Fixed point theorems of GPS carrier phase ambiguity resolution and their application to massive network processing: Ambizap

NASA Astrophysics Data System (ADS)

Blewitt, Geoffrey

2008-12-01

Precise point positioning (PPP) has become popular for Global Positioning System (GPS) geodetic network analysis because for n stations, PPP has O(n) processing time, yet solutions closely approximate those of O(n3) full network analysis. Subsequent carrier phase ambiguity resolution (AR) further improves PPP precision and accuracy; however, full-network bootstrapping AR algorithms are O(n4), limiting single network solutions to n < 100. In this contribution, fixed point theorems of AR are derived and then used to develop "Ambizap," an O(n) algorithm designed to give results that closely approximate full network AR. Ambizap has been tested to n ≈ 2800 and proves to be O(n) in this range, adding only ˜50% to PPP processing time. Tests show that a 98-station network is resolved on a 3-GHz CPU in 7 min, versus 22 h using O(n4) AR methods. Ambizap features a novel network adjustment filter, producing solutions that precisely match O(n4) full network analysis. The resulting coordinates agree to ≪1 mm with current AR methods, much smaller than the ˜3-mm RMS precision of PPP alone. A 2000-station global network can be ambiguity resolved in ˜2.5 h. Together with PPP, Ambizap enables rapid, multiple reanalysis of large networks (e.g., ˜1000-station EarthScope Plate Boundary Observatory) and facilitates the addition of extra stations to an existing network solution without need to reprocess all data. To meet future needs, PPP plus Ambizap is designed to handle ˜10,000 stations per day on a 3-GHz dual-CPU desktop PC.

Global Hopf bifurcation analysis on a BAM neural network with delays

NASA Astrophysics Data System (ADS)

Sun, Chengjun; Han, Maoan; Pang, Xiaoming

2007-01-01

A delayed differential equation that models a bidirectional associative memory (BAM) neural network with four neurons is considered. By using a global Hopf bifurcation theorem for FDE and a Bendixon's criterion for high-dimensional ODE, a group of sufficient conditions for the system to have multiple periodic solutions are obtained when the sum of delays is sufficiently large.

The Unified Lunar Control Network 2005

USGS Publications Warehouse

Archinal, Brent A.; Rosiek, Mark R.; Kirk, Randolph L.; Redding, Bonnie L.

2006-01-01

This report documents a new general unified lunar control network and lunar topographic model based on a combination of Clementine images and a previous network derived from Earth-based & Apollo photographs, and Mariner 10, & Galileo images. This photogrammetric network solution is the largest planetary control network ever completed. It includes the determination of the 3-D positions of 272,931 points on the lunar surface and the correction of the camera angles for 43,866 Clementine images, using 546,126 tie point measurements. The solution RMS is 20 ?m (= 0.9 pixels) in the image plane, with the largest residual of 6.4 pixels. The explanation given here, along with the accompanying files, comprises the release of the network information and of global lunar digital elevation models (DEMs) derived from the network. A paper that will describe the solution and network in further detail will be submitted to a refereed journal, and will include additional background information, solution details, discussion of accuracy and precision, and explanatory figures.

Periodic bidirectional associative memory neural networks with distributed delays

NASA Astrophysics Data System (ADS)

Chen, Anping; Huang, Lihong; Liu, Zhigang; Cao, Jinde

2006-05-01

Some sufficient conditions are obtained for the existence and global exponential stability of a periodic solution to the general bidirectional associative memory (BAM) neural networks with distributed delays by using the continuation theorem of Mawhin's coincidence degree theory and the Lyapunov functional method and the Young's inequality technique. These results are helpful for designing a globally exponentially stable and periodic oscillatory BAM neural network, and the conditions can be easily verified and be applied in practice. An example is also given to illustrate our results.

The emergence and effectiveness of global health networks: findings and future research.

PubMed

Shiffman, Jeremy; Schmitz, Hans Peter; Berlan, David; Smith, Stephanie L; Quissell, Kathryn; Gneiting, Uwe; Pelletier, David

2016-04-01

Global health issues vary in the amount of attention and resources they receive. One reason is that the networks of individuals and organizations that address these issues differ in their effectiveness. This article presents key findings from a research project on the emergence and effectiveness of global health networks addressing tobacco use, alcohol harm, maternal mortality, neonatal mortality, tuberculosis and pneumonia. Although networks are only one of many factors influencing priority, they do matter, particularly for shaping the way the problem and solutions are understood, and convincing governments, international organizations and other global actors to address the issue. Their national-level effects vary by issue and are more difficult to ascertain. Networks are most likely to produce effects when (1) their members construct a compelling framing of the issue, one that includes a shared understanding of the problem, a consensus on solutions and convincing reasons to act and (2) they build a political coalition that includes individuals and organizations beyond their traditional base in the health sector, a task that demands engagement in the politics of the issue, not just its technical aspects. Maintaining a focused frame and sustaining a broad coalition are often in tension: effective networks find ways to balance the two challenges. The emergence and effectiveness of a network are shaped both by its members' decisions and by contextual factors, including historical influences (e.g. prior failed attempts to address the problem), features of the policy environment (e.g. global development goals) and characteristics of the issue the network addresses (e.g. its mortality burden). Their proliferation raises the issue of their legitimacy. Reasons to consider them legitimate include their members' expertise and the attention they bring to neglected issues. Reasons to question their legitimacy include their largely elite composition and the fragmentation they bring to global health governance. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2016; all rights reserved.

The emergence and effectiveness of global health networks: findings and future research

PubMed Central

Shiffman, Jeremy; Peter Schmitz, Hans; Berlan, David; Smith, Stephanie L; Quissell, Kathryn; Gneiting, Uwe; Pelletier, David

2016-01-01

Global health issues vary in the amount of attention and resources they receive. One reason is that the networks of individuals and organizations that address these issues differ in their effectiveness. This article presents key findings from a research project on the emergence and effectiveness of global health networks addressing tobacco use, alcohol harm, maternal mortality, neonatal mortality, tuberculosis and pneumonia. Although networks are only one of many factors influencing priority, they do matter, particularly for shaping the way the problem and solutions are understood, and convincing governments, international organizations and other global actors to address the issue. Their national-level effects vary by issue and are more difficult to ascertain. Networks are most likely to produce effects when (1) their members construct a compelling framing of the issue, one that includes a shared understanding of the problem, a consensus on solutions and convincing reasons to act and (2) they build a political coalition that includes individuals and organizations beyond their traditional base in the health sector, a task that demands engagement in the politics of the issue, not just its technical aspects. Maintaining a focused frame and sustaining a broad coalition are often in tension: effective networks find ways to balance the two challenges. The emergence and effectiveness of a network are shaped both by its members’ decisions and by contextual factors, including historical influences (e.g. prior failed attempts to address the problem), features of the policy environment (e.g. global development goals) and characteristics of the issue the network addresses (e.g. its mortality burden). Their proliferation raises the issue of their legitimacy. Reasons to consider them legitimate include their members’ expertise and the attention they bring to neglected issues. Reasons to question their legitimacy include their largely elite composition and the fragmentation they bring to global health governance. PMID:27067141

Comparing global alcohol and tobacco control efforts: network formation and evolution in international health governance.

PubMed

Gneiting, Uwe; Schmitz, Hans Peter

2016-04-01

Smoking and drinking constitute two risk factors contributing to the rising burden of non-communicable diseases in low- and middle-income countries. Both issues have gained increased international attention, but tobacco control has made more sustained progress in terms of international and domestic policy commitments, resources dedicated to reducing harm, and reduction of tobacco use in many high-income countries. The research presented here offers insights into why risk factors with comparable levels of harm experience different trajectories of global attention. The analysis focuses particular attention on the role of dedicated global health networks composed of individuals and organizations producing research and engaging in advocacy on a given health problem. Variation in issue characteristics and the policy environment shape the opportunities and challenges of global health networks focused on reducing the burden of disease. What sets the tobacco case apart was the ability of tobacco control advocates to create and maintain a consensus on policy solutions, expand their reach in low- and middle-income countries and combine evidence-based research with advocacy reaching beyond the public health-centered focus of the core network. In contrast, a similar network in the alcohol case struggled with expanding its reach and has yet to overcome divisions based on competing problem definitions and solutions to alcohol harm. The tobacco control network evolved from a group of dedicated individuals to a global coalition of membership-based organizations, whereas the alcohol control network remains at the stage of a collection of dedicated and like-minded individuals. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2016; all rights reserved.

Global asymptotic stability to a generalized Cohen-Grossberg BAM neural networks of neutral type delays.

PubMed

Zhang, Zhengqiu; Liu, Wenbin; Zhou, Dongming

2012-01-01

In this paper, we first discuss the existence of a unique equilibrium point of a generalized Cohen-Grossberg BAM neural networks of neutral type delays by means of the Homeomorphism theory and inequality technique. Then, by applying the existence result of an equilibrium point and constructing a Lyapunov functional, we study the global asymptotic stability of the equilibrium solution to the above Cohen-Grossberg BAM neural networks of neutral type. In our results, the hypothesis for boundedness in the existing paper, which discussed Cohen-Grossberg neural networks of neutral type on the activation functions, are removed. Finally, we give an example to demonstrate the validity of our global asymptotic stability result for the above neural networks. Copyright © 2011 Elsevier Ltd. All rights reserved.

Robust Analysis of Network-Based Real-Time Kinematic for GNSS-Derived Heights.

PubMed

Bae, Tae-Suk; Grejner-Brzezinska, Dorota; Mader, Gerald; Dennis, Michael

2015-10-26

New guidelines and procedures for real-time (RT) network-based solutions are required in order to support Global Navigation Satellite System (GNSS) derived heights. Two kinds of experiments were carried out to analyze the performance of the network-based real-time kinematic (RTK) solutions. New test marks were installed in different surrounding environments, and the existing GPS benchmarks were used for analyzing the effect of different factors, such as baseline lengths, antenna types, on the final accuracy and reliability of the height estimation. The RT solutions are categorized into three groups: single-base RTK, multiple-epoch network RTK (mRTN), and single-epoch network RTK (sRTN). The RTK solution can be biased up to 9 mm depending on the surrounding environment, but there was no notable bias for a longer reference base station (about 30 km) In addition, the occupation time for the network RTK was investigated in various cases. There is no explicit bias in the solution for different durations, but smoother results were obtained for longer durations. Further investigation is needed into the effect of changing the occupation time between solutions and into the possibility of using single-epoch solutions in precise determination of heights by GNSS.

Discrete-time neural network for fast solving large linear L1 estimation problems and its application to image restoration.

PubMed

Xia, Youshen; Sun, Changyin; Zheng, Wei Xing

2012-05-01

There is growing interest in solving linear L1 estimation problems for sparsity of the solution and robustness against non-Gaussian noise. This paper proposes a discrete-time neural network which can calculate large linear L1 estimation problems fast. The proposed neural network has a fixed computational step length and is proved to be globally convergent to an optimal solution. Then, the proposed neural network is efficiently applied to image restoration. Numerical results show that the proposed neural network is not only efficient in solving degenerate problems resulting from the nonunique solutions of the linear L1 estimation problems but also needs much less computational time than the related algorithms in solving both linear L1 estimation and image restoration problems.

Generation of Global Geodetic Networks for GGOS

NASA Astrophysics Data System (ADS)

MacMillan, Daniel; Pavlis, Erricos C.; Kuzmicz-Cieslak, Magda; Koenig, Daniel

2016-12-01

We simulated future networks of VLBI+SLR sites to assess their performance. The objective is to build a global network of geographically well distributed, co-located next-generation sites from each of the space geodetic techniques. The network is being designed to meet the GGOS terrestrial reference frame goals of 1 mm in accuracy and 0.1 mm/yr in stability. We simulated the next generation networks that should be available in five years and in ten years to assess the likelihood that these networks will meet the reference frame goals. Simulations were based on the expectation that 17 broadband VLBI stations will be available in five years and 27 stations in ten years. We also consider the improvement resulting from expanding the network by six additional VLBI sites to improve the global distribution of the network. In the simulations, the networks will operate continuously, but we account for station downtime for maintenance or because of bad weather. We ran SLR+VLBI combination TRF solutions, where site ties were used to connect the two networks in the same way as in combination solutions with observed data. The strengths of VLBI and SLR allows them to provide the necessary reference frame accuracy in scale, geocenter, and orientation. With the +10-year extended network operating for ten years, simulations indicate that scale, origin, and orientation accuracies will be at the level of 0.02 ppb, 0.2 mm, and 6 μas. Combining the +5-year and +10-year network realizations will provide better estimates of accuracy and estimates of stability.

Bifurcation analysis of eight coupled degenerate optical parametric oscillators

NASA Astrophysics Data System (ADS)

Ito, Daisuke; Ueta, Tetsushi; Aihara, Kazuyuki

2018-06-01

A degenerate optical parametric oscillator (DOPO) network realized as a coherent Ising machine can be used to solve combinatorial optimization problems. Both theoretical and experimental investigations into the performance of DOPO networks have been presented previously. However a problem remains, namely that the dynamics of the DOPO network itself can lower the search success rates of globally optimal solutions for Ising problems. This paper shows that the problem is caused by pitchfork bifurcations due to the symmetry structure of coupled DOPOs. Some two-parameter bifurcation diagrams of equilibrium points express the performance deterioration. It is shown that the emergence of non-ground states regarding local minima hampers the system from reaching the ground states corresponding to the global minimum. We then describe a parametric strategy for leading a system to the ground state by actively utilizing the bifurcation phenomena. By adjusting the parameters to break particular symmetry, we find appropriate parameter sets that allow the coherent Ising machine to obtain the globally optimal solution alone.

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Neural network for nonsmooth pseudoconvex optimization with general convex constraints.

PubMed

Bian, Wei; Ma, Litao; Qin, Sitian; Xue, Xiaoping

2018-05-01

In this paper, a one-layer recurrent neural network is proposed for solving a class of nonsmooth, pseudoconvex optimization problems with general convex constraints. Based on the smoothing method, we construct a new regularization function, which does not depend on any information of the feasible region. Thanks to the special structure of the regularization function, we prove the global existence, uniqueness and "slow solution" character of the state of the proposed neural network. Moreover, the state solution of the proposed network is proved to be convergent to the feasible region in finite time and to the optimal solution set of the related optimization problem subsequently. In particular, the convergence of the state to an exact optimal solution is also considered in this paper. Numerical examples with simulation results are given to show the efficiency and good characteristics of the proposed network. In addition, some preliminary theoretical analysis and application of the proposed network for a wider class of dynamic portfolio optimization are included. Copyright © 2018 Elsevier Ltd. All rights reserved.

Complementarity and Area-Efficiency in the Prioritization of the Global Protected Area Network.

PubMed

Kullberg, Peter; Toivonen, Tuuli; Montesino Pouzols, Federico; Lehtomäki, Joona; Di Minin, Enrico; Moilanen, Atte

2015-01-01

Complementarity and cost-efficiency are widely used principles for protected area network design. Despite the wide use and robust theoretical underpinnings, their effects on the performance and patterns of priority areas are rarely studied in detail. Here we compare two approaches for identifying the management priority areas inside the global protected area network: 1) a scoring-based approach, used in recently published analysis and 2) a spatial prioritization method, which accounts for complementarity and area-efficiency. Using the same IUCN species distribution data the complementarity method found an equal-area set of priority areas with double the mean species ranges covered compared to the scoring-based approach. The complementarity set also had 72% more species with full ranges covered, and lacked any coverage only for half of the species compared to the scoring approach. Protected areas in our complementarity-based solution were on average smaller and geographically more scattered. The large difference between the two solutions highlights the need for critical thinking about the selected prioritization method. According to our analysis, accounting for complementarity and area-efficiency can lead to considerable improvements when setting management priorities for the global protected area network.

Something Old, Not Much New, and a Lot Borrowed: Philanthropy, Business, and the Changing Roles of Government in Global Education Policy Networks

ERIC Educational Resources Information Center

Olmedo, Antonio

2017-01-01

This paper focuses on the role of governments in contemporary networked political configurations. Such networks constitute policy communities, usually based upon shared conceptions of social problems and their solutions. By enabling social, political, and economic connections at local, regional, national, and international levels, such networks…

Precise Clock Solutions Using Carrier Phase from GPS Receivers in the International GPS Service

NASA Technical Reports Server (NTRS)

Zumberge, J. F.; Jefferson, D. C.; Stowers, D. A.; Tjoelker, R. L.; Young, L. E.

1999-01-01

As one of its activities as an Analysis Center in the International GPS Service (IGS), the Jet Propulsion Laboratory (JPL) uses data from a globally distributed network of geodetic-quality GPS receivers to estimate precise clock solutions, relative to a chosen reference, for both the GPS satellites and GPS receiver internal clocks, every day. The GPS constellation and ground network provide geometrical strength resulting in formal errors of about 100 p sec for these estimates. Some of the receivers in the global IGS network contain high quality frequency references, such as hydrogen masers. The clock solutions for such receivers are smooth at the 20-p sec level on time scales of a few minutes. There are occasional (daily to weekly) shifts at the microsec level, symptomatic of receiver resets, and 200-p sec-level discontinuities at midnight due to 1-day processing boundaries. Relative clock solutions among 22 IGS sites proposed as "fiducial" in the IGS/BIPM pilot project have been examined over a recent 4-week period. This allows a quantitative measure of receiver reset frequency as a function of site. For days and-sites without resets, the Allan deviation of the relative clock solutions is also computed for subdaily values of tau..

Extracting Association Patterns in Network Communications

PubMed Central

Portela, Javier; Villalba, Luis Javier García; Trujillo, Alejandra Guadalupe Silva; Orozco, Ana Lucila Sandoval; Kim, Tai-hoon

2015-01-01

In network communications, mixes provide protection against observers hiding the appearance of messages, patterns, length and links between senders and receivers. Statistical disclosure attacks aim to reveal the identity of senders and receivers in a communication network setting when it is protected by standard techniques based on mixes. This work aims to develop a global statistical disclosure attack to detect relationships between users. The only information used by the attacker is the number of messages sent and received by each user for each round, the batch of messages grouped by the anonymity system. A new modeling framework based on contingency tables is used. The assumptions are more flexible than those used in the literature, allowing to apply the method to multiple situations automatically, such as email data or social networks data. A classification scheme based on combinatoric solutions of the space of rounds retrieved is developed. Solutions about relationships between users are provided for all pairs of users simultaneously, since the dependence of the data retrieved needs to be addressed in a global sense. PMID:25679311

Extracting association patterns in network communications.

PubMed

Portela, Javier; Villalba, Luis Javier García; Trujillo, Alejandra Guadalupe Silva; Orozco, Ana Lucila Sandoval; Kim, Tai-hoon

2015-02-11

In network communications, mixes provide protection against observers hiding the appearance of messages, patterns, length and links between senders and receivers. Statistical disclosure attacks aim to reveal the identity of senders and receivers in a communication network setting when it is protected by standard techniques based on mixes. This work aims to develop a global statistical disclosure attack to detect relationships between users. The only information used by the attacker is the number of messages sent and received by each user for each round, the batch of messages grouped by the anonymity system. A new modeling framework based on contingency tables is used. The assumptions are more flexible than those used in the literature, allowing to apply the method to multiple situations automatically, such as email data or social networks data. A classification scheme based on combinatoric solutions of the space of rounds retrieved is developed. Solutions about relationships between users are provided for all pairs of users simultaneously, since the dependence of the data retrieved needs to be addressed in a global sense.

Calibration of the clock-phase biases of GNSS networks: the closure-ambiguity approach

NASA Astrophysics Data System (ADS)

Lannes, A.; Prieur, J.-L.

2013-08-01

In global navigation satellite systems (GNSS), the problem of retrieving clock-phase biases from network data has a basic rank defect. We analyse the different ways of removing this rank defect, and define a particular strategy for obtaining these phase biases in a standard form. The minimum-constrained problem to be solved in the least-squares (LS) sense depends on some integer vector which can be fixed in an arbitrary manner. We propose to solve the problem via an undifferenced approach based on the notion of closure ambiguity. We present a theoretical justification of this closure-ambiguity approach (CAA), and the main elements for a practical implementation. The links with other methods are also established. We analyse all those methods in a unified interpretative framework, and derive functional relations between the corresponding solutions and our CAA solution. This could be interesting for many GNSS applications like real-time kinematic PPP for instance. To compare the methods providing LS estimates of clock-phase biases, we define a particular solution playing the role of reference solution. For this solution, when a phase bias is estimated for the first time, its fractional part is confined to the one-cycle width interval centred on zero; the integer-ambiguity set is modified accordingly. Our theoretical study is illustrated with some simple and generic examples; it could have applications in data processing of most GNSS networks, and particularly global networks using GPS, Glonass, Galileo, or BeiDou/Compass satellites.

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Global dynamic optimization approach to predict activation in metabolic pathways.

PubMed

de Hijas-Liste, Gundián M; Klipp, Edda; Balsa-Canto, Eva; Banga, Julio R

2014-01-06

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been successfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework. In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results. The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.

Mars Digital Image Model 2.1 Control Network

NASA Technical Reports Server (NTRS)

Archinal, B. A.; Kirk, R. L.; Duxbury, T. C.; Lee, E. M.; Sucharski, R.; Cook, D.

2003-01-01

USGS is currently preparing a new version of its global Mars digital image mosaic, which will be known as MDIM 2.1. As part of this process we are completing a new photogrammetric solution of the global Mars control network. This is an improved version of the network established earlier by RAND and USGS personnel, as partially described previously. MDIM 2.1 will have many improvements over earlier Viking Orbiter (VO) global mosaics. Geometrically, it will be an orthoimage product, draped on Mars Orbiter Laser Altimeter (MOLA) derived topography, thus accounting properly for the commonly oblique VO imagery. Through the network being described here it will be tied to the newly defined IAU/IAG 2000 Mars coordinate system via ties to MOLA data. Thus, MDIM 2.1 will provide complete global orthorectified imagery coverage of Mars at the resolution of 1/256 deg of MDIM 2.0, and be compatible with MOLA and other products produced in the current coordinate system.

Rigorous GNSS network solutions of unlimited size

NASA Astrophysics Data System (ADS)

Boomkamp, H.; Iag Working Group 1. 1. 1

2010-12-01

The session description states that rigorous estimation processes for millions of parameters are computationally impossible. A more accurate observation would be that such solutions exceed the capacity of current Analysis Centres by several orders of magnitude, as was already discussed during the IGS Workshop of 2004. We can however make processing elements that are smaller and simpler than conventional Analysis Centres, until we have a “centre” that can be replicated in arbitrary amounts, at zero cost. In practice this means that the processing element is reduced to a single, automated computer application that can run anywhere. These analysis elements are connected via the internet into a scalable grid computing scheme that can handle GNSS networks of any size. The approach is not fundamentally different from current combination solutions among a network of Analysis Centres, but refines the granularity of the network elements in order to reduce system complexity and eliminate cost. The Dancer project of IAG Working Group 1 has developed a JXTA peer-to-peer application to this purpose. Dancer splits a conventional batch least squares process into as many interacting subtasks as there are receivers. Each task can then run on a local PC of a permanent GNSS site, or anywhere else. All Dancer instances find the same global solution for satellite orbits, clocks and Earth rotation parameters via an efficient vector averaging method called square dancing. The hardware requirements for a single Dancer process do not exceed those of e.g. current mobile phone applications, so that future generations of GNSS receivers may be able to run such a task as an embedded process. This leads to the concept of “smart receivers” that no longer require any post-processing infrastructure. Instead they need an internet connection to join thousands of other smart receivers in a global network solution. The key algorithms, project status and further deployment of the Dancer system will be presented. A brief summary is also given of two follow-on projects, called Digger (distributed computing for global geodetic reprocessing) and Dart (Dancer real-time). For more details, see www.GPSdancer.com.

Improvement of the Asia-Pacific TWSTFT network solutions by using DPN results.

PubMed

Lin, Huang-Tien; Huang, Yi-Jiun; Liao, Chia-Shu; Chu, Fang-Dar; Tseng, Wen-Hung

2012-03-01

Two major time and frequency transfer techniques, two-way satellite time and frequency transfer (TWSTFT) and global navigation satellite systems (GNSS: GPS, GALILEO, GLONASS, etc.), are used for the generation of Coordinated Universal Time (UTC)/International Atomic Time (TAI). These time and frequency transfer links comprise a worldwide network and the utilization of the highly redundant time and frequency data is an important topic. Two methods, either TW-only network (i.e., TWSTFT) or single-link combination of TW and Global Positioning System (GPS), have been developed for combining the redundant data from different techniques. In our previous study, we have proposed a feasible method, utilizing full time-transfer network data, to improve the results of TWSTFT network. The National Institute of Information and Communications Technology (NICT) has recently developed a software-based two-way time-transfer modem using a dual pseudo-random noise (DPN) signal. The first international DPN TWSTFT experiment, using these modems, was performed between NICT (Japan) and Telecommunication Laboratories (TL; Taiwan)and its ability to improve the time transfer precision was demonstrated. In comparison with the conventional NICT–TLTWSTFT link, the DPN time transfer results have higher precision and lower diurnal effects. The estimation also shows that DPN is comparable to GPS precise point positioning (PPP).Because the DPN results show better performance than the conventional TWSTFT results, we would adopt the DPN data for the NICT–TL link and solve the TW+DPN network solutions by using our proposed method. The concept of this application is similar to the so-called multi-technique-network time/frequency transfer. The encouraging results confirm that the TWSTFT network performance can benefit from DPN data by improving short-term stabilities and reducing diurnal effects.The results of TW+PPP network solutions are also illustrated.

A novel recurrent neural network with finite-time convergence for linear programming.

PubMed

Liu, Qingshan; Cao, Jinde; Chen, Guanrong

2010-11-01

In this letter, a novel recurrent neural network based on the gradient method is proposed for solving linear programming problems. Finite-time convergence of the proposed neural network is proved by using the Lyapunov method. Compared with the existing neural networks for linear programming, the proposed neural network is globally convergent to exact optimal solutions in finite time, which is remarkable and rare in the literature of neural networks for optimization. Some numerical examples are given to show the effectiveness and excellent performance of the new recurrent neural network.

Spatial effects in real networks: Measures, null models, and applications

NASA Astrophysics Data System (ADS)

Ruzzenenti, Franco; Picciolo, Francesco; Basosi, Riccardo; Garlaschelli, Diego

2012-12-01

Spatially embedded networks are shaped by a combination of purely topological (space-independent) and space-dependent formation rules. While it is quite easy to artificially generate networks where the relative importance of these two factors can be varied arbitrarily, it is much more difficult to disentangle these two architectural effects in real networks. Here we propose a solution to this problem, by introducing global and local measures of spatial effects that, through a comparison with adequate null models, effectively filter out the spurious contribution of nonspatial constraints. Our filtering allows us to consistently compare different embedded networks or different historical snapshots of the same network. As a challenging application we analyze the World Trade Web, whose topology is known to depend on geographic distances but is also strongly determined by nonspatial constraints (degree sequence or gross domestic product). Remarkably, we are able to detect weak but significant spatial effects both locally and globally in the network, showing that our method succeeds in retrieving spatial information even when nonspatial factors dominate. We finally relate our results to the economic literature on gravity models and trade globalization.

Knowledge networks for global public health.

PubMed

Natividad, Maria Dulce F; Fiereck, Kirk J; Parker, Richard

2012-01-01

The challenges posed by a globalised world have made it imperative for society to search for solutions to emerging issues and to develop new ways of looking at old problems. Current discussions about global public health demand a shift in paradigms and the strategic positioning of public health within broader policy discussions that will enable it to influence political and action agendas. Critical to responding to these challenges is the generation, transmission and dissemination of new knowledge to create value. Recognising the cutting-edge role of knowledge, as a new form of capital that drives innovation and transforms society, the formation of knowledge networks is viewed as a strategy for developing a shared intellectual, conceptual and ethical infrastructure for the field of global public health. These knowledge networks are envisioned as a vehicle for sharing diverse perspectives, encouraging debate and sustaining alternative ways of thinking about and responding to the challenges that confront global public health today and in the future.

A multi-scale network method for two-phase flow in porous media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khayrat, Karim, E-mail: khayratk@ifd.mavt.ethz.ch; Jenny, Patrick

Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces withinmore » each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.« less

Global Mittag-Leffler stability analysis of fractional-order impulsive neural networks with one-side Lipschitz condition.

PubMed

Zhang, Xinxin; Niu, Peifeng; Ma, Yunpeng; Wei, Yanqiao; Li, Guoqiang

2017-10-01

This paper is concerned with the stability analysis issue of fractional-order impulsive neural networks. Under the one-side Lipschitz condition or the linear growth condition of activation function, the existence of solution is analyzed respectively. In addition, the existence, uniqueness and global Mittag-Leffler stability of equilibrium point of the fractional-order impulsive neural networks with one-side Lipschitz condition are investigated by the means of contraction mapping principle and Lyapunov direct method. Finally, an example with numerical simulation is given to illustrate the validity and feasibility of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Teach for All: Storytelling "Shared Solutions" and Scaling Global Reform

ERIC Educational Resources Information Center

Ahmann, Chloe

2015-01-01

"Teach For All" is a global network of state-based organizations that translate "Teach For America's" market model of school reform into moral projects of nation-building abroad. Referring to this challenge as one of "scaling" the organization, its leaders elaborate a theory of change that hinges on replicability: in…

Neural-network-assisted genetic algorithm applied to silicon clusters

NASA Astrophysics Data System (ADS)

Marim, L. R.; Lemes, M. R.; dal Pino, A.

2003-03-01

Recently, a new optimization procedure that combines the power of artificial neural-networks with the versatility of the genetic algorithm (GA) was introduced. This method, called neural-network-assisted genetic algorithm (NAGA), uses a neural network to restrict the search space and it is expected to speed up the solution of global optimization problems if some previous information is available. In this paper, we have tested NAGA to determine the ground-state geometry of Sin (10⩽n⩽15) according to a tight-binding total-energy method. Our results indicate that NAGA was able to find the desired global minimum of the potential energy for all the test cases and it was at least ten times faster than pure genetic algorithm.

The Mobile Internet -The Next Big Thing. Electrons & Photons: You Need Both! (BRIEFING CHARTS)

DTIC Science & Technology

2007-03-05

Links Network Centric Warfighting Comms Wired & Wireless Links 20th Century 21th Century The Military Comms Problem Network Centric Operationst t i ti...Small Unit Operations TEL Underwater Vehicles & Towed Arrays RC-135V Rivet Joint Tier II+ UAV Global Hawk E-2C Hawkeye Networked Manned and Unmanned...RF Front-End Solutions ● >20 DARPA/MTO RF Programs across the spectrum - RF & Mixed Signal Electronics - Analog & Digital Photonics Enables Network

2016 AAE National Membership Survey: Professional Educators Embrace Solutions

ERIC Educational Resources Information Center

Association of American Educators, 2016

2016-01-01

Competing in a new global economy is a top national priority. Citing declining student performance in core subjects, policymakers are calling for solutions that give students an edge. The Association of American Educators (AAE) knows that a growing network of professional educators will be instrumental in building the bridge between sweeping…

The use of global image characteristics for neural network pattern recognitions

NASA Astrophysics Data System (ADS)

Kulyas, Maksim O.; Kulyas, Oleg L.; Loshkarev, Aleksey S.

2017-04-01

The recognition system is observed, where the information is transferred by images of symbols generated by a television camera. For descriptors of objects the coefficients of two-dimensional Fourier transformation generated in a special way. For solution of the task of classification the one-layer neural network trained on reference images is used. Fast learning of a neural network with a single neuron calculation of coefficients is applied.

The extended tracking network and indications of baseline precision and accuracy in the North Andes

NASA Technical Reports Server (NTRS)

Freymueller, Jeffrey T.; Kellogg, James N.

1990-01-01

The CASA Uno Global Positioning System (GPS) experiment (January-February 1988) included an extended tracking network which covered three continents in addition to the network of scientific interest in Central and South America. The repeatability of long baselines (400-1000 km) in South America is improved by up to a factor of two in the horizontal vector baseline components by using tracking stations in the Pacific and Europe to supplement stations in North America. In every case but one, the differences between the mean solutions obtained using different tracking networks was equal to or smaller than day-to-day rms repeatabilities for the same baselines. The mean solutions obtained by using tracking stations in North America and the Pacific agreed at the 2-3 millimeter level with those using tracking stations in North America and Europe. The agreement of the extended tracking network solutions suggests that a broad distribution of tracking stations provides better geometric constraints on the satellite orbits and that solutions are not sensitive to changes in tracking network configuration when an extended network is use. A comparison of the results from the North Andes and a baseline in North America suggests that the use of a geometrically strong extended tracking network is most important when the network of interest is far from North America.

Global Education Inc.: New Policy Networks and the Neoliberal Imaginary

ERIC Educational Resources Information Center

Ball, Stephen J.

2012-01-01

Do private and philanthropic solutions to the problems of education signal the end of state education in its "welfare" form? Education policy is being reformed and re-worked on a global scale. Policies are flowing and converging to produce a singular vision of "best practice" based on the methods and tenets of the "neo-liberal imaginary".…

Enabling Research Network Connectivity to Clouds with Virtual Router Technology

NASA Astrophysics Data System (ADS)

Seuster, R.; Casteels, K.; Leavett-Brown, CR; Paterson, M.; Sobie, RJ

2017-10-01

The use of opportunistic cloud resources by HEP experiments has significantly increased over the past few years. Clouds that are owned or managed by the HEP community are connected to the LHCONE network or the research network with global access to HEP computing resources. Private clouds, such as those supported by non-HEP research funds are generally connected to the international research network; however, commercial clouds are either not connected to the research network or only connect to research sites within their national boundaries. Since research network connectivity is a requirement for HEP applications, we need to find a solution that provides a high-speed connection. We are studying a solution with a virtual router that will address the use case when a commercial cloud has research network connectivity in a limited region. In this situation, we host a virtual router in our HEP site and require that all traffic from the commercial site transit through the virtual router. Although this may increase the network path and also the load on the HEP site, it is a workable solution that would enable the use of the remote cloud for low I/O applications. We are exploring some simple open-source solutions. In this paper, we present the results of our studies and how it will benefit our use of private and public clouds for HEP computing.

Focal Solute Trapping and Global Glymphatic Pathway Impairment in a Murine Model of Multiple Microinfarcts

PubMed Central

Wang, Minghuan; Ding, Fengfei; Deng, SaiYue; Guo, Xuequn; Wang, Wei

2017-01-01

Microinfarcts occur commonly in the aging brain as a consequence of diffuse embolic events and are associated with the development of vascular dementia and Alzheimer's disease. However, the manner in which disperse microscopic lesions reduce global cognitive function and increase the risk for Alzheimer's disease is unclear. The glymphatic system, which is a brain-wide perivascular network that supports the recirculation of CSF through the brain parenchyma, facilitates the clearance of interstitial solutes including amyloid β and tau. We investigated whether glymphatic pathway function is impaired in a murine model of multiple microinfarcts induced by intraarterial injection of cholesterol crystals. The analysis showed that multiple microinfarcts markedly impaired global influx of CSF along the glymphatic pathway. Although suppression of global glymphatic function was transient, resolving within 2 weeks of injury, CSF tracers also accumulated within tissue associated with microinfarcts. The effect of diffuse microinfarcts on global glymphatic pathway function was exacerbated in the mice aged 12 months compared with the 2- to 3-month-old mice. These findings indicate that glymphatic function is focally disrupted around microinfarcts and that the aging brain is more vulnerable to this disruption than the young brain. These observations suggest that microlesions may trap proteins and other interstitial solutes within the brain parenchyma, increasing the risk of amyloid plaque formation. SIGNIFICANCE STATEMENT Microinfarcts, small (<1 mm) ischemic lesions, are strongly associated with age-related dementia. However, how these microscopic lesions affect global cognitive function and predispose to Alzheimer's disease is unclear. The glymphatic system is a brain-wide network of channels surrounding brain blood vessels that allows CSF to exchange with interstitial fluid, clearing away cellular wastes such as amyloid β. We observed that, in mice, microinfarcts impaired global glymphatic function and solutes from the CSF became trapped in tissue associated with microinfarcts. These data suggest that small, disperse ischemic lesions can impair glymphatic function across the brain and trapping of solutes in these lesions may promote protein aggregation and neuroinflammation and eventually lead to neurodegeneration, especially in the aging brain. PMID:28188218

Focal Solute Trapping and Global Glymphatic Pathway Impairment in a Murine Model of Multiple Microinfarcts.

PubMed

Wang, Minghuan; Ding, Fengfei; Deng, SaiYue; Guo, Xuequn; Wang, Wei; Iliff, Jeffrey J; Nedergaard, Maiken

2017-03-15

Microinfarcts occur commonly in the aging brain as a consequence of diffuse embolic events and are associated with the development of vascular dementia and Alzheimer's disease. However, the manner in which disperse microscopic lesions reduce global cognitive function and increase the risk for Alzheimer's disease is unclear. The glymphatic system, which is a brain-wide perivascular network that supports the recirculation of CSF through the brain parenchyma, facilitates the clearance of interstitial solutes including amyloid β and tau. We investigated whether glymphatic pathway function is impaired in a murine model of multiple microinfarcts induced by intraarterial injection of cholesterol crystals. The analysis showed that multiple microinfarcts markedly impaired global influx of CSF along the glymphatic pathway. Although suppression of global glymphatic function was transient, resolving within 2 weeks of injury, CSF tracers also accumulated within tissue associated with microinfarcts. The effect of diffuse microinfarcts on global glymphatic pathway function was exacerbated in the mice aged 12 months compared with the 2- to 3-month-old mice. These findings indicate that glymphatic function is focally disrupted around microinfarcts and that the aging brain is more vulnerable to this disruption than the young brain. These observations suggest that microlesions may trap proteins and other interstitial solutes within the brain parenchyma, increasing the risk of amyloid plaque formation. SIGNIFICANCE STATEMENT Microinfarcts, small (<1 mm) ischemic lesions, are strongly associated with age-related dementia. However, how these microscopic lesions affect global cognitive function and predispose to Alzheimer's disease is unclear. The glymphatic system is a brain-wide network of channels surrounding brain blood vessels that allows CSF to exchange with interstitial fluid, clearing away cellular wastes such as amyloid β. We observed that, in mice, microinfarcts impaired global glymphatic function and solutes from the CSF became trapped in tissue associated with microinfarcts. These data suggest that small, disperse ischemic lesions can impair glymphatic function across the brain and trapping of solutes in these lesions may promote protein aggregation and neuroinflammation and eventually lead to neurodegeneration, especially in the aging brain. Copyright © 2017 the authors 0270-6474/17/372870-08$15.00/0.

Solutions Network Formulation Report. The Potential Contributions of the Global Precipitation Measurement Mission to Phosphorus Reduction Efforts in the Florida Everglades

NASA Technical Reports Server (NTRS)

Anderson, Daniel; Hilbert, Kent; Lewis, David

2009-01-01

This candidate solution suggests the use of GPM precipitation observations to enhance the CERP. Specifically, GPM measurements could augment in situ precipitation data that are used to model agricultural phosphorus discharged into the Everglades. This solution benefits society by aiding water resource managers in identifying effective phosphorus reduction scenarios and thereby returning the Everglades to a more natural state. This solution supports the Water Management, Coastal Management, and Ecological Forecasting National Applications.

Validation results of the IAG Dancer project for distributed GPS analysis

NASA Astrophysics Data System (ADS)

Boomkamp, H.

2012-12-01

The number of permanent GPS stations in the world has grown far too large to allow processing of all this data at analysis centers. The majority of these GPS sites do not even make their observation data available to the analysis centers, for various valid reasons. The current ITRF solution is still based on centralized analysis by the IGS, and subsequent densification of the reference frame via regional network solutions. Minor inconsistencies in analysis methods, software systems and data quality imply that this centralized approach is unlikely to ever reach the ambitious accuracy objectives of GGOS. The dependence on published data also makes it clear that a centralized approach will never provide a true global ITRF solution for all GNSS receivers in the world. If the data does not come to the analysis, the only alternative is to bring the analysis to the data. The IAG Dancer project has implemented a distributed GNSS analysis system on the internet in which each receiver can have its own analysis center in the form of a freely distributed JAVA peer-to-peer application. Global parameters for satellite orbits, clocks and polar motion are solved via a distributed least squares solution among all participating receivers. A Dancer instance can run on any computer that has simultaneous access to the receiver data and to the public internet. In the future, such a process may be embedded in the receiver firmware directly. GPS network operators can join the Dancer ITRF realization without having to publish their observation data or estimation products. GPS users can run a Dancer process without contributing to the global solution, to have direct access to the ITRF in near real-time. The Dancer software has been tested on-line since late 2011. A global network of processes has gradually evolved to allow stabilization and tuning of the software in order to reach a fully operational system. This presentation reports on the current performance of the Dancer system, and demonstrates the obvious benefits of distributed analysis of geodetic data in general. IAG Dancer screenshot

WaterNet:The NASA Water Cycle Solutions Network

NASA Astrophysics Data System (ADS)

Belvedere, D. R.; Houser, P. R.; Pozzi, W.; Imam, B.; Schiffer, R.; Schlosser, C. A.; Gupta, H.; Martinez, G.; Lopez, V.; Vorosmarty, C.; Fekete, B.; Matthews, D.; Lawford, R.; Welty, C.; Seck, A.

2008-12-01

Water is essential to life and directly impacts and constrains society's welfare, progress, and sustainable growth, and is continuously being transformed by climate change, erosion, pollution, and engineering. Projections of the effects of such factors will remain speculative until more effective global prediction systems and applications are implemented. NASA's unique role is to use its view from space to improve water and energy cycle monitoring and prediction, and has taken steps to collaborate and improve interoperability with existing networks and nodes of research organizations, operational agencies, science communities, and private industry. WaterNet is a Solutions Network, devoted to the identification and recommendation of candidate solutions that propose ways in which water-cycle related NASA research results can be skillfully applied by partner agencies, international organizations, state, and local governments. It is designed to improve and optimize the sustained ability of water cycle researchers, stakeholders, organizations and networks to interact, identify, harness, and extend NASA research results to augment Decision Support Tools that address national needs.

An efficient annealing in Boltzmann machine in Hopfield neural network

NASA Astrophysics Data System (ADS)

Kin, Teoh Yeong; Hasan, Suzanawati Abu; Bulot, Norhisam; Ismail, Mohammad Hafiz

2012-09-01

This paper proposes and implements Boltzmann machine in Hopfield neural network doing logic programming based on the energy minimization system. The temperature scheduling in Boltzmann machine enhancing the performance of doing logic programming in Hopfield neural network. The finest temperature is determined by observing the ratio of global solution and final hamming distance using computer simulations. The study shows that Boltzmann Machine model is more stable and competent in term of representing and solving difficult combinatory problems.

Periodicity and stability for variable-time impulsive neural networks.

PubMed

Li, Hongfei; Li, Chuandong; Huang, Tingwen

2017-10-01

The paper considers a general neural networks model with variable-time impulses. It is shown that each solution of the system intersects with every discontinuous surface exactly once via several new well-proposed assumptions. Moreover, based on the comparison principle, this paper shows that neural networks with variable-time impulse can be reduced to the corresponding neural network with fixed-time impulses under well-selected conditions. Meanwhile, the fixed-time impulsive systems can be regarded as the comparison system of the variable-time impulsive neural networks. Furthermore, a series of sufficient criteria are derived to ensure the existence and global exponential stability of periodic solution of variable-time impulsive neural networks, and to illustrate the same stability properties between variable-time impulsive neural networks and the fixed-time ones. The new criteria are established by applying Schaefer's fixed point theorem combined with the use of inequality technique. Finally, a numerical example is presented to show the effectiveness of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rumor diffusion model with spatio-temporal diffusion and uncertainty of behavior decision in complex social networks

NASA Astrophysics Data System (ADS)

Zhu, Liang; Wang, Youguo

2018-07-01

In this paper, a rumor diffusion model with uncertainty of human behavior under spatio-temporal diffusion framework is established. Take physical significance of spatial diffusion into account, a diffusion threshold is set under which the rumor is not a trend topic and only spreads along determined physical connections. Heterogeneity of degree distribution and distance distribution has also been considered in theoretical model at the same time. The global existence and uniqueness of classical solution are proved with a Lyapunov function and an approximate classical solution in form of infinite series is constructed with a system of eigenfunction. Simulations and numerical solutions both on Watts-Strogatz (WS) network and Barabási-Albert (BA) network display the variation of density of infected connections from spatial and temporal dimensions. Relevant results show that the density of infected connections is dominated by network topology and uncertainty of human behavior at threshold time. With increase of social capability, rumor diffuses to the steady state in a higher speed. And the variation trends of diffusion size with uncertainty are diverse on different artificial networks.

Global exponential stability and lag synchronization for delayed memristive fuzzy Cohen-Grossberg BAM neural networks with impulses.

PubMed

Yang, Wengui; Yu, Wenwu; Cao, Jinde; Alsaadi, Fuad E; Hayat, Tasawar

2018-02-01

This paper investigates the stability and lag synchronization for memristor-based fuzzy Cohen-Grossberg bidirectional associative memory (BAM) neural networks with mixed delays (asynchronous time delays and continuously distributed delays) and impulses. By applying the inequality analysis technique, homeomorphism theory and some suitable Lyapunov-Krasovskii functionals, some new sufficient conditions for the uniqueness and global exponential stability of equilibrium point are established. Furthermore, we obtain several sufficient criteria concerning globally exponential lag synchronization for the proposed system based on the framework of Filippov solution, differential inclusion theory and control theory. In addition, some examples with numerical simulations are given to illustrate the feasibility and validity of obtained results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relations between macropore network characteristics and the degree of preferential solute transport

NASA Astrophysics Data System (ADS)

Larsbo, M.; Koestel, J.; Jarvis, N.

2014-12-01

The characteristics of the soil macropore network determine the potential for fast transport of agrochemicals and contaminants through the soil. The objective of this study was to examine the relationships between macropore network characteristics, hydraulic properties and state variables and measures of preferential transport. Experiments were carried out under near-saturated conditions on undisturbed columns sampled from four agricultural topsoils of contrasting texture and structure. Macropore network characteristics were computed from 3-D X-ray tomography images of the soil pore system. Non-reactive solute transport experiments were carried out at five steady-state water flow rates from 2 to 12 mm h-1. The degree of preferential transport was evaluated by the normalised 5% solute arrival time and the apparent dispersivity calculated from the resulting breakthrough curves. Near-saturated hydraulic conductivities were measured on the same samples using a tension disc infiltrometer placed on top of the columns. Results showed that many of the macropore network characteristics were inter-correlated. For example, large macroporosities were associated with larger specific macropore surface areas and better local connectivity of the macropore network. Generally, an increased flow rate resulted in earlier solute breakthrough and a shifting of the arrival of peak concentration towards smaller drained volumes. Columns with smaller macroporosities, poorer local connectivity of the macropore network and smaller near-saturated hydraulic conductivities exhibited a greater degree of preferential transport. This can be explained by the fact that, with only two exceptions, global (i.e. sample scale) continuity of the macropore network was still preserved at low macroporosities. Thus, for any given flow rate, pores of larger diameter were actively conducting solute in soils of smaller near-saturated hydraulic conductivity. This was associated with larger local transport velocities and, hence, less time for equilibration between the macropores and the surrounding matrix which made the transport more preferential. Conversely, the large specific macropore surface area and well-connected macropore networks associated with columns with large macroporosities limit the degree of preferential transport because they increase the diffusive flux between macropores and the soil matrix and they increase the near-saturated hydraulic conductivity. The normalised 5% arrival times were most strongly correlated with the estimated hydraulic state variables (e.g. with the degree of saturation in the macropores R2 = 0.589), since these combine into one measure the effects of irrigation rate and the near-saturated hydraulic conductivity function, which in turn implicitly depends on the volume, size distribution, global continuity, local connectivity and tortuosity of the macropore network.

Precise tracking of remote sensing satellites with the Global Positioning System

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong; Thornton, Catherine L.

1990-01-01

The Global Positioning System (GPS) can be applied in a number of ways to track remote sensing satellites at altitudes below 3000 km with accuracies of better than 10 cm. All techniques use a precise global network of GPS ground receivers operating in concert with a receiver aboard the user satellite, and all estimate the user orbit, GPS orbits, and selected ground locations simultaneously. The GPS orbit solutions are always dynamic, relying on the laws of motion, while the user orbit solution can range from purely dynamic to purely kinematic (geometric). Two variations show considerable promise. The first one features an optimal synthesis of dynamics and kinematics in the user solution, while the second introduces a novel gravity model adjustment technique to exploit data from repeat ground tracks. These techniques, to be demonstrated on the Topex/Poseidon mission in 1992, will offer subdecimeter tracking accuracy for dynamically unpredictable satellites down to the lowest orbital altitudes.

Periodicity and global exponential stability of generalized Cohen-Grossberg neural networks with discontinuous activations and mixed delays.

PubMed

Wang, Dongshu; Huang, Lihong

2014-03-01

In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen-Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and the fixed point theorem of multi-valued maps, the existence of periodic solutions for the neural networks is obtained. After that, we derive some sufficient conditions for the global exponential stability and convergence of the neural networks, in terms of nonsmooth analysis theory with generalized Lyapunov approach. Without assuming the boundedness (or the growth condition) and monotonicity of the discontinuous neuron activation functions, our results will also be valid. Moreover, our results extend previous works not only on discrete time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete time-varying and distributed delayed neural networks with discontinuous activations. We give some numerical examples to show the applicability and effectiveness of our main results. Copyright © 2013 Elsevier Ltd. All rights reserved.

Discourse, ideas and power in global health policy networks: political attention for maternal and child health in the millennium development goal era.

PubMed

McDougall, Lori

2016-05-18

Maternal and child health issues have gained global political attention and resources in the past 10 years, due in part to their prominence on the Millennium Development Goal agenda and the use of evidence-based advocacy by policy networks. This paper identifies key factors for this achievement, and raises questions about prospective challenges for sustaining attention in the transition to the post-2015 Sustainable Development Goals, far broader in scope than the Millennium Development Goals. This paper relies on participant observation methods and document analysis to develop a case study of the behaviours of global maternal and child health advocacy networks during 2005-2015. The development of coordinated networks of heterogeneous actors facilitated the rise in attention to maternal and child health during the past 10 years. The strategic use of epidemiological and economic evidence by these networks enabled policy attention and promoted network cohesion. The time-bound opportunity of reaching the 2015 Millennium Development Goals created a window of opportunity for joint action. As the new post-2015 goals emerge, networks seek to sustain attention by repositioning their framing of issues, network structures, and external alliances, including with networks that lay both inside and outside of the health domain. Issues rise on global policy agendas because of how ideas are constructed, portrayed and positioned by actors within given contexts. Policy networks play a critical role by uniting stakeholders to promote persuasive ideas about policy problems and solutions. The behaviours of networks in issue-framing, member-alignment, and strategic outreach can force open windows of opportunity for political attention -- or prevent them from closing.

Near-optimal strategies for sub-decimeter satellite tracking with GPS

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong

1986-01-01

Decimeter tracking of low Earth orbiters using differential Global Positioning System (GPS) techniques is discussed. A precisely known global network of GPS ground receivers and a receiver aboard the user satellite are needed, and all techniques simultaneously estimate the user and GPS satellite orbits. Strategies include a purely geometric, a fully dynamic, and a hybrid strategy. The last combines dynamic GPS solutions with a geometric user solution. Two powerful extensions of the hybrid strategy show the most promise. The first uses an optimized synthesis of dynamics and geometry in the user solution, while the second uses a gravity adjustment method to exploit data from repeat ground tracks. These techniques promise to deliver subdecimeter accuracy down to the lowest satellite altitudes.

Solutions Network Formulation Report. The Potential Contributions of the Global Precipitation Measurement Mission to Estuary Management in Acadia National Park

NASA Technical Reports Server (NTRS)

Anderson, Daniel; Hilbert, Kent; Lewis, David

2007-01-01

This candidate solution suggests the use of GPM precipitation observations to enhance the Acadia National Park NLERDSS. Simulated GPM data should provide measurements that would enable analysis of how precipitation affects runoff and nutrient load in the park?s wetlands. This solution benefits society by aiding park and resource managers in making predictions based on hypothetical changes and in identifying effective mitigation scenarios. This solution supports the Coastal Management, Water Management, and Ecological Forecasting National Applications.

Wireless sensor networks to assess the impacts of global change in Sierra Nevada (Spain) mountains

NASA Astrophysics Data System (ADS)

Sánchez-Cano, Francisco M.; Bonet-García, Francisco J.; Pérez-Luque, Antonio J.; Suárez-Muñoz, María

2017-04-01

Sierra Nevada Global Change Observatory (southern Spain) aims to improve the ability of ecosystems to address the impacts of global change. To this end, a monitoring program has been implemented based on the collection of long time series on a multitude of biophysical variables. This initiative is part of the Long Term Ecological Research network and is connected to similar ones at national and international level. One of the specific objectives of this LTER site is to improve understanding of the relationships between abiotic factors and ecosystem functioning / structure. Wireless sensor networks are a key instrument for achieving this aim. This contribution describes the design and management of a sensor network that is intended to monitor several biophysical variables with high temporal and spatial resolution in Quercus pyrenaica forests located in this mountain region. The following solution has been adopted in order to obtain the observational data (physical and biological variables). The biological variables will be monitored by PAR sensors (photosynthetically active radiation), and the physical variables will be acquired by a meteorological station and a sensor network composed of temperature and soil moisture sensors, as well as air temperature and humidity ones. To complete the monitoring of the biological variables, a NDVI (Normalized Difference Vegetation Index) camera will be deployed focusing to a Quercus pyrenaica forest from the opposite slope. It should be noted that all monitoring systems exposed will be powered by solar energy. The management of the sensor network covers the deployment of more than 100 sensors, guaranteeing both remote accessibility and reliability of the data. The chosen solution is provided by the company Adevice whose ONE-GO communication system ensures a consistent and efficient sending of those values read by the different sensors towards a central point, from where the information (RAW data) is accessible through WiFi/3G. RAW data is dumped daily in our data center for further processing with the open source software Get-IT. Get-IT was developed by the CNR (National Research Council of Italy) in the context of the RITMARE Flagship Project and LifeWatch Italy in order to combine geographic information with observational data by coupling GeoNode with SOS implementation by 52° North. This solution conforms to our requirements for two reasons, the first is that it provides data persistence, metadata editing and data visualisation tools. The second is that it is the solution adopted by LTER, platform previously mentioned in which we are integrated. This research has been funded by eLTER (Integrated European Long-Term Ecosystem & Socio-Ecological Research Infrastructure) Horizon 2020 EU project, and Sierra Nevada Global Change Observatory (LTER-site).

From the physics of interacting polymers to optimizing routes on the London Underground

PubMed Central

Yeung, Chi Ho; Saad, David; Wong, K. Y. Michael

2013-01-01

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise. PMID:23898198

From the physics of interacting polymers to optimizing routes on the London Underground.

PubMed

Yeung, Chi Ho; Saad, David; Wong, K Y Michael

2013-08-20

Optimizing paths on networks is crucial for many applications, ranging from subway traffic to Internet communication. Because global path optimization that takes account of all path choices simultaneously is computationally hard, most existing routing algorithms optimize paths individually, thus providing suboptimal solutions. We use the physics of interacting polymers and disordered systems to analyze macroscopic properties of generic path optimization problems and derive a simple, principled, generic, and distributed routing algorithm capable of considering all individual path choices simultaneously. We demonstrate the efficacy of the algorithm by applying it to: (i) random graphs resembling Internet overlay networks, (ii) travel on the London Underground network based on Oyster card data, and (iii) the global airport network. Analytically derived macroscopic properties give rise to insightful new routing phenomena, including phase transitions and scaling laws, that facilitate better understanding of the appropriate operational regimes and their limitations, which are difficult to obtain otherwise.

New solutions for climate network visualization

NASA Astrophysics Data System (ADS)

Nocke, Thomas; Buschmann, Stefan; Donges, Jonathan F.; Marwan, Norbert

2016-04-01

An increasing amount of climate and climate impact research methods deals with geo-referenced networks, including energy, trade, supply-chain, disease dissemination and climatic tele-connection networks. At the same time, the size and complexity of these networks increases, resulting in networks of more than hundred thousand or even millions of edges, which are often temporally evolving, have additional data at nodes and edges, and can consist of multiple layers even in real 3D. This gives challenges to both the static representation and the interactive exploration of these networks, first of all avoiding edge clutter ("edge spagetti") and allowing interactivity even for unfiltered networks. Within this presentation, we illustrate potential solutions to these challenges. Therefore, we give a glimpse on a questionnaire performed with climate and complex system scientists with respect to their network visualization requirements, and on a review of available state-of-the-art visualization techniques and tools for this purpose (see as well Nocke et al., 2015). In the main part, we present alternative visualization solutions for several use cases (global, regional, and multi-layered climate networks) including alternative geographic projections, edge bundling, and 3-D network support (based on CGV and GTX tools), and implementation details to reach interactive frame rates. References: Nocke, T., S. Buschmann, J. F. Donges, N. Marwan, H.-J. Schulz, and C. Tominski: Review: Visual analytics of climate networks, Nonlinear Processes in Geophysics, 22, 545-570, doi:10.5194/npg-22-545-2015, 2015

A Microcomputer-Based Network Optimization Package.

DTIC Science & Technology

1981-09-01

from either cases a or c as Truncated-Newton directions. It can be shown [Ref. 27] that the TNCG algorithm is globally convergent and capable of...nonzero values of LGB indicate bounds at which arcs are fixed or reversed. Fixed arcs have negative T ( ) while free arcs have positive T ( ) values...Solution of Generalized Network Problems," Working Paper, Department of Finance and Business Economics , School of Business , University of Southern

A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks.

PubMed

Gallos, Lazaros K; Makse, Hernán A; Sigman, Mariano

2012-02-21

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are "large-world" self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the "strength of weak ties" crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain.

A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks

PubMed Central

Gallos, Lazaros K.; Makse, Hernán A.; Sigman, Mariano

2012-01-01

The human brain is organized in functional modules. Such an organization presents a basic conundrum: Modules ought to be sufficiently independent to guarantee functional specialization and sufficiently connected to bind multiple processors for efficient information transfer. It is commonly accepted that small-world architecture of short paths and large local clustering may solve this problem. However, there is intrinsic tension between shortcuts generating small worlds and the persistence of modularity, a global property unrelated to local clustering. Here, we present a possible solution to this puzzle. We first show that a modified percolation theory can define a set of hierarchically organized modules made of strong links in functional brain networks. These modules are “large-world” self-similar structures and, therefore, are far from being small-world. However, incorporating weaker ties to the network converts it into a small world preserving an underlying backbone of well-defined modules. Remarkably, weak ties are precisely organized as predicted by theory maximizing information transfer with minimal wiring cost. This trade-off architecture is reminiscent of the “strength of weak ties” crucial concept of social networks. Such a design suggests a natural solution to the paradox of efficient information flow in the highly modular structure of the brain. PMID:22308319

Convergence dynamics and pseudo almost periodicity of a class of nonautonomous RFDEs with applications

NASA Astrophysics Data System (ADS)

Fan, Meng; Ye, Dan

2005-09-01

This paper studies the dynamics of a system of retarded functional differential equations (i.e., RF=Es), which generalize the Hopfield neural network models, the bidirectional associative memory neural networks, the hybrid network models of the cellular neural network type, and some population growth model. Sufficient criteria are established for the globally exponential stability and the existence and uniqueness of pseudo almost periodic solution. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. The paper ends with some applications of the main results to some neural network models and population growth models and numerical simulations.

Hybrid genetic algorithm in the Hopfield network for maximum 2-satisfiability problem

NASA Astrophysics Data System (ADS)

Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf

2017-08-01

Heuristic method was designed for finding optimal solution more quickly compared to classical methods which are too complex to comprehend. In this study, a hybrid approach that utilizes Hopfield network and genetic algorithm in doing maximum 2-Satisfiability problem (MAX-2SAT) was proposed. Hopfield neural network was used to minimize logical inconsistency in interpretations of logic clauses or program. Genetic algorithm (GA) has pioneered the implementation of methods that exploit the idea of combination and reproduce a better solution. The simulation incorporated with and without genetic algorithm will be examined by using Microsoft Visual 2013 C++ Express software. The performance of both searching techniques in doing MAX-2SAT was evaluate based on global minima ratio, ratio of satisfied clause and computation time. The result obtained form the computer simulation demonstrates the effectiveness and acceleration features of genetic algorithm in doing MAX-2SAT in Hopfield network.

A New Stochastic Technique for Painlevé Equation-I Using Neural Network Optimized with Swarm Intelligence

PubMed Central

Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Ahmad, Siraj-ul-Islam; Qureshi, Ijaz Mansoor

2012-01-01

A methodology for solution of Painlevé equation-I is presented using computational intelligence technique based on neural networks and particle swarm optimization hybridized with active set algorithm. The mathematical model of the equation is developed with the help of linear combination of feed-forward artificial neural networks that define the unsupervised error of the model. This error is minimized subject to the availability of appropriate weights of the networks. The learning of the weights is carried out using particle swarm optimization algorithm used as a tool for viable global search method, hybridized with active set algorithm for rapid local convergence. The accuracy, convergence rate, and computational complexity of the scheme are analyzed based on large number of independents runs and their comprehensive statistical analysis. The comparative studies of the results obtained are made with MATHEMATICA solutions, as well as, with variational iteration method and homotopy perturbation method. PMID:22919371

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Experiments in Reconstructing Twentieth-Century Sea Levels

NASA Technical Reports Server (NTRS)

Ray, Richard D.; Douglas, Bruce C.

2011-01-01

One approach to reconstructing historical sea level from the relatively sparse tide-gauge network is to employ Empirical Orthogonal Functions (EOFs) as interpolatory spatial basis functions. The EOFs are determined from independent global data, generally sea-surface heights from either satellite altimetry or a numerical ocean model. The problem is revisited here for sea level since 1900. A new approach to handling the tide-gauge datum problem by direct solution offers possible advantages over the method of integrating sea-level differences, with the potential of eventually adjusting datums into the global terrestrial reference frame. The resulting time series of global mean sea levels appears fairly insensitive to the adopted set of EOFs. In contrast, charts of regional sea level anomalies and trends are very sensitive to the adopted set of EOFs, especially for the sparser network of gauges in the early 20th century. The reconstructions appear especially suspect before 1950 in the tropical Pacific. While this limits some applications of the sea-level reconstructions, the sensitivity does appear adequately captured by formal uncertainties. All our solutions show regional trends over the past five decades to be fairly uniform throughout the global ocean, in contrast to trends observed over the shorter altimeter era. Consistent with several previous estimates, the global sea-level rise since 1900 is 1.70 +/- 0.26 mm/yr. The global trend since 1995 exceeds 3 mm/yr which is consistent with altimeter measurements, but this large trend was possibly also reached between 1935 and 1950.

Unified Alignment of Protein-Protein Interaction Networks.

PubMed

Malod-Dognin, Noël; Ban, Kristina; Pržulj, Nataša

2017-04-19

Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.

Dynamic analysis of a stochastic delayed rumor propagation model

NASA Astrophysics Data System (ADS)

Jia, Fangju; Lv, Guangying; Wang, Shuangfeng; Zou, Guang-an

2018-02-01

The rapid development of the Internet, especially the emergence of the social networks, has led rumor propagation into a new media era. In this paper, we are concerned with a stochastic delayed rumor propagation model. Firstly, we obtain the existence of the global solution. Secondly, sufficient conditions for extinction of the rumor are established. Lastly, the boundedness of solution is proved and some simulations are given to verify our results.

Point Positioning Service for Natural Hazard Monitoring

NASA Astrophysics Data System (ADS)

Bar-Sever, Y. E.

2014-12-01

In an effort to improve natural hazard monitoring, JPL has invested in updating and enlarging its global real-time GNSS tracking network, and has launched a unique service - real-time precise positioning for natural hazard monitoring, entitled GREAT Alert (GNSS Real-Time Earthquake and Tsunami Alert). GREAT Alert leverages the full technological and operational capability of the JPL's Global Differential GPS System [www.gdgps.net] to offer owners of real-time dual-frequency GNSS receivers: Sub-5 cm (3D RMS) real-time, absolute positioning in ITRF08, regardless of location Under 5 seconds turnaround time Full covariance information Estimates of ancillary parameters (such as troposphere) optionally provided This service enables GNSS networks operators to instantly have access to the most accurate and reliable real-time positioning solutions for their sites, and also to the hundreds of participating sites globally, assuring inter-consistency and uniformity across all solutions. Local authorities with limited technical and financial resources can now access to the best technology, and share environmental data to the benefit of the entire pacific region. We will describe the specialized precise point positioning techniques employed by the GREAT Alert service optimized for natural hazard monitoring, and in particular Earthquake monitoring. We address three fundamental aspects of these applications: 1) small and infrequent motion, 2) the availability of data at a central location, and 3) the need for refined solutions at several time scales

A new graph-based method for pairwise global network alignment

PubMed Central

Klau, Gunnar W

2009-01-01

Background In addition to component-based comparative approaches, network alignments provide the means to study conserved network topology such as common pathways and more complex network motifs. Yet, unlike in classical sequence alignment, the comparison of networks becomes computationally more challenging, as most meaningful assumptions instantly lead to NP-hard problems. Most previous algorithmic work on network alignments is heuristic in nature. Results We introduce the graph-based maximum structural matching formulation for pairwise global network alignment. We relate the formulation to previous work and prove NP-hardness of the problem. Based on the new formulation we build upon recent results in computational structural biology and present a novel Lagrangian relaxation approach that, in combination with a branch-and-bound method, computes provably optimal network alignments. The Lagrangian algorithm alone is a powerful heuristic method, which produces solutions that are often near-optimal and – unlike those computed by pure heuristics – come with a quality guarantee. Conclusion Computational experiments on the alignment of protein-protein interaction networks and on the classification of metabolic subnetworks demonstrate that the new method is reasonably fast and has advantages over pure heuristics. Our software tool is freely available as part of the LISA library. PMID:19208162

TIGA Tide Gauge Data Reprocessing at GFZ

NASA Astrophysics Data System (ADS)

Deng, Zhiguo; Schöne, Tilo; Gendt, Gerd

2014-05-01

To analyse the tide gauge measurements for the purpose of global long-term sea level change research a well-defined absolute reference frame is required by oceanographic community. To create such frame the data from a global GNSS network located at or near tide gauges are processed. For analyzing the GNSS data on a preferably continuous basis the International GNSS Service (IGS) Tide Gauge Benchmark Monitoring Working Group (TIGA-WG) is responsible. As one of the TIGA Analysis Centers the German Research Centre for Geosciences (GFZ) is contributing to the IGS TIGA Reprocessing Campaign. The solutions of the TIGA Reprocessing Campaign will also contribute to 2nd IGS Data Reprocessing Campaign with GFZ IGS reprocessing solution. After the first IGS reprocessing finished in 2010 some improvements were implemented into the latest GFZ software version EPOS.P8: reference frame IGb08 based on ITRF2008, antenna calibration igs08.atx, geopotential model (EGM2008), higher-order ionospheric effects, new a priori meteorological model (GPT2), VMF mapping function, and other minor improvements. GPS data of the globally distributed tracking network of 794 stations for the time span from 1994 until end of 2012 are used for the TIGA reprocessing. To handle such large network a new processing strategy is developed and described in detail. In the TIGA reprocessing the GPS@TIGA data are processed in precise point positioning (PPP) mode to clean data using the IGS reprocessing orbit and clock products. To validate the quality of the PPP coordinate results the rates of 80 GPS@TIGA station vertical movement are estimated from the PPP results using Maximum Likelihood Estimation (MLE) method. The rates are compared with the solution of University of LaRochelle Consortium (ULR) (named ULR5). 56 of the 80 stations have a difference of the vertical velocities below 1 mm/yr. The error bars of PPP rates are significant larger than those of ULR5, which indicates large time correlated noise in the PPP solutions.

Data management for the internet of things: design primitives and solution.

PubMed

Abu-Elkheir, Mervat; Hayajneh, Mohammad; Ali, Najah Abu

2013-11-14

The Internet of Things (IoT) is a networking paradigm where interconnected, smart objects continuously generate data and transmit it over the Internet. Much of the IoT initiatives are geared towards manufacturing low-cost and energy-efficient hardware for these objects, as well as the communication technologies that provide objects interconnectivity. However, the solutions to manage and utilize the massive volume of data produced by these objects are yet to mature. Traditional database management solutions fall short in satisfying the sophisticated application needs of an IoT network that has a truly global-scale. Current solutions for IoT data management address partial aspects of the IoT environment with special focus on sensor networks. In this paper, we survey the data management solutions that are proposed for IoT or subsystems of the IoT. We highlight the distinctive design primitives that we believe should be addressed in an IoT data management solution, and discuss how they are approached by the proposed solutions. We finally propose a data management framework for IoT that takes into consideration the discussed design elements and acts as a seed to a comprehensive IoT data management solution. The framework we propose adapts a federated, data- and sources-centric approach to link the diverse Things with their abundance of data to the potential applications and services that are envisioned for IoT.

Data Management for the Internet of Things: Design Primitives and Solution

PubMed Central

Abu-Elkheir, Mervat; Hayajneh, Mohammad; Ali, Najah Abu

2013-01-01

The Internet of Things (IoT) is a networking paradigm where interconnected, smart objects continuously generate data and transmit it over the Internet. Much of the IoT initiatives are geared towards manufacturing low-cost and energy-efficient hardware for these objects, as well as the communication technologies that provide objects interconnectivity. However, the solutions to manage and utilize the massive volume of data produced by these objects are yet to mature. Traditional database management solutions fall short in satisfying the sophisticated application needs of an IoT network that has a truly global-scale. Current solutions for IoT data management address partial aspects of the IoT environment with special focus on sensor networks. In this paper, we survey the data management solutions that are proposed for IoT or subsystems of the IoT. We highlight the distinctive design primitives that we believe should be addressed in an IoT data management solution, and discuss how they are approached by the proposed solutions. We finally propose a data management framework for IoT that takes into consideration the discussed design elements and acts as a seed to a comprehensive IoT data management solution. The framework we propose adapts a federated, data- and sources-centric approach to link the diverse Things with their abundance of data to the potential applications and services that are envisioned for IoT. PMID:24240599

Evaluation of Tools for Protection of Interest against Hacking and Cracking

NASA Astrophysics Data System (ADS)

Jahankhani, Hossein; Antonijevic, Branko; Walcott, Terry

The internet considered a tool that effectively ensures communication globally has been hindered by hackers and crackers continuously. In so doing, a multitude of network facilitated tools such as firewalls, virtual private networks (VPN) and a variety of antivirus software packages has been enabled for dealing with such predicaments. However, more often than not these facilitated tools are marketed as perfect solutions to the ever culminating problems such as loss of data and privacy in networked and world wide intercommunications. We provide a forum for addressing these perceived problems in this paper.

Regulation of Dynamical Systems to Optimal Solutions of Semidefinite Programs: Algorithms and Applications to AC Optimal Power Flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

2015-07-01

This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the controlmore » of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.« less

Transforming LandWarNet: Implementing the Enterprise Strategy

DTIC Science & Technology

2010-08-01

Prescribed by ANSI Std Z39-18 2 HHH HHH 3 Over the past decade, the United States’ global defense posture has...when they need it, in any environment. n HHH A Soldier’s Story HHH 4 LandWarNet is the Army’s solution to this enterprise network requirement...Architecture HHH LandWarNet HHH 5 To form a truly unified enterprise network, demarcated only by classification enclaves, the Army must change its

Urban Water Innovation Network (UWIN): Transitioning Toward Sustainbale Urban Water Systems

NASA Astrophysics Data System (ADS)

Arabi, M.

2015-12-01

City water systems are at risk of disruption from global social and environmental hazards, which could have deleterious effects on human health, property, and loss of critical infrastructure. The Urban Water Innovation Network (UWIN), a consortium of 14 academic institutions and other key partners across the U.S., is working to address challenges that threaten urban water systems across the nation. UWIN's mission is to create technological, institutional and management solutions to help communities increase the resilience of their water systems and enhance their preparedness for responding to water crisis. The network seeks solutions that achieve widespread adoption consistent with inclusive, equitable and sustainable urban development. The integrative and adaptive analysis framework of UWIN is presented. The framework identifies a toolbox of sustainable solutions by simultaneously minimizing pressures, enhancing resilience to extreme events, and maximizing cobenefits. The benefits of sustainable urban water solutions for linked urban ecosystems, economies, and arrangements for environmental justice and social equity, will be discussed. The network encompasses six U.S. regions with varying ecohydrologic and climatic regimes ranging from the coastal moist mid-latitude climates of the Mid-Atlantic to the subtropical semi-arid deserts of the Southwest. These regions also represent a wide spectrum of demographic, cultural, and policy settings. The opportunities for cross-site assessments that facilitate the exploration of locally appropriate solutions across regions undergoing various development trajectories will be discussed.

A Small World of Neuronal Synchrony

PubMed Central

Yu, Shan; Huang, Debin; Singer, Wolf

2008-01-01

A small-world network has been suggested to be an efficient solution for achieving both modular and global processing—a property highly desirable for brain computations. Here, we investigated functional networks of cortical neurons using correlation analysis to identify functional connectivity. To reconstruct the interaction network, we applied the Ising model based on the principle of maximum entropy. This allowed us to assess the interactions by measuring pairwise correlations and to assess the strength of coupling from the degree of synchrony. Visual responses were recorded in visual cortex of anesthetized cats, simultaneously from up to 24 neurons. First, pairwise correlations captured most of the patterns in the population's activity and, therefore, provided a reliable basis for the reconstruction of the interaction networks. Second, and most importantly, the resulting networks had small-world properties; the average path lengths were as short as in simulated random networks, but the clustering coefficients were larger. Neurons differed considerably with respect to the number and strength of interactions, suggesting the existence of “hubs” in the network. Notably, there was no evidence for scale-free properties. These results suggest that cortical networks are optimized for the coexistence of local and global computations: feature detection and feature integration or binding. PMID:18400792

Securing the Global Airspace System Via Identity-Based Security

NASA Technical Reports Server (NTRS)

Ivancic, William D.

2015-01-01

Current telecommunications systems have very good security architectures that include authentication and authorization as well as accounting. These three features enable an edge system to obtain access into a radio communication network, request specific Quality-of-Service (QoS) requirements and ensure proper billing for service. Furthermore, the links are secure. Widely used telecommunication technologies are Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) This paper provides a system-level view of network-centric operations for the global airspace system and the problems and issues with deploying new technologies into the system. The paper then focuses on applying the basic security architectures of commercial telecommunication systems and deployment of federated Authentication, Authorization and Accounting systems to provide a scalable, evolvable reliable and maintainable solution to enable a globally deployable identity-based secure airspace system.

A New Global Vertical Land Movement Data Set from the TIGA Combined Solution

NASA Astrophysics Data System (ADS)

Hunegnaw, Addisu; Teferle, Felix Norman; Ebuy Abraha, Kibrom; Santamaría-Gómez, Alvaro; Gravelle, Médéric; Wöppelman, Guy; Schöne, Tilo; Deng, Zhiguo; Bingley, Richard; Hansen, Dionne Nicole; Sanchez, Laura; Moore, Michael; Jia, Minghai

2017-04-01

Globally averaged sea level has been estimated from the network of tide gauges installed around the world since the 19th century. These mean sea level (MSL) records provide sea level relative to a nearby tide gauge benchmark (TGBM), which allows for the continuation of the instrumental record in time. Any changes in the benchmark levels, induced by vertical land movements (VLM) affect the MSL records and hence sea level estimates. Over the last two decades sea level has also been observed using satellite altimeters. While the satellite observations are globally more homogeneous providing a picture of sea level not confined to coastlines, they require the VLM-corrected MSL records for the bias calibration of instrumental drifts. Without this calibration altimeter instruments from different missions cannot be combined. GPS has made it possible to obtain highly accurate estimates of VLM in a geocentric reference frame for stations at or close to tide gauges. Under the umbrella of the International GNSS Service (IGS), the Tide Gauge Benchmark Monitoring (TIGA) Working Group (WG) has been established to apply the expertise of the GNSS community to solving issues related to the accuracy and reliability of the vertical component to provide estimates of VLM in a well-defined global reference frame. To achieve this objective, five TIGA Analysis Centers (TACs) contributed re-processed global GPS network solutions to TIGA, employing the latest bias models and processing strategies in accordance with the second re-processing campaign (repro2) of the IGS. These solutions include those of the British Isles continuous GNSS Facility - University of Luxembourg consortium (BLT), the German Research Centre for Geosciences (GFZ) Potsdam, the German Geodetic Research Institute (DGF) at the Technical University of Munich, Geoscience Australia (AUT) and the University of La Rochelle (ULR). In this study we present to the sea level community an evaluation of the VLM estimates from the first combined solution from the IGS TIGA WG. The TAC solutions include more than 700 stations and span the common period 1995-2014. The combined solution was computed by the TIGA Combination Centre (TCC) at the University of Luxembourg, which used the Combination and Analysis of Terrestrial Reference Frame (CATREF) software package for this purpose. This first solution forms Release 1.0 and further releases will be made available after further reprocessing campaigns. We evaluate the combined solution internally using the TAC solutions and externally using solutions from the IGS and the ITRF2008. The derived VLM estimates have undergone an initial evaluation and should be considered as the primary TIGA product for the sea level community to correct MSL records for land level changes.

Rapid determination of global moment-tensor solutions

USGS Publications Warehouse

Sipkin, S.A.

1994-01-01

In an effort to improve data services, the National Earthquake Information Center has begun a program, in cooperation with the Incorporated Research Institutions for Seismology Data Management Center (IRIS DMC), to produce rapid estimates of the seismic moment tensor for most earthquakes with a bodywave magnitude of 5.8 or greater. An estimate of the moment tensor can usually be produced within 20 minutes of the arrival of the broadband P-waveform data from the IRIS DMC. The solutions do not vary significantly from the final solutions determined using the entire network. -from Author

Dragon pulse information management system (DPIMS): A unique model-based approach to implementing domain agnostic system of systems and behaviors

NASA Astrophysics Data System (ADS)

Anderson, Thomas S.

2016-05-01

The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.

SIRGAS: ITRF densification in Latin America and the Caribbean

NASA Astrophysics Data System (ADS)

Brunini, C.; Costa, S.; Mackern, V.; Martínez, W.; Sánchez, L.; Seemüller, W.; da Silva, A.

2009-04-01

The continental reference frame of SIRGAS (Sistema de Referencia Geocéntrico para las Américas) is at present realized by the SIRGAS Continuously Operating Network (SIRGAS-CON) composed by about 200 stations distributed over all Latin America and the Caribbean. SIRGAS member countries are qualifying their national reference frames by installing continuously operating GNSS stations, which have to be consistently integrated into the continental network. As the number of these stations is rapidly increasing, the processing strategy of the SIRGAS-CON network was redefined during the SIRGAS 2008 General Meeting in May 2008. The new strategy relies upon the definition of two hierarchy levels: a) A core network (SIRGAS-CON-C) with homogeneous continental coverage and stabile site locations ensures the long-term stability of the reference frame and provides the primary link to the ITRS. Stations belonging to this network have been selected so that each country contributes with a number of stations defined according to its surface and guarantying that the selected stations are the best in operability, continuity, reliability, and geographical coverage. b) Several densification sub-networks (SIRGAS-CON-D) improve the accessibility to the reference frame. The SIRGAS-CON-D sub-networks shall correspond to the national reference frames, i.e., as an optimum there shall be as many sub-networks as countries in the region. The goal is that each country processes its own continuously stations following the SIRGAS processing guidelines, which are defined in accordance with the IERS and IGS standards and conventions. Since at present not all of the countries are operating a processing centre, the existing stations are classified in three densification networks (a Northern, a middle, and a Southern one), which are processed by three local processing centres until new ones are installed. As SIRGAS is defined as a densification of the ITRS, stations included in the core network, as well as in the densification sub-networks match the requirements, characteristics, and processing performance of the ITRF. The SIRGAS-CON-C network is processed by DGFI (Deutsches Geodätisches Forschungsinstitut, Germany) as the IGS-RNAAC-SIR. The Local Processing Centres are for the Northern sub-network IGAC (Instituto Geográfico Augustín Codazzi, Colombia), for the middle sub-network IBGE (Instituto Brasileiro de Geografia e Estátistica, Brazil), and for the Southern sub-network IGG-CIMA (Instituto de Geodesia y Geodinámica, Universidad Nacional de Cuyo, Argentina). These four Processing Centres deliver loosely constrained weekly solutions for station coordinates (i.e., satellite orbits, satellite clock offsets, and Earth orientation parameters are fixed to the final weekly IGS solutions and coordinates for all sites are constrained to 1 m). The individual contributions are integrated in a unified solution by the SIRGAS Combination Centres (DGFI and IBGE) according to the following strategy: 1) Individual solutions are reviewed/corrected for possible format problems, data inconsistencies, etc. 2) Constraints imposed in the delivered normal equations are removed. 3) Sub-networks are individually aligned to the IGS05 reference frame by applying the No Net Rotation (NNR) and No Net Translation (NNT) conditions. 4) Coordinates obtained in (3) for each sub-network are compared to IGS05 values and to each other in order to identify possible outliers. 5) Stations with large residuals (more than 10 mm in the N-E component, and more than 20 mm in the Up component) are reduced from the normal equations. Steps (3), (4), and (5) are done iteratively. 6) Since at present the four Analysis Centres are processing GPS observations only and all of them use the Bernese Software for computing weekly solutions, relative weighting factors are not applied in the combination. 7) Individual normal equations are accumulated and solved for computing a loosely constrained weekly solution for station coordinates (i.e., coordinates for all stations are constrained to 1 m). This solution in SINEX format is submitted to IGS for the global polyhedron. 8) Combination obtained in (7) is constrained by applying NNR+NNT conditions with respect to the IGS05 stations included the SIRGAS region to provide constrained coordinates for all SIRGAS-CON (core + densification) stations. The applied IGS05 reference coordinates correspond to the weekly IGS solution for the global network, i.e., coordinates included in the igsYYPwwww.snx files. This constrained solution provides the final weekly SIRGAS-CON coordinates for practical applications. The DGFI (i.e. IGS RNAAC SIR) weekly combinations are delivered to the IGS Data Centres for combination in the global polyhedron, and made available for users as official SIRGAS products, respectively. The IBGE weekly combinations provide control and back-up. The above described analysis strategy is applied since GPS week 1495. Before (since June 1996 to August 2008), the SIRGAS-CON network was totally processed by DGFI. Until now, results show a very good agreement with previous computations; however, the present sub-networks distribution has two main disadvantages: 1) Not all SIRGAS-CON stations are included in the same number of individual solutions, i.e., they are unequally weighted in the weekly combinations, and 2) since there are not enough Local Processing Centres, the required redundancy (each station processed by at least three processing centres) is not fulfilled. Therefore, efforts are being made to install additional Local Processing Centres in Latin American countries as Argentina, Ecuador, Mexico, Peru, Uruguay, and Venezuela.

Competition among networks highlights the power of the weak

PubMed Central

Iranzo, Jaime; Buldú, Javier M.; Aguirre, Jacobo

2016-01-01

The unpreventable connections between real networked systems have recently called for an examination of percolation, diffusion or synchronization phenomena in multilayer networks. Here we use network science and game theory to explore interactions in networks-of-networks and model these as a game for gaining importance. We propose a viewpoint where networks choose the connection strategies, in contrast with classical approaches where nodes are the active players. Specifically, we investigate how creating paths between networks leads to different Nash equilibria that determine their structural and dynamical properties. In a wide variety of cases, selecting adequate connections leads to a cooperative solution that allows weak networks to overcome the strongest opponent. Counterintuitively, each weak network can induce a global transition to such cooperative configuration regardless of the actions of the strongest network. This power of the weak reveals a critical dominance of the underdogs in the fate of networks-of-networks. PMID:27841258

A new neural network model for solving random interval linear programming problems.

PubMed

Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza

2017-05-01

This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mobility management techniques for the next-generation wireless networks

NASA Astrophysics Data System (ADS)

Sun, Junzhao; Howie, Douglas P.; Sauvola, Jaakko J.

2001-10-01

The tremendous demands from social market are pushing the booming development of mobile communications faster than ever before, leading to plenty of new advanced techniques emerging. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Mobility management is an important issue in the area of mobile communications, which can be best solved at the network layer. One of the key features of the next generation wireless networks is all-IP infrastructure. This paper discusses the mobility management schemes for the next generation mobile networks through extending IP's functions with mobility support. A global hierarchical framework model for the mobility management of wireless networks is presented, in which the mobility management is divided into two complementary tasks: macro mobility and micro mobility. As the macro mobility solution, a basic principle of Mobile IP is introduced, together with the optimal schemes and the advances in IPv6. The disadvantages of the Mobile IP on solving the micro mobility problem are analyzed, on the basis of which three main proposals are discussed as the micro mobility solutions for mobile communications, including Hierarchical Mobile IP (HMIP), Cellular IP, and Handoff-Aware Wireless Access Internet Infrastructure (HAWAII). A unified model is also described in which the different micro mobility solutions can coexist simultaneously in mobile networks.

Densification of the ITRF through the weekly combination of regional and global GNSS solutions

NASA Astrophysics Data System (ADS)

Legrand, J.; Bruyninx, C.; Saria, E.; Griffiths, J.; Craymer, M. R.; Dawson, J. H.; Kenyeres, A.; Santamaría-Gómez, A.; Sanchez, L.; Altamimi, Z.

2012-12-01

The IAG Working Group (WG) "Integration of Dense Velocity Fields in the ITRF" was created in 2011 as a follow-up of the WG "Regional Dense Velocity Fields" (2007-2011). The goal of the WG is to densify the International Terrestrial Reference Frame (ITRF) using regional GNSS solutions as well as global solutions. This was originally done by combining several cumulative position/velocity solutions submitted to the WG by the global analysis center (ULR) and the IAG regional reference frame sub-commissions (APREF, EUREF, SIRGAS, NAREF) analysis centers. However, several test combinations together with the comparison of the residual position time series demonstrated the limitations of this approach. In June 2012, the WG decided to adopt a new approach based on a weekly combination of the GNSS solutions. This new approach will enable us to mitigate network effects, have full control over the discontinuities and the velocity constraints, manage the different data spans and derive residual position time series in addition to a velocity field. All initial contributors have agreed to submit weekly solutions and in addition initial contacts have been made with other sub-commissions, particularly Africa, in order to extent the densified velocity field to all continents. Preliminary results of the analysis of weekly solutions will be presented. More details on the WG are available from http://epncb.oma.be/IAG/.

Plate tectonics from VLBI and SLR global data

NASA Technical Reports Server (NTRS)

Harrison, Christopher G. A.; Robaudo, Stefano

1992-01-01

This study is based on data derived from fifteen years of observations of the SLR (side-looking radar) network and six years of the VLBI (very long baseline interferometry) network. In order to use all available information VLBI and SLR global data sets were combined in a least squares fashion to calculate station horizontal velocities. All significant data pertaining to a single site contribute to the station horizontal motion. The only constraint on the solution is that no vertical motion is allowed. This restriction does not greatly affect the precision of the overall solution given the fact that the expected vertical motion for most stations, even those experiencing post glacial uplift, is well under 1 cm/yr. Since the average baseline is under 4,000 km, only a small fraction of the station vertical velocity is translated into baseline rates so that the error introduced in the solution by restricting up-down station movement is minimal. As a reference, station velocities were then compared to the ones predicted by the NUVEL-1 geological model of DeMets et al. (1990). The focus of the study is on analyzing these discrepancies for global plate tectonics as well as regional tectonic settings. The method used also allows us not only to derive horizontal motion for individual stations but also to calculate Euler vectors for those plates that have enough stations located on the stable interior like North America, Pacific, Eurasia, and Australia.

SPACEWAY: Providing affordable and versatile communication solutions

NASA Astrophysics Data System (ADS)

Fitzpatrick, E. J.

1995-08-01

By the end of this decade, Hughes' SPACEWAY network will provide the first interactive 'bandwidth on demand' communication services for a variety of applications. High quality digital voice, interactive video, global access to multimedia databases, and transborder workgroup computing will make SPACEWAY an essential component of the computer-based workplace of the 21st century. With relatively few satellites to construct, insure, and launch -- plus extensive use of cost-effective, tightly focused spot beams on the world's most populated areas -- the high capacity SPACEWAY system can pass its significant cost savings onto its customers. The SPACEWAY network is different from other proposed global networks in that its geostationary orbit location makes it a truly market driven system: each satellite will make available extensive telecom services to hundreds of millions of people within the continuous view of that satellite, providing immediate capacity within a specific region of the world.

SPACEWAY: Providing affordable and versatile communication solutions

NASA Technical Reports Server (NTRS)

Fitzpatrick, E. J.

1995-01-01

By the end of this decade, Hughes' SPACEWAY network will provide the first interactive 'bandwidth on demand' communication services for a variety of applications. High quality digital voice, interactive video, global access to multimedia databases, and transborder workgroup computing will make SPACEWAY an essential component of the computer-based workplace of the 21st century. With relatively few satellites to construct, insure, and launch -- plus extensive use of cost-effective, tightly focused spot beams on the world's most populated areas -- the high capacity SPACEWAY system can pass its significant cost savings onto its customers. The SPACEWAY network is different from other proposed global networks in that its geostationary orbit location makes it a truly market driven system: each satellite will make available extensive telecom services to hundreds of millions of people within the continuous view of that satellite, providing immediate capacity within a specific region of the world.

Programmable synaptic devices for electronic neural nets

NASA Technical Reports Server (NTRS)

Moopenn, A.; Thakoor, A. P.

1990-01-01

The architecture, design, and operational characteristics of custom VLSI and thin film synaptic devices are described. The devices include CMOS-based synaptic chips containing 1024 reprogrammable synapses with a 6-bit dynamic range, and nonvolatile, write-once, binary synaptic arrays based on memory switching in hydrogenated amorphous silicon films. Their suitability for embodiment of fully parallel and analog neural hardware is discussed. Specifically, a neural network solution to an assignment problem of combinatorial global optimization, implemented in fully parallel hardware using the synaptic chips, is described. The network's ability to provide optimal and near optimal solutions over a time scale of few neuron time constants has been demonstrated and suggests a speedup improvement of several orders of magnitude over conventional search methods.

Applications of neural network methods to the processing of earth observation satellite data.

PubMed

Loyola, Diego G

2006-03-01

The new generation of earth observation satellites carries advanced sensors that will gather very precise data for studying the Earth system and global climate. This paper shows that neural network methods can be successfully used for solving forward and inverse remote sensing problems, providing both accurate and fast solutions. Two examples of multi-neural network systems for the determination of cloud properties and for the retrieval of total columns of ozone using satellite data are presented. The developed algorithms based on multi-neural network are currently being used for the operational processing of European atmospheric satellite sensors and will play a key role in related satellite missions planed for the near future.

Distributed Grooming in Multi-Domain IP/MPLS-DWDM Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Qing

2009-12-01

This paper studies distributed multi-domain, multilayer provisioning (grooming) in IP/MPLS-DWDM networks. Although many multi-domain studies have emerged over the years, these have primarily considered 'homogeneous' network layers. Meanwhile, most grooming studies have assumed idealized settings with 'global' link state across all layers. Hence there is a critical need to develop practical distributed grooming schemes for real-world networks consisting of multiple domains and technology layers. Along these lines, a detailed hierarchical framework is proposed to implement inter-layer routing, distributed grooming, and setup signaling. The performance of this solution is analyzed in detail using simulation studies and future work directions are alsomore » high-lighted.« less

Are autonomous cities our urban future?

PubMed

Norman, Barbara

2018-05-29

Cities are rapidly expanding in size, wealth and power, with some now larger than nation states. Smart city solutions and strong global urban networks are developing to manage massive urban growth. However, cities exist within a wider system and it may take more than technological advances, innovation and city autonomy to develop a sustainable urban future.

Noise reduction in urban LRT networks by combining track based solutions.

PubMed

Vogiatzis, Konstantinos; Vanhonacker, Patrick

2016-10-15

The overall objective of the Quiet-Track project is to provide step-changing track based noise mitigation and maintenance schemes for railway rolling noise in LRT (Light Rail Transit) networks. WP 4 in particular focuses on the combination of existing track based solutions to yield a global performance of at least 6dB(A). The validation was carried out using a track section in the network of Athens Metro Line 1 with an existing outside concrete slab track (RHEDA track) where high airborne rolling noise was observed. The procedure for the selection of mitigation measures is based on numerical simulations, combining WRNOISE and IMMI software tools for noise prediction with experimental determination of the required track and vehicle parameters (e.g., rail and wheel roughness). The availability of a detailed rolling noise calculation procedure allows for detailed designing of measures and of ranking individual measures. It achieves this by including the modelling of the wheel/rail source intensity and of the noise propagation with the ability to evaluate the effect of modifications at source level (e.g., grinding, rail dampers, wheel dampers, change in resiliency of wheels and/or rail fixation) and of modifications in the propagation path (absorption at the track base, noise barriers, screening). A relevant combination of existing solutions was selected in the function of the simulation results. Three distinct existing solutions were designed in detail aiming at a high rolling noise attenuation and not affecting the normal operation of the metro system: Action 1: implementation of sound absorbing precast elements (panel type) on the track bed, Action 2: implementation of an absorbing noise barrier with a height of 1.10-1.20m above rail level, and Action 3: installation of rail dampers. The selected solutions were implemented on site and the global performance was measured step by step for comparison with simulations. Copyright © 2015 Elsevier B.V. All rights reserved.

On the Role of Hyper-arid Regions within the Virtual Water Trade Network

NASA Astrophysics Data System (ADS)

Aggrey, James; Alshamsi, Aamena; Molini, Annalisa

2016-04-01

Climate change, economic development, and population growth are bound to increasingly impact global water resources, posing a significant threat to the sustainable development of arid regions, where water consumption highly exceeds the natural carrying capacity, population growth rate is high, and climate variability is going to impact both water consumption and availability. Virtual Water Trade (VWT) - i.e. the international trade network of water-intensive products - has been proposed as a possible solution to optimize the allocation of water resources on the global scale. By increasing food availability and lowering food prices it may in fact help the rapid development of water-scarce regions. The structure of the VWT network has been analyzed by a number of authors both in connection with trade policies, socioeconomic constrains and agricultural efficiency. However a systematic analysis of the structure and the dynamics of the VWT network conditional to aridity, climatic forcing and energy availability, is still missing. Our goal is hence to analyze the role of arid and hyper-arid regions within the VWN under diverse climatic, demographic, and energy constraints with an aim to contribute to the ongoing Energy-Water-Food nexus discussion. In particular, we focus on the hyper-arid lands of the Arabian Peninsula, the role they play in the global network and the assessment of their specific criticalities, as reflected in the VWN resilience.

Sustaining a Global Social Network: a quasi-experimental study.

PubMed

Benton, D C; Ferguson, S L

2017-03-01

To examine the longer term impact on the social network of participating nurses in the Global Nursing Leadership Institute (GNLI2013) through using differing frequencies of follow-up to assess impact on maintenance of network cohesion. Social network analysis is increasingly been used by nurse researchers, however, studies tend to use single point-in-time descriptive methods. This study utilizes a repeated measures, block group, control-intervention, quasi-experimental design. Twenty-eight nurse leaders, competitively selected through a double-blind peer review process, were allocated to five action learning-based learning groups. Network architecture, measures of cohesion and node degree frequency were all used to assess programme impact. The programme initiated and sustained connections between nurse leaders drawn from a geographically dispersed heterogeneous group. Modest inputs of two to three e-mails over a 6-month period seem sufficient to maintain connectivity as indicated by measures of network density, diameter and path length. Due to the teaching methodology used, the study sample was relatively small and the follow-up data collection took place after a relatively short time. Replication and further cohort data collection would be advantageous. In an era where many policy solutions are being debated and initiated at the global level, action learning leadership development that utilizes new technology follow-up appears to show significant impact and is worthy of wider application. The approach warrants further inquiry and testing as to its longer term effects on nursing's influence on policy formulation and implementation. © 2016 International Council of Nurses.

Continuum Modeling and Control of Large Nonuniform Wireless Networks via Nonlinear Partial Differential Equations

DOE PAGES

Zhang, Yang; Chong, Edwin K. P.; Hannig, Jan; ...

2013-01-01

We inmore » troduce a continuum modeling method to approximate a class of large wireless networks by nonlinear partial differential equations (PDEs). This method is based on the convergence of a sequence of underlying Markov chains of the network indexed by N , the number of nodes in the network. As N goes to infinity, the sequence converges to a continuum limit, which is the solution of a certain nonlinear PDE. We first describe PDE models for networks with uniformly located nodes and then generalize to networks with nonuniformly located, and possibly mobile, nodes. Based on the PDE models, we develop a method to control the transmissions in nonuniform networks so that the continuum limit is invariant under perturbations in node locations. This enables the networks to maintain stable global characteristics in the presence of varying node locations.« less

Long Term Eddy Covariance Networks - When Collaboration Works: An Example from Ameriflux, ICOS and Fluxnet

NASA Astrophysics Data System (ADS)

Papale, D.; Baldocchi, D. D.; Loescher, H. W.; Torn, M. S.

2014-12-01

Small networks of eddy covariance sites measuring exchanges of CO2, water and energy between ecosystems and atmosphere started to be organized in Europe and USA more than 15 years ago with the AmeriFlux and EuroFlux initiatives. They were composed by less than 20 sites each, mainly over undisturbed forest and without a strong coordination between sites, in particular across the ocean. In the following years the networks grew exponentially both at continental and global level, reaching more than 500 sites few years ago and expanding the eddy covariance measurement to different ecosystem types, climate regions and management/disturbance regimes. At the same time, important steps were done in terms of cooperation and harmonization related to data processing, data description and data sharing policies, leading to inter-continental and global activities under the FLUXNET framework. Today the networks are facing a new evolution step, moving from pure research activities to something that includes also monitoring and research infrastructure characteristics. AmeriFlux and NEON (National Ecological Observatory Network) in USA and ICOS (Integrated Carbon Observation System) in Europe are opening a new phase in the eddy covariance networks: with a long term perspective, increased level of standardization and a completely open access policy, will hopefully stimulate even more global synthesis studies and a wider use of the flux measurements by other scientific communities. AmeriFlux, NEON and ICOS are also strongly involved in cross-networks harmonization activities in terms of data acquisition, data processing and data format, in order to simplify and encourage the joint use of their measurements. A brief history of the development, challenges and solutions in the organization of the different networks and their common activities will be presented, to focus then on selected scientific results that have been possible only thanks to the global integration and international collaboration and finally discuss future developments and current ongoing activities in terms of data harmonization/standardization and sharing.

First-order design of geodetic networks using the simulated annealing method

NASA Astrophysics Data System (ADS)

Berné, J. L.; Baselga, S.

2004-09-01

The general problem of the optimal design for a geodetic network subject to any extrinsic factors, namely the first-order design problem, can be dealt with as a numeric optimization problem. The classic theory of this problem and the optimization methods are revised. Then the innovative use of the simulated annealing method, which has been successfully applied in other fields, is presented for this classical geodetic problem. This method, belonging to iterative heuristic techniques in operational research, uses a thermodynamical analogy to crystalline networks to offer a solution that converges probabilistically to the global optimum. Basic formulation and some examples are studied.

Measurement-Device-Independent Quantum Key Distribution over Untrustful Metropolitan Network

NASA Astrophysics Data System (ADS)

Tang, Yan-Lin; Yin, Hua-Lei; Zhao, Qi; Liu, Hui; Sun, Xiang-Xiang; Huang, Ming-Qi; Zhang, Wei-Jun; Chen, Si-Jing; Zhang, Lu; You, Li-Xing; Wang, Zhen; Liu, Yang; Lu, Chao-Yang; Jiang, Xiao; Ma, Xiongfeng; Zhang, Qiang; Chen, Teng-Yun; Pan, Jian-Wei

2016-01-01

Quantum cryptography holds the promise to establish an information-theoretically secure global network. All field tests of metropolitan-scale quantum networks to date are based on trusted relays. The security critically relies on the accountability of the trusted relays, which will break down if the relay is dishonest or compromised. Here, we construct a measurement-device-independent quantum key distribution (MDIQKD) network in a star topology over a 200-square-kilometer metropolitan area, which is secure against untrustful relays and against all detection attacks. In the field test, our system continuously runs through one week with a secure key rate 10 times larger than previous results. Our results demonstrate that the MDIQKD network, combining the best of both worlds—security and practicality, constitutes an appealing solution to secure metropolitan communications.

Mittag-Leffler synchronization of delayed fractional-order bidirectional associative memory neural networks with discontinuous activations: state feedback control and impulsive control schemes.

PubMed

Ding, Xiaoshuai; Cao, Jinde; Zhao, Xuan; Alsaadi, Fuad E

2017-08-01

This paper is concerned with the drive-response synchronization for a class of fractional-order bidirectional associative memory neural networks with time delays, as well as in the presence of discontinuous activation functions. The global existence of solution under the framework of Filippov for such networks is firstly obtained based on the fixed-point theorem for condensing map. Then the state feedback and impulsive controllers are, respectively, designed to ensure the Mittag-Leffler synchronization of these neural networks and two new synchronization criteria are obtained, which are expressed in terms of a fractional comparison principle and Razumikhin techniques. Numerical simulations are presented to validate the proposed methodologies.

Connecting source aggregating areas with distributive regions via Optimal Transportation theory.

NASA Astrophysics Data System (ADS)

Lanzoni, S.; Putti, M.

2016-12-01

We study the application of Optimal Transport (OT) theory to the transfer of water and sediments from a distributed aggregating source to a distributing area connected by a erodible hillslope. Starting from the Monge-Kantorovich equations, We derive a global energy functional that nonlinearly combines the cost of constructing the drainage network over the entire domain and the cost of water and sediment transportation through the network. It can be shown that the minimization of this functional is equivalent to the infinite time solution of a system of diffusion partial differential equations coupled with transient ordinary differential equations, that closely resemble the classical conservation laws of water and sediments mass and momentum. We present several numerical simulations applied to realstic test cases. For example, the solution of the proposed model forms network configurations that share strong similiratities with rill channels formed on an hillslope. At a larger scale, we obtain promising results in simulating the network patterns that ensure a progressive and continuous transition from a drainage drainage area to a distributive receiving region.

Macroscopic self-oscillations and aging transition in a network of synaptically coupled quadratic integrate-and-fire neurons.

PubMed

Ratas, Irmantas; Pyragas, Kestutis

2016-09-01

We analyze the dynamics of a large network of coupled quadratic integrate-and-fire neurons, which represent the canonical model for class I neurons near the spiking threshold. The network is heterogeneous in that it includes both inherently spiking and excitable neurons. The coupling is global via synapses that take into account the finite width of synaptic pulses. Using a recently developed reduction method based on the Lorentzian ansatz, we derive a closed system of equations for the neuron's firing rate and the mean membrane potential, which are exact in the infinite-size limit. The bifurcation analysis of the reduced equations reveals a rich scenario of asymptotic behavior, the most interesting of which is the macroscopic limit-cycle oscillations. It is shown that the finite width of synaptic pulses is a necessary condition for the existence of such oscillations. The robustness of the oscillations against aging damage, which transforms spiking neurons into nonspiking neurons, is analyzed. The validity of the reduced equations is confirmed by comparing their solutions with the solutions of microscopic equations for the finite-size networks.

Global nurse leader perspectives on health systems and workforce challenges.

PubMed

Gantz, Nancy Rollins; Sherman, Rose; Jasper, Melanie; Choo, Chua Gek; Herrin-Griffith, Donna; Harris, Kathy

2012-05-01

As part of the 2011 annual American Organization of Nurse Executives conference held in San Diego, California, a session was presented that focused on nursing workforce and health systems challenges from a global perspective. This article includes content addressed during the session representing nurse leader perspectives from the UK, Singapore and the USA. Recent events in global economic markets have highlighted the interdependence of countries. There is now a global focus on health-care costs and quality as government leaders struggle to reduce budgets and remain solvent. Finding solutions to these complex problems requires that nurse leaders adopt more of a world view and network with one another as they look for best practices and creative strategies. Nursing leadership challenges such as staffing, competency development, ageing populations, reduced health-care funding and maintaining quality are now common global problems. There is a need for innovation in nursing practice to accommodate the enormous challenges facing nursing's future. Opportunities on an international scale for nurse leaders to have dialogue and network, such as the conference presentation discussed in this article, will become increasingly more important to facilitate the development of innovative leadership strategies. © 2012 Blackwell Publishing Ltd.

New Habits of Heart and Mind: "Third Wave" Transformational Leaders. Creating Solution-Based Learning Focused on Children and Families and Math, Science, and Technology in the Era of Smart Homes, Wired Communities, Fast Systems, Global Networks, and Fast Forward Learners in a Borderless World.

ERIC Educational Resources Information Center

Groff, Warren H.

One purpose of education is that of human-resource development--to provide society with the critical mass of intellectual capital and competent work forces. This paper presents an analysis of the emerging global context and school restructuring in industrialized nations. It also describes an evaluation conducted by the Education Committee of the…

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

PubMed

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

2015-08-01

This paper is concerned with the periodic synchronization problem for a general class of delayed neural networks (DNNs) with discontinuous neuron activation. One of the purposes is to analyze the problem of periodic orbits. To do so, we introduce new tools including inequality techniques and Kakutani's fixed point theorem of set-valued maps to derive the existence of periodic solution. Another purpose is to design a switching state-feedback control for realizing global exponential synchronization of the drive-response network system with periodic coefficients. Unlike the previous works on periodic synchronization of neural network, both the neuron activations and controllers in this paper are allowed to be discontinuous. Moreover, owing to the occurrence of delays in neuron signal, the neural network model is described by the functional differential equation. So we introduce extended Filippov-framework to deal with the basic issues of solutions for discontinuous DNNs. Finally, two examples and simulation experiments are given to illustrate the proposed method and main results which have an important instructional significance in the design of periodic synchronized DNNs circuits involving discontinuous or switching factors. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming

PubMed Central

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-01-01

In order to recycle and dispose of all people’s expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies. PMID:26184252

An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming.

PubMed

Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

2015-07-09

In order to recycle and dispose of all people's expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.

Mitigation of epidemics in contact networks through optimal contact adaptation *

PubMed Central

Youssef, Mina; Scoglio, Caterina

2013-01-01

This paper presents an optimal control problem formulation to minimize the total number of infection cases during the spread of susceptible-infected-recovered SIR epidemics in contact networks. In the new approach, contact weighted are reduced among nodes and a global minimum contact level is preserved in the network. In addition, the infection cost and the cost associated with the contact reduction are linearly combined in a single objective function. Hence, the optimal control formulation addresses the tradeoff between minimization of total infection cases and minimization of contact weights reduction. Using Pontryagin theorem, the obtained solution is a unique candidate representing the dynamical weighted contact network. To find the near-optimal solution in a decentralized way, we propose two heuristics based on Bang-Bang control function and on a piecewise nonlinear control function, respectively. We perform extensive simulations to evaluate the two heuristics on different networks. Our results show that the piecewise nonlinear control function outperforms the well-known Bang-Bang control function in minimizing both the total number of infection cases and the reduction of contact weights. Finally, our results show awareness of the infection level at which the mitigation strategies are effectively applied to the contact weights. PMID:23906209

Mitigation of epidemics in contact networks through optimal contact adaptation.

PubMed

Youssef, Mina; Scoglio, Caterina

2013-08-01

This paper presents an optimal control problem formulation to minimize the total number of infection cases during the spread of susceptible-infected-recovered SIR epidemics in contact networks. In the new approach, contact weighted are reduced among nodes and a global minimum contact level is preserved in the network. In addition, the infection cost and the cost associated with the contact reduction are linearly combined in a single objective function. Hence, the optimal control formulation addresses the tradeoff between minimization of total infection cases and minimization of contact weights reduction. Using Pontryagin theorem, the obtained solution is a unique candidate representing the dynamical weighted contact network. To find the near-optimal solution in a decentralized way, we propose two heuristics based on Bang-Bang control function and on a piecewise nonlinear control function, respectively. We perform extensive simulations to evaluate the two heuristics on different networks. Our results show that the piecewise nonlinear control function outperforms the well-known Bang-Bang control function in minimizing both the total number of infection cases and the reduction of contact weights. Finally, our results show awareness of the infection level at which the mitigation strategies are effectively applied to the contact weights.

Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things.

PubMed

Ding, Kaiqi; Zhao, Haitao; Hu, Xiping; Wei, Jibo

2017-10-28

In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node's learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.

How Well Can We Assess Atmospheric Ozone Changes? The OzoneSonde Data Quality Assessment (O3S-DQA)

NASA Astrophysics Data System (ADS)

Tarasick, D. W.; Smit, H. G. J.; Thompson, A. M.; Morris, G. A.; Witte, J. C.; Davies, J.

2017-12-01

Ozonesondes are the backbone of the global ozone observing network, making inexpensive, accurate measurements of ozone from the ground to 30km, with high vertical resolution ( 100 m), for more than 50 years. The data are used extensively for validation of satellite data products, and are also part of merged satellite data sets and climatologies that are used for trend analyses and as a priori data for satellite retrievals. The importance of ECC sondes for trend analyses and as a stable reference for satellite validation recommends research effort to better quantify uncertainties in ECC data and to understand changes therein. Comparison with UV-absorption measurements in a number of studies (e.g. JOSIE, BESOS) has shown that small changes in sensor type, preparation or sensing solution can introduce significant inhomogenities in long-term sounding records. The major goal of the O3S-DQA is the homogenization of ozonesonde data sets. Essential aspects of this are the detailed estimation of uncertainties and documentation of the reprocessing. Corrections to historical data for known issues may reduce biases but introduce additional uncertainties. We take a systematic approach to quantifying these uncertainties by considering the physical and chemical processes involved, and attempt to place our estimates on a firm theoretical or empirical footing. We discuss stoichiometry, sensing solutions, background current, humidity and temperature corrections to pump flow rate, altitude-dependent pump flow corrections, variations in radiosonde pressure offsets, and normalization of sonde total ozone to spectrophotometric measurements. In the past 20 years ozonesonde precision has improved by a factor of 2, primarily through the adoption of strict standard operating procedures. We identify remaining quality assurance issues that can be better evaluated with further research. We present a "roadmap" for achieving a goal of better than 5% overall uncertainty throughout the global ozonesonde network. Finally, we note that the global network is very uneven. Additional sites would be of global benefit. Objective methods of quantifying spatial representativeness can optimize future network design. International cooperation and data sharing will continue to be of immense importance.

Deterministic and stochastic algorithms for resolving the flow fields in ducts and networks using energy minimization

NASA Astrophysics Data System (ADS)

Sochi, Taha

2016-09-01

Several deterministic and stochastic multi-variable global optimization algorithms (Conjugate Gradient, Nelder-Mead, Quasi-Newton and global) are investigated in conjunction with energy minimization principle to resolve the pressure and volumetric flow rate fields in single ducts and networks of interconnected ducts. The algorithms are tested with seven types of fluid: Newtonian, power law, Bingham, Herschel-Bulkley, Ellis, Ree-Eyring and Casson. The results obtained from all those algorithms for all these types of fluid agree very well with the analytically derived solutions as obtained from the traditional methods which are based on the conservation principles and fluid constitutive relations. The results confirm and generalize the findings of our previous investigations that the energy minimization principle is at the heart of the flow dynamics systems. The investigation also enriches the methods of computational fluid dynamics for solving the flow fields in tubes and networks for various types of Newtonian and non-Newtonian fluids.

GNAT: A Global Network of Astronomical Telescopes

NASA Astrophysics Data System (ADS)

Crawford, David L.

1995-12-01

Astronomical resources are increasingly directed toward development of very large telescopes, and many facilities are compelled to cease operations of smaller telescopes. A real concern is emerging with respect to issues of access to astronomical imaging systems for the majority of astronomers who will have little or no opportunity to work with the larger telescopes. Further concern is developing with regard to the means for conducting observationally intensive fundamental astronomical imaging programs, such as surveys, monitoring, and standards calibration. One attractive potential solution is a global network of (automated) astronomical telescopes (GNAT). Initial steps have been taken to turn this network into a reality. GNAT has been incorporated as a nonprofit corporation, membership drives have begun and several institutions have joined. The first two open GNAT meetings have now been held to define hardware and software systems, and an order has been placed for the first of the GNAT automated telescopes. In this presentation we discuss the goals and status of GNAT and its implications for astronomical imaging.

A multiobjective optimization framework for multicontaminant industrial water network design.

PubMed

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

2011-07-01

The optimal design of multicontaminant industrial water networks according to several objectives is carried out in this paper. The general formulation of the water allocation problem (WAP) is given as a set of nonlinear equations with binary variables representing the presence of interconnections in the network. For optimization purposes, three antagonist objectives are considered: F(1), the freshwater flow-rate at the network entrance, F(2), the water flow-rate at inlet of regeneration units, and F(3), the number of interconnections in the network. The multiobjective problem is solved via a lexicographic strategy, where a mixed-integer nonlinear programming (MINLP) procedure is used at each step. The approach is illustrated by a numerical example taken from the literature involving five processes, one regeneration unit and three contaminants. The set of potential network solutions is provided in the form of a Pareto front. Finally, the strategy for choosing the best network solution among those given by Pareto fronts is presented. This Multiple Criteria Decision Making (MCDM) problem is tackled by means of two approaches: a classical TOPSIS analysis is first implemented and then an innovative strategy based on the global equivalent cost (GEC) in freshwater that turns out to be more efficient for choosing a good network according to a practical point of view. Copyright © 2011 Elsevier Ltd. All rights reserved.

Linking Geophysical Networks to International Economic Development Through Integration of Global and National Monitoring

NASA Astrophysics Data System (ADS)

Lerner-Lam, A.

2007-05-01

Outside of the research community and mission agencies, global geophysical monitoring rarely receives sustained attention except in the aftermath of a humanitarian disaster. The recovery and rebuilding period focuses attention and resources for a short time on regional needs for geophysical observation, often at the national or sub-national level. This can result in the rapid deployment of national monitoring networks, but may overlook the longer-term benefits of integration with global networks. Even in the case of multinational disasters, such as the Indian Ocean tsunami, it has proved difficult to promote the integration of national solutions with global monitoring, research and operations infrastructure. More importantly, continuing operations at the national or sub-national scale are difficult to sustain once the resources associated with recovery and rebuilding are depleted. Except for some notable examples, the vast infrastructure associated with global geophysical monitoring is not utilized constructively to promote the integration of national networks with international efforts. This represents a missed opportunity not only for monitoring, but for developing the international research and educational collaborations necessary for technological transfer and capacity building. The recent confluence of highly visible disasters, global multi-hazard risk assessments, evaluations of the relationships between natural disasters and socio-economic development, and shifts in development agency policies, provides an opportunity to link global geophysical monitoring initiatives to central issues in international development. Natural hazard risk reduction has not been the first priority of international development agendas for understandable, mainly humanitarian reasons. However, it is now recognized that the so-called risk premium associated with making development projects more risk conscious or risk resilient is relatively small relative to potential losses. Thus there is an attitudinal shift emerging whereby disaster risk management can be "mainstreamed" into the sustainable development programs in many countries. Consequently, it is incumbent to demonstrate that multi-scale geophysical monitoring, comprising integration of global networks with national and sub-national operations, is a foundational component of sustainable development infrastructure. This suggests even greater emphasis on developing dynamic and adaptive multi- hazard risk assessments, encompassing valid estimates of social and physical vulnerabilities; designing multi- scale network integration strategies that consider risk as well as hazard; providing operational and flexible templates for developing national networks in a global context; emphasizing the backbone characteristics of global geophysical monitoring to nations seeking to develop their own monitoring capacity; promoting sustained international research, education and training collaborations coinciding with the development of monitoring capacity; and continuing to promote the free and open exchange of data as a necessary component of sustained intellectual interest in monitoring. A combination of these strategies may counteract the decay of interest in regional geophysical monitoring after a disaster.

Multi-objective Optimization of Pulsed Gas Metal Arc Welding Process Using Neuro NSGA-II

NASA Astrophysics Data System (ADS)

Pal, Kamal; Pal, Surjya K.

2018-05-01

Weld quality is a critical issue in fabrication industries where products are custom-designed. Multi-objective optimization results number of solutions in the pareto-optimal front. Mathematical regression model based optimization methods are often found to be inadequate for highly non-linear arc welding processes. Thus, various global evolutionary approaches like artificial neural network, genetic algorithm (GA) have been developed. The present work attempts with elitist non-dominated sorting GA (NSGA-II) for optimization of pulsed gas metal arc welding process using back propagation neural network (BPNN) based weld quality feature models. The primary objective to maintain butt joint weld quality is the maximization of tensile strength with minimum plate distortion. BPNN has been used to compute the fitness of each solution after adequate training, whereas NSGA-II algorithm generates the optimum solutions for two conflicting objectives. Welding experiments have been conducted on low carbon steel using response surface methodology. The pareto-optimal front with three ranked solutions after 20th generations was considered as the best without further improvement. The joint strength as well as transverse shrinkage was found to be drastically improved over the design of experimental results as per validated pareto-optimal solutions obtained.

Dynamics of global supply chain and electric power networks: Models, pricing analysis, and computations

NASA Astrophysics Data System (ADS)

Matsypura, Dmytro

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following coauthored papers: Nagurney, Cruz, and Matsypura (2003), Nagurney and Matsypura (2004, 2005, 2006), Matsypura and Nagurney (2005), Matsypura, Nagurney, and Liu (2006).

A generalized optimization principle for asymmetric branching in fluidic networks

PubMed Central

Stephenson, David

2016-01-01

When applied to a branching network, Murray’s law states that the optimal branching of vascular networks is achieved when the cube of the parent channel radius is equal to the sum of the cubes of the daughter channel radii. It is considered integral to understanding biological networks and for the biomimetic design of artificial fluidic systems. However, despite its ubiquity, we demonstrate that Murray’s law is only optimal (i.e. maximizes flow conductance per unit volume) for symmetric branching, where the local optimization of each individual channel corresponds to the global optimum of the network as a whole. In this paper, we present a generalized law that is valid for asymmetric branching, for any cross-sectional shape, and for a range of fluidic models. We verify our analytical solutions with the numerical optimization of a bifurcating fluidic network for the examples of laminar, turbulent and non-Newtonian fluid flows. PMID:27493583

Impact of Multi-GNSS Observations on Precise Orbit Determination and Precise Point Positioning Solutions

NASA Astrophysics Data System (ADS)

Amiri, N.; Bertiger, W. I.; Lu, W.; Miller, M. A.; David, M. W.; Ries, P.; Romans, L.; Sibois, A. E.; Sibthorpe, A.; Sakumura, C.

2017-12-01

Impact of Multi-GNSS Observations on Precise Orbit Determination and Precise Point Positioning Solutions Authors: Nikta Amiri, Willy Bertiger, Wenwen Lu, Mark Miller, David Murphy, Paul Ries, Larry Romans, Carly Sakumura, Aurore Sibois, Anthony Sibthorpe All at the Jet Propulsion Laboratory, California Institute of Technology Multiple Global Navigation Satellite Systems (GNSS) are now in various stages of completion. The four current constellations (GPS, GLONASS, BeiDou, Galileo) comprise more than 80 satellites as of July 2017, with 120 satellites expected to be available when all four constellations become fully operational. We investigate the impact of simultaneous observations to these four constellations on global network precise orbit determination (POD) solutions, and compare them to available sets of orbit and clock products submitted to the Multi-GNSS Experiment (MGEX). Using JPL's GipsyX software, we generate orbit and clock products for the four constellations. The resulting solutions are evaluated based on a number of metrics including day-to-day internal and external orbit and/or clock overlaps and estimated constellation biases. Additionally, we examine estimated station positions obtained from precise point positioning (PPP) solutions by comparing results generated from multi-GNSS and GPS-only orbit and clock products.

A Contribution For The Understanding of The Deformation Pattern Across The Terceira Axis

NASA Astrophysics Data System (ADS)

Navarro, A.; Catalão, J.; Miranda, J. M.

In spite of several geodynamics studies performed in the Azores region, little is known about the deformation pattern of the tectonically more active sector around the Ter- ceira Axis. GPS campaigns performed in the area, in the last few years, were mainly concerned to the study of the relative motions between the Eurasian, African and North-American plates. This study, developed in the scope of the STAMINA project, has as main purpose the establishment of a dense GPS network to study the crustal deformation pattern in the area between the North Hirondelle basin and the East Gra- ciosa basin. The GPS network consists of 20 stations uniformly distributed throughout the island. The first GPS survey was carried out during days 90 to 98 of 2001. TERC and TCAT stations were used as reference stations, recording continuously throughout the survey. All the other stations were occupied for at least three sessions, except for cases of receiver malfunction, each session has a duration of 12 to 24 hours. The GPS data processing approach consisted of three main steps: (1) first, all sessions were processed separately using GAMIT in order to obtain a daily solution for two local sites (TERC and TCAT) and six global tracking stations (CCV3, RABT, SAV1, SFER, STJO and WSRT) using precise orbits from the IGS; (2) then, all stations of the local network are processed together and (3) finally, all station, including the global tracking ones, are reprocessed again. Precise orbits from the IGS were used in the processing. In each step a compensation program was used to compute a least squares network adjusted solution for the campaign, where all sessions are combined to yield estimates of improved station coordinates. The final solution achieved with the described methodology is documented in this paper. Further geodetic observations are needed in order to estimate the stations ve- locities and displacements and consequently to determine the rate of deformation of the island.

Comparison of the genetic algorithm and incremental optimisation routines for a Bayesian inverse modelling based network design

NASA Astrophysics Data System (ADS)

Nickless, A.; Rayner, P. J.; Erni, B.; Scholes, R. J.

2018-05-01

The design of an optimal network of atmospheric monitoring stations for the observation of carbon dioxide (CO2) concentrations can be obtained by applying an optimisation algorithm to a cost function based on minimising posterior uncertainty in the CO2 fluxes obtained from a Bayesian inverse modelling solution. Two candidate optimisation methods assessed were the evolutionary algorithm: the genetic algorithm (GA), and the deterministic algorithm: the incremental optimisation (IO) routine. This paper assessed the ability of the IO routine in comparison to the more computationally demanding GA routine to optimise the placement of a five-member network of CO2 monitoring sites located in South Africa. The comparison considered the reduction in uncertainty of the overall flux estimate, the spatial similarity of solutions, and computational requirements. Although the IO routine failed to find the solution with the global maximum uncertainty reduction, the resulting solution had only fractionally lower uncertainty reduction compared with the GA, and at only a quarter of the computational resources used by the lowest specified GA algorithm. The GA solution set showed more inconsistency if the number of iterations or population size was small, and more so for a complex prior flux covariance matrix. If the GA completed with a sub-optimal solution, these solutions were similar in fitness to the best available solution. Two additional scenarios were considered, with the objective of creating circumstances where the GA may outperform the IO. The first scenario considered an established network, where the optimisation was required to add an additional five stations to an existing five-member network. In the second scenario the optimisation was based only on the uncertainty reduction within a subregion of the domain. The GA was able to find a better solution than the IO under both scenarios, but with only a marginal improvement in the uncertainty reduction. These results suggest that the best use of resources for the network design problem would be spent in improvement of the prior estimates of the flux uncertainties rather than investing these resources in running a complex evolutionary optimisation algorithm. The authors recommend that, if time and computational resources allow, that multiple optimisation techniques should be used as a part of a comprehensive suite of sensitivity tests when performing such an optimisation exercise. This will provide a selection of best solutions which could be ranked based on their utility and practicality.

Legitimacy and status groups in financial markets.

PubMed

Preda, Alex

2005-09-01

Economic sociologists have argued that financial markets should be analysed as uncertainty-processing social networks and intermediary groups. Networks and intermediaries alone cannot confer legitimacy upon financial actors and transactions. Status groups are a solution to this problem. They emphasize reputation, honour and good social behaviour as stabilizers of collective action, as means of social control and as indicators of legitimacy. I examine here the emergence and evolution of status groups of brokers in London, New York and Paris, and show how emphasis on honour was used to legitimize financial transactions. I argue that financial markets should be conceived as networks, intermediary and status groups. In global, automated financial markets status groups like securities analysts are gaining in prominence.

The comparison of performance by using alternative refrigerant R152a in automobile climate system with different artificial neural network models

NASA Astrophysics Data System (ADS)

Kalkisim, A. T.; Hasiloglu, A. S.; Bilen, K.

2016-04-01

Due to the refrigerant gas R134a which is used in automobile air conditioning systems and has greater global warming impact will be phased out gradually, an alternative gas is being desired to be used without much change on existing air conditioning systems. It is aimed to obtain the easier solution for intermediate values on the performance by creating a Neural Network Model in case of using a fluid (R152a) in automobile air conditioning systems that has the thermodynamic properties close to each other and near-zero global warming impact. In this instance, a network structure giving the most accurate result has been established by identifying which model provides the best education with which network structure and makes the most accurate predictions in the light of the data obtained after five different ANN models was trained with three different network structures. During training of Artificial Neural Network, Quick Propagation, Quasi-Newton, Levenberg-Marquardt and Conjugate Gradient Descent Batch Back Propagation methodsincluding five inputs and one output were trained with various network structures. Over 1500 iterations have been evaluated and the most appropriate model was identified by determining minimum error rates. The accuracy of the determined ANN model was revealed by comparing with estimates made by the Multi-Regression method.

Mic Flocks in the Cloud: Harnessing Mobile Ubiquitous Sensor Networks

NASA Astrophysics Data System (ADS)

Garces, M. A.; Christe, A.

2015-12-01

Smartphones provide a commercial, off-the-shelf solution to capture, store, analyze, and distribute infrasound using on-board or external microphones (mics) as well as on-board barometers. Free iOS infrasound apps can be readily downloaded from the Apple App Store, and Android versions are in progress. Infrasound propagates for great distances, has low sample rates, and provides a tractable pilot study scenario for open distributed sensor networks at regional and global scales using one of the most ubiquitous sensors on Earth - microphones. Data collection is no longer limited to selected vendors at exclusive prices: anybody on Earth can record and stream infrasound, and the diversity of recording systems and environments is rapidly expanding. Global deployment may be fast and easy (www.redvox.io), but comes with the cost of increasing data volume, velocity, variety, and complexity. Flocking - the collective motion of mobile agents - is a natural human response to threats or events of interest. Anticipating, modeling and harnessing flocking sensor topologies will be necessary for adaptive array and network processing. The increasing data quantity and complexity will exceed the processing capacity of human analysts and most research servers. We anticipate practical real-time applications will require the on-demand adaptive scalability and resources of the Cloud. Cloud architectures for such heterogeneous sensor networks will consider eventual integration into the Global Earth Observation System of Systems (GEOSS).

[Global MED-NET].

PubMed

Slatina, E

2000-01-01

This poster will show a concept as well as some practical solutions for the database which is intended to be used by all members and institutions of the Emergency Medical Care international institutions network. This poster shows how data is automatically processed in a rapid and good quality way, while in the same time the lives are saved and time and money are saved too.

Military Interoperable Digital Hospital Testbed (MIDHT)

DTIC Science & Technology

2010-07-01

solutions to optimize healthcare resources for rural communities and identify lessons learned and best practices that benefit both the global MHS...providers and three CHS facilities on their business practices and process flows. Research initiatives will focus on the impact of an electronic...strategic goals and the Nationwide Health Information Network (NHIN). The MIDHT will continue to identify lessons learned/best practices that benefit

Fortified Anonymous Communication Protocol for Location Privacy in WSN: A Modular Approach

PubMed Central

Abuzneid, Abdel-Shakour; Sobh, Tarek; Faezipour, Miad; Mahmood, Ausif; James, John

2015-01-01

Wireless sensor network (WSN) consists of many hosts called sensors. These sensors can sense a phenomenon (motion, temperature, humidity, average, max, min, etc.) and represent what they sense in a form of data. There are many applications for WSNs including object tracking and monitoring where in most of the cases these objects need protection. In these applications, data privacy itself might not be as important as the privacy of source location. In addition to the source location privacy, sink location privacy should also be provided. Providing an efficient end-to-end privacy solution would be a challenging task to achieve due to the open nature of the WSN. The key schemes needed for end-to-end location privacy are anonymity, observability, capture likelihood, and safety period. We extend this work to allow for countermeasures against multi-local and global adversaries. We present a network model protected against a sophisticated threat model: passive /active and local/multi-local/global attacks. This work provides a solution for end-to-end anonymity and location privacy as well. We will introduce a framework called fortified anonymous communication (FAC) protocol for WSN. PMID:25763649

An efficient solution of real-time data processing for multi-GNSS network

NASA Astrophysics Data System (ADS)

Gong, Xiaopeng; Gu, Shengfeng; Lou, Yidong; Zheng, Fu; Ge, Maorong; Liu, Jingnan

2017-12-01

Global navigation satellite systems (GNSS) are acting as an indispensable tool for geodetic research and global monitoring of the Earth, and they have been rapidly developed over the past few years with abundant GNSS networks, modern constellations, and significant improvement in mathematic models of data processing. However, due to the increasing number of satellites and stations, the computational efficiency becomes a key issue and it could hamper the further development of GNSS applications. In this contribution, this problem is overcome from the aspects of both dense linear algebra algorithms and GNSS processing strategy. First, in order to fully explore the power of modern microprocessors, the square root information filter solution based on the blocked QR factorization employing as many matrix-matrix operations as possible is introduced. In addition, the algorithm complexity of GNSS data processing is further decreased by centralizing the carrier-phase observations and ambiguity parameters, as well as performing the real-time ambiguity resolution and elimination. Based on the QR factorization of the simulated matrix, we can conclude that compared to unblocked QR factorization, the blocked QR factorization can greatly improve processing efficiency with a magnitude of nearly two orders on a personal computer with four 3.30 GHz cores. Then, with 82 globally distributed stations, the processing efficiency is further validated in multi-GNSS (GPS/BDS/Galileo) satellite clock estimation. The results suggest that it will take about 31.38 s per epoch for the unblocked method. While, without any loss of accuracy, it only takes 0.50 and 0.31 s for our new algorithm per epoch for float and fixed clock solutions, respectively.

Adaptiveness in monotone pseudo-Boolean optimization and stochastic neural computation.

PubMed

Grossi, Giuliano

2009-08-01

Hopfield neural network (HNN) is a nonlinear computational model successfully applied in finding near-optimal solutions of several difficult combinatorial problems. In many cases, the network energy function is obtained through a learning procedure so that its minima are states falling into a proper subspace (feasible region) of the search space. However, because of the network nonlinearity, a number of undesirable local energy minima emerge from the learning procedure, significantly effecting the network performance. In the neural model analyzed here, we combine both a penalty and a stochastic process in order to enhance the performance of a binary HNN. The penalty strategy allows us to gradually lead the search towards states representing feasible solutions, so avoiding oscillatory behaviors or asymptotically instable convergence. Presence of stochastic dynamics potentially prevents the network to fall into shallow local minima of the energy function, i.e., quite far from global optimum. Hence, for a given fixed network topology, the desired final distribution on the states can be reached by carefully modulating such process. The model uses pseudo-Boolean functions both to express problem constraints and cost function; a combination of these two functions is then interpreted as energy of the neural network. A wide variety of NP-hard problems fall in the class of problems that can be solved by the model at hand, particularly those having a monotonic quadratic pseudo-Boolean function as constraint function. That is, functions easily derived by closed algebraic expressions representing the constraint structure and easy (polynomial time) to maximize. We show the asymptotic convergence properties of this model characterizing its state space distribution at thermal equilibrium in terms of Markov chain and give evidence of its ability to find high quality solutions on benchmarks and randomly generated instances of two specific problems taken from the computational graph theory.

SDTCP: Towards Datacenter TCP Congestion Control with SDN for IoT Applications.

PubMed

Lu, Yifei; Ling, Zhen; Zhu, Shuhong; Tang, Ling

2017-01-08

The Internet of Things (IoT) has gained popularity in recent years. Today's IoT applications are now increasingly deployed in cloud platforms to perform Big Data analytics. In cloud data center networks (DCN), TCP incast usually happens when multiple senders simultaneously communicate with a single receiver. However, when TCP incast happens, DCN may suffer from both throughput collapse for TCP burst flows and temporary starvation for TCP background flows. In this paper, we propose a software defined network (SDN)-based TCP congestion control mechanism, referred to as SDTCP, to leverage the features, e.g., centralized control methods and the global view of the network, in order to solve the TCP incast problems. When we detect network congestion on an OpenFlow switch, our controller can select the background flows and reduce their bandwidth by adjusting the advertised window of TCP ACK packets of the corresponding background flows so as to reserve more bandwidth for burst flows. SDTCP is transparent to the end systems and can accurately decelerate the rate of background flows by leveraging the global view of the network gained via SDN. The experiments demonstrate that our SDTCP can provide high tolerance for burst flows and achieve better flow completion time for short flows. Therefore, SDTCP is an effective and scalable solution for the TCP incast problem.

Experimental damage detection of wind turbine blade using thin film sensor array

NASA Astrophysics Data System (ADS)

Downey, Austin; Laflamme, Simon; Ubertini, Filippo; Sarkar, Partha

2017-04-01

Damage detection of wind turbine blades is difficult due to their large sizes and complex geometries. Additionally, economic restraints limit the viability of high-cost monitoring methods. While it is possible to monitor certain global signatures through modal analysis, obtaining useful measurements over a blade's surface using off-the-shelf sensing technologies is difficult and typically not economical. A solution is to deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel large-area electronic sensor measuring strain over very large surfaces. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a hybrid dense sensor network of soft elastomeric capacitors to detect, localize, and quantify damage, and resistive strain gauges to augment such dense sensor network with high accuracy data at key locations. The proposed hybrid dense sensor network is installed inside a wind turbine blade model and tested in a wind tunnel to simulate an operational environment. Damage in the form of changing boundary conditions is introduced into the monitored section of the blade. Results demonstrate the ability of the hybrid dense sensor network, and associated algorithms, to detect, localize, and quantify damage.

Measuring global monopole velocities, one by one

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lopez-Eiguren, Asier; Urrestilla, Jon; Achúcarro, Ana, E-mail: asier.lopez@ehu.eus, E-mail: jon.urrestilla@ehu.eus, E-mail: achucar@lorentz.leidenuniv.nl

We present an estimation of the average velocity of a network of global monopoles in a cosmological setting using large numerical simulations. In order to obtain the value of the velocity, we improve some already known methods, and present a new one. This new method estimates individual global monopole velocities in a network, by means of detecting each monopole position in the lattice and following the path described by each one of them. Using our new estimate we can settle an open question previously posed in the literature: velocity-dependent one-scale (VOS) models for global monopoles predict two branches of scalingmore » solutions, one with monopoles moving at subluminal speeds and one with monopoles moving at luminal speeds. Previous attempts to estimate monopole velocities had large uncertainties and were not able to settle that question. Our simulations find no evidence of a luminal branch. We also estimate the values of the parameters of the VOS model. With our new method we can also study the microphysics of the complicated dynamics of individual monopoles. Finally we use our large simulation volume to compare the results from the different estimator methods, as well as to asses the validity of the numerical approximations made.« less

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

An Intelligent Cooperative Visual Sensor Network for Urban Mobility

PubMed Central

Leone, Giuseppe Riccardo; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea

2017-01-01

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities. PMID:29125535

An Intelligent Cooperative Visual Sensor Network for Urban Mobility.

PubMed

Leone, Giuseppe Riccardo; Moroni, Davide; Pieri, Gabriele; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea; Marino, Francesco

2017-11-10

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.

Joint Program Executive Office for Chemical and Biological Defense Strategic Plan FY13-18

DTIC Science & Technology

2012-06-01

strategy calls for a global Biosurveillance network for timely disease surveillance of biological pathogens whether intentionally made or naturally... Biosurveillance . The President and Secretary of Defense provided renewed emphasis on rapidly and efficiently developing and manufacturing effective medical...and Force Protection Solutions to the Whole of Government and the Nation  Provide MCM for pre- and post- radiation exposure application , including

The Evolution and Expansion of Regional Disease Surveillance Networks and Their Role in Mitigating the Threat of Infectious Disease Outbreaks

PubMed Central

Bond, Katherine C.; Macfarlane, Sarah B.; Burke, Charlanne; Ungchusak, Kumnuan; Wibulpolprasert, Suwit

2013-01-01

We examine the emergence, development, and value of regional infectious disease surveillance networks that neighboring countries worldwide are organizing to control cross-border outbreaks at their source. The regional perspective represented in the paper is intended to serve as an instructive framework for others who decide to launch such networks as new technologies and emerging threats bring countries even closer together. Distinct from more formal networks in geographic regions designated by the World Health Organization (WHO), these networks usually involve groupings of fewer countries chosen by national governments to optimize surveillance efforts. Sometimes referred to as sub-regional, these “self-organizing” networks complement national and local government recognition with informal relationships across borders among epidemiologists, scientists, ministry officials, health workers, border officers, and community members. Their development over time reflects both incremental learning and growing connections among network actors; and changing disease patterns, with infectious disease threats shifting over time from local to regional to global levels. Not only has this regional disease surveillance network model expanded across the globe, it has also expanded from a mostly practitioner-based network model to one that covers training, capacity-building, and multidisciplinary research. Today, several of these networks are linked through Connecting Organizations for Regional Disease Surveillance (CORDS). We explore how regional disease surveillance networks add value to global disease detection and response by complementing other systems and efforts, by harnessing their power to achieve other goals such as health and human security, and by helping countries adapt to complex challenges via multi-sectoral solutions. We note that governmental commitment and trust among participating individuals are critical to the success of regional infectious disease surveillance networks. PMID:23362414

A Case for Open Network Health Systems: Systems as Networks in Public Mental Health

PubMed Central

Rhodes, Michael Grant; de Vries, Marten W.

2017-01-01

Increases in incidents involving so-called confused persons have brought attention to the potential costs of recent changes to public mental health (PMH) services in the Netherlands. Decentralized under the (Community) Participation Act (2014), local governments must find resources to compensate for reduced central funding to such services or "innovate." But innovation, even when pressure for change is intense, is difficult. This perspective paper describes experience during and after an investigation into a particularly violent incident and murder. The aim was to provide recommendations to improve the functioning of local PMH services. The investigation concluded that no specific failure by an individual professional or service provider facility led to the murder. Instead, also as a result of the Participation Act that severed communication lines between individuals and organizations, information sharing failures were likely to have reduced system level capacity to identify risks. The methods and analytical frameworks employed to reach this conclusion, also lead to discussion as to the plausibility of an unconventional solution. If improving communication is the primary problem, non-hierarchical information, and organizational networks arise as possible and innovative system solutions. The proposal for debate is that traditional "health system" definitions, literature and narratives, and operating assumptions in public (mental) health are ‘locked in’ constraining technical and organization innovations. If we view a "health system" as an adaptive system of economic and social "networks," it becomes clear that the current orthodox solution, the so-called integrated health system, typically results in a "centralized hierarchical" or "tree" network. An overlooked alternative that breaks out of the established policy narratives is the view of a ‘health systems’ as a non-hierarchical organizational structure or ‘Open Network.’ In turn, this opens new technological and organizational possibilities in seeking policy solutions, and suggests an alternative governance model of huge potential value in public health both locally and globally. PMID:28812792

A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing.

PubMed

Wang, Lipo; Li, Sa; Tian, Fuyu; Fu, Xiuju

2004-10-01

Recently Chen and Aihara have demonstrated both experimentally and mathematically that their chaotic simulated annealing (CSA) has better search ability for solving combinatorial optimization problems compared to both the Hopfield-Tank approach and stochastic simulated annealing (SSA). However, CSA may not find a globally optimal solution no matter how slowly annealing is carried out, because the chaotic dynamics are completely deterministic. In contrast, SSA tends to settle down to a global optimum if the temperature is reduced sufficiently slowly. Here we combine the best features of both SSA and CSA, thereby proposing a new approach for solving optimization problems, i.e., stochastic chaotic simulated annealing, by using a noisy chaotic neural network. We show the effectiveness of this new approach with two difficult combinatorial optimization problems, i.e., a traveling salesman problem and a channel assignment problem for cellular mobile communications.

Well-balanced high-order solver for blood flow in networks of vessels with variable properties.

PubMed

Müller, Lucas O; Toro, Eleuterio F

2013-12-01

We present a well-balanced, high-order non-linear numerical scheme for solving a hyperbolic system that models one-dimensional flow in blood vessels with variable mechanical and geometrical properties along their length. Using a suitable set of test problems with exact solution, we rigorously assess the performance of the scheme. In particular, we assess the well-balanced property and the effective order of accuracy through an empirical convergence rate study. Schemes of up to fifth order of accuracy in both space and time are implemented and assessed. The numerical methodology is then extended to realistic networks of elastic vessels and is validated against published state-of-the-art numerical solutions and experimental measurements. It is envisaged that the present scheme will constitute the building block for a closed, global model for the human circulation system involving arteries, veins, capillaries and cerebrospinal fluid. Copyright © 2013 John Wiley & Sons, Ltd.

Global interrupt and barrier networks

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E; Heidelberger, Philip; Kopcsay, Gerard V.; Steinmacher-Burow, Burkhard D.; Takken, Todd E.

2008-10-28

A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected by multiple independent networks, with each node including one or more processing elements for performing computation or communication activity as required when performing parallel algorithm operations. One multiple independent network includes a global tree network for enabling high-speed global tree communications among global tree network nodes or sub-trees thereof. The global interrupt and barrier network may operate in parallel with the global tree network for providing global asynchronous sideband signals.

Invasive species information networks: Collaboration at multiple scales for prevention, early detection, and rapid response to invasive alien species

USGS Publications Warehouse

Simpson, Annie; Jarnevich, Catherine S.; Madsen, John; Westbrooks, Randy G.; Fournier, Christine; Mehrhoff, Les; Browne, Michael; Graham, Jim; Sellers, Elizabeth A.

2009-01-01

Accurate analysis of present distributions and effective modeling of future distributions of invasive alien species (IAS) are both highly dependent on the availability and accessibility of occurrence data and natural history information about the species. Invasive alien species monitoring and detection networks (such as the Invasive Plant Atlas of New England and the Invasive Plant Atlas of the MidSouth) generate occurrence data at local and regional levels within the United States, which are shared through the US National Institute of Invasive Species Science. The Inter-American Biodiversity Information Network's Invasives Information Network (I3N), facilitates cooperation on sharing invasive species occurrence data throughout the Western Hemisphere. The I3N and other national and regional networks expose their data globally via the Global Invasive Species Information Network (GISIN). International and interdisciplinary cooperation on data sharing strengthens cooperation on strategies and responses to invasions. However, limitations to effective collaboration among invasive species networks leading to successful early detection and rapid response to invasive species include: lack of interoperability; data accessibility; funding; and technical expertise. This paper proposes various solutions to these obstacles at different geographic levels and briefly describes success stories from the invasive species information networks mentioned above. Using biological informatics to facilitate global information sharing is especially critical in invasive species science, as research has shown that one of the best indicators of the invasiveness of a species is whether it has been invasive elsewhere. Data must also be shared across disciplines because natural history information (e.g. diet, predators, habitat requirements, etc.) about a species in its native range is vital for effective prevention, detection, and rapid response to an invasion. Finally, it has been our experience that sharing information, including invasive species dispersal mechanisms and rates, impacts, and prevention and control strategies, enables resource managers and decision-makers to mount a more effective response to biological invasions.

Design and Analysis of Self-Adapted Task Scheduling Strategies in Wireless Sensor Networks

PubMed Central

Guo, Wenzhong; Xiong, Naixue; Chao, Han-Chieh; Hussain, Sajid; Chen, Guolong

2011-01-01

In a wireless sensor network (WSN), the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO) algorithm for the dynamic alliance (DPSO-DA) with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm’s ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms. PMID:22163971

Symmetry, Hopf bifurcation, and the emergence of cluster solutions in time delayed neural networks.

PubMed

Wang, Zhen; Campbell, Sue Ann

2017-11-01

We consider the networks of N identical oscillators with time delayed, global circulant coupling, modeled by a system of delay differential equations with Z N symmetry. We first study the existence of Hopf bifurcations induced by the coupling time delay and then use symmetric Hopf bifurcation theory to determine how these bifurcations lead to different patterns of symmetric cluster oscillations. We apply our results to a case study: a network of FitzHugh-Nagumo neurons with diffusive coupling. For this model, we derive the asymptotic stability, global asymptotic stability, absolute instability, and stability switches of the equilibrium point in the plane of coupling time delay (τ) and excitability parameter (a). We investigate the patterns of cluster oscillations induced by the time delay and determine the direction and stability of the bifurcating periodic orbits by employing the multiple timescales method and normal form theory. We find that in the region where stability switching occurs, the dynamics of the system can be switched from the equilibrium point to any symmetric cluster oscillation, and back to equilibrium point as the time delay is increased.

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

Evaluation of global satellite gravity models using terrestrial gravity observations over the Kingdom of Saudi Arabia A. Alothman and B. Elsaka

NASA Astrophysics Data System (ADS)

Alothman, Abdulaziz; Elsaka, Basem

The gravity field models from the GRACE and GOCE missions have increased the knowledge of the earth’s global gravity field. The latter GOCE mission has provided accuracies of about 1-2 cm and 1milli-Gal level in the global geoid and gravity anomaly, respectively. However, determining all wavelength ranges of the gravity field spectrum cannot be only achieved from satellite gravimetry but from the allowed terrestrial gravity data. In this contribution, we use a gravity network of 42 first-order absolute gravity stations, observed by LaCosta Romberg gravimeter during the period 1967-1969 by Ministry of Petroleum and Mineral Resources, to validate the GOCE gravity models in order to gain more detailed regional gravity information. The network stations are randomly distributed all over the country with a spacing of about 200 km apart. The results show that the geoid height and gravity anomaly determined from terrestrial gravity data agree with the GOCE based models and give additional information to the satellite gravity solutions.

Stability and global Hopf bifurcation in a delayed food web consisting of a prey and two predators

NASA Astrophysics Data System (ADS)

Meng, Xin-You; Huo, Hai-Feng; Zhang, Xiao-Bing

2011-11-01

This paper is concerned with a predator-prey system with Holling II functional response and hunting delay and gestation. By regarding the sum of delays as the bifurcation parameter, the local stability of the positive equilibrium and the existence of Hopf bifurcation are investigated. We obtained explicit formulas to determine the properties of Hopf bifurcation by using the normal form method and center manifold theorem. Special attention is paid to the global continuation of local Hopf bifurcation. Using a global Hopf bifurcation result of Wu [Wu JH. Symmetric functional differential equations and neural networks with memory, Trans Amer Math Soc 1998;350:4799-4838] for functional differential equations, we may show the global existence of the periodic solutions. Finally, several numerical simulations illustrating the theoretical analysis are also given.

Squeezeposenet: Image Based Pose Regression with Small Convolutional Neural Networks for Real Time Uas Navigation

NASA Astrophysics Data System (ADS)

Müller, M. S.; Urban, S.; Jutzi, B.

2017-08-01

The number of unmanned aerial vehicles (UAVs) is increasing since low-cost airborne systems are available for a wide range of users. The outdoor navigation of such vehicles is mostly based on global navigation satellite system (GNSS) methods to gain the vehicles trajectory. The drawback of satellite-based navigation are failures caused by occlusions and multi-path interferences. Beside this, local image-based solutions like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) can e.g. be used to support the GNSS solution by closing trajectory gaps but are computationally expensive. However, if the trajectory estimation is interrupted or not available a re-localization is mandatory. In this paper we will provide a novel method for a GNSS-free and fast image-based pose regression in a known area by utilizing a small convolutional neural network (CNN). With on-board processing in mind, we employ a lightweight CNN called SqueezeNet and use transfer learning to adapt the network to pose regression. Our experiments show promising results for GNSS-free and fast localization.

Geocenter variations derived from a combined processing of LEO- and ground-based GPS observations

NASA Astrophysics Data System (ADS)

Männel, Benjamin; Rothacher, Markus

2017-08-01

GNSS observations provided by the global tracking network of the International GNSS Service (IGS, Dow et al. in J Geod 83(3):191-198, 2009) play an important role in the realization of a unique terrestrial reference frame that is accurate enough to allow a detailed monitoring of the Earth's system. Combining these ground-based data with GPS observations tracked by high-quality dual-frequency receivers on-board low earth orbiters (LEOs) is a promising way to further improve the realization of the terrestrial reference frame and the estimation of geocenter coordinates, GPS satellite orbits and Earth rotation parameters. To assess the scope of the improvement on the geocenter coordinates, we processed a network of 53 globally distributed and stable IGS stations together with four LEOs (GRACE-A, GRACE-B, OSTM/Jason-2 and GOCE) over a time interval of 3 years (2010-2012). To ensure fully consistent solutions, the zero-difference phase observations of the ground stations and LEOs were processed in a common least-squares adjustment, estimating all the relevant parameters such as GPS and LEO orbits, station coordinates, Earth rotation parameters and geocenter motion. We present the significant impact of the individual LEO and a combination of all four LEOs on the geocenter coordinates. The formal errors are reduced by around 20% due to the inclusion of one LEO into the ground-only solution, while in a solution with four LEOs LEO-specific characteristics are significantly reduced. We compare the derived geocenter coordinates w.r.t. LAGEOS results and external solutions based on GPS and SLR data. We found good agreement in the amplitudes of all components; however, the phases in x- and z-direction do not agree well.

Local and global Hopf bifurcation analysis in a neutral-type neuron system with two delays

NASA Astrophysics Data System (ADS)

Lv, Qiuyu; Liao, Xiaofeng

2018-03-01

In recent years, neutral-type differential-difference equations have been applied extensively in the field of engineering, and their dynamical behaviors are more complex than that of the delay differential-difference equations. In this paper, the equations used to describe a neutral-type neural network system of differential difference equation with two delays are studied (i.e. neutral-type differential equations). Firstly, by selecting τ1, τ2 respectively as a parameter, we provide an analysis about the local stability of the zero equilibrium point of the equations, and sufficient conditions of asymptotic stability for the system are derived. Secondly, by using the theory of normal form and applying the theorem of center manifold introduced by Hassard et al., the Hopf bifurcation is found and some formulas for deciding the stability of periodic solutions and the direction of Hopf bifurcation are given. Moreover, by applying the theorem of global Hopf bifurcation, the existence of global periodic solution of the system is studied. Finally, an example is given, and some computer numerical simulations are taken to demonstrate and certify the correctness of the presented results.

The Air Force Interactive Meteorological System: A Research Tool for Satellite Meteorology

DTIC Science & Technology

1992-12-02

NFARnet itself is a subnet to the global computer network INTERNET that links nearly all U.S. government research facilities and universi- ties along...required input to a generalized mathematical solution to the satellite/earth coordinate transform used for earth location of GOES sensor data. A direct...capability also exists to convert absolute coordinates to relative coordinates for transformations associated with gridded fields. 3. Spatial objective

Restructuring for the 90s and Beyond: Solution Based Learning in the Era of Smart Homes, Wired Communities, Fast Systems, Global Networks, and Fast Forward Learners in a Borderless World.

ERIC Educational Resources Information Center

Groff, Warren H.

An ultimate purpose of education is human resource development to provide society with a critical mass of intellectual capital and competent workforces. To accomplish this end, leaders implement planning processes to guide policy-making, develop institutions, and allocate resources. Although new information technologies are becoming commonplace in…

Evolutionary optimization with data collocation for reverse engineering of biological networks.

PubMed

Tsai, Kuan-Yao; Wang, Feng-Sheng

2005-04-01

Modern experimental biology is moving away from analyses of single elements to whole-organism measurements. Such measured time-course data contain a wealth of information about the structure and dynamic of the pathway or network. The dynamic modeling of the whole systems is formulated as a reverse problem that requires a well-suited mathematical model and a very efficient computational method to identify the model structure and parameters. Numerical integration for differential equations and finding global parameter values are still two major challenges in this field of the parameter estimation of nonlinear dynamic biological systems. We compare three techniques of parameter estimation for nonlinear dynamic biological systems. In the proposed scheme, the modified collocation method is applied to convert the differential equations to the system of algebraic equations. The observed time-course data are then substituted into the algebraic system equations to decouple system interactions in order to obtain the approximate model profiles. Hybrid differential evolution (HDE) with population size of five is able to find a global solution. The method is not only suited for parameter estimation but also can be applied for structure identification. The solution obtained by HDE is then used as the starting point for a local search method to yield the refined estimates.

Analyzing milestoning networks for molecular kinetics: definitions, algorithms, and examples.

PubMed

Viswanath, Shruthi; Kreuzer, Steven M; Cardenas, Alfredo E; Elber, Ron

2013-11-07

Network representations are becoming increasingly popular for analyzing kinetic data from techniques like Milestoning, Markov State Models, and Transition Path Theory. Mapping continuous phase space trajectories into a relatively small number of discrete states helps in visualization of the data and in dissecting complex dynamics to concrete mechanisms. However, not only are molecular networks derived from molecular dynamics simulations growing in number, they are also getting increasingly complex, owing partly to the growth in computer power that allows us to generate longer and better converged trajectories. The increased complexity of the networks makes simple interpretation and qualitative insight of the molecular systems more difficult to achieve. In this paper, we focus on various network representations of kinetic data and algorithms to identify important edges and pathways in these networks. The kinetic data can be local and partial (such as the value of rate coefficients between states) or an exact solution to kinetic equations for the entire system (such as the stationary flux between vertices). In particular, we focus on the Milestoning method that provides fluxes as the main output. We proposed Global Maximum Weight Pathways as a useful tool for analyzing molecular mechanism in Milestoning networks. A closely related definition was made in the context of Transition Path Theory. We consider three algorithms to find Global Maximum Weight Pathways: Recursive Dijkstra's, Edge-Elimination, and Edge-List Bisection. The asymptotic efficiency of the algorithms is analyzed and numerical tests on finite networks show that Edge-List Bisection and Recursive Dijkstra's algorithms are most efficient for sparse and dense networks, respectively. Pathways are illustrated for two examples: helix unfolding and membrane permeation. Finally, we illustrate that networks based on local kinetic information can lead to incorrect interpretation of molecular mechanisms.

Optimal water networks in protein cavities with GAsol and 3D-RISM.

PubMed

Fusani, Lucia; Wall, Ian; Palmer, David; Cortes, Alvaro

2018-06-01

Water molecules in protein binding sites play essential roles in biological processes. The popular 3D-RISM prediction method can calculate the solvent density distribution within minutes, but is difficult to convert it into explicit water molecules. We present GAsol, a tool that is capable of finding the network of water molecules that best fits a particular 3D-RISM density distribution in a fast and accurate manner and that outperforms other available tools by finding the globally optimal solution thanks to its genetic algorithm. https://github.com/accsc/GAsol. BSD 3-clauses license. alvaro.x.cortes@gsk.com. Supplementary data are available at Bioinformatics online.

Application of the Undifferenced GNSS Precise Positioning in Determining Coordinates in National Reference Frames

NASA Astrophysics Data System (ADS)

Krzan, Grzegorz; Stępniak, Katarzyna

2017-09-01

In high-accuracy positioning using GNSS, the most common solution is still relative positioning using double-difference observations of dual-frequency measurements. An increasingly popular alternative to relative positioning are undifferenced approaches, which are designed to make full use of modern satellite systems and signals. Positions referenced to global International Terrestrial Reference Frame (ITRF2008) obtained from Precise Point Positioning (PPP) or Undifferenced (UD) network solutions have to be transformed to national (regional) reference frame, which introduces additional bases related to the transformation process. In this paper, satellite observations from two test networks using different observation time series were processed. The first test concerns the positioning accuracy from processing one year of dual-frequency GPS observations from 14 EUREF Permanent Network (EPN) stations using NAPEOS 3.3.1 software. The results were transformed into a national reference frame (PL-ETRF2000) and compared to positions from an EPN cumulative solution, which was adopted as the true coordinates. Daily observations were processed using PPP and UD multi-station solutions to determine the final accuracy resulting from satellite positioning, the transformation to national coordinate systems and Eurasian intraplate plate velocities. The second numerical test involved similar processing strategies of post-processing carried out using different observation time series (30 min., 1 hour, 2 hours, daily) and different classes of GNSS receivers. The centimeter accuracy of results presented in the national coordinate system satisfies the requirements of many surveying and engineering applications.

Impact of ambiguity resolution and application of transformation parameters obtained by regional GNSS network in Precise Point Positioning

NASA Astrophysics Data System (ADS)

Gandolfi, S.; Poluzzi, L.; Tavasci, L.

2012-12-01

Precise Point Positioning (PPP) is one of the possible approaches for GNSS data processing. As known this technique is faster and more flexible compared to the others which are based on a differenced approach and constitute a reliable methods for accurate positioning of remote GNSS stations, even in some remote area such as Antarctica. Until few years ago one of the major limits of the method was the impossibility to resolve the ambiguity as integer but nowadays many methods are available to resolve this aspect. The first software package permitting a PPP solution was the GIPSY OASIS realized, developed and maintained by JPL (NASA). JPL produce also orbits and files ready to be used with GIPSY. Recently, using these products came possible to resolve ambiguities improving the stability of solutions. PPP permit to estimate position into the reference frame of the orbits (IGS) and when coordinate in others reference frames, such al ITRF, are needed is necessary to apply a transformation. Within his products JPL offer, for each day, a global 7 parameter transformation that permit to locate the survey into the ITRF RF. In some cases it's also possible to create a costumed process and obtain analogous parameters using local/regional reference network of stations which coordinates are available also in the desired reference frame. In this work some tests on accuracy has been carried out comparing different PPP solutions obtained using the same software packages (GIPSY) but considering the ambiguity resolution, the global and regional transformation parameters. In particular two test area have been considered, first one located in Antarctica and the second one in Italy. Aim of the work is the evaluation of the impact of ambiguity resolution and the use of local/regional transformation parameter in the final solutions. Tests shown how the ambiguity resolution improve the precision, especially in the EAST component with a scattering reduction about 8%. And the use of global transformation parameter permit to improve the accuracy of about 59%, 63% and 29% in the three components N E U, but other tests shown how is possible to improve the accuracy of 67% 71% and 53% using regional transformation parameters. Example of the impact of global vs regional parameters transformation in a GPS time series

Extracellular magnesium enhances the damage to locomotor networks produced by metabolic perturbation mimicking spinal injury in the neonatal rat spinal cord in vitro.

PubMed

Margaryan, G; Mladinic, M; Mattioli, C; Nistri, A

2009-10-06

An acute injury to brain or spinal cord produces profound metabolic perturbation that extends and exacerbates tissue damage. Recent clinical interventions to treat this condition with i.v. Mg(2+) to stabilize its extracellular concentration provided disappointing results. The present study used an in vitro spinal cord model from the neonatal rat to investigate the role of extracellular Mg(2+) in the lesion evoked by a pathological medium mimicking the metabolic perturbation (hypoxia, aglycemia, oxidative stress, and acid pH) occurring in vivo. Damage was measured by taking as outcome locomotor network activity for up to 24 h after the primary insult. Pathological medium in 1 mM Mg(2+) solution (1 h) largely depressed spinal reflexes and suppressed fictive locomotion on the same and the following day. Conversely, pathological medium in either Mg(2+)-free or 5 mM Mg(2+) solution evoked temporary network depression and enabled fictive locomotion the day after. While global cell death was similar regardless of extracellular Mg(2+) solution, white matter was particularly affected. In ventral horn the number of surviving neurons was the highest in Mg(2+) free solution and the lowest in 1 mM Mg(2+), while motoneurons were unaffected. Although the excitotoxic damage elicited by kainate was insensitive to extracellular Mg(2+), 1 mM Mg(2+) potentiated the effect of combining pathological medium with kainate at low concentrations. These results indicate that preserving Mg(2+) homeostasis rendered experimental spinal injury more severe. Furthermore, analyzing ventral horn neuron numbers in relation to fictive locomotion expression might provide a first estimate of the minimal size of the functional locomotor network.

SDTCP: Towards Datacenter TCP Congestion Control with SDN for IoT Applications

PubMed Central

Lu, Yifei; Ling, Zhen; Zhu, Shuhong; Tang, Ling

2017-01-01

The Internet of Things (IoT) has gained popularity in recent years. Today’s IoT applications are now increasingly deployed in cloud platforms to perform Big Data analytics. In cloud data center networks (DCN), TCP incast usually happens when multiple senders simultaneously communicate with a single receiver. However, when TCP incast happens, DCN may suffer from both throughput collapse for TCP burst flows and temporary starvation for TCP background flows. In this paper, we propose a software defined network (SDN)-based TCP congestion control mechanism, referred to as SDTCP, to leverage the features, e.g., centralized control methods and the global view of the network, in order to solve the TCP incast problems. When we detect network congestion on an OpenFlow switch, our controller can select the background flows and reduce their bandwidth by adjusting the advertised window of TCP ACK packets of the corresponding background flows so as to reserve more bandwidth for burst flows. SDTCP is transparent to the end systems and can accurately decelerate the rate of background flows by leveraging the global view of the network gained via SDN. The experiments demonstrate that our SDTCP can provide high tolerance for burst flows and achieve better flow completion time for short flows. Therefore, SDTCP is an effective and scalable solution for the TCP incast problem. PMID:28075347

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bordetsky, A; Dougan, A D; Nekoogar, F

The paper addresses technological and operational challenges of developing a global plug-and-play Maritime Domain Security testbed for the Global War on Terrorism mission. This joint NPS-LLNL project is based on the NPS Tactical Network Topology (TNT) composed of long-haul OFDM networks combined with self-forming wireless mesh links to air, surface, ground, and underwater unmanned vehicles. This long-haul network is combined with ultra-wideband (UWB) communications systems for wireless communications in harsh radio propagation channels. LLNL's UWB communication prototypes are designed to overcome shortcomings of the present narrowband communications systems in heavy metallic and constricted corridors inside ships. In the center ofmore » our discussion are networking solutions for the Maritime Interdiction Operation (MIO) Experiments in which geographically distributed command centers and subject matter experts collaborate with the Boarding Party in real time to facilitate situational understanding and course of action selection. The most recent experiment conducted via the testbed extension to the Alameda Island exercised several key technologies aimed at improving MIO. These technologies included UWB communications from within the ship to Boarding Party leader sending data files and pictures, advanced radiation detection equipment for search and identification, biometric equipment to record and send fingerprint files to facilitate rapid positive identification of crew members, and the latest updates of the NPS Tactical Network Topology facilitating reachback to LLNL, Biometric Fusion Center, USCG, and DTRA experts.« less

Assessment of second- and third-order ionospheric effects on regional networks: case study in China with longer CMONOC GPS coordinate time series

NASA Astrophysics Data System (ADS)

Deng, Liansheng; Jiang, Weiping; Li, Zhao; Chen, Hua; Wang, Kaihua; Ma, Yifang

2017-02-01

Higher-order ionospheric (HOI) delays are one of the principal technique-specific error sources in precise global positioning system analysis and have been proposed to become a standard part of precise GPS data processing. In this research, we apply HOI delay corrections to the Crustal Movement Observation Network of China's (CMONOC) data processing (from January 2000 to December 2013) and furnish quantitative results for the effects of HOI on CMONOC coordinate time series. The results for both a regional reference frame and global reference frame are analyzed and compared to clarify the HOI effects on the CMONOC network. We find that HOI corrections can effectively reduce the semi-annual signals in the northern and vertical components. For sites with lower semi-annual amplitudes, the average decrease in magnitude can reach 30 and 10 % for the northern and vertical components, respectively. The noise amplitudes with HOI corrections and those without HOI corrections are not significantly different. Generally, the HOI effects on CMONOC networks in a global reference frame are less obvious than the results in the regional reference frame, probably because the HOI-induced errors are smaller in comparison to the higher noise levels seen when using a global reference frame. Furthermore, we investigate the combined contributions of environmental loading and HOI effects on the CMONOC stations. The largest loading effects on the vertical displacement are found in the mid- to high-latitude areas. The weighted root mean square differences between the corrected and original weekly GPS height time series of the loading model indicate that the mass loading adequately reduced the scatter on the CMONOC height time series, whereas the results in the global reference frame showed better agreements between the GPS coordinate time series and the environmental loading. When combining the effects of environmental loading and HOI corrections, the results with the HOI corrections reduced the scatter on the observed GPS height coordinates better than the height when estimated without HOI corrections, and the combined solutions in the regional reference frame indicate more preferred improvements. Therefore, regional reference frames are recommended to investigate the HOI effects on regional networks.

Software for autonomous astronomical observatories: challenges and opportunities in the age of big data

NASA Astrophysics Data System (ADS)

Sybilski, Piotr W.; Pawłaszek, Rafał; Kozłowski, Stanisław K.; Konacki, Maciej; Ratajczak, Milena; Hełminiak, Krzysztof G.

2014-07-01

We present the software solution developed for a network of autonomous telescopes, deployed and tested in Solaris Project. The software aims to fulfil the contemporary needs of distributed autonomous observatories housing medium sized telescopes: ergonomics, availability, security and reusability. The datafication of such facilities seems inevitable and we give a preliminary study of the challenges and opportunities waiting for software developers. Project Solaris is a global network of four 0.5 m autonomous telescopes conducting a survey of eclipsing binaries in the Southern Hemisphere. The Project's goal is to detect and characterise circumbinary planets using the eclipse timing method. The observatories are located on three continents, and the headquarters coordinating and monitoring the network is in Poland. All four are operational as of December 2013.

Human-centric sensing.

PubMed

Srivastava, Mani; Abdelzaher, Tarek; Szymanski, Boleslaw

2012-01-13

The first decade of the century witnessed a proliferation of devices with sensing and communication capabilities in the possession of the average individual. Examples range from camera phones and wireless global positioning system units to sensor-equipped, networked fitness devices and entertainment platforms (such as Wii). Social networking platforms emerged, such as Twitter, that allow sharing information in real time. The unprecedented deployment scale of such sensors and connectivity options ushers in an era of novel data-driven applications that rely on inputs collected by networks of humans or measured by sensors acting on their behalf. These applications will impact domains as diverse as health, transportation, energy, disaster recovery, intelligence and warfare. This paper surveys the important opportunities in human-centric sensing, identifies challenges brought about by such opportunities and describes emerging solutions to these challenges.

O(t-α)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations.

PubMed

Chen, Jiejie; Chen, Boshan; Zeng, Zhigang

2018-04-01

This paper investigates O(t -α )-synchronization and adaptive Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations. Firstly, based on the framework of Filippov solution and differential inclusion theory, using a Razumikhin-type method, some sufficient conditions ensuring the global O(t -α )-synchronization of considered networks are established via a linear-type discontinuous control. Next, a new fractional differential inequality is established and two new discontinuous adaptive controller is designed to achieve Mittag-Leffler synchronization between the drive system and the response systems using this inequality. Finally, two numerical simulations are given to show the effectiveness of the theoretical results. Our approach and theoretical results have a leading significance in the design of synchronized fractional-order memristive neural networks circuits involving discontinuous activations and time-varying delays. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dynamic Business Networks: A Headache for Sustainable Systems Interoperability

NASA Astrophysics Data System (ADS)

Agostinho, Carlos; Jardim-Goncalves, Ricardo

Collaborative networked environments emerged with the spread of the internet, contributing to overcome past communication barriers, and identifying interoperability as an essential property. When achieved seamlessly, efficiency is increased in the entire product life cycle. Nowadays, most organizations try to attain interoperability by establishing peer-to-peer mappings with the different partners, or in optimized networks, by using international standard models as the core for information exchange. In current industrial practice, mappings are only defined once, and the morphisms that represent them, are hardcoded in the enterprise systems. This solution has been effective for static environments, where enterprise and product models are valid for decades. However, with an increasingly complex and dynamic global market, models change frequently to answer new customer requirements. This paper draws concepts from the complex systems science and proposes a framework for sustainable systems interoperability in dynamic networks, enabling different organizations to evolve at their own rate.

National research and education network

NASA Technical Reports Server (NTRS)

Villasenor, Tony

1991-01-01

Some goals of this network are as follows: Extend U.S. technological leadership in high performance computing and computer communications; Provide wide dissemination and application of the technologies both to the speed and the pace of innovation and to serve the national economy, national security, education, and the global environment; and Spur gains in the U.S. productivity and industrial competitiveness by making high performance computing and networking technologies an integral part of the design and production process. Strategies for achieving these goals are as follows: Support solutions to important scientific and technical challenges through a vigorous R and D effort; Reduce the uncertainties to industry for R and D and use of this technology through increased cooperation between government, industry, and universities and by the continued use of government and government funded facilities as a prototype user for early commercial HPCC products; and Support underlying research, network, and computational infrastructures on which U.S. high performance computing technology is based.

The Power of Many: Nanosatellites For Cost Effective Global Weather Data

NASA Astrophysics Data System (ADS)

Greenberg, A.; Platzer, P.

2015-12-01

While weather processing technology through modeling and simulations has continued to advance, the amount of raw data available for analysis has dwindled. Most raw weather data is collected from satellites that are past their intended decommission date, and the likelihood of a catastrophic failure and diminishing reliability increases with each passing day. A United States government report released this year recognized the potential risk that this creates, citing a few alternatives to our aging satellite technology to at least maintain the level of raw weather data we currently have available. This report also highlighted nanosatellites as one of the most promising solutions, due in no small part to their standard form factor, translating into increased launch capabilities and better resiliency with fewer points of failure, rapidly advancing technology and low capital expenditure. Taking advantage of rapid advancements in sensor technology, these nanosatellites are replaced every two years or less and de-orbit quickly. Each new generation carries an improved payload and offers more network-wide resiliency. A constellation of just ten GPS-RO enabled nanosatellites taking measurements from every point on Earth, coupled with a globally distributed network of ground stations, can provide five times more radio occultation data than the combined efforts of current weather satellites. By the end of this year, Spire Global, Inc. will launch the world's first network of commercial weather satellites using GPS-RO for raw data collection.

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.

Network structure impacts global commodity trade growth and resilience.

PubMed

Kharrazi, Ali; Rovenskaya, Elena; Fath, Brian D

2017-01-01

Global commodity trade networks are critical to our collective sustainable development. Their increasing interconnectedness pose two practical questions: (i) Do the current network configurations support their further growth? (ii) How resilient are these networks to economic shocks? We analyze the data of global commodity trade flows from 1996 to 2012 to evaluate the relationship between structural properties of the global commodity trade networks and (a) their dynamic growth, as well as (b) the resilience of their growth with respect to the 2009 global economic shock. Specifically, we explore the role of network efficiency and redundancy using the information theory-based network flow analysis. We find that, while network efficiency is positively correlated with growth, highly efficient systems appear to be less resilient, losing more and gaining less growth following an economic shock. While all examined networks are rather redundant, we find that network redundancy does not hinder their growth. Moreover, systems exhibiting higher levels of redundancy lose less and gain more growth following an economic shock. We suggest that a strategy to support making global trade networks more efficient via, e.g., preferential trade agreements and higher specialization, can promote their further growth; while a strategy to increase the global trade networks' redundancy via e.g., more abundant free-trade agreements, can improve their resilience to global economic shocks.

Local effects of redundant terrestrial and GPS-based tie vectors in ITRF-like combinations

NASA Astrophysics Data System (ADS)

Abbondanza, Claudio; Altamimi, Zuheir; Sarti, Pierguido; Negusini, Monia; Vittuari, Luca

2009-11-01

Tie vectors (TVs) between co-located space geodetic instruments are essential for combining terrestrial reference frames (TRFs) realised using different techniques. They provide relative positioning between instrumental reference points (RPs) which are part of a global geodetic network such as the international terrestrial reference frame (ITRF). This paper gathers the set of very long baseline interferometry (VLBI)-global positioning system (GPS) local ties performed at the observatory of Medicina (Northern Italy) during the years 2001-2006 and discusses some important aspects related to the usage of co-location ties in the combinations of TRFs. Two measurement approaches of local survey are considered here: a GPS-based approach and a classical approach based on terrestrial observations (i.e. angles, distances and height differences). The behaviour of terrestrial local ties, which routinely join combinations of space geodetic solutions, is compared to that of GPS-based local ties. In particular, we have performed and analysed different combinations of satellite laser ranging (SLR), VLBI and GPS long term solutions in order to (i) evaluate the local effects of the insertion of the series of TVs computed at Medicina, (ii) investigate the consistency of GPS-based TVs with respect to space geodetic solutions, (iii) discuss the effects of an imprecise alignment of TVs from a local to a global reference frame. Results of ITRF-like combinations show that terrestrial TVs originate the smallest residuals in all the three components. In most cases, GPS-based TVs fit space geodetic solutions very well, especially in the horizontal components (N, E). On the contrary, the estimation of the VLBI RP Up component through GPS technique appears to be awkward, since the corresponding post fit residuals are considerably larger. Besides, combination tests including multi-temporal TVs display local effects of residual redistribution, when compared to those solutions where Medicina TVs are added one at a time. Finally, the combination of TRFs turns out to be sensitive to the orientation of the local tie into the global frame.

Random Evolution of Idiotypic Networks: Dynamics and Architecture

NASA Astrophysics Data System (ADS)

Brede, Markus; Behn, Ulrich

The paper deals with modelling a subsystem of the immune system, the so-called idiotypic network (INW). INWs, conceived by N.K. Jerne in 1974, are functional networks of interacting antibodies and B cells. In principle, Jernes' framework provides solutions to many issues in immunology, such as immunological memory, mechanisms for antigen recognition and self/non-self discrimination. Explaining the interconnection between the elementary components, local dynamics, network formation and architecture, and possible modes of global system function appears to be an ideal playground of statistical mechanics. We present a simple cellular automaton model, based on a graph representation of the system. From a simplified description of idiotypic interactions, rules for the random evolution of networks of occupied and empty sites on these graphs are derived. In certain biologically relevant parameter ranges the resultant dynamics leads to stationary states. A stationary state is found to correspond to a specific pattern of network organization. It turns out that even these very simple rules give rise to a multitude of different kinds of patterns. We characterize these networks by classifying `static' and `dynamic' network-patterns. A type of `dynamic' network is found to display many features of real INWs.

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

GPS-Only Terrestrial Reference Frame Based on a Global Reprocessing

NASA Astrophysics Data System (ADS)

Dietrich, R.; Rothacher, M.; Ruelke, A.; Fritsche, M.; Steigenberger, P.

2007-12-01

The realization of the International Terrestrial Reference System (ITRS) with highest accuracy and stability is fundamental and crucial for applications in geodesy, geodynamics, geophysics and global change. In a joint effort TU Dresden and TU Munich/GFZ Potsdam reprocessed a global GPS network of more than 200 stations. As a contribution to an ITRS realization daily normal equations from 1994 to 2005 were rigorously combined in order to determine a global GPS-only reference frame (PDR05/Potsdam-Dresden-Reprocessing Reference Frame). We present a realization of the global terrestrial reference system which follows the center of mass approach in consideration of the load-induced deformation of the Earth's crust due to the redistribution of surface masses. The stability of our reference frame will be evaluated based on the obtained long-term trends of station coordinates, the load-induced deformation estimates and the homogeneous time series of station positions. We will compare our solution with other recent terrestrial reference system realizations and give some conclusions for future realizations of the ITRS.

Implementation study of an analog spiking neural network for assisting cardiac delay prediction in a cardiac resynchronization therapy device.

PubMed

Sun, Qing; Schwartz, François; Michel, Jacques; Herve, Yannick; Dalmolin, Renzo

2011-06-01

In this paper, we aim at developing an analog spiking neural network (SNN) for reinforcing the performance of conventional cardiac resynchronization therapy (CRT) devices (also called biventricular pacemakers). Targeting an alternative analog solution in 0.13- μm CMOS technology, this paper proposes an approach to improve cardiac delay predictions in every cardiac period in order to assist the CRT device to provide real-time optimal heartbeats. The primary analog SNN architecture is proposed and its implementation is studied to fulfill the requirement of very low energy consumption. By using the Hebbian learning and reinforcement learning algorithms, the intended adaptive CRT device works with different functional modes. The simulations of both learning algorithms have been carried out, and they were shown to demonstrate the global functionalities. To improve the realism of the system, we introduce various heart behavior models (with constant/variable heart rates) that allow pathologic simulations with/without noise on the signals of the input sensors. The simulations of the global system (pacemaker models coupled with heart models) have been investigated and used to validate the analog spiking neural network implementation.

Deriving Global Convection Maps From SuperDARN Measurements

NASA Astrophysics Data System (ADS)

Gjerloev, J. W.; Waters, C. L.; Barnes, R. J.

2018-04-01

A new statistical modeling technique for determining the global ionospheric convection is described. The principal component regression (PCR)-based technique is based on Super Dual Auroral Radar Network (SuperDARN) observations and is an advanced version of the PCR technique that Waters et al. (https//:doi.org.10.1002/2015JA021596) used for the SuperMAG data. While SuperMAG ground magnetic field perturbations are vector measurements, SuperDARN provides line-of-sight measurements of the ionospheric convection flow. Each line-of-sight flow has a known azimuth (or direction), which must be converted into the actual vector flow. However, the component perpendicular to the azimuth direction is unknown. Our method uses historical data from the SuperDARN database and PCR to determine a fill-in model convection distribution for any given universal time. The fill-in data process is driven by a list of state descriptors (magnetic indices and the solar zenith angle). The final solution is then derived from a spherical cap harmonic fit to the SuperDARN measurements and the fill-in model. When compared with the standard SuperDARN fill-in model, we find that our fill-in model provides improved solutions, and the final solutions are in better agreement with the SuperDARN measurements. Our solutions are far less dynamic than the standard SuperDARN solutions, which we interpret as being due to a lack of magnetosphere-ionosphere inertia and communication delays in the standard SuperDARN technique while it is inherently included in our approach. Rather, we argue that the magnetosphere-ionosphere system has inertia that prevents the global convection from changing abruptly in response to an interplanetary magnetic field change.

A Case for Open Network Health Systems: Systems as Networks in Public Mental Health.

PubMed

Rhodes, Michael Grant; de Vries, Marten W

2017-01-08

Increases in incidents involving so-called confused persons have brought attention to the potential costs of recent changes to public mental health (PMH) services in the Netherlands. Decentralized under the (Community) Participation Act (2014), local governments must find resources to compensate for reduced central funding to such services or "innovate." But innovation, even when pressure for change is intense, is difficult. This perspective paper describes experience during and after an investigation into a particularly violent incident and murder. The aim was to provide recommendations to improve the functioning of local PMH services. The investigation concluded that no specific failure by an individual professional or service provider facility led to the murder. Instead, also as a result of the Participation Act that severed communication lines between individuals and organizations, information sharing failures were likely to have reduced system level capacity to identify risks. The methods and analytical frameworks employed to reach this conclusion, also lead to discussion as to the plausibility of an unconventional solution. If improving communication is the primary problem, non-hierarchical information, and organizational networks arise as possible and innovative system solutions. The proposal for debate is that traditional "health system" definitions, literature and narratives, and operating assumptions in public (mental) health are 'locked in' constraining technical and organization innovations. If we view a "health system" as an adaptive system of economic and social "networks," it becomes clear that the current orthodox solution, the so-called integrated health system, typically results in a "centralized hierarchical" or "tree" network. An overlooked alternative that breaks out of the established policy narratives is the view of a 'health systems' as a non-hierarchical organizational structure or 'Open Network.' In turn, this opens new technological and organizational possibilities in seeking policy solutions, and suggests an alternative governance model of huge potential value in public health both locally and globally. © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Network structure impacts global commodity trade growth and resilience

PubMed Central

Rovenskaya, Elena; Fath, Brian D.

2017-01-01

Global commodity trade networks are critical to our collective sustainable development. Their increasing interconnectedness pose two practical questions: (i) Do the current network configurations support their further growth? (ii) How resilient are these networks to economic shocks? We analyze the data of global commodity trade flows from 1996 to 2012 to evaluate the relationship between structural properties of the global commodity trade networks and (a) their dynamic growth, as well as (b) the resilience of their growth with respect to the 2009 global economic shock. Specifically, we explore the role of network efficiency and redundancy using the information theory-based network flow analysis. We find that, while network efficiency is positively correlated with growth, highly efficient systems appear to be less resilient, losing more and gaining less growth following an economic shock. While all examined networks are rather redundant, we find that network redundancy does not hinder their growth. Moreover, systems exhibiting higher levels of redundancy lose less and gain more growth following an economic shock. We suggest that a strategy to support making global trade networks more efficient via, e.g., preferential trade agreements and higher specialization, can promote their further growth; while a strategy to increase the global trade networks’ redundancy via e.g., more abundant free-trade agreements, can improve their resilience to global economic shocks. PMID:28207790

International GPS Service for Geodynamics

NASA Technical Reports Server (NTRS)

Zumberge, J. F. (Editor); Urban, M. P. (Editor); Liu, R. (Editor); Neilan, R. E. (Editor)

1996-01-01

This 1995 annual report of the IGS International GPS (Global Positioning System) Service for Geodynamics - describes the second operational year of the service. It provides the many IGS contributing agencies and the rapidly growing user community with essential information on current organizational and technical matters promoting the IGS standards and products (including organizational framework, data processing strategies, and statistics showing the remarkable expansion of the GPS monitoring network, the improvement of IGS performance, and product quality). It also introduces important practical concepts for network densification by integration of regional stations and the combination of station coordinate solutions. There are groups of articles describing general aspects of the IGS, the Associate Analysis Centers (AACs), Data Centers, and IGS stations.

The DYNES Instrument: A Description and Overview

NASA Astrophysics Data System (ADS)

Zurawski, Jason; Ball, Robert; Barczyk, Artur; Binkley, Mathew; Boote, Jeff; Boyd, Eric; Brown, Aaron; Brown, Robert; Lehman, Tom; McKee, Shawn; Meekhof, Benjeman; Mughal, Azher; Newman, Harvey; Rozsa, Sandor; Sheldon, Paul; Tackett, Alan; Voicu, Ramiro; Wolff, Stephen; Yang, Xi

2012-12-01

Scientific innovation continues to increase requirements for the computing and networking infrastructures of the world. Collaborative partners, instrumentation, storage, and processing facilities are often geographically and topologically separated, as is the case with LHC virtual organizations. These separations challenge the technology used to interconnect available resources, often delivered by Research and Education (R&E) networking providers, and leads to complications in the overall process of end-to-end data management. Capacity and traffic management are key concerns of R&E network operators; a delicate balance is required to serve both long-lived, high capacity network flows, as well as more traditional end-user activities. The advent of dynamic circuit services, a technology that enables the creation of variable duration, guaranteed bandwidth networking channels, allows for the efficient use of common network infrastructures. These gains are seen particularly in locations where overall capacity is scarce compared to the (sustained peak) needs of user communities. Related efforts, including those of the LHCOPN [3] operations group and the emerging LHCONE [4] project, may take advantage of available resources by designating specific network activities as a “high priority”, allowing reservation of dedicated bandwidth or optimizing for deadline scheduling and predicable delivery patterns. This paper presents the DYNES instrument, an NSF funded cyberinfrastructure project designed to facilitate end-to-end dynamic circuit services [2]. This combination of hardware and software innovation is being deployed across R&E networks in the United States at selected end-sites located on University Campuses. DYNES is peering with international efforts in other countries using similar solutions, and is increasing the reach of this emerging technology. This global data movement solution could be integrated into computing paradigms such as cloud and grid computing platforms, and through the use of APIs can be integrated into existing data movement software.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks.

PubMed

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-08-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

Efficient Characterization of Parametric Uncertainty of Complex (Bio)chemical Networks

PubMed Central

Schillings, Claudia; Sunnåker, Mikael; Stelling, Jörg; Schwab, Christoph

2015-01-01

Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is “non-intrusive” and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design. PMID:26317784

An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network.

PubMed

Cheng, Jing; Xia, Linyuan

2016-08-31

Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm.

An Effective Cuckoo Search Algorithm for Node Localization in Wireless Sensor Network

PubMed Central

Cheng, Jing; Xia, Linyuan

2016-01-01

Localization is an essential requirement in the increasing prevalence of wireless sensor network (WSN) applications. Reducing the computational complexity, communication overhead in WSN localization is of paramount importance in order to prolong the lifetime of the energy-limited sensor nodes and improve localization performance. This paper proposes an effective Cuckoo Search (CS) algorithm for node localization. Based on the modification of step size, this approach enables the population to approach global optimal solution rapidly, and the fitness of each solution is employed to build mutation probability for avoiding local convergence. Further, the approach restricts the population in the certain range so that it can prevent the energy consumption caused by insignificant search. Extensive experiments were conducted to study the effects of parameters like anchor density, node density and communication range on the proposed algorithm with respect to average localization error and localization success ratio. In addition, a comparative study was conducted to realize the same localization task using the same network deployment. Experimental results prove that the proposed CS algorithm can not only increase convergence rate but also reduce average localization error compared with standard CS algorithm and Particle Swarm Optimization (PSO) algorithm. PMID:27589756

Collective network for computer structures

DOEpatents

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

2014-01-07

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to the needs of a processing algorithm.

Collective network for computer structures

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Coteus, Paul W [Yorktown Heights, NY; Chen, Dong [Croton On Hudson, NY; Gara, Alan [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Hoenicke, Dirk [Ossining, NY; Takken, Todd E [Brewster, NY; Steinmacher-Burow, Burkhard D [Wernau, DE; Vranas, Pavlos M [Bedford Hills, NY

2011-08-16

A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

A Novel Adjustment Method for Shearer Traction Speed through Integration of T-S Cloud Inference Network and Improved PSO

PubMed Central

Si, Lei; Wang, Zhongbin; Yang, Yinwei

2014-01-01

In order to efficiently and accurately adjust the shearer traction speed, a novel approach based on Takagi-Sugeno (T-S) cloud inference network (CIN) and improved particle swarm optimization (IPSO) is proposed. The T-S CIN is built through the combination of cloud model and T-S fuzzy neural network. Moreover, the IPSO algorithm employs parameter automation adjustment strategy and velocity resetting to significantly improve the performance of basic PSO algorithm in global search and fine-tuning of the solutions, and the flowchart of proposed approach is designed. Furthermore, some simulation examples are carried out and comparison results indicate that the proposed method is feasible, efficient, and is outperforming others. Finally, an industrial application example of coal mining face is demonstrated to specify the effect of proposed system. PMID:25506358

GPS IPW as a Meteorological Parameter and Climate Global Change Indicator

NASA Astrophysics Data System (ADS)

Kruczyk, M.; Liwosz, T.

2011-12-01

Paper focuses on comprehensive investigation of the GPS derived IPW (Integrated Precipitable Water, also IWV) as a geophysical tool. GPS meteorology is now widely acknowledged indirect method of atmosphere sensing. First we demonstrate GPS IPW quality. Most thorough inter-technique comparisons of directly measured IPW are attainable only for some observatories (note modest percentage of GPS stations equipped with meteorological devices). Nonetheless we have managed to compare IPW series derived from GPS tropospheric solutions (ZTD mostly from IGS and EPN solutions) and some independent techniques. IPW values from meteorological sources we used are: radiosoundings, sun photometer and input fields of numerical weather prediction model. We can treat operational NWP models as meteorological database within which we can calculate IWV for all GPS stations independently from network of direct measurements (COSMO-LM model maintained by Polish Institute of Meteorology and Water Management was tried). Sunphotometer (CIMEL-318, Central Geophysical Observatory IGF PAS, Belsk, Poland) data seems the most genuine source - so we decided for direct collocation of GPS measurements and sunphotometer placing permanent GPS receiver on the roof of Belsk Observatory. Next we analyse IPW as geophysical parameter: IPW demonstrates some physical effects evoked by station location (height and series correlation coefficient as a function of distance) and weather patterns like dominant wind directions (in case of neighbouring stations). Deficiency of surface humidity data to model IPW is presented for different climates. This inadequacy and poor humidity data representation in NWP model extremely encourages investigating information exchange potential between Numerical Model and GPS network. The second and most important aspect of this study concerns long series of IPW (daily averaged) which can serve as climatological information indicator (water vapour role in climate system is hard to exaggerate). Especially intriguing are relatively unique shape of such series in different climates. Long lasting changes in weather conditions: 'dry' and 'wet' years are also visible. The longer and more uniform our series are the better chance to estimate the magnitude of climatological IWV changes. Homogenous ZTD solution during long period is great concern in this approach (problems with GPS strategy and reference system changes). In case of continental network (EUREF Permanent Network) reliable data we get only after reprocessing. Simple sinusoidal model has been adjusted to the IPW series (LS method) for selected stations (mainly Europe but also other continents - IGS stations), every year separately. Not only amplitudes but also phases of annual signal differ from year to year. Longer IPW series (up to 14 years) searched for some climatological signal sometimes reveal weak steady trend. Large number of GPS permanent stations, relative easiness of IPW derivation (only and surface meteo data needed apart from GPS solution) and water vapour significance in water cycle and global climate make this GPS IPW promising element of global environmental change monitoring.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

Exploring information transmission in gene networks using stochastic simulation and machine learning

NASA Astrophysics Data System (ADS)

Park, Kyemyung; Prüstel, Thorsten; Lu, Yong; Narayanan, Manikandan; Martins, Andrew; Tsang, John

How gene regulatory networks operate robustly despite environmental fluctuations and biochemical noise is a fundamental question in biology. Mathematically the stochastic dynamics of a gene regulatory network can be modeled using chemical master equation (CME), but nonlinearity and other challenges render analytical solutions of CMEs difficult to attain. While approaches of approximation and stochastic simulation have been devised for simple models, obtaining a more global picture of a system's behaviors in high-dimensional parameter space without simplifying the system substantially remains a major challenge. Here we present a new framework for understanding and predicting the behaviors of gene regulatory networks in the context of information transmission among genes. Our approach uses stochastic simulation of the network followed by machine learning of the mapping between model parameters and network phenotypes such as information transmission behavior. We also devised ways to visualize high-dimensional phase spaces in intuitive and informative manners. We applied our approach to several gene regulatory circuit motifs, including both feedback and feedforward loops, to reveal underexplored aspects of their operational behaviors. This work is supported by the Intramural Program of NIAID/NIH.

Social medicine and international expert networks in Latin America, 1930-1945.

PubMed

Carter, Eric D

2018-01-03

This paper examines the international networks that influenced ideas and policy in social medicine in the 1930s and 1940s in Latin America, focusing on institutional networks organised by the League of Nations Health Organization, the International Labour Organization, and the Pan-American Sanitary Bureau. After examining the architecture of these networks, this paper traces their influence on social and health policy in two policy domains: social security and nutrition. Closer scrutiny of a series of international conferences and local media accounts of them reveals that international networks were not just 'conveyor belts' for policy ideas from the industrialised countries of the US and Europe into Latin America; rather, there was often contentious debate over the relevance and appropriateness of health and social policy models in the Latin American context. Recognition of difference between Latin America and the global economic core regions was a key impetus for seeking 'national solutions to national problems' in countries like Argentina and Chile, even as integration into these networks provided progressive doctors, scientists, and other intellectuals important international support for local political reforms.

[Cognitive advantages of the third age: a neural network model of brain aging].

PubMed

Karpenko, M P; Kachalova, L M; Budilova, E V; Terekhin, A T

2009-01-01

We consider a neural network model of age-related cognitive changes in aging brain based on Hopfield network with a sigmoid function of neuron activation. Age is included in the activation function as a parameter in the form of exponential rate denominator, which makes it possible to take into account the weakening of interneuronal links really observed in the aging brain. Analysis of properties of the Lyapunov function associated with the network shows that, with increasing parameter of age, its relief becomes smoother and the number of local minima (network attractors) decreases. As a result, the network gets less frequently stuck in the nearest local minima of the Lyapunov function and reaches a global minimum corresponding to the most effective solution of the cognitive task. It is reasonable to assume that similar changes really occur in the aging brain. Phenomenologically, these changes can be manifested as emergence in aged people of a cognitive quality such as wisdom i.e. ability to find optimal decisions in difficult controversial situations, to distract from secondary aspects and to see the problem as a whole.

On the impact of reducing global geophysical fluid model deformations in SLR data processing

NASA Astrophysics Data System (ADS)

Weigelt, Matthias; Thaller, Daniela

2016-04-01

Mass redistributions in the atmosphere, oceans and the continental hydrology cause elastic loading deformations of the Earth's crust and thus systematically influence Earth-bound observation systems such as VLBI, GNSS or SLR. Causing non-linear station variations, these loading deformations have a direct impact on the estimated station coordinates and an indirect impact on other parameters of global space-geodetic solutions, e.g. Earth orientation parameters, geocenter coordinates, satellite orbits or troposphere parameters. Generally, the impact can be mitigated by co-parameterisation or by reducing deformations derived from global geophysical fluid models. Here, we focus on the latter approach. A number of data sets modelling the (non-tidal) loading deformations are generated by various groups. They show regionally and locally significant differences and consequently the impact on the space-geodetic solutions heavily depends on the available network geometry. We present and discuss the differences between these models and choose SLR as the speace-geodetic technique of interest in order to discuss the impact of atmospheric, oceanic and hydrological loading on the parameters of space-geodetic solutions when correcting for the global geophysical fluid models at the observation level. Special emphasis is given to a consistent usage of models for geometric and gravimetric corrections during the data processing. We quantify the impact of the different deformation models on the station coordinates and discuss the improvement in the Earth orientation parameters and the geocenter motion. We also show that a significant reduction in the RMS of the station coordinates can be achieved depending on the model of choice.

An Optimization-Based Method for Feature Ranking in Nonlinear Regression Problems.

PubMed

Bravi, Luca; Piccialli, Veronica; Sciandrone, Marco

2017-04-01

In this paper, we consider the feature ranking problem, where, given a set of training instances, the task is to associate a score with the features in order to assess their relevance. Feature ranking is a very important tool for decision support systems, and may be used as an auxiliary step of feature selection to reduce the high dimensionality of real-world data. We focus on regression problems by assuming that the process underlying the generated data can be approximated by a continuous function (for instance, a feedforward neural network). We formally state the notion of relevance of a feature by introducing a minimum zero-norm inversion problem of a neural network, which is a nonsmooth, constrained optimization problem. We employ a concave approximation of the zero-norm function, and we define a smooth, global optimization problem to be solved in order to assess the relevance of the features. We present the new feature ranking method based on the solution of instances of the global optimization problem depending on the available training data. Computational experiments on both artificial and real data sets are performed, and point out that the proposed feature ranking method is a valid alternative to existing methods in terms of effectiveness. The obtained results also show that the method is costly in terms of CPU time, and this may be a limitation in the solution of large-dimensional problems.

Experimental study of thin film sensor networks for wind turbine blade damage detection

NASA Astrophysics Data System (ADS)

Downey, A.; Laflamme, S.; Ubertini, F.; Sauder, H.; Sarkar, P.

2017-02-01

Damage detection of wind turbine blades is difficult due to their complex geometry and large size, for which large deployment of sensing systems is typically not economical. A solution is to develop and deploy dedicated sensor networks fabricated from inexpensive materials and electronics. The authors have recently developed a novel skin-type strain gauge for measuring strain over very large surfaces. The skin, a type of large-area electronics, is constituted from a network of soft elastomeric capacitors. The sensing system is analogous to a biological skin, where local strain can be monitored over a global area. In this paper, we propose the utilization of a dense network of soft elastomeric capacitors to detect, localize, and quantify damage on wind turbine blades. We also leverage mature off-the-shelf technologies, in particular resistive strain gauges, to augment such dense sensor network with high accuracy data at key locations, therefore constituting a hybrid dense sensor network. The proposed hybrid dense sensor network is installed inside a wind turbine blade model, and tested in a wind tunnel to simulate an operational environment. Results demonstrate the ability of the hybrid dense sensor network to detect, localize, and quantify damage.

International trade network: fractal properties and globalization puzzle.

PubMed

Karpiarz, Mariusz; Fronczak, Piotr; Fronczak, Agata

2014-12-12

Globalization is one of the central concepts of our age. The common perception of the process is that, due to declining communication and transport costs, distance becomes less and less important. However, the distance coefficient in the gravity model of trade, which grows in time, indicates that the role of distance increases rather than decreases. This, in essence, captures the notion of the globalization puzzle. Here, we show that the fractality of the international trade system (ITS) provides a simple solution for the puzzle. We argue that the distance coefficient corresponds to the fractal dimension of ITS. We provide two independent methods, the box counting method and spatial choice model, which confirm this statement. Our results allow us to conclude that the previous approaches to solving the puzzle misinterpreted the meaning of the distance coefficient in the gravity model of trade.

International Trade Network: Fractal Properties and Globalization Puzzle

NASA Astrophysics Data System (ADS)

Karpiarz, Mariusz; Fronczak, Piotr; Fronczak, Agata

2014-12-01

Globalization is one of the central concepts of our age. The common perception of the process is that, due to declining communication and transport costs, distance becomes less and less important. However, the distance coefficient in the gravity model of trade, which grows in time, indicates that the role of distance increases rather than decreases. This, in essence, captures the notion of the globalization puzzle. Here, we show that the fractality of the international trade system (ITS) provides a simple solution for the puzzle. We argue that the distance coefficient corresponds to the fractal dimension of ITS. We provide two independent methods, the box counting method and spatial choice model, which confirm this statement. Our results allow us to conclude that the previous approaches to solving the puzzle misinterpreted the meaning of the distance coefficient in the gravity model of trade.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

PubMed

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

PubMed

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

PubMed Central

2018-01-01

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884

Cooperation, social networks, and the emergence of leadership in a prisoner's dilemma with adaptive local interactions

NASA Astrophysics Data System (ADS)

Zimmermann, Martín G.; Eguíluz, Víctor M.

2005-11-01

Cooperative behavior among a group of agents is studied assuming adaptive interactions. Each agent plays a Prisoner’s Dilemma game with its local neighbors, collects an aggregate payoff, and imitates the strategy of its best neighbor. Agents may punish or reward their neighbors by removing or sustaining the interactions, according to their satisfaction level and strategy played. An agent may dismiss an interaction, and the corresponding neighbor is replaced by another randomly chosen agent, introducing diversity and evolution to the network structure. We perform an extensive numerical and analytical study, extending results in M. G. Zimmermann, V. M. Eguíluz, and M. San Miguel, Phys. Rev. E 69, 065102(R) (2004). We show that the system typically reaches either a full-defective state or a highly cooperative steady state. The latter equilibrium solution is composed mostly by cooperative agents, with a minor population of defectors that exploit the cooperators. It is shown how the network adaptation dynamics favors the emergence of cooperators with the highest payoff. These “leaders” are shown to sustain the global cooperative steady state. Also we find that the average payoff of defectors is larger than the average payoff of cooperators. Whenever “leaders” are perturbed (e.g., by addition of noise), an unstable situation arises and global cascades with oscillations between the nearly full defection network and the fully cooperative outcome are observed.

Privacy Management and Networked PPD Systems - Challenges Solutions.

PubMed

Ruotsalainen, Pekka; Pharow, Peter; Petersen, Francoise

2015-01-01

Modern personal portable health devices (PPDs) become increasingly part of a larger, inhomogeneous information system. Information collected by sensors are stored and processed in global clouds. Services are often free of charge, but at the same time service providers' business model is based on the disclosure of users' intimate health information. Health data processed in PPD networks is not regulated by health care specific legislation. In PPD networks, there is no guarantee that stakeholders share same ethical principles with the user. Often service providers have own security and privacy policies and they rarely offer to the user possibilities to define own, or adapt existing privacy policies. This all raises huge ethical and privacy concerns. In this paper, the authors have analyzed privacy challenges in PPD networks from users' viewpoint using system modeling method and propose the principle "Personal Health Data under Personal Control" must generally be accepted at global level. Among possible implementation of this principle, the authors propose encryption, computer understandable privacy policies, and privacy labels or trust based privacy management methods. The latter can be realized using infrastructural trust calculation and monitoring service. A first step is to require the protection of personal health information and the principle proposed being internationally mandatory. This requires both regulatory and standardization activities, and the availability of open and certified software application which all service providers can implement. One of those applications should be the independent Trust verifier.

The GEOSS Clearinghouse based on the GeoNetwork opensource

NASA Astrophysics Data System (ADS)

Liu, K.; Yang, C.; Wu, H.; Huang, Q.

2010-12-01

The Global Earth Observation System of Systems (GEOSS) is established to support the study of the Earth system in a global community. It provides services for social management, quick response, academic research, and education. The purpose of GEOSS is to achieve comprehensive, coordinated and sustained observations of the Earth system, improve monitoring of the state of the Earth, increase understanding of Earth processes, and enhance prediction of the behavior of the Earth system. In 2009, GEO called for a competition for an official GEOSS clearinghouse to be selected as a source to consolidating catalogs for Earth observations. The Joint Center for Intelligent Spatial Computing at George Mason University worked with USGS to submit a solution based on the open-source platform - GeoNetwork. In the spring of 2010, the solution is selected as the product for GEOSS clearinghouse. The GEOSS Clearinghouse is a common search facility for the Intergovernmental Group on Ea rth Observation (GEO). By providing a list of harvesting functions in Business Logic, GEOSS clearinghouse can collect metadata from distributed catalogs including other GeoNetwork native nodes, webDAV/sitemap/WAF, catalog services for the web (CSW)2.0, GEOSS Component and Service Registry (http://geossregistries.info/), OGC Web Services (WCS, WFS, WMS and WPS), OAI Protocol for Metadata Harvesting 2.0, ArcSDE Server and Local File System. Metadata in GEOSS clearinghouse are managed in a database (MySQL, Postgresql, Oracle, or MckoiDB) and an index of the metadata is maintained through Lucene engine. Thus, EO data, services, and related resources can be discovered and accessed. It supports a variety of geospatial standards including CSW and SRU for search, FGDC and ISO metadata, and WMS related OGC standards for data access and visualization, as linked from the metadata.

State Support: A Prerequisite for Global Health Network Effectiveness Comment on "Four Challenges that Global Health Networks Face".

PubMed

Marten, Robert; Smith, Richard D

2017-07-24

Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks' success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks' effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research. © 2018 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Development and psychometric testing of the clinical networks engagement tool

PubMed Central

Hecker, Kent G.; Rabatach, Leora; Noseworthy, Tom W.; White, Deborah E.

2017-01-01

Background Clinical networks are being used widely to facilitate large system transformation in healthcare, by engagement of stakeholders throughout the health system. However, there are no available instruments that measure engagement in these networks. Methods The study purpose was to develop and assess the measurement properties of a multiprofessional tool to measure engagement in clinical network initiatives. Based on components of the International Association of Public Participation Spectrum and expert panel review, we developed 40 items for testing. The draft instrument was distributed to 1,668 network stakeholders across different governance levels (leaders, members, support, frontline stakeholders) in 9 strategic clinical networks in Alberta (January to July 2014). With data from 424 completed surveys (25.4% response rate), descriptive statistics, exploratory and confirmatory factor analysis, Pearson correlations, linear regression, multivariate analysis, and Cronbach alpha were conducted to assess reliability and validity of the scores. Results Sixteen items were retained in the instrument. Exploratory factor analysis indicated a four-factor solution and accounted for 85.7% of the total variance in engagement with clinical network initiatives: global engagement, inform (provided with information), involve (worked together to address concerns), and empower (given final decision-making authority). All subscales demonstrated acceptable reliability (Cronbach alpha 0.87 to 0.99). Both the confirmatory factor analysis and regression analysis confirmed that inform, involve, and empower were all significant predictors of global engagement, with involve as the strongest predictor. Leaders had higher mean scores than frontline stakeholders, while members and support staff did not differ in mean scores. Conclusions This study provided foundational evidence for the use of this tool for assessing engagement in clinical networks. Further work is necessary to evaluate engagement in broader network functions and activities; to assess barriers and facilitators of engagement; and, to elucidate how the maturity of networks and other factors influence engagement. PMID:28350834

International global network of fiducial stations: Scientific and implementation issues

NASA Astrophysics Data System (ADS)

1991-11-01

In this report, an ad hoc panel of the National Research Council's Committee on Geodesy, Board of Earth Sciences and Resources (1) evaluates the scientific importance of a global network of fiducial sites, monitored very precisely, using a combination of surface- and space-geodetic techniques; (2) examines strategies for implementing and operating such a network; and (3) assesses whether such a network would provide a suitable global infrastructure for geodetic and other geophysical systems of the next century. The panel concludes that a global network of fiducial sites would be a valuable tool for addressing global change issues and play a critical role in providing a reference frame for scientific Earth missions. The panel suggests that existing global networks be integrated and anticipates that such a network would grow from about 30 to the ultimate size of about 200 fiducial sites. It is noted that such a global network will provide a long-term infrastructure for geodetic and geophysical studies. The panel expects that these fiducial sites would evolve into terrestrial observatories or laboratories that would permit more comprehensive studies of the Earth than those now possible.

International global network of fiducial stations: Scientific and implementation issues

NASA Technical Reports Server (NTRS)

1991-01-01

In this report, an ad hoc panel of the National Research Council's Committee on Geodesy, Board of Earth Sciences and Resources (1) evaluates the scientific importance of a global network of fiducial sites, monitored very precisely, using a combination of surface- and space-geodetic techniques; (2) examines strategies for implementing and operating such a network; and (3) assesses whether such a network would provide a suitable global infrastructure for geodetic and other geophysical systems of the next century. The panel concludes that a global network of fiducial sites would be a valuable tool for addressing global change issues and play a critical role in providing a reference frame for scientific Earth missions. The panel suggests that existing global networks be integrated and anticipates that such a network would grow from about 30 to the ultimate size of about 200 fiducial sites. It is noted that such a global network will provide a long-term infrastructure for geodetic and geophysical studies. The panel expects that these fiducial sites would evolve into terrestrial observatories or laboratories that would permit more comprehensive studies of the Earth than those now possible.

The total laboratory solution: a new laboratory E-business model based on a vertical laboratory meta-network.

PubMed

Friedman, B A

2001-08-01

Major forces are now reshaping all businesses on a global basis, including the healthcare and clinical laboratory industries. One of the major forces at work is information technology (IT), which now provides the opportunity to create a new economic and business model for the clinical laboratory industry based on the creation of an integrated vertical meta-network, referred to here as the "total laboratory solution" (TLS). Participants at the most basic level of such a network would include a hospital-based laboratory, a reference laboratory, a laboratory information system/application service provider/laboratory portal vendor, an in vitro diagnostic manufacturer, and a pharmaceutical/biotechnology manufacturer. It is suggested that each of these participants would add value to the network primarily in its area of core competency. Subvariants of such a network have evolved over recent years, but a TLS comprising all or most of these participants does not exist at this time. Although the TLS, enabled by IT and closely akin to the various e-businesses that are now taking shape, offers many advantages from a theoretical perspective over the current laboratory business model, its success will depend largely on (a) market forces, (b) how the collaborative networks are organized and managed, and (c) whether the network can offer healthcare organizations higher quality testing services at lower cost. If the concept is successful, new demands will be placed on hospital-based laboratory professionals to shift the range of professional services that they offer toward clinical consulting, integration of laboratory information from multiple sources, and laboratory information management. These information management and integration tasks can only increase in complexity in the future as new genomic and proteomics testing modalities are developed and come on-line in clinical laboratories.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

PubMed

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

PubMed Central

Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-01-01

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. PMID:29462929

Assessing lateral flows and solute transport during floods in a conduit-flow-dominated karst system using the inverse problem for the advection-diffusion equation

NASA Astrophysics Data System (ADS)

Cholet, Cybèle; Charlier, Jean-Baptiste; Moussa, Roger; Steinmann, Marc; Denimal, Sophie

2017-07-01

The aim of this study is to present a framework that provides new ways to characterize the spatio-temporal variability of lateral exchanges for water flow and solute transport in a karst conduit network during flood events, treating both the diffusive wave equation and the advection-diffusion equation with the same mathematical approach, assuming uniform lateral flow and solute transport. A solution to the inverse problem for the advection-diffusion equations is then applied to data from two successive gauging stations to simulate flows and solute exchange dynamics after recharge. The study site is the karst conduit network of the Fourbanne aquifer in the French Jura Mountains, which includes two reaches characterizing the network from sinkhole to cave stream to the spring. The model is applied, after separation of the base from the flood components, on discharge and total dissolved solids (TDSs) in order to assess lateral flows and solute concentrations and compare them to help identify water origin. The results showed various lateral contributions in space - between the two reaches located in the unsaturated zone (R1), and in the zone that is both unsaturated and saturated (R2) - as well as in time, according to hydrological conditions. Globally, the two reaches show a distinct response to flood routing, with important lateral inflows on R1 and large outflows on R2. By combining these results with solute exchanges and the analysis of flood routing parameters distribution, we showed that lateral inflows on R1 are the addition of diffuse infiltration (observed whatever the hydrological conditions) and localized infiltration in the secondary conduit network (tributaries) in the unsaturated zone, except in extreme dry periods. On R2, despite inflows on the base component, lateral outflows are observed during floods. This pattern was attributed to the concept of reversal flows of conduit-matrix exchanges, inducing a complex water mixing effect in the saturated zone. From our results we build the functional scheme of the karst system. It demonstrates the impact of the saturated zone on matrix-conduit exchanges in this shallow phreatic aquifer and highlights the important role of the unsaturated zone on storage and transfer functions of the system.

The Promise of Global Networks. 1999 Annual Review.

ERIC Educational Resources Information Center

Institute for Information Studies, Queenstown, MD.

This collection of commissioned papers provides a variety of perspectives on the impact of global information networks. The following articles are included: "The Promise of Global Networks: An Introduction" (Jorge Reina Schement); "Architecture and Expectations: Networks of the World--Unite!" (Marjory S. Blumenthal); "The…

Building Sustainable Local Capacity for Global Health Research in West Africa.

PubMed

Sam-Agudu, Nadia A; Paintsil, Elijah; Aliyu, Muktar H; Kwara, Awewura; Ogunsola, Folasade; Afrane, Yaw A; Onoka, Chima; Awandare, Gordon A; Amponsah, Gladys; Cornelius, Llewellyn J; Mendy, Gabou; Sturke, Rachel; Ghansah, Anita; Siberry, George K; Ezeanolue, Echezona E

Global health research in resource-limited countries has been largely sponsored and led by foreign institutions. Thus, these countries' training capacity and productivity in global health research is limited. Local participation at all levels of global health knowledge generation promotes equitable access to evidence-based solutions. Additionally, leadership inclusive of competent local professionals promotes best outcomes for local contextualization and implementation of successful global health solutions. Among the sub-Saharan African regions, West Africa in particular lags in research infrastructure, productivity, and impact in global health research. In this paper, experts discuss strategies for scaling up West Africa's participation in global health evidence generation using examples from Ghana and Nigeria. We conducted an online and professional network search to identify grants awarded for global health research and research education in Ghana and Nigeria. Principal investigators, global health educators, and representatives of funding institutions were invited to add their knowledge and expertise with regard to strengthening research capacity in West Africa. While there has been some progress in obtaining foreign funding, foreign institutions still dominate local research. Local research funding opportunities in the 2 countries were found to be insufficient, disjointed, poorly sustained, and inadequately publicized, indicating weak infrastructure. As a result, research training programs produce graduates who ultimately fail to launch independent investigator careers because of lack of mentoring and poor infrastructural support. Research funding and training opportunities in Ghana and Nigeria remain inadequate. We recommend systems-level changes in mentoring, collaboration, and funding to drive the global health research agenda in these countries. Additionally, research training programs should be evaluated not only by numbers of individuals graduated but also by numbers of independent investigators and grants funded. Through equitable collaborations, infrastructure, and mentoring, West Africa can match the rest of Africa in impactful global health research. Copyright © 2016 Icahn School of Medicine at Mount Sinai. All rights reserved.

Differences Between S/X and VLBI2010 Operation

NASA Technical Reports Server (NTRS)

Hase, Hayo; Himwich, Ed; Neidhardt, Alexander

2010-01-01

The intended VLBI2010 operation has some significant differences to the current S/X operation. The presentation focuses on the problem of extending the operation of a global VLBI network to continuous operation within the frame of the same given amount of human resources. Remote control operation is a suitable solution to minimize operational expenses. The implementation of remote control operation requires more site specific information. A concept of a distributed-centralized remote control of the operation and its implications is presented.

Quantum information to the home

NASA Astrophysics Data System (ADS)

Choi, Iris; Young, Robert J.; Townsend, Paul D.

2011-06-01

Information encoded on individual quanta will play an important role in our future lives, much as classically encoded digital information does today. Combining quantum information carried by single photons with classical signals encoded on strong laser pulses in modern fibre-to-the-home (FTTH) networks is a significant challenge, the solution to which will facilitate the global distribution of quantum information to the home and with it a quantum internet [1]. In real-world networks, spontaneous Raman scattering in the optical fibre would induce crosstalk between the high-power classical channels and a single-photon quantum channel, such that the latter is unable to operate. Here, we show that the integration of quantum and classical information on an FTTH network is possible by performing quantum key distribution (QKD) on a network while simultaneously transferring realistic levels of classical data. Our novel scheme involves synchronously interleaving a channel of quantum data with the Raman scattered photons from a classical channel, exploiting the periodic minima in the instantaneous crosstalk and thereby enabling secure QKD to be performed.

Generation of political priority for global surgery: a qualitative policy analysis.

PubMed

Shawar, Yusra Ribhi; Shiffman, Jeremy; Spiegel, David A

2015-08-01

Despite the high burden of surgical conditions, the provision of surgical services has been a low global health priority. We examined factors that have shaped priority for global surgical care. We undertook semi-structured interviews by telephone with members of global surgical networks and ministries of health to explore the challenges and opportunities surgeons, anaesthesiologists, and other proponents face in increasing global priority for surgery. We did a literature review and collected information from reports from organisations involved in surgery. We used a policy framework consisting of four categories-actor power, ideas, political contexts, and characteristics of the issue itself-to analyse factors that have shaped global political priority for surgery. We did a thematic analysis on the collected information. Several factors hinder the acquisition of attention and resources for global surgery. With respect to actor power, the global surgery community is fragmented, does not have unifying leadership, and is missing guiding institutions. Regarding ideas, community members disagree on how to address and publicly position the problem. With respect to political contexts, the community has made insufficient efforts to capitalise on political opportunities such as the Millennium Development Goals. Regarding issue characteristics, data on the burden of surgical diseases are limited and public misperceptions surrounding the cost and complexity of surgery are widespread. However, the community has several strengths that portend well for the acquisition of political support. These include the existence of networks deeply committed to the cause, the potential to link with global health priorities, and emerging research on the cost-effectiveness of some procedures. To improve global priority for surgery, proponents will need to create an effective governance structure that facilitates achievement of collective goals, generate consensus on solutions, and find an effective public positioning of the issue that attracts political support. None. Copyright © 2015 Shawar et al. Open Access article distributed under the terms of CC BY-NC-ND. Published by Elsevier Ltd.. All rights reserved.

Evaluation of the Horizontal and Vertical Accuracy of GNSS Survey Observations from a Real-Time Network

NASA Astrophysics Data System (ADS)

Allahyari, M.; Olsen, M. J.; Gillins, D. T.; Dennis, M. L.

2016-12-01

Many current surveying standards in the United States require several long-duration, static Global Navigation Satellite System (GNSS) observations to derive high-accuracy geodetic coordinates. However, over the past decade, many entities have established real-time GNSS networks (RTNs), which could reduce the field time for establishing geodetic control from hours to minutes. To evaluate the accuracy of RTN GNSS observations, data collected from two National Geodetic Survey (NGS) surveys in South Carolina and Oregon were studied. The objectives were to: 1) determine the accuracy of a real-time observation as a function of duration; 2) examine the influence of including GLONASS (Russia's version of GPS); 3) compare results using a single base to the full RTN network solution; and 4) assess the effect of baseline length on accuracy. In South Carolina, 360 observations ranging from 5 to 600 seconds were collected on 20 passive marks using RTN and single-base solutions, both with GPS+GLONASS and GPS-only. In Oregon, 18 passive marks were observed from 5 to 900 seconds using GPS-only with the RTN, and with GPS+GLONASS and GPS-only from a single-base. To develop "truth" coordinates, at least 30 hours of static GPS data were also collected on all marks. Each static survey session was post-processed in OPUS-Projects, and the resulting vectors were used to build survey networks that were least-squares adjusted using the NGS software ADJUST. The resulting coordinates provided the basis for evaluating the accuracy of the real-time observations. Results from this study indicate great potential in the use of RTNs for accurate derivation of geodetic coordinates. Both case studies showed an optimal observation duration of 180 seconds. RTN data tended to be more accurate and consistent than single-base data, and GLONASS slightly improved accuracy. A key benefit of GLONASS was the ability to obtain more fixed solutions at longer baseline lengths than single-base solutions.

Solutions Network Formulation Report. Aerosol Polarimetry Sensor Measurements of Diffuse-to-Global Irradiance Ratio for Improved Forecasting of Plant Productivity and Health

NASA Technical Reports Server (NTRS)

Knowlton, Kelly; Andrews, Jane C.; Ryan, Robert E.

2007-01-01

Studies have shown that vegetation is directly sensitive to changes in the diffuse-to-global irradiance ratio and that increased percentage of diffuse irradiation can accelerate photosynthesis. Therefore, measurements of diffuse versus global irradiance could be useful for monitoring crop productivity and overall vegetative health as they relate to the total amount of particulates in the air that result from natural disasters or anthropogenic (manmade) causes. While the components of solar irradiance are measured by satellite and surface sensors and calculated with atmospheric models, disagreement exists between the results, creating a need for more accurate and comprehensive retrievals of atmospheric aerosol parameters. Two satellite sensors--APS and VIIRS--show promise for retrieving aerosol properties at an unprecedented level of accuracy. APS is expected to be launched in December 2008. The planned launch date for VIIRS onboard NPP is September 2009. Identified partners include the USDA s ARS, North Carolina State University, Purdue Climate Change Research Center, and the Cooperative Institute for Research in the Atmosphere at Colorado State University. Although at present no formal DSSs (decision support systems) require accurate values of diffuse-to-global irradiance, this parameter is sufficiently important that models are being developed that will incorporate these measurements. This candidate solution is aligned with the Agricultural Efficiency and Air Quality National Applications.

Community detection in networks with unequal groups.

PubMed

Zhang, Pan; Moore, Cristopher; Newman, M E J

2016-01-01

Recently, a phase transition has been discovered in the network community detection problem below which no algorithm can tell which nodes belong to which communities with success any better than a random guess. This result has, however, so far been limited to the case where the communities have the same size or the same average degree. Here we consider the case where the sizes or average degrees differ. This asymmetry allows us to assign nodes to communities with better-than-random success by examining their local neighborhoods. Using the cavity method, we show that this removes the detectability transition completely for networks with four groups or fewer, while for more than four groups the transition persists up to a critical amount of asymmetry but not beyond. The critical point in the latter case coincides with the point at which local information percolates, causing a global transition from a less-accurate solution to a more-accurate one.

A Cost-Effective Vehicle Localization Solution Using an Interacting Multiple Model−Unscented Kalman Filters (IMM-UKF) Algorithm and Grey Neural Network

PubMed Central

Xu, Qimin; Li, Xu; Chan, Ching-Yao

2017-01-01

In this paper, we propose a cost-effective localization solution for land vehicles, which can simultaneously adapt to the uncertain noise of inertial sensors and bridge Global Positioning System (GPS) outages. First, three Unscented Kalman filters (UKFs) with different noise covariances are introduced into the framework of Interacting Multiple Model (IMM) algorithm to form the proposed IMM-based UKF, termed as IMM-UKF. The IMM algorithm can provide a soft switching among the three UKFs and therefore adapt to different noise characteristics. Further, two IMM-UKFs are executed in parallel when GPS is available. One fuses the information of low-cost GPS, in-vehicle sensors, and micro electromechanical system (MEMS)-based reduced inertial sensor systems (RISS), while the other fuses only in-vehicle sensors and MEMS-RISS. The differences between the state vectors of the two IMM-UKFs are considered as training data of a Grey Neural Network (GNN) module, which is known for its high prediction accuracy with a limited amount of samples. The GNN module can predict and compensate position errors when GPS signals are blocked. To verify the feasibility and effectiveness of the proposed solution, road-test experiments with various driving scenarios were performed. The experimental results indicate that the proposed solution outperforms all the compared methods. PMID:28629165

An Actor-Network Theory Analysis of Policy Innovation for Smoke-Free Places: Understanding Change in Complex Systems

PubMed Central

Borland, Ron; Coghill, Ken

2010-01-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems. PMID:20466949

WS-BP: An efficient wolf search based back-propagation algorithm

NASA Astrophysics Data System (ADS)

Nawi, Nazri Mohd; Rehman, M. Z.; Khan, Abdullah

2015-05-01

Wolf Search (WS) is a heuristic based optimization algorithm. Inspired by the preying and survival capabilities of the wolves, this algorithm is highly capable to search large spaces in the candidate solutions. This paper investigates the use of WS algorithm in combination with back-propagation neural network (BPNN) algorithm to overcome the local minima problem and to improve convergence in gradient descent. The performance of the proposed Wolf Search based Back-Propagation (WS-BP) algorithm is compared with Artificial Bee Colony Back-Propagation (ABC-BP), Bat Based Back-Propagation (Bat-BP), and conventional BPNN algorithms. Specifically, OR and XOR datasets are used for training the network. The simulation results show that the WS-BP algorithm effectively avoids the local minima and converge to global minima.

An actor-network theory analysis of policy innovation for smoke-free places: understanding change in complex systems.

PubMed

Young, David; Borland, Ron; Coghill, Ken

2010-07-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems.

Epidemic spreading on random surfer networks with optimal interaction radius

NASA Astrophysics Data System (ADS)

Feng, Yun; Ding, Li; Hu, Ping

2018-03-01

In this paper, the optimal control problem of epidemic spreading on random surfer heterogeneous networks is considered. An epidemic spreading model is established according to the classification of individual's initial interaction radii. Then, a control strategy is proposed based on adjusting individual's interaction radii. The global stability of the disease free and endemic equilibrium of the model is investigated. We prove that an optimal solution exists for the optimal control problem and the explicit form of which is presented. Numerical simulations are conducted to verify the correctness of the theoretical results. It is proved that the optimal control strategy is effective to minimize the density of infected individuals and the cost associated with the adjustment of interaction radii.

Advanced time and wavelength division multiplexing for metropolitan area optical data communication networks

NASA Astrophysics Data System (ADS)

Watford, M.; DeCusatis, C.

2005-09-01

With the advent of new regulations governing the protection and recovery of sensitive business data, including the Sarbanes-Oxley Act, there has been a renewed interest in business continuity and disaster recovery applications for metropolitan area networks. Specifically, there has been a need for more efficient bandwidth utilization and lower cost per channel to facilitate mirroring of multi-terabit data bases. These applications have further blurred the boundary between metropolitan and wide area networks, with synchronous disaster recovery applications running up to 100 km and asynchronous solutions extending to 300 km or more. In this paper, we discuss recent enhancements in the Nortel Optical Metro 5200 Dense Wavelength Division Multiplexing (DWDM) platform, including features recently qualified for data communication applications such as Metro Mirror, Global Mirror, and Geographically Distributed Parallel Sysplex (GDPS). Using a 10 Gigabit/second (Gbit/s) backbone, this solution transports significantly more Fibre Channel protocol traffic with up to five times greater hardware density in the same physical package. This is also among the first platforms to utilize forward error correction (FEC) on the aggregate signals to improve bit error rate (BER) performance beyond industry standards. When combined with encapsulation into wide area network protocols, the use of FEC can compensate for impairments in BER across a service provider infrastructure without impacting application level performance. Design and implementation of these features will be discussed, including results from experimental test beds which validate these solutions for a number of applications. Future extensions of this environment will also be considered, including ways to provide configurable bandwidth on demand, mitigate Fibre Channel buffer credit management issues, and support for other GDPS protocols.

Links between global meat trade and organic river pollution

NASA Astrophysics Data System (ADS)

Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick

2017-04-01

Rising demand of meat boosts livestock farming intensification. Due to international meat trade, the environmental costs of production are becoming increasingly separated from where the meat is consumed. However, little is known about the impact of trade on the environment for both importers and exporters. Combining multi-scale (national, regional and gridded) data, we present a new method to quantify the impacts of international meat trade on global river organic pollution. We computed spatially distributed organic pollution in global river networks with and without meat trade, where the without-trade scenario assumes that meat imports are replaced by local production. Our analysis indicates high potential savings of livestock population and pollutants production at the global scale due to the international meat trade. The spatially detailed analysis shows that current trade contributes to organic pollution reductions in meat importing regions, especially in rich nations. The deterioration of river water quality, especially in developing regions, points to an urgent need for affordable infrastructure and technology development and wastewater solutions.

Influence of network topology on cooperative problem-solving systems.

PubMed

Fontanari, José F; Rodrigues, Francisco A

2016-09-01

The idea of a collective intelligence behind the complex natural structures built by organisms suggests that the organization of social networks is selected so as to optimize problem-solving competence at the group level. Here we study the influence of the social network topology on the performance of a group of agents whose task is to locate the global maxima of NK fitness landscapes. Agents cooperate by broadcasting messages informing on their fitness and use this information to imitate the fittest agent in their influence networks. In the case those messages convey accurate information on the proximity of the solution (i.e., for smooth fitness landscapes), we find that high connectivity as well as centralization boosts the group performance. For rugged landscapes, however, these characteristics are beneficial for small groups only. For large groups, it is advantageous to slow down the information transmission through the network to avoid local maximum traps. Long-range links and modularity have marginal effects on the performance of the group, except for a very narrow region of the model parameters.

Raspberry Shake- A World-Wide Citizen Seismograph Network

NASA Astrophysics Data System (ADS)

Christensen, B. C.; Blanco Chia, J. F.

2017-12-01

Raspberry Shake was conceived as an inexpensive plug-and-play solution to satisfy the need for universal, quick and accurate earthquake detections. First launched on Kickstarter's crowdfunding platform in July of 2016, the Raspberry Shake project was funded within hours of the launch date and, by the end of the campaign, reached more than 1000% of its initial funding goal. This demonstrated for the first time that there exists a strong interest among Makers, Hobbyists and Do It Yourselfers for personal seismographs. From here, a citizen scientist network was created and it has steadily been growing. The Raspberry Shake network is currently being used in conjunction with publicly available broadband data from the GSN and other state-run seismic networks available through the IRIS, Geoscope and GEOFON data centers to detect and locate earthquakes large and small around the globe. Raspberry Shake looks well positioned to improve local monitoring of earthquakes on a global scale, deepen community's understanding of earthquakes, and serve as a formidable teaching tool. We present the main results of the project, the current state of the network, and the new Raspberry Shake models that are being built.

Inferring global network properties from egocentric data with applications to epidemics.

PubMed

Britton, Tom; Trapman, Pieter

2015-03-01

Social networks are often only partly observed, and it is sometimes desirable to infer global properties of the network from 'egocentric' data. In the current paper, we study different types of egocentric data, and show which global network properties are consistent with data. Two global network properties are considered: the size of the largest connected component (the giant) and the size of an epidemic outbreak taking place on the network. The main conclusion is that, in most cases, egocentric data allow for a large range of possible sizes of the giant and the outbreak, implying that egocentric data carry very little information about these global properties. The asymptotic size of the giant and the outbreak is also characterized, assuming the network is selected uniformly among networks with prescribed egocentric data. © The Authors 2013. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Military Cyberspace: From Evolution to Revolution

DTIC Science & Technology

2012-02-08

support the GCCs and enable USCYBERCOM to accomplish its mission? 15. SUBJECT TERMS Network Operations, Global Information Grid ( GIG ), Network...DATE: 08 February 2012 WORD COUNT: 5,405 PAGES: 30 KEY TERMS: Network Operations, Global Information Grid ( GIG ), Network Architecture...defense of the DOD global information grid ( GIG ). The DOD must pursue an enterprise approach to network management in the cyberspace domain to

Networking among young global health researchers through an intensive training approach: a mixed methods exploratory study.

PubMed

Lenters, Lindsey M; Cole, Donald C; Godoy-Ruiz, Paula

2014-01-25

Networks are increasingly regarded as essential in health research aimed at influencing practice and policies. Less research has focused on the role networking can play in researchers' careers and its broader impacts on capacity strengthening in health research. We used the Canadian Coalition for Global Health Research (CCGHR) annual Summer Institute for New Global Health Researchers (SIs) as an opportunity to explore networking among new global health researchers. A mixed-methods exploratory study was conducted among SI alumni and facilitators who had participated in at least one SI between 2004 and 2010. Alumni and facilitators completed an online short questionnaire, and a subset participated in an in-depth interview. Thematic analysis of the qualitative data was triangulated with quantitative results and CCGHR reports on SIs. Synthesis occurred through the development of a process model relevant to networking through the SIs. Through networking at the SIs, participants experienced decreased isolation and strengthened working relationships. Participants accessed new knowledge, opportunities, and resources through networking during the SI. Post-SI, participants reported ongoing contact and collaboration, although most participants desired more opportunities for interaction. They made suggestions for structural supports to networking among new global health researchers. Networking at the SI contributed positively to opportunities for individuals, and contributed to the formation of a network of global health researchers. Intentional inclusion of networking in health research capacity strengthening initiatives, with supportive resources and infrastructure could create dynamic, sustainable networks accessible to global health researchers around the world.

Assessment of local GNSS baselines at co-location sites

NASA Astrophysics Data System (ADS)

Herrera Pinzón, Iván; Rothacher, Markus

2018-01-01

As one of the major contributors to the realisation of the International Terrestrial Reference System (ITRS), the Global Navigation Satellite Systems (GNSS) are prone to suffer from irregularities and discontinuities in time series. While often associated with hardware/software changes and the influence of the local environment, these discrepancies constitute a major threat for ITRS realisations. Co-located GNSS at fundamental sites, with two or more available instruments, provide the opportunity to mitigate their influence while improving the accuracy of estimated positions by examining data breaks, local biases, deformations, time-dependent variations and the comparison of GNSS baselines with existing local tie measurements. With the use of co-located GNSS data from a subset sites of the International GNSS Service network, this paper discusses a global multi-year analysis with the aim of delivering homogeneous time series of coordinates to analyse system-specific error sources in the local baselines. Results based on the comparison of different GNSS-based solutions with the local survey ties show discrepancies of up to 10 mm despite GNSS coordinate repeatabilities at the sub-mm level. The discrepancies are especially large for the solutions using the ionosphere-free linear combination and estimating tropospheric zenith delays, thus corresponding to the processing strategy used for global solutions. Snow on the antennas causes further problems and seasonal variations of the station coordinates. These demonstrate the need for a permanent high-quality monitoring of the effects present in the short GNSS baselines at fundamental sites.

A Miniaturized Laser Heterodyne Radiometer for a Global Ground-Based Column Carbon Monitoring Network

NASA Technical Reports Server (NTRS)

Wilson, Emily L.; Melroy, Hilary R.; Miller, J. Houston; McLinden, Matthew L.; Ott, Lesley E.; Holben, Brent

2012-01-01

We present progress in the development of a passive, miniaturized Laser Heterodyne Radiometer (mini-LHR) that will measure key greenhouse gases (C02, CH4, CO) in the atmospheric column as well as their respective altitude profiles, and O2 for a measure of atmospheric pressure. Laser heterodyne radiometry is a spectroscopic method that borrows from radio receiver technology. In this technique, a weak incoming signal containing information of interest is mixed with a stronger signal (local oscillator) at a nearby frequency. In this case, the weak signal is sunlight that has undergone absorption by a trace gas of interest and the local oscillator is a distributive feedback (DFB) laser that is tuned to a wavelength near the absorption feature of the trace gas. Mixing the sunlight with the laser light, in a fast photoreceiver, results in a beat signal in the RF. The amplitude of the beat signal tracks the concentration of the trace gas in the atmospheric column. The mini-LHR operates in tandem with AERONET, a global network of more than 450 aerosol sensing instruments. This partnership simplifies the instrument design and provides an established global network into which the mini-LHR can rapidly expand. This network offers coverage in key arctic regions (not covered by OCO-2) where accelerated warming due to the release of CO2 and CH4 from thawing tundra and permafrost is a concern as well as an uninterrupted data record that will both bridge gaps in data sets and offer validation for key flight missions such as OCO-2, OCO-3, and ASCENDS. Currently, the only ground global network that routinely measures multiple greenhouse gases in the atmospheric column is TCCON (Total Column Carbon Observing Network) with 18 operational sites worldwide and two in the US. Cost and size of TCCON installations will limit the potential for expansion, We offer a low-cost $30Klunit) solution to supplement these measurements with the added benefit of an established aerosol optical depth measurement. Aerosols induce a radiative effect that is an important modulator of regional carbon cycles. Changes in the diffuse radiative flux fraction (DRF) due to aerosol loading have the potential to alter the terrestrial carbon exchange.

GRACE Solutions for the Gravity Field over Central Europe Compared to the Surface Field as Recorded by the GGP Network.

NASA Astrophysics Data System (ADS)

Crossley, D. J.; de Linage, C.; Hinderer, J.; Boy, J.

2007-12-01

As the number of different solutions from the GRACE satellite gravity project evolves, we can make more meaningful comparisons between the satellite-derived field and the surface field as recorded by superconducting gravimeters. On the GRACE side, we use CSR Level 2 products RL01 and the recent RL04 solutions, GFZ RL04 solutions, and the CNES/GRGS 10-day solutions, all for the time periods these are available. On the GGP side, we take advantage of the 10 years of SG data since July 1997 from 6-8 ground stations in Europe, allowing for the change in the network configuration as stations begin and end recording. Only data since 2002 can be compared directly to GRACE. Our primary measure of variability is the first principal component of the EOF analysis of all the fields. Unsurprisingly, the seasonal components for all the comparisons are similar in phase, but different in amplitude, to the predictions from a global hydrology model (GLDAS), provided allowance is made for the location of the SG stations above or below the soil moisture horizon that controls the gravity signature. We use detailed modeling at the Strasbourg station, as well as published results for Moxa and Membach, to confirm the gravity effect of hydrology. Good agreement is found between the GGP and the CNES/GRGS 10-day solutions, indicating the higher temporal resolution of this satellite solution is valid for our limited geographical area. We also synthesize the gravity field over the sub-group of GGP stations in N.E. Asia to see how the GRACE variability compares to that for the European array and to assess future ground validation using new GGP stations in that part of the world.

Ocean Data Interoperability Platform (ODIP): developing a common framework for marine data management on a global scale

NASA Astrophysics Data System (ADS)

Glaves, Helen; Schaap, Dick

2016-04-01

The increasingly ocean basin level approach to marine research has led to a corresponding rise in the demand for large quantities of high quality interoperable data. This requirement for easily discoverable and readily available marine data is currently being addressed by initiatives such as SeaDataNet in Europe, Rolling Deck to Repository (R2R) in the USA and the Australian Ocean Data Network (AODN) with each having implemented an e-infrastructure to facilitate the discovery and re-use of standardised multidisciplinary marine datasets available from a network of distributed repositories, data centres etc. within their own region. However, these regional data systems have been developed in response to the specific requirements of their users and in line with the priorities of the funding agency. They have also been created independently of the marine data infrastructures in other regions often using different standards, data formats, technologies etc. that make integration of marine data from these regional systems for the purposes of basin level research difficult. Marine research at the ocean basin level requires a common global framework for marine data management which is based on existing regional marine data systems but provides an integrated solution for delivering interoperable marine data to the user. The Ocean Data Interoperability Platform (ODIP/ODIP II) project brings together those responsible for the management of the selected marine data systems and other relevant technical experts with the objective of developing interoperability across the regional e-infrastructures. The commonalities and incompatibilities between the individual data infrastructures are identified and then used as the foundation for the specification of prototype interoperability solutions which demonstrate the feasibility of sharing marine data across the regional systems and also with relevant larger global data services such as GEO, COPERNICUS, IODE, POGO etc. The potential impact for the individual regional data infrastructures of implementing these prototype interoperability solutions is also being evaluated to determine both the technical and financial implications of their integration within existing systems. These impact assessments form part of the strategy to encourage wider adoption of the ODIP solutions and approach beyond the current scope of the project which is focussed on regional marine data systems in Europe, Australia, the USA and, more recently, Canada.

Mapping the African thunderstorm center in absolute units using Schumann resonance spectral decomposition method

NASA Astrophysics Data System (ADS)

Dyrda, Michal; Kulak, Andrzej; Mlynarczyk, Janusz

2015-04-01

Monitoring of the global lightning activity provides a very useful tool to study the global warming phenomenon and the other longer-scale climate changes induced by humans. The lightning activity is measured using various observational methods form space (optical satellite observations) as well as from the ground mostly by VLF /LF lightning detection networks, i.e. World Wide Lightning Location Network (WWLLN) or lightning detection network (LINET) in Europe. However, the global lightning activity measurements are possible only in the ELF range. Here we examine the African thunderstorm activity center, which is the most violent and active one. In a spherical damped resonator, such as the Earth-ionosphere cavity, the electromagnetic field is described by the solution of an inhomogeneous wave equation. For such equation the general solution can be expressed by the superposition of the solutions of the homogeneous equation, describing the resonance field, and the component, which is quite strong close to the source and weakens with source-observer separation. Thus, the superposition of the standing wave field with the field of traveling waves, which supply the energy from the lighting discharges to the global resonator, is a main reason for an asymmetric shape of the observational Schumann resonance (SR) power spectra, which highly deviate from the Lorentz curves. It is possible to separate this component from the signal using the spectrum decomposition method proposed by Kułak et al. [2006]. In our approach, we apply the inverse problem solution for determining the distance of the dominant lightning source. The distances to the thunderstorm centers are calculated using the analytical models for the electromagnetic waves propagation in the Earth-ionosphere cavity. Such forms of analytic solutions of the resonant field in the spherical cavity is the zonal harmonic series representation, described by Mushtak and Williams [2002] and we calculated the sets of such curves for different source-observer separations, starting at 1 Mm up to 20 Mm with a step of 0.1 Mm. We selected two observational data sets, collected during different seasons of the year, from our Hylaty station, located in Poland. The data were binned in 10-minute files for which the SR power spectra were derived. In the next step a decomposition curve describing 7 asymmetric SR modes was fitted to the observational data. To compare the resulted decomposed power spectra with analytic model we use chi-squared test and hence we obtained the distances to the dominant thunderstorm center, located in Africa. We computed the monthly lighting activity maps and possible locations on the African continent with the spatial resolution of 1 degree and temporal resolution of 10 minute. Moreover we calculated the thunderstorm intensities in physical units, which are of the order of 2 × 1011 [C2 m2 s-1]. We also notice the seasonal variations of the African thunderstorm centers distributions and as well as intensities. Finally, we compared our results with satellite data recorded by the Lighting Imaging Sensor (LIS) and we obtained very high correlation. Acknowledgements. This work has been supported by the National Science Centre grant 2012/04/M/ST10/00565. The numerical computations were done using the PL-Grid infrastructure.

Impact of the topology of global macroeconomic network on the spreading of economic crises.

PubMed

Lee, Kyu-Min; Yang, Jae-Suk; Kim, Gunn; Lee, Jaesung; Goh, Kwang-Il; Kim, In-mook

2011-03-31

Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more "globalized" random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises.

Inmarsat and personal mobile satellite services

NASA Astrophysics Data System (ADS)

McDougal, Patrick; Barendse, Victor

Personal communications - mobile satellite services (PC-MSS) hold much promise as a profitable business opportunity for a number of interested operators and manufacturers. What will be their impact on the overall mobile communications landscape, and what role will they play in the drive towards the universal personal communicator? It is the thesis of this paper that PC-MSS can provide one of the critical enabling technologies to allow a more rapid, global assimilation of personal mobile communications. Terrestrial mobile communications are local by definition, both in terms of service reach and regulatory oversight. It is estimated that cellular, and other forms of terrestrial mobile communications, will cover over 50% of the world's population, but only 15% of the land mass area by the year 2000. PC-MSS will allow 'cellular extension' to interested users in the uncovered parts of the world. The market opportunity is established and technical solutions are available. However 'user cooperation' will be required and cross mapping of market needs to the technology solutions is the key to financially viable solutions. The potential political and regulatory hurdles are daunting. Inmarsat, as the existing global MSS partnership, is already introducing PC-MSS products and services in the 1990s. The widespread use of briefcase satphones (Inm-M), laptop-sized data terminals (Inm-C), and pocket satpagers (Inm-paging) will break new ground in reshaping the international regulatory context of mobile communications, and in initiating the optimal public switched network integration necessary for global interconnect. It is suggested that this evolutionary approach, by means of international consensus-building within a global partnership of operators, is an effective and proven method to ensure both a sufficient financial return for investors, and fair and equitable access of these services for all countries and users.

General, crystallized and fluid intelligence are not associated with functional global network efficiency: A replication study with the human connectome project 1200 data set.

PubMed

Kruschwitz, J D; Waller, L; Daedelow, L S; Walter, H; Veer, I M

2018-05-01

One hallmark example of a link between global topological network properties of complex functional brain connectivity and cognitive performance is the finding that general intelligence may depend on the efficiency of the brain's intrinsic functional network architecture. However, although this association has been featured prominently over the course of the last decade, the empirical basis for this broad association of general intelligence and global functional network efficiency is quite limited. In the current study, we set out to replicate the previously reported association between general intelligence and global functional network efficiency using the large sample size and high quality data of the Human Connectome Project, and extended the original study by testing for separate association of crystallized and fluid intelligence with global efficiency, characteristic path length, and global clustering coefficient. We were unable to provide evidence for the proposed association between general intelligence and functional brain network efficiency, as was demonstrated by van den Heuvel et al. (2009), or for any other association with the global network measures employed. More specifically, across multiple network definition schemes, ranging from voxel-level networks to networks of only 100 nodes, no robust associations and only very weak non-significant effects with a maximal R 2 of 0.01 could be observed. Notably, the strongest (non-significant) effects were observed in voxel-level networks. We discuss the possibility that the low power of previous studies and publication bias may have led to false positive results fostering the widely accepted notion of general intelligence being associated to functional global network efficiency. Copyright © 2018 Elsevier Inc. All rights reserved.

Volcano monitoring using the Global Positioning System: Filtering strategies

USGS Publications Warehouse

Larson, K.M.; Cervelli, Peter; Lisowski, M.; Miklius, Asta; Segall, P.; Owen, S.

2001-01-01

Permanent Global Positioning System (GPS) networks are routinely used for producing improved orbits and monitoring secular tectonic deformation. For these applications, data are transferred to an analysis center each day and routinely processed in 24-hour segments. To use GPS for monitoring volcanic events, which may last only a few hours, real-time or near real-time data processing and subdaily position estimates are valuable. Strategies have been researched for obtaining station coordinates every 15 min using a Kalman filter; these strategies have been tested on data collected by a GPS network on Kilauea Volcano. Data from this network are tracked continuously, recorded every 30 s, and telemetered hourly to the Hawaiian Volcano Observatory. A white noise model is heavily impacted by data outages and poor satellite geometry, but a properly constrained random walk model fits the data well. Using a borehole tiltmeter at Kilauea's summit as ground-truth, solutions using different random walk constraints were compared. This study indicates that signals on the order of 5 mm/h are resolvable using a random walk standard deviation of 0.45 cm/???h. Values lower than this suppress small signals, and values greater than this have significantly higher noise at periods of 1-6 hours. Copyright 2001 by the American Geophysical Union.

Personalized Telehealth in the Future: A Global Research Agenda

PubMed Central

2016-01-01

As telehealth plays an even greater role in global health care delivery, it will be increasingly important to develop a strong evidence base of successful, innovative telehealth solutions that can lead to scalable and sustainable telehealth programs. This paper has two aims: (1) to describe the challenges of promoting telehealth implementation to advance adoption and (2) to present a global research agenda for personalized telehealth within chronic disease management. Using evidence from the United States and the European Union, this paper provides a global overview of the current state of telehealth services and benefits, presents fundamental principles that must be addressed to advance the status quo, and provides a framework for current and future research initiatives within telehealth for personalized care, treatment, and prevention. A broad, multinational research agenda can provide a uniform framework for identifying and rapidly replicating best practices, while concurrently fostering global collaboration in the development and rigorous testing of new and emerging telehealth technologies. In this paper, the members of the Transatlantic Telehealth Research Network offer a 12-point research agenda for future telehealth applications within chronic disease management. PMID:26932229

Personalized Telehealth in the Future: A Global Research Agenda.

PubMed

Dinesen, Birthe; Nonnecke, Brandie; Lindeman, David; Toft, Egon; Kidholm, Kristian; Jethwani, Kamal; Young, Heather M; Spindler, Helle; Oestergaard, Claus Ugilt; Southard, Jeffrey A; Gutierrez, Mario; Anderson, Nick; Albert, Nancy M; Han, Jay J; Nesbitt, Thomas

2016-03-01

As telehealth plays an even greater role in global health care delivery, it will be increasingly important to develop a strong evidence base of successful, innovative telehealth solutions that can lead to scalable and sustainable telehealth programs. This paper has two aims: (1) to describe the challenges of promoting telehealth implementation to advance adoption and (2) to present a global research agenda for personalized telehealth within chronic disease management. Using evidence from the United States and the European Union, this paper provides a global overview of the current state of telehealth services and benefits, presents fundamental principles that must be addressed to advance the status quo, and provides a framework for current and future research initiatives within telehealth for personalized care, treatment, and prevention. A broad, multinational research agenda can provide a uniform framework for identifying and rapidly replicating best practices, while concurrently fostering global collaboration in the development and rigorous testing of new and emerging telehealth technologies. In this paper, the members of the Transatlantic Telehealth Research Network offer a 12-point research agenda for future telehealth applications within chronic disease management.

Time evolution of an SLR reference frame

NASA Astrophysics Data System (ADS)

Angermann, D.; Gerstl, M.; Kelm, R.; Müller, H.; Seemüller, W.; Vei, M.

2002-07-01

On the basis of LAGEOS-1 and LAGEOS-2 data we computed a 10-years (1990-2000) solution for SLR station positions and velocities. The paper describes the data processing with the DGFI software package DOGS. We present results for station coordinates and their time variation for 41 stations of the global SLR network, and discuss the stability and time evolution of the SLR reference frame established in the same way. We applied different methods to assess the quality and consistency of the SLR results. The results presented in this paper include: (1) a time series of weekly estimated station coordinates; (2) a comparison of a 10-year LAGEOS-1 and LAGEOS-2 solution; (3) a comparison of 2.5-year solutions with the combined 10-year solution to assess the internal stability and the time evolution of the SLR reference frame; (4) a comparison of the SLR reference frame with ITRF97; and (5) a comparison of SLR station velocities with those of ITRF97 and NNR NUVEL-1A.

An Object-Oriented Network-Centric Software Architecture for Physical Computing

NASA Astrophysics Data System (ADS)

Palmer, Richard

1997-08-01

Recent developments in object-oriented computer languages and infrastructure such as the Internet, Web browsers, and the like provide an opportunity to define a more productive computational environment for scientific programming that is based more closely on the underlying mathematics describing physics than traditional programming languages such as FORTRAN or C++. In this talk I describe an object-oriented software architecture for representing physical problems that includes classes for such common mathematical objects as geometry, boundary conditions, partial differential and integral equations, discretization and numerical solution methods, etc. In practice, a scientific program written using this architecture looks remarkably like the mathematics used to understand the problem, is typically an order of magnitude smaller than traditional FORTRAN or C++ codes, and hence easier to understand, debug, describe, etc. All objects in this architecture are ``network-enabled,'' which means that components of a software solution to a physical problem can be transparently loaded from anywhere on the Internet or other global network. The architecture is expressed as an ``API,'' or application programmers interface specification, with reference embeddings in Java, Python, and C++. A C++ class library for an early version of this API has been implemented for machines ranging from PC's to the IBM SP2, meaning that phidentical codes run on all architectures.

Evaluation of 14 global GIA forward models using a novel GPS dataset and GRACE

NASA Astrophysics Data System (ADS)

Bamber, J. L.; Schumacher, M.; Sha, Z.; Rougier, J.; King, M. A.; Khan, S. A.; Shum, C. K.; Luthcke, S. B.

2017-12-01

Observed mass movement from GRACE and vertical land motion from a global network of permanent GPS stations are used in a data driven approach to estimate GIA signals without introducing any assumptions about Earth structure nor ice loading history. Satellite data and in-situ observations are combined using a multivariate spatiotemporal model within a Bayesian Hierarchical Modelling (BHM) framework. In this study, the GPS data set of the Nevada Geodetic Laboratory (NGL) is used as the starting point for providing an observational estimate of global GIA uplift rates. A novel fully automatic post-processing strategy is developed to correct for non-GIA artifacts, including: (i) outlier detection (e.g. due to icing of Choke Ring Antennas or the antenna being buried in snow); (ii) automatic removal of reported and unreported jumps due to geophysical and hardware issues (a refinement of the jump database provided by NGL); and (iii) filtering for GPS stations that observe primarily the GIA signal rather than unwanted local effects (e.g., unmodelled loading effects from land hydrology, atmosphere, or tides). In order to accurately account for the elastic response of the Earth's crust over Antarctica and Greenland, uplift rates in these regions were corrected for the contemporary ice mass loading impact on elastic deformation using high-resolution ice mass balance time series. The novel global GPS data set shows a clean GIA signal at all post-processed stations and is therefore suitable to investigate the behavior of global GIA forward models. In addition, NASA's GSFC GRACE global mascon solutions are employed. The equal area 1x1 degree gridded mascons are spatially aggregated for larger regions to account for their spatial error correlations. Both the GPS and GRACE datasets are combined with prior information about spatial wavelengths of GIA signals obtained from the ICE-6G model within the BHM framework to solve for GIA. The results are compared with 14 global GIA forward model solutions to identify statistically significant deviations between the forward and inverse solutions, which may be due to either uncertain mantle rheology and/or ice loading history/magnitude.

State Support: A Prerequisite for Global Health Network Effectiveness

PubMed Central

Marten, Robert; Smith, Richard D.

2018-01-01

Shiffman recently summarized lessons for network effectiveness from an impressive collection of case-studies. However, in common with most global health governance analysis in recent years, Shiffman underplays the important role of states in these global networks. As the body which decides and signs international agreements, often provides the resourcing, and is responsible for implementing initiatives all contributing to the prioritization of certain issues over others, state recognition and support is a prerequisite to enabling and determining global health networks’ success. The role of states deserves greater attention, analysis and consideration. We reflect upon the underappreciated role of the state within the current discourse on global health. We present the tobacco case study to illustrate the decisive role of states in determining progress for global health networks, and highlight how states use a legitimacy loop to gain legitimacy from and provide legitimacy to global health networks. Moving forward in assessing global health networks’ effectiveness, further investigating state support as a determinant of success will be critical. Understanding how global health networks and states interact and evolve to shape and support their respective interests should be a focus for future research. PMID:29524958

Comparing and contrasting 'innovation platforms' with other forms of professional networks for strengthening primary healthcare systems for Indigenous Australians.

PubMed

Bailie, Jodie; Cunningham, Frances Clare; Bainbridge, Roxanne Gwendalyn; Passey, Megan E; Laycock, Alison Frances; Bailie, Ross Stewart; Larkins, Sarah L; Brands, Jenny S M; Ramanathan, Shanthi; Abimbola, Seye; Peiris, David

2018-01-01

Efforts to strengthen health systems require the engagement of diverse, multidisciplinary stakeholder networks. Networks provide a forum for experimentation and knowledge creation, information exchange and the spread of good ideas and practice. They might be useful in addressing complex issues or 'wicked' problems, the solutions to which go beyond the control and scope of any one agency. Innovation platforms are proposed as a novel type of network because of their diverse stakeholder composition and focus on problem solving within complex systems. Thus, they have potential applicability to health systems strengthening initiatives, even though they have been predominantly applied in the international agricultural development sector. In this paper, we compare and contrast the concept of innovation platforms with other types of networks that can be used in efforts to strengthen primary healthcare systems, such as communities of practice, practice-based research networks and quality improvement collaboratives. We reflect on our ongoing research programme that applies innovation platform concepts to drive large-scale quality improvement in primary healthcare for Aboriginal and Torres Strait Islander Australians and outline our plans for evaluation. Lessons from our experience will find resonance with others working on similar initiatives in global health.

Global Electricity Trade Network: Structures and Implications

PubMed Central

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions. PMID:27504825

Global Electricity Trade Network: Structures and Implications.

PubMed

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S F; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions.

Delineation and geometric modeling of road networks

NASA Astrophysics Data System (ADS)

Poullis, Charalambos; You, Suya

In this work we present a novel vision-based system for automatic detection and extraction of complex road networks from various sensor resources such as aerial photographs, satellite images, and LiDAR. Uniquely, the proposed system is an integrated solution that merges the power of perceptual grouping theory (Gabor filtering, tensor voting) and optimized segmentation techniques (global optimization using graph-cuts) into a unified framework to address the challenging problems of geospatial feature detection and classification. Firstly, the local precision of the Gabor filters is combined with the global context of the tensor voting to produce accurate classification of the geospatial features. In addition, the tensorial representation used for the encoding of the data eliminates the need for any thresholds, therefore removing any data dependencies. Secondly, a novel orientation-based segmentation is presented which incorporates the classification of the perceptual grouping, and results in segmentations with better defined boundaries and continuous linear segments. Finally, a set of gaussian-based filters are applied to automatically extract centerline information (magnitude, width and orientation). This information is then used for creating road segments and transforming them to their polygonal representations.

A Computational Approach to Estimate Interorgan Metabolic Transport in a Mammal

PubMed Central

Cui, Xiao; Geffers, Lars; Eichele, Gregor; Yan, Jun

2014-01-01

In multicellular organisms metabolism is distributed across different organs, each of which has specific requirements to perform its own specialized task. But different organs also have to support the metabolic homeostasis of the organism as a whole by interorgan metabolite transport. Recent studies have successfully reconstructed global metabolic networks in tissues and cell types and attempts have been made to connect organs with interorgan metabolite transport. Instead of these complicated approaches to reconstruct global metabolic networks, we proposed in this study a novel approach to study interorgan metabolite transport focusing on transport processes mediated by solute carrier (Slc) transporters and their couplings to cognate enzymatic reactions. We developed a computational approach to identify and score potential interorgan metabolite transports based on the integration of metabolism and transports in different organs in the adult mouse from quantitative gene expression data. This allowed us to computationally estimate the connectivity between 17 mouse organs via metabolite transport. Finally, by applying our method to circadian metabolism, we showed that our approach can shed new light on the current understanding of interorgan metabolite transport at a whole-body level in mammals. PMID:24971892

Networking among young global health researchers through an intensive training approach: a mixed methods exploratory study

PubMed Central

2014-01-01

Background Networks are increasingly regarded as essential in health research aimed at influencing practice and policies. Less research has focused on the role networking can play in researchers’ careers and its broader impacts on capacity strengthening in health research. We used the Canadian Coalition for Global Health Research (CCGHR) annual Summer Institute for New Global Health Researchers (SIs) as an opportunity to explore networking among new global health researchers. Methods A mixed-methods exploratory study was conducted among SI alumni and facilitators who had participated in at least one SI between 2004 and 2010. Alumni and facilitators completed an online short questionnaire, and a subset participated in an in-depth interview. Thematic analysis of the qualitative data was triangulated with quantitative results and CCGHR reports on SIs. Synthesis occurred through the development of a process model relevant to networking through the SIs. Results Through networking at the SIs, participants experienced decreased isolation and strengthened working relationships. Participants accessed new knowledge, opportunities, and resources through networking during the SI. Post-SI, participants reported ongoing contact and collaboration, although most participants desired more opportunities for interaction. They made suggestions for structural supports to networking among new global health researchers. Conclusions Networking at the SI contributed positively to opportunities for individuals, and contributed to the formation of a network of global health researchers. Intentional inclusion of networking in health research capacity strengthening initiatives, with supportive resources and infrastructure could create dynamic, sustainable networks accessible to global health researchers around the world. PMID:24460819

Estimating multi-period global cost efficiency and productivity change of systems with network structures

NASA Astrophysics Data System (ADS)

Tohidnia, S.; Tohidi, G.

2018-02-01

The current paper develops three different ways to measure the multi-period global cost efficiency for homogeneous networks of processes when the prices of exogenous inputs are known at all time periods. A multi-period network data envelopment analysis model is presented to measure the minimum cost of the network system based on the global production possibility set. We show that there is a relationship between the multi-period global cost efficiency of network system and its subsystems, and also its processes. The proposed model is applied to compute the global cost Malmquist productivity index for measuring the productivity changes of network system and each of its process between two time periods. This index is circular. Furthermore, we show that the productivity changes of network system can be defined as a weighted average of the process productivity changes. Finally, a numerical example will be presented to illustrate the proposed approach.

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

2008-01-01

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Exploring earthquake databases for the creation of magnitude-homogeneous catalogues: tools for application on a regional and global scale

NASA Astrophysics Data System (ADS)

Weatherill, G. A.; Pagani, M.; Garcia, J.

2016-09-01

The creation of a magnitude-homogenized catalogue is often one of the most fundamental steps in seismic hazard analysis. The process of homogenizing multiple catalogues of earthquakes into a single unified catalogue typically requires careful appraisal of available bulletins, identification of common events within multiple bulletins and the development and application of empirical models to convert from each catalogue's native scale into the required target. The database of the International Seismological Center (ISC) provides the most exhaustive compilation of records from local bulletins, in addition to its reviewed global bulletin. New open-source tools are developed that can utilize this, or any other compiled database, to explore the relations between earthquake solutions provided by different recording networks, and to build and apply empirical models in order to harmonize magnitude scales for the purpose of creating magnitude-homogeneous earthquake catalogues. These tools are described and their application illustrated in two different contexts. The first is a simple application in the Sub-Saharan Africa region where the spatial coverage and magnitude scales for different local recording networks are compared, and their relation to global magnitude scales explored. In the second application the tools are used on a global scale for the purpose of creating an extended magnitude-homogeneous global earthquake catalogue. Several existing high-quality earthquake databases, such as the ISC-GEM and the ISC Reviewed Bulletins, are harmonized into moment magnitude to form a catalogue of more than 562 840 events. This extended catalogue, while not an appropriate substitute for a locally calibrated analysis, can help in studying global patterns in seismicity and hazard, and is therefore released with the accompanying software.

An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

PubMed Central

Wang, Xue; Wang, Sheng; Ma, Jun-Jie

2007-01-01

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

Three Eras in Global Tobacco Control: How Global Governance Processes Influenced Online Tobacco Control Networking.

PubMed

Wipfli, Heather; Chu, Kar-Hai; Lancaster, Molly; Valente, Thomas

2016-01-01

Online networks can serve as a platform to diffuse policy innovations and enhance global health governance. This study focuses on how shifts in global health governance may influence related online networks. We compare social network metrics (average degree centrality [AVGD], density [D] and clustering coefficient [CC]) of Globalink, an online network of tobacco control advocates, across three eras in global tobacco control governance; pre-Framework Convention on Tobacco Control (FCTC) policy transfer (1992-1998), global regime formation through the FCTC negotiations (1999-2005), and philanthropic funding through the Bloomberg Initiative (2006-2012). Prior to 1999, Globalink was driven by a handful of high-income countries (AVGD=1.908 D=0.030, CC=0.215). The FCTC negotiations (1999-2005) corresponded with a rapid uptick in the number of countries represented within Globalink and new members were most often brought into the network through relationships with regional neighbors (AVGD=2.824, D=0.021, CC=0.253). Between 2006 and 2012, the centrality of the US in the network increases significantly (AVGD=3.414, D=0.023, CC=0.310). The findings suggest that global institutionalization through WHO, as with the FCTC, can lead to the rapid growth of decentralized online networks. Alternatively, private initiatives, such as the Bloomberg Initiative, can lead to clustering in which a single source of information gains increasing influence over an online network.

Global tree network for computing structures enabling global processing operations

DOEpatents

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

2010-01-19

A system and method for enabling high-speed, low-latency global tree network communications among processing nodes interconnected according to a tree network structure. The global tree network enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices are included that interconnect the nodes of the tree via links to facilitate performance of low-latency global processing operations at nodes of the virtual tree and sub-tree structures. The global operations performed include one or more of: broadcast operations downstream from a root node to leaf nodes of a virtual tree, reduction operations upstream from leaf nodes to the root node in the virtual tree, and point-to-point message passing from any node to the root node. The global tree network is configurable to provide global barrier and interrupt functionality in asynchronous or synchronized manner, and, is physically and logically partitionable.

Impact of the Topology of Global Macroeconomic Network on the Spreading of Economic Crises

PubMed Central

Lee, Kyu-Min; Yang, Jae-Suk; Kim, Gunn; Lee, Jaesung; Goh, Kwang-Il; Kim, In-mook

2011-01-01

Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more “globalized” random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises. PMID:21483794

Stormy Weather: 101 Solutions to Global Climate Change.

ERIC Educational Resources Information Center

Dauncey, Guy

This document presents 101 solutions to global climate change. These solutions are actions that are well suited to every level of society. This book creates awareness about global climate change. The history of Earth and the greenhouse effect are discussed, and explanations and solutions to global climate change are provided including traveling…

75 FR 34171 - Trueheat, Inc., a Subsidiary of Global Heating Solutions, Inc., Currently Known as Truheat, a...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-16

..., Inc., a Subsidiary of Global Heating Solutions, Inc., Currently Known as Truheat, a Division of Three Heat LLC, Allegan, MI; Electro-Heat, Inc., a Subsidiary of Global Heating Solutions, Inc., Currently... subsidiary of Global Heating Solutions, Inc., Allegan, Michigan and Electro-Heat, Inc., a subsidiary of...

Global deformation of the Earth, surface mass anomalies, and the geodetic infrastructure required to study these processes

NASA Astrophysics Data System (ADS)

Kusche, J.; Rietbroek, R.; Gunter, B.; Mark-Willem, J.

2008-12-01

Global deformation of the Earth can be linked to loading caused by mass changes in the atmosphere, the ocean and the terrestrial hydrosphere. World-wide geodetic observation systems like GPS, e.g., the global IGS network, can be used to study the global deformation of the Earth directly and, when other effects are properly modeled, provide information regarding the surface loading mass (e.g., to derive geo-center motion estimates). Vice versa, other observing systems that monitor mass change, either through gravitational changes (GRACE) or through a combination of in-situ and modeled quantities (e.g., the atmosphere, ocean or hydrosphere), can provide indirect information on global deformation. In the framework of the German 'Mass transport and mass distribution' program, we estimate surface mass anomalies at spherical harmonic resolution up to degree and order 30 by linking three complementary data sets in a least squares approach. Our estimates include geo-center motion and the thickness of a spatially uniform layer on top of the ocean surface (that is otherwise estimated from surface fluxes, evaporation and precipitation, and river run-off) as a time-series. As with all current Earth observing systems, each dataset has its own limitations and do not realize homogeneous coverage over the globe. To assess the impact that these limitations might have on current and future deformation and loading mass solutions, a sensitivity study was conducted. Simulated real-case and idealized solutions were explored in which the spatial distribution and quality of GPS, GRACE and OBP data sets were varied. The results show that significant improvements, e.g., over the current GRACE monthly gravity fields, in particular at the low degrees, can be achieved when these solutions are combined with present day GPS and OBP products. Our idealized scenarios also provide quantitative implications on how much surface mass change estimates may improve in the future when improved observing systems become available.

Comparison of potential field solutions for Carrington Rotation 2144

NASA Astrophysics Data System (ADS)

Hayashi, Keiji; Yang, Shangbin; Deng, Yuagyong

2016-02-01

We examined differences among the coronal magnetic field structures derived with the potential field source surface (PFSS) model for Carrington Rotation 2144, from 21 November to 19 December 2013. We used the synoptic maps of solar photospheric magnetic field from four observatories, the Huairou Solar Observing Station (HSOS), Global Oscillation Network Group (GONG), Helioseismic Magnetic Imager (HMI), and Wilcox Solar Observatory (WSO). We tested two smoothing methods, Gaussian and boxcar averaging, and correction of unbalanced net magnetic flux. The solutions of three-dimensional coronal magnetic field are significantly different each other. An open-field region derived with HSOS data agrees best with the corresponding coronal hole observed by Solar Dynamics Observatories/Atmospheric Imaging Assembly, while HMI data yielded best agreements with the near-Earth OMNI database. The GONG data overall gave agreements as good as the HMI. The PFSS calculations using WSO data were least sensitive to the choices we examined in this work. Differences in PFSS solutions using different choices and parameters in smoothing imply that the photospheric magnetic field distributions with size of several degrees at midlatitude and low-latitude regions can be decisive, at least, in the examined period. To better determine the global solar corona, therefore, further evaluation of influences from compact bipolar magnetic field is needed.

From Dyadic Ties to Information Infrastructures: Care-Coordination between Patients, Providers, Students and Researchers

PubMed Central

Purkayastha, S.; Biswas, R.; Jai Ganesh, A.U.; Otero, P.

2015-01-01

Summary Objective To share how an effectual merging of local and online networks in low resource regions can supplement and strengthen the local practice of patient centered care through the use of an online digital infrastructure powered by all stakeholders in healthcare. User Driven Health Care offers the dynamic integration of patient values and evidence based solutions for improved medical communication in medical care. Introduction This paper conceptualizes patient care-coordination through the lens of engaged stakeholders using digital infrastructures tools to integrate information technology. We distinguish this lens from the prevalent conceptualization of dyadic ties between clinician-patient, patient-nurse, clinician-nurse, and offer the holistic integration of all stakeholder inputs, in the clinic and augmented by online communication in a multi-national setting. Methods We analyze an instance of the user-driven health care (UDHC), a network of providers, patients, students and researchers working together to help manage patient care. The network currently focuses on patients from LMICs, but the provider network is global in reach. We describe UDHC and its opportunities and challenges in care-coordination to reduce costs, bring equity, and improve care quality and share evidence. Conclusion UDHC has resulted in coordinated global based local care, affecting multiple facets of medical practice. Shared information resources between providers with disparate knowledge, results in better understanding by patients, unique and challenging cases for students, innovative community based research and discovery learning for all. PMID:26123908

From Dyadic Ties to Information Infrastructures: Care-Coordination between Patients, Providers, Students and Researchers. Contribution of the Health Informatics Education Working Group.

PubMed

Purkayastha, S; Price, A; Biswas, R; Jai Ganesh, A U; Otero, P

2015-08-13

To share how an effectual merging of local and online networks in low resource regions can supplement and strengthen the local practice of patient centered care through the use of an online digital infrastructure powered by all stakeholders in healthcare. User Driven Health Care offers the dynamic integration of patient values and evidence based solutions for improved medical communication in medical care. This paper conceptualizes patient care-coordination through the lens of engaged stakeholders using digital infrastructures tools to integrate information technology. We distinguish this lens from the prevalent conceptualization of dyadic ties between clinician-patient, patient-nurse, clinician-nurse, and offer the holistic integration of all stakeholder inputs, in the clinic and augmented by online communication in a multi-national setting. We analyze an instance of the user-driven health care (UDHC), a network of providers, patients, students and researchers working together to help manage patient care. The network currently focuses on patients from LMICs, but the provider network is global in reach. We describe UDHC and its opportunities and challenges in care-coordination to reduce costs, bring equity, and improve care quality and share evidence. UDHC has resulted in coordinated global based local care, affecting multiple facets of medical practice. Shared information resources between providers with disparate knowledge, results in better understanding by patients, unique and challenging cases for students, innovative community based research and discovery learning for all.

Decreased Metabolism in the Posterior Medial Network with Concomitantly Increased Metabolism in the Anterior Temporal Network During Transient Global Amnesia.

PubMed

Yi, SangHak; Park, Young Ho; Jang, Jae-Won; Lim, Jae-Sung; Chun, In Kook; Kim, SangYun

2018-05-01

Perturbation of corticohippocampal circuits is a key step in the pathogenesis of transient global amnesia. We evaluated the spatial distribution of altered cerebral metabolism to determine the location of the corticohippocampal circuits perturbed during the acute stage of transient global amnesia. A consecutive series of 12 patients with transient global amnesia who underwent 18 F-fluorodeoxyglucose positron emission tomography within 3 days after symptom onset was identified. We used statistical parametric mapping with two contrasts to identify regions of decreased and increased brain metabolism in transient global amnesia patients compared with 25 age-matched controls. Transient global amnesia patients showed hypometabolic clusters in the left temporal and bilateral parieto-occipital regions that belong to the posterior medial network as well as, hypermetabolic clusters in the bilateral inferior frontal regions that belong to the anterior temporal network. The posterior medial and anterior temporal networks are the two main corticohippocampal circuits involved in memory-guided behavior. Decreased metabolism in the posterior medial network might explain the impairment of episodic memory observed during the acute stage of transient global amnesia. Concomitant increased metabolism within the anterior temporal network might occur as a compensatory mechanism.

Aberrant Global and Regional Topological Organization of the Fractional Anisotropy-weighted Brain Structural Networks in Major Depressive Disorder

PubMed Central

Chen, Jian-Huai; Yao, Zhi-Jian; Qin, Jiao-Long; Yan, Rui; Hua, Ling-Ling; Lu, Qing

2016-01-01

Background: Most previous neuroimaging studies have focused on the structural and functional abnormalities of local brain regions in major depressive disorder (MDD). Moreover, the exactly topological organization of networks underlying MDD remains unclear. This study examined the aberrant global and regional topological patterns of the brain white matter networks in MDD patients. Methods: The diffusion tensor imaging data were obtained from 27 patients with MDD and 40 healthy controls. The brain fractional anisotropy-weighted structural networks were constructed, and the global network and regional nodal metrics of the networks were explored by the complex network theory. Results: Compared with the healthy controls, the brain structural network of MDD patients showed an intact small-world topology, but significantly abnormal global network topological organization and regional nodal characteristic of the network in MDD were found. Our findings also indicated that the brain structural networks in MDD patients become a less strongly integrated network with a reduced central role of some key brain regions. Conclusions: All these resulted in a less optimal topological organization of networks underlying MDD patients, including an impaired capability of local information processing, reduced centrality of some brain regions and limited capacity to integrate information across different regions. Thus, these global network and regional node-level aberrations might contribute to understanding the pathogenesis of MDD from the view of the brain network. PMID:26960371

The UNESCO Global Network of National Geoparks

NASA Astrophysics Data System (ADS)

Mc Keever1, P.; Zouros, N.; Patzak, M.; Missotten, R.

2009-12-01

The UNESCO Global Network of National Geoparks was founded in 2004, following the model successfully established by the European Geoparks Network in 2000. It now comprises 63 members in 19 nations across the world. A Global Geopark is an area with geological heritage of international value but where that heritage is being used for the sustainable economic benefit if the local inhabitants, primarily through education and tourism. Supported by IUGS and IUCN, the aim of the Global Geoparks Network is to facilitate exchange and sharing between members to assist in the protection and conservation of the geological heritage of our planet but to do so in way where local communities can take ownership of these special places and where they can get some sustainable economic benefit from them. While allowing for the sustainable economic development of geoparks, the network explicitly forbids the destruction or sale of the geological value of a geopark. This paper outlines the ethos of the Global Geoparks Network and describes the typical activities of geoparks and how the network functions. Using two examples it also illustrates how members of the Global Geoparks Network provide good examples as tools not only for holistic nature conservation but also for economic development.

Association of Structural Global Brain Network Properties with Intelligence in Normal Aging

PubMed Central

Fischer, Florian U.; Wolf, Dominik; Scheurich, Armin; Fellgiebel, Andreas

2014-01-01

Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60–85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R) and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient) were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience. PMID:24465994

The challenge of sustaining effectiveness over time: the case of the global network to stop tuberculosis

PubMed Central

Quissell, Kathryn; Walt, Gill

2016-01-01

Where once global health decisions were largely the domain of national governments and the World Health Organization, today networks of international organizations, governments, private philanthropies and other entities are actively shaping public policy. However, there is still limited understanding of how global networks form, how they create institutions, how they promote and sustain collective action, and how they adapt to changes in the policy environment. Understanding these processes is crucial to understanding their effectiveness: whether and how global networks influence policy and public health outcomes. This study seeks to address these gaps through the examination of the global network to stop tuberculosis (TB) and the factors influencing its effectiveness over time. Drawing from ∼200 document sources and 16 interviews with key informants, we trace the development of the Global Partnership to Stop TB and its work over the past decade. We find that having a centralized core group and a strategic brand helped the network to coalesce around a primary intervention strategy, directly observed treatment short course. This strategy was created before the network was formalized, and helped bring in donors, ministries of health and other organizations committed to fighting TB—growing the network. Adaptations to this strategy, the creation of a consensus-based Global Plan, and the creation of a variety of participatory venues for discussion, helped to expand and sustain the network. Presently, however, tensions have become more apparent within the network as it struggles with changing internal political dynamics and the evolution of the disease. While centralization and stability helped to launch and grow the network, the institutionalization of governance and strategy may have constrained adaptation. Institutionalization and centralization may, therefore, facilitate short-term success for networks, but may end up complicating longer-term effectiveness. PMID:26282859

Neocortical dynamics due to axon propagation delays in cortico-cortical fibers: EEG traveling and standing waves with implications for top-down influences on local networks and white matter disease

PubMed Central

Nunez, Paul L.; Srinivasan, Ramesh

2013-01-01

The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628

Structure and evolution of the global seafood trade network

NASA Astrophysics Data System (ADS)

Gephart, Jessica A.; Pace, Michael L.

2015-12-01

The food production system is increasingly global and seafood is among the most highly traded commodities. Global trade can improve food security by providing access to a greater variety of foods, increasing wealth, buffering against local supply shocks, and benefit the environment by increasing overall use efficiency for some resources. However, global trade can also expose countries to external supply shocks and degrade the environment by increasing resource demand and loosening feedbacks between consumers and the impacts of food production. As a result, changes in global food trade can have important implications for both food security and the environmental impacts of production. Measurements of globalization and the environmental impacts of food production require data on both total trade and the origin and destination of traded goods (the network structure). While the global trade network of agricultural and livestock products has previously been studied, seafood products have been excluded. This study describes the structure and evolution of the global seafood trade network, including metrics quantifying the globalization of seafood, shifts in bilateral trade flows, changes in centrality and comparisons of seafood to agricultural and industrial trade networks. From 1994 to 2012 the number of countries trading in the network remained relatively constant, while the number of trade partnerships increased by over 65%. Over this same period, the total quantity of seafood traded increased by 58% and the value increased 85% in real terms. These changes signify the increasing globalization of seafood products. Additionally, the trade patterns in the network indicate: increased influence of Thailand and China, strengthened intraregional trade, and increased exports from South America and Asia. In addition to characterizing these network changes, this study identifies data needs in order to connect seafood trade with environmental impacts and food security outcomes.

Location estimation in wireless sensor networks using spring-relaxation technique.

PubMed

Zhang, Qing; Foh, Chuan Heng; Seet, Boon-Chong; Fong, A C M

2010-01-01

Accurate and low-cost autonomous self-localization is a critical requirement of various applications of a large-scale distributed wireless sensor network (WSN). Due to its massive deployment of sensors, explicit measurements based on specialized localization hardware such as the Global Positioning System (GPS) is not practical. In this paper, we propose a low-cost WSN localization solution. Our design uses received signal strength indicators for ranging, light weight distributed algorithms based on the spring-relaxation technique for location computation, and the cooperative approach to achieve certain location estimation accuracy with a low number of nodes with known locations. We provide analysis to show the suitability of the spring-relaxation technique for WSN localization with cooperative approach, and perform simulation experiments to illustrate its accuracy in localization.

Convergence and attractivity of memristor-based cellular neural networks with time delays.

PubMed

Qin, Sitian; Wang, Jun; Xue, Xiaoping

2015-03-01

This paper presents theoretical results on the convergence and attractivity of memristor-based cellular neural networks (MCNNs) with time delays. Based on a realistic memristor model, an MCNN is modeled using a differential inclusion. The essential boundedness of its global solutions is proven. The state of MCNNs is further proven to be convergent to a critical-point set located in saturated region of the activation function, when the initial state locates in a saturated region. It is shown that the state convergence time period is finite and can be quantitatively estimated using given parameters. Furthermore, the positive invariance and attractivity of state in non-saturated regions are also proven. The simulation results of several numerical examples are provided to substantiate the results. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hydraulic tomography of discrete networks of conduits and fractures in a karstic aquifer by using a deterministic inversion algorithm

NASA Astrophysics Data System (ADS)

Fischer, P.; Jardani, A.; Lecoq, N.

2018-02-01

In this paper, we present a novel inverse modeling method called Discrete Network Deterministic Inversion (DNDI) for mapping the geometry and property of the discrete network of conduits and fractures in the karstified aquifers. The DNDI algorithm is based on a coupled discrete-continuum concept to simulate numerically water flows in a model and a deterministic optimization algorithm to invert a set of observed piezometric data recorded during multiple pumping tests. In this method, the model is partioned in subspaces piloted by a set of parameters (matrix transmissivity, and geometry and equivalent transmissivity of the conduits) that are considered as unknown. In this way, the deterministic optimization process can iteratively correct the geometry of the network and the values of the properties, until it converges to a global network geometry in a solution model able to reproduce the set of data. An uncertainty analysis of this result can be performed from the maps of posterior uncertainties on the network geometry or on the property values. This method has been successfully tested for three different theoretical and simplified study cases with hydraulic responses data generated from hypothetical karstic models with an increasing complexity of the network geometry, and of the matrix heterogeneity.

Cyber-Ed.

ERIC Educational Resources Information Center

Ruben, Barbara

1994-01-01

Reviews a number of interactive environmental computer education networks and software packages. Computer networks include National Geographic Kids Network, Global Lab, and Global Rivers Environmental Education Network. Computer software involve environmental decision making, simulation games, tropical rainforests, the ocean, the greenhouse…

Bluetooth Low Energy Mesh Networks: A Survey.

PubMed

Darroudi, Seyed Mahdi; Gomez, Carles

2017-06-22

Bluetooth Low Energy (BLE) has gained significant momentum. However, the original design of BLE focused on star topology networking, which limits network coverage range and precludes end-to-end path diversity. In contrast, other competing technologies overcome such constraints by supporting the mesh network topology. For these reasons, academia, industry, and standards development organizations have been designing solutions to enable BLE mesh networks. Nevertheless, the literature lacks a consolidated view on this emerging area. This paper comprehensively surveys state of the art BLE mesh networking. We first provide a taxonomy of BLE mesh network solutions. We then review the solutions, describing the variety of approaches that leverage existing BLE functionality to enable BLE mesh networks. We identify crucial aspects of BLE mesh network solutions and discuss their advantages and drawbacks. Finally, we highlight currently open issues.

Optimization of deformation monitoring networks using finite element strain analysis

NASA Astrophysics Data System (ADS)

Alizadeh-Khameneh, M. Amin; Eshagh, Mehdi; Jensen, Anna B. O.

2018-04-01

An optimal design of a geodetic network can fulfill the requested precision and reliability of the network, and decrease the expenses of its execution by removing unnecessary observations. The role of an optimal design is highlighted in deformation monitoring network due to the repeatability of these networks. The core design problem is how to define precision and reliability criteria. This paper proposes a solution, where the precision criterion is defined based on the precision of deformation parameters, i. e. precision of strain and differential rotations. A strain analysis can be performed to obtain some information about the possible deformation of a deformable object. In this study, we split an area into a number of three-dimensional finite elements with the help of the Delaunay triangulation and performed the strain analysis on each element. According to the obtained precision of deformation parameters in each element, the precision criterion of displacement detection at each network point is then determined. The developed criterion is implemented to optimize the observations from the Global Positioning System (GPS) in Skåne monitoring network in Sweden. The network was established in 1989 and straddled the Tornquist zone, which is one of the most active faults in southern Sweden. The numerical results show that 17 out of all 21 possible GPS baseline observations are sufficient to detect minimum 3 mm displacement at each network point.

The community structure of the global corporate network.

PubMed

Vitali, Stefania; Battiston, Stefano

2014-01-01

We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the meta-network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide a quantitative assessment of the financial sector role in connecting the global economy.

The Community Structure of the Global Corporate Network

PubMed Central

Vitali, Stefania; Battiston, Stefano

2014-01-01

We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the meta-network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide a quantitative assessment of the financial sector role in connecting the global economy. PMID:25126722

Three Eras in Global Tobacco Control: How Global Governance Processes Influenced Online Tobacco Control Networking

PubMed Central

Wipfli, Heather; Chu, Kar-Hai; Lancaster, Molly; Valente, Thomas

2017-01-01

Online networks can serve as a platform to diffuse policy innovations and enhance global health governance. This study focuses on how shifts in global health governance may influence related online networks. We compare social network metrics (average degree centrality [AVGD], density [D] and clustering coefficient [CC]) of Globalink, an online network of tobacco control advocates, across three eras in global tobacco control governance; pre-Framework Convention on Tobacco Control (FCTC) policy transfer (1992–1998), global regime formation through the FCTC negotiations (1999–2005), and philanthropic funding through the Bloomberg Initiative (2006–2012). Prior to 1999, Globalink was driven by a handful of high-income countries (AVGD=1.908 D=0.030, CC=0.215). The FCTC negotiations (1999–2005) corresponded with a rapid uptick in the number of countries represented within Globalink and new members were most often brought into the network through relationships with regional neighbors (AVGD=2.824, D=0.021, CC=0.253). Between 2006 and 2012, the centrality of the US in the network increases significantly (AVGD=3.414, D=0.023, CC=0.310). The findings suggest that global institutionalization through WHO, as with the FCTC, can lead to the rapid growth of decentralized online networks. Alternatively, private initiatives, such as the Bloomberg Initiative, can lead to clustering in which a single source of information gains increasing influence over an online network. PMID:28596813

Expansion of Surveillance for Vaccine-preventable Diseases: Building on the Global Polio Laboratory Network and the Global Measles and Rubella Laboratory Network Platforms.

PubMed

Mulders, Mick N; Serhan, Fatima; Goodson, James L; Icenogle, Joseph; Johnson, Barbara W; Rota, Paul A

2017-07-01

Laboratory networks were established to provide accurate and timely laboratory confirmation of infections, an essential component of disease surveillance systems. The World Health Organization (WHO) coordinates global laboratory surveillance of vaccine-preventable diseases (VPDs), including polio, measles and rubella, yellow fever, Japanese encephalitis, rotavirus, and invasive bacterial diseases. In addition to providing high-quality laboratory surveillance data to help guide disease control, elimination, and eradication programs, these global networks provide capacity-building and an infrastructure for public health laboratories. There are major challenges with sustaining and expanding the global laboratory surveillance capacity: limited resources and the need for expansion to meet programmatic goals. Here, we describe the WHO-coordinated laboratory networks supporting VPD surveillance and present a plan for the further development of these networks. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America.

Identification of the connections in biologically inspired neural networks

NASA Technical Reports Server (NTRS)

Demuth, H.; Leung, K.; Beale, M.; Hicklin, J.

1990-01-01

We developed an identification method to find the strength of the connections between neurons from their behavior in small biologically-inspired artificial neural networks. That is, given the network external inputs and the temporal firing pattern of the neurons, we can calculate a solution for the strengths of the connections between neurons and the initial neuron activations if a solution exists. The method determines directly if there is a solution to a particular neural network problem. No training of the network is required. It should be noted that this is a first pass at the solution of a difficult problem. The neuron and network models chosen are related to biology but do not contain all of its complexities, some of which we hope to add to the model in future work. A variety of new results have been obtained. First, the method has been tailored to produce connection weight matrix solutions for networks with important features of biological neural (bioneural) networks. Second, a computationally efficient method of finding a robust central solution has been developed. This later method also enables us to find the most consistent solution in the presence of noisy data. Prospects of applying our method to identify bioneural network connections are exciting because such connections are almost impossible to measure in the laboratory. Knowledge of such connections would facilitate an understanding of bioneural networks and would allow the construction of the electronic counterparts of bioneural networks on very large scale integrated (VLSI) circuits.

Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks

DTIC Science & Technology

2014-03-31

Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks M.M. Asadi H. Mahboubi A...2014 Global Network Connectivity Assessment via Local Data Exchange for Underwater Acoustic Sensor Networks Contract Report # AMBUSH.1.1 Contract...pi j /= 0. The sensor network considered in this work is composed of underwater sensors , which use acoustic waves for

Predicting the global spread range via small subnetworks

NASA Astrophysics Data System (ADS)

Sun, Jiachen; Dong, Junyou; Ma, Xiao; Feng, Ling; Hu, Yanqing

2017-04-01

Modern online social network platforms are replacing traditional media due to their effectiveness in both spreading information and communicating opinions. One of the key problems in these online platforms is to predict the global spread range of any given information. Due to its gigantic size as well as time-varying dynamics, an online social network's global structure, however, is usually inaccessible to most researchers. Thus, it raises the very important issue of how to use solely small subnetworks to predict the global influence. In this paper, based on percolation theory, we show that the global spread range can be predicted well from only two small subnetworks. We test our methods in an artificial network and three empirical online social networks, such as the full Sina Weibo network with 99546027 nodes.

Controller–Pilot Data Link Communication Security

PubMed Central

Polishchuk, Tatiana; Wernberg, Max

2018-01-01

The increased utilization of the new types of cockpit communications, including controller–pilot data link communications (CPDLC), puts the airplane at higher risk of hacking or interference than ever before. We review the technological characteristics and properties of the CPDLC and construct the corresponding threat model. Based on the limitations imposed by the system parameters, we propose several solutions for the improved security of the data messaging communication used in air traffic management (ATM). We discuss the applicability of elliptical curve cryptography (ECC), protected aircraft communications addressing and reporting systems (PACARs) and the Host Identity Protocol (HIP) as possible countermeasures to the identified security threats. In addition, we consider identity-defined networking (IDN) as an example of a genuine security solution which implies global changes in the whole air traffic communication system. PMID:29783791

Controller⁻Pilot Data Link Communication Security.

PubMed

Gurtov, Andrei; Polishchuk, Tatiana; Wernberg, Max

2018-05-20

The increased utilization of the new types of cockpit communications, including controller⁻pilot data link communications (CPDLC), puts the airplane at higher risk of hacking or interference than ever before. We review the technological characteristics and properties of the CPDLC and construct the corresponding threat model. Based on the limitations imposed by the system parameters, we propose several solutions for the improved security of the data messaging communication used in air traffic management (ATM). We discuss the applicability of elliptical curve cryptography (ECC), protected aircraft communications addressing and reporting systems (PACARs) and the Host Identity Protocol (HIP) as possible countermeasures to the identified security threats. In addition, we consider identity-defined networking (IDN) as an example of a genuine security solution which implies global changes in the whole air traffic communication system.

A strategic outlook for coordination of ground-based measurement networks of atmospheric state variables and atmospheric composition

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Thorne, P.; Braathen, G.; De Maziere, M.; Thompson, A. M.; Kurylo, M. J., III

2016-12-01

There are a number of ground-based global observing networks that collectively aim to make key measurements of atmospheric state variables and atmospheric chemical composition. These networks include, but are not limited to:NDACC: Network for the Detection of Atmospheric Composition Change GUAN: GCOS Upper Air Network GRUAN: GCOS Reference Upper Air Network EARLINET: the European Aerosol Research Lidar Network GAW: Global Atmosphere Watch SHADOZ: Southern Hemisphere ADditional OZonesondes TCCON: Total Carbon Column Observing Network BSRN: Baseline Surface Radiation Network While each network brings unique capabilities to the global observing system, there are many instances where the activities and capabilities of the networks overlap. These commonalities across multiple networks can confound funding agencies when allocating scarce financial resources. Overlaps between networks may also result in some duplication of effort and a resultant sub-optimal use of funding resource for the global observing system. While some degree of overlap is useful for quality assurance, it is essential to identify the degree to which one network can take on a specific responsibility on behalf of all other networks to avoid unnecessary duplication, to identify where expertise in any one network may serve other networks, and to develop a long-term strategy for the evolution of these networks that clarifies to funding agencies where new investment is required. This presentation will briefly summarise the key characteristics of each network listed above, adopt a matrix approach to identify commonalities and, in particular, where there may be a danger of duplication of effort, and where gaps between the networks may be compromising the services that these networks are expected to collectively deliver to the global atmospheric and climate science research communities. The presentation will also examine where sharing of data and tools between networks may result in a more efficient delivery of records of essential climate variables to the global research community. There are aspects of underpinning research that are needed across all of these networks, such as laboratory spectroscopy, that often do not receive the attention they deserve. The presentation will also seek to identify where that underpinning research is lacking.

Geometry Genetics and Evolution

NASA Astrophysics Data System (ADS)

Siggia, Eric

2011-03-01

Darwin argued that highly perfected organs such as the vertebrate eye could evolve by a series of small changes, each of which conferred a selective advantage. In the context of gene networks, this idea can be recast into a predictive algorithm, namely find networks that can be built by incremental adaptation (gradient search) to perform some task. It embodies a ``kinetic'' view of evolution where a solution that is quick to evolve is preferred over a global optimum. Examples of biochemical kinetic networks were evolved for temporal adaptation, temperature compensated entrainable clocks, explore-exploit trade off in signal discrimination, will be presented as well as networks that model the spatially periodic somites (vertebrae) and HOX gene expression in the vertebrate embryo. These models appear complex by the criterion of 19th century applied mathematics since there is no separation of time or spatial scales, yet they are all derivable by gradient optimization of simple functions (several in the Pareto evolution) often based on the Shannon entropy of the time or spatial response. Joint work with P. Francois, Physics Dept. McGill University. With P. Francois, Physics Dept. McGill University

Self-organising mixture autoregressive model for non-stationary time series modelling.

PubMed

Ni, He; Yin, Hujun

2008-12-01

Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.

Bluetooth Low Energy Mesh Networks: A Survey

PubMed Central

Darroudi, Seyed Mahdi; Gomez, Carles

2017-01-01

Bluetooth Low Energy (BLE) has gained significant momentum. However, the original design of BLE focused on star topology networking, which limits network coverage range and precludes end-to-end path diversity. In contrast, other competing technologies overcome such constraints by supporting the mesh network topology. For these reasons, academia, industry, and standards development organizations have been designing solutions to enable BLE mesh networks. Nevertheless, the literature lacks a consolidated view on this emerging area. This paper comprehensively surveys state of the art BLE mesh networking. We first provide a taxonomy of BLE mesh network solutions. We then review the solutions, describing the variety of approaches that leverage existing BLE functionality to enable BLE mesh networks. We identify crucial aspects of BLE mesh network solutions and discuss their advantages and drawbacks. Finally, we highlight currently open issues. PMID:28640183

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

PubMed

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies.

Applying differential dynamic logic to reconfigurable biological networks.

PubMed

Figueiredo, Daniel; Martins, Manuel A; Chaves, Madalena

2017-09-01

Qualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system's global dynamics and the latter providing more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS). In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is differential dynamic logic (dL), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how dL can be used as an alternative, or also as a complement to methods already used. Copyright © 2017 Elsevier Inc. All rights reserved.

Road networks as collections of minimum cost paths

NASA Astrophysics Data System (ADS)

Wegner, Jan Dirk; Montoya-Zegarra, Javier Alexander; Schindler, Konrad

2015-10-01

We present a probabilistic representation of network structures in images. Our target application is the extraction of urban roads from aerial images. Roads appear as thin, elongated, partially curved structures forming a loopy graph, and this complex layout requires a prior that goes beyond standard smoothness and co-occurrence assumptions. In the proposed model the network is represented as a union of 1D paths connecting distant (super-)pixels. A large set of putative candidate paths is constructed in such a way that they include the true network as much as possible, by searching for minimum cost paths in the foreground (road) likelihood. Selecting the optimal subset of candidate paths is posed as MAP inference in a higher-order conditional random field. Each path forms a higher-order clique with a type of clique potential, which attracts the member nodes of cliques with high cumulative road evidence to the foreground label. That formulation induces a robust PN -Potts model, for which a global MAP solution can be found efficiently with graph cuts. Experiments with two road data sets show that the proposed model significantly improves per-pixel accuracies as well as the overall topological network quality with respect to several baselines.

Electronic neural network for dynamic resource allocation

NASA Technical Reports Server (NTRS)

Thakoor, A. P.; Eberhardt, S. P.; Daud, T.

1991-01-01

A VLSI implementable neural network architecture for dynamic assignment is presented. The resource allocation problems involve assigning members of one set (e.g. resources) to those of another (e.g. consumers) such that the global 'cost' of the associations is minimized. The network consists of a matrix of sigmoidal processing elements (neurons), where the rows of the matrix represent resources and columns represent consumers. Unlike previous neural implementations, however, association costs are applied directly to the neurons, reducing connectivity of the network to VLSI-compatible 0 (number of neurons). Each row (and column) has an additional neuron associated with it to independently oversee activations of all the neurons in each row (and each column), providing a programmable 'k-winner-take-all' function. This function simultaneously enforces blocking (excitatory/inhibitory) constraints during convergence to control the number of active elements in each row and column within desired boundary conditions. Simulations show that the network, when implemented in fully parallel VLSI hardware, offers optimal (or near-optimal) solutions within only a fraction of a millisecond, for problems up to 128 resources and 128 consumers, orders of magnitude faster than conventional computing or heuristic search methods.

Status report on the establishment of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) International Monitoring System (IMS) infrasound network

NASA Astrophysics Data System (ADS)

Vivas Veloso, J. A.; Christie, D. R.; Campus, P.; Bell, M.; Hoffmann, T. L.; Langlois, A.; Martysevich, P.; Demirovik, E.; Carvalho, J.; Kramer, A.

2002-11-01

The infrasound component of the International Monitoring System (IMS) for Comprehensive Nuclear-Test-Ban Treaty verification aims for global detection and localization of low-frequency sound waves originating from atmospheric nuclear explosions. The infrasound network will consist of 60 array stations, distributed as evenly as possible over the globe to assure at least two-station detection capability for 1-kton explosions at any point on earth. This network will be larger and more sensitive than any other previously operated infrasound network. As of today, 85% of the site surveys for IMS infrasound stations have been completed, 25% of the stations have been installed, and 8% of the installations have been certified and are transmitting high-quality continuous data to the International Data Center in Vienna. By the end of 2002, 20% of the infrasound network is expected to be certified and operating in post-certification mode. This presentation will discuss the current status and progress made in the site survey, installation, and certification programs for IMS infrasound stations. A review will be presented of the challenges and difficulties encountered in these programs, together with practical solutions to these problems.

Congestion control for a fair packet delivery in WSN: from a complex system perspective.

PubMed

Aguirre-Guerrero, Daniela; Marcelín-Jiménez, Ricardo; Rodriguez-Colina, Enrique; Pascoe-Chalke, Michael

2014-01-01

In this work, we propose that packets travelling across a wireless sensor network (WSN) can be seen as the active agents that make up a complex system, just like a bird flock or a fish school, for instance. From this perspective, the tools and models that have been developed to study this kind of systems have been applied. This is in order to create a distributed congestion control based on a set of simple rules programmed at the nodes of the WSN. Our results show that it is possible to adapt the carried traffic to the network capacity, even under stressing conditions. Also, the network performance shows a smooth degradation when the traffic goes beyond a threshold which is settled by the proposed self-organized control. In contrast, without any control, the network collapses before this threshold. The use of the proposed solution provides an effective strategy to address some of the common problems found in WSN deployment by providing a fair packet delivery. In addition, the network congestion is mitigated using adaptive traffic mechanisms based on a satisfaction parameter assessed by each packet which has impact on the global satisfaction of the traffic carried by the WSN.

Switch-connected HyperX network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Dong; Heidelberger, Philip

A network system includes a plurality of sub-network planes and global switches. The sub-network planes have a same network topology as each other. Each of the sub-network planes includes edge switches. Each of the edge switches has N ports. Each of the global switches is configured to connect a group of edge switches at a same location in the sub-network planes. In each of the sub-network planes, some of the N ports of each of the edge switches are connected to end nodes, and others of the N ports are connected to other edge switches in the same sub-network plane,more » other of the N ports are connected to at least one of the global switches.« less

East/West Perspectives on Education for Peace and Security. Conference Report of the International Network for Global Education (INGE) (New Paltz, New York, November 8-12, 1986).

ERIC Educational Resources Information Center

Global Perspectives in Education, Inc., New York, NY.

The purpose of the International Network for Global Education (INGE) is to promote global education within the educational systems of network member countries. Areas of study are listed under the following headings: Peace Studies; East/West Relations; North/South Relations; Human Rights; Global Environment; Human Values; and Cross-cultural Issues.…

Anti-correlated Networks, Global Signal Regression, and the Effects of Caffeine in Resting-State Functional MRI

PubMed Central

Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T.

2012-01-01

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. PMID:22743194

A new technique in the global reliability of cyclic communications network

NASA Technical Reports Server (NTRS)

Sjogren, Jon A.

1989-01-01

The global reliability of a communications network is the probability that given any pair of nodes, there exists a viable path between them. A characterization of connectivity, for a given class of networks, can enable one to find this reliability. Such a characterization is described for a useful class of undirected networks called daisy-chained or braided networks. This leads to a new method of quickly computing the global reliability of these networks. Asymptotic behavior in terms of component reliability is related to geometric properties of the given graph. Generalization of the technique is discussed.

Comparison of Velocity Models for South America through Seismic Wave Modeling of Ten Andean Earthquakes Recorded by the Brazilian Seismographic Network using the Spectral Element Method

NASA Astrophysics Data System (ADS)

Ciardelli, C.; Assumpcao, M.

2016-12-01

In this work, we carried out simulations of seismic waves propagation for ten large earthquakes occurred in Chile between 2011 and 2016,using the SPECFEM3D Global software (Komatitsch and Tromp, 2000) and the Centroid Moment Tensor solutions from the global catalog (Dziewonski, Chou and Woodhouse, 1981; Ekström, Nettles and Dziewonski, 2012). For each event, the complete wave field was calculated using the spectral element method and recorded at the coordinates of the Brazilian Seismographic Network, thus we can compare the synthetic seismograms with the real data. Initially, we assess the differences between CRUST1.0 and CRUST2.0 models using the transversely isotropic PREM for the internal part of the planet. We will also compare the PREM velocity model plus CRUST1.0 with the Feng's velocity model for South America (Feng, Van der Lee and Assumpção, 2007), calculated using Partitioned Waveform Inversion. For each model, we will evaluate the misfit for all stations of the network. The similarity can be estimated by pure RMS or combining it with cross-correlation. Travel-time residuals can also be used to better constrain velocity anomalies and avoid cycle-skipping. The results will help to assess which model is more appropriated to start a Full-waveform Tomography of the South American continent and the surrounding oceans.

Structure and controls of the global virtual water trade network

NASA Astrophysics Data System (ADS)

Suweis, S.; Konar, M.; Dalin, C.; Hanasaki, N.; Rinaldo, A.; Rodriguez-Iturbe, I.

2011-05-01

Recurrent or ephemeral water shortages are a crucial global challenge, in particular because of their impacts on food production. The global character of this challenge is reflected in the trade among nations of virtual water, i.e., the amount of water used to produce a given commodity. We build, analyze and model the network describing the transfer of virtual water between world nations for staple food products. We find that all the key features of the network are well described by a model that reproduces both the topological and weighted properties of the global virtual water trade network, by assuming as sole controls each country's gross domestic product and yearly rainfall on agricultural areas. We capture and quantitatively describe the high degree of globalization of water trade and show that a small group of nations play a key role in the connectivity of the network and in the global redistribution of virtual water. Finally, we illustrate examples of prediction of the structure of the network under future political, economic and climatic scenarios, suggesting that the crucial importance of the countries that trade large volumes of water will be strengthened.

A framework on the emergence and effectiveness of global health networks

PubMed Central

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

2016-01-01

Since 1990 mortality and morbidity decline has been more extensive for some conditions prevalent in low- and middle-income countries than for others. One reason may be differences in the effectiveness of global health networks, which have proliferated in recent years. Some may be more capable than others in attracting attention to a condition, in generating funding, in developing interventions and in convincing national governments to adopt policies. This article introduces a supplement on the emergence and effectiveness of global health networks. The supplement examines networks concerned with six global health problems: tuberculosis (TB), pneumonia, tobacco use, alcohol harm, maternal mortality and newborn deaths. This article presents a conceptual framework delineating factors that may shape why networks crystallize more easily surrounding some issues than others, and once formed, why some are better able than others to shape policy and public health outcomes. All supplement papers draw on this framework. The framework consists of 10 factors in three categories: (1) features of the networks and actors that comprise them, including leadership, governance arrangements, network composition and framing strategies; (2) conditions in the global policy environment, including potential allies and opponents, funding availability and global expectations concerning which issues should be prioritized; (3) and characteristics of the issue, including severity, tractability and affected groups. The article also explains the design of the project, which is grounded in comparison of networks surrounding three matched issues: TB and pneumonia, tobacco use and alcohol harm, and maternal and newborn survival. Despite similar burden and issue characteristics, there has been considerably greater policy traction for the first in each pair. The supplement articles aim to explain the role of networks in shaping these differences, and collectively represent the first comparative effort to understand the emergence and effectiveness of global health networks. PMID:26318679

Convergence and rate analysis of neural networks for sparse approximation.

PubMed

Balavoine, Aurèle; Romberg, Justin; Rozell, Christopher J

2012-09-01

We present an analysis of the Locally Competitive Algorithm (LCA), which is a Hopfield-style neural network that efficiently solves sparse approximation problems (e.g., approximating a vector from a dictionary using just a few nonzero coefficients). This class of problems plays a significant role in both theories of neural coding and applications in signal processing. However, the LCA lacks analysis of its convergence properties, and previous results on neural networks for nonsmooth optimization do not apply to the specifics of the LCA architecture. We show that the LCA has desirable convergence properties, such as stability and global convergence to the optimum of the objective function when it is unique. Under some mild conditions, the support of the solution is also proven to be reached in finite time. Furthermore, some restrictions on the problem specifics allow us to characterize the convergence rate of the system by showing that the LCA converges exponentially fast with an analytically bounded convergence rate. We support our analysis with several illustrative simulations.

Remote sensing and the Mississippi high accuracy reference network

NASA Technical Reports Server (NTRS)

Mick, Mark; Alexander, Timothy M.; Woolley, Stan

1994-01-01

Since 1986, NASA's Commercial Remote Sensing Program (CRSP) at Stennis Space Center has supported commercial remote sensing partnerships with industry. CRSP's mission is to maximize U.S. market exploitation of remote sensing and related space-based technologies and to develop advanced technical solutions for spatial information requirements. Observation, geolocation, and communications technologies are converging and their integration is critical to realize the economic potential for spatial informational needs. Global positioning system (GPS) technology enables a virtual revolution in geopositionally accurate remote sensing of the earth. A majority of states are creating GPS-based reference networks, or high accuracy reference networks (HARN). A HARN can be defined for a variety of local applications and tied to aerial or satellite observations to provide an important contribution to geographic information systems (GIS). This paper details CRSP's experience in the design and implementation of a HARN in Mississippi and the design and support of future applications of integrated earth observations, geolocation, and communications technology.

A security framework for nationwide health information exchange based on telehealth strategy.

PubMed

Zaidan, B B; Haiqi, Ahmed; Zaidan, A A; Abdulnabi, Mohamed; Kiah, M L Mat; Muzamel, Hussaen

2015-05-01

This study focuses on the situation of health information exchange (HIE) in the context of a nationwide network. It aims to create a security framework that can be implemented to ensure the safe transmission of health information across the boundaries of care providers in Malaysia and other countries. First, a critique of the major elements of nationwide health information networks is presented from the perspective of security, along with such topics as the importance of HIE, issues, and main approaches. Second, a systematic evaluation is conducted on the security solutions that can be utilized in the proposed nationwide network. Finally, a secure framework for health information transmission is proposed within a central cloud-based model, which is compatible with the Malaysian telehealth strategy. The outcome of this analysis indicates that a complete security framework for a global structure of HIE is yet to be defined and implemented. Our proposed framework represents such an endeavor and suggests specific techniques to achieve this goal.

Impact of RNA Degradation on Viral Diagnosis: An Understated but Essential Step for the Successful Establishment of a Diagnosis Network

PubMed Central

Relova, Damarys; Acevedo, Ana M.; Coronado, Liani; Perera, Carmen L.

2018-01-01

The current global conditions, which include intensive globalization, climate changes, and viral evolution among other factors, have led to an increased emergence of viruses and new viral diseases; RNA viruses are key drivers of this evolution. Laboratory networks that are linked to central reference laboratories are required to conduct both active and passive environmental surveillance of this complicated global viral environment. These tasks require a continuous exchange of strains or field samples between different diagnostic laboratories. The shipment of these samples on dry ice represents both a biological hazard and a general health risk. Moreover, the requirement to ship on dry ice could be hampered by high costs, particularly in underdeveloped countries or regions located far from each other. To solve these issues, the shipment of RNA isolated from viral suspensions or directly from field samples could be a useful way to share viral genetic material. However, extracted RNA stored in aqueous solutions, even at −70 °C, is highly prone to degradation. The current study evaluated different RNA storage conditions for safety and feasibility for future use in molecular diagnostics. The in vitro RNA-transcripts obtained from an inactivated highly pathogenic avian influenza (HPAI) H5N1 virus was used as a model. The role of secondary structures in the protection of the RNA was also explored. Of the conditions evaluated, the dry pellet matrix was best able to protect viral RNA under extreme storage conditions. This method is safe, cost-effective and assures the integrity of RNA samples for reliable molecular diagnosis. This study aligns with the globally significant “Global One Health” paradigm, especially with respect to the diagnosis of emerging diseases that require confirmation by reference laboratories. PMID:29415432

Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata

USGS Publications Warehouse

Ringler, A.T.; Hutt, C.R.; Aster, R.; Bolton, H.; Gee, L.S.; Storm, T.

2012-01-01

Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).

The challenge of sustaining effectiveness over time: the case of the global network to stop tuberculosis.

PubMed

Quissell, Kathryn; Walt, Gill

2016-04-01

Where once global health decisions were largely the domain of national governments and the World Health Organization, today networks of international organizations, governments, private philanthropies and other entities are actively shaping public policy. However, there is still limited understanding of how global networks form, how they create institutions, how they promote and sustain collective action, and how they adapt to changes in the policy environment. Understanding these processes is crucial to understanding their effectiveness: whether and how global networks influence policy and public health outcomes. This study seeks to address these gaps through the examination of the global network to stop tuberculosis (TB) and the factors influencing its effectiveness over time. Drawing from ∼ 200 document sources and 16 interviews with key informants, we trace the development of the Global Partnership to Stop TB and its work over the past decade. We find that having a centralized core group and a strategic brand helped the network to coalesce around a primary intervention strategy, directly observed treatment short course. This strategy was created before the network was formalized, and helped bring in donors, ministries of health and other organizations committed to fighting TB-growing the network. Adaptations to this strategy, the creation of a consensus-based Global Plan, and the creation of a variety of participatory venues for discussion, helped to expand and sustain the network. Presently, however, tensions have become more apparent within the network as it struggles with changing internal political dynamics and the evolution of the disease. While centralization and stability helped to launch and grow the network, the institutionalization of governance and strategy may have constrained adaptation. Institutionalization and centralization may, therefore, facilitate short-term success for networks, but may end up complicating longer-term effectiveness. © Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2015; all rights reserved.

Global Efficiency of Structural Networks Mediates Cognitive Control in Mild Cognitive Impairment

PubMed Central

Berlot, Rok; Metzler-Baddeley, Claudia; Ikram, M. Arfan; Jones, Derek K.; O’Sullivan, Michael J.

2016-01-01

Background: Cognitive control has been linked to both the microstructure of individual tracts and the structure of whole-brain networks, but their relative contributions in health and disease remain unclear. Objective: To determine the contribution of both localized white matter tract damage and disruption of global network architecture to cognitive control, in older age and Mild Cognitive Impairment (MCI). Materials and Methods: Twenty-five patients with MCI and 20 age, sex, and intelligence-matched healthy volunteers were investigated with 3 Tesla structural magnetic resonance imaging (MRI). Cognitive control and episodic memory were evaluated with established tests. Structural network graphs were constructed from diffusion MRI-based whole-brain tractography. Their global measures were calculated using graph theory. Regression models utilized both global network metrics and microstructure of specific connections, known to be critical for each domain, to predict cognitive scores. Results: Global efficiency and the mean clustering coefficient of networks were reduced in MCI. Cognitive control was associated with global network topology. Episodic memory, in contrast, correlated with individual temporal tracts only. Relationships between cognitive control and network topology were attenuated by addition of single tract measures to regression models, consistent with a partial mediation effect. The mediation effect was stronger in MCI than healthy volunteers, explaining 23-36% of the effect of cingulum microstructure on cognitive control performance. Network clustering was a significant mediator in the relationship between tract microstructure and cognitive control in both groups. Conclusion: The status of critical connections and large-scale network topology are both important for maintenance of cognitive control in MCI. Mediation via large-scale networks is more important in patients with MCI than healthy volunteers. This effect is domain-specific, and true for cognitive control but not for episodic memory. Interventions to improve cognitive control will need to address both dysfunction of local circuitry and global network architecture to be maximally effective. PMID:28018208

Optimal percolation on multiplex networks.

PubMed

Osat, Saeed; Faqeeh, Ali; Radicchi, Filippo

2017-11-16

Optimal percolation is the problem of finding the minimal set of nodes whose removal from a network fragments the system into non-extensive disconnected clusters. The solution to this problem is important for strategies of immunization in disease spreading, and influence maximization in opinion dynamics. Optimal percolation has received considerable attention in the context of isolated networks. However, its generalization to multiplex networks has not yet been considered. Here we show that approximating the solution of the optimal percolation problem on a multiplex network with solutions valid for single-layer networks extracted from the multiplex may have serious consequences in the characterization of the true robustness of the system. We reach this conclusion by extending many of the methods for finding approximate solutions of the optimal percolation problem from single-layer to multiplex networks, and performing a systematic analysis on synthetic and real-world multiplex networks.

Quantitative evaluation of simulated functional brain networks in graph theoretical analysis.

PubMed

Lee, Won Hee; Bullmore, Ed; Frangou, Sophia

2017-02-01

There is increasing interest in the potential of whole-brain computational models to provide mechanistic insights into resting-state brain networks. It is therefore important to determine the degree to which computational models reproduce the topological features of empirical functional brain networks. We used empirical connectivity data derived from diffusion spectrum and resting-state functional magnetic resonance imaging data from healthy individuals. Empirical and simulated functional networks, constrained by structural connectivity, were defined based on 66 brain anatomical regions (nodes). Simulated functional data were generated using the Kuramoto model in which each anatomical region acts as a phase oscillator. Network topology was studied using graph theory in the empirical and simulated data. The difference (relative error) between graph theory measures derived from empirical and simulated data was then estimated. We found that simulated data can be used with confidence to model graph measures of global network organization at different dynamic states and highlight the sensitive dependence of the solutions obtained in simulated data on the specified connection densities. This study provides a method for the quantitative evaluation and external validation of graph theory metrics derived from simulated data that can be used to inform future study designs. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-12-01

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

Organic pollution of rivers: Combined threats of urbanization, livestock farming and global climate change

NASA Astrophysics Data System (ADS)

Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick

2017-02-01

Organic pollution of rivers by wastewater discharge from human activities negatively impacts people and ecosystems. Without treatment, pollution control relies on a combination of natural degradation and dilution by natural runoff to reduce downstream effects. We quantify here for the first time the global sanitation crisis through its impact on organic river pollution from the threats of (1) increasing wastewater discharge due to urbanization and intensification of livestock farming, and (2) reductions in river dilution capacity due to climate change and water extractions. Using in-stream Biochemical Oxygen Demand (BOD) as an overall indicator of organic river pollution, we calculate historical (2000) and future (2050) BOD concentrations in global river networks. Despite significant self-cleaning capacities of rivers, the number of people affected by organic pollution (BOD >5 mg/l) is projected to increase from 1.1 billion in 2000 to 2.5 billion in 2050. With developing countries disproportionately affected, our results point to a growing need for affordable wastewater solutions.

Organic pollution of rivers: Combined threats of urbanization, livestock farming and global climate change.

PubMed

Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick

2017-02-23

Organic pollution of rivers by wastewater discharge from human activities negatively impacts people and ecosystems. Without treatment, pollution control relies on a combination of natural degradation and dilution by natural runoff to reduce downstream effects. We quantify here for the first time the global sanitation crisis through its impact on organic river pollution from the threats of (1) increasing wastewater discharge due to urbanization and intensification of livestock farming, and (2) reductions in river dilution capacity due to climate change and water extractions. Using in-stream Biochemical Oxygen Demand (BOD) as an overall indicator of organic river pollution, we calculate historical (2000) and future (2050) BOD concentrations in global river networks. Despite significant self-cleaning capacities of rivers, the number of people affected by organic pollution (BOD >5 mg/l) is projected to increase from 1.1 billion in 2000 to 2.5 billion in 2050. With developing countries disproportionately affected, our results point to a growing need for affordable wastewater solutions.

Global positioning method based on polarized light compass system

NASA Astrophysics Data System (ADS)

Liu, Jun; Yang, Jiangtao; Wang, Yubo; Tang, Jun; Shen, Chong

2018-05-01

This paper presents a global positioning method based on a polarized light compass system. A main limitation of polarization positioning is the environment such as weak and locally destroyed polarization environments, and the solution to the positioning problem is given in this paper which is polarization image de-noising and segmentation. Therefore, the pulse coupled neural network is employed for enhancing positioning performance. The prominent advantages of the present positioning technique are as follows: (i) compared to the existing position method based on polarized light, better sun tracking accuracy can be achieved and (ii) the robustness and accuracy of positioning under weak and locally destroyed polarization environments, such as cloudy or building shielding, are improved significantly. Finally, some field experiments are given to demonstrate the effectiveness and applicability of the proposed global positioning technique. The experiments have shown that our proposed method outperforms the conventional polarization positioning method, the real time longitude and latitude with accuracy up to 0.0461° and 0.0911°, respectively.

Organic pollution of rivers: Combined threats of urbanization, livestock farming and global climate change

PubMed Central

Wen, Yingrong; Schoups, Gerrit; van de Giesen, Nick

2017-01-01

Organic pollution of rivers by wastewater discharge from human activities negatively impacts people and ecosystems. Without treatment, pollution control relies on a combination of natural degradation and dilution by natural runoff to reduce downstream effects. We quantify here for the first time the global sanitation crisis through its impact on organic river pollution from the threats of (1) increasing wastewater discharge due to urbanization and intensification of livestock farming, and (2) reductions in river dilution capacity due to climate change and water extractions. Using in-stream Biochemical Oxygen Demand (BOD) as an overall indicator of organic river pollution, we calculate historical (2000) and future (2050) BOD concentrations in global river networks. Despite significant self-cleaning capacities of rivers, the number of people affected by organic pollution (BOD >5 mg/l) is projected to increase from 1.1 billion in 2000 to 2.5 billion in 2050. With developing countries disproportionately affected, our results point to a growing need for affordable wastewater solutions. PMID:28230079

Link-prediction to tackle the boundary specification problem in social network surveys

PubMed Central

De Wilde, Philippe; Buarque de Lima-Neto, Fernando

2017-01-01

Diffusion processes in social networks often cause the emergence of global phenomena from individual behavior within a society. The study of those global phenomena and the simulation of those diffusion processes frequently require a good model of the global network. However, survey data and data from online sources are often restricted to single social groups or features, such as age groups, single schools, companies, or interest groups. Hence, a modeling approach is required that extrapolates the locally restricted data to a global network model. We tackle this Missing Data Problem using Link-Prediction techniques from social network research, network generation techniques from the area of Social Simulation, as well as a combination of both. We found that techniques employing less information may be more adequate to solve this problem, especially when data granularity is an issue. We validated the network models created with our techniques on a number of real-world networks, investigating degree distributions as well as the likelihood of links given the geographical distance between two nodes. PMID:28426826

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Development of a Low Cost Microcontroller-Enabled Handheld Sunphotometer and Comparison with NASA AERONET and MODIS

NASA Astrophysics Data System (ADS)

Krintz, I. A.; Ruble, W.; Sherman, J. P.

2017-12-01

Satellite-based measurements of aerosol optical depth (AOD), such as those made by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the TERRA and AQUA spacecraft, are often used in studies of aerosol direct radiative forcing (DRF) on regional to global scales due to daily near-global coverage. However, these measurements require validation by ground-based instrumentation, which is limited due to the cost of research-grade instrumentation. Furthermore, satellite-based AOD agreement with "ground-truth" instruments is weaker over mountainous regions (Levy et al., 2010). To aid in satellite validation, a low cost handheld sunphotometer has been developed which will be suitable for deployment to multiple sites to form a citizen science network as part of an upcoming proposal. A microcontroller, along with temperature and pressure sensors, has been included in this design to ease the process of taking measurements and transferring data for processing. Although LED-based sunphotometers have been used for a number of years (Brooks and Mims, 2001), this design uses filtered photodiodes which appear to have less of a temperature dependence. The interface has been designed to be intuitive to citizen scientists of all ages, nationalities, and backgrounds, so that deployment to primary schools and international sites will be as seamless as possible. Presented here is the instrument design, as well as initial results of a comparison with NASA Aerosol Robotic Network (AERONET) and MODIS-measured AOD. Future revisions to the instrument design, such as incorporation of surface-mount devices to cut down on circuit board size, will allow for an even smaller and more cost effective solution suitable for a global sunphotometer network.

GLOBAL SOLUTIONS TO FOLDED CONCAVE PENALIZED NONCONVEX LEARNING

PubMed Central

Liu, Hongcheng; Yao, Tao; Li, Runze

2015-01-01

This paper is concerned with solving nonconvex learning problems with folded concave penalty. Despite that their global solutions entail desirable statistical properties, there lack optimization techniques that guarantee global optimality in a general setting. In this paper, we show that a class of nonconvex learning problems are equivalent to general quadratic programs. This equivalence facilitates us in developing mixed integer linear programming reformulations, which admit finite algorithms that find a provably global optimal solution. We refer to this reformulation-based technique as the mixed integer programming-based global optimization (MIPGO). To our knowledge, this is the first global optimization scheme with a theoretical guarantee for folded concave penalized nonconvex learning with the SCAD penalty (Fan and Li, 2001) and the MCP penalty (Zhang, 2010). Numerical results indicate a significant outperformance of MIPGO over the state-of-the-art solution scheme, local linear approximation, and other alternative solution techniques in literature in terms of solution quality. PMID:27141126

ISKANDARnet IOMOS: Near real-time equatorial space weather monitoring and alert system in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Musa, Tajul Ariffin; Leong, Shien Kwun; Abdullah, Khairul Anuar; Othman, Rusli

2012-11-01

This work proposes ISKANDARnet Ionospheric Outburst MOnitoring and alert System (IOMOS), along with Ionospheric Outburst Index (IOX) to develop an operational near real-time space weather service for Malaysia. The IOMOS is based on Global Positioning System (GPS) Network-based Real-Time Kinematic (NRTK) concept which is by nature for atmospheric (ionosphere and troposphere) modeling within the network coverage. The elegance of this solution lies in the fact that IOMOS utilize differential ionospheric residual from network of GPS baselines which incur no additional cost for operation. Users will be informed about the ionospheric perturbation through Short Message Service (SMS), email or Twitter®. This approach will ultimately beneficial for the navigation and satellite positioning communities, particularly during the coming Solar Cycle 24. In addition, a combination of local and global GPS network has been employed to study the equatorial ionosphere geomorphology and climatology in the Malaysian sector. Equatorial Total Electron Content (TEC) over Malaysia shows semi-annual, annual, and seasonal variations with maximum values appearing during equinoctial months and minimum during solstices months. The TEC value during vernal equinox is about 21% higher than autumnal equinox, and December solstice exceeds that at the June solstice by around 14%. It is also found that semi-annual variation is present at all levels of solar activity, whereas June solstice predominates December solstice during high solar activity for annual and seasonal variations. In near future, a near real-time TEC derivation system will be developed to support equatorial ionosphere modeling to enhance space weather service for Malaysia.

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2013-07-12

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Advanced Algorithms for Local Routing Strategy on Complex Networks

PubMed Central

Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K.; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

2016-01-01

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks. PMID:27434502

Advanced Algorithms for Local Routing Strategy on Complex Networks.

PubMed

Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

2016-01-01

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70-90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks.

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

PubMed

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations.

Impact of centrality on cooperative processes

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Herrmann, Sebastian; Fontanari, José F.

2017-02-01

The solution of today's complex problems requires the grouping of task forces whose members are usually connected remotely over long physical distances and different time zones. Hence, understanding the effects of imposed communication patterns (i.e., who can communicate with whom) on group performance is important. Here we use an agent-based model to explore the influence of the betweenness centrality of the nodes on the time the group requires to find the global maxima of NK-fitness landscapes. The agents cooperate by broadcasting messages, informing on their fitness to their neighbors, and use this information to copy the more successful agents in their neighborhood. We find that for easy tasks (smooth landscapes), the topology of the communication network has no effect on the performance of the group, and that the more central nodes are the most likely to find the global maximum first. For difficult tasks (rugged landscapes), however, we find a positive correlation between the variance of the betweenness among the network nodes and the group performance. For these tasks, the performances of individual nodes are strongly influenced by the agents' dispositions to cooperate and by the particular realizations of the rugged landscapes.

The Worldviews Network: Innovative Strategies for Increasing Climate and Ecological Literacy in Your Community

NASA Astrophysics Data System (ADS)

Connolly, R.; Yu, K.; McConville, D.; Sickler, J.; "Irving, Lindsay", L. S.; Gardiner, N.; Hamilton, H.

2011-12-01

Informal science Institutions (ISI) are in the unique position to convene and support community dialogues surrounding local ecological impacts of global change. The Worldviews Network-a collaboration between museums, scientists, and community-based organizations-is developing and testing innovative approaches for promoting and encouraging ecological literacy with the American public. In this session, we will share strategies for sparking and sustaining dialogue and action in local communities through high-impact visual presentations and real-world examples of successful projects that are increasing the healthy functioning of regional and global ecosystems. Educating the public about interconnected global change issues can be a daunting task. ISIs can help communities by facilitating dialogues about realistic and regionally relevant approaches for systemically addressing global challenges. Managing the complexity of these challenges requires going far beyond the standard prescriptions for behavior change; it requires inspiring participants with positive examples of system-wide solutions as well as actively involving the audience in scientifically informed design processes. This session will demonstrate how you can implement and sustain these community dialogues, using real-world examples from our partners' national events. We present visualization story templates and a model for facilitating dialogues that can be adapted at your institution. Based on video and written assessment feedback from visitors of our first Worldviews events, we will present initial evaluation findings about the impact that these strategies are having on our audiences and ISI partners. These findings show that engaging the public and NGO partners in sustainability and design dialogues is a powerful way to maintain the relevance of ISIs within their communities.

Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI.

PubMed

Wong, Chi Wah; Olafsson, Valur; Tal, Omer; Liu, Thomas T

2012-10-15

Resting-state functional connectivity magnetic resonance imaging is proving to be an essential tool for the characterization of functional networks in the brain. Two of the major networks that have been identified are the default mode network (DMN) and the task positive network (TPN). Although prior work indicates that these two networks are anti-correlated, the findings are controversial because the anti-correlations are often found only after the application of a pre-processing step, known as global signal regression, that can produce artifactual anti-correlations. In this paper, we show that, for subjects studied in an eyes-closed rest state, caffeine can significantly enhance the detection of anti-correlations between the DMN and TPN without the need for global signal regression. In line with these findings, we find that caffeine also leads to widespread decreases in connectivity and global signal amplitude. Using a recently introduced geometric model of global signal effects, we demonstrate that these decreases are consistent with the removal of an additive global signal confound. In contrast to the effects observed in the eyes-closed rest state, caffeine did not lead to significant changes in global functional connectivity in the eyes-open rest state. Copyright © 2012 Elsevier Inc. All rights reserved.

Increasing Susceptibility of the Global Network of Food Trade to Climate Disturbances

NASA Astrophysics Data System (ADS)

Puma, M. J.; Bose, S.; Chon, S.; Cook, B.

2013-12-01

Globalization of agriculture through trade liberalization has led to a dramatic transformation of the global network of food trade. The many benefits of this globalization include greater and more efficient global agricultural production, reduced variability of regional and global food supplies, and savings in global water resources. However, a potential hidden cost is an increasingly fragile network that is more susceptible to shocks or disruptions. Recent studies suggest that complex systems, like the global food trade network, may have architectural features typically associated with the existence of tipping points and susceptibility to collapse. Here we present evidence that this global agricultural network is increasingly connected, homogeneous, and in a state where network nodes (here countries) can flip between alternate states. We use production and trade data from 1986 to 2009 to identify shifts in national self sufficiency and to quantify changes in connectivity and homogeneity of the wheat, maize and rice trade. We then simulate the possible impacts of climate and crop-disease disruptions, which could potentially trigger a global food crisis through an export-restriction-induced domino effect. Changes in self-sufficiency ratio (SSR) over time for various country groups. The SSR is computed based on production and trade of cereals and starchy roots. (Top row) Time series of SSR for the Group of Eight + Five (G8+5) countries. The '+ Five' refers to the five leading emerging economies in the world. (Bottom row) Boxplots of average SSR over two periods (1986-1990 and 2005-2009) for countries designated as 'Annex I' and 'Least Developed Countries' (LDC) by the United Nations.

A connectionist model for diagnostic problem solving

NASA Technical Reports Server (NTRS)

Peng, Yun; Reggia, James A.

1989-01-01

A competition-based connectionist model for solving diagnostic problems is described. The problems considered are computationally difficult in that (1) multiple disorders may occur simultaneously and (2) a global optimum in the space exponential to the total number of possible disorders is sought as a solution. The diagnostic problem is treated as a nonlinear optimization problem, and global optimization criteria are decomposed into local criteria governing node activation updating in the connectionist model. Nodes representing disorders compete with each other to account for each individual manifestation, yet complement each other to account for all manifestations through parallel node interactions. When equilibrium is reached, the network settles into a locally optimal state. Three randomly generated examples of diagnostic problems, each of which has 1024 cases, were tested, and the decomposition plus competition plus resettling approach yielded very high accuracy.

Report of the panel on plate motion and deformation, section 2

NASA Technical Reports Server (NTRS)

Bock, Yehuda; Kastens, Kim A.; Mcnutt, Marcia K.; Minster, J. Bernard; Peltzer, Gilles; Prescott, William H.; Reilinger, Robert E.; Royden, Leigh; Rundle, John B.; Sauber, Jeanne M.

1991-01-01

Given here is a panel report on the goals and objectives, requirements and recommendations for the investigation of plate motion and deformation. The goals are to refine our knowledge of plate motions, study regional and local deformation, and contribute to the solution of important societal problems. The requirements include basic space-positioning measurements, the use of global and regional data sets obtained with space-based techniques, topographic and geoid data to help characterize the internal processes that shape the planet, gravity data to study the density structure at depth and help determine the driving mechanisms for plate tectonics, and satellite images to map lithology, structure and morphology. The most important recommendation of the panel is for the implementation of a world-wide space-geodetic fiducial network to provide a systematic and uniform measure of global strain.

Optimization of wireless Bluetooth sensor systems.

PubMed

Lonnblad, J; Castano, J; Ekstrom, M; Linden, M; Backlund, Y

2004-01-01

Within this study, three different Bluetooth sensor systems, replacing cables for transmission of biomedical sensor data, have been designed and evaluated. The three sensor architectures are built on 1-, 2- and 3-chip solutions and depending on the monitoring situation and signal character, different solutions are optimal. Essential parameters for all systems have been low physical weight and small size, resistance to interference and interoperability with other technologies as global- or local networks, PC's and mobile phones. Two different biomedical input signals, ECG and PPG (photoplethysmography), have been used to evaluate the three solutions. The study shows that it is possibly to continuously transmit an analogue signal. At low sampling rates and slowly varying parameters, as monitoring the heart rate with PPG, the 1-chip solution is the most suitable, offering low power consumption and thus a longer battery lifetime or a smaller battery, minimizing the weight of the sensor system. On the other hand, when a higher sampling rate is required, as an ECG, the 3-chip architecture, with a FPGA or micro-controller, offers the best solution and performance. Our conclusion is that Bluetooth might be useful in replacing cables of medical monitoring systems.

The Complexity of Dynamics in Small Neural Circuits

PubMed Central

Panzeri, Stefano

2016-01-01

Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

PubMed Central

Murphy, Kevin; Birn, Rasmus M.; Handwerker, Daniel A.; Jones, Tyler B.; Bandettini, Peter A.

2009-01-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step. PMID:18976716

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

PubMed

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

An update to the analysis of the Canadian Spatial Reference System

NASA Astrophysics Data System (ADS)

Ferland, R.; Piraszewski, M.; Craymer, M.

2015-12-01

The primary objective of the Canadian Spatial Reference System (CSRS) is to provide users access to a consistent geo-referencing infrastructure over the Canadian landmass. Global Navigation Satellite System (GNSS) positioning accuracy requirements ranges from meter level to mm level (e.g.: crustal deformation). The highest level of the Canadian infrastructure consist of a network of continually operating GPS and GNSS receivers, referred to as active control stations. The network includes all Canadian public active control stations, some bordering US CORS and Alaska stations, Greenland active control stations, as well as a selection of IGS reference frame stations. The Bernese analysis software is used for the daily processing and the combination into weekly solutions which form the basis for this analysis. IGS weekly final orbit, Earth Rotation parameters (ERP's) and coordinates products are used in the processing. For the more demanding users, the time dependant changes of station coordinates is often more important.All station coordinate estimates and related covariance information is used in this analysis. For each input solution, variance factor, translation, rotation and scale (and if needed their rates) or subsets of these are estimated. In the combination of these weekly solutions, station positions and velocities are estimated. Since the time series from the stations in these networks often experience changes in behavior, new (or reuse of) parameters are generally used in these situations. As is often the case with real data, unrealistic coordinates may occur. Automatic detection and removal of outliers is used in these cases. For the transformation, position and velocity parameters loose apriori estimates and uncertainties are provided. Alignment using the usual Helmert transformation to the latest IGb08 realization of ITRF is also performed during the adjustment.

New results on global exponential dissipativity analysis of memristive inertial neural networks with distributed time-varying delays.

PubMed

Zhang, Guodong; Zeng, Zhigang; Hu, Junhao

2018-01-01

This paper is concerned with the global exponential dissipativity of memristive inertial neural networks with discrete and distributed time-varying delays. By constructing appropriate Lyapunov-Krasovskii functionals, some new sufficient conditions ensuring global exponential dissipativity of memristive inertial neural networks are derived. Moreover, the globally exponential attractive sets and positive invariant sets are also presented here. In addition, the new proposed results here complement and extend the earlier publications on conventional or memristive neural network dynamical systems. Finally, numerical simulations are given to illustrate the effectiveness of obtained results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

PubMed Central

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific preprocessing choices on both the global and nodal topological properties of functional brain networks. This study also has important implications for how to choose reliable analytical schemes in brain network studies. PMID:22412922

Location Management in a Transport Layer Mobility Architecture

NASA Technical Reports Server (NTRS)

Eddy, Wesley M.; Ishac, Joseph

2005-01-01

Mobility architectures that place complexity in end nodes rather than in the network interior have many advantageous properties and are becoming popular research topics. Such architectures typically push mobility support into higher layers of the protocol stack than network layer approaches like Mobile IP. The literature is ripe with proposals to provide mobility services in the transport, session, and application layers. In this paper, we focus on a mobility architecture that makes the most significant changes to the transport layer. A common problem amongst all mobility protocols at various layers is location management, which entails translating some form of static identifier into a mobile node's dynamic location. Location management is required for mobile nodes to be able to provide globally-reachable services on-demand to other hosts. In this paper, we describe the challenges of location management in a transport layer mobility architecture, and discuss the advantages and disadvantages of various solutions proposed in the literature. Our conclusion is that, in principle, secure dynamic DNS is most desirable, although it may have current operational limitations. We note that this topic has room for further exploration, and we present this paper largely as a starting point for comparing possible solutions.

Networking: the view from HEP

NASA Astrophysics Data System (ADS)

McKee, Shawn

2017-10-01

Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. National and global-scale collaborations that characterize HEP would not be feasible without ubiquitous capable networks. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. This paper will briefly discuss the history of networking in HEP, the current activities and challenges we are facing, and try to provide some understanding of where networking may be going in the next 5 to 10 years.

The effect of tracking network configuration on GPS baseline estimates for the CASA Uno experiment

NASA Technical Reports Server (NTRS)

Wolf, S. Kornreich; Dixon, T. H.; Freymueller, J. T.

1990-01-01

The effect of the tracking network on long (greater than 100 km) GPS baseline estimates was estimated using various subsets of the global tracking network initiated by the first Central and South America (CASA Uno) experiment. It was found that best results could be obtained with a global tacking network consisting of three U.S. stations, two sites in the southwestern Pacific, and two sites in Europe. In comparison with smaller subsets, this global network improved the baseline repeatability, the resolution of carrier phase cycle ambiguities, and formal errors of the orbit estimates.

Bayesian networks in overlay recipe optimization

NASA Astrophysics Data System (ADS)

Binns, Lewis A.; Reynolds, Greg; Rigden, Timothy C.; Watkins, Stephen; Soroka, Andrew

2005-05-01

Currently, overlay measurements are characterized by "recipe", which defines both physical parameters such as focus, illumination et cetera, and also the software parameters such as algorithm to be used and regions of interest. Setting up these recipes requires both engineering time and wafer availability on an overlay tool, so reducing these requirements will result in higher tool productivity. One of the significant challenges to automating this process is that the parameters are highly and complexly correlated. At the same time, a high level of traceability and transparency is required in the recipe creation process, so a technique that maintains its decisions in terms of well defined physical parameters is desirable. Running time should be short, given the system (automatic recipe creation) is being implemented to reduce overheads. Finally, a failure of the system to determine acceptable parameters should be obvious, so a certainty metric is also desirable. The complex, nonlinear interactions make solution by an expert system difficult at best, especially in the verification of the resulting decision network. The transparency requirements tend to preclude classical neural networks and similar techniques. Genetic algorithms and other "global minimization" techniques require too much computational power (given system footprint and cost requirements). A Bayesian network, however, provides a solution to these requirements. Such a network, with appropriate priors, can be used during recipe creation / optimization not just to select a good set of parameters, but also to guide the direction of search, by evaluating the network state while only incomplete information is available. As a Bayesian network maintains an estimate of the probability distribution of nodal values, a maximum-entropy approach can be utilized to obtain a working recipe in a minimum or near-minimum number of steps. In this paper we discuss the potential use of a Bayesian network in such a capacity, reducing the amount of engineering intervention. We discuss the benefits of this approach, especially improved repeatability and traceability of the learning process, and quantification of uncertainty in decisions made. We also consider the problems associated with this approach, especially in detailed construction of network topology, validation of the Bayesian network and the recipes it generates, and issues arising from the integration of a Bayesian network with a complex multithreaded application; these primarily relate to maintaining Bayesian network and system architecture integrity.

Environmental monitoring network for India

Treesearch

P.V. Sundareshwar; R. Murtugudde; G. Srinivasan; S. Singh; K.J. Ramesh; R. Ramesh; S.B. Verma; D. Agarwal; D. Baldocchi; C.K. Baru; K.K. Baruah; G.R. Chowdhury; V.K. Dadhwal; C.B.S. Dutt; J. Fuentes; Prabhat Gupta; W.W. Hardgrove; M. Howard; C.S. Jha; S. Lal; W.K. Michener; A.P. Mitra; J.T. Morris; R.R. Myneni; M. Naja; R. Nemani; R. Purvaja; S. Raha; S.K. Santhana Vanan; M. Sharma; A. Subramaniam; R. Sukumar; R.R. Twilley; P.R. Zimmerman

2007-01-01

Understanding the consequences of global environmental change and its mitigation will require an integrated global effort of comprehensive long-term data collection, synthesis, and action (1). The last decade has seen a dramatic global increase in the number of networked monitoring sites. For example, FLUXNET is a global collection of >300 micrometeorological...

Satellite Communications for Aeronautical Applications: Recent research and Development Results

NASA Technical Reports Server (NTRS)

Kerczewski, Robert J.

2001-01-01

Communications systems have always been a critical element in aviation. Until recently, nearly all communications between the ground and aircraft have been based on analog voice technology. But the future of global aviation requires a more sophisticated "information infrastructure" which not only provides more and better communications, but integrates the key information functions (communications, navigation, and surveillance) into a modern, network-based infrastructure. Satellite communications will play an increasing role in providing information infrastructure solutions for aviation. Developing and adapting satellite communications technologies for aviation use is now receiving increased attention as the urgency to develop information infrastructure solutions grows. The NASA Glenn Research Center is actively involved in research and development activities for aeronautical satellite communications, with a key emphasis on air traffic management communications needs. This paper describes the recent results and status of NASA Glenn's research program.

Photovoltaic Inverter Controllers Seeking AC Optimal Power Flow Solutions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

This paper considers future distribution networks featuring inverter-interfaced photovoltaic (PV) systems, and addresses the synthesis of feedback controllers that seek real- and reactive-power inverter setpoints corresponding to AC optimal power flow (OPF) solutions. The objective is to bridge the temporal gap between long-term system optimization and real-time inverter control, and enable seamless PV-owner participation without compromising system efficiency and stability. The design of the controllers is grounded on a dual ..epsilon..-subgradient method, while semidefinite programming relaxations are advocated to bypass the non-convexity of AC OPF formulations. Global convergence of inverter output powers is analytically established for diminishing stepsize rules formore » cases where: i) computational limits dictate asynchronous updates of the controller signals, and ii) inverter reference inputs may be updated at a faster rate than the power-output settling time.« less

W phase source inversion for moderate to large earthquakes (1990-2010)

USGS Publications Warehouse

Duputel, Zacharie; Rivera, Luis; Kanamori, Hiroo; Hayes, Gavin P.

2012-01-01

Rapid characterization of the earthquake source and of its effects is a growing field of interest. Until recently, it still took several hours to determine the first-order attributes of a great earthquake (e.g. Mw≥ 7.5), even in a well-instrumented region. The main limiting factors were data saturation, the interference of different phases and the time duration and spatial extent of the source rupture. To accelerate centroid moment tensor (CMT) determinations, we have developed a source inversion algorithm based on modelling of the W phase, a very long period phase (100–1000 s) arriving at the same time as the P wave. The purpose of this work is to finely tune and validate the algorithm for large-to-moderate-sized earthquakes using three components of W phase ground motion at teleseismic distances. To that end, the point source parameters of all Mw≥ 6.5 earthquakes that occurred between 1990 and 2010 (815 events) are determined using Federation of Digital Seismograph Networks, Global Seismographic Network broad-band stations and STS1 global virtual networks of the Incorporated Research Institutions for Seismology Data Management Center. For each event, a preliminary magnitude obtained from W phase amplitudes is used to estimate the initial moment rate function half duration and to define the corner frequencies of the passband filter that will be applied to the waveforms. Starting from these initial parameters, the seismic moment tensor is calculated using a preliminary location as a first approximation of the centroid. A full CMT inversion is then conducted for centroid timing and location determination. Comparisons with Harvard and Global CMT solutions highlight the robustness of W phase CMT solutions at teleseismic distances. The differences in Mw rarely exceed 0.2 and the source mechanisms are very similar to one another. Difficulties arise when a target earthquake is shortly (e.g. within 10 hr) preceded by another large earthquake, which disturbs the waveforms of the target event. To deal with such difficult situations, we remove the perturbation caused by earlier disturbing events by subtracting the corresponding synthetics from the data. The CMT parameters for the disturbed event can then be retrieved using the residual seismograms. We also explore the feasibility of obtaining source parameters of smaller earthquakes in the range 6.0 ≤Mw w= 6 or larger.

Verification of the Usefulness of the Trimble Rtx Extended Satellite Technology with the Xfill Function in the Local Network Implementing Rtk Measurements

NASA Astrophysics Data System (ADS)

Siejka, Zbigniew

2014-12-01

The paper presents the method of satellite measurements, which gives users the ability of GNSS continuous precise positioning in real time, even in the case of short interruptions in receiving the correction of the local ground system of measurements support. The proposed method is a combination of two satellite positioning technologies RTN GNSS and RTX Extended. In technology RTX Extended the xFill function was used for precise positioning in real time and in the local reference system. This function provides the ability to perform measurement without the need for constant communication with the ground support satellite system. Test measurements were performed on a test basis located in Krakow, and RTN GNSS positioning was done based on the national network of reference stations of the ASGEUPOS. The solution allows for short (up to 5 minutes) interruptions in radio or internet communication. When the primary stream of RTN correction is not available, then the global corrections Trimble xFill broadcasted by satellite are used. The new technology uses in the real-time data from the global network of tracking stations and contributes significantly to improving the quality and efficiency of surveying works. At present according to the authors, technology Trimble CenterPoint RTX can guarantee repeatability of measurements not worse than 3.8 cm (Trimble Survey Division, 2012). In the paper the comparative analysis of measurement results between the two technologies was performed: RTN carried out in the classic way, which was based on the corrections of the terrestrial local network of the Polish system of active geodetic network (ASG-EUPOS) and RTK xFill technology. The results were related to the data of test network, established as error free. The research gave satisfactory results and confirmed the great potential of the use of the new technology in the geodetic work realization. By combining these two technologies of GNSS surveying the user can greatly improve the overall performance of real-time positioning.

Minimising food waste: a call for multidisciplinary research.

PubMed

Alamar, Maria Del Carmen; Falagán, Natalia; Aktas, Emel; Terry, Leon A

2018-01-01

Food losses and waste have always been a significant global problem for mankind, and one which has become increasingly recognised as such by policy makers, food producers, processors, retailers, and consumers. It is, however, an emotive subject whereby the extent, accuracy and resolution of available data on postharvest loss and waste are questionable, such that key performance indicators on waste can be misinformed. The nature and extent of food waste differ among developed economies, economies in transition and developing countries. While most emphasis has been put on increasing future crop production, far less resource has been and is still channelled towards enabling both established and innovative food preservation technologies to reduce food waste while maintaining safety and quality. Reducing food loss and waste is a more tractable problem than increasing production in the short to medium term, as its solution is not directly limited, for instance, by available land and water resources. Here we argue the need for a paradigm shift of current funding strategies and research programmes that will encourage the development, implementation and translation of collective biological, engineering and management solutions to better preserve and utilise food. Such multidisciplinary thinking across global supply chains is an essential element in the pursuit of achieving sustainable food and nutritional security. The implementation of allied technological and management solutions is reliant on there being sufficient skilled human capital and resources. There is currently a lack of robust postharvest research networks outside of the developed world, and insufficient global funding mechanisms that can support such interdisciplinary collaborations. There is, thus, a collective need for schemes that encourage inter-supply chain research, knowledge exchange and capacity building to reduce food losses and waste. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Global connectivity of prefrontal cortex predicts cognitive control and intelligence

PubMed Central

Cole, Michael W.; Yarkoni, Tal; Repovs, Grega; Anticevic, Alan; Braver, Todd S.

2012-01-01

Control of thought and behavior is fundamental to human intelligence. Evidence suggests a fronto-parietal brain network implements such cognitive control across diverse contexts. We identify a mechanism – global connectivity – by which components of this network might coordinate control of other networks. A lateral prefrontal cortex (LPFC) region’s activity was found to predict performance in a high control demand working memory task, and also to exhibit high global connectivity. Critically, global connectivity in this LPFC region, involving connections both within and outside the fronto-parietal network, showed a highly selective relationship with individual differences in fluid intelligence. These findings suggest LPFC is a global hub with a brain-wide influence that facilitates the ability to implement control processes central to human intelligence. PMID:22745498

Inequality measures perform differently in global and local assessments: An exploratory computational experiment

NASA Astrophysics Data System (ADS)

Chiang, Yen-Sheng

2015-11-01

Inequality measures are widely used in both the academia and public media to help us understand how incomes and wealth are distributed. They can be used to assess the distribution of a whole society-global inequality-as well as inequality of actors' referent networks-local inequality. How different is local inequality from global inequality? Formalizing the structure of reference groups as a network, the paper conducted a computational experiment to see how the structure of complex networks influences the difference between global and local inequality assessed by a selection of inequality measures. It was found that local inequality tends to be higher than global inequality when population size is large; network is dense and heterophilously assorted, and income distribution is less dispersed. The implications of the simulation findings are discussed.

The Global GNSS, SLR, VLBI, and DORIS Networks and their Support of GGOS: IGS+ILRS+IVS+IDS

NASA Technical Reports Server (NTRS)

Noll, Carey

2008-01-01

The global network of the International GNSS Service (IGS), the International Laser Ranging Service (ILRS), the International VLBI Service for Geodesy and Astrometry (IVS), and the International DORIS Service (IDS) are part of the ground-based infrastructure for GGOS. The observations obtained from these global networks provide for the determination and maintenance of the International Terrestrial Reference Frame (ITRF), an accurate set of positions and velocities that provides a stable coordinate system allowing scientists ts to link measurements over space and time. Many of these sites offer co-location of two or more techniques. Co-location provides integration of technique-specific networks into the ITRF as well as an assessment/validation of the quality and accuracy of the resulting measurements. As of fall 2008, these networks consisted of 410 GNSS sites, 42 laser ranging sites, 45 VLBI sites, and 58 DORIS sites. This poster will illustrate the global coverage of these networks, highlighting inter-technique co-locations, and show the importance of these networks 60 the underlying goals of GGOS including providing the observational basis to maintain a stable, accurate, global reference frame.

A graph decomposition-based approach for water distribution network optimization

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.; Deuerlein, Jochen W.

2013-04-01

A novel optimization approach for water distribution network design is proposed in this paper. Using graph theory algorithms, a full water network is first decomposed into different subnetworks based on the connectivity of the network's components. The original whole network is simplified to a directed augmented tree, in which the subnetworks are substituted by augmented nodes and directed links are created to connect them. Differential evolution (DE) is then employed to optimize each subnetwork based on the sequence specified by the assigned directed links in the augmented tree. Rather than optimizing the original network as a whole, the subnetworks are sequentially optimized by the DE algorithm. A solution choice table is established for each subnetwork (except for the subnetwork that includes a supply node) and the optimal solution of the original whole network is finally obtained by use of the solution choice tables. Furthermore, a preconditioning algorithm is applied to the subnetworks to produce an approximately optimal solution for the original whole network. This solution specifies promising regions for the final optimization algorithm to further optimize the subnetworks. Five water network case studies are used to demonstrate the effectiveness of the proposed optimization method. A standard DE algorithm (SDE) and a genetic algorithm (GA) are applied to each case study without network decomposition to enable a comparison with the proposed method. The results show that the proposed method consistently outperforms the SDE and GA (both with tuned parameters) in terms of both the solution quality and efficiency.

Analysis of inter-country input-output table based on citation network: How to measure the competition and collaboration between industrial sectors on the global value chain

PubMed Central

2017-01-01

The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization. PMID:28873432

Analysis of inter-country input-output table based on citation network: How to measure the competition and collaboration between industrial sectors on the global value chain.

PubMed

Xing, Lizhi

2017-01-01

The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization.

Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption

NASA Astrophysics Data System (ADS)

Wang, Rong; Andrews, Elisabeth; Balkanski, Yves; Boucher, Olivier; Myhre, Gunnar; Samset, Bjørn Hallvard; Schulz, Michael; Schuster, Gregory L.; Valari, Myrto; Tao, Shu

2018-02-01

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top-down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error.

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

PubMed

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

2016-04-01

Since 1990 mortality and morbidity decline has been more extensive for some conditions prevalent in low- and middle-income countries than for others. One reason may be differences in the effectiveness of global health networks, which have proliferated in recent years. Some may be more capable than others in attracting attention to a condition, in generating funding, in developing interventions and in convincing national governments to adopt policies. This article introduces a supplement on the emergence and effectiveness of global health networks. The supplement examines networks concerned with six global health problems: tuberculosis (TB), pneumonia, tobacco use, alcohol harm, maternal mortality and newborn deaths. This article presents a conceptual framework delineating factors that may shape why networks crystallize more easily surrounding some issues than others, and once formed, why some are better able than others to shape policy and public health outcomes. All supplement papers draw on this framework. The framework consists of 10 factors in three categories: (1) features of the networks and actors that comprise them, including leadership, governance arrangements, network composition and framing strategies; (2) conditions in the global policy environment, including potential allies and opponents, funding availability and global expectations concerning which issues should be prioritized; (3) and characteristics of the issue, including severity, tractability and affected groups. The article also explains the design of the project, which is grounded in comparison of networks surrounding three matched issues: TB and pneumonia, tobacco use and alcohol harm, and maternal and newborn survival. Despite similar burden and issue characteristics, there has been considerably greater policy traction for the first in each pair. The supplement articles aim to explain the role of networks in shaping these differences, and collectively represent the first comparative effort to understand the emergence and effectiveness of global health networks. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2015; all rights reserved.

Multicriteria hierarchical iterative interactive algorithm for organizing operational modes of large heat supply systems

NASA Astrophysics Data System (ADS)

Korotkova, T. I.; Popova, V. I.

2017-11-01

The generalized mathematical model of decision-making in the problem of planning and mode selection providing required heat loads in a large heat supply system is considered. The system is multilevel, decomposed into levels of main and distribution heating networks with intermediate control stages. Evaluation of the effectiveness, reliability and safety of such a complex system is carried out immediately according to several indicators, in particular pressure, flow, temperature. This global multicriteria optimization problem with constraints is decomposed into a number of local optimization problems and the coordination problem. An agreed solution of local problems provides a solution to the global multicriterion problem of decision making in a complex system. The choice of the optimum operational mode of operation of a complex heat supply system is made on the basis of the iterative coordination process, which converges to the coordinated solution of local optimization tasks. The interactive principle of multicriteria task decision-making includes, in particular, periodic adjustment adjustments, if necessary, guaranteeing optimal safety, reliability and efficiency of the system as a whole in the process of operation. The degree of accuracy of the solution, for example, the degree of deviation of the internal air temperature from the required value, can also be changed interactively. This allows to carry out adjustment activities in the best way and to improve the quality of heat supply to consumers. At the same time, an energy-saving task is being solved to determine the minimum required values of heads at sources and pumping stations.

Future global SLR network evolution and its impact on the terrestrial reference frame

NASA Astrophysics Data System (ADS)

Kehm, Alexander; Bloßfeld, Mathis; Pavlis, Erricos C.; Seitz, Florian

2018-06-01

Satellite laser ranging (SLR) is an important technique that contributes to the determination of terrestrial geodetic reference frames, especially to the realization of the origin and the scale of global networks. One of the major limiting factors of SLR-derived reference frame realizations is the datum accuracy which significantly suffers from the current global SLR station distribution. In this paper, the impact of a potential future development of the SLR network on the estimated datum parameters is investigated. The current status of the SLR network is compared to a simulated potential future network featuring additional stations improving the global network geometry. In addition, possible technical advancements resulting in a higher amount of observations are taken into account as well. As a result, we find that the network improvement causes a decrease in the scatter of the network translation parameters of up to 24%, and up to 20% for the scale, whereas the technological improvement causes a reduction in the scatter of up to 27% for the translations and up to 49% for the scale. The Earth orientation parameters benefit by up to 15% from both effects.

Hierarchicality of trade flow networks reveals complexity of products.

PubMed

Shi, Peiteng; Zhang, Jiang; Yang, Bo; Luo, Jingfei

2014-01-01

With globalization, countries are more connected than before by trading flows, which amounts to at least 36 trillion dollars today. Interestingly, around 30-60 percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent η can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely.

Lateral Prefrontal Cortex Contributes to Fluid Intelligence Through Multinetwork Connectivity.

PubMed

Cole, Michael W; Ito, Takuya; Braver, Todd S

2015-10-01

Our ability to effectively adapt to novel circumstances--as measured by general fluid intelligence--has recently been tied to the global connectivity of lateral prefrontal cortex (LPFC). Global connectivity is a broad measure that summarizes both within-network connectivity and across-network connectivity. We used additional graph theoretical measures to better characterize the nature of LPFC connectivity and its relationship with fluid intelligence. We specifically hypothesized that LPFC is a connector hub with an across-network connectivity that contributes to fluid intelligence independent of within-network connectivity. We verified that LPFC was in the top 10% of brain regions in terms of across-network connectivity, suggesting it is a strong connector hub. Importantly, we found that the LPFC across-network connectivity predicted individuals' fluid intelligence and this correlation remained statistically significant when controlling for global connectivity (which includes within-network connectivity). This supports the conclusion that across-network connectivity independently contributes to the relationship between LPFC connectivity and intelligence. These results suggest that LPFC contributes to fluid intelligence by being a connector hub with a truly global multisystem connectivity throughout the brain.

Hierarchicality of Trade Flow Networks Reveals Complexity of Products

PubMed Central

Shi, Peiteng; Zhang, Jiang; Yang, Bo; Luo, Jingfei

2014-01-01

With globalization, countries are more connected than before by trading flows, which amounts to at least trillion dollars today. Interestingly, around percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely. PMID:24905753

Studies on spatio-temporal filtering of GNSS-derived coordinates

NASA Astrophysics Data System (ADS)

Gruszczynski, Maciej; Bogusz, Janusz; Kłos, Anna; Figurski, Mariusz

2015-04-01

The information about lithospheric deformations may be obtained nowadays by analysis of velocity field derived from permanent GNSS (Global Navigation Satellite System) observations. Despite developing more and more reliable models, the permanent stations residuals must still be considered as coloured noise. Meeting the GGOS (Global Geodetic Observing System) requirements, we are obliged to investigate the correlations between residuals, which are the result of common mode error (CME). This type of error may arise from mismodelling of: satellite orbits, the Earth Orientation Parameters, satellite antenna phase centre variations or unmodelling of large scale atmospheric effects. The above described together cause correlations between stochastic parts of coordinate time series obtained at stations located of even few thousands kilometres from each other. Permanent stations that meet the aforementioned terms form the regional (EPN - EUREF Permanent Network) or local sub-networks of global (IGS - International GNSS Service) network. Other authors (Wdowinski et al., 1997; Dong et al., 2006) dealt with spatio-temporal filtering and indicated three major regional filtering approaches: the stacking, the Principal Component Analysis (PCA) based on the empirical orthogonal function and the Karhunen-Loeve expansion. The need for spatio-temporal filtering is evident today, but the question whether the size of the network affects the accuracy of station's position and its velocity still remains unanswered. With the aim to determine the network's size, for which the assumption of spatial uniform distribution of CME is retained, we used stacking approach. We analyzed time series of IGS stations with daily network solutions processed by the Military University of Technology EPN Local Analysis Centre in Bernese 5.0 software and compared it with the JPL (Jet Propulsion Laboratory) PPP (Precice Point Positioning). The method we propose is based on the division of local GNSS networks into concentric ring-shaped areas. Such an approach allows us to specify the maximum size of the network, where the evident uniform spatial response can be still noticed. In terms of reliable CMEs extraction, the local networks have to be up to 500-600 kilometres extent depending on its character (location). In this study we examined three approaches of spatio-temporal filtering based on stacking procedure. First was based on non-weighted (Wdowinski et. al., 1997) and second on weighted average formula, where the weights are formed by the RMS of individual station position in the corresponding epoch (Nikolaidis, 2002). The third stacking approach, proposed here, was previously unused. It combines the weighted stacking together with the distance between the station and network barycentre into one approach. The analysis allowed to determine the optimal size of local GNSS network and to select the appropriate stacking method for obtaining the most stable solutions for e.g. geodynamical studies. The values of L1 and L2 norms, RMS values of time series (describing stability of the time series) and Pearson correlation coefficients were calculated for the North, East and Up components from more than 200 permanent stations twice: before performing the filtration and after weighted stacking approach. We showed the improvement in the quality of time series analysis using MLE (Maximum Likelihood Estimation) to estimate noise parameters. We demonstrated that the relative RMS improvement of 10, 20 and 30% reduces the noise amplitudes of about 20, 35 and 45%, respectively, what causes the velocity uncertainty to be reduced of 0.3 mm/yr (for the assumption of 7-years of data and flicker noise). The relative decrement of spectral index kappa is 25, 35 and 45%, what means lower velocity uncertainty of even 0.2 mm/yr (when assuming 7 years of data and noise amplitude of 15 mm/yr^-kappa/4) . These results refer to the growing demands on the stability of the series due to their use to realize the kinematic reference frames and for geodynamical studies.

Structure and Controls of the Global Virtual Water Trade Network

NASA Astrophysics Data System (ADS)

Suweis, S. S.

2011-12-01

Recurrent or ephemeral water shortages are a crucial global challenge, in particular because of their impacts on food production. The global character of this challenge is reflected in the trade among nations of virtual water, i.e. the amount of water used to produce a given commodity. We build, analyze and model the network describing the transfer of virtual water between world nations for staple food products. We find that all the key features of the network are well described by a model, the fitness model, that reproduces both the topological and weighted properties of the global virtual water trade network, by assuming as sole controls each country's gross domestic product and yearly rainfall on agricultural areas. We capture and quantitatively describe the high degree of globalization of water trade and show that a small group of nations play a key role in the connectivity of the network and in the global redistribution of virtual water. Finally, we illustrate examples of prediction of the structure of the network under future political, economic and climatic scenarios, suggesting that the crucial importance of the countries that trade large volumes of water will be strengthened. Our results show the importance of incorporating a network framework in the study of virtual water trades and provide a model to study the structure and resilience of the GVWTN under future scenarios for social, economic and climate change.

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J; Faraj, Ahmad A; Inglett, Todd A; Ratterman, Joseph D

2013-04-16

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selected link to the adjacent compute node connected to the compute node through the selected link.

A Clementine Derived Control Network and Topographic Model - The Unified Lunar Control Network 2005

NASA Astrophysics Data System (ADS)

Archinal, B. A.; Rosiek, M. R.; Kirk, R. L.; Redding, B. L.

2006-08-01

U. S. Geological Survey, Astrogeology Team, Flagstaff, AZ, United States Introduction: We have completed a new general unified lunar control network and lunar topographic model based on Clementine images. It includes the determination, in the lunar mean Earth/polar axis system, of the 3-D positions of 272,931 points on the lunar surface and the correction of the camera angles for 43,866 Clementine images, using 546,126 tie point measurements. The solution RMS is 0.9 pixels in the image plane, with the largest residual of 6.4 pixels. We are now documenting our solution and plan to release the solution results soon, initially as a USGS Open File report. ULCN 2005 Features: The new network is a combination of the Unified Lunar Control Network (ULCN), derived from the Apollo, Mariner 10, and Galileo missions, and Earth-based photographs, [1] and the Clementine Lunar Control Network (CLCN) [2], both derived from (mostly 750-nm) Clementine images, by M. Davies and T. Colvin at RAND. The primary difference between our new network and the previous ones is that we solve for the radii of the control points. This avoids (~7 km) distortion of horizontal positions present in the CLCN. The expected precision of such information is on the order of several hundred m, and compatible with Clementine LIDAR [3]. Thus, a by-product of this network is a global lunar topographic model that is denser than that provided by LIDAR and of similar accuracy, and denser than any other lunar topography information except that provided in limited areas ([4-7]). This is the only lunar topographic model positioning where both heights and horizontal positions are estimated in a globally-consistent system. Other features of the ULCN 2005 are that the camera angles to their values as measured during the mission, supposedly with an accuracy of 0.03º [8], and we have identified a majority of the original ULCN points on Clementine images. Future Work: The Lunar Orbiter (LO) digital mosaics now being generated [9] will be registered to the ULCN 2005. We will also further improve this network through the addition of Mariner 10, Galileo, and LO image measurements, and Clementine stereo [10], and by adding ties to the current absolute LLR and ALSEP network [11]. Although unfunded, the Clementine mosaics could also be regenerated in this system. It will be absolutely essential to further update and improve this network with data from future missions. This is necessary so that these new datasets can be compared to the prior data, particularly the LO and Clementine multispectral products. References: [1] Davies, M. E. et al. (1994) JGR, 99, E11, 23,211-23,214. [2] Edwards, et al. (1996), LPS XXVII, 335-336. [3] Smith, D. E. et al. (1997), JGR, 102, E1, 1591-1611. [4] Cook, A. C. et al. (2000), JGR, 105, E5, 12,023-12,033. [5] Rosiek, M. R. et al. (1998), LPS XXX, Abstract #1853. Rosiek, M. R., and Aeschliman, R. A. (2001) LPS XXXII, Abstract #1943. [6] Margot, J-L. C. (1999), PhD Thesis, Cornell University. [7] Wu, S. S. C. and Doyle, F. J. (1990), in Planetary Mapping, R. Greeley and R.M. Batson, eds., CUP, 169-207. [8] Nozette, S., et al. (1994), Science, 266, 1835-1839. [9] Weller, L., et al. (2006), LPS XXXVII, Abstract #2143. [10] Cook, A. C. et al. (2002), AGU Fall Meeting, Abstract #P22D-09. [11] Davies, M. E. and Colvin, T. R. (2000), JGR, 105, E8, 20,277-20,280.

Providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOEpatents

Archer, Charles J.; Faraj, Ahmad A.; Inglett, Todd A.; Ratterman, Joseph D.

2012-10-23

Methods, apparatus, and products are disclosed for providing nearest neighbor point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: identifying each link in the global combining network for each compute node of the operational group; designating one of a plurality of point-to-point class routing identifiers for each link such that no compute node in the operational group is connected to two adjacent compute nodes in the operational group with links designated for the same class routing identifiers; and configuring each compute node of the operational group for point-to-point communications with each adjacent compute node in the global combining network through the link between that compute node and that adjacent compute node using that link's designated class routing identifier.

How to simulate global cosmic strings with large string tension

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klaer, Vincent B.; Moore, Guy D., E-mail: vklaer@theorie.ikp.physik.tu-darmstadt.de, E-mail: guy.moore@physik.tu-darmstadt.de

Global string networks may be relevant in axion production in the early Universe, as well as other cosmological scenarios. Such networks contain a large hierarchy of scales between the string core scale and the Hubble scale, ln( f {sub a} / H ) ∼ 70, which influences the network dynamics by giving the strings large tensions T ≅ π f {sub a} {sup 2} ln( f {sub a} / H ). We present a new numerical approach to simulate such global string networks, capturing the tension without an exponentially large lattice.

Global and System-Specific Resting-State fMRI Fluctuations Are Uncorrelated: Principal Component Analysis Reveals Anti-Correlated Networks

PubMed Central

Carbonell, Felix; Bellec, Pierre

2011-01-01

Abstract The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)–based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations. PMID:22444074

Quality of service provision assessment in the healthcare information and telecommunications infrastructures.

PubMed

Babulak, Eduard

2006-01-01

The continuous increase in the complexity and the heterogeneity of corporate and healthcare telecommunications infrastructures will require new assessment methods of quality of service (QoS) provision that are capable of addressing all engineering and social issues with much faster speeds. Speed and accessibility to any information at any time from anywhere will create global communications infrastructures with great performance bottlenecks that may put in danger human lives, power supplies, national economy and security. Regardless of the technology supporting the information flows, the final verdict on the QoS is made by the end user. The users' perception of telecommunications' network infrastructure QoS provision is critical to the successful business management operation of any organization. As a result, it is essential to assess the QoS Provision in the light of user's perception. This article presents a cost effective methodology to assess the user's perception of quality of service provision utilizing the existing Staffordshire University Network (SUN) by adding a component of measurement to the existing model presented by Walker. This paper presents the real examples of CISCO Networking Solutions for Health Care givers and offers a cost effective approach to assess the QoS provision within the campus network, which could be easily adapted to any health care organization or campus network in the world.

The Obesity Learning Centre (OLC) – a website supporting those working towards a healthy weight and reducing obesity levels

PubMed Central

Korjonen, Helena

2011-01-01

Objectives: Develop a website, the OLC, which supports those people who work on promoting a healthy weight and tackling obesity. Research shows that original networks where sharing of information and peer interaction take place create solutions to current public health challenges. Methods: Considerations that are relevant when building a new information service as well as the technical set up and information needs of users were taken into account prior to building the OLC and during continuous development and maintenance. Results: The OLC provides global news, resources and tools and link out to other networks, websites and organisations providing similar useful information. The OLC also uses social networking tools to highlight new and important information. Discussion: Networks contribute to a stronger community that can respond to emerging challenges in public health. The OLC improves connections of people and services from different backgrounds and organisations. Some challenges exist in the technical set up and also because of other aspects, e.g. public health information and differing information needs. Conclusion: Public health work programmes should include networking opportunities where public policy can be disseminated. The provision of necessary tools and resources can lead to better decision-making, save time and money and lead to improved public health outcomes. PMID:23569599

Reconstruction of in-plane strain maps using hybrid dense sensor network composed of sensing skin

NASA Astrophysics Data System (ADS)

Downey, Austin; Laflamme, Simon; Ubertini, Filippo

2016-12-01

The authors have recently developed a soft-elastomeric capacitive (SEC)-based thin film sensor for monitoring strain on mesosurfaces. Arranged in a network configuration, the sensing system is analogous to a biological skin, where local strain can be monitored over a global area. Under plane stress conditions, the sensor output contains the additive measurement of the two principal strain components over the monitored surface. In applications where the evaluation of strain maps is useful, in structural health monitoring for instance, such signal must be decomposed into linear strain components along orthogonal directions. Previous work has led to an algorithm that enabled such decomposition by leveraging a dense sensor network configuration with the addition of assumed boundary conditions. Here, we significantly improve the algorithm’s accuracy by leveraging mature off-the-shelf solutions to create a hybrid dense sensor network (HDSN) to improve on the boundary condition assumptions. The system’s boundary conditions are enforced using unidirectional RSGs and assumed virtual sensors. Results from an extensive experimental investigation demonstrate the good performance of the proposed algorithm and its robustness with respect to sensors’ layout. Overall, the proposed algorithm is seen to effectively leverage the advantages of a hybrid dense network for application of the thin film sensor to reconstruct surface strain fields over large surfaces.

Firewall systems: the next generation

NASA Astrophysics Data System (ADS)

McGhie, Lynda L.

1996-01-01

To be competitive in today's globally connected marketplace, a company must ensure that their internal network security methodologies and supporting policies are current and reflect an overall understanding of today's technology and its resultant threats. Further, an integrated approach to information security should ensure that new ways of sharing information and doing business are accommodated; such as electronic commerce, high speed public broadband network services, and the federally sponsored National Information Infrastructure. There are many challenges, and success is determined by the establishment of a solid and firm baseline security architecture that accommodate today's external connectivity requirements, provides transitional solutions that integrate with evolving and dynamic technologies, and ultimately acknowledges both the strategic and tactical goals of an evolving network security architecture and firewall system. This paper explores the evolution of external network connectivity requirements, the associated challenges and the subsequent development and evolution of firewall security systems. It makes the assumption that a firewall is a set of integrated and interoperable components, coming together to form a `SYSTEM' and must be designed, implement and managed as such. A progressive firewall model will be utilized to illustrates the evolution of firewall systems from earlier models utilizing separate physical networks, to today's multi-component firewall systems enabling secure heterogeneous and multi-protocol interfaces.

Explicit Context Matching in Content-Based Publish/Subscribe Systems

PubMed Central

Vavassori, Sergio; Soriano, Javier; Lizcano, David; Jiménez, Miguel

2013-01-01

Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without altering the cost of SIENA-like topology changes. PMID:23529118

Sensitivity Analysis for Probabilistic Neural Network Structure Reduction.

PubMed

Kowalski, Piotr A; Kusy, Maciej

2018-05-01

In this paper, we propose the use of local sensitivity analysis (LSA) for the structure simplification of the probabilistic neural network (PNN). Three algorithms are introduced. The first algorithm applies LSA to the PNN input layer reduction by selecting significant features of input patterns. The second algorithm utilizes LSA to remove redundant pattern neurons of the network. The third algorithm combines the proposed two and constitutes the solution of how they can work together. PNN with a product kernel estimator is used, where each multiplicand computes a one-dimensional Cauchy function. Therefore, the smoothing parameter is separately calculated for each dimension by means of the plug-in method. The classification qualities of the reduced and full structure PNN are compared. Furthermore, we evaluate the performance of PNN, for which global sensitivity analysis (GSA) and the common reduction methods are applied, both in the input layer and the pattern layer. The models are tested on the classification problems of eight repository data sets. A 10-fold cross validation procedure is used to determine the prediction ability of the networks. Based on the obtained results, it is shown that the LSA can be used as an alternative PNN reduction approach.

Technology Directions for the 21st Century. Volume 3

NASA Technical Reports Server (NTRS)

Crimi, Giles F.; Botta, Robert; Ditanna, Thomas; Verheggen, Henry; Stancati, Michael; Feingold, Harvey; Jacobs, Mark

1996-01-01

New technologies will unleash the huge capacity of fiber-optic cable to meet growing demands for bandwidth. Companies will continue to replace private networks with public network bandwidth-on-demand. Although asynchronous transfer mode (ATM) is the transmission technology favored by many, its penetration will be slower than anticipated. Hybrid networks - e.g., a mix of ATM, frame relay, and fast Ethernet - may predominate, both as interim and long-term solutions, based on factors such as availability, interoperability, and cost. Telecommunications equipment and services prices will decrease further due to increased supply and more competition. Explosive Internet growth will continue, requiring additional backbone transmission capacity and enhanced protocols, but it is not clear who will fund the upgrade. Within ten years, space-based constellations of satellites in Low Earth orbit (LEO) will serve mobile users employing small, low-power terminals. 'Little LEO's' will provide packet transmission services and geo-position determination. 'Big LEO's' will function as global cellular telephone networks, with some planning to offer video and interactive multimedia services. Geosynchronous satellites also are proposed for mobile voice grade links and high-bandwidth services. NASA may benefit from resulting cost reductions in components, space hardware, launch services, and telecommunications services.

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

PubMed

Guo, Zhenyuan; Yang, Shaofu; Wang, Jun

2016-12-01

This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Using temporal ICA to selectively remove global noise while preserving global signal in functional MRI data.

PubMed

Glasser, Matthew F; Coalson, Timothy S; Bijsterbosch, Janine D; Harrison, Samuel J; Harms, Michael P; Anticevic, Alan; Van Essen, David C; Smith, Stephen M

2018-06-02

Temporal fluctuations in functional Magnetic Resonance Imaging (fMRI) have been profitably used to study brain activity and connectivity for over two decades. Unfortunately, fMRI data also contain structured temporal "noise" from a variety of sources, including subject motion, subject physiology, and the MRI equipment. Recently, methods have been developed to automatically and selectively remove spatially specific structured noise from fMRI data using spatial Independent Components Analysis (ICA) and machine learning classifiers. Spatial ICA is particularly effective at removing spatially specific structured noise from high temporal and spatial resolution fMRI data of the type acquired by the Human Connectome Project and similar studies. However, spatial ICA is mathematically, by design, unable to separate spatially widespread "global" structured noise from fMRI data (e.g., blood flow modulations from subject respiration). No methods currently exist to selectively and completely remove global structured noise while retaining the global signal from neural activity. This has left the field in a quandary-to do or not to do global signal regression-given that both choices have substantial downsides. Here we show that temporal ICA can selectively segregate and remove global structured noise while retaining global neural signal in both task-based and resting state fMRI data. We compare the results before and after temporal ICA cleanup to those from global signal regression and show that temporal ICA cleanup removes the global positive biases caused by global physiological noise without inducing the network-specific negative biases of global signal regression. We believe that temporal ICA cleanup provides a "best of both worlds" solution to the global signal and global noise dilemma and that temporal ICA itself unlocks interesting neurobiological insights from fMRI data. Copyright © 2018 Elsevier Inc. All rights reserved.

Globalizing Social Justice Education: The Case of The Global Solidarity Network Study e-Broad Program

ERIC Educational Resources Information Center

Harrison, Yvonne D.; Kostic, Kevin; Toton, Suzanne C.; Zurek, Jerome

2010-01-01

This paper documents the development, implementation, and evaluation of "The Global Solidarity Network Study e-Broad Program (GSNSeBP)", an online social justice educational program that is blended into an onsite academic course. This global electronic program, which was developed through a partnership between Catholic Relief Services (CRS) and…

Enhancing Polyhedral Relaxations for Global Optimization

ERIC Educational Resources Information Center

Bao, Xiaowei

2009-01-01

During the last decade, global optimization has attracted a lot of attention due to the increased practical need for obtaining global solutions and the success in solving many global optimization problems that were previously considered intractable. In general, the central question of global optimization is to find an optimal solution to a given…

Aftermath of bustamante attack on genomic beacon service.

PubMed

Aziz, Md Momin Al; Ghasemi, Reza; Waliullah, Md; Mohammed, Noman

2017-07-26

With the enormous need for federated eco-system for holding global genomic and clinical data, Global Alliance for Genomic and Health (GA4GH) has created an international website called beacon service which allows a researcher to find out whether a specific dataset can be utilized to his or her research beforehand. This simple webservice is quite useful as it allows queries like whether a certain position of a target chromosome has a specific nucleotide. However, the increased integration of individuals genomic data into clinical practice and research raised serious privacy concern. Though the answer of such queries are yes or no in Bacon network, it results in serious privacy implication as demonstrated in a recent work from Shringarpure and Bustamante. In their attack model, the authors demonstrated that with a limited number of queries, presence of an individual in any dataset can be determined. We propose two lightweight algorithms (based on randomized response) which captures the efficacy while preserving the privacy of the participants in a genomic beacon service. We also elaborate the strength and weakness of the attack by explaining some of their statistical and mathematical models using real world genomic database. We extend their experimental simulations for different adversarial assumptions and parameters. We experimentally evaluated the solutions on the original attack model with different parameters for better understanding of the privacy and utility tradeoffs provided by these two methods. Also, the statistical analysis further elaborates the different aspects of the prior attack which leads to a better risk management for the participants in a beacon service. The differentially private and lightweight solutions discussed here will make the attack much difficult to succeed while maintaining the fundamental motivation of beacon database network.

ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software.

PubMed

Jacomy, Mathieu; Venturini, Tommaso; Heymann, Sebastien; Bastian, Mathieu

2014-01-01

Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics...). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users' typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.

ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software

PubMed Central

Jacomy, Mathieu; Venturini, Tommaso; Heymann, Sebastien; Bastian, Mathieu

2014-01-01

Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics…). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users’ typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices. PMID:24914678

The global health network on alcohol control: successes and limits of evidence-based advocacy

PubMed Central

Schmitz, Hans Peter

2016-01-01

Global efforts to address alcohol harm have significantly increased since the mid-1990s. By 2010, the World Health Organization (WHO) had adopted the non-binding Global Strategy to Reduce the Harmful Use of Alcohol. This study investigates the role of a global health network, anchored by the Global Alcohol Policy Alliance (GAPA), which has used scientific evidence on harm and effective interventions to advocate for greater global public health efforts to reduce alcohol harm. The study uses process-tracing methodology and expert interviews to evaluate the accomplishments and limitations of this network. The study documents how network members have not only contributed to greater global awareness about alcohol harm, but also advanced a public health approach to addressing this issue at the global level. Although the current network represents an expanding global coalition of like-minded individuals, it faces considerable challenges in advancing its cause towards successful implementation of effective alcohol control policies across many low- and middle-income countries (LMICs). The analysis reveals a need to transform the network into a formal coalition of regional and national organizations that represent a broader variety of constituents, including the medical community, consumer groups and development-focused non-governmental organizations. Considering the growing harm of alcohol abuse in LMICs and the availability of proven and cost-effective public health interventions, alcohol control represents an excellent ‘buy’ for donors interested in addressing non-communicable diseases. Alcohol control has broad beneficial effects for human development, including promoting road safety and reducing domestic violence and health care costs across a wide variety of illnesses caused by alcohol consumption. PMID:26276763

The global health network on alcohol control: successes and limits of evidence-based advocacy.

PubMed

Schmitz, Hans Peter

2016-04-01

Global efforts to address alcohol harm have significantly increased since the mid-1990 s. By 2010, the World Health Organization (WHO) had adopted the non-binding Global Strategy to Reduce the Harmful Use of Alcohol. This study investigates the role of a global health network, anchored by the Global Alcohol Policy Alliance (GAPA), which has used scientific evidence on harm and effective interventions to advocate for greater global public health efforts to reduce alcohol harm. The study uses process-tracing methodology and expert interviews to evaluate the accomplishments and limitations of this network. The study documents how network members have not only contributed to greater global awareness about alcohol harm, but also advanced a public health approach to addressing this issue at the global level. Although the current network represents an expanding global coalition of like-minded individuals, it faces considerable challenges in advancing its cause towards successful implementation of effective alcohol control policies across many low- and middle-income countries (LMICs). The analysis reveals a need to transform the network into a formal coalition of regional and national organizations that represent a broader variety of constituents, including the medical community, consumer groups and development-focused non-governmental organizations. Considering the growing harm of alcohol abuse in LMICs and the availability of proven and cost-effective public health interventions, alcohol control represents an excellent 'buy' for donors interested in addressing non-communicable diseases. Alcohol control has broad beneficial effects for human development, including promoting road safety and reducing domestic violence and health care costs across a wide variety of illnesses caused by alcohol consumption. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2015; all rights reserved.

Multiscale Methods for Nuclear Reactor Analysis

NASA Astrophysics Data System (ADS)

Collins, Benjamin S.

The ability to accurately predict local pin powers in nuclear reactors is necessary to understand the mechanisms that cause fuel pin failure during steady state and transient operation. In the research presented here, methods are developed to improve the local solution using high order methods with boundary conditions from a low order global solution. Several different core configurations were tested to determine the improvement in the local pin powers compared to the standard techniques, that use diffusion theory and pin power reconstruction (PPR). Two different multiscale methods were developed and analyzed; the post-refinement multiscale method and the embedded multiscale method. The post-refinement multiscale methods use the global solution to determine boundary conditions for the local solution. The local solution is solved using either a fixed boundary source or an albedo boundary condition; this solution is "post-refinement" and thus has no impact on the global solution. The embedded multiscale method allows the local solver to change the global solution to provide an improved global and local solution. The post-refinement multiscale method is assessed using three core designs. When the local solution has more energy groups, the fixed source method has some difficulties near the interface: however the albedo method works well for all cases. In order to remedy the issue with boundary condition errors for the fixed source method, a buffer region is used to act as a filter, which decreases the sensitivity of the solution to the boundary condition. Both the albedo and fixed source methods benefit from the use of a buffer region. Unlike the post-refinement method, the embedded multiscale method alters the global solution. The ability to change the global solution allows for refinement in areas where the errors in the few group nodal diffusion are typically large. The embedded method is shown to improve the global solution when it is applied to a MOX/LEU assembly interface, the fuel/reflector interface, and assemblies where control rods are inserted. The embedded method also allows for multiple solution levels to be applied in a single calculation. The addition of intermediate levels to the solution improves the accuracy of the method. Both multiscale methods considered here have benefits and drawbacks, but both can provide improvements over the current PPR methodology.

Global low-energy weak solution and large-time behavior for the compressible flow of liquid crystals

NASA Astrophysics Data System (ADS)

Wu, Guochun; Tan, Zhong

2018-06-01

In this paper, we consider the weak solution of the simplified Ericksen-Leslie system modeling compressible nematic liquid crystal flows in R3. When the initial data are of small energy and initial density is positive and essentially bounded, we prove the existence of a global weak solution in R3. The large-time behavior of a global weak solution is also established.

GEOSS: Addressing Big Data Challenges

NASA Astrophysics Data System (ADS)

Nativi, S.; Craglia, M.; Ochiai, O.

2014-12-01

In the sector of Earth Observation, the explosion of data is due to many factors including: new satellite constellations, the increased capabilities of sensor technologies, social media, crowdsourcing, and the need for multidisciplinary and collaborative research to face Global Changes. In this area, there are many expectations and concerns about Big Data. Vendors have attempted to use this term for their commercial purposes. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This presentation tries to explore and discuss the impact of Big Data challenges and new capabilities on the Global Earth Observation System of Systems (GEOSS) and particularly on its common digital infrastructure called GCI. GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information at their desk. The impact of the Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on GEOSS is discussed. The main solutions and experimentation developed by GEOSS along these axes are introduced and analyzed. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the Earth Observation realm; its experience on Big Data is valuable for the many lessons learned.

Partial differential equations constrained combinatorial optimization on an adiabatic quantum computer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh

Partial differential equation-constrained combinatorial optimization (PDECCO) problems are a mixture of continuous and discrete optimization problems. PDECCO problems have discrete controls, but since the partial differential equations (PDE) are continuous, the optimization space is continuous as well. Such problems have several applications, such as gas/water network optimization, traffic optimization, micro-chip cooling optimization, etc. Currently, no efficient classical algorithm which guarantees a global minimum for PDECCO problems exists. A new mapping has been developed that transforms PDECCO problem, which only have linear PDEs as constraints, into quadratic unconstrained binary optimization (QUBO) problems that can be solved using an adiabatic quantum optimizer (AQO). The mapping is efficient, it scales polynomially with the size of the PDECCO problem, requires only one PDE solve to form the QUBO problem, and if the QUBO problem is solved correctly and efficiently on an AQO, guarantees a global optimal solution for the original PDECCO problem.

Providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Archer, Charles J.; Faraj, Daniel A.; Inglett, Todd A.

Methods, apparatus, and products are disclosed for providing full point-to-point communications among compute nodes of an operational group in a global combining network of a parallel computer, each compute node connected to each adjacent compute node in the global combining network through a link, that include: receiving a network packet in a compute node, the network packet specifying a destination compute node; selecting, in dependence upon the destination compute node, at least one of the links for the compute node along which to forward the network packet toward the destination compute node; and forwarding the network packet along the selectedmore » link to the adjacent compute node connected to the compute node through the selected link.« less

Spatial Representativeness Error in the Ground‐Level Observation Networks for Black Carbon Radiation Absorption

PubMed Central

Andrews, Elisabeth; Balkanski, Yves; Boucher, Olivier; Myhre, Gunnar; Samset, Bjørn Hallvard; Schulz, Michael; Schuster, Gregory L.; Valari, Myrto; Tao, Shu

2018-01-01

Abstract There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation‐constrained estimate, which is several times larger than the bottom‐up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry‐transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top‐down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error. PMID:29937603

Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding.

PubMed

Pedersen, Mangor; Omidvarnia, Amir H; Walz, Jennifer M; Jackson, Graeme D

2015-01-01

Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications.

Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding

PubMed Central

Pedersen, Mangor; Omidvarnia, Amir H.; Walz, Jennifer M.; Jackson, Graeme D.

2015-01-01

Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications. PMID:26110111

Integrating legacy medical data sensors in a wireless network infrastucture.

PubMed

Dembeyiotis, S; Konnis, G; Koutsouris, D

2005-01-01

In the process of developing a wireless networking solution to provide effective field-deployable communications and telemetry support for rescuers during major natural disasters, we are faced with the task of interfacing the multitude of medical and other legacy data collection sensors to the network grid. In this paper, we detail a number of solutions, with particular attention given to the issue of data security. The chosen implementation allows for sensor control and management from remote network locations, while the sensors can wirelessly transmit their data to nearby network nodes securely, utilizing the latest commercially available cryptography solutions. Initial testing validates the design choices, while the network-enabled sensors are being integrated in the overall wireless network security framework.

76 FR 25310 - Notice of Intent To Grant a Partially Exclusive Patent License to videoNEXT Network Solutions, Inc.

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-04

... DEPARTMENT OF DEFENSE Department of the Army Notice of Intent To Grant a Partially Exclusive Patent License to videoNEXT Network Solutions, Inc. AGENCY: Department of the Army, DoD. ACTION: Notice... notice of its intent to grant to videoNEXT Network Solutions, Inc., a corporation having its principle...

Optimization of multicast optical networks with genetic algorithm

NASA Astrophysics Data System (ADS)

Lv, Bo; Mao, Xiangqiao; Zhang, Feng; Qin, Xi; Lu, Dan; Chen, Ming; Chen, Yong; Cao, Jihong; Jian, Shuisheng

2007-11-01

In this letter, aiming to obtain the best multicast performance of optical network in which the video conference information is carried by specified wavelength, we extend the solutions of matrix games with the network coding theory and devise a new method to solve the complex problems of multicast network switching. In addition, an experimental optical network has been testified with best switching strategies by employing the novel numerical solution designed with an effective way of genetic algorithm. The result shows that optimal solutions with genetic algorithm are accordance with the ones with the traditional fictitious play method.

78 FR 15049 - The Evercare Company Including On-Site Leased Workers From Global Personnel Solutions and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-08

... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-81,932] The Evercare Company Including On-Site Leased Workers From Global Personnel Solutions and Manpower Waynesboro, Georgia; Amended... group included on-site leased workers from Global Personnel Solutions. In response to an inquiry by the...

50 years of Global Seismic Observations

NASA Astrophysics Data System (ADS)

Anderson, K. R.; Butler, R.; Berger, J.; Davis, P.; Derr, J.; Gee, L.; Hutt, C. R.; Leith, W. S.; Park, J. J.

2007-12-01

Seismological recordings have been made on Earth for hundreds of years in some form or another, however, global monitoring of earthquakes only began in the 1890's when John Milne created 40 seismic observatories to measure the waves from these events. Shortly after the International Geophysical Year (IGY), a concerted effort was made to establish and maintain a more modern standardized seismic network on the global scale. In the early 1960's, the World-Wide Standardized Seismograph Network (WWSSN) was established through funding from the Advanced Research Projects Agency (ARPA) and was installed and maintained by the USGS's Albuquerque Seismological Laboratory (then a part of the US Coast and Geodetic Survey). This network of identical seismic instruments consisted of 120 stations in 60 countries. Although the network was motivated by nuclear test monitoring, the WWSSN facilitated numerous advances in observational seismology. From the IGY to the present, the network has been upgraded (High-Gain Long-Period Seismograph Network, Seismic Research Observatories, Digital WWSSN, Global Telemetered Seismograph Network, etc.) and expanded (International Deployment of Accelerometers, US National Seismic Network, China Digital Seismograph Network, Joint Seismic Project, etc.), bringing the modern day Global Seismographic Network (GSN) to a current state of approximately 150 stations. The GSN consists of state-of-the-art very broadband seismic transducers, continuous power and communications, and ancillary sensors including geodetic, geomagnetic, microbarographic, meteorological and other related instrumentation. Beyond the GSN, the system of global network observatories includes contributions from other international partners (e.g., GEOSCOPE, GEOFON, MEDNET, F-Net, CTBTO), forming an even larger backbone of permanent seismological observatories as a part of the International Federation of Digital Seismograph Networks. 50 years of seismic network operations have provided valuable data for earth science research. Developments in communications and other technological advances have expanded the role of the GSN in rapid earthquake analysis, tsunami warning, and nuclear test monitoring. With such long-term observations, scientists are now getting a glimpse of Earth structure changes on human time scales, such as the rotation of the inner core, as well as views into climate processes. Continued observations for the next 50 years will enhance our image of the Earth and its processes.

Advanced Optical Burst Switched Network Concepts

NASA Astrophysics Data System (ADS)

Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network would have to securely transport 1.2 GB of data every 30 s [230]. According to the above explanation it is clear that these types of applications need a new network infrastructure and transport technology that makes large amounts of bandwidth at subwavelength granularity, storage, computation, and visualization resources potentially available to a wide user base for specified time durations. As these types of collaborative and network-based applications evolve addressing a wide range and large number of users, it is infeasible to build dedicated networks for each application type or category. Consequently, there should be an adaptive network infrastructure able to support all application types, each with their own access, network, and resource usage patterns. This infrastructure should offer flexible and intelligent network elements and control mechanism able to deploy new applications quickly and efficiently.

The effect of tracking network configuration on Global Positioning System (GPS) baseline estimates for the CASA (Central and South America) Uno experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolf, S.K.; Dixon, T.H.; Freymueller, J.T.

1990-04-01

Geodetic monitoring of subduction of the Nazca and Cocos plates is a goal of the CASA (Central and South America) Global Positioning System (GPS) experiments, and requires measurement of intersite distances (baselines) in excess of 500 km. The major error source in these measurements is the uncertainty in the position of the GPS satellites at the time of observation. A key aspect of the first CASA experiment, CASA Uno, was the initiation of a global network of tracking stations minimize these errors. The authors studied the effect of using various subsets of this global tracking network on long (>100 km)more » baseline estimates in the CASA region. Best results were obtained with a global tracking network consisting of three U.S. fiducial stations, two sites in the southwest pacific and two sites in Europe. Relative to smaller subsets, this global network improved baseline repeatability, resolution of carrier phase cycle ambiguities, and formal errors of the orbit estimates. Describing baseline repeatability for horizontal components as {sigma}=(a{sup 2} + b{sup 2}L{sup 2}){sup 1/2} where L is baseline length, the authors obtained a = 4 and 9 mm and b = 2.8{times}10{sup {minus}8} and 2.3{times}10{sup {minus}8} for north and east components, respectively, on CASA baselines up to 1,000 km in length with this global network.« less

Extensive cross-talk and global regulators identified from an analysis of the integrated transcriptional and signaling network in Escherichia coli.

PubMed

Antiqueira, Lucas; Janga, Sarath Chandra; Costa, Luciano da Fontoura

2012-11-01

To understand the regulatory dynamics of transcription factors (TFs) and their interplay with other cellular components we have integrated transcriptional, protein-protein and the allosteric or equivalent interactions which mediate the physiological activity of TFs in Escherichia coli. To study this integrated network we computed a set of network measurements followed by principal component analysis (PCA), investigated the correlations between network structure and dynamics, and carried out a procedure for motif detection. In particular, we show that outliers identified in the integrated network based on their network properties correspond to previously characterized global transcriptional regulators. Furthermore, outliers are highly and widely expressed across conditions, thus supporting their global nature in controlling many genes in the cell. Motifs revealed that TFs not only interact physically with each other but also obtain feedback from signals delivered by signaling proteins supporting the extensive cross-talk between different types of networks. Our analysis can lead to the development of a general framework for detecting and understanding global regulatory factors in regulatory networks and reinforces the importance of integrating multiple types of interactions in underpinning the interrelationships between them.

Information transfer network of global market indices

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

Development of the Global Measles Laboratory Network.

PubMed

Featherstone, David; Brown, David; Sanders, Ray

2003-05-15

The routine reporting of suspected measles cases and laboratory testing of samples from these cases is the backbone of measles surveillance. The Global Measles Laboratory Network (GMLN) has developed standards for laboratory confirmation of measles and provides training resources for staff of network laboratories, reference materials and expertise for the development and quality control of testing procedures, and accurate information for the Measles Mortality Reduction and Regional Elimination Initiative. The GMLN was developed along the lines of the successful Global Polio Laboratory Network, and much of the polio laboratory infrastructure was utilized for measles. The GMLN has developed as countries focus on measles control activities following successful eradication of polio. Currently more than 100 laboratories are part of the global network and follow standardized testing and reporting procedures. A comprehensive laboratory accreditation process will be introduced in 2002 with six quality assurance and performance indicators.

Abnormal functional global and local brain connectivity in female patients with anorexia nervosa

PubMed Central

Geisler, Daniel; Borchardt, Viola; Lord, Anton R.; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A.; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

2016-01-01

Background Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. Methods To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Results Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. Limitations The present results may be limited to the methods applied during preprocessing and network construction. Conclusion We demonstrated anorexia nervosa–related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger. PMID:26252451

Abnormal functional global and local brain connectivity in female patients with anorexia nervosa.

PubMed

Geisler, Daniel; Borchardt, Viola; Lord, Anton R; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

2016-01-01

Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. The present results may be limited to the methods applied during preprocessing and network construction. We demonstrated anorexia nervosa-related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger.

Shifting Tides in Global Higher Education: Agency, Autonomy, and Governance in the Global Network. Global Studies in Education, Volume 9

ERIC Educational Resources Information Center

Witt, Mary Allison

2011-01-01

The increasing connection among higher education institutions worldwide is well documented. What is less understood is how this connectivity is enacted and manifested on specific levels of the global education network. This book details the planning process of a multi-institutional program in engineering between institutions in the US and…

Ubiquitous wireless ECG recording: a powerful tool physicians should embrace.

PubMed

Saxon, Leslie A

2013-04-01

The use of smart phones has increased dramatically and there are nearly a billion users on 3G and 4G networks worldwide. Nearly 60% of the U.S. population uses smart phones to access the internet, and smart phone sales now surpass those of desktop and laptop computers. The speed of wireless communication technology on 3G and 4G networks and the widespread adoption and use of iOS equipped smart phones (Apple Inc., Cupertino, CA, USA) provide infrastructure for the transmission of wireless biomedical data, including ECG data. These technologies provide an unprecedented opportunity for physicians to continually access data that can be used to detect issues before symptoms occur or to have definitive data when symptoms are present. The technology also greatly empowers and enables the possibility for unprecedented patient participation in their own medical education and health status as well as that of their social network. As patient advocates, physicians and particularly cardiac electrophysiologists should embrace the future and promise of wireless ECG recording, a technology solution that can truly scale across the global population. © 2013 Wiley Periodicals, Inc.

Networking for rare diseases: a necessity for Europe.

PubMed

Aymé, S; Schmidtke, J

2007-12-01

Most rare diseases are life-threatening and chronically debilitating conditions, and the vast majority of them are genetically determined. Their individually low prevalence requires special combined efforts to address them so as to improve diagnosis, care and prevention. Though it is difficult to develop a public health policy specific to each rare disease, it is possible to have a global rather than a piecemeal approach in the areas of scientific and biomedical research, drug research and development, industry policy, information and training, social benefits, hospitalisation and outpatient care. In the recent past, several initiatives at EU and Member States levels have been taken and proved efficient in developing suitable solutions which are now having a positive impact on the quality of life of patients. These initiatives are presented here. They include the establishment of Orphanet, a database of rare diseases and orphan drugs providing an encyclopedia of rare diseases and a directory of associated expert services, the funding of research networks to boost the collaboration between research teams, as well as the funding of networks of clinical centres of reference to better serve the patients and contribute to developing clinical research.

PROPER: global protein interaction network alignment through percolation matching.

PubMed

Kazemi, Ehsan; Hassani, Hamed; Grossglauser, Matthias; Pezeshgi Modarres, Hassan

2016-12-12

The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PPI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch .

Brain parcellation choice affects disease-related topology differences increasingly from global to local network levels.

PubMed

Lord, Anton; Ehrlich, Stefan; Borchardt, Viola; Geisler, Daniel; Seidel, Maria; Huber, Stefanie; Murr, Julia; Walter, Martin

2016-03-30

Network-based analyses of deviant brain function have become extremely popular in psychiatric neuroimaging. Underpinning brain network analyses is the selection of appropriate regions of interest (ROIs). Although ROI selection is fundamental in network analysis, its impact on detecting disease effects remains unclear. We investigated the impact of parcellation choice when comparing results from different studies. We investigated the effects of anatomical (AAL) and literature-based (Dosenbach) parcellation schemes on comparability of group differences in 35 female patients with anorexia nervosa and 35 age- and sex-matched healthy controls. Global and local network properties, including network-based statistics (NBS), were assessed on resting state functional magnetic resonance imaging data obtained at 3T. Parcellation schemes were comparably consistent on global network properties, while NBS and local metrics differed in location, but not metric type. Location of local metric alterations varied for AAL (parietal and cingulate cortices) versus Dosenbach (insula, thalamus) parcellation approaches. However, consistency was observed for the occipital cortex. Patient-specific global network properties can be robustly observed using different parcellation schemes, while graph metrics characterizing impairments of individual nodes vary considerably. Therefore, the impact of parcellation choice on specific group differences varies depending on the level of network organization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Station Coordinates Combination Status and Contribution to ITRF2005

NASA Astrophysics Data System (ADS)

Ferland, R.

2007-12-01

Under the auspices of the International GNSS Service (IGS), the Reference Frame Working Group combines at Natural Resources Canada (NRCan) an accurate and consistent set of station coordinates, velocities and Earth Rotation Parameters (ERP) that are updated weekly. The consistency of these parameters is ensured by simultaneously combining them using their full variance-covariance information. The IGS Analysis Centers (ACs) (cod, emr, esa, gfz, jpl, mit, ngs, sio) provide the solutions used in the IGS weekly combination. The Global Network Associates Analysis Centers (GNAAC) (mit, ncl) also generate weekly combined solutions that include consistent station coordinates and ERPs. Those GNAAC solutions are used for comparisons and quality control of the IGS weekly solution. In recent weeks each AC has been contributing between about 50 and 250 station coordinates estimates. The combined product currently approaches 300 stations. Of those, between 40 and 110 are used for the current IGS reference frame realization of the ITRF2005 in each AC solution. The quality of the AC station coordinates solutions has improved significantly since they have started contributing in early 1996. This is due to the densification of the network of stations along with gradual improvements in station hardware and processing software. For recent solutions, the estimated noise (std. dev.) level between the AC weekly solutions and the different combined solutions varies between 1-3mm horizontally and 2-10mm vertically. More details about the statistics, their evolution and differences between the ACs will be presented. IGS weekly station coordinates and ERP combined products have also been contributed to the ITRF2005. Those weekly solutions were all recombined from the original AC contributions, going back to the beginning of 1996. The recombined solutions were edited for known problems (e.g. incorrect antenna heights and outliers). Several stations with short time span were also removed. A list of station coordinates discontinuities was also prepared, in collaboration with several individuals and contributed to the IERS. Since November 5, 2006 (GPS week 1400), the IGS has implemented a realization of ITRF2005. It includes mainly the change from relative to absolute antenna phase centers and an update of the selected reference frame stations for the new realization. An expected change of scale from about 3 ppb to -0.7 ppb caused by the phase center shift was observed.

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan

2006-01-01

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks.

PubMed

Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

2015-01-01

Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators' careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system throughput performance.

Evolvable rough-block-based neural network and its biomedical application to hypoglycemia detection system.

PubMed

San, Phyo Phyo; Ling, Sai Ho; Nuryani; Nguyen, Hung

2014-08-01

This paper focuses on the hybridization technology using rough sets concepts and neural computing for decision and classification purposes. Based on the rough set properties, the lower region and boundary region are defined to partition the input signal to a consistent (predictable) part and an inconsistent (random) part. In this way, the neural network is designed to deal only with the boundary region, which mainly consists of an inconsistent part of applied input signal causing inaccurate modeling of the data set. Owing to different characteristics of neural network (NN) applications, the same structure of conventional NN might not give the optimal solution. Based on the knowledge of application in this paper, a block-based neural network (BBNN) is selected as a suitable classifier due to its ability to evolve internal structures and adaptability in dynamic environments. This architecture will systematically incorporate the characteristics of application to the structure of hybrid rough-block-based neural network (R-BBNN). A global training algorithm, hybrid particle swarm optimization with wavelet mutation is introduced for parameter optimization of proposed R-BBNN. The performance of the proposed R-BBNN algorithm was evaluated by an application to the field of medical diagnosis using real hypoglycemia episodes in patients with Type 1 diabetes mellitus. The performance of the proposed hybrid system has been compared with some of the existing neural networks. The comparison results indicated that the proposed method has improved classification performance and results in early convergence of the network.

GraphStore: A Distributed Graph Storage System for Big Data Networks

ERIC Educational Resources Information Center

Martha, VenkataSwamy

2013-01-01

Networks, such as social networks, are a universal solution for modeling complex problems in real time, especially in the Big Data community. While previous studies have attempted to enhance network processing algorithms, none have paved a path for the development of a persistent storage system. The proposed solution, GraphStore, provides an…

Essential elements of online information networks on invasive alien species

USGS Publications Warehouse

Simpson, A.; Sellers, E.; Grosse, A.; Xie, Y.

2006-01-01

In order to be effective, information must be placed in the proper context and organized in a manner that is logical and (preferably) standardized. Recently, invasive alien species (IAS) scientists have begun to create online networks to share their information concerning IAS prevention and control. At a special networking session at the Beijing International Symposium on Biological Invasions, an online Eastern Asia-North American IAS Information Network (EA-NA Network) was proposed. To prepare for the development of this network, and to provide models for other regional collaborations, we compare four examples of global, regional, and national online IAS information networks: the Global Invasive Species Information Network, the Invasives Information Network of the Inter-American Biodiversity Information Network, the Chinese Species Information System, and the Invasive Species Information Node of the US National Biological Information Infrastructure. We conclude that IAS networks require a common goal, dedicated leaders, effective communication, and broad endorsement, in order to obtain sustainable, long-term funding and long-term stability. They need to start small, use the experience of other networks, partner with others, and showcase benefits. Global integration and synergy among invasive species networks will succeed with contributions from both the top-down and the bottom-up. ?? 2006 Springer.

Darboux Transformation and N-soliton Solution for Extended Form of Modified Kadomtsev—Petviashvili Equation with Variable-Coefficient

NASA Astrophysics Data System (ADS)

Luo, Xing-Yu; Chen, Yong

2016-08-01

The extended form of modified Kadomtsev—Petviashvili equation with variable-coefficient is investigated in the framework of Painlevé analysis. The Lax pairs are obtained by analysing two Painlevé branches of this equation. Starting with the Lax pair, the N-times Darboux transformation is constructed and the N-soliton solution formula is given, which contains 2n free parameters and two arbitrary functions. Furthermore, with different combinations of the parameters, several types of soliton solutions are calculated from the first order to the third order. The regularity conditions are discussed in order to avoid the singularity of the solutions. Moreover, we construct the generalized Darboux transformation matrix by considering a special limiting process and find a rational-type solution for this equation. Supported by the Global Change Research Program of China under Grant No. 2015CB953904, National Natural Science Foundation of China under Grant Nos. 11275072 and 11435005, Doctoral Program of Higher Education of China under Grant No. 20120076110024, The Network Information Physics Calculation of basic research innovation research group of China under Grant No. 61321064, Shanghai Collaborative Innovation Center of Trustworthy Software for Internet of Things under Grant No. ZF1213, Shanghai Minhang District talents of high level scientific research project

Simulated Stochastic Approximation Annealing for Global Optimization with a Square-Root Cooling Schedule

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liang, Faming; Cheng, Yichen; Lin, Guang

2014-06-13

Simulated annealing has been widely used in the solution of optimization problems. As known by many researchers, the global optima cannot be guaranteed to be located by simulated annealing unless a logarithmic cooling schedule is used. However, the logarithmic cooling schedule is so slow that no one can afford to have such a long CPU time. This paper proposes a new stochastic optimization algorithm, the so-called simulated stochastic approximation annealing algorithm, which is a combination of simulated annealing and the stochastic approximation Monte Carlo algorithm. Under the framework of stochastic approximation Markov chain Monte Carlo, it is shown that themore » new algorithm can work with a cooling schedule in which the temperature can decrease much faster than in the logarithmic cooling schedule, e.g., a square-root cooling schedule, while guaranteeing the global optima to be reached when the temperature tends to zero. The new algorithm has been tested on a few benchmark optimization problems, including feed-forward neural network training and protein-folding. The numerical results indicate that the new algorithm can significantly outperform simulated annealing and other competitors.« less

Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting.

PubMed

Corzo, Gerald; Solomatine, Dimitri

2007-05-01

Natural phenomena are multistationary and are composed of a number of interacting processes, so one single model handling all processes often suffers from inaccuracies. A solution is to partition data in relation to such processes using the available domain knowledge or expert judgment, to train separate models for each of the processes, and to merge them in a modular model (committee). In this paper a problem of water flow forecast in watershed hydrology is considered where the flow process can be presented as consisting of two subprocesses -- base flow and excess flow, so that these two processes can be separated. Several approaches to data separation techniques are studied. Two case studies with different forecast horizons are considered. Parameters of the algorithms responsible for data partitioning are optimized using genetic algorithms and global pattern search. It was found that modularization of ANN models using domain knowledge makes models more accurate, if compared with a global model trained on the whole data set, especially when forecast horizon (and hence the complexity of the modelled processes) is increased.

The Collaboration Challenge: Global Partnerships to Achieve Global Goals.

PubMed

Bzdak, Michael

2017-01-01

As capitalism is being re-invented and the voices of multiple stakeholders are becoming more prevalent and demanding, it is the perfect time for the private sector to embrace large-scale collaboration and a shared sense of purpose. Since the explosive growth of Corporate Social Responsibility (CSR) in the 1990s, a new era of responsibility, purpose and a re-envisioned capitalism are dramatically apparent. Beyond financial support, business leaders have the opportunity to galvanize networks, advocate for regulation and policy change, and form supporting consortia to support global development. The role of the private sector in development has changed significantly from a model of benevolent contributor to a model of collaborator, investor, business partner and exponential value creator. The new era of collaboration should move beyond a shared value mindset to new models of partnership where each contributor plays an equal role in defining challenges and designing solutions with the greater goal of sustainable value creation. Non-Governmental Organizations (NGOs) have the unprecedented opportunity to take leadership roles in engaging the private sector in more game-changing collaborations.

A quantum network of clocks

NASA Astrophysics Data System (ADS)

Komar, Peter; Kessler, Eric; Bishof, Michael; Jiang, Liang; Sorensen, Anders; Ye, Jun; Lukin, Mikhail

2014-05-01

Shared timing information constitutes a key resource for positioning and navigation with a direct correspondence between timing accuracy and precision in applications such as the Global Positioning System (GPS). By combining precision metrology and quantum networks, we propose here a quantum, cooperative protocol for the operation of a network consisting of geographically remote optical atomic clocks. Using non-local entangled states, we demonstrate an optimal utilization of the global network resources, and show that such a network can be operated near the fundamental limit set by quantum theory yielding an ultra-precise clock signal. Furthermore, the internal structure of the network, combined with basic techniques from quantum communication, guarantees security both from internal and external threats. Realization of such a global quantum network of clocks may allow construction of a real-time single international time scale (world clock) with unprecedented stability and accuracy. See also: Komar et al. arXiv:1310.6045 (2013) and Kessler et al. arXiv:1310.6043 (2013).

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Aires, F.; Prigent, C.; Rossow, W. B.; Rothstein, M.; Hansen, James E. (Technical Monitor)

2000-01-01

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Neural network feedforward control of a closed-circuit wind tunnel

NASA Astrophysics Data System (ADS)

Sutcliffe, Peter

Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the derived NNMPC controller provided an excellent level of control over the test-section temperature in adherence to a reference trajectory even when faced with unforeseen disturbances such as rapid changes in the operating environment.

Power and Networks in Worldwide Knowledge Coordination: The Case of Global Science

ERIC Educational Resources Information Center

King, Roger

2011-01-01

The article considers the global governance of knowledge systems, exploring concepts of power, networks, standards (defined as normative practices), and structuration. The focus is on science as a form of predominantly private global governance, particularly the self-regulatory and collaborative processes stretching across time and space. These…

Global epidemic invasion thresholds in directed cattle subpopulation networks having source, sink, and transit nodes

USDA-ARS?s Scientific Manuscript database

Through the characterization of a metapopulation cattle disease model on a directed network having source, transit, and sink nodes, we derive two global epidemic invasion thresholds. The first threshold defines the conditions necessary for an epidemic to successfully spread at the global scale. The ...

Is Social Network a Protective Factor for Cognitive Impairment in US Chinese Older Adults? Findings from the PINE Study.

PubMed

Li, Mengting; Dong, Xinqi

2018-01-01

Social network has been identified as a protective factor for cognitive impairment. However, the relationship between social network and global and subdomains of cognitive function remains unclear. This study aims to provide an analytic framework to examine quantity, composition, and quality of social network and investigate the association between social network, global cognition, and cognitive domains among US Chinese older adults. Data were derived from the Population Study of Chinese Elderly (PINE), a community-engaged, population-based epidemiological study of US Chinese older adults aged 60 and above in the greater Chicago area, with a sample size of 3,157. Social network was assessed by network size, volume of contact, proportion kin, proportion female, proportion co-resident, and emotional closeness. Cognitive function was evaluated by global cognition, episodic memory, executive function, working memory, and Chinese Mini-Mental State Examination (C-MMSE). Linear regression and quantile regression were performed. Every 1-point increase in network size (b = 0.048, p < 0.001) and volume of contact (b = 0.049, p < 0.01) and every 1-point decrease in proportion kin (b = -0.240, p < 0.01) and proportion co-resident (b = -0.099, p < 0.05) were associated with higher level of global cognition. Similar trends were observed in specific cognitive domains, including episodic memory, working memory, executive function, and C-MMSE. However, emotional closeness was only significantly associated with C-MMSE (b = 0.076, p < 0.01). Social network has differential effects on female versus male older adults. This study found that social network dimensions have different relationships with global and domains of cognitive function. Quantitative and structural aspects of social network were essential to maintain an optimal level of cognitive function. Qualitative aspects of social network were protective factors for C-MMSE. It is necessary for public health practitioners to consider interventions that enhance different aspects of older adults' social network. © 2017 S. Karger AG, Basel.

Sex differences in the relationship between white matter connectivity and creativity.

PubMed

Ryman, Sephira G; van den Heuvel, Martijn P; Yeo, Ronald A; Caprihan, Arvind; Carrasco, Jessica; Vakhtin, Andrei A; Flores, Ranee A; Wertz, Christopher; Jung, Rex E

2014-11-01

Creative cognition emerges from a complex network of interacting brain regions. This study investigated the relationship between the structural organization of the human brain and aspects of creative cognition tapped by divergent thinking tasks. Diffusion weighted imaging (DWI) was used to obtain fiber tracts from 83 segmented cortical regions. This information was represented as a network and metrics of connectivity organization, including connectivity strength, clustering and communication efficiency were computed, and their relationship to individual levels of creativity was examined. Permutation testing identified significant sex differences in the relationship between global connectivity and creativity as measured by divergent thinking tests. Females demonstrated significant inverse relationships between global connectivity and creative cognition, whereas there were no significant relationships observed in males. Node specific analyses revealed inverse relationships across measures of connectivity, efficiency, clustering and creative cognition in widespread regions in females. Our findings suggest that females involve more regions of the brain in processing to produce novel ideas to solutions, perhaps at the expense of efficiency (greater path lengths). Males, in contrast, exhibited few, relatively weak positive relationships across these measures. Extending recent observations of sex differences in connectome structure, our findings of sexually dimorphic relationships suggest a unique topological organization of connectivity underlying the generation of novel ideas in males and females. Published by Elsevier Inc.

From global agenda-setting to domestic implementation: successes and challenges of the global health network on tobacco control.

PubMed

Gneiting, Uwe

2016-04-01

Global policy attention to tobacco control has increased significantly since the 1990 s and culminated in the first international treaty negotiated under the auspices of the World Health Organization--the Framework Convention on Tobacco Control (FCTC). Although the political process that led to the creation of the FCTC has been extensively researched, the FCTC's progression from an aspirational treaty towards a global health governance framework with tangible policy effects within FCTC member countries has not been well-understood to date. This article analyses the role of the global health network of tobacco control advocates and scientists, which formed during the FCTC negotiations during the late 1990 s, in translating countries' commitment to the FCTC into domestic policy change. By comparing the network's influence around two central tobacco control interventions (smoke-free environments and taxation), the study identifies several scope conditions, which have shaped the network's effectiveness around the FCTC's implementation: the complexity of the policy issue and the relative importance of non-health expertise, the required scope of domestic political buy-in, the role of the general public as network allies, and the strength of policy opposition. These political factors had a greater influence on the network's success than the evidence base for the effectiveness of tobacco control interventions. The network's variable success points to a trade-off faced by global health networks between their need to maintain internal cohesion and their ability to form alliances with actors in their social environment. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2015; all rights reserved.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

Tropical medicine: Telecommunications and technology transfer

NASA Technical Reports Server (NTRS)

Legters, Llewellyn J.

1991-01-01

The potential for global outbreaks of tropical infectious diseases, and our ability to identify and respond to such outbreaks is a major concern. Rapid, efficient telecommunications is viewed as part of the solution to this set of problems - the means to link a network of epidemiological field stations via satellite with U.S. academic institutions and government agencies, for purposes of research, training in tropical medicine, and observation of and response to epidemic emergencies. At a workshop, telecommunications and technology transfer were addressed and applications of telecommunications technology in long-distance consultation, teaching and disaster relief were demonstrated. Applications in teaching and consultation in tropical infectious diseases is discussed.

Fast, Nonlinear, Fully Probabilistic Inversion of Large Geophysical Problems

NASA Astrophysics Data System (ADS)

Curtis, A.; Shahraeeni, M.; Trampert, J.; Meier, U.; Cho, G.

2010-12-01

Almost all Geophysical inverse problems are in reality nonlinear. Fully nonlinear inversion including non-approximated physics, and solving for probability distribution functions (pdf’s) that describe the solution uncertainty, generally requires sampling-based Monte-Carlo style methods that are computationally intractable in most large problems. In order to solve such problems, physical relationships are usually linearized leading to efficiently-solved, (possibly iterated) linear inverse problems. However, it is well known that linearization can lead to erroneous solutions, and in particular to overly optimistic uncertainty estimates. What is needed across many Geophysical disciplines is a method to invert large inverse problems (or potentially tens of thousands of small inverse problems) fully probabilistically and without linearization. This talk shows how very large nonlinear inverse problems can be solved fully probabilistically and incorporating any available prior information using mixture density networks (driven by neural network banks), provided the problem can be decomposed into many small inverse problems. In this talk I will explain the methodology, compare multi-dimensional pdf inversion results to full Monte Carlo solutions, and illustrate the method with two applications: first, inverting surface wave group and phase velocities for a fully-probabilistic global tomography model of the Earth’s crust and mantle, and second inverting industrial 3D seismic data for petrophysical properties throughout and around a subsurface hydrocarbon reservoir. The latter problem is typically decomposed into 104 to 105 individual inverse problems, each solved fully probabilistically and without linearization. The results in both cases are sufficiently close to the Monte Carlo solution to exhibit realistic uncertainty, multimodality and bias. This provides far greater confidence in the results, and in decisions made on their basis.

The most remote point method for the site selection of the future GGOS network

NASA Astrophysics Data System (ADS)

Hase, Hayo; Pedreros, Felipe

2014-10-01

The Global Geodetic Observing System (GGOS) proposes 30-40 geodetic observatories as global infrastructure for the most accurate reference frame to monitor the global change. To reach this goal, several geodetic observatories have upgrade plans to become GGOS stations. Most initiatives are driven by national institutions following national interests. From a global perspective, the site distribution remains incomplete and the initiatives to improve this are up until now insufficient. This article is a contribution to answer the question on where to install new GGOS observatories and where to add observation techniques to existing observatories. It introduces the iterative most remote point (MRP) method for filling in the largest gaps in existing technique-specific networks. A spherical version of the Voronoi-diagram is used to pick the optimal location of the new observatory, but practical concerns determine its realistic location. Once chosen, the process is iterated. A quality and a homogeneity parameter of global networks measure the progress of improving the homogeneity of the global site distribution. This method is applied to the global networks of VGOS, and VGOS co-located with SLR to derive some clues about where additional observatory sites or additional observation techniques at existing observatories will improve the GGOS network configuration. With only six additional VGOS-stations, the homogeneity of the global VGOS-network could be significantly improved by more than . From the presented analysis, 25 known or new co-located VGOS and SLR sites are proposed as the future GGOS backbone: Colombo, Easter Island, Fairbanks, Fortaleza, Galapagos, GGAO, Hartebeesthoek, Honiara, Ibadan, Kokee Park, La Plata, Mauritius, McMurdo, Metsahövi, Ny Alesund, Riyadh, San Diego, Santa Maria, Shanghai, Syowa, Tahiti, Tristan de Cunha, Warkworth, Wettzell, and Yarragadee.

[Study on Abnormal Topological Properties of Structural Brain Networks of Patients with Depression Comorbid with Anxiety].

PubMed

Wu, Xiuyong; Wu, Xiaoming; Peng, Hongjun; Ning, Yuping; Wu, Kai

2016-06-01

This paper is aimed to analyze the topological properties of structural brain networks in depressive patients with and without anxiety and to explore the neuropath logical mechanisms of depression comorbid with anxiety.Diffusion tensor imaging and deterministic tractography were applied to map the white matter structural networks.We collected 20 depressive patients with anxiety(DPA),18 depressive patients without anxiety(DP),and 28 normal controls(NC)as comparative groups.The global and nodal properties of the structural brain networks in the three groups were analyzed with graph theoretical methods.The result showed that1 the structural brain networks in three groups showed small-world properties and highly connected global hubs predominately from association cortices;2DP group showed lower local efficiency and global efficiency compared to NC group,whereas DPA group showed higher local efficiency and global efficiency compared to NC group;3significant differences of network properties(clustering coefficient,characteristic path lengths,local efficiency,global efficiency)were found between DPA and DP groups;4DP group showed significant changes of nodal efficiency in the brain areas primarily in the temporal lobe and bilateral frontal gyrus,compared to DPA and NC groups.The analysis indicated that the DP and DPA groups showed nodal properties of the structural brain networks,compared to NC group.Moreover,the two diseased groups indicated an opposite trend in the network properties.The results of this study may provide a new imaging index for clinical diagnosis for depression comorbid with anxiety.

Security and Dependability Solutions for Networks and Devices

NASA Astrophysics Data System (ADS)

Gücrgens, Sigrid; Fuchs, Andreas

In this chapter we give an overview over the denotation of the SERENITY artefacts S&D Classes, Patterns and Implementations in the context of networks and devices. In order to demonstrate their necessity we sketch an example for confidential and authentic communication and storage that utilizes a trusted platform module, and model the relevant pattern. We then dissociate solutions for network and device related S&D requirements from those targeting the context of organizational or workflow and web services based solutions. Then we give a summary of the broad field of application for network and device solutions. Finally we clarify the meaning and interaction between classes, patterns and implementations by giving some concrete examples.

Real-time community detection in full social networks on a laptop

PubMed Central

Chamberlain, Benjamin Paul; Levy-Kramer, Josh; Humby, Clive

2018-01-01

For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide free services that are valued by billions of people globally. PMID:29342158

Cooperative spreading processes in multiplex networks.

PubMed

Wei, Xiang; Chen, Shihua; Wu, Xiaoqun; Ning, Di; Lu, Jun-An

2016-06-01

This study is concerned with the dynamic behaviors of epidemic spreading in multiplex networks. A model composed of two interacting complex networks is proposed to describe cooperative spreading processes, wherein the virus spreading in one layer can penetrate into the other to promote the spreading process. The global epidemic threshold of the model is smaller than the epidemic thresholds of the corresponding isolated networks. Thus, global epidemic onset arises in the interacting networks even though an epidemic onset does not arise in each isolated network. Simulations verify the analysis results and indicate that cooperative spreading processes in multiplex networks enhance the final infection fraction.

The GCOS Reference Upper-Air Network (GRUAN)

NASA Astrophysics Data System (ADS)

Vömel, H.; Berger, F. H.; Immler, F. J.; Seidel, D.; Thorne, P.

2009-04-01

While the global upper-air observing network has provided useful observations for operational weather forecasting for decades, its measurements lack the accuracy and long-term continuity needed for understanding climate change. Consequently, the scientific community faces uncertainty on such key issues as the trends of temperature in the upper troposphere and stratosphere or the variability and trends of stratospheric water vapour. To address these shortcomings, and to ensure that future climate records will be more useful than the records to date, the Global Climate Observing System (GCOS) program initiated the GCOS Reference Upper Air Network (GRUAN). GRUAN will be a network of about 30-40 observatories with a representative sampling of geographic regions and surface types. These stations will provide upper-air reference observations of the essential climate variables, i.e. temperature, geopotential, humidity, wind, radiation and cloud properties using specialized radiosondes and complementary remote sensing profiling instrumentation. Long-term stability, quality assurance / quality control, and a detailed assessment of measurement uncertainties will be the key aspects of GRUAN observations. The network will not be globally complete but will serve to constrain and adjust data from more spatially comprehensive global observing systems including satellites and the current radiosonde networks. This paper outlines the scientific rationale for GRUAN, its role in the Global Earth Observation System of Systems, network requirements and likely instrumentation, management structure, current status and future plans.

Global and national laboratory networks support high quality surveillance for measles and rubella.

PubMed

Xu, Wenbo; Zhang, Yan; Wang, Huiling; Zhu, Zhen; Mao, Naiying; Mulders, Mick N; Rota, Paul A

2017-05-01

Laboratory networks are an essential component of disease surveillance systems because they provide accurate and timely confirmation of infection. WHO coordinates global laboratory surveillance of vaccine preventable diseases, including measles and rubella. The more than 700 laboratories within the WHO Global Measles and Rubella Laboratory Network (GMRLN) supports surveillance for measles, rubella and congenial rubella syndrome in 191 counties. This paper describes the overall structure and function of the GMRLN and highlights the largest of the national laboratory networks, the China Measles and Rubella Laboratory Network. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Stable configurations in social networks

NASA Astrophysics Data System (ADS)

Bronski, Jared C.; DeVille, Lee; Ferguson, Timothy; Livesay, Michael

2018-06-01

We present and analyze a model of opinion formation on an arbitrary network whose dynamics comes from a global energy function. We study the global and local minimizers of this energy, which we call stable opinion configurations, and describe the global minimizers under certain assumptions on the friendship graph. We show a surprising result that the number of stable configurations is not necessarily monotone in the strength of connection in the social network, i.e. the model sometimes supports more stable configurations when the interpersonal connections are made stronger.

Assessing the evolving fragility of the global food system

NASA Astrophysics Data System (ADS)

Puma, Michael J.; Bose, Satyajit; Chon, So Young; Cook, Benjamin I.

2015-02-01

The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18 year study period, we show that the global food system is relatively homogeneous (85% of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90%, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9% (3.8%) for 1992-1996, increasing to 11% (5.7%) for 2005-2009. Over the same intervals, rice losses increase from 8.2% (2.2%) to 14% (5.2%). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

Assessing the Evolving Fragility of the Global Food System

NASA Technical Reports Server (NTRS)

Puma, Michael Joseph; Bose, Satyajit; Chon, So Young; Cook, Benjamin I.

2015-01-01

The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18-year study period, we show that the global food system is relatively homogeneous (85 of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9 (3.8) for 1992-1996, increasing to 11 (5.7) for 20052009. Over the same intervals, rice losses increase from 8.2 (2.2) to 14 (5.2). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

A quantum network of clocks

NASA Astrophysics Data System (ADS)

Kómár, P.; Kessler, E. M.; Bishof, M.; Jiang, L.; Sørensen, A. S.; Ye, J.; Lukin, M. D.

2014-08-01

The development of precise atomic clocks plays an increasingly important role in modern society. Shared timing information constitutes a key resource for navigation with a direct correspondence between timing accuracy and precision in applications such as the Global Positioning System. By combining precision metrology and quantum networks, we propose a quantum, cooperative protocol for operating a network of geographically remote optical atomic clocks. Using nonlocal entangled states, we demonstrate an optimal utilization of global resources, and show that such a network can be operated near the fundamental precision limit set by quantum theory. Furthermore, the internal structure of the network, combined with quantum communication techniques, guarantees security both from internal and external threats. Realization of such a global quantum network of clocks may allow construction of a real-time single international time scale (world clock) with unprecedented stability and accuracy.

Global exponential stability of inertial memristor-based neural networks with time-varying delays and impulses.

PubMed

Zhang, Wei; Huang, Tingwen; He, Xing; Li, Chuandong

2017-11-01

In this study, we investigate the global exponential stability of inertial memristor-based neural networks with impulses and time-varying delays. We construct inertial memristor-based neural networks based on the characteristics of the inertial neural networks and memristor. Impulses with and without delays are considered when modeling the inertial neural networks simultaneously, which are of great practical significance in the current study. Some sufficient conditions are derived under the framework of the Lyapunov stability method, as well as an extended Halanay differential inequality and a new delay impulsive differential inequality, which depend on impulses with and without delays, in order to guarantee the global exponential stability of the inertial memristor-based neural networks. Finally, two numerical examples are provided to illustrate the efficiency of the proposed methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-GNSS phase delay estimation and PPP ambiguity resolution: GPS, BDS, GLONASS, Galileo

NASA Astrophysics Data System (ADS)

Li, Xingxing; Li, Xin; Yuan, Yongqiang; Zhang, Keke; Zhang, Xiaohong; Wickert, Jens

2017-10-01

This paper focuses on the precise point positioning (PPP) ambiguity resolution (AR) using the observations acquired from four systems: GPS, BDS, GLONASS, and Galileo (GCRE). A GCRE four-system uncalibrated phase delay (UPD) estimation model and multi-GNSS undifferenced PPP AR method were developed in order to utilize the observations from all systems. For UPD estimation, the GCRE-combined PPP solutions of the globally distributed MGEX and IGS stations are performed to obtain four-system float ambiguities and then UPDs of GCRE satellites can be precisely estimated from these ambiguities. The quality of UPD products in terms of temporal stability and residual distributions is investigated for GPS, BDS, GLONASS, and Galileo satellites, respectively. The BDS satellite-induced code biases were corrected for GEO, IGSO, and MEO satellites before the UPD estimation. The UPD results of global and regional networks were also evaluated for Galileo and BDS, respectively. As a result of the frequency-division multiple-access strategy of GLONASS, the UPD estimation was performed using a network of homogeneous receivers including three commonly used GNSS receivers (TRIMBLE NETR9, JAVAD TRE_G3TH DELTA, and LEICA). Data recorded from 140 MGEX and IGS stations for a 30-day period in January in 2017 were used to validate the proposed GCRE UPD estimation and multi-GNSS dual-frequency PPP AR. Our results show that GCRE four-system PPP AR enables the fastest time to first fix (TTFF) solutions and the highest accuracy for all three coordinate components compared to the single and dual system. An average TTFF of 9.21 min with 7{°} cutoff elevation angle can be achieved for GCRE PPP AR, which is much shorter than that of GPS (18.07 min), GR (12.10 min), GE (15.36 min) and GC (13.21 min). With observations length of 10 min, the positioning accuracy of the GCRE fixed solution is 1.84, 1.11, and 1.53 cm, while the GPS-only result is 2.25, 1.29, and 9.73 cm for the east, north, and vertical components, respectively. When the cutoff elevation angle is increased to 30{°} , the GPS-only PPP AR results are very unreliable, while 13.44 min of TTFF is still achievable for GCRE four-system solutions.

Multi-GNSS phase delay estimation and PPP ambiguity resolution: GPS, BDS, GLONASS, Galileo

NASA Astrophysics Data System (ADS)

Li, Xingxing; Li, Xin; Yuan, Yongqiang; Zhang, Keke; Zhang, Xiaohong; Wickert, Jens

2018-06-01

This paper focuses on the precise point positioning (PPP) ambiguity resolution (AR) using the observations acquired from four systems: GPS, BDS, GLONASS, and Galileo (GCRE). A GCRE four-system uncalibrated phase delay (UPD) estimation model and multi-GNSS undifferenced PPP AR method were developed in order to utilize the observations from all systems. For UPD estimation, the GCRE-combined PPP solutions of the globally distributed MGEX and IGS stations are performed to obtain four-system float ambiguities and then UPDs of GCRE satellites can be precisely estimated from these ambiguities. The quality of UPD products in terms of temporal stability and residual distributions is investigated for GPS, BDS, GLONASS, and Galileo satellites, respectively. The BDS satellite-induced code biases were corrected for GEO, IGSO, and MEO satellites before the UPD estimation. The UPD results of global and regional networks were also evaluated for Galileo and BDS, respectively. As a result of the frequency-division multiple-access strategy of GLONASS, the UPD estimation was performed using a network of homogeneous receivers including three commonly used GNSS receivers (TRIMBLE NETR9, JAVAD TRE_G3TH DELTA, and LEICA). Data recorded from 140 MGEX and IGS stations for a 30-day period in January in 2017 were used to validate the proposed GCRE UPD estimation and multi-GNSS dual-frequency PPP AR. Our results show that GCRE four-system PPP AR enables the fastest time to first fix (TTFF) solutions and the highest accuracy for all three coordinate components compared to the single and dual system. An average TTFF of 9.21 min with 7{°} cutoff elevation angle can be achieved for GCRE PPP AR, which is much shorter than that of GPS (18.07 min), GR (12.10 min), GE (15.36 min) and GC (13.21 min). With observations length of 10 min, the positioning accuracy of the GCRE fixed solution is 1.84, 1.11, and 1.53 cm, while the GPS-only result is 2.25, 1.29, and 9.73 cm for the east, north, and vertical components, respectively. When the cutoff elevation angle is increased to 30{°}, the GPS-only PPP AR results are very unreliable, while 13.44 min of TTFF is still achievable for GCRE four-system solutions.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson-Teixeira, Kristina J.; Davies, Stuart J.; Bennett, Amy C.

2014-09-25

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services, including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamic research sites useful for characterizing forest responses to global change. The broad suite of measurements made at the CTFS-ForestGEO sites make it possible to investigate the complex ways in which global change is impacting forest dynamics. ongoing research across the network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forestmore » diversity and dynamics in a era of global change« less

A cooperative positioning algorithm for DSRC enabled vehicular networks

NASA Astrophysics Data System (ADS)

Efatmaneshnik, M.; Kealy, A.; Alam, N.; Dempster, A. G.

2011-12-01

Many of the safety related applications that can be facilitated by Dedicated Short Range Communications (DSRC), such as vehicle proximity warnings, automated braking (e.g. at level crossings), speed advisories, pedestrian alerts etc., rely on a robust vehicle positioning capability such as that provided by a Global Navigation Satellite System (GNSS). Vehicles in remote areas, entering tunnels, high rise areas or any high multipath/ weak signal environment will challenge the integrity of GNSS position solutions, and ultimately the safety application it underpins. To address this challenge, this paper presents an innovative application of Cooperative Positioning techniques within vehicular networks. CP refers to any method of integrating measurements from different positioning systems and sensors in order to improve the overall quality (accuracy and reliability) of the final position solution. This paper investigates the potential of the DSRC infrastructure itself to provide an inter-vehicular ranging signal that can be used as a measurement within the CP algorithm. In this paper, time-based techniques of ranging are introduced and bandwidth requirements are investigated and presented. The robustness of the CP algorithm to inter-vehicle connection failure as well as GNSS dropouts is also demonstrated using simulation studies. Finally, the performance of the Constrained Kalman Filter used to integrate GNSS measurements with DSRC derived range estimates within a typical VANET is described and evaluated.

Concepts for fast acquisition in optical communications systems

NASA Astrophysics Data System (ADS)

Wilkerson, Brandon L.; Giggenbach, Dirk; Epple, Bernhard

2006-09-01

As free-space laser communications systems proliferate due to improved technology and transmission techniques, optical communication networks comprised of ground stations, aircraft, high altitude platforms, and satellites become an attainable goal. An important consideration for optical networks is the ability of optical communication terminals (OCT) to quickly locate one another and align their laser beams to initiate the acquisition sequence. This paper investigates promising low-cost technologies and novel approaches that will facilitate the targeting and acquisition tasks between counter terminals. Specifically, two critical technology areas are investigated: position determination (which includes location and attitude determination) and inter-terminal communications. A feasibility study identified multiple-antenna global navigation satellite system (GNSS) systems and GNSS-aided inertial systems as possible position determination solutions. Personal satellite communication systems (e.g. Iridium or Inmarsat), third generation cellular technology (IMT-2000/UMTS), and a relatively new air traffic surveillance technology called Autonomous Dependent Surveillance-Broadcast (ADS-B) were identified as possible inter-terminal communication solutions. A GNSS-aided inertial system and an ADS-B system were integrated into an OCT to demonstrate their utility in a typical optical communication scenario. Testing showed that these technologies have high potential in future OCTs, although improvements can be made to both to increase tracking accuracy.

An Enhanced MEMS Error Modeling Approach Based on Nu-Support Vector Regression

PubMed Central

Bhatt, Deepak; Aggarwal, Priyanka; Bhattacharya, Prabir; Devabhaktuni, Vijay

2012-01-01

Micro Electro Mechanical System (MEMS)-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design of low-cost navigation systems. These sensors exhibit significant errors like biases, drift, noises; which are negligible for higher grade units. Different conventional techniques utilizing the Gauss Markov model and neural network method have been previously utilized to model the errors. However, Gauss Markov model works unsatisfactorily in the case of MEMS units due to the presence of high inherent sensor errors. On the other hand, modeling the random drift utilizing Neural Network (NN) is time consuming, thereby affecting its real-time implementation. We overcome these existing drawbacks by developing an enhanced Support Vector Machine (SVM) based error model. Unlike NN, SVMs do not suffer from local minimisation or over-fitting problems and delivers a reliable global solution. Experimental results proved that the proposed SVM approach reduced the noise standard deviation by 10–35% for gyroscopes and 61–76% for accelerometers. Further, positional error drifts under static conditions improved by 41% and 80% in comparison to NN and GM approaches. PMID:23012552

Multistability, local pattern formation, and global collective firing in a small-world network of nonleaky integrate-and-fire neurons.

PubMed

Rothkegel, Alexander; Lehnertz, Klaus

2009-03-01

We investigate numerically the collective dynamical behavior of pulse-coupled nonleaky integrate-and-fire neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Besides a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulentlike patterns, which-depending on network parameters-interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the spatiotemporal dynamics of biological networks.

Final Report - Cloud-Based Management Platform for Distributed, Multi-Domain Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chowdhury, Pulak; Mukherjee, Biswanath

2017-11-03

In this Department of Energy (DOE) Small Business Innovation Research (SBIR) Phase II project final report, Ennetix presents the development of a solution for end-to-end monitoring, analysis, and visualization of network performance for distributed networks. This solution benefits enterprises of all sizes, operators of distributed and federated networks, and service providers.

Dewetting-mediated pattern formation in nanoparticle assemblies

NASA Astrophysics Data System (ADS)

Stannard, Andrew

2011-03-01

The deposition of nanoparticles from solution onto solid substrates is a diverse subfield of current nanoscience research. Complex physical and chemical processes underpin the self-assembly and self-organization of colloidal nanoparticles at two-phase (solid-liquid, liquid-air) interfaces and three-phase (solid-liquid-air) contact lines. This review discusses key recent advances made in the understanding of nonequilibrium dewetting processes of nanoparticle-containing solutions, detailing how such an apparently simple experimental system can give rise to such a strikingly varied palette of two-dimensional self-organized nanoparticle array morphologies. Patterns discussed include worm-like domains, cellular networks, microscale rings, and fractal-like fingering structures. There remain many unresolved issues regarding the role of the solvent dewetting dynamics in assembly processes of this type, with a significant focus on how dewetting can be coerced to produce nanoparticle arrays with desirable characteristics such as long-range order. In addition to these topics, methods developed to control nanofluid dewetting through routes such as confining the geometries of drying solutions, depositing onto pre-patterned heterogeneous substrates, and post-dewetting pattern evolution via local or global manipulation are covered.

Dewetting-mediated pattern formation in nanoparticle assemblies.

PubMed

Stannard, Andrew

2011-03-02

The deposition of nanoparticles from solution onto solid substrates is a diverse subfield of current nanoscience research. Complex physical and chemical processes underpin the self-assembly and self-organization of colloidal nanoparticles at two-phase (solid-liquid, liquid-air) interfaces and three-phase (solid-liquid-air) contact lines. This review discusses key recent advances made in the understanding of nonequilibrium dewetting processes of nanoparticle-containing solutions, detailing how such an apparently simple experimental system can give rise to such a strikingly varied palette of two-dimensional self-organized nanoparticle array morphologies. Patterns discussed include worm-like domains, cellular networks, microscale rings, and fractal-like fingering structures. There remain many unresolved issues regarding the role of the solvent dewetting dynamics in assembly processes of this type, with a significant focus on how dewetting can be coerced to produce nanoparticle arrays with desirable characteristics such as long-range order. In addition to these topics, methods developed to control nanofluid dewetting through routes such as confining the geometries of drying solutions, depositing onto pre-patterned heterogeneous substrates, and post-dewetting pattern evolution via local or global manipulation are covered.

An Experimental Seismic Data and Parameter Exchange System for Interim NEAMTWS

NASA Astrophysics Data System (ADS)

Hanka, W.; Hoffmann, T.; Weber, B.; Heinloo, A.; Hoffmann, M.; Müller-Wrana, T.; Saul, J.

2009-04-01

In 2008 GFZ Potsdam has started to operate its global earthquake monitoring system as an experimental seismic background data centre for the interim NEAMTWS (NE Atlantic and Mediterranean Tsunami Warning System). The SeisComP3 (SC3) software, developed within the GITEWS (German Indian Ocean Tsunami Early Warning System) project was extended to test the export and import of individual processing results within a cluster of SC3 systems. The initiated NEAMTWS SC3 cluster consists presently of the 24/7 seismic services at IMP, IGN, LDG/EMSC and KOERI, whereas INGV and NOA are still pending. The GFZ virtual real-time seismic network (GEOFON Extended Virtual Network - GEVN) was substantially extended by many stations from Western European countries optimizing the station distribution for NEAMTWS purposes. To amend the public seismic network (VEBSN - Virtual European Broadband Seismic Network) some attached centres provided additional private stations for NEAMTWS usage. In parallel to the data collection by Internet the GFZ VSAT hub for the secured data collection of the EuroMED GEOFON and NEAMTWS backbone network stations became operational and the first data links were established. In 2008 the experimental system could already prove its performance since a number of relevant earthquakes have happened in NEAMTWS area. The results are very promising in terms of speed as the automatic alerts (reliable solutions based on a minimum of 25 stations and disseminated by emails and SMS) were issued between 2 1/2 and 4 minutes for Greece and 5 minutes for Iceland. They are also promising in terms of accuracy since epicenter coordinates, depth and magnitude estimates were sufficiently accurate from the very beginning, usually don't differ substantially from the final solutions and provide a good starting point for the operations of the interim NEAMTWS. However, although an automatic seismic system is a good first step, 24/7 manned RTWCs are mandatory for regular manual verification of the automatic seismic results and the estimation of the tsunami potential for a given event.

Investment in Open Innovation Service Providers: NASA's Innovative Strategy for Solving Space Exploration Challenges

NASA Technical Reports Server (NTRS)

Fogarty, Jennifer A.; Rando, Cynthia; Baumann, David; Richard, Elizabeth; Davis, Jeffrey

2010-01-01

In an effort to expand routes for open communication and create additional opportunities for public involvement with NASA, Open Innovation Service Provider (OISP) methodologies have been incorporated as a tool in NASA's problem solving strategy. NASA engaged the services of two OISP providers, InnoCentive and Yet2.com, to test this novel approach and its feasibility in solving NASA s space flight challenges. The OISPs were chosen based on multiple factors including: network size and knowledge area span, established process, methodology, experience base, and cost. InnoCentive and Yet2.com each met the desired criteria; however each company s approach to Open Innovation is distinctly different. InnoCentive focuses on posting individual challenges to an established web-based network of approximately 200,000 solvers; viable solutions are sought and granted a financial award if found. Based on a specific technological need, Yet2.com acts as a talent scout providing a broad external network of experts as potential collaborators to NASA. A relationship can be established with these contacts to develop technologies and/or maintained as an established network of future collaborators. The results from the first phase of the pilot study have shown great promise for long term efficacy of utilizing the OISP methodologies. Solution proposals have been received for the challenges posted on InnoCentive and are currently under review for final disposition. In addition, Yet2.com has identified new external partners for NASA and we are in the process of understanding and acting upon these new opportunities. Compared to NASA's traditional routes for external problem solving, the OISP methodologies offered NASA a substantial savings in terms of time and resources invested. In addition, these strategies will help NASA extend beyond its current borders to build an ever expanding network of experts and global solvers.

Moment tensor inversions using strong motion waveforms of Taiwan TSMIP data, 1993–2009

USGS Publications Warehouse

Chang, Kaiwen; Chi, Wu-Cheng; Gung, Yuancheng; Dreger, Douglas; Lee, William H K.; Chiu, Hung-Chie

2011-01-01

Earthquake source parameters are important for earthquake studies and seismic hazard assessment. Moment tensors are among the most important earthquake source parameters, and are now routinely derived using modern broadband seismic networks around the world. Similar waveform inversion techniques can also apply to other available data, including strong-motion seismograms. Strong-motion waveforms are also broadband, and recorded in many regions since the 1980s. Thus, strong-motion data can be used to augment moment tensor catalogs with a much larger dataset than that available from the high-gain, broadband seismic networks. However, a systematic comparison between the moment tensors derived from strong motion waveforms and high-gain broadband waveforms has not been available. In this study, we inverted the source mechanisms of Taiwan earthquakes between 1993 and 2009 by using the regional moment tensor inversion method using digital data from several hundred stations in the Taiwan Strong Motion Instrumentation Program (TSMIP). By testing different velocity models and filter passbands, we were able to successfully derive moment tensor solutions for 107 earthquakes of Mw >= 4.8. The solutions for large events agree well with other available moment tensor catalogs derived from local and global broadband networks. However, for Mw = 5.0 or smaller events, we consistently over estimated the moment magnitudes by 0.5 to 1.0. We have tested accelerograms, and velocity waveforms integrated from accelerograms for the inversions, and found the results are similar. In addition, we used part of the catalogs to study important seismogenic structures in the area near Meishan Taiwan which was the site of a very damaging earthquake a century ago, and found that the structures were dominated by events with complex right-lateral strike-slip faulting during the recent decade. The procedures developed from this study may be applied to other strong-motion datasets to compliment or fill gaps in catalogs from regional broadband networks and teleseismic networks.

Nurturing Global Collaboration and Networked Learning in Higher Education

ERIC Educational Resources Information Center

Cronin, Catherine; Cochrane, Thomas; Gordon, Averill

2016-01-01

We consider the principles of communities of practice (CoP) and networked learning in higher education, illustrated with a case study. iCollab has grown from an international community of practice connecting students and lecturers in seven modules across seven higher education institutions in six countries, to a global network supporting the…

Fractal Inequality: A Social Network Analysis of Global and Regional International Student Mobility

ERIC Educational Resources Information Center

Macrander, Ashley

2017-01-01

Literature on global international student mobility (ISM) highlights the uneven nature of student flows--from the developing to the developed world--however, studies have yet to address whether this pattern is replicated within expanding regional networks. Utilizing social network analysis, UNESCO ISM data, and World Bank income classifications,…

Geoscience Australia Continuous Global Positioning System (CGPS) Station Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruddick, R.; Twilley, B.

2016-03-01

This station formed part of the Australian Regional GPS Network (ARGN) and South Pacific Regional GPS Network (SPRGN), which is a network of continuous GPS stations operating within Australia and its Territories (including Antarctica) and the Pacific. These networks support a number of different science applications including maintenance of the Geospatial Reference Frame, both national and international, continental and tectonic plate motions, sea level rise, and global warming.

The Network of Global Corporate Control

PubMed Central

Vitali, Stefania; Glattfelder, James B.; Battiston, Stefano

2011-01-01

The structure of the control network of transnational corporations affects global market competition and financial stability. So far, only small national samples were studied and there was no appropriate methodology to assess control globally. We present the first investigation of the architecture of the international ownership network, along with the computation of the control held by each global player. We find that transnational corporations form a giant bow-tie structure and that a large portion of control flows to a small tightly-knit core of financial institutions. This core can be seen as an economic “super-entity” that raises new important issues both for researchers and policy makers. PMID:22046252

Effects of multiple spreaders in community networks

NASA Astrophysics Data System (ADS)

Hu, Zhao-Long; Ren, Zhuo-Ming; Yang, Guang-Yong; Liu, Jian-Guo

2014-12-01

Human contact networks exhibit the community structure. Understanding how such community structure affects the epidemic spreading could provide insights for preventing the spreading of epidemics between communities. In this paper, we explore the spreading of multiple spreaders in community networks. A network based on the clustering preferential mechanism is evolved, whose communities are detected by the Girvan-Newman (GN) algorithm. We investigate the spreading effectiveness by selecting the nodes as spreaders in the following ways: nodes with the largest degree in each community (community hubs), the same number of nodes with the largest degree from the global network (global large-degree) and randomly selected one node within each community (community random). The experimental results on the SIR model show that the spreading effectiveness based on the global large-degree and community hubs methods is the same in the early stage of the infection and the method of community random is the worst. However, when the infection rate exceeds the critical value, the global large-degree method embodies the worst spreading effectiveness. Furthermore, the discrepancy of effectiveness for the three methods will decrease as the infection rate increases. Therefore, we should immunize the hubs in each community rather than those hubs in the global network to prevent the outbreak of epidemics.

The value and limitations of global air-sampling networks for improving our understanding trace gas behavior

NASA Astrophysics Data System (ADS)

Montzka, S. A.

2016-12-01

Measurements from global surface-based air sampling networks provide a fundamental understanding of how and why concentrations of long-lived trace gases are changing over time. Results from these networks are used to quantify trace-gas concentrations and their time-dependent changes on global and smaller scales, and thus provide a means to quantify emission rates, loss frequencies, and mixing processes. Substantial advances in measurement and sampling technologies and the ability of these programs to create and maintain reliable gas standards mean that spatial concentration gradients and time-dependent changes are often very reliably measured. The presence of multiple independent networks allows an assessment of this reliability. Furthermore, recent global `snap-shot' surveys (e.g., HIPPO and ATom) and ongoing atmospheric profiling programs help us assess the ability of surface-based data to describe concentration distributions throughout most of the atmosphere ( 80% of its mass). In this overview talk, I'll explore the usefulness and limitations of existing long-term, ongoing sampling network programs and their advantages and disadvantages for characterizing concentrations on global and regional scales, and how recent advances (and short-term sampling programs) help us assess the accuracy of the surface networks to provide estimates of source and sink magnitudes, and inter-annual variability in both.

Global teaching and training initiatives for emerging cohort studies

PubMed Central

Paulus, Jessica K.; Santoyo-Vistrain, Rocío; Havelick, David; Cohen, Amy; Kalyesubula, Robert; Ajayi, Ikeoluwapo O.; Mattsson, Jens G.; Adami, Hans-Olov; Dalal, Shona

2015-01-01

A striking disparity exists across the globe, with essentially no large-scale longitudinal studies ongoing in regions that will be significantly affected by the oncoming non-communicable disease epidemic. The successful implementation of cohort studies in most low-resource research environments presents unique challenges that may be aided by coordinated training programs. Leaders of emerging cohort studies attending the First World Cohort Integration Workshop were surveyed about training priorities, unmet needs and potential cross-cohort solutions to these barriers through an electronic pre-workshop questionnaire and focus groups. Cohort studies representing India, Mexico, Nigeria, South Africa, Sweden, Tanzania and Uganda described similar training needs, including on-the-job training, data analysis software instruction, and database and bio-bank management. A lack of funding and protected time for training activities were commonly identified constraints. Proposed solutions include a collaborative cross-cohort teaching platform with web-based content and interactive teaching methods for a range of research personnel. An international network for research mentorship and idea exchange, and modifying the graduate thesis structure were also identified as key initiatives. Cross-cohort integrated educational initiatives will efficiently meet shared needs, catalyze the development of emerging cohorts, speed closure of the global disparity in cohort research, and may fortify scientific capacity development in low-resource settings. PMID:23856451

Global Citizenship Incorporated: Competing Responsibilities in the Education of Global Citizens

ERIC Educational Resources Information Center

Hartung, Catherine

2017-01-01

Interest in the education of young people to be 'responsible global citizens' has grown exponentially since the turn of the century, led by increasingly diverse networks of sectors, including government, community, business and philanthropy. These networks now have a significant influence on education policy and practice, indicative of wider…

Global 4-H Network: Laying the Groundwork for Global Extension Opportunities

ERIC Educational Resources Information Center

Major, Jennifer; Miller, Rhonda

2012-01-01

A descriptive study examining 4-H programs in Africa, Asia, and Europe was conducted to provide understanding and direction in the establishment of a Global 4-H Network. Information regarding structure, organizational support, funding, and programming areas was gathered. Programs varied greatly by country, and many partnered with other 4-H…

Scaling-up camera traps: monitoring the planet's biodiversity with networks of remote sensors

USGS Publications Warehouse

Steenweg, Robin; Hebblewhite, Mark; Kays, Roland; Ahumada, Jorge A.; Fisher, Jason T.; Burton, Cole; Townsend, Susan E.; Carbone, Chris; Rowcliffe, J. Marcus; Whittington, Jesse; Brodie, Jedediah; Royle, Andy; Switalski, Adam; Clevenger, Anthony P.; Heim, Nicole; Rich, Lindsey N.

2017-01-01

Countries committed to implementing the Convention on Biological Diversity's 2011–2020 strategic plan need effective tools to monitor global trends in biodiversity. Remote cameras are a rapidly growing technology that has great potential to transform global monitoring for terrestrial biodiversity and can be an important contributor to the call for measuring Essential Biodiversity Variables. Recent advances in camera technology and methods enable researchers to estimate changes in abundance and distribution for entire communities of animals and to identify global drivers of biodiversity trends. We suggest that interconnected networks of remote cameras will soon monitor biodiversity at a global scale, help answer pressing ecological questions, and guide conservation policy. This global network will require greater collaboration among remote-camera studies and citizen scientists, including standardized metadata, shared protocols, and security measures to protect records about sensitive species. With modest investment in infrastructure, and continued innovation, synthesis, and collaboration, we envision a global network of remote cameras that not only provides real-time biodiversity data but also serves to connect people with nature.

Application of neural network technique to determine a corrector surface for global geopotential model using GPS/levelling measurements in Egypt

NASA Astrophysics Data System (ADS)

Elshambaky, Hossam Talaat

2018-01-01

Owing to the appearance of many global geopotential models, it is necessary to determine the most appropriate model for use in Egyptian territory. In this study, we aim to investigate three global models, namely EGM2008, EIGEN-6c4, and GECO. We use five mathematical transformation techniques, i.e., polynomial expression, exponential regression, least-squares collocation, multilayer feed forward neural network, and radial basis neural networks to make the conversion from regional geometrical geoid to global geoid models and vice versa. From a statistical comparison study based on quality indexes between previous transformation techniques, we confirm that the multilayer feed forward neural network with two neurons is the most accurate of the examined transformation technique, and based on the mean tide condition, EGM2008 represents the most suitable global geopotential model for use in Egyptian territory to date. The final product gained from this study was the corrector surface that was used to facilitate the transformation process between regional geometrical geoid model and the global geoid model.

A report on the Unified Lunar Control Network 2005 and lunar topographic model

NASA Astrophysics Data System (ADS)

Archinal, B.; Rosiek, M.; Kirk, R.; Redding, B.

Introduction: We have finished a new general unified lunar control network and lunar topographic model based on Clementine images. This photogrammetric network solution is the largest planetary control network ever completed. It includes the determination of the 3-D positions of 272,931 points on the lunar surface and the correction of the camera angles for 43,866 Clementine images, using 546,126 tie point measurements. The solution RMS is 20 µm (= 0.9 pixels) in the image plane, with the largest residual of 6.4 pixels. We are now documenting our solution [1] and plan to release the solution results soon [2]. Previous Networks: In recent years there have been two generally accepted lunar control networks. These are the Unified Lunar Control Network (ULCN) and the Clementine Lunar Control Network (CLCN), both derived by M. Davies and T. Colvin at RAND. The original ULCN was described in the last major publication about a lunar control network [3]. Images for this network are from the Apollo, Mariner 10, and Galileo missions, and Earth-based photographs. The CLCN was derived from Clementine images and measurements on Clementine 750-nm images. The purpose of this network was to determine the geometry for the Clementine Base Map [4]. The geometry of that mosaic was used to produce the Clementine UVVIS digital image model [5] and the Near-Infrared Global Multispectral Map of the Moon from Clementine [6]. Through the extensive use of these products, they and the underlying CLCN in effect define the generally accepted current coordinate system for reporting and describing the location of lunar features. The CLCN is described in print only briefly [7]. See [8] for ULCN and CLCN files. Our efforts have merged these two networks into an improved ULCN. ULCN 2005 Features: The primary difference between our new network and the previous ones is that we solve for the radii of the control points. This avoids distortion of horizontal positions (of about 7 km average, and up to 15 km or more [9-11]) present in the CLCN primarily due to its points being constrained to the surface of a sphere of radius 1736.7 km. This is possible since the overlapping Clementine images provide stereo information. The expected precision of such information is on the order of several hundred m, but these data appear to be compatible with Clementine LIDAR ([12], previously the most accurate elevation data); the mean absolute difference between 1 the our values and a reference surface derived from the LIDAR values is 137 m with a standard deviation of 219 m. This shows that radii are being recovered at that level or better. Thus, a by-product of this network is a global lunar topographic model that is denser than that provided by LIDAR and of similar accuracy, and denser than any other lunar topography information except that provided in limited areas ([10, 13-15]). This radius information is also defined in a consistent, full, absolute, 3D system. This is the only lunar topographic model positioning where both heights and horizontal positions are estimated in a globally-consistent system. A second significant feature of the ULCN 2005 is that we have constrained the camera angles to their values as measured during the mission, supposedly with an accuracy of 0.03o [16]. We have used a constraint of 1o , with angles that show changes of more than 0.6o allowed to change freely, on the assumption they are from angle measurement blunders (a few angles change by up to ˜25o , probably due to unaccounted for spacecraft operations). We believe this provides significant improvement in the horizontal accuracy of the network (and therefore improves the vertical accuracy, which is coupled), because from an average altitude of 640 km, the implied horizontal position accuracy due to this 0.03o a priori information is 335 m. Since 99% of the angles change less than 0.45o , this and the 640 km altitude would also imply that even if the a priori angles were perfect, the 3σ horizontal error introduced by our solution is 5.1 km. This also assumes that the spacecraft positions - which we do not adjust - are perfectly accurate. Obviously this is not the case, but the cited errors [17] in the orbit positions (at least radially) are ˜100 m, which when RSS added to the pointing errors, would still cause a maximum of a few hundred m additional errors. A third feature is that we identified a majority of the original ULCN points on Clementine images and included measurements of them in the new ULCN 2005. 1261 points are measured, with 754 of them having two or more measurements. This therefore allows for the direct incorporation of the ULCN into the new ULCN 2005. We have done so by weighting the ULCN points appropriately (0.18-5 km horizontally, 2-6 km vertically) for the accuracies as described in [3]. 124 ULCN points, which had particularly high residuals, were interpreted as misidentified points or points where the original ULCN was in error and weighted the same as non-ULCN points (2° and 10 km, effectively free). This tie to the ULCN and the use of Clementine a priori spacecraft data in the mean Earth/polar axis system also places our solution in the same system (see [3]). Future Work: We now plan to finish the analysis of our ULCN 2005 solution, publish a paper describing it, and release the solution data on the web ([8]). Although difficult, given the lack of any higher accuracy data, we will attempt to quantify the horizontal 2 and vertical accuracy of this network. We will provide the topographic information in various formats, and also provide information for converting CLCN coordinates and CLCN registered images to the new system. The Lunar Orbiter digital mosaics now being generated [18] will also be registered to this system. Finally, we plan to continue to improve this network by the addition of the direct use of Mariner 10, Galileo, and Lunar Orbiter image measurements, and Clementine stereo [10]. We will also add ties to the current absolute LLR and ALSEP network [19]. It will be essential to further update and improve this network with data from future missions. This is necessary so that these new datasets can be compared to the prior data, particularly the Lunar Orbiter and Clementine multispectral products. References: [1] Archinal, B. A., et al. (2006). In preparation. [2] Archinal, B. A, et al. (2006). USGS Open File Report. In preparation. [3] Davies, M. E. et al. (1994) JGR, 99, E11, 23,211-23,214. [4] USGS (1997) Clementine Basemap Mosaic, USA_NASA_PDS_CL_30xx, NASA PDS. [5] USGS (1999) Clementine UVVIS Mosaic, USA_NASA_PDS_CL_40xx, NASA PDS. Eliason, E. M. et al. (1999), LPS XXX, Abstract #1933. [6] USGS, in publication. Eliason, E. (2003), LPS XXXIV, Abstract #2093. [7] Edwards, et al. (1996), LPS XXVII, 335-336. [8] http://astrogeology.usgs.gov/Projects/ControlNetworks/. [9] Malin, M. and M. Ravine (1998), Clementine High Resolution Camera Mosaicking Project, TR, Malin Space Science Systems San Diego. [10] Cook, A. C. et al. (2000), JGR, 105, E5, 12,023-12,033. [11] Cook, A. C. et al. (2002), AGU Fall Meeting, Abstract #P22D- 09. [12] Smith, D. E. et al. (1997), JGR, 102, E1, 1591-1611. [13] Rosiek, M. R. et al. (1998), LPS XXX, Abstract #1853. Rosiek, M. R., and Aeschliman, R. A. (2001) LPS XXXII, Abstract #1943. Rosiek, M. R. et al. (2001), Planetary Mapping 2001, ISPRS WG IV/9, http://astrogeology.usgs.gov/Projects/ISPRS/MEETINGS/. [14] Margot, J-L. C. (1999), PhD Thesis, Cornell University. [15] Wu, S. S. C. and Doyle, F. J. (1990), in Planetary Mapping, R. Greeley and R.M. Batson, eds., CUP, 169-207. [16] Nozette, S., et al. (1994), Science, 266, 1835-1839. [17] Zuber, M. T., et al. (1994) Science, 266, 1839-1843. [18] Weller, L., et al. (2006), LPS XXXVII, Abstract #2143. Also http://astrogeology.usgs.gov/Projects/LunarOrbiterDigitization/. [19] Davies, M. E. and Colvin, T. R. (2000), JGR, 105, E8, 20,277-20,280. 3

Tipping Points and Balancing Acts: Grand Challenges and Synergistic Opportunities of Integrating Research and Education, Science and Solutions

NASA Astrophysics Data System (ADS)

McCaffrey, M. S.; Stroeve, J. C.

2011-12-01

The "Grand Challenges" to address Global Change identified by the International Council for Science (ICSU) and its partners through the Earth System Sustainability Initiative-improving forecasting, enhancing and integrating observation systems, confining and minimizing global environmental change, responding effectively to change, as well as innovating and evaluating these efforts-require an integrative approach that engages and inspires society in general and young people in particular. What are some of the effective strategies-and stumbling blocks-in being able to make Earth System science and related sustainability efforts relevant and practical to non-technical audiences? Recent climate education projects have pioneered new strategies toward linking and infusing research with education, science with solutions. For example, the Climate Literacy and Energy Awareness Network (CLEAN), a National Science Digital Library Pathway funded by NSF, has approached this integral approach by "closing the loop" between climate and energy topics, identifying and annotating high quality online resources relating to the carbon cycle and related topics. The Inspiring Climate Education Excellence (ICEE) project, funded by NASA, offers professional development for teachers that infuses climate science with solutions as an emerging "best practice" while being sensitive to the emotional, psychological and political aspects of avoiding "gloom and doom" on one hand or advocating for particular policy solutions on another. Other examples includes NASA's climate website (http://climate.nasa.gov ), which serves as a robust, engaging portal for climate research and data, especially for educators. The recent PBS series Earth: The Operators' Manual and related book and website are other recent example of how climate science research, education and solutions can be incorporated in a way that is appealing and informative. The Alliance for Climate Education (ACE) has given assemblies in thousands of US high schools that integrate climate science and solutions in a way that inspires and informs youth, and similar programs exist internationally. Other approaches to prepare vulnerable communities, especially young people, for natural hazards and human-induced environmental change include programs such as Plan International's "Child Centered Disaster Risk Reduction- Building Resilience Through Participation," and their "Weathering the Storm" project, focusing on integrating the needs of teenage girls with climate change adaptation and risk reduction. While minimizing global environmental and climate change is crucial, these and related programs that weave research with education, science with solutions offer the potential for addressing the "Grand Challenges" by better preparing for societal and environmental tipping points through a more balanced and integrated approach to addressing change."

An improved global dynamic routing strategy for scale-free network with tunable clustering

NASA Astrophysics Data System (ADS)

Sun, Lina; Huang, Ning; Zhang, Yue; Bai, Yannan

2016-08-01

An efficient routing strategy can deliver packets quickly to improve the network capacity. Node congestion and transmission path length are inevitable real-time factors for a good routing strategy. Existing dynamic global routing strategies only consider the congestion of neighbor nodes and the shortest path, which ignores other key nodes’ congestion on the path. With the development of detection methods and techniques, global traffic information is readily available and important for the routing choice. Reasonable use of this information can effectively improve the network routing. So, an improved global dynamic routing strategy is proposed, which considers the congestion of all nodes on the shortest path and incorporates the waiting time of the most congested node into the path. We investigate the effectiveness of the proposed routing for scale-free network with different clustering coefficients. The shortest path routing strategy and the traffic awareness routing strategy only considering the waiting time of neighbor node are analyzed comparatively. Simulation results show that network capacity is greatly enhanced compared with the shortest path; congestion state increase is relatively slow compared with the traffic awareness routing strategy. Clustering coefficient increase will not only reduce the network throughput, but also result in transmission average path length increase for scale-free network with tunable clustering. The proposed routing is favorable to ease network congestion and network routing strategy design.

HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks.

PubMed

Hashemifar, Somaye; Xu, Jinbo

2014-09-01

High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency. This paper presents a novel global network alignment algorithm, denoted as HubAlign, that makes use of both network topology and sequence homology information, based upon the observation that topologically important proteins in a PPI network usually are much more conserved and thus, more likely to be aligned. HubAlign uses a minimum-degree heuristic algorithm to estimate the topological and functional importance of a protein from the global network topology information. Then HubAlign aligns topologically important proteins first and gradually extends the alignment to the whole network. Extensive tests indicate that HubAlign greatly outperforms several popular methods in terms of both accuracy and efficiency, especially in detecting functionally similar proteins. HubAlign is available freely for non-commercial purposes at http://ttic.uchicago.edu/∼hashemifar/software/HubAlign.zip. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

PubMed

Yang, S; Wang, D

2000-01-01

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

Beyond health aid: would an international equalization scheme for universal health coverage serve the international collective interest?

PubMed Central

2014-01-01

It has been argued that the international community is moving ‘beyond aid’. International co-financing in the international collective interest is expected to replace altruistically motivated foreign aid. The World Health Organization promotes ‘universal health coverage’ as the overarching health goal for the next phase of the Millennium Development Goals. In order to provide a basic level of health care coverage, at least some countries will need foreign aid for decades to come. If international co-financing of global public goods is replacing foreign aid, is universal health coverage a hopeless endeavor? Or would universal health coverage somehow serve the international collective interest? Using the Sustainable Development Solutions Network proposal to finance universal health coverage as a test case, we examined the hypothesis that national social policies face the threat of a ‘race to the bottom’ due to global economic integration and that this threat could be mitigated through international social protection policies that include international cross-subsidies – a kind of ‘equalization’ at the international level. The evidence for the race to the bottom theory is inconclusive. We seem to be witnessing a ‘convergence to the middle’. However, the ‘middle’ where ‘convergence’ of national social policies is likely to occur may not be high enough to keep income inequality in check. The implementation of the international equalization scheme proposed by the Sustainable Development Solutions Network would allow to ensure universal health coverage at a cost of US$55 in low income countries-the minimum cost estimated by the World Health Organization. The domestic efforts expected from low and middle countries are far more substantial than the international co-financing efforts expected from high income countries. This would contribute to ‘convergence’ of national social policies at a higher level. We therefore submit that the proposed international equalization scheme should not be considered as foreign aid, but rather as an international collective effort to protect and promote national social policy in times of global economic integration: thus serving the international collective interest. PMID:24886583

Travel times of P and S from the global digital seismic networks: Implications for the relative variation of P and S velocity in the mantle

USGS Publications Warehouse

Bolton, H.; Masters, G.

2001-01-01

We present new data sets of P and S arrival times which have been handpicked from long-period vertical and transverse component recordings of the various global seismic networks. Using events which occurred from 1976 to 1994 results in ???38,000 globally well-distributed measurements of teleseismic P and ???41,000 measurements of S. These data are particularly useful for looking at the relative variation of S and P velocities in the lower mantle. We describe both the measurement techniques and the gross characteristics of the data sets. The size of our data sets allows us to exploit the internal consistency of the data to identify outliers using a summary ray analysis. Since the polarity of each arrival is also known, we can construct fault plane solutions and J.or compare with polarities predicted by the Harvard centroid moment tensor solutions to further diagnose phase misidentification. This analysis results in ???5% of the data being identified as outliers. An analysis of variance indicates that the S residual travel times are dominated by the effects of three-dimensional structure but the P data have comparable contributions from noise and source mislocation effects. The summary ray analysis reveals the basic character of lower mantle structure, and there are large-scale patterns in both the S and P data sets that correlate quite well with each other. This analysis suggests that on average, d ln vS J.d. In vP is an increasing function of depth in the mantle going from a value of ???1.7 at the top of the lower mantle to an apparent value of 4 near the base of the mantle. This latter extreme value of R seems to result mainly from data which sample one region in the lowermost mantle under the central Pacific, where large positive S residuals are associated with very small P residuals. Such an anomaly cannot be thermal in origin. Copyright 2001 by the American Geophysical Union.