

  20. Family Support Networks.

    ERIC Educational Resources Information Center

    Frazier, Billie H.

    This document contains a brief bibliography of peer-reviewed literature, with abstracts, on family support networks. It is one of 12 bibliographies on aging prepared by the National Agricultural Library for its "Pathfinders" series of publications. Topics covered by the other 11 bibliographies include aging parents, adult children, dementia and…

  1. 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.

  2. Prototyping distributed simulation networks

    NASA Technical Reports Server (NTRS)

    Doubleday, Dennis L.

    1990-01-01

    Durra is a declarative language designed to support application-level programming. The use of Durra is illustrated to describe a simple distributed application: a simulation of a collection of networked vehicle simulators. It is shown how the language is used to describe the application, its components and structure, and how the runtime executive provides for the execution of the application.

  3. 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

  4. 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)

  5. Transactional Network Platform: Applications

    SciTech Connect

    Katipamula, Srinivas; Lutes, Robert G.; Ngo, Hung; Underhill, Ronald M.

    2013-10-31

    In FY13, Pacific Northwest National Laboratory (PNNL) with funding from the Department of Energy’s (DOE’s) Building Technologies Office (BTO) designed, prototyped and tested a transactional network platform to support energy, operational and financial transactions between any networked entities (equipment, organizations, buildings, grid, etc.). Initially, in FY13, the concept demonstrated transactions between packaged rooftop air conditioners and heat pump units (RTUs) and the electric grid using applications or "agents" that reside on the platform, on the equipment, on a local building controller or in the Cloud. The transactional network project is a multi-lab effort with Oakridge National Laboratory (ORNL) and Lawrence Berkeley National Laboratory (LBNL) also contributing to the effort. PNNL coordinated the project and also was responsible for the development of the transactional network (TN) platform and three different applications associated with RTUs. This document describes two applications or "agents" in details, and also summarizes the platform. The TN platform details are described in another companion document.

  6. Communicability across evolving networks

    NASA Astrophysics Data System (ADS)

    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.

  7. Management of space networks

    NASA Technical Reports Server (NTRS)

    Markley, R. W.; Williams, B. F.

    1993-01-01

    NASA has proposed missions to the Moon and Mars that reflect three areas of emphasis: human presence, exploration, and space resource development for the benefit of Earth. A major requirement for such missions is a robust and reliable communications architecture. Network management--the ability to maintain some degree of human and automatic control over the span of the network from the space elements to the end users on Earth--is required to realize such robust and reliable communications. This article addresses several of the architectural issues associated with space network management. Round-trip delays, such as the 5- to 40-min delays in the Mars case, introduce a host of problems that must be solved by delegating significant control authority to remote nodes. Therefore, management hierarchy is one of the important architectural issues. The following article addresses these concerns, and proposes a network management approach based on emerging standards that covers the needs for fault, configuration, and performance management, delegated control authority, and hierarchical reporting of events. A relatively simple approach based on standards was demonstrated in the DSN 2000 Information Systems Laboratory, and the results are described.

  8. Congenital Heart Information Network

    MedlinePlus

    ... Barmash and Uwe 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

  9. Microsystem process networks

    DOEpatents

    Wegeng, Robert S.; TeGrotenhuis, Ward E.; Whyatt, Greg A.

    2006-10-24

    Various aspects and applications of microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having exergetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  10. Microsystem process networks

    DOEpatents

    Wegeng, Robert S [Richland, WA; TeGrotenhuis, Ward E [Kennewick, WA; Whyatt, Greg A [West Richland, WA

    2010-01-26

    Various aspects and applications or microsystem process networks are described. The design of many types of microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  11. Microsystem process networks

    DOEpatents

    Wegeng, Robert S.; TeGrotenhuis, Ward E.; Whyatt, Greg A.

    2007-09-18

    Various aspects and applications of microsystem process networks are described. The design of many types of Microsystems can be improved by ortho-cascading mass, heat, or other unit process operations. Microsystems having energetically efficient microchannel heat exchangers are also described. Detailed descriptions of numerous design features in microcomponent systems are also provided.

  12. Network Systems Technician.

    ERIC Educational Resources Information Center

    Ohio State Univ., Columbus. Center on Education and Training for Employment.

    This publication contains 17 subjects appropriate for use in a competency list for the occupation of network systems technician, 1 of 12 occupations within the business/computer technologies cluster. Each unit consists of a number of competencies; a list of competency builders is provided for each competency. Titles of the 17 units are as follows:…

  13. Seismic Computerized Alert Network

    USGS Publications Warehouse

    1986-01-01

    In 1985 the USGS devised a model for a Seismic Computerized Alert Network (SCAN) that would use continuous monitoring of seismic data from existing types of instruments to provide automatic, highly-reliable early warnings of earthquake shaking. In a large earthquake, substantial damaging ground motions may occur at great distances from the earthquake's epicenter.

  14. BER Science Network Requirements

    SciTech Connect

    Alapaty, Kiran; Allen, Ben; Bell, Greg; Benton, David; Brettin, Tom; Canon, Shane; Dart, Eli; Cotter, Steve; Crivelli, Silvia; Carlson, Rich; Dattoria, Vince; Desai, Narayan; Egan, Richard; Tierney, Brian; Goodwin, Ken; Gregurick, Susan; Hicks, Susan; Johnston, Bill; de Jong, Bert; Kleese van Dam, Kerstin; Livny, Miron; Markowitz, Victor; McGraw, Jim; McCord, Raymond; Oehmen, Chris; Regimbal, Kevin; Shipman, Galen; Strand, Gary; Flick, Jeff; Turnbull, Susan; Williams, Dean; Zurawski, Jason

    2010-11-01

    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 2010 ESnet and the Office of Biological and Environmental Research, of the DOE Office of Science, organized a workshop to characterize the networking requirements of the science programs funded by BER. The requirements identified at the workshop are summarized and described in more detail in the case studies and the Findings section. A number of common themes emerged from the case studies and workshop discussions. One is that BER science, like many other disciplines, is becoming more and more distributed and collaborative in nature. Another common theme is that data set sizes are exploding. Climate Science in particular is on the verge of needing to manage exabytes of data, and Genomics is on the verge of a huge paradigm shift in the number of sites with sequencers and the amount of sequencer data being generated.

  15. The Falcon Telescope Network

    NASA Astrophysics Data System (ADS)

    Chun, F.; Tippets, R.; Dearborn, M.; Gresham, K.; Freckleton, R.; Douglas, M.

    2014-09-01

    The Falcon Telescope Network (FTN) is a global network of small aperture telescopes developed by the Center for Space Situational Awareness Research in the Department of Physics at the United States Air Force Academy (USAFA). Consisting of commercially available equipment, the FTN is a collaborative effort between USAFA and other educational institutions ranging from two- and four-year colleges to major research universities. USAFA provides the equipment (e.g. telescope, mount, camera, filter wheel, dome, weather station, computers and storage devices) while the educational partners provide the building and infrastructure to support an observatory. The user base includes USAFA along with K-12 and higher education faculty and students. Since the FTN has a general use purpose, objects of interest include satellites, astronomical research, and STEM support images. The raw imagery, all in the public domain, will be accessible to FTN partners and will be archived at USAFA in the Cadet Space Operations Center. FTN users will be able to submit observational requests via a web interface. The requests will then be prioritized based on the type of user, the object of interest, and a user-defined priority. A network wide schedule will be developed every 24 hours and each FTN site will autonomously execute its portion of the schedule. After an observational request is completed, the FTN user will receive notification of collection and a link to the data. The Falcon Telescope Network is an ambitious endeavor, but demonstrates the cooperation that can be achieved by multiple educational institutions.

  16. Critical Branching Neural Networks

    ERIC Educational Resources Information Center

    Kello, Christopher T.

    2013-01-01

    It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

  17. 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"…

  18. Designing Networks for Innovation

    ERIC Educational Resources Information Center

    Laskowski, Paul Luke

    2009-01-01

    The last decades have seen tremendous growth and transformation in the Internet's commercial landscape. Underneath this success, however, the underlying network architecture has shown a marked resistance to change; it is now described as stagnant and ossified. Numerous design proposals have been developed by researchers, implemented in code, and…

  19. 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.

  20. Transportation Network Topologies

    NASA Technical Reports Server (NTRS)

    Holmes, Bruce J.; Scott, John M.

    2004-01-01

    A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21PstP thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within

  1. Transportation Network Topologies

    NASA Technical Reports Server (NTRS)

    Holmes, Bruce J.; Scott, John

    2004-01-01

    A discomforting reality has materialized on the transportation scene: our existing air and ground infrastructures will not scale to meet our nation's 21st century demands and expectations for mobility, commerce, safety, and security. The consequence of inaction is diminished quality of life and economic opportunity in the 21st century. Clearly, new thinking is required for transportation that can scale to meet to the realities of a networked, knowledge-based economy in which the value of time is a new coin of the realm. This paper proposes a framework, or topology, for thinking about the problem of scalability of the system of networks that comprise the aviation system. This framework highlights the role of integrated communication-navigation-surveillance systems in enabling scalability of future air transportation networks. Scalability, in this vein, is a goal of the recently formed Joint Planning and Development Office for the Next Generation Air Transportation System. New foundations for 21st thinking about air transportation are underpinned by several technological developments in the traditional aircraft disciplines as well as in communication, navigation, surveillance and information systems. Complexity science and modern network theory give rise to one of the technological developments of importance. Scale-free (i.e., scalable) networks represent a promising concept space for modeling airspace system architectures, and for assessing network performance in terms of scalability, efficiency, robustness, resilience, and other metrics. The paper offers an air transportation system topology as framework for transportation system innovation. Successful outcomes of innovation in air transportation could lay the foundations for new paradigms for aircraft and their operating capabilities, air transportation system architectures, and airspace architectures and procedural concepts. The topology proposed considers air transportation as a system of networks, within which

  2. Wide area sensor network

    NASA Astrophysics Data System (ADS)

    Mukhopadhyay, Sanjoy; Nix, Tricia; Junker, Robert; Brentano, Josef; Khona, Dhiren

    2006-05-01

    The technical concept for this project has existed since the Chernobyl accident in 1986. A host of Eastern European nations have developed countrywide grid of sensors to monitor airborne radiation. The objective is to build a radiological sensor network for real-time monitoring of environmental radiation levels in order to provide data for warning, and consequentially the assessment of a nuclear event. A network of radiation measuring equipment consisting of gamma, neutron, alpha, and beta counters would be distributed over a large area (preferably on fire station roof tops) and connected by a wireless network to the emergency response center. The networks would be deployed in urban environments and would supply first responders and federal augmentation teams (including those from the U.S. Departments of Energy, Defense, Justice, and Homeland Security) with detailed, accurate information regarding the transport of radioactive environmental contaminants, so the agencies can provide a safe and effective response. A networked sensor capability would be developed, with fixed sensors deployed at key locations and in sufficient numbers, to provide adequate coverage for early warning, and input to post-event emergency response. An overall system description and specification will be provided, including detector characteristics, communication protocols, infrastructure and maintenance requirements, and operation procedures. The system/network can be designed for a specifically identified urban area, or for a general urban area scalable to cities of specified size. Data collected via the network will be transmitted directly to the appropriate emergency response center and shared with multiple agencies via the Internet or an Intranet. The data collected will be managed using commercial off - the - shelf Geographical Information System (GIS). The data will be stored in a database and the GIS software will aid in analysis and management of the data. Unique features of the

  3. Parallel architectures and neural networks

    SciTech Connect

    Calianiello, E.R. )

    1989-01-01

    This book covers parallel computer architectures and neural networks. Topics include: neural modeling, use of ADA to simulate neural networks, VLSI technology, implementation of Boltzmann machines, and analysis of neural nets.

  4. Dynamic behaviors in directed networks

    SciTech Connect

    Park, Sung Min; Kim, Beom Jun

    2006-08-15

    Motivated by the abundance of directed synaptic couplings in a real biological neuronal network, we investigate the synchronization behavior of the Hodgkin-Huxley model in a directed network. We start from the standard model of the Watts-Strogatz undirected network and then change undirected edges to directed arcs with a given probability, still preserving the connectivity of the network. A generalized clustering coefficient for directed networks is defined and used to investigate the interplay between the synchronization behavior and underlying structural properties of directed networks. We observe that the directedness of complex networks plays an important role in emerging dynamical behaviors, which is also confirmed by a numerical study of the sociological game theoretic voter model on directed networks.

  5. Rare Diseases Clinical Research Network

    MedlinePlus

    ... RDCRN? Aims of the Rare Diseases Clinical Research Network Contact Us RDCRN Members Login Accessibility Disclaimer The Rare Diseases Clinical Research Network is an initiative of the Office of Rare ...

  6. Complex networks: A winning strategy

    NASA Astrophysics Data System (ADS)

    D'Souza, Raissa M.

    2013-04-01

    Introducing connections between two distinct networks can tip the balance of power -- at times enhancing the weaker system. The properties of the nodes that are linked together often determine which network claims the competitive advantage.

  7. AIDS Clinical Trials Group Network

    MedlinePlus

    ... Search About Our Mission History of the ACTG Network Leadership Committees Organizational Matrix (PDF - 68 KB) State ... Guidelines Annual Progress Reports Leadership and Operations Center Network Coordinating Center Statistical and Data Management Center Performance ...

  8. Online Advertising in Social Networks

    NASA Astrophysics Data System (ADS)

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

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

  9. Local Area Networks (The Printout).

    ERIC Educational Resources Information Center

    Aron, Helen; Balajthy, Ernest

    1989-01-01

    Describes the Local Area Network (LAN), a project in which students used LAN-based word processing and electronic mail software as the center of a writing process approach. Discusses the advantages and disadvantages of networking. (MM)

  10. Information cascade on networks

    NASA Astrophysics Data System (ADS)

    Hisakado, Masato; Mori, Shintaro

    2016-05-01

    In this paper, we discuss a voting model by considering three different kinds of networks: a random graph, the Barabási-Albert (BA) model, and a fitness model. A voting model represents the way in which public perceptions are conveyed to voters. Our voting model is constructed by using two types of voters-herders and independents-and two candidates. Independents conduct voting based on their fundamental values; on the other hand, herders base their voting on the number of previous votes. Hence, herders vote for the majority candidates and obtain information relating to previous votes from their networks. We discuss the difference between the phases on which the networks depend. Two kinds of phase transitions, an information cascade transition and a super-normal transition, were identified. The first of these is a transition between a state in which most voters make the correct choices and a state in which most of them are wrong. The second is a transition of convergence speed. The information cascade transition prevails when herder effects are stronger than the super-normal transition. In the BA and fitness models, the critical point of the information cascade transition is the same as that of the random network model. However, the critical point of the super-normal transition disappears when these two models are used. In conclusion, the influence of networks is shown to only affect the convergence speed and not the information cascade transition. We are therefore able to conclude that the influence of hubs on voters' perceptions is limited.

  11. Space Network Devices Developed

    NASA Technical Reports Server (NTRS)

    Jones, Robert E.

    2004-01-01

    The NASA Glenn Research Center through a contract with Spectrum Astro, Inc., has been developing space network hardware as an enabling technology using open systems interconnect (OSI) standards for space-based communications applications. The OSI standard is a well-recognized layered reference model that specifies how data should be sent node to node in a communications network. Because of this research and technology development, a space-qualifiable Ethernet-based network interface card (similar to the type found in a networked personal computer) and the associated four-port hub were designed and developed to flight specifications. During this research and development, there also have been many lessons learned for determining approaches for migrating existing spacecraft architectures to an OSI-network-based platform. Industry has recognized the benefits of targeting hardware developed around OSI standards such as Transmission Control Protocol/Internet Protocol (TCP/IP) or similar protocols for use in future generations of space communication systems. Some of these tangible benefits include overall reductions in mission schedule and cost and in system complexity. This development also brings us a step closer to the realization of a principal investigator on a terrestrial Internet site being able to interact with space platform assets in near real time. To develop this hardware, Spectrum Astro first conducted a technology analysis of alternatives study. For this analysis, they looked at the features of three protocol specifications: Ethernet (IEEE 802.3), Firewire (IEEE 1394), and Spacewire (IEEE 1355). A thorough analysis was performed on the basis of criteria such as current protocol performance and suitability for future space applications. Spectrum Astro also projected future influences such as cost, hardware and software availability, throughput performance, and integration procedures for current and transitive space architectures. After a thorough analysis

  12. Drainage networks after wildfire

    USGS Publications Warehouse

    Kinner, D.A.; Moody, J.A.

    2005-01-01

    Predicting runoff and erosion from watersheds burned by wildfires requires an understanding of the three-dimensional structure of both hillslope and channel drainage networks. We investigate the small-and large-scale structures of drainage networks using field studies and computer analysis of 30-m digital elevation model. Topologic variables were derived from a composite 30-m DEM, which included 14 order 6 watersheds within the Pikes Peak batholith. Both topologic and hydraulic variables were measured in the field in two smaller burned watersheds (3.7 and 7.0 hectares) located within one of the order 6 watersheds burned by the 1996 Buffalo Creek Fire in Central Colorado. Horton ratios of topologic variables (stream number, drainage area, stream length, and stream slope) for small-scale and large-scale watersheds are shown to scale geometrically with stream order (i.e., to be scale invariant). However, the ratios derived for the large-scale drainage networks could not be used to predict the rill and gully drainage network structure. Hydraulic variables (width, depth, cross-sectional area, and bed roughness) for small-scale drainage networks were found to be scale invariant across 3 to 4 stream orders. The relation between hydraulic radius and cross-sectional area is similar for rills and gullies, suggesting that their geometry can be treated similarly in hydraulic modeling. Additionally, the rills and gullies have relatively small width-to-depth ratios, implying sidewall friction may be important to the erosion and evolutionary process relative to main stem channels.

  13. Search in weighted complex networks

    NASA Astrophysics Data System (ADS)

    Thadakamalla, Hari P.; Albert, R.; Kumara, S. R. T.

    2005-12-01

    We study trade-offs presented by local search algorithms in complex networks which are heterogeneous in edge weights and node degree. We show that search based on a network measure, local betweenness centrality (LBC), utilizes the heterogeneity of both node degrees and edge weights to perform the best in scale-free weighted networks. The search based on LBC is universal and performs well in a large class of complex networks.

  14. The AAVSO High Energy Network

    NASA Astrophysics Data System (ADS)

    Price, Aaron

    2004-06-01

    The AAVSO is expanding its International Gamma-Ray Burst Network to incorporate other high energy objects such as blazars and magnetic cataclysmic variables (polars). The new AAVSO High Energy Network will be collaborating with the Global Telescope Network (GTN) to observe bright blazars in support of the upcoming GLAST mission. We also will be observing polars in support of the XMM mission. This new network will involve both visual and CCD obsrvers and is expected to last for many years.

  15. Online social networking for radiology.

    PubMed

    Auffermann, William F; Chetlen, Alison L; Colucci, Andrew T; DeQuesada, Ivan M; Grajo, Joseph R; Heller, Matthew T; Nowitzki, Kristina M; Sherry, Steven J; Tillack, Allison A

    2015-01-01

    Online social networking services have changed the way we interact as a society and offer many opportunities to improve the way we practice radiology and medicine in general. This article begins with an introduction to social networking. Next, the latest advances in online social networking are reviewed, and areas where radiologists and clinicians may benefit from these new tools are discussed. This article concludes with several steps that the interested reader can take to become more involved in online social networking.

  16. Network-dosage compensation topologies as recurrent network motifs in natural gene networks

    PubMed Central

    2014-01-01

    Background Global noise in gene expression and chromosome duplication during cell-cycle progression cause inevitable fluctuations in the effective number of copies of gene networks in cells. These indirect and direct alterations of network copy numbers have the potential to change the output or activity of a gene network. For networks whose specific activity levels are crucial for optimally maintaining cellular functions, cells need to implement mechanisms to robustly compensate the effects of network dosage fluctuations. Results Here, we determine the necessary conditions for generalized N-component gene networks to be network-dosage compensated and show that the compensation mechanism can robustly operate over large ranges of gene expression levels. Furthermore, we show that the conditions that are necessary for network-dosage compensation are also sufficient. Finally, using genome-wide protein-DNA and protein-protein interaction data, we search the yeast genome for the abundance of specific dosage-compensation motifs and show that a substantial percentage of the natural networks identified contain at least one dosage-compensation motif. Conclusions Our results strengthen the hypothesis that the special network topologies that are necessary for network-dosage compensation may be recurrent network motifs in eukaryotic genomes and therefore may be an important design principle in gene network assembly in cells. PMID:24929807

  17. 78 FR 12359 - Goodman Networks, Inc., Core Network Engineering (Deployment Engineering) Division Including...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-22

    ... Employment and Training Administration Goodman Networks, Inc., Core Network Engineering (Deployment Engineering) Division Including Workers in the Core Network Engineering (Deployment Engineering) Division in... of Goodman Networks, Inc., Core Network Engineering (Deployment Engineering) Division,...

  18. Process-in-Network: A Comprehensive Network Processing Approach

    PubMed Central

    Urzaiz, Gabriel; Villa, David; Villanueva, Felix; Lopez, Juan Carlos

    2012-01-01

    A solid and versatile communications platform is very important in modern Ambient Intelligence (AmI) applications, which usually require the transmission of large amounts of multimedia information over a highly heterogeneous network. This article focuses on the concept of Process-in-Network (PIN), which is defined as the possibility that the network processes information as it is being transmitted, and introduces a more comprehensive approach than current network processing technologies. PIN can take advantage of waiting times in queues of routers, idle processing capacity in intermediate nodes, and the information that passes through the network. PMID:22969390

  19. Network-Based Management Procedures.

    ERIC Educational Resources Information Center

    Buckner, Allen L.

    Network-based management procedures serve as valuable aids in organizational management, achievement of objectives, problem solving, and decisionmaking. Network techniques especially applicable to educational management systems are the program evaluation and review technique (PERT) and the critical path method (CPM). Other network charting…

  20. Kohonen neural networks and language.

    PubMed

    Anderson, B

    1999-10-15

    Kohonen neural networks are a type of self-organizing network that recognizes the statistical characteristics of input datasets. The application of this type of neural network to language theory is demonstrated in the present note by showing three brief applications: recognizing word borders, learning the limited phonemes of one's native tongue, and category-specific naming impairments.

  1. Network Systems Administration Needs Assessment.

    ERIC Educational Resources Information Center

    Lexington Community Coll., KY. Office of Institutional Research.

    In spring 1996, Lexington Community College (LCC) in Kentucky, conducted a survey to gather information on employment trends and educational needs in the field of network systems administration (NSA). NSA duties involve the installation and administration of network operating systems, applications software, and networking infrastructure;…

  2. The Johns Hopkins Hospital Network

    PubMed Central

    Tolchin, Stephen G.; Barta, Wendy; Harkness, Kenneth

    1985-01-01

    The Johns Hopkins Hospital has initiated an ambitious program to apply modern technologies to the development of a new, comprehensive clinical information system. One component of this system is a networking technology for supporting the integration of diverse and functionally distinct information systems. This paper discusses the selection of the networking technology implemented at JHH, issues and problems, networking concepts, protocols and reliability.

  3. Gateways among Academic Computer Networks.

    ERIC Educational Resources Information Center

    McCredie, John W.

    1984-01-01

    Local area networks for intracampus facilities and national inter-campus networks are discussed. Descriptions of some of these networks (ARPAnet, BITNET, CSNET, EDUNET, MAILNET, RLIN, AND USENET) are provided that illustrate the wide range of academic applications currently available. (Author/MLW)

  4. NASA Integrated Space Communications Network

    NASA Technical Reports Server (NTRS)

    Tai, Wallace; Wright, Nate; Prior, Mike; Bhasin, Kul

    2012-01-01

    The NASA Integrated Network for Space Communications and Navigation (SCaN) has been in the definition phase since 2010. It is intended to integrate NASA s three existing network elements, i.e., the Space Network, Near Earth Network, and Deep Space Network, into a single network. In addition to the technical merits, the primary purpose of the Integrated Network is to achieve a level of operating cost efficiency significantly higher than it is today. Salient features of the Integrated Network include (a) a central system element that performs service management functions and user mission interfaces for service requests; (b) a set of common service execution equipment deployed at the all stations that provides return, forward, and radiometric data processing and delivery capabilities; (c) the network monitor and control operations for the entire integrated network are conducted remotely and centrally at a prime-shift site and rotating among three sites globally (a follow-the-sun approach); (d) the common network monitor and control software deployed at all three network elements that supports the follow-the-sun operations.

  5. Teachers Seek Specialized Peer Networks

    ERIC Educational Resources Information Center

    Tomassini, Jason

    2013-01-01

    Within the wide expanse of social networking, educators appear to be gravitating to more protected and exclusive spaces. While teachers often use such popular mainstream social networks as Facebook, they are more likely to seek out and return to less-established networks that offer the privacy, peer-to-peer connections, and resource sharing that…

  6. Generalized Adaptive Artificial Neural Networks

    NASA Technical Reports Server (NTRS)

    Tawel, Raoul

    1993-01-01

    Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.

  7. Neural Networks for Readability Analysis.

    ERIC Educational Resources Information Center

    McEneaney, John E.

    This paper describes and reports on the performance of six related artificial neural networks that have been developed for the purpose of readability analysis. Two networks employ counts of linguistic variables that simulate a traditional regression-based approach to readability. The remaining networks determine readability from "visual snapshots"…

  8. Accelerating, hyperaccelerating, and decelerating networks

    NASA Astrophysics Data System (ADS)

    Gagen, M. J.; Mattick, J. S.

    2005-07-01

    Many growing networks possess accelerating statistics where the number of links added with each new node is an increasing function of network size so the total number of links increases faster than linearly with network size. In particular, biological networks can display a quadratic growth in regulator number with genome size even while remaining sparsely connected. These features are mutually incompatible in standard treatments of network theory which typically require that every new network node possesses at least one connection. To model sparsely connected networks, we generalize existing approaches and add each new node with a probabilistic number of links to generate either accelerating, hyperaccelerating, or even decelerating network statistics in different regimes. Under preferential attachment for example, slowly accelerating networks display stationary scale-free statistics relatively independent of network size while more rapidly accelerating networks display a transition from scale-free to exponential statistics with network growth. Such transitions explain, for instance, the evolutionary record of single-celled organisms which display strict size and complexity limits.

  9. The Selling of a Network.

    ERIC Educational Resources Information Center

    1976

    The Lister Hill Network was a federally supported program designed to share computer-assisted instruction (CAI) programs among health science institutions through a national computer network. In May 1975, federal support of the program was discontinued. At that time, the Health Education Network Users Group (HENUG) was formed to insure the…

  10. Wireless networking for international safeguards.

    SciTech Connect

    Smartt, Heidi Anne; Caskey, Susan Adele

    2003-06-01

    Wireless networking using the IEEE 802.11standards is a viable alternative for data communications in safeguards applications. This paper discusses the range of 802.11-based networking applications, along with their advantages and disadvantages. For maximum performance, safety, and security, Wireless networking should be implemented only after a comprehensive site survey has determined detailed requirements, hazards, and threats.

  11. Network Coding for Function Computation

    ERIC Educational Resources Information Center

    Appuswamy, Rathinakumar

    2011-01-01

    In this dissertation, the following "network computing problem" is considered. Source nodes in a directed acyclic network generate independent messages and a single receiver node computes a target function f of the messages. The objective is to maximize the average number of times f can be computed per network usage, i.e., the "computing…

  12. Telecommunications Networking in Online Retrieval.

    ERIC Educational Resources Information Center

    Mahon, Barry

    1991-01-01

    Reviews the development of telecommunications networks and describes current technology being used for online information retrieval. Highlights include use for military and research needs; experiences in Europe versus those in the United States; value-added networks (VANs); local area networks (LANs) and personal computers; and the Integrated…

  13. Ohio: Library and Information Networks.

    ERIC Educational Resources Information Center

    Byerly, Greg

    1996-01-01

    Describes the development, current status, and future goals and plans of library and information networks in Ohio. Highlights include OCLC; OhioLINK, incorporating state-assisted universities, two-year colleges, the state library, and private university libraries; a school library network; a public library information network; a telecommunications…

  14. Space-Time Neural Networks

    NASA Technical Reports Server (NTRS)

    Villarreal, James A.; Shelton, Robert O.

    1992-01-01

    Concept of space-time neural network affords distributed temporal memory enabling such network to model complicated dynamical systems mathematically and to recognize temporally varying spatial patterns. Digital filters replace synaptic-connection weights of conventional back-error-propagation neural network.

  15. Underage Children and Social Networking

    ERIC Educational Resources Information Center

    Weeden, Shalynn; Cooke, Bethany; McVey, Michael

    2013-01-01

    Despite minimum age requirements for joining popular social networking services such as Facebook, many students misrepresent their real ages and join as active participants in the networks. This descriptive study examines the use of social networking services (SNSs) by children under the age of 13. The researchers surveyed a sample of 199…

  16. Breaking Free with Wireless Networks.

    ERIC Educational Resources Information Center

    Fleischman, John

    2002-01-01

    Discusses wireless local area networks (LANs) which typically consist of laptop computers that connect to fixed access points via infrared or radio signals. Topics include wide area networks; personal area networks; problems, including limitations of available bandwidth, interference, and security concerns; use in education; interoperability;…

  17. Deep space network energy program

    NASA Technical Reports Server (NTRS)

    Friesema, S. E.

    1980-01-01

    If the Deep Space Network is to exist in a cost effective and reliable manner in the next decade, the problems presented by international energy cost increases and energy availability must be addressed. The Deep Space Network Energy Program was established to implement solutions compatible with the ongoing development of the total network.

  18. Undermining and Strengthening Social Networks through Network Modification

    NASA Astrophysics Data System (ADS)

    Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

    2016-10-01

    Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

  19. Fluvial network imprints on microbial diversity and community network topology

    NASA Astrophysics Data System (ADS)

    Battin, T. J.; Besemer, K.; Widder, S.; Singer, G. A.; Ceola, S.; Bertuzzo, E.; Quince, C.; Sloan, W. T.; Rinaldo, A.

    2013-12-01

    Streams and rivers sculpt continental landscapes and the networks they form carry universal signatures of spatial organization. Biodiversity in fluvial networks ranks among the highest on Earth and microorganisms therein, often enclosed in biofilms, fulfill critical ecosystem functions even with repercussions on the global carbon cycle. We extensively used 454 pyrosequencing on biofilm samples from more than 100 streams from a 5th-order catchment, derived alpha and beta diversity patterns and, using co-occurrence analyses, we studied community network organization. Contrary to current theory and to animal diversity studies, we found microbial alpha diversity in biofilms to decrease downstream with confluences likely acting as filters to biodiversity as it propagates from the smallest headwaters to larger rivers. Along with higher beta diversity in the headwaters, these findings highlight headwaters as critical reservoirs of microbial diversity for entire fluvial networks. Co-occurrence analyses revealed a lower level of fragmentation of community networks in headwaters than in larger rivers downstream and further identified gatekeepers (at family level) as potential architects of the observed network topology. Similarly, fragmentation was higher downstream than upstream of confluences. Consistent with current network theory, simple model simulations suggest that fragmentation patterns are linked to persistence against perturbations. We further explore the role of perturbation for community network topology in the context of fluvial network hydrology. Our findings have deep implications for restoration and conservation. They portrait the imprint of fluvial networks on microbial community networks and thereby expand our knowledge on biodiversity and ecosystem persistence.

  20. A random interacting network model for complex networks.

    PubMed

    Goswami, Bedartha; Shekatkar, Snehal M; Rheinwalt, Aljoscha; Ambika, G; Kurths, Jürgen

    2015-01-01

    We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems. PMID:26657032

  1. Undermining and Strengthening Social Networks through Network Modification

    PubMed Central

    Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

    2016-01-01

    Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention. PMID:27703198

  2. A random interacting network model for complex networks

    NASA Astrophysics Data System (ADS)

    Goswami, Bedartha; Shekatkar, Snehal M.; Rheinwalt, Aljoscha; Ambika, G.; Kurths, Jürgen

    2015-12-01

    We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems.

  3. Weighted Scale-Free Network Properties of Ecological Network

    NASA Astrophysics Data System (ADS)

    Lee, Jae Woo; Maeng, Seong Eun

    2013-02-01

    We investigate the scale-free network properties of the bipartite ecological network, in particular, the plant-pollinator network. In plant-pollinator network, the pollinators visit the plant to get the nectars. In contrast to the other complex network, the plant-pollinator network has not only the trophic relationships among the interacting partners but also the complexities of the coevolutionary effects. The interactions between the plant and pollinators are beneficial relations. The plant-pollinator network is a bipartite and weighted network. The networks have two types of the nodes: plant and pollinator. We consider the visiting frequency of a pollinator to a plant as the weighting value of the link. We defined the strength of a node as the sum of the weighting value of the links. We reported the cumulative distribution function (CDF) of the degree and the strength of the plant-pollinator network. The CDF of the plants followed stretched exponential functions for both degree and strength, but the CDF of the pollinators showed the power law for both degree and strength. The average strength of the links showed the nonlinear dependence on the degree of the networks.

  4. Multiple network interface core apparatus and method

    DOEpatents

    Underwood, Keith D.; Hemmert, Karl Scott

    2011-04-26

    A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

  5. Network robustness of multiplex networks with interlayer degree correlations

    NASA Astrophysics Data System (ADS)

    Min, Byungjoon; Yi, Su Do; Lee, Kyu-Min; Goh, K.-I.

    2014-04-01

    We study the robustness properties of multiplex networks consisting of multiple layers of distinct types of links, focusing on the role of correlations between degrees of a node in different layers. We use generating function formalism to address various notions of the network robustness relevant to multiplex networks, such as the resilience of ordinary and mutual connectivity under random or targeted node removals, as well as the biconnectivity. We found that correlated coupling can affect the structural robustness of multiplex networks in diverse fashion. For example, for maximally correlated duplex networks, all pairs of nodes in the giant component are connected via at least two independent paths and network structure is highly resilient to random failure. In contrast, anticorrelated duplex networks are on one hand robust against targeted attack on high-degree nodes, but on the other hand they can be vulnerable to random failure.

  6. Network architecture in a converged optical + IP network

    NASA Astrophysics Data System (ADS)

    Wakim, Walid; Zottmann, Harald

    2012-01-01

    As demands on Provider Networks continue to grow at exponential rates, providers are forced to evaluate how to continue to grow the network while increasing service velocity, enhancing resiliency while decreasing the total cost of ownership (TCO). The bandwidth growth that networks are experiencing is in the form packet based multimedia services such as video, video conferencing, gaming, etc... mixed with Over the Top (OTT) content providers such as Netflix, and the customer's expectations that best effort is not enough you end up with a situation that forces the provider to analyze how to gain more out of the network with less cost. In this paper we will discuss changes in the network that are driving us to a tighter integration between packet and optical layers and how to improve on today's multi - layer inefficiencies to drive down network TCO and provide for a fully integrated and dynamic network that will decrease time to revenue.

  7. Lagged correlation networks

    NASA Astrophysics Data System (ADS)

    Curme, Chester

    Technological advances have provided scientists with large high-dimensional datasets that describe the behaviors of complex systems: from the statistics of energy levels in complex quantum systems, to the time-dependent transcription of genes, to price fluctuations among assets in a financial market. In this environment, where it may be difficult to infer the joint distribution of the data, network science has flourished as a way to gain insight into the structure and organization of such systems by focusing on pairwise interactions. This work focuses on a particular setting, in which a system is described by multivariate time series data. We consider time-lagged correlations among elements in this system, in such a way that the measured interactions among elements are asymmetric. Finally, we allow these interactions to be characteristically weak, so that statistical uncertainties may be important to consider when inferring the structure of the system. We introduce a methodology for constructing statistically validated networks to describe such a system, extend the methodology to accommodate interactions with a periodic component, and show how consideration of bipartite community structures in these networks can aid in the construction of robust statistical models. An example of such a system is a financial market, in which high frequency returns data may be used to describe contagion, or the spreading of shocks in price among assets. These data provide the experimental testing ground for our methodology. We study NYSE data from both the present day and one decade ago, examine the time scales over which the validated lagged correlation networks exist, and relate differences in the topological properties of the networks to an increasing economic efficiency. We uncover daily periodicities in the validated interactions, and relate our findings to explanations of the Epps Effect, an empirical phenomenon of financial time series. We also study bipartite community

  8. Topology of the European Network of Earth Observation Networks and the need for an European Network of Networks

    NASA Astrophysics Data System (ADS)

    Masó, Joan; Serral, Ivette; McCallum, Ian; Blonda, Palma; Plag, Hans-Peter

    2016-04-01

    ConnectinGEO (Coordinating an Observation Network of Networks EnCompassing saTellite and IN-situ to fill the Gaps in European Observations" is an H2020 Coordination and Support Action with the primary goal of linking existing Earth Observation networks with science and technology (S&T) communities, the industry sector, the Group on Earth Observations (GEO), and Copernicus. The project will end in February 2017. ConnectinGEO will initiate a European Network of Earth Observation Networks (ENEON) that will encompass space-based, airborne and in-situ observations networks. ENEON will be composed of project partners representing thematic observation networks along with the GEOSS Science and Technology Stakeholder Network, GEO Communities of Practices, Copernicus services, Sentinel missions and in-situ support data representatives, representatives of the European space-based, airborne and in-situ observations networks. This communication presents the complex panorama of Earth Observations Networks in Europe. The list of networks is classified by discipline, variables, geospatial scope, etc. We also capture the membership and relations with other networks and umbrella organizations like GEO. The result is a complex interrelation between networks that can not be clearly expressed in a flat list. Technically the networks can be represented as nodes with relations between them as lines connecting the nodes in a graph. We have chosen RDF as a language and an AllegroGraph 3.3 triple store that is visualized in several ways using for example Gruff 5.7. Our final aim is to identify gaps in the EO Networks and justify the need for a more structured coordination between them.

  9. Functional Module Analysis for Gene Coexpression Networks with Network Integration

    PubMed Central

    Zhang, Shuqin; Zhao, Hongyu

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with 3 complete subgraphs, and 11 modules with 2 complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally. PMID:26451826

  10. Evolution of cosmic string networks

    NASA Technical Reports Server (NTRS)

    Albrecht, Andreas; Turok, Neil

    1989-01-01

    A discussion of the evolution and observable consequences of a network of cosmic strings is given. A simple model for the evolution of the string network is presented, and related to the statistical mechanics of string networks. The model predicts the long string density throughout the history of the universe from a single parameter, which researchers calculate in radiation era simulations. The statistical mechanics arguments indicate a particular thermal form for the spectrum of loops chopped off the network. Detailed numerical simulations of string networks in expanding backgrounds are performed to test the model. Consequences for large scale structure, the microwave and gravity wave backgrounds, nucleosynthesis and gravitational lensing are calculated.

  11. Queueing in networks of computers

    NASA Technical Reports Server (NTRS)

    Denning, Peter J.

    1991-01-01

    The designers of networks of computers must assess the capacity of the network to complete work within reasonable times. The utilization law, Little's law, forced-flow law, and response time formula are simple tools that can be used to calculate throughput and response times of networks. Bottleneck analysis can be used to calculate simple lower bounds on response time in terms of individual server parameters and the load on network as a whole. These simple results are important tools for all users of scientific networks - back of the envelope calculations can quickly reveal the effects of distant servers on local throughput and response time.

  12. Nonlinear Dynamics on Interconnected Networks

    NASA Astrophysics Data System (ADS)

    Arenas, Alex; De Domenico, Manlio

    2016-06-01

    Networks of dynamical interacting units can represent many complex systems, from the human brain to transportation systems and societies. The study of these complex networks, when accounting for different types of interactions has become a subject of interest in the last few years, especially because its representational power in the description of users' interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.) [1], or in representing different transportation modes in urban networks [2,3]. The general name coined for these networks is multilayer networks, where each layer accounts for a type of interaction (see Fig. 1).

  13. Quantization Effects on Complex Networks

    PubMed Central

    Wang, Ying; Wang, Lin; Yang, Wen; Wang, Xiaofan

    2016-01-01

    Weights of edges in many complex networks we constructed are quantized values of the real weights. To what extent does the quantization affect the properties of a network? In this work, quantization effects on network properties are investigated based on the spectrum of the corresponding Laplacian. In contrast to the intuition that larger quantization level always implies a better approximation of the quantized network to the original one, we find a ubiquitous periodic jumping phenomenon with peak-value decreasing in a power-law relationship in all the real-world weighted networks that we investigated. We supply theoretical analysis on the critical quantization level and the power laws. PMID:27226049

  14. Network effects of animal conflicts

    NASA Astrophysics Data System (ADS)

    Yu, You-Yang; Ni, Yang-Chun

    2008-11-01

    We simulated animal conflicts on different networks, where five strategies that the animals may take are considered. The result of the evolution of the five strategies on networks shows that whether one strategy dominates or two strategies coexist on the network is determined by the structure of the network. But no matter what structure the network is, the total-war strategy is constrained and never becomes a final winning strategy when it contests with the other four limited-war strategies. This may be the reason that the animals choose the limited-war strategies to fight against other animals of the same species.

  15. Quantization Effects on Complex Networks

    NASA Astrophysics Data System (ADS)

    Wang, Ying; Wang, Lin; Yang, Wen; Wang, Xiaofan

    2016-05-01

    Weights of edges in many complex networks we constructed are quantized values of the real weights. To what extent does the quantization affect the properties of a network? In this work, quantization effects on network properties are investigated based on the spectrum of the corresponding Laplacian. In contrast to the intuition that larger quantization level always implies a better approximation of the quantized network to the original one, we find a ubiquitous periodic jumping phenomenon with peak-value decreasing in a power-law relationship in all the real-world weighted networks that we investigated. We supply theoretical analysis on the critical quantization level and the power laws.

  16. Quantization Effects on Complex Networks.

    PubMed

    Wang, Ying; Wang, Lin; Yang, Wen; Wang, Xiaofan

    2016-01-01

    Weights of edges in many complex networks we constructed are quantized values of the real weights. To what extent does the quantization affect the properties of a network? In this work, quantization effects on network properties are investigated based on the spectrum of the corresponding Laplacian. In contrast to the intuition that larger quantization level always implies a better approximation of the quantized network to the original one, we find a ubiquitous periodic jumping phenomenon with peak-value decreasing in a power-law relationship in all the real-world weighted networks that we investigated. We supply theoretical analysis on the critical quantization level and the power laws. PMID:27226049

  17. Rule generation from neural networks

    SciTech Connect

    Fu, L.

    1994-08-01

    The neural network approach has proven useful for the development of artificial intelligence systems. However, a disadvantage with this approach is that the knowledge embedded in the neural network is opaque. In this paper, we show how to interpret neural network knowledge in symbolic form. We lay down required definitions for this treatment, formulate the interpretation algorithm, and formally verify its soundness. The main result is a formalized relationship between a neural network and a rule-based system. In addition, it has been demonstrated that the neural network generates rules of better performance than the decision tree approach in noisy conditions. 7 refs.

  18. [Epilepsy care network].

    PubMed

    Otsuki, Taisuke

    2014-05-01

    Build-up of community health coalition system is now an essential part of medicine. However, little attention has been paid to epilepsy care in Japan, which resulted in a chaotic and difficult situation to find epilepsy-care physicians in the community. The reason is that responsible medical specialty in charge has been ambiguous historically in Japan and a lack of post-in-charge in the government to plan epilepsy care system is aggravating this condition. To solve this issue, epilepsy care network connecting the primary, secondary and tertiary epilepsy care physicians should be established and open to the community. In this context, our Epilepsy Care Network-Japan was started on July 2012 proposing a new epilepsy care algorithm suitable for our complex medical community. PMID:24912299

  19. Dynamics of associating networks

    NASA Astrophysics Data System (ADS)

    Tang, Shengchang; Habicht, Axel; Wang, Muzhou; Li, Shuaili; Seiffert, Sebastian; Olsen, Bradley

    Associating polymers offer important technological solutions to renewable and self-healing materials, conducting electrolytes for energy storage and transport, and vehicles for cell and protein deliveries. The interplay between polymer topologies and association chemistries warrants new interesting physics from associating networks, yet poses significant challenges to study these systems over a wide range of time and length scales. In a series of studies, we explored self-diffusion mechanisms of associating polymers above the percolation threshold, by combining experimental measurements using forced Rayleigh scattering and analytical insights from a two-state model. Despite the differences in molecular structures, a universal super-diffusion phenomenon is observed when diffusion of molecular species is hindered by dissociation kinetics. The molecular dissociation rate can be used to renormalize shear rheology data, which yields an unprecedented time-temperature-concentration superposition. The obtained shear rheology master curves provide experimental evidence of the relaxation hierarchy in associating networks.

  20. The language network.

    PubMed

    Friederici, Angela D; Gierhan, Sarah M E

    2013-04-01

    Language processing is supported by different regions located in separate parts of the brain. A crucial condition for these regions to function as a network is the information transfer between them. This is guaranteed by dorsal and ventral pathways connecting prefrontal and temporal language-relevant regions. Based on functional brain imaging studies, these pathways' language functions can be assigned indirectly. Dorsally, one pathway connecting the temporal cortex (TC) and premotor cortex supports speech repetition, another one connecting the TC and posterior Broca's area supports complex syntactic processes. Ventrally, the uncinate fascile and the inferior fronto-occipital fascile subserve semantic and basic syntactic processes. Thus, the available evidence points towards a neural language network with at least two dorsal and two ventral pathways. PMID:23146876

  1. Parallel processing neural networks

    SciTech Connect

    Zargham, M.

    1988-09-01

    A model for Neural Network which is based on a particular kind of Petri Net has been introduced. The model has been implemented in C and runs on the Sequent Balance 8000 multiprocessor, however it can be directly ported to different multiprocessor environments. The potential advantages of using Petri Nets include: (1) the overall system is often easier to understand due to the graphical and precise nature of the representation scheme, (2) the behavior of the system can be analyzed using Petri Net theory. Though, the Petri Net is an obvious choice as a basis for the model, the basic Petri Net definition is not adequate to represent the neuronal system. To eliminate certain inadequacies more information has been added to the Petri Net model. In the model, a token represents either a processor or a post synaptic potential. Progress through a particular Neural Network is thus graphically depicted in the movement of the processor tokens through the Petri Net.

  2. IT product competition Network

    NASA Astrophysics Data System (ADS)

    Xu, Xiu-Lian; Zhou, Lei; Shi, Jian-Jun; Wang, Yong-Li; Feng, Ai-Xia; He, Da-Ren

    2008-03-01

    Along with the technical development, the IT product competition becomes increasingly fierce in recent years. The factories, which produce the same IT product, have to improve continuously their own product quality for taking a large piece of cake in the product sale market. We suggest using a complex network description for the IT product competition. In the network the factories are defined as nodes, and two nodes are connected by a link if they produce a common IT product. The edge represents the sale competition relationship. 2121 factories and 265 products have been investigated. Some statistical properties, such as the degree distribution, node strength distribution, assortativity, and node degree correlation have been empirically obtained.

  3. Proximity Networks and Epidemics

    NASA Astrophysics Data System (ADS)

    Guclu, Hasan; Toroczkai, Zoltán

    2007-03-01

    We presented the basis of a framework to account for the dynamics of contacts in epidemic processes, through the notion of dynamic proximity graphs. By varying the integration time-parameter T, which is the period of infectivity one can give a simple account for some of the differences in the observed contact networks for different diseases, such as smallpox, or AIDS. Our simplistic model also seems to shed some light on the shape of the degree distribution of the measured people-people contact network from the EPISIM data. We certainly do not claim that the simplistic graph integration model above is a good model for dynamic contact graphs. It only contains the essential ingredients for such processes to produce a qualitative agreement with some observations. We expect that further refinements and extensions to this picture, in particular deriving the link-probabilities in the dynamic proximity graph from more realistic contact dynamics should improve the agreement between models and data.

  4. Modular sensor network node

    DOEpatents

    Davis, Jesse Harper Zehring; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick; Kyker, Ronald Dean

    2008-06-10

    A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

  5. Network Coordinator Report

    NASA Technical Reports Server (NTRS)

    Himwich, Ed; Strand, Richard

    2013-01-01

    This report includes an assessment of the network performance in terms of lost observing time for the 2012 calendar year. Overall, the observing time loss was about 12.3%, which is in-line with previous years. A table of relative incidence of problems with various subsystems is presented. The most significant identified causes of loss were electronics rack problems (accounting for about 21.8% of losses), antenna reliability (18.1%), RFI (11.8%), and receiver problems (11.7%). About 14.2% of the losses occurred for unknown reasons. New antennas are under development in the USA, Germany, and Spain. There are plans for new telescopes in Norway and Sweden. Other activities of the Network Coordinator are summarized.

  6. Beijing restaurant network

    NASA Astrophysics Data System (ADS)

    Fu, Chun-Hua; Zhnag, Pei-Fang; Wang, Yong-Li; Shi, Jian-Jun; Feng, Ai-Xia; He, Da-Ren

    2008-03-01

    We have empirically studied the restaurants in Beijing and suggested a network description on the system. We define the restaurants as nodes and connect a link between two nodes if the two restaurants sell a common dish. The edge represents the sale competition relationship. In order to describe the competition, we define a node weight, which is the mark given by consumers on an evaluation network (http://www.dianping.com), to the restaurant in cooking the dish. 3338 nodes and 688 dishes have been investigated. We find that both the total node weight, which is defined as the sum of the node weight in all the dishes, and the so-called dish weight, which is defined as the sum of the node weight in one dish, show a rather nice power law distribution.

  7. Strongly anisotropic polymer networks

    NASA Astrophysics Data System (ADS)

    Ulrich, Stephan; Zippelius, Annette; Benetatos, Panayotis

    2011-03-01

    We investigate a network of worm-like chains, which are strongly oriented along a preferred direction due to an external field, boundary conditions, or a nematic environment. We discuss the effects of random permanent cross-links, whose density may follow an arbitrary distribution along the alignment direction. We show that the tilt modulus is unaffected by cross-links. As the cross-link density is increased beyond the gel point, the network develops a stiffness to in-plane shear deformations. Results for the shear elasticity and fluctuations of the polymer chains are presented. The case of cross-linking the chains on one end only is highlighted, it constitutes a simple model for polymer brushes. Moreover force-extension curves are presented for a toy model that consists of two cross-linked chains.

  8. Tensor Network Renormalization.

    PubMed

    Evenbly, G; Vidal, G

    2015-10-30

    We introduce a coarse-graining transformation for tensor networks that can be applied to study both the partition function of a classical statistical system and the Euclidean path integral of a quantum many-body system. The scheme is based upon the insertion of optimized unitary and isometric tensors (disentanglers and isometries) into the tensor network and has, as its key feature, the ability to remove short-range entanglement or correlations at each coarse-graining step. Removal of short-range entanglement results in scale invariance being explicitly recovered at criticality. In this way we obtain a proper renormalization group flow (in the space of tensors), one that in particular (i) is computationally sustainable, even for critical systems, and (ii) has the correct structure of fixed points, both at criticality and away from it. We demonstrate the proposed approach in the context of the 2D classical Ising model.

  9. Noise in coevolving networks

    NASA Astrophysics Data System (ADS)

    Diakonova, Marina; Eguíluz, Víctor M.; San Miguel, Maxi

    2015-09-01

    Coupling dynamics of the states of the nodes of a network to the dynamics of the network topology leads to generic absorbing and fragmentation transitions. The coevolving voter model is a typical system that exhibits such transitions at some critical rewiring. We study the robustness of these transitions under two distinct ways of introducing noise. Noise affecting all the nodes destroys the absorbing-fragmentation transition, giving rise in finite-size systems to two regimes: bimodal magnetization and dynamic fragmentation. Noise targeting a fraction of nodes preserves the transitions but introduces shattered fragmentation with its characteristic fraction of isolated nodes and one or two giant components. Both the lack of absorbing state for homogeneous noise and the shift in the absorbing transition to higher rewiring for targeted noise are supported by analytical approximations.

  10. Symbolic function network.

    PubMed

    Eskander, George S; Atiya, Amir F

    2009-05-01

    In this paper a model called symbolic function network (SFN) is introduced; that is based on using elementary functions (for example powers, the exponential function, and the logarithm) as building blocks. The proposed method uses these building blocks to synthesize a function that best fits the training data in a regression framework. The resulting network is of the form of a tree, where adding nodes horizontally means having a summation of elementary functions and adding nodes vertically means concatenating elementary functions. Several new algorithms were proposed to construct the tree based on the concepts of forward greedy search and backward greedy search, together with applying the steepest descent concept. The method is tested on a number of examples and it is shown to exhibit good performance.

  11. Theorizing Network-Centric Activity in Education

    ERIC Educational Resources Information Center

    HaLevi, Andrew

    2011-01-01

    Networks and network-centric activity are increasingly prevalent in schools and school districts. In addition to ubiquitous social network tools like Facebook and Twitter, educational leaders deal with a wide variety of network organizational forms that include professional development, advocacy, informational networks and network-centric reforms.…

  12. Network Information Management Subsystem

    NASA Technical Reports Server (NTRS)

    Chatburn, C. C.

    1985-01-01

    The Deep Space Network is implementing a distributed data base management system in which the data are shared among several applications and the host machines are not totally dedicated to a particular application. Since the data and resources are to be shared, the equipment must be operated carefully so that the resources are shared equitably. The current status of the project is discussed and policies, roles, and guidelines are recommended for the organizations involved in the project.

  13. Neural networks for triggering

    SciTech Connect

    Denby, B. ); Campbell, M. ); Bedeschi, F. ); Chriss, N.; Bowers, C. ); Nesti, F. )

    1990-01-01

    Two types of neural network beauty trigger architectures, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment. The efficiencies for B's and rejection of background obtained are encouraging. If hardware tests are successful, the electron identification architecture will be tested in the 1991 run of CDF. 10 refs., 5 figs., 1 tab.

  14. The International Lunar Network

    NASA Technical Reports Server (NTRS)

    Cohen, Barbara A.

    2008-01-01

    A new lunar science flight projects line has been introduced within NASA s Science Mission Directorate's (SMDs) proposed 2009 budget, including two new robotic missions designed to accomplish key scientific objectives and, when possible, provide results useful to the Exploration Systems Mission Directorate (ESMD) and the Space Operations Mission Directorate (SOMD) as those organizations grapple with the challenges of returning humans to the Moon. The first mission in this line will be the Lunar Reconnaissance Orbiter, an ESMD mission that will acquire key information for human return to the moon activities, which will transition after one year of operations to the SMD Lunar Science Program for a 2-year nominal science mission. The second mission, the Lunar Atmosphere and Dust Environment Explorer (LADEE) will be launch in 2011 along with the GRAIL Discovery mission to the moon. The third is delivery of two landed payloads as part of the International Lunar Network (ILN). This flight projects line provides a robust robotic lunar science program for the next 8 years and beyond, complements SMD s initiatives to build a robust lunar science community through R&A lines, and increases international participation in NASA s robotic exploration plans. The International Lunar Network is envisioned as a global lunar geophysical network, which fulfills many of the stated recommendations of the recent National Research Council report on The Scientific Context for Exploration of the Moon [2], but is difficult for any single space agency to accomplish on its own. The ILN would provide the necessary global coverage by involving US and international landed missions as individual nodes working together. Ultimately, this network could comprise 8-10 or more nodes operating simultaneously, while minimizing the required contribution from each space agency. Indian, Russian, Japanese, and British landed missions are currently being formulated and SMD is actively seeking partnership with

  15. Understanding deep convolutional networks.

    PubMed

    Mallat, Stéphane

    2016-04-13

    Deep convolutional networks provide state-of-the-art classifications and regressions results over many high-dimensional problems. We review their architecture, which scatters data with a cascade of linear filter weights and nonlinearities. A mathematical framework is introduced to analyse their properties. Computations of invariants involve multiscale contractions with wavelets, the linearization of hierarchical symmetries and sparse separations. Applications are discussed. PMID:26953183

  16. [Network structures in biological systems].

    PubMed

    Oleskin, A V

    2013-01-01

    Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

  17. Measuring distances between complex networks

    NASA Astrophysics Data System (ADS)

    Andrade, Roberto F. S.; Miranda, José G. V.; Pinho, Suani T. R.; Lobão, Thierry Petit

    2008-08-01

    A previously introduced concept of higher order neighborhoods in complex networks, [R.F.S. Andrade, J.G.V. Miranda, T.P. Lobão, Phys. Rev. E 73 (2006) 046101] is used to define a distance between networks with the same number of nodes. With such measure, expressed in terms of the matrix elements of the neighborhood matrices of each network, it is possible to compare, in a quantitative way, how far apart in the space of neighborhood matrices two networks are. The distance between these matrices depends on both the network topologies and the adopted node numberings. While the numbering of one network is fixed, a Monte Carlo algorithm is used to find the best numbering of the other network, in the sense that it minimizes the distance between the matrices. The minimal value found for the distance reflects differences in the neighborhood structures of the two networks that arise only from distinct topologies. This procedure ends up by providing a projection of the first network on the pattern of the second one. Examples are worked out allowing for a quantitative comparison for distances among distinct networks, as well as among distinct realizations of random networks.

  18. Dynamics near a heteroclinic network

    NASA Astrophysics Data System (ADS)

    Aguiar, Manuela A. D.; Castro, Sofia B. S. D.; Labouriau, Isabel S.

    2005-01-01

    We study the dynamical behaviour of a smooth vector field on a three-manifold near a heteroclinic network. Under some generic assumptions on the network, we prove that every path on the network is followed by a neighbouring trajectory of the vector field—there is switching on the network. We also show that near the network there is an infinite number of hyperbolic suspended horseshoes. This leads to the existence of a horseshoe of suspended horseshoes with the shape of the network. Our results are motivated by an example constructed by Field (1996 Lectures on Bifurcations, Dynamics, and Symmetry (Pitman Research Notes in Mathematics Series vol 356) (Harlow: Longman)), where we have observed, numerically, the existence of such a network.

  19. Effective Augmentation of Complex Networks

    PubMed Central

    Wang, Jinjian; Yu, Xinghuo; Stone, Lewi

    2016-01-01

    Networks science plays an enormous role in many aspects of modern society from distributing electrical power across nations to spreading information and social networking amongst global populations. While modern networks constantly change in size, few studies have sought methods for the difficult task of optimising this growth. Here we study theoretical requirements for augmenting networks by adding source or sink nodes, without requiring additional driver-nodes to accommodate the change i.e., conserving structural controllability. Our “effective augmentation” algorithm takes advantage of clusters intrinsic to the network topology, and permits rapidly and efficient augmentation of a large number of nodes in one time-step. “Effective augmentation” is shown to work successfully on a wide range of model and real networks. The method has numerous applications (e.g. study of biological, social, power and technological networks) and potentially of significant practical and economic value. PMID:27165120

  20. Effective Augmentation of Complex Networks

    NASA Astrophysics Data System (ADS)

    Wang, Jinjian; Yu, Xinghuo; Stone, Lewi

    2016-05-01

    Networks science plays an enormous role in many aspects of modern society from distributing electrical power across nations to spreading information and social networking amongst global populations. While modern networks constantly change in size, few studies have sought methods for the difficult task of optimising this growth. Here we study theoretical requirements for augmenting networks by adding source or sink nodes, without requiring additional driver-nodes to accommodate the change i.e., conserving structural controllability. Our “effective augmentation” algorithm takes advantage of clusters intrinsic to the network topology, and permits rapidly and efficient augmentation of a large number of nodes in one time-step. “Effective augmentation” is shown to work successfully on a wide range of model and real networks. The method has numerous applications (e.g. study of biological, social, power and technological networks) and potentially of significant practical and economic value.

  1. Controllability of structural brain networks

    PubMed Central

    Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K.; Yu, Alfred B.; Kahn, Ari E.; Medaglia, John D.; Vettel, Jean M.; Miller, Michael B.; Grafton, Scott T.; Bassett, Danielle S.

    2015-01-01

    Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function. PMID:26423222

  2. Pattern formation in multiplex networks

    PubMed Central

    Kouvaris, Nikos E.; Hata, Shigefumi; Guilera, Albert Díaz-

    2015-01-01

    The advances in understanding complex networks have generated increasing interest in dynamical processes occurring on them. Pattern formation in activator-inhibitor systems has been studied in networks, revealing differences from the classical continuous media. Here we study pattern formation in a new framework, namely multiplex networks. These are systems where activator and inhibitor species occupy separate nodes in different layers. Species react across layers but diffuse only within their own layer of distinct network topology. This multiplicity generates heterogeneous patterns with significant differences from those observed in single-layer networks. Remarkably, diffusion-induced instability can occur even if the two species have the same mobility rates; condition which can never destabilize single-layer networks. The instability condition is revealed using perturbation theory and expressed by a combination of degrees in the different layers. Our theory demonstrates that the existence of such topology-driven instabilities is generic in multiplex networks, providing a new mechanism of pattern formation. PMID:26042606

  3. Observability of Neuronal Network Motifs

    PubMed Central

    Whalen, Andrew J.; Brennan, Sean N.; Sauer, Timothy D.; Schiff, Steven J.

    2014-01-01

    We quantify observability in small (3 node) neuronal networks as a function of 1) the connection topology and symmetry, 2) the measured nodes, and 3) the nodal dynamics (linear and nonlinear). We find that typical observability metrics for 3 neuron motifs range over several orders of magnitude, depending upon topology, and for motifs containing symmetry the network observability decreases when observing from particularly confounded nodes. Nonlinearities in the nodal equations generally decrease the average network observability and full network information becomes available only in limited regions of the system phase space. Our findings demonstrate that such networks are partially observable, and suggest their potential efficacy in reconstructing network dynamics from limited measurement data. How well such strategies can be used to reconstruct and control network dynamics in experimental settings is a subject for future experimental work. PMID:25909092

  4. Renormalization flows in complex networks.

    PubMed

    Radicchi, Filippo; Barrat, Alain; Fortunato, Santo; Ramasco, José J

    2009-02-01

    Complex networks have acquired a great popularity in recent years, since the graph representation of many natural, social, and technological systems is often very helpful to characterize and model their phenomenology. Additionally, the mathematical tools of statistical physics have proven to be particularly suitable for studying and understanding complex networks. Nevertheless, an important obstacle to this theoretical approach is still represented by the difficulties to draw parallelisms between network science and more traditional aspects of statistical physics. In this paper, we explore the relation between complex networks and a well known topic of statistical physics: renormalization. A general method to analyze renormalization flows of complex networks is introduced. The method can be applied to study any suitable renormalization transformation. Finite-size scaling can be performed on computer-generated networks in order to classify them in universality classes. We also present applications of the method on real networks.

  5. Electroelasticity of polymer networks

    NASA Astrophysics Data System (ADS)

    Cohen, Noy; Dayal, Kaushik; deBotton, Gal

    2016-07-01

    A multiscale analysis of the electromechanical coupling in elastic dielectrics is conducted, starting from the discrete monomer level through the polymer chain and up to the macroscopic level. Three models for the local relations between the molecular dipoles and the electric field that can fit a variety of dipolar monomers are considered. The entropy of the network is accounted for within the framework of statistical mechanics with appropriate kinematic and energetic constraints. At the macroscopic level closed-form explicit expressions for the behaviors of amorphous dielectrics and isotropic polymer networks are determined, none of which admits the commonly assumed linear relation between the polarization and the electric field. The analysis reveals the dependence of the macroscopic coupled behavior on three primary microscopic parameters: the model assumed for the local behavior, the intensity of the local dipole, and the length of the chain. We show how these parameters influence the directional distributions of the monomers and the hence the resulting overall response of the network. In particular, the dependences of the polarization and the polarization induced stress on the deformation of the dielectric are illustrated. More surprisingly, we also reveal a dependence of the stress on the electric field which stems from the kinematic constraint imposed on the chains.

  6. The SIM Time Network.

    PubMed

    Lombardi, Michael A; Novick, Andrew N; Lopez R, J Mauricio; Jimenez, Francisco; de Carlos Lopez, Eduardo; Boulanger, Jean-Simon; Pelletier, Raymond; de Carvalho, Ricardo J; Solis, Raul; Sanchez, Harold; Quevedo, Carlos Andres; Pascoe, Gregory; Perez, Daniel; Bances, Eduardo; Trigo, Leonardo; Masi, Victor; Postigo, Henry; Questelles, Anthony; Gittens, Anselm

    2011-01-01

    The Sistema Interamericano de Metrologia (SIM) is a regional metrology organization (RMO) whose members are the national metrology institutes (NMIs) located in the 34 nations of the Organization of American States (OAS). The SIM/OAS region extends throughout North, Central, and South America and the Caribbean Islands. About half of the SIM NMIs maintain national standards of time and frequency and must participate in international comparisons in order to establish metrological traceability to the International System (SI) of units. The SIM time network (SIMTN) was developed as a practical, cost effective, and technically sound way to automate these comparisons. The SIMTN continuously compares the time standards of SIM NMIs and produces measurement results in near real-time by utilizing the Internet and the Global Positioning System (GPS). Fifteen SIM NMIs have joined the network as of December 2010. This paper provides a brief overview of SIM and a technical description of the SIMTN. It presents international comparison results and examines the measurement uncertainties. It also discusses the metrological benefits that the network provides to its participants. PMID:26989584

  7. The SIM Time Network

    PubMed Central

    Lombardi, Michael A.; Novick, Andrew N.; Lopez R, J. Mauricio; Jimenez, Francisco; de Carlos Lopez, Eduardo; Boulanger, Jean-Simon; Pelletier, Raymond; de Carvalho, Ricardo J.; Solis, Raul; Sanchez, Harold; Quevedo, Carlos Andres; Pascoe, Gregory; Perez, Daniel; Bances, Eduardo; Trigo, Leonardo; Masi, Victor; Postigo, Henry; Questelles, Anthony; Gittens, Anselm

    2011-01-01

    The Sistema Interamericano de Metrologia (SIM) is a regional metrology organization (RMO) whose members are the national metrology institutes (NMIs) located in the 34 nations of the Organization of American States (OAS). The SIM/OAS region extends throughout North, Central, and South America and the Caribbean Islands. About half of the SIM NMIs maintain national standards of time and frequency and must participate in international comparisons in order to establish metrological traceability to the International System (SI) of units. The SIM time network (SIMTN) was developed as a practical, cost effective, and technically sound way to automate these comparisons. The SIMTN continuously compares the time standards of SIM NMIs and produces measurement results in near real-time by utilizing the Internet and the Global Positioning System (GPS). Fifteen SIM NMIs have joined the network as of December 2010. This paper provides a brief overview of SIM and a technical description of the SIMTN. It presents international comparison results and examines the measurement uncertainties. It also discusses the metrological benefits that the network provides to its participants. PMID:26989584

  8. The SIM Time Network.

    PubMed

    Lombardi, Michael A; Novick, Andrew N; Lopez R, J Mauricio; Jimenez, Francisco; de Carlos Lopez, Eduardo; Boulanger, Jean-Simon; Pelletier, Raymond; de Carvalho, Ricardo J; Solis, Raul; Sanchez, Harold; Quevedo, Carlos Andres; Pascoe, Gregory; Perez, Daniel; Bances, Eduardo; Trigo, Leonardo; Masi, Victor; Postigo, Henry; Questelles, Anthony; Gittens, Anselm

    2011-01-01

    The Sistema Interamericano de Metrologia (SIM) is a regional metrology organization (RMO) whose members are the national metrology institutes (NMIs) located in the 34 nations of the Organization of American States (OAS). The SIM/OAS region extends throughout North, Central, and South America and the Caribbean Islands. About half of the SIM NMIs maintain national standards of time and frequency and must participate in international comparisons in order to establish metrological traceability to the International System (SI) of units. The SIM time network (SIMTN) was developed as a practical, cost effective, and technically sound way to automate these comparisons. The SIMTN continuously compares the time standards of SIM NMIs and produces measurement results in near real-time by utilizing the Internet and the Global Positioning System (GPS). Fifteen SIM NMIs have joined the network as of December 2010. This paper provides a brief overview of SIM and a technical description of the SIMTN. It presents international comparison results and examines the measurement uncertainties. It also discusses the metrological benefits that the network provides to its participants.

  9. Insecurity of Wireless Networks

    SciTech Connect

    Sheldon, Frederick T; Weber, John Mark; Yoo, Seong-Moo; Pan, W. David

    2012-01-01

    Wireless is a powerful core technology enabling our global digital infrastructure. Wi-Fi networks are susceptible to attacks on Wired Equivalency Privacy, Wi-Fi Protected Access (WPA), and WPA2. These attack signatures can be profiled into a system that defends against such attacks on the basis of their inherent characteristics. Wi-Fi is the standard protocol for wireless networks used extensively in US critical infrastructures. Since the Wired Equivalency Privacy (WEP) security protocol was broken, the Wi-Fi Protected Access (WPA) protocol has been considered the secure alternative compatible with hardware developed for WEP. However, in November 2008, researchers developed an attack on WPA, allowing forgery of Address Resolution Protocol (ARP) packets. Subsequent enhancements have enabled ARP poisoning, cryptosystem denial of service, and man-in-the-middle attacks. Open source systems and methods (OSSM) have long been used to secure networks against such attacks. This article reviews OSSMs and the results of experimental attacks on WPA. These experiments re-created current attacks in a laboratory setting, recording both wired and wireless traffic. The article discusses methods of intrusion detection and prevention in the context of cyber physical protection of critical Internet infrastructure. The basis for this research is a specialized (and undoubtedly incomplete) taxonomy of Wi-Fi attacks and their adaptations to existing countermeasures and protocol revisions. Ultimately, this article aims to provide a clearer picture of how and why wireless protection protocols and encryption must achieve a more scientific basis for detecting and preventing such attacks.

  10. Bicriteria network design problems

    SciTech Connect

    Marathe, M.V.; Ravi, R.; Sundaram, R.; Ravi, S.S.; Rosenkrantz, D.J.; Hunt, H.B. III

    1997-11-20

    The authors study a general class of bicriteria network design problems. A generic problem in this class is as follows: Given an undirected graph and two minimization objectives (under different cost functions), with a budget specified on the first, find a subgraph from a given subgraph class that minimizes the second objective subject to the budget on the first. They consider three different criteria -- the total edge cost, the diameter and the maximum degree of the network. Here, they present the first polynomial-time approximation algorithms for a large class of bicriteria network design problems for the above mentioned criteria. The following general types of results are presented. First, they develop a framework for bicriteria problems and their approximations. Second, when the two criteria are the same they present a black box parametric search technique. This black box takes in as input an (approximation) algorithm for the criterion situation and generates an approximation algorithm for the bicriteria case with only a constant factor loss in the performance guarantee. Third, when the two criteria are the diameter and the total edge costs they use a cluster based approach to devise approximation algorithms. The solutions violate both the criteria by a logarithmic factor. Finally, for the class of treewidth-bounded graphs, they provide pseudopolynomial-time algorithms for a number of bicriteria problems using dynamic programming. The authors show how these pseudopolynomial-time algorithms can be converted to fully polynomial-time approximation schemes using a scaling technique.

  11. Networked differential GPS system

    NASA Technical Reports Server (NTRS)

    Mueller, K. Tysen (Inventor); Loomis, Peter V. W. (Inventor); Kalafus, Rudolph M. (Inventor); Sheynblat, Leonid (Inventor)

    1994-01-01

    An embodiment of the present invention relates to a worldwide network of differential GPS reference stations (NDGPS) that continually track the entire GPS satellite constellation and provide interpolations of reference station corrections tailored for particular user locations between the reference stations Each reference station takes real-time ionospheric measurements with codeless cross-correlating dual-frequency carrier GPS receivers and computes real-time orbit ephemerides independently. An absolute pseudorange correction (PRC) is defined for each satellite as a function of a particular user's location. A map of the function is constructed, with iso-PRC contours. The network measures the PRCs at a few points, so-called reference stations and constructs an iso-PRC map for each satellite. Corrections are interpolated for each user's site on a subscription basis. The data bandwidths are kept to a minimum by transmitting information that cannot be obtained directly by the user and by updating information by classes and according to how quickly each class of data goes stale given the realities of the GPS system. Sub-decimeter-level kinematic accuracy over a given area is accomplished by establishing a mini-fiducial network.

  12. [The Pasteur network].

    PubMed

    Durosoir, J L

    1995-01-14

    Inspired by Louis Pasteur, the international network of Pasteur Institutes forms an original body of research institutes whose vitality has grown steadily since Albert Calmette first created the Saigon Institute in 1891. The dynamic development of the 23 Pasteur Institutes currently implanted throughout the world was made possible by three driving forces. First of all, Pasteur's own teaching--"Advance only what you can prove experimentally"--the founding principle of modern research. Secondly, the international missions headed by leading collaborators including Thuillier who worked on cholera in Egypt, Loir who initiated antirabies research in Australia and Russia, Calmette in Saigon, and others in Rio de Janeiro, Dalat, Tunis and Alger. And finally Pasteur's own personal renown. Today the Pasteur Institutes fill a vital need in their respective countries developing and producing vaccines locally, serving often as the only competent medical laboratory in developing countries and helping improve standards of hygiene adapted to local situations. Fundamental research has always been at the heart of Pasteur Institutes, coupled with essential training for technicians and researchers alike. Despite political incertitudes and turmoil, the international network of Pasteur Institutes has held its place as the leader in scientific progress for over a century, setting the place for modern international research. The Cantacuzene Institute in Bucarest and the Pasteur Institute in Saint-Petersburg which joined the network in 1991 and 1993 are the most recent examples of the fundamental principle of exchange and cooperation so important for further development.

  13. Wideband, mobile networking technologies

    NASA Astrophysics Data System (ADS)

    Hyer, Kevin L.; Bowen, Douglas G.; Pulsipher, Dennis C.

    2005-05-01

    Ubiquitous communications will be the next era in the evolving communications revolution. From the human perspective, access to information will be instantaneous and provide a revolution in services available to both the consumer and the warfighter. Services will be from the mundane - anytime, anywhere access to any movie ever made - to the vital - reliable and immediate access to the analyzed real-time video from the multi-spectral sensors scanning for snipers in the next block. In the former example, the services rely on a fixed infrastructure of networking devices housed in controlled environments and coupled to fixed terrestrial fiber backbones - in the latter, the services are derived from an agile and highly mobile ad-hoc backbone established in a matter of minutes by size, weight, and power-constrained platforms. This network must mitigate significant changes in the transmission media caused by millisecond-scale atmospheric temperature variations, the deployment of smoke, or the drifting of a cloud. It must mitigate against structural obscurations, jet wash, or incapacitation of a node. To maintain vital connectivity, the mobile backbone must be predictive and self-healing on both near-real-time and real-time time scales. The nodes of this network must be reconfigurable to mitigate intentional and environmental jammers, block attackers, and alleviate interoperability concerns caused by changing standards. The nodes must support multi-access of disparate waveform and protocols.

  14. Network configuration management : paving the way to network agility.

    SciTech Connect

    Maestas, Joseph H.

    2007-08-01

    Sandia networks consist of nearly nine hundred routers and switches and nearly one million lines of command code, and each line ideally contributes to the capabilities of the network to convey information from one location to another. Sandia's Cyber Infrastructure Development and Deployment organizations recognize that it is therefore essential to standardize network configurations and enforce conformance to industry best business practices and documented internal configuration standards to provide a network that is agile, adaptable, and highly available. This is especially important in times of constrained budgets as members of the workforce are called upon to improve efficiency, effectiveness, and customer focus. Best business practices recommend using the standardized configurations in the enforcement process so that when root cause analysis results in recommended configuration changes, subsequent configuration auditing will improve compliance to the standard. Ultimately, this minimizes mean time to repair, maintains the network security posture, improves network availability, and enables efficient transition to new technologies. Network standardization brings improved network agility, which in turn enables enterprise agility, because the network touches all facets of corporate business. Improved network agility improves the business enterprise as a whole.

  15. Network structure exploration in networks with node attributes

    NASA Astrophysics Data System (ADS)

    Chen, Yi; Wang, Xiaolong; Bu, Junzhao; Tang, Buzhou; Xiang, Xin

    2016-05-01

    Complex networks provide a powerful way to represent complex systems and have been widely studied during the past several years. One of the most important tasks of network analysis is to detect structures (also called structural regularities) embedded in networks by determining group number and group partition. Most of network structure exploration models only consider network links. However, in real world networks, nodes may have attributes that are useful for network structure exploration. In this paper, we propose a novel Bayesian nonparametric (BNP) model to explore structural regularities in networks with node attributes, called Bayesian nonparametric attribute (BNPA) model. This model does not only take full advantage of both links between nodes and node attributes for group partition via shared hidden variables, but also determine group number automatically via the Bayesian nonparametric theory. Experiments conducted on a number of real and synthetic networks show that our BNPA model is able to automatically explore structural regularities in networks with node attributes and is competitive with other state-of-the-art models.

  16. Psychology and social networks: a dynamic network theory perspective.

    PubMed

    Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

    2014-04-01

    Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

  17. Network Monitor and Control of Disruption-Tolerant Networks

    NASA Technical Reports Server (NTRS)

    Torgerson, J. Leigh

    2014-01-01

    For nearly a decade, NASA and many researchers in the international community have been developing Internet-like protocols that allow for automated network operations in networks where the individual links between nodes are only sporadically connected. A family of Disruption-Tolerant Networking (DTN) protocols has been developed, and many are reaching CCSDS Blue Book status. A NASA version of DTN known as the Interplanetary Overlay Network (ION) has been flight-tested on the EPOXI spacecraft and ION is currently being tested on the International Space Station. Experience has shown that in order for a DTN service-provider to set up a large scale multi-node network, a number of network monitor and control technologies need to be fielded as well as the basic DTN protocols. The NASA DTN program is developing a standardized means of querying a DTN node to ascertain its operational status, known as the DTN Management Protocol (DTNMP), and the program has developed some prototypes of DTNMP software. While DTNMP is a necessary component, it is not sufficient to accomplish Network Monitor and Control of a DTN network. JPL is developing a suite of tools that provide for network visualization, performance monitoring and ION node control software. This suite of network monitor and control tools complements the GSFC and APL-developed DTN MP software, and the combined package can form the basis for flight operations using DTN.

  18. Airport Surface Network Architecture Definition

    NASA Technical Reports Server (NTRS)

    Nguyen, Thanh C.; Eddy, Wesley M.; Bretmersky, Steven C.; Lawas-Grodek, Fran; Ellis, Brenda L.

    2006-01-01

    Currently, airport surface communications are fragmented across multiple types of systems. These communication systems for airport operations at most airports today are based dedicated and separate architectures that cannot support system-wide interoperability and information sharing. The requirements placed upon the Communications, Navigation, and Surveillance (CNS) systems in airports are rapidly growing and integration is urgently needed if the future vision of the National Airspace System (NAS) and the Next Generation Air Transportation System (NGATS) 2025 concept are to be realized. To address this and other problems such as airport surface congestion, the Space Based Technologies Project s Surface ICNS Network Architecture team at NASA Glenn Research Center has assessed airport surface communications requirements, analyzed existing and future surface applications, and defined a set of architecture functions that will help design a scalable, reliable and flexible surface network architecture to meet the current and future needs of airport operations. This paper describes the systems approach or methodology to networking that was employed to assess airport surface communications requirements, analyze applications, and to define the surface network architecture functions as the building blocks or components of the network. The systems approach used for defining these functions is relatively new to networking. It is viewing the surface network, along with its environment (everything that the surface network interacts with or impacts), as a system. Associated with this system are sets of services that are offered by the network to the rest of the system. Therefore, the surface network is considered as part of the larger system (such as the NAS), with interactions and dependencies between the surface network and its users, applications, and devices. The surface network architecture includes components such as addressing/routing, network management, network

  19. Breakdown of interdependent directed networks.

    PubMed

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

    2016-02-01

    Increasing evidence shows that real-world systems interact with one another via dependency connectivities. Failing connectivities are the mechanism behind the breakdown of interacting complex systems, e.g., blackouts caused by the interdependence of power grids and communication networks. Previous research analyzing the robustness of interdependent networks has been limited to undirected networks. However, most real-world networks are directed, their in-degrees and out-degrees may be correlated, and they are often coupled to one another as interdependent directed networks. To understand the breakdown and robustness of interdependent directed networks, we develop a theoretical framework based on generating functions and percolation theory. We find that for interdependent Erdős-Rényi networks the directionality within each network increases their vulnerability and exhibits hybrid phase transitions. We also find that the percolation behavior of interdependent directed scale-free networks with and without degree correlations is so complex that two criteria are needed to quantify and compare their robustness: the percolation threshold and the integrated size of the giant component during an entire attack process. Interestingly, we find that the in-degree and out-degree correlations in each network layer increase the robustness of interdependent degree heterogeneous networks that most real networks are, but decrease the robustness of interdependent networks with homogeneous degree distribution and with strong coupling strengths. Moreover, by applying our theoretical analysis to real interdependent international trade networks, we find that the robustness of these real-world systems increases with the in-degree and out-degree correlations, confirming our theoretical analysis. PMID:26787907

  20. Attack Vulnerability of Network Controllability

    PubMed Central

    2016-01-01

    Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model networks as well as the real-world networks subject to attacks on nodes and edges. The attack strategies are selected based on degree and betweenness centralities calculated for either the initial network or the current network during the removal, among which random failure is as a comparison. It is found that the node-based strategies are often more harmful to the network controllability than the edge-based ones, and so are the recalculated strategies than their counterparts. The Barabási-Albert scale-free model, which has a highly biased structure, proves to be the most vulnerable of the tested model networks. In contrast, the Erdős-Rényi random model, which lacks structural bias, exhibits much better robustness to both node-based and edge-based attacks. We also survey the control robustness of 25 real-world networks, and the numerical results show that most real networks are control robust to random node failures, which has not been observed in the model networks. And the recalculated betweenness-based strategy is the most efficient way to harm the controllability of real-world networks. Besides, we find that the edge degree is not a good quantity to measure the importance of an edge in terms of network controllability. PMID:27588941

  1. Attack Vulnerability of Network Controllability.

    PubMed

    Lu, Zhe-Ming; Li, Xin-Feng

    2016-01-01

    Controllability of complex networks has attracted much attention, and understanding the robustness of network controllability against potential attacks and failures is of practical significance. In this paper, we systematically investigate the attack vulnerability of network controllability for the canonical model networks as well as the real-world networks subject to attacks on nodes and edges. The attack strategies are selected based on degree and betweenness centralities calculated for either the initial network or the current network during the removal, among which random failure is as a comparison. It is found that the node-based strategies are often more harmful to the network controllability than the edge-based ones, and so are the recalculated strategies than their counterparts. The Barabási-Albert scale-free model, which has a highly biased structure, proves to be the most vulnerable of the tested model networks. In contrast, the Erdős-Rényi random model, which lacks structural bias, exhibits much better robustness to both node-based and edge-based attacks. We also survey the control robustness of 25 real-world networks, and the numerical results show that most real networks are control robust to random node failures, which has not been observed in the model networks. And the recalculated betweenness-based strategy is the most efficient way to harm the controllability of real-world networks. Besides, we find that the edge degree is not a good quantity to measure the importance of an edge in terms of network controllability. PMID:27588941

  2. Breakdown of interdependent directed networks.

    PubMed

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

    2016-02-01

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

  3. Deploying temporary networks for upscaling of sparse network stations

    NASA Astrophysics Data System (ADS)

    Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

    2016-10-01

    Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

  4. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    PubMed

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan

    2016-08-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  5. High fidelity wireless network evaluation for heterogeneous cognitive radio networks

    NASA Astrophysics Data System (ADS)

    Ding, Lei; Sagduyu, Yalin; Yackoski, Justin; Azimi-Sadjadi, Babak; Li, Jason; Levy, Renato; Melodia, Tammaso

    2012-06-01

    We present a high fidelity cognitive radio (CR) network emulation platform for wireless system tests, measure- ments, and validation. This versatile platform provides the configurable functionalities to control and repeat realistic physical channel effects in integrated space, air, and ground networks. We combine the advantages of scalable simulation environment with reliable hardware performance for high fidelity and repeatable evaluation of heterogeneous CR networks. This approach extends CR design only at device (software-defined-radio) or lower-level protocol (dynamic spectrum access) level to end-to-end cognitive networking, and facilitates low-cost deployment, development, and experimentation of new wireless network protocols and applications on frequency- agile programmable radios. Going beyond the channel emulator paradigm for point-to-point communications, we can support simultaneous transmissions by network-level emulation that allows realistic physical-layer inter- actions between diverse user classes, including secondary users, primary users, and adversarial jammers in CR networks. In particular, we can replay field tests in a lab environment with real radios perceiving and learning the dynamic environment thereby adapting for end-to-end goals over distributed spectrum coordination channels that replace the common control channel as a single point of failure. CR networks offer several dimensions of tunable actions including channel, power, rate, and route selection. The proposed network evaluation platform is fully programmable and can reliably evaluate the necessary cross-layer design solutions with configurable op- timization space by leveraging the hardware experiments to represent the realistic effects of physical channel, topology, mobility, and jamming on spectrum agility, situational awareness, and network resiliency. We also provide the flexibility to scale up the test environment by introducing virtual radios and establishing seamless signal

  6. The NASA Fireball Network

    NASA Technical Reports Server (NTRS)

    Cooke, William J.

    2013-01-01

    In the summer of 2008, the NASA Meteoroid Environments Office (MEO) began to establish a video fireball network, based on the following objectives: (1) determine the speed distribution of cm size meteoroids, (2) determine the major sources of cm size meteoroids (showers/sporadic sources), (3) characterize meteor showers (numbers, magnitudes, trajectories, orbits), (4) determine the size at which showers dominate the meteor flux, (5) discriminate between re-entering space debris and meteors, and 6) locate meteorite falls. In order to achieve the above with the limited resources available to the MEO, it was necessary that the network function almost fully autonomously, with very little required from humans in the areas of upkeep or analysis. With this in mind, the camera design and, most importantly, the ASGARD meteor detection software were adopted from the University of Western Ontario's Southern Ontario Meteor Network (SOMN), as NASA has a cooperative agreement with Western's Meteor Physics Group. 15 cameras have been built, and the network now consists of 8 operational cameras, with at least 4 more slated for deployment in calendar year 2013. The goal is to have 15 systems, distributed in two or more groups east of automatic analysis; every morning, this server also automatically generates an email and a web page (http://fireballs.ndc.nasa.gov) containing an automated analysis of the previous night's events. This analysis provides the following for each meteor: UTC date and time, speed, start and end locations (longitude, latitude, altitude), radiant, shower identification, light curve (meteor absolute magnitude as a function of time), photometric mass, orbital elements, and Tisserand parameter. Radiant/orbital plots and various histograms (number versus speed, time, etc) are also produced. After more than four years of operation, over 5,000 multi-station fireballs have been observed, 3 of which potentially dropped meteorites. A database containing data on all

  7. Constellations and Networks

    NASA Astrophysics Data System (ADS)

    Greenwald, R. A.

    2013-12-01

    Constellations and Networks Prior to the late 1970's, most satellites probing the Earth's upper atmosphere, ionosphere, and magnetosphere and most ground-based experiments measuring the upper atmosphere and ionosphere provided uncoordinated, localized measurements of different regions of the Earth's near-space environment with the objective of determining their basic properties. These measurements showed that the magnetosphere was divided into a number of regions, each containing plasmas with different properties and varying concentrations of energetic particles. By the mid 1970's, this discovery phase of the various regions of the Earth's magnetosphere had essentially been completed. The next step was to understand how the various plasma domains of the magnetosphere and ionosphere were coupled into a complex plasma system and how energy flowed through this system from the solar wind to the upper atmosphere. To achieve this goal, satellite missions sponsored by NASA, ESA, and ISAS became more complex beginning with ISEE and extending to ISTP, Cluster, and many others. Specifically, the research effort evolved into coordinated multipoint measurements provided by constellations of spacecraft, all with on-board propulsion and station-keeping capability. During the same period, other scientific funding agencies in many countries supplemented the satellite-based research effort with the development of ground-based instrumentation networks capable of remote sensing the ionosphere and upper atmosphere. These networks provide measurements that complement the satellite data sets by providing large-scale contextual views of the state of the ionosphere and magnetically conjugate determinations of important physical parameters such as ionospheric electric fields and current systems. In this paper I discuss several of these ground-based networks and highlight research areas where they have made important contributions to satellite constellation missions as well as other topic

  8. Dynamic and interacting complex networks

    NASA Astrophysics Data System (ADS)

    Dickison, Mark E.

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

  9. Networked characteristics of the urban rail transit networks

    NASA Astrophysics Data System (ADS)

    Zhang, Jianhua; Zhao, Mingwei; Liu, Haikuan; Xu, Xiaoming

    2013-03-01

    Urban rail transit networks (URTNs) have experienced rapid development and have been receiving much attention recently. In this paper, we comprehensively analyze the topological characteristics of urban rail transit networks, and we find that the average degrees of nodes of urban rail transit networks lie in the interval [2, 2.45], most of the average shortest path lengths between pairs of nodes belong to the interval [10, 16] and the average betweenness of nodes and edges linearly increase with the increase of the number of stations. Moreover, the cumulative probability distributions of the degree and shortest path length can be fitted by exponential distribution and Gauss distribution, respectively. The network failures of the urban rail transit networks are discussed and we also discover that the highest betweenness node-based attack is the most effective method to destroy the network.

  10. Probabilistic logic modeling of network reliability for hybrid network architectures

    SciTech Connect

    Wyss, G.D.; Schriner, H.K.; Gaylor, T.R.

    1996-10-01

    Sandia National Laboratories has found that the reliability and failure modes of current-generation network technologies can be effectively modeled using fault tree-based probabilistic logic modeling (PLM) techniques. We have developed fault tree models that include various hierarchical networking technologies and classes of components interconnected in a wide variety of typical and atypical configurations. In this paper we discuss the types of results that can be obtained from PLMs and why these results are of great practical value to network designers and analysts. After providing some mathematical background, we describe the `plug-and-play` fault tree analysis methodology that we have developed for modeling connectivity and the provision of network services in several current- generation network architectures. Finally, we demonstrate the flexibility of the method by modeling the reliability of a hybrid example network that contains several interconnected ethernet, FDDI, and token ring segments. 11 refs., 3 figs., 1 tab.

  11. Dynamics-based scalability of complex networks.

    PubMed

    Huang, Liang; Lai, Ying-Cheng; Gatenby, Robert A

    2008-10-01

    We address the fundamental issue of network scalability in terms of dynamics and topology. In particular, we consider different network topologies and investigate, for every given topology, the dependence of certain dynamical properties on the network size. By focusing on network synchronizability, we find both analytically and numerically that globally coupled networks and random networks are scalable, but locally coupled regular networks are not. Scale-free networks are scalable for certain types of node dynamics. We expect our findings to provide insights into the ubiquity and workings of networks arising in nature and to be potentially useful for designing technological networks as well. PMID:18999478

  12. Growing Networks with Positive and Negative Links

    NASA Astrophysics Data System (ADS)

    Dech, Corynne; Antwi, Shadrack; Shaw, Leah

    Scale-free networks grown via preferential attachment have been used to model real-world networks such as the Internet, citation networks, and social networks. Here we investigate signed scale-free networks where an edge represents a positive or negative connection. We present analytic results and simulation for a growing signed network model. We compare the signed network to an unsigned scale-free network. We discuss several options for preferential attachment in a signed network that could be further adapted to model the accumulation of links over time in real-world signed networks.

  13. Network Robustness: the whole story

    NASA Astrophysics Data System (ADS)

    Longjas, A.; Tejedor, A.; Zaliapin, I. V.; Ambroj, S.; Foufoula-Georgiou, E.

    2014-12-01

    A multitude of actual processes operating on hydrological networks may exhibit binary outcomes such as clean streams in a river network that may become contaminated. These binary outcomes can be modeled by node removal processes (attacks) acting in a network. Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. However, the current definition of robustness is only accounting for the connectivity of the nodes unaffected by the attack. Here, we put forward the idea that the connectivity of the affected nodes can play a crucial role in proper evaluation of the overall network robustness and its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and the efficiency of building-up the IN. This approach is motivated by concrete applied problems, since, for example, if we study the dynamics of contamination in river systems, it is necessary to know both the connectivity of the healthy and contaminated parts of the river to assess its ecological functionality. We show that trade-offs between the efficiency of the Active and Idle network dynamics give rise to surprising crossovers and re-ranking of different attack strategies, pointing to significant implications for decision making.

  14. Synchronization Dynamics in Complex Networks

    NASA Astrophysics Data System (ADS)

    Zhou, Changsong; Zemanová, Lucia; Kurths, Jürgen

    Previous chapters have discussed tools from graph theory and their contribution to our understanding of the structural organization of mammalian brains and its functional implications. The brain functions are mediated by complicated dynamical processes which arise from the underlying complex neural networks, and synchronization has been proposed as an important mechanism for neural information processing. In this chapter, we discuss synchronization dynamics on complex networks. We first present a general theory and tools to characterize the relationship of some structural measures of networks to their synchronizability (the ability of the networks to achieve complete synchronization) and to the organization of effective synchronization patterns on the networks. Then, we study synchronization in a realistic network of cat cortical connectivity by modeling the nodes (which are cortical areas composed of large ensembles of neurons) by a neural mass model or a subnetwork of interacting neurons. We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns can be understood by the general principles discussed in the first part of the chapter. With weak couplings, the model with subnetworks displays biologically plausible dynamics and the synchronization pattern reveals a hierarchically clustered organization in the network structure. Thus, the study of synchronization of complex networks can provide insights into the relationship between network topology and functional organization of complex brain networks.

  15. "Conjectural" links in complex networks

    NASA Astrophysics Data System (ADS)

    Snarskii, A. A.; Zorinets, D. I.; Lande, D. V.

    2016-11-01

    This paper introduces the concept of Conjectural Link for Complex Networks, in particular, social networks. Conjectural Link we understand as an implicit link, not available in the network, but supposed to be present, based on the characteristics of its topology. It is possible, for example, when in the formal description of the network some connections are skipped due to errors, deliberately hidden or withdrawn (e.g. in the case of partial destruction of the network). Introduced a parameter that allows ranking the Conjectural Link. The more this parameter - the more likely that this connection should be present in the network. This paper presents a method of recovery of partially destroyed Complex Networks using Conjectural Links finding. Presented two methods of finding the node pairs that are not linked directly to one another, but have a great possibility of Conjectural Link communication among themselves: a method based on the determination of the resistance between two nodes, and method based on the computation of the lengths of routes between two nodes. Several examples of real networks are reviewed and performed a comparison to know network links prediction methods, not intended to find the missing links in already formed networks.

  16. Cascaded failures in weighted networks.

    PubMed

    Mirzasoleiman, Baharan; Babaei, Mahmoudreza; Jalili, Mahdi; Safari, Mohammadali

    2011-10-01

    Many technological networks can experience random and/or systematic failures in their components. More destructive situations can happen if the components have limited capacity, where the failure in one of them might lead to a cascade of failures in other components, and consequently break down the structure of the network. In this paper, the tolerance of cascaded failures was investigated in weighted networks. Three weighting strategies were considered including the betweenness centrality of the edges, the product of the degrees of the end nodes, and the product of their betweenness centralities. Then, the effect of the cascaded attack was investigated by considering the local weighted flow redistribution rule. The capacity of the edges was considered to be proportional to their initial weight distribution. The size of the survived part of the attacked network was determined in model networks as well as in a number of real-world networks including the power grid, the internet in the level of autonomous system, the railway network of Europe, and the United States airports network. We found that the networks in which the weight of each edge is the multiplication of the betweenness centrality of the end nodes had the best robustness against cascaded failures. In other words, the case where the load of the links is considered to be the product of the betweenness centrality of the end nodes is favored for the robustness of the network against cascaded failures.

  17. Network Effects on Scientific Collaborations

    PubMed Central

    Uddin, Shahadat; Hossain, Liaquat; Rasmussen, Kim

    2013-01-01

    Background The analysis of co-authorship network aims at exploring the impact of network structure on the outcome of scientific collaborations and research publications. However, little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly. Methodology/Principal Findings Measures of social network analysis, for example network centrality and tie strength, have been utilized extensively in current co-authorship literature to explore different behavioural patterns of co-authorship networks. Using three SNA measures (i.e., degree centrality, closeness centrality and betweenness centrality), we explore scientific collaboration networks to understand factors influencing performance (i.e., citation count) and formation (tie strength between authors) of such networks. A citation count is the number of times an article is cited by other articles. We use co-authorship dataset of the research field of ‘steel structure’ for the year 2005 to 2009. To measure the strength of scientific collaboration between two authors, we consider the number of articles co-authored by them. In this study, we examine how citation count of a scientific publication is influenced by different centrality measures of its co-author(s) in a co-authorship network. We further analyze the impact of the network positions of authors on the strength of their scientific collaborations. We use both correlation and regression methods for data analysis leading to statistical validation. We identify that citation count of a research article is positively correlated with the degree centrality and betweenness centrality values of its co-author(s). Also, we reveal that degree centrality and betweenness centrality values of authors in a co-authorship network are positively correlated with the strength of their scientific collaborations. Conclusions/Significance Authors’ network positions in co-authorship networks influence

  18. Understanding resilience in industrial symbiosis networks: insights from network analysis.

    PubMed

    Chopra, Shauhrat S; Khanna, Vikas

    2014-08-01

    Industrial symbiotic networks are based on the principles of ecological systems where waste equals food, to develop synergistic networks. For example, industrial symbiosis (IS) at Kalundborg, Denmark, creates an exchange network of waste, water, and energy among companies based on contractual dependency. Since most of the industrial symbiotic networks are based on ad-hoc opportunities rather than strategic planning, gaining insight into disruptive scenarios is pivotal for understanding the balance of resilience and sustainability and developing heuristics for designing resilient IS networks. The present work focuses on understanding resilience as an emergent property of an IS network via a network-based approach with application to the Kalundborg Industrial Symbiosis (KIS). Results from network metrics and simulated disruptive scenarios reveal Asnaes power plant as the most critical node in the system. We also observe a decrease in the vulnerability of nodes and reduction in single points of failure in the system, suggesting an increase in the overall resilience of the KIS system from 1960 to 2010. Based on our findings, we recommend design strategies, such as increasing diversity, redundancy, and multi-functionality to ensure flexibility and plasticity, to develop resilient and sustainable industrial symbiotic networks.

  19. The ASCI Network for SC 2000: Gigabyte Per Second Networking

    SciTech Connect

    PRATT, THOMAS J.; NAEGLE, JOHN H.; MARTINEZ JR., LUIS G.; HU, TAN CHANG; MILLER, MARC M.; BARNABY, MARTY L.; ADAMS, ROGER L.; KLAUS, EDWARD J.

    2001-11-01

    This document highlights the Discom's Distance computing and communication team activities at the 2000 Supercomputing conference in Dallas Texas. This conference is sponsored by the IEEE and ACM. Sandia's participation in the conference has now spanned a decade, for the last five years Sandia National Laboratories, Los Alamos National Lab and Lawrence Livermore National Lab have come together at the conference under the DOE's ASCI, Accelerated Strategic Computing Initiatives, Program rubric to demonstrate ASCI's emerging capabilities in computational science and our combined expertise in high performance computer science and communication networking developments within the program. At SC 2000, DISCOM demonstrated an infrastructure. DISCOM2 uses this forum to demonstrate and focus communication and pre-standard implementation of 10 Gigabit Ethernet, the first gigabyte per second data IP network transfer application, and VPN technology that enabled a remote Distributed Resource Management tools demonstration. Additionally a national OC48 POS network was constructed to support applications running between the show floor and home facilities. This network created the opportunity to test PSE's Parallel File Transfer Protocol (PFTP) across a network that had similar speed and distances as the then proposed DISCOM WAN. The SCINET SC2000 showcased wireless networking and the networking team had the opportunity to explore this emerging technology while on the booth. This paper documents those accomplishments, discusses the details of their convention exhibit floor. We also supported the production networking needs of the implementation, and describes how these demonstrations supports DISCOM overall strategies in high performance computing networking.

  20. An Adaptive Complex Network Model for Brain Functional Networks

    PubMed Central

    Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

    2009-01-01

    Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902