A new paradigm for particle tracking velocimetry, based on graph-theory and pulsed neural network

International Nuclear Information System (INIS)

Derou, D.; Herault, L.

1994-01-01

The Particle Tracking Velocimetry (PTV) technique works by recording, at different instances in time, positions of small tracers particles following a flow and illuminated by a sheet, or pseudo sheet, of light. It aims to recognize each particle trajectory, constituted of n different spots and determine thus each particle velocity vector. In this paper, we devise a new method, taking into account a global consistency of the trajectories to be extracted, in terms of visual perception and physical properties. It is based on a graph-theoretic formulation of the particle tracking problem and the use of an original neural network, called pulsed neural network. (authors). 4 figs

Collaborative In-Network Processing for Target Tracking

Directory of Open Access Journals (Sweden)

Juan Liu

2003-03-01

Full Text Available This paper presents a class of signal processing techniques for collaborative signal processing in ad hoc sensor networks, focusing on a vehicle tracking application. In particular, we study two types of commonly used sensors—acoustic-amplitude sensors for target distance estimation and direction-of-arrival sensors for bearing estimation—and investigate how networks of such sensors can collaborate to extract useful information with minimal resource usage. The information-driven sensor collaboration has several advantages: tracking is distributed, and the network is energy-efficient, activated only on a when-needed basis. We demonstrate the effectiveness of the approach to target tracking using both simulation and field data.

Robust visual tracking via multiscale deep sparse networks

Science.gov (United States)

Wang, Xin; Hou, Zhiqiang; Yu, Wangsheng; Xue, Yang; Jin, Zefenfen; Dai, Bo

2017-04-01

In visual tracking, deep learning with offline pretraining can extract more intrinsic and robust features. It has significant success solving the tracking drift in a complicated environment. However, offline pretraining requires numerous auxiliary training datasets and is considerably time-consuming for tracking tasks. To solve these problems, a multiscale sparse networks-based tracker (MSNT) under the particle filter framework is proposed. Based on the stacked sparse autoencoders and rectifier linear unit, the tracker has a flexible and adjustable architecture without the offline pretraining process and exploits the robust and powerful features effectively only through online training of limited labeled data. Meanwhile, the tracker builds four deep sparse networks of different scales, according to the target's profile type. During tracking, the tracker selects the matched tracking network adaptively in accordance with the initial target's profile type. It preserves the inherent structural information more efficiently than the single-scale networks. Additionally, a corresponding update strategy is proposed to improve the robustness of the tracker. Extensive experimental results on a large scale benchmark dataset show that the proposed method performs favorably against state-of-the-art methods in challenging environments.

Identifying Tracks Duplicates via Neural Network

CERN Document Server

Sunjerga, Antonio; CERN. Geneva. EP Department

2017-01-01

The goal of the project is to study feasibility of state of the art machine learning techniques in track reconstruction. Machine learning techniques provide promising ways to speed up the pattern recognition of tracks by adding more intelligence in the algorithms. Implementation of neural network to process of track duplicates identifying will be discussed. Different approaches are shown and results are compared to method that is currently in use.

Track classification within wireless sensor network

Science.gov (United States)

Doumerc, Robin; Pannetier, Benjamin; Moras, Julien; Dezert, Jean; Canevet, Loic

2017-05-01

In this paper, we present our study on track classification by taking into account environmental information and target estimated states. The tracker uses several motion model adapted to different target dynamics (pedestrian, ground vehicle and SUAV, i.e. small unmanned aerial vehicle) and works in centralized architecture. The main idea is to explore both: classification given by heterogeneous sensors and classification obtained with our fusion module. The fusion module, presented in his paper, provides a class on each track according to track location, velocity and associated uncertainty. To model the likelihood on each class, a fuzzy approach is used considering constraints on target capability to move in the environment. Then the evidential reasoning approach based on Dempster-Shafer Theory (DST) is used to perform a time integration of this classifier output. The fusion rules are tested and compared on real data obtained with our wireless sensor network.In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of this system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Comparison of home and away-from-home physical activity using accelerometers and cellular network-based tracking devices.

Science.gov (United States)

Ramulu, Pradeep Y; Chan, Emilie S; Loyd, Tara L; Ferrucci, Luigi; Friedman, David S

2012-08-01

Measuring physical at home and away from home is essential for assessing health and well-being, and could help design interventions to increase physical activity. Here, we describe how physical activity at home and away from home can be quantified by combining information from cellular network-based tracking devices and accelerometers. Thirty-five working adults wore a cellular network-based tracking device and an accelerometer for 6 consecutive days and logged their travel away from home. Performance of the tracking device was determined using the travel log for reference. Tracking device and accelerometer data were merged to compare physical activity at home and away from home. The tracking device detected 98.6% of all away-from-home excursions, accurately measured time away from home and demonstrated few prolonged signal drop-out periods. Most physical activity took place away from home on weekdays, but not on weekends. Subjects were more physically active per unit of time while away from home, particularly on weekends. Cellular network-based tracking devices represent an alternative to global positioning systems for tracking location, and provide information easily integrated with accelerometers to determine where physical activity takes place. Promoting greater time spent away from home may increase physical activity.

Development of target-tracking algorithms using neural network

Energy Technology Data Exchange (ETDEWEB)

Park, Dong Sun; Lee, Joon Whaoan; Yoon, Sook; Baek, Seong Hyun; Lee, Myung Jae [Chonbuk National University, Chonjoo (Korea)

1998-04-01

The utilization of remote-control robot system in atomic power plants or nuclear-related facilities grows rapidly, to protect workers form high radiation environments. Such applications require complete stability of the robot system, so that precisely tracking the robot is essential for the whole system. This research is to accomplish the goal by developing appropriate algorithms for remote-control robot systems. A neural network tracking system is designed and experimented to trace a robot Endpoint. This model is aimed to utilized the excellent capabilities of neural networks; nonlinear mapping between inputs and outputs, learning capability, and generalization capability. The neural tracker consists of two networks for position detection and prediction. Tracking algorithms are developed and experimented for the two models. Results of the experiments show that both models are promising as real-time target-tracking systems for remote-control robot systems. (author). 10 refs., 47 figs.

Siamese convolutional networks for tracking the spine motion

Science.gov (United States)

Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

2017-09-01

Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

Enhanced online convolutional neural networks for object tracking

Science.gov (United States)

Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

2018-04-01

In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

BackTrack testing wireless network security

CERN Document Server

Cardwell, Kevin

2013-01-01

Written in an easy-to-follow step-by-step format, you will be able to get started in next to no time with minimal effort and zero fuss.BackTrack: Testing Wireless Network Security is for anyone who has an interest in security and who wants to know more about wireless networks.All you need is some experience with networks and computers and you will be ready to go.

Elastic tracking versus neural network tracking for very high multiplicity problems

International Nuclear Information System (INIS)

Harlander, M.; Gyulassy, M.

1991-04-01

A new Elastic Tracking (ET) algorithm is proposed for finding tracks in very high multiplicity and noisy environments. It is based on a dynamical reinterpretation and generalization of the Radon transform and is related to elastic net algorithms for geometrical optimization. ET performs an adaptive nonlinear fit to noisy data with a variable number of tracks. Its numerics is more efficient than that of the traditional Radon or Hough transform method because it avoids binning of phase space and the costly search for valid minima. Spurious local minima are avoided in ET by introducing a time-dependent effective potential. The method is shown to be very robust to noise and measurement error and extends tracking capabilities to much higher track densities than possible via local road finding or even the novel Denby-Peterson neural network tracking algorithms. 12 refs., 2 figs

The Influence of Academic Tracking on Adolescent Social Networks

Science.gov (United States)

Fisher, Kim W.; Shogren, Karrie A.

2016-01-01

This study examined adolescents' social capital, through social network analyses (i.e., ego network analyses), in two high schools where students were placed into academic tracks adopted by the schools and shaped by disability status (i.e., general education, co-taught, segregated special education classrooms). The impact of academic tracks, as…

GSFC network operations with Tracking and Data Relay Satellites

Science.gov (United States)

Spearing, R.; Perreten, D. E.

The Tracking and Data Relay Satellite System (TDRSS) Network (TN) has been developed to provide services to all NASA User spacecraft in near-earth orbits. Three inter-relating entities will provide these services. The TN has been transformed from a network continuously changing to meet User specific requirements to a network which is flexible to meet future needs without significant changes in operational concepts. Attention is given to the evolution of the TN network, the TN capabilities-space segment, forward link services, tracking services, return link services, the three basic capabilities, single access services, multiple access services, simulation services, the White Sands Ground Terminal, the NASA communications network, and the network control center.

Global Operations Networks

DEFF Research Database (Denmark)

In the current context of global economic liberalisation and technological advancements, industrial companies are less likely to generate value in the traditional vertically integrated chain. Instead, they are doing so by means of elaborate cross-border and cross-organisational networks. As a rule......, these networks are configured on a global basis and consist of diverse and interdependent affiliates (linked both through ownership and non-equity relationships), which are engaged in an exchange of goods, services and information. The Scandinavian context is no exception to this trend. Nevertheless......, international comparative studies providing comprehensive insights from it are still rare. With the objective of bridging this gap, Global Operations Networks (GONE) project (sponsored by the Danish Research Council) brought together numerous academic and industrial partners from Denmark, Sweden and Finland...

Identifying and tracking dynamic processes in social networks

Science.gov (United States)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

Improving Global Multi-target Tracking with Local Updates

DEFF Research Database (Denmark)

Milan, Anton; Gade, Rikke; Dick, Anthony

2014-01-01

-target tracker, if they result in a reduction in the global cost function. Since tracking failures typically arise when targets become occluded, we propose a local data association scheme to maintain the target identities in these situations. We demonstrate a reduction of up to 50% in the global cost function...

Tests of track segment and vertex finding with neural networks

International Nuclear Information System (INIS)

Denby, B.; Lessner, E.; Lindsey, C.S.

1990-04-01

Feed forward neural networks have been trained, using back-propagation, to find the slopes of simulated track segments in a straw chamber and to find the vertex of tracks from both simulated and real events in a more conventional drift chamber geometry. Network architectures, training, and performance are presented. 12 refs., 7 figs

Network configuration of global R&D networks

DEFF Research Database (Denmark)

Hansen, Zaza Nadja Lee; Srai, Jagjit Singh

2011-01-01

, network configuration of global R&D has tended to focus on strategic elements with limited attention given operational effectiveness, or to interfaces with downstream manufacturing operations. Within OM literature, the drivers of configuration of global networks within, engineering, production, supply...... to R&D networks emerged, e.g. product features were more prominent in R&D networks. Furthermore, the study has shown extensive interaction with other operations, including many downstream manufacturing operations. By extending the OM configuration concepts to the configuration of R&D networks......Companies are increasingly globalising their R&D activities, both within the firms and with external partners, with consequent implications for their interaction with manufacturing operations. Previous research in R&D networks has focused on coordination, governance and support elements. However...

A framework for multi-object tracking over distributed wireless camera networks

Science.gov (United States)

Gau, Victor; Hwang, Jenq-Neng

2010-07-01

In this paper, we propose a unified framework targeting at two important issues in a distributed wireless camera network, i.e., object tracking and network communication, to achieve reliable multi-object tracking over distributed wireless camera networks. In the object tracking part, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping field of views without initial training. To effectively exchange the tracking information among the distributed cameras, we proposed an idle probability based broadcasting method, iPro, which adaptively adjusts the broadcast probability to improve the broadcast effectiveness in a dense saturated camera network. Experimental results for the multi-object tracking demonstrate the promising performance of our approach on real video sequences for cameras with overlapping and non-overlapping views. The modeling and ns-2 simulation results show that iPro almost approaches the theoretical performance upper bound if cameras are within each other's transmission range. In more general scenarios, e.g., in case of hidden node problems, the simulation results show that iPro significantly outperforms standard IEEE 802.11, especially when the number of competing nodes increases.

Tracking progress toward global polio eradication, 2010-2011.

Science.gov (United States)

2012-04-20

In January 2012, polio eradication was declared a "programmatic emergency for global public health" by the Executive Board of the World Health Organization (WHO). Since the Global Polio Eradication Initiative (GPEI) began in 1988, progress has been tracked by surveillance of acute flaccid paralysis (AFP) cases and testing of linked stool specimens for polioviruses (PVs) in WHO-accredited Global Polio Laboratory Network (GPLN) laboratories, complemented by sewage testing (environmental surveillance) in selected areas. Monitoring AFP surveillance quality at national and subnational administrative levels using standard performance indicators identifies potential gaps where PV circulation might go undetected; monitoring specimen transport and laboratory reporting timeliness identifies areas where reporting delays could lead to late response, permitting ongoing transmission. This report provides an assessment of 2010-2011 performance indicators for AFP surveillance at national and subnational levels in polio-affected countries and laboratory reporting at the regional level, updated from 2009-2010. Overall, 16 (62%) of 26 countries with circulating wild PV (WPV) met national AFP surveillance indicator targets during both 2010 and 2011. All three countries with reestablished WPV transmission and 16 of 19 countries with WPV outbreaks had substantial proportions (>20%) of their respective populations living in areas with underperforming surveillance during 2010 or 2011. Targets for timely reporting of PV isolation and type characterization results were met in three of six WHO regions in 2010 and five regions in 2011. To achieve polio eradication, efforts are needed to improve AFP surveillance and laboratory performance.

Tracking the global footprint of fisheries

Science.gov (United States)

Kroodsma, David A.; Mayorga, Juan; Hochberg, Timothy; Miller, Nathan A.; Boerder, Kristina; Ferretti, Francesco; Wilson, Alex; Bergman, Bjorn; White, Timothy D.; Block, Barbara A.; Woods, Paul; Sullivan, Brian; Costello, Christopher; Worm, Boris

2018-02-01

Although fishing is one of the most widespread activities by which humans harvest natural resources, its global footprint is poorly understood and has never been directly quantified. We processed 22 billion automatic identification system messages and tracked >70,000 industrial fishing vessels from 2012 to 2016, creating a global dynamic footprint of fishing effort with spatial and temporal resolution two to three orders of magnitude higher than for previous data sets. Our data show that industrial fishing occurs in >55% of ocean area and has a spatial extent more than four times that of agriculture. We find that global patterns of fishing have surprisingly low sensitivity to short-term economic and environmental variation and a strong response to cultural and political events such as holidays and closures.

Track finding with neural networks in ALICE ITS

International Nuclear Information System (INIS)

Batyunya, B.V.; Belikov, Yu.A.; Fedunov, A.G.; Zinchenko, A.I.

1996-01-01

A program based on Neural Networks technique was developed for track recognition in ALICE ITS. The efficiency of this program was estimated on Monte Carlo simulated events for particles with p T ≤ 100 MeV/c. The advantages of this program are the high performance, the capability of track finding in conditions of the high particle multiplicity and the ability to find tracks distorted by the multiple Coulomb scattering and the energy losses. 7 refs., 1 tab

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

Hopfield neural network in HEP track reconstruction

International Nuclear Information System (INIS)

Muresan, Raluca; Pentia, Mircea

1996-01-01

This work uses neural network technique (Hopfield method) to reconstruct particle tracks starting from a data set obtained with a coordinate detector system placed around a high energy accelerated particle interaction region. A learning algorithm for finding the optimal connection of the signal points have been elaborated and tested. We used a single layer neutral network with constraints in order to obtain the particle tracks drawn through the detected signal points. The dynamics of the systems is given by the MFT equations which determine the system evolution to a minimum energy function. We carried out a computing program that has been tested on a lot of Monte Carlo simulated data. With this program we obtained good results even for noise/signal ratio 200. (authors)

Real time track finding in a drift chamber with a VLSI neural network

International Nuclear Information System (INIS)

Lindsey, C.S.; Denby, B.; Haggerty, H.; Johns, K.

1992-01-01

In a test setup, a hardware neural network determined track parameters of charged particles traversing a drift chamber. Voltages proportional to the drift times in 6 cells of the 3-layer chamber were inputs to the Intel ETANN neural network chip which had been trained to give the slope and intercept of tracks. We compare network track parameters to those obtained from off-line track fits. To our knowledge this is the first on-line application of a VLSI neural network to a high energy physics detector. This test explored the potential of the chip and the practical problems of using it in a real world setting. We compare the chip performance to a neural network simulation on a conventional computer. We discuss possible applications of the chip in high energy physics detector triggers. (orig.)

PEAK TRACKING WITH A NEURAL NETWORK FOR SPECTRAL RECOGNITION

NARCIS (Netherlands)

COENEGRACHT, PMJ; METTING, HJ; VANLOO, EM; SNOEIJER, GJ; DOORNBOS, DA

1993-01-01

A peak tracking method based on a simulated feed-forward neural network with back-propagation is presented. The network uses the normalized UV spectra and peak areas measured in one chromatogram for peak recognition. It suffices to train the network with only one set of spectra recorded in one

Global tree network for computing structures enabling global processing operations

Science.gov (United States)

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.

Radiology film tracking in a distributed clinical network

International Nuclear Information System (INIS)

Marquette, D.D.; Arrildt, W.

1985-01-01

This paper describes a system for tracking radiology films designed and installed at the Johns Hopkins Hospital. The installation of database and network capabilities in a large hospital environment provide the opportunity to extend to all nursing units and clinics access to the hospital's film tracking system. Ethernet communication technology allows communication to remote libraries. The integration of film tracking with scheduling and order entry systems in radiology make it possible to attain a high level of automated database interface and film jacket label production

Data fusion for target tracking and classification with wireless sensor network

Science.gov (United States)

Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

2016-10-01

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Conducting swift heavy ion track networks

Czech Academy of Sciences Publication Activity Database

Fink, Dietmar; Kiv, A.; Fuks, D.; Vacík, Jiří; Hnatowicz, Vladimír; Chandra, A.; Saad, A.

2010-01-01

Roč. 165, č. 3 (2010), s. 227-244 ISSN 1042-0150 R&D Projects: GA AV ČR(CZ) KAN400480701 Institutional research plan: CEZ:AV0Z10480505 Keywords : ion tracks * negative differential resistance * neural networks Subject RIV: JJ - Other Materials Impact factor: 0.660, year: 2010

Global Operations Networks in Motion

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Jørgensen, Claus; Wæhrens, Brian Vejrum

2009-01-01

This paper addresses the phenomenon of global operations networks and how they change over time. The paper is based on the cases of three Danish companies and their global operations networks. It finds a number of common patterns highlighting some organisational effects and managerial challenges...... the companies face regarding rapid changes in their networks configurations and capabilities. The paper details the variables determining these changes and suggests how the on-going interplay between the focal organisation, its network partners, and their various contextual conditions can be approached....

Charged particle track reconstruction using artificial neural networks

International Nuclear Information System (INIS)

Glover, C.; Fu, P.; Gabriel, T.; Handler, T.

1992-01-01

This paper summarizes the current state of our research in developing and applying artificial neural network (ANN) algorithm described here is based on a crude model of the retina. It takes as input the coordinates of each charged particle's interaction point (''hit'') in the tracking chamber. The algorithm's output is a set of vectors pointing to other hits that most likely to form a track

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

Science.gov (United States)

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.

Almost-global tracking for a rigid body with internal rotors

OpenAIRE

Nayak, Aradhana; Banavar, Ravi N.

2017-01-01

Almost-global orientation trajectory tracking for a rigid body with external actuation has been well studied in the literature, and in the geometric setting as well. The tracking control law relies on the fact that a rigid body is a simple mechanical system (SMS) on the $3-$dimensional group of special orthogonal matrices. However, the problem of designing feedback control laws for tracking using internal actuation mechanisms, like rotors or control moment gyros, has received lesser attention...

Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Suliang Ma

2016-11-01

Full Text Available Photovoltaic (PV systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP. Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL non-linear controller combined with an artificial neural network (ANN is proposed. This approach linearizes the non-linear characteristics in PV systems and DC/DC converters, for tracking and optimizing the PV system operation. It also reduces the dependency of the designed controller on linearized models, to provide global stability. A complete model of the PV system is simulated. The existing maximum power-point tracking (MPPT and DC/DC boost-converter controller techniques are compared with the proposed ANN method. Two case studies, which simulate realistic circumstances, are presented to demonstrate the effectiveness and superiority of the proposed method. The AFL with ANN controller can provide good dynamic operation, faster convergence speed, and fewer operating-point oscillations around the MPP. It also tracks the global maxima under different conditions, especially irradiance-mutating situations, more effectively than the conventional methods. Detailed mathematical models and a control approach for a three-phase grid-connected intelligent hybrid system are proposed using MATLAB/Simulink.

Efficient and Adaptive Node Selection for Target Tracking in Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Juan Feng

2016-01-01

Full Text Available In target tracking wireless sensor network, choosing the proper working nodes can not only minimize the number of active nodes, but also satisfy the tracking reliability requirement. However, most existing works focus on selecting sensor nodes which are the nearest to the target for tracking missions and they did not consider the correlation of the location of the sensor nodes so that these approaches can not meet all the goals of the network. This work proposes an efficient and adaptive node selection approach for tracking a target in a distributed wireless sensor network. The proposed approach combines the distance-based node selection strategy and particle filter prediction considering the spatial correlation of the different sensing nodes. Moreover, a joint distance weighted measurement is proposed to estimate the information utility of sensing nodes. Experimental results show that EANS outperformed the state-of-the-art approaches by reducing the energy cost and computational complexity as well as guaranteeing the tracking accuracy.

Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Feng Juan

2013-10-01

Full Text Available Energy efficiency is very important for wireless sensor networks (WSNs since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual-grid-based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.

Computer Networks and Globalization

Directory of Open Access Journals (Sweden)

J. Magliaro

2007-07-01

Full Text Available Communication and information computer networks connect the world in ways that make globalization more natural and inequity more subtle. As educators, we look at these phenomena holistically analyzing them from the realist’s view, thus exploring tensions, (in equity and (injustice, and from the idealist’s view, thus embracing connectivity, convergence and development of a collective consciousness. In an increasingly market- driven world we find examples of openness and human generosity that are based on networks, specifically the Internet. After addressing open movements in publishing, software industry and education, we describe the possibility of a dialectic equilibrium between globalization and indigenousness in view of ecologically designed future smart networks

Railway track circuit fault diagnosis using recurrent neural networks

NARCIS (Netherlands)

de Bruin, T.D.; Verbert, K.A.J.; Babuska, R.

2017-01-01

Timely detection and identification of faults in railway track circuits are crucial for the safety and availability of railway networks. In this paper, the use of the long-short-term memory (LSTM) recurrent neural network is proposed to accomplish these tasks based on the commonly available

State Support: A Prerequisite for Global Health Network Effectiveness; Comment on “Four Challenges that Global Health Networks Face”

Directory of Open Access Journals (Sweden)

Robert Marten

2018-03-01

Full Text Available 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.

The Motus Wildlife Tracking System: a collaborative research network to enhance the understanding of wildlife movement

Directory of Open Access Journals (Sweden)

Philip D. Taylor

2017-06-01

Full Text Available We describe a new collaborative network, the Motus Wildlife Tracking System (Motus; https://motus.org, which is an international network of researchers using coordinated automated radio-telemetry arrays to study movements of small flying organisms including birds, bats, and insects, at local, regional, and hemispheric scales. Radio-telemetry has been a cornerstone of tracking studies for over 50 years, and because of current limitations of geographic positioning systems (GPS and satellite transmitters, has remained the primary means to track movements of small animals with high temporal and spatial precision. Automated receivers, along with recent miniaturization and digital coding of tags, have further improved the utility of radio-telemetry by allowing many individuals to be tracked continuously and simultaneously across broad landscapes. Motus is novel among automated arrays in that collaborators employ a single radio frequency across receiving stations over a broad geographic scale, allowing individuals to be detected at sites maintained by others. Motus also coordinates, disseminates, and archives detections and associated metadata in a central repository. Combined with the ability to track many individuals simultaneously, Motus has expanded the scope and spatial scale of research questions that can be addressed using radio-telemetry from local to regional and even hemispheric scales. Since its inception in 2012, more than 9000 individuals of over 87 species of birds, bats, and insects have been tracked, resulting in more than 250 million detections. This rich and comprehensive dataset includes detections of individuals during all phases of the annual cycle (breeding, migration, and nonbreeding, and at a variety of spatial scales, resulting in novel insights into the movement behavior of small flying animals. The value of the Motus network will grow as spatial coverage of stations and number of partners and collaborators increases. With

Global fluctuations of cerebral blood flow indicate a global brain network independent of systemic factors.

Science.gov (United States)

Zhao, Li; Alsop, David C; Detre, John A; Dai, Weiying

2017-01-01

Global synchronization across specialized brain networks is a common feature of network models and in-vivo electrical measurements. Although the imaging of specialized brain networks with blood oxygenation sensitive resting state functional magnetic resonance imaging (rsfMRI) has enabled detailed study of regional networks, the study of globally correlated fluctuations with rsfMRI is confounded by spurious contributions to the global signal from systemic physiologic factors and other noise sources. Here we use an alternative rsfMRI method, arterial spin labeled perfusion MRI, to characterize global correlations and their relationship to correlations and anti-correlations between regional networks. Global fluctuations that cannot be explained by systemic factors dominate the fluctuations in cerebral blood flow. Power spectra of these fluctuations are band limited to below 0.05 Hz, similar to prior measurements of regional network fluctuations in the brain. Removal of these global fluctuations prior to measurement of regional networks reduces all regional network fluctuation amplitudes to below the global fluctuation amplitude and changes the strength and sign of inter network correlations. Our findings support large amplitude, globally synchronized activity across networks that require a reassessment of regional network amplitude and correlation measures.

Moving target tracking through distributed clustering in directional sensor networks.

Science.gov (United States)

Enayet, Asma; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Almogren, Ahmad; Alamri, Atif

2014-12-18

The problem of moving target tracking in directional sensor networks (DSNs) introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target's location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works.

Moving Target Tracking through Distributed Clustering in Directional Sensor Networks

Directory of Open Access Journals (Sweden)

Asma Enayet

2014-12-01

Full Text Available The problem of moving target tracking in directional sensor networks (DSNs introduces new research challenges, including optimal selection of sensing and communication sectors of the directional sensor nodes, determination of the precise location of the target and an energy-efficient data collection mechanism. Existing solutions allow individual sensor nodes to detect the target’s location through collaboration among neighboring nodes, where most of the sensors are activated and communicate with the sink. Therefore, they incur much overhead, loss of energy and reduced target tracking accuracy. In this paper, we have proposed a clustering algorithm, where distributed cluster heads coordinate their member nodes in optimizing the active sensing and communication directions of the nodes, precisely determining the target location by aggregating reported sensing data from multiple nodes and transferring the resultant location information to the sink. Thus, the proposed target tracking mechanism minimizes the sensing redundancy and maximizes the number of sleeping nodes in the network. We have also investigated the dynamic approach of activating sleeping nodes on-demand so that the moving target tracking accuracy can be enhanced while maximizing the network lifetime. We have carried out our extensive simulations in ns-3, and the results show that the proposed mechanism achieves higher performance compared to the state-of-the-art works.

Managing Evolving Global Operations Networks

DEFF Research Database (Denmark)

Mykhaylenko, Alona; Wæhrens, Brian Vejrum; Johansen, John

2015-01-01

For many globally dispersed organisations, the home base (HB) is a historic locus of integrative and coordinating efforts that safeguard overall performance. However, the dynamism of global operations networks is increasingly pulling the centre of gravity away from the HB and dispersing it across...... the network, challenging the HB’s ability to sustain its centrality over time. To counteract this tendency, this paper addresses the gap in the literature regarding the development of the network management capability of the HB within the context of its network. Data was collected through a retrospective...... longitudinal case study of an intra-organisational operations network of one OEM and its three foreign subsidiaries. The findings suggest a row of strategic roles and corresponding managerial capabilities, which the HB needs to develop depending on the changing subsidiaries’ competencies and HB...

The scheduling of tracking times for interplanetary spacecraft on the Deep Space Network

Science.gov (United States)

Webb, W. A.

1978-01-01

The Deep Space Network (DSN) is a network of tracking stations, located throughout the globe, used to track spacecraft for NASA's interplanetary missions. This paper describes a computer program, DSNTRAK, which provides an optimum daily tracking schedule for the DSN given the view periods at each station for a mission set of n spacecraft, where n is between 2 and 6. The objective function is specified in terms of relative total daily tracking time requirements between the n spacecraft. Linear programming is used to maximize the total daily tracking time and determine an optimal daily tracking schedule consistent with DSN station capabilities. DSNTRAK is used as part of a procedure to provide DSN load forecasting information for proposed future NASA mission sets.

Labour in Global Production Networks

DEFF Research Database (Denmark)

Lund-Thomsen, Peter; Nadvi, Khalid; Chan, Anita

A critical challenge facing developing country producers is to meet international labour standards and codes of conduct in order to engage in global production networks. Evidence of gains for workers from compliance with such standards and codes remains limited and patchy. This paper focuses...... on the global football industry, a sector dominated by leading global brands who manage dispersed global production networks. It assesses the work conditions for football stitchers engaged in different forms of work organisation, factories, stitching centres, and home-based settings, in Pakistan, India......, and China. It draws on detailed qualitative primary field research with football stitching workers and producers in these three countries. The paper explains how, and why, work conditions of football stitchers differ across these locations through an analytical framework that interweaves both global...

Global action networks: agents for collective action

NARCIS (Netherlands)

Glasbergen, P.

2010-01-01

Global action networks (GANs) are civil society initiated multi-stakeholder arrangements that aim to fulfill a leadership role for systemic change in global governance for sustainable development. The paper develops a network approach to study some of these GANs as motivators of global collective

Global Electricity Trade Network: Structures and Implications

Science.gov (United States)

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

Research on Key Technologies of Network Centric System Distributed Target Track Fusion

Directory of Open Access Journals (Sweden)

Yi Mao

2017-01-01

Full Text Available To realize common tactical picture in network-centered system, this paper proposes a layered architecture for distributed information processing and a method for distributed track fusion on the basis of analyzing the characteristics of network-centered systems. Basing on the noncorrelation of three-dimensional measurement of surveillance and reconnaissance sensors under polar coordinates, it also puts forward an algorithm for evaluating track quality (TQ using statistical decision theory. According to simulation results, the TQ value is associated with the measurement accuracy of sensors and the motion state of targets, which is well matched with the convergence process of tracking filters. Besides, the proposed algorithm has good reliability and timeliness in track quality evaluation.

Moving Target Detection and Active Tracking with a Multicamera Network

Directory of Open Access Journals (Sweden)

Long Zhao

2014-01-01

Full Text Available We propose a systematic framework for Intelligence Video Surveillance System (IVSS with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. The target detection and tracking is realized by fixed cameras using a moving target detection and tracking algorithm; the PTZ camera is manoeuvred to actively track the target from the tracking results of the static camera. The experiments are carried out using practical surveillance system data, and the experimental results show that the systematic framework and algorithms presented in this paper are efficient.

The UNESCO Global Network of National Geoparks

Science.gov (United States)

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.

Optical track width measurements below 100 nm using artificial neural networks

Science.gov (United States)

Smith, R. J.; See, C. W.; Somekh, M. G.; Yacoot, A.; Choi, E.

2005-12-01

This paper discusses the feasibility of using artificial neural networks (ANNs), together with a high precision scanning optical profiler, to measure very fine track widths that are considerably below the conventional diffraction limit of a conventional optical microscope. The ANN is trained using optical profiles obtained from tracks of known widths, the network is then assessed by applying it to test profiles. The optical profiler is an ultra-stable common path scanning interferometer, which provides extremely precise surface measurements. Preliminary results, obtained with a 0.3 NA objective lens and a laser wavelength of 633 nm, show that the system is capable of measuring a 50 nm track width, with a standard deviation less than 4 nm.

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

Science.gov (United States)

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

A Network of Networks Perspective on Global Trade.

Science.gov (United States)

Maluck, Julian; Donner, Reik V

2015-01-01

Mutually intertwined supply chains in contemporary economy result in a complex network of trade relationships with a highly non-trivial topology that varies with time. In order to understand the complex interrelationships among different countries and economic sectors, as well as their dynamics, a holistic view on the underlying structural properties of this network is necessary. This study employs multi-regional input-output data to decompose 186 national economies into 26 industry sectors and utilizes the approach of interdependent networks to analyze the substructure of the resulting international trade network for the years 1990-2011. The partition of the network into national economies is observed to be compatible with the notion of communities in the sense of complex network theory. By studying internal versus cross-subgraph contributions to established complex network metrics, new insights into the architecture of global trade are obtained, which allow to identify key elements of global economy. Specifically, financial services and business activities dominate domestic trade whereas electrical and machinery industries dominate foreign trade. In order to further specify each national sector's role individually, (cross-)clustering coefficients and cross-betweenness are obtained for different pairs of subgraphs. The corresponding analysis reveals that specific industrial sectors tend to favor distinct directionality patterns and that the cross-clustering coefficient for geographically close country pairs is remarkably high, indicating that spatial factors are still of paramount importance for the organization of trade patterns in modern economy. Regarding the evolution of the trade network's substructure, globalization is well-expressed by trends of several structural characteristics (e.g., link density and node strength) in the interacting network framework. Extreme events, such as the financial crisis 2008/2009, are manifested as anomalies superimposed to

Performance analysis of tracked panel according to predicted global radiation

International Nuclear Information System (INIS)

Chang, T.P.

2009-01-01

In this paper, the performance of a south facing single-axis tracked panel was analyzed according to global radiation predicted by empirical model. Mathematic expressions appropriate for single-axis tracking system were derived to calculate the radiation on it. Instantaneous increments of solar energy collected by the tracked panel relative to fixed panel are illustrated. The validity of the empirical model to Taiwan area will also be examined with the actual irradiation data observed in Taipei. The results are summarized as follows: the gains made by the tracked panel relative to a fixed panel are between 20.0% and 33.9% for four specified days of year, between 20.9% and 33.2% for the four seasons and 27.6% over the entire year. For latitudes below 65 deg., the yearly optimal tilt angle of a fixed panel is close to 0.8 times latitude, the irradiation ratio of the tracked panel to the fixed panel is about 1.3, which are smaller than the corresponding values calculated from extraterrestrial radiation, suggesting us that the installation angle should be adjusted toward a flatter angle and that the gain of the tracked panel will reduce while it works in cloudy climate or in air pollution environment. Although the captured radiation increases with the maximal rotation angle of panel, but the benefit on the global radiation case is still not so good as that on extraterrestrial radiation case. The irradiation data observed is much less than the data predicted by the empirical model, however the trend of fitting curve to the observed data is somewhat in agreement with that to the predicted one; the yearly gain is 14.3% when a tracked panel is employed throughout the year.

The Ocean Tracking Network and its contribution to ocean biological observation

Science.gov (United States)

Whoriskey, F. G.

2016-02-01

Animals move to meet their needs for food, shelter, reproduction and to avoid unfavorable environments. In aquatic systems, it is essential that we understand these movements if we are to sustainably manage populations and maintain healthy ecosystems. Thus the ability to document and monitor changes in aquatic animal movements is a biological observing system need. The Ocean Tracking Network (OTN) is a global research, technology development, and data management platform headquartered at Dalhousie University, in Halifax, Nova Scotia working to fill this need. OTN uses electronic telemetry to document the local-to-global movements and survival of aquatic animals, and to correlate them to oceanographic or limnological variables that are influencing movements. Such knowledge can assist with planning for and managing of anthropogenic impacts on present and future animal distributions, including those due to climate change. OTN works with various tracking methods including satellite and data storage tag systems, but its dominant focus is acoustic telemetry. OTN is built on global partnerships for the sharing of equipment and data, and has stimulated technological development in telemetry by bringing researchers with needs for new capabilities together with manufacturers to generate, test, and operationalize new technologies. This has included pioneering work into the use of marine autonomous vehicles (Slocum electric gliders; Liquid Robotics Wave Glider) in animal telemetry research. Similarly, OTN scientists worked with the Sea Mammal Research Unit to develop mobile acoustic receiver that have been placed on grey seals and linked via Bluetooth to a satellite transmitter/receiver. This provided receiver coverage in areas occupied by the seals during their typically extensive migrations and allowed for the examination of ecosystem linkages by documenting behavioral interactions the seals had with the physical environment, conspecifics, and other tagged species.

A Network of Networks Perspective on Global Trade

Science.gov (United States)

Maluck, Julian; Donner, Reik V.

2015-01-01

Mutually intertwined supply chains in contemporary economy result in a complex network of trade relationships with a highly non-trivial topology that varies with time. In order to understand the complex interrelationships among different countries and economic sectors, as well as their dynamics, a holistic view on the underlying structural properties of this network is necessary. This study employs multi-regional input-output data to decompose 186 national economies into 26 industry sectors and utilizes the approach of interdependent networks to analyze the substructure of the resulting international trade network for the years 1990–2011. The partition of the network into national economies is observed to be compatible with the notion of communities in the sense of complex network theory. By studying internal versus cross-subgraph contributions to established complex network metrics, new insights into the architecture of global trade are obtained, which allow to identify key elements of global economy. Specifically, financial services and business activities dominate domestic trade whereas electrical and machinery industries dominate foreign trade. In order to further specify each national sector’s role individually, (cross-)clustering coefficients and cross-betweenness are obtained for different pairs of subgraphs. The corresponding analysis reveals that specific industrial sectors tend to favor distinct directionality patterns and that the cross-clustering coefficient for geographically close country pairs is remarkably high, indicating that spatial factors are still of paramount importance for the organization of trade patterns in modern economy. Regarding the evolution of the trade network’s substructure, globalization is well-expressed by trends of several structural characteristics (e.g., link density and node strength) in the interacting network framework. Extreme events, such as the financial crisis 2008/2009, are manifested as anomalies superimposed

Tracking Mobile Robot in Indoor Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Liping Zhang

2014-01-01

Full Text Available This work addresses the problem of tracking mobile robots in indoor wireless sensor networks (WSNs. Our approach is based on a localization scheme with RSSI (received signal strength indication which is used widely in WSN. The developed tracking system is designed for continuous estimation of the robot’s trajectory. A WSN, which is composed of many very simple and cheap wireless sensor nodes, is deployed at a specific region of interest. The wireless sensor nodes collect RSSI information sent by mobile robots. A range-based data fusion scheme is used to estimate the robot’s trajectory. Moreover, a Kalman filter is designed to improve tracking accuracy. Experiments are provided to assess the performance of the proposed scheme.

Tracking progress toward global polio eradication--worldwide, 2009-2010.

Science.gov (United States)

2011-04-15

Since the Global Polio Eradication Initiative (GPEI) began in 1988, progress has been tracked by 1) surveillance comprised of detection and investigation of cases of acute flaccid paralysis (AFP), coupled with environmental surveillance (sewage testing) in selected areas, and 2) timely testing of fecal specimens in accredited laboratories to identify polioviruses. The sensitivity of AFP case detection and the timeliness of AFP investigations are monitored with performance indicators. Polioviruses are isolated and characterized by the Global Polio Laboratory Network (GPLN). This report assesses the quality of polio surveillance and the timeliness of poliovirus isolation reporting and characterization worldwide during 2009--2010. During that period, 77% of countries affected by wild poliovirus (WPV) met national performance standards for AFP surveillance; underperforming subnational areas were identified in two of four countries with reestablished WPV transmission and in 13 of 22 countries with WPV outbreaks. Targets for timely GPLN reporting of poliovirus isolation results were met in five World Health Organization (WHO) regions in 2009 and in four of six regions in 2010; targets for timely poliovirus characterization were met in four WHO regions in 2009 and in five regions in 2010. Monitoring of surveillance performance indicators at subnational levels continues to be critical to identifying surveillance gaps that might allow WPV circulation to be missed in certain areas or subpopulations. To achieve polio eradication, efforts are needed to further strengthen AFP surveillance, implement targeted environmental surveillance, and ensure that GPLN quality is maintained.

Controlled neural network application in track-match problem

International Nuclear Information System (INIS)

Baginyan, S.A.; Ososkov, G.A.

1993-01-01

Track-match problem of high energy physics (HEP) data handling is formulated in terms of incidence matrices. The corresponding Hopfield neural network is developed to solve this type of constraint satisfaction problems (CSP). A special concept of the controlled neural network is proposed as a basis of an algorithm for the effective CSP solution. Results of comparable calculations show the very high performance of this algorithm against conventional search procedures. 8 refs.; 1 fig.; 1 tab

Recognition of decays of charged tracks with neural network techniques

International Nuclear Information System (INIS)

Stimpfl-Abele, G.

1991-01-01

We developed neural-network learning techniques for the recognition of decays of charged tracks using a feed-forward network with error back-propagation. Two completely different methods are described in detail and their efficiencies for several NN architectures are compared with conventional methods. Excellent results are obtained. (orig.)

Ensuring dynamic strategic fit of firms that compete globally in alliances and networks: proposing the Global SNA - Strategic Network Analysis - framework

Directory of Open Access Journals (Sweden)

T. Diana L. Van Aduard de Macedo-Soares

2011-02-01

Full Text Available In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

Logistical networking: a global storage network

International Nuclear Information System (INIS)

Beck, Micah; Moore, Terry

2005-01-01

The absence of an adequate distributed storage infrastructure for data buffering has become a significant impediment to the flow of work in the wide area, data intensive collaborations that are increasingly characteristic of leading edge research in several fields. One solution to this problem, pioneered under DOE's SciDAC program, is Logistical Networking, which provides a framework for a globally scalable, maximally interoperable storage network based on the Internet Backplane Protocol (IBP). This paper provides a brief overview of the Logistical Networking (LN) architecture, the middleware developed to exploit its value, and a few of the applications that some of research communities have made of it

Neural network fusion capabilities for efficient implementation of tracking algorithms

Science.gov (United States)

Sundareshan, Malur K.; Amoozegar, Farid

1997-03-01

The ability to efficiently fuse information of different forms to facilitate intelligent decision making is one of the major capabilities of trained multilayer neural networks that is now being recognized. While development of innovative adaptive control algorithms for nonlinear dynamical plants that attempt to exploit these capabilities seems to be more popular, a corresponding development of nonlinear estimation algorithms using these approaches, particularly for application in target surveillance and guidance operations, has not received similar attention. We describe the capabilities and functionality of neural network algorithms for data fusion and implementation of tracking filters. To discuss details and to serve as a vehicle for quantitative performance evaluations, the illustrative case of estimating the position and velocity of surveillance targets is considered. Efficient target- tracking algorithms that can utilize data from a host of sensing modalities and are capable of reliably tracking even uncooperative targets executing fast and complex maneuvers are of interest in a number of applications. The primary motivation for employing neural networks in these applications comes from the efficiency with which more features extracted from different sensor measurements can be utilized as inputs for estimating target maneuvers. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The innovation lies in the way the fusion of multisensor data is accomplished to facilitate improved estimation without increasing the computational complexity of the dynamical state estimator itself.

Solidarity Action in Global Labor Networks

DEFF Research Database (Denmark)

Wad, Peter

2014-01-01

Globalization transforms workforces of transnational corporation from predominantly home countrydominated workforces into foreign-dominated, multinational workforces. Thus, the national grounding of trade unions as the key form of labor organizing is challenged by new multinational compositions...... and cross-border relocations of corporate employment affecting working conditions of employees and trade unions in local places. We assume that economic globalization is characterized by expanding global corporate network of vertically and horizontally integrated (equity-based) and disintegrated (nonequity......-based) value chains. We also assume that globalization can both impede and enable labor empowerment. Based on these premises the key question is, how can labor leverage effective power against management in global corporate networks? This question is split into two subquestions: a) How can labor theoretically...

A lightweight target-tracking scheme using wireless sensor network

International Nuclear Information System (INIS)

Kuang, Xing-hong; Shao, Hui-he; Feng, Rui

2008-01-01

This paper describes a lightweight target-tracking scheme using wireless sensor network, where randomly distributed sensor nodes take responsibility for tracking the moving target based on the acoustic sensing signal. At every localization interval, a backoff timer algorithm is performed to elect the leader node and determine the transmission order of the localization nodes. An adaptive active region size algorithm based on the node density is proposed to select the optimal nodes taking part in localization. An improved particle filter algorithm performed by the leader node estimates the target state based on the selected nodes' acoustic energy measurements. Some refinements such as optimal linear combination algorithm, residual resampling algorithm, Markov chain Monte Carlo method are introduced in the scheme to improve the tracking performance. Simulation results validate the efficiency of the proposed tracking scheme

Strabismus Recognition Using Eye-Tracking Data and Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Zenghai Chen

2018-01-01

Full Text Available Strabismus is one of the most common vision diseases that would cause amblyopia and even permanent vision loss. Timely diagnosis is crucial for well treating strabismus. In contrast to manual diagnosis, automatic recognition can significantly reduce labor cost and increase diagnosis efficiency. In this paper, we propose to recognize strabismus using eye-tracking data and convolutional neural networks. In particular, an eye tracker is first exploited to record a subject’s eye movements. A gaze deviation (GaDe image is then proposed to characterize the subject’s eye-tracking data according to the accuracies of gaze points. The GaDe image is fed to a convolutional neural network (CNN that has been trained on a large image database called ImageNet. The outputs of the full connection layers of the CNN are used as the GaDe image’s features for strabismus recognition. A dataset containing eye-tracking data of both strabismic subjects and normal subjects is established for experiments. Experimental results demonstrate that the natural image features can be well transferred to represent eye-tracking data, and strabismus can be effectively recognized by our proposed method.

Robust Myocardial Motion Tracking for Echocardiography: Variational Framework Integrating Local-to-Global Deformation

Directory of Open Access Journals (Sweden)

Chi Young Ahn

2013-01-01

Full Text Available This paper proposes a robust real-time myocardial border tracking algorithm for echocardiography. Commonly, after an initial contour of LV border is traced at one or two frames from the entire cardiac cycle, LV contour tracking is performed over the remaining frames. Among a variety of tracking techniques, optical flow method is the most widely used for motion estimation of moving objects. However, when echocardiography data is heavily corrupted in some local regions, the errors bring the tracking point out of the endocardial border, resulting in distorted LV contours. This shape distortion often occurs in practice since the data acquisition is affected by ultrasound artifacts, dropouts, or shadowing phenomena of cardiac walls. The proposed method is designed to deal with this shape distortion problem by integrating local optical flow motion and global deformation into a variational framework. The proposed descent method controls the individual tracking points to follow the local motions of a specific speckle pattern, while their overall motions are confined to the global motion constraint being approximately an affine transform of the initial tracking points. Many real experiments show that the proposed method achieves better overall performance than conventional methods.

MANAGING GLOBAL OPERATIONS NETWORKS IN MOTION

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Jørgensen, Claus; Sørensen, Brian Vejrum

2008-01-01

capabilities and intensified need for transfer, assimilation and augmentation of activities and know-how within the network. Based on these the paper highlights some organisational effects and managerial challenges the companies face regarding rapid changes in their networks configurations and capabilities.......Most industrial companies are, for reasons related to cost, market access or knowledge, working with some aspect of offshore operations. This may take form of captive operations or through outsourcing of activities overseas. With this trend, global operations networks are emerging resulting...... in corporate strategic repositioning, re-configurations of sites, and changes to the underlying capabilities. The paper is based on cases of 3 Danish companies and their global supply networks. These networks are not in a steady state, they evolve as a consequence of the ongoing co-evolution between the focal...

Use of artificial neural networks on optical track width measurements

Science.gov (United States)

Smith, Richard J.; See, Chung W.; Somekh, Mike G.; Yacoot, Andrew

2007-08-01

We have demonstrated recently that, by using an ultrastable optical interferometer together with artificial neural networks (ANNs), track widths down to 60 nm can be measured with a 0.3 NA objective lens. We investigate the effective conditions for training ANNs. Experimental results will be used to show the characteristics of the training samples and the data format of the ANN inputs required to produce suitably trained ANNs. Results obtained with networks measuring double tracks, and classifying different structures, will be presented to illustrate the capability of the technique. We include a discussion on expansion of the application areas of the system, allowing it to be used as a general purpose instrument.

Track finding in a Time Projection Chamber with a neural network

International Nuclear Information System (INIS)

Espe, I.; Engeland, T.

1994-03-01

A Hopfield neutral network has been designed in order to reproduce particle tracks in electric and magnetic fields. The main goal is to reproduce tracks from particles in a relativistic heavy ion CERN experiment. In the present work properties of the system are investigated on simulated data. 6 refs., 14 figs., 9 tabs

Strategic Knowledge Networks for Global Education

Science.gov (United States)

Peterson, J. Fiona

2009-01-01

The inherent opportunities for communication, collaboration and experiential learning in an online and global network create the impetus for the new network paradigm in higher education. A strategic knowledge network in education was designed and developed to build "Mode 2" knowledge capabilities; create new knowledge for innovative…

Launch vehicle tracking enhancement through Global Positioning System Metric Tracking

Science.gov (United States)

Moore, T. C.; Li, Hanchu; Gray, T.; Doran, A.

United Launch Alliance (ULA) initiated operational flights of both the Atlas V and Delta IV launch vehicle families in 2002. The Atlas V and Delta IV launch vehicles were developed jointly with the US Air Force (USAF) as part of the Evolved Expendable Launch Vehicle (EELV) program. Both Launch Vehicle (LV) families have provided 100% mission success since their respective inaugural launches and demonstrated launch capability from both Vandenberg Air Force Base (VAFB) on the Western Test Range and Cape Canaveral Air Force Station (CCAFS) on the Eastern Test Range. However, the current EELV fleet communications, tracking, & control architecture & technology, which date back to the origins of the space launch business, require support by a large and high cost ground footprint. The USAF has embarked on an initiative known as Future Flight Safety System (FFSS) that will significantly reduce Test Range Operations and Maintenance (O& M) cost by closing facilities and decommissioning ground assets. In support of the FFSS, a Global Positioning System Metric Tracking (GPS MT) System based on the Global Positioning System (GPS) satellite constellation has been developed for EELV which will allow both Ranges to divest some of their radar assets. The Air Force, ULA and Space Vector have flown the first 2 Atlas Certification vehicles demonstrating the successful operation of the GPS MT System. The first Atlas V certification flight was completed in February 2012 from CCAFS, the second Atlas V certification flight from VAFB was completed in September 2012 and the third certification flight on a Delta IV was completed October 2012 from CCAFS. The GPS MT System will provide precise LV position, velocity and timing information that can replace ground radar tracking resource functionality. The GPS MT system will provide an independent position/velocity S-Band telemetry downlink to support the current man-in-the-loop ground-based commanded destruct of an anomalous flight- The system

State Support: A Prerequisite for Global Health Network Effectiveness

Science.gov (United States)

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

Anthropomorphic Networks as Representatives of Global Consciousness

Directory of Open Access Journals (Sweden)

Sergii Yahodzinskyi

2018-02-01

Full Text Available There has been analyzed a phenomenon of global consciousness, and its cultural and historical, civilizational dimensions have been substantiated. There has been demonstrated that the concept of planetary consciousness, global thinking, noosphere was described for the first time in the philosophy of cosmism. However, in modern conditions ideas of representatives of the naturalistic philosophical direction of cosmism have not lost their heuristic potential. They can be reconsidered in a new fashion within the context of emerging anthropomorphic (human dimension networks. There has been proved that global consciousness is a component of the social and cultural potential of global information networks defining vectors to prospects of humanity progress in the 21st century. Relying on methodology of the structural and functional analysis, the author arrives at a conclusion about global networks obtaining the status of representatives of global consciousness. This is the area of networks where all relevant information is concentrated – from statistical data to scientific and technical information. Access to these data is limited by human abilities and is realized in the form of discrete requests with using heuristic algorithms of information procession. A suggestion is introduced considering the fact that modern society being a self-organized system seeks to gain stable condition. Anthropomorphic networks are means of decreasing social entropy, which is growing as a result of any kind of human intervention into social processes. Thus, for the first time a human is challenged by their intellect, ability to create, discover and control.

Neural network based satellite tracking for deep space applications

Science.gov (United States)

Amoozegar, F.; Ruggier, C.

2003-01-01

The objective of this paper is to provide a survey of neural network trends as applied to the tracking of spacecrafts in deep space at Ka-band under various weather conditions and examine the trade-off between tracing accuracy and communication link performance.

The network of global corporate control.

Science.gov (United States)

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.

Track filtering by robust neural network

International Nuclear Information System (INIS)

Baginyan, S.A.; Kisel', I.V.; Konotopskaya, E.V.; Ososkov, G.A.

1993-01-01

In the present paper we study the following problems of track information extraction by the artificial neural network (ANN) rotor model: providing initial ANN configuration by an algorithm general enough to be applicable for any discrete detector in- or out of a magnetic field; robustness to heavy contaminated raw data (up to 100% signal-to-noise ratio); stability to the growing event multiplicity. These problems were carried out by corresponding innovations of our model, namely: by a special one-dimensional histogramming, by multiplying weights by a specially designed robust multiplier, and by replacing the simulated annealing schedule by ANN dynamics with an optimally fixed temperature. Our approach is valid for both circular and straight (non-magnetic) tracks and tested on 2D simulated data contaminated by 100% noise points distributed uniformly. To be closer to some reality in our simulation, we keep parameters of the cylindrical spectrometer ARES. 12 refs.; 9 figs

The CERN Global Network opens its doors to companies

CERN Multimedia

Francesco Poppi

2010-01-01

Six months after its launch, the CERN Global Network already has almost one thousand members. Today, it is opening its doors to companies from CERN's Member States. This will open up a variety of new professional and career opportunities to all the members and will enhance the networking capabilities of all parties involved.   Screenshot of the CERN Global Network website. A new item has recently appeared on the top menu of the Network's website: “Organisations”. This is the entry point for companies and, later, research institutes, wishing to join. “The CERN Global Network brings together hundreds of people who have worked at or with CERN and who have a wealth of skills and expertise. Thanks to the Network, the job opportunities made available by the companies will become visible to the wider community,” says Linda Orr-Easo, a member of the Knowledge and Technology Transfer Group and the CERN Global Network Manager. In addition to creating new career opp...

Infrared dim moving target tracking via sparsity-based discriminative classifier and convolutional network

Science.gov (United States)

Qian, Kun; Zhou, Huixin; Wang, Bingjian; Song, Shangzhen; Zhao, Dong

2017-11-01

Infrared dim and small target tracking is a great challenging task. The main challenge for target tracking is to account for appearance change of an object, which submerges in the cluttered background. An efficient appearance model that exploits both the global template and local representation over infrared image sequences is constructed for dim moving target tracking. A Sparsity-based Discriminative Classifier (SDC) and a Convolutional Network-based Generative Model (CNGM) are combined with a prior model. In the SDC model, a sparse representation-based algorithm is adopted to calculate the confidence value that assigns more weights to target templates than negative background templates. In the CNGM model, simple cell feature maps are obtained by calculating the convolution between target templates and fixed filters, which are extracted from the target region at the first frame. These maps measure similarities between each filter and local intensity patterns across the target template, therefore encoding its local structural information. Then, all the maps form a representation, preserving the inner geometric layout of a candidate template. Furthermore, the fixed target template set is processed via an efficient prior model. The same operation is applied to candidate templates in the CNGM model. The online update scheme not only accounts for appearance variations but also alleviates the migration problem. At last, collaborative confidence values of particles are utilized to generate particles' importance weights. Experiments on various infrared sequences have validated the tracking capability of the presented algorithm. Experimental results show that this algorithm runs in real-time and provides a higher accuracy than state of the art algorithms.

E-njoy the first CERN Global Network e-vent!

CERN Multimedia

CERN Bulletin

2010-01-01

Empowered by the considerable interest it received after it was launched, the CERN Global Network takes off and organizes the first e-vent, which will be a special talk on science communication that will be held on 29 June at 4.30 p.m. in the Council Chamber. You can experience it live on the Global Network site and, if you are a Member, provide feedback. Stay linked!   On the CERN Global Network webpage, you will be able to choose the topic of the next e-vents. Seven weeks after its launch, about 600 people have already joined the CERN Global Network and six thematic groups have been created. The whole idea of joining the Network is to stay connected or reconnect with life at CERN where seminars, talks and discussions are undoubtedly a very important and much appreciated part of it. This is where the e-vents come into play. “The e-vents enable members of the Global Network to participate in selected events taking place at CERN, such as lectures or panel discussions. They will...

Development of the Global Measles Laboratory Network.

Science.gov (United States)

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.

Global dissipativity of continuous-time recurrent neural networks with time delay

International Nuclear Information System (INIS)

Liao Xiaoxin; Wang Jun

2003-01-01

This paper addresses the global dissipativity of a general class of continuous-time recurrent neural networks. First, the concepts of global dissipation and global exponential dissipation are defined and elaborated. Next, the sets of global dissipativity and global exponentially dissipativity are characterized using the parameters of recurrent neural network models. In particular, it is shown that the Hopfield network and cellular neural networks with or without time delays are dissipative systems

Air Quality Measures on the National Environmental Health Tracking Network

Data.gov (United States)

U.S. Department of Health & Human Services — The Environmental Protection Agency (EPA) provides air pollution data about ozone and particulate matter (PM2.5) to CDC for the Tracking Network. The EPA maintains a...

Web-Enabling an Early Warning and Tracking System for Network Vulnerabilities

National Research Council Canada - National Science Library

Coffman, James

2001-01-01

.... Additionally, it lacked support for automated data validation, resulting in unreliable vulnerability tracking information As a result, the process was ineffective, and Navy networks remained highly...

Structure and evolution of the global seafood trade network

Science.gov (United States)

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.

GLOBAL CONVERGENCE FOR THE XOR BOOLEAN NETWORKS

OpenAIRE

Ho, Juei-Ling

2009-01-01

Shih and Ho have proved a global convergent theorem for boolean network: if a map from $\\{0,1\\}^{n}$ to itself defines a boolean network has the conditions: (1) each column of the discrete Jacobian matrix of each element of $\\{0,1\\}^{n}$ is either a unit vector or a zero vector; (2) all the boolean eigenvalues of the discrete Jacobian matrix of this map evaluated at each element of $\\{0,1\\}^{n}$ are zero, then it has a unique fixed point and this boolean network is global convergent to the fi...

Experimental validation of concept for real-time wavelength monitoring and tracking in densely populated WDM networks

Science.gov (United States)

Vukovic, Alex; Savoie, Michel; Hua, Heng; Campbell, Scott; Nguyen, Thao

2005-10-01

As the telecom industry responds with technological innovations to requests for higher data rates, increased number of wavelengths at higher densities, longer transmission distances and more intelligence for next generation optical networks, new monitoring schemes based on monitoring and tracking of each wavelength need to be developed and deployed. An optical layer monitoring scheme, based on tracking key optical parameters per each wavelength, is considered to be one of enablers for the transformation of today's opaque networks to dynamic, agile future networks. Ever-tighter network monitoring and control will be required to fulfill customer Service Level Agreements (SLAs). A wavelength monitoring and tracking concept was developed as a three-step approach. It started with the identification of all critical parameters required to obtain sufficient information about each wavelength; followed by the deployment of a cost-efficient device to provide simultaneous, accurate measurements in real-time of all critical parameters; and finally, the formulation of a specification for wavelength monitoring and tracking devices for real-time, simultaneous measurements and processing the data. A prototype solution based on a commercially available integrated modular spectrometer within a testbed environment associated with the all-optical network (AON) demonstrator program was used to verify and validate the wavelength monitoring and tracking concept. The developed concept verified that it can manage tracking of 32 wavelengths within a wavelength division multiplexing network. The developed concept presented in this paper can be used inside the transparent domains of networks to detect, identify and locate signal degradations in real-time, even sometimes to recognize the cause of the failure. Aside from the reduction of operational expenses due to the elimination of the need for operators at every site and skilled field technicians to isolate and repair faults, the developed

An Energy-Efficient Sleep Strategy for Target Tracking Sensor Networks

Directory of Open Access Journals (Sweden)

Juan FENG

2014-02-01

Full Text Available Energy efficiency is very important for sensor networks since sensor nodes have limited energy supply from battery. So far, many researches have been focused on this issue, while less emphasis was placed on the optimal sleep time of each node. This paper proposed an adaptive energy conservation strategy for target tracking based on a grid network structure, where each node autonomously determines when and if to sleep. It allows sensor nodes far away from targets to sleep to save energy and guarantee the tracking accuracy. The proposed approach extend network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of sensor nodes. And each node can choose an optimal sleep time so as to make system adaptive and energy-efficient. We show the performance of our approach in terms of energy drop, comparing it to a naive approach, dynamic PM with fixed sleep time and the coordinate PM strategies. From the experimental results, it is readily seen that the efficiency of the proposed approach.

Global Tracking Control of Quadrotor VTOL Aircraft in Three-Dimensional Space

Directory of Open Access Journals (Sweden)

Duc Khac Do

2014-07-01

Full Text Available This paper presents a method to design controllers that force a quadrotor vertical take-off and landing (VTOL aircraft to globally asymptotically track a reference trajectory in three-dimensional space. Motivated by the vehicle's steering practice, the roll and pitch angles are considered as immediate controls plus the total thrust force  provided by the aircraft's four rotors to control the position and yaw angle of the aircraft. The control design is based on the newly introduced one-step ahead backstepping, the standard backstepping and Lyapunov's direct methods. A combination of Euler angles and unit-quaternion for the attitude representation of the aircraft is used to obtain global tracking control results. The paper also includes a design of observers that exponentially estimate the aircraft's linear velocity vector and disturbances. Simulations illustrate the results.

Are we connected? : Ports in Global Networks

NARCIS (Netherlands)

R.A. Zuidwijk (Rob)

2015-01-01

markdownabstractAbstract Global supply chains are built on organizational, information, and logistics networks. Ports are connected via these networks and also need to connect these networks. Synchromodality is an innovative concept for container transportation, and the port plays an important

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

Science.gov (United States)

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.

Resistance Genes in Global Crop Breeding Networks.

Science.gov (United States)

Garrett, K A; Andersen, K F; Asche, F; Bowden, R L; Forbes, G A; Kulakow, P A; Zhou, B

2017-10-01

Resistance genes are a major tool for managing crop diseases. The networks of crop breeders who exchange resistance genes and deploy them in varieties help to determine the global landscape of resistance and epidemics, an important system for maintaining food security. These networks function as a complex adaptive system, with associated strengths and vulnerabilities, and implications for policies to support resistance gene deployment strategies. Extensions of epidemic network analysis can be used to evaluate the multilayer agricultural networks that support and influence crop breeding networks. Here, we evaluate the general structure of crop breeding networks for cassava, potato, rice, and wheat. All four are clustered due to phytosanitary and intellectual property regulations, and linked through CGIAR hubs. Cassava networks primarily include public breeding groups, whereas others are more mixed. These systems must adapt to global change in climate and land use, the emergence of new diseases, and disruptive breeding technologies. Research priorities to support policy include how best to maintain both diversity and redundancy in the roles played by individual crop breeding groups (public versus private and global versus local), and how best to manage connectivity to optimize resistance gene deployment while avoiding risks to the useful life of resistance genes. [Formula: see text] Copyright © 2017 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Techniques for Efficient Tracking of Road-Network-Based Moving Objects

DEFF Research Database (Denmark)

Civilis, Alminas; Jensen, Christian Søndergaard; Saltenis, Simonas

With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

Techniques for efficient road-network-based tracking of moving objects

DEFF Research Database (Denmark)

Civilis, A.; Jensen, Christian Søndergaard; Pakalnis, Stardas

2005-01-01

With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

From Local to Global Dilemmas in Social Networks

OpenAIRE

Pinheiro, Fl?vio L.; Pacheco, Jorge M.; Santos, Francisco C.

2012-01-01

Social networks affect in such a fundamental way the dynamics of the population they support that the global, population-wide behavior that one observes often bears no relation to the individual processes it stems from. Up to now, linking the global networked dynamics to such individual mechanisms has remained elusive. Here we study the evolution of cooperation in networked populations and let individuals interact via a 2-person Prisoner's Dilemma ? a characteristic defection dominant social ...

Tracking performance and global stability guaranteed neural control of uncertain hypersonic flight vehicle

Directory of Open Access Journals (Sweden)

Tao Teng

2016-02-01

Full Text Available In this article, a global adaptive neural dynamic surface control with predefined tracking performance is developed for a class of hypersonic flight vehicles, whose accurate dynamics is hard to obtain. The control scheme developed in this paper overcomes the limitations of neural approximation region by employing a switching mechanism which incorporates an additional robust controller outside the neural approximation region to pull the transient state variables back when they overstep the neural approximation region, such that globally uniformly ultimately bounded stability can be guaranteed. Especially, the developed global adaptive neural control also improves the tracking performance by introducing an error transformation mechanism, such that both transient and steady-state performance can be shaped according to the predefined bounds. Simulation studies on the hypersonic flight vehicle validate that the designed controller has good velocity modulation and velocity stability performance.

Quantification of global myocardial function by cine MRI deformable registration-based analysis: Comparison with MR feature tracking and speckle-tracking echocardiography.

Science.gov (United States)

Lamacie, Mariana M; Thavendiranathan, Paaladinesh; Hanneman, Kate; Greiser, Andreas; Jolly, Marie-Pierre; Ward, Richard; Wintersperger, Bernd J

2017-04-01

To evaluate deformable registration algorithms (DRA)-based quantification of cine steady-state free-precession (SSFP) for myocardial strain assessment in comparison with feature-tracking (FT) and speckle-tracking echocardiography (STE). Data sets of 28 patients/10 volunteers, undergoing same-day 1.5T cardiac MRI and echocardiography were included. LV global longitudinal (GLS), circumferential (GCS) and radial (GRS) peak systolic strain were assessed on cine SSFP data using commercially available FT algorithms and prototype DRA-based algorithms. STE was applied as standard of reference for accuracy, precision and intra-/interobserver reproducibility testing. DRA showed narrower limits of agreement compared to STE for GLS (-4.0 [-0.9,-7.9]) and GCS (-5.1 [1.1,-11.2]) than FT (3.2 [11.2,-4.9]; 3.8 [13.9,-6.3], respectively). While both DRA and FT demonstrated significant differences to STE for GLS and GCS (all pcine MRI. • Inverse DRA demonstrated superior reproducibility compared to feature-tracking (FT) methods. • Cine MR DRA and FT analysis demonstrate differences to speckle-tracking echocardiography • DRA demonstrated better correlation with STE than FT for MR-derived global strain data.

Artificial Neural Network In Maximum Power Point Tracking Algorithm Of Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Modestas Pikutis

2014-05-01

Full Text Available Scientists are looking for ways to improve the efficiency of solar cells all the time. The efficiency of solar cells which are available to the general public is up to 20%. Part of the solar energy is unused and a capacity of solar power plant is significantly reduced – if slow controller or controller which cannot stay at maximum power point of solar modules is used. Various algorithms of maximum power point tracking were created, but mostly algorithms are slow or make mistakes. In the literature more and more oftenartificial neural networks (ANN in maximum power point tracking process are mentioned, in order to improve performance of the controller. Self-learner artificial neural network and IncCond algorithm were used for maximum power point tracking in created solar power plant model. The algorithm for control was created. Solar power plant model is implemented in Matlab/Simulink environment.

Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

Directory of Open Access Journals (Sweden)

Zhijun Xie

2014-10-01

Full Text Available Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT. In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

The global structure of knowledge network

NARCIS (Netherlands)

Angelopoulos, Spyros; Lomi, Alessandro

2017-01-01

In this paper, we treat patent citations as knowledge networks connecting pieces of formalized knowledge and people, and focus on how ideas are connected, rather than how they are protected. We focus on the global structural properties of formalized knowledge network, and more specifically on the

The limits of direct satellite tracking with the Global Positioning System (GPS)

Science.gov (United States)

Bertiger, W. I.; Yunck, T. P.

1988-01-01

Recent advances in high precision differential Global Positioning System-based satellite tracking can be applied to the more conventional direct tracking of low earth satellites. To properly evaluate the limiting accuracy of direct GPS-based tracking, it is necessary to account for the correlations between the a-priori errors in GPS states, Y-bias, and solar pressure parameters. These can be obtained by careful analysis of the GPS orbit determination process. The analysis indicates that sub-meter accuracy can be readily achieved for a user above 1000 km altitude, even when the user solution is obtained with data taken 12 hours after the data used in the GPS orbit solutions.

Design and optimization of wireless sensor networks for localization and tracking

OpenAIRE

Pino Povedano, Sara

2016-01-01

Knowledge of the position of nodes in a WSN is crucial in most wireless sensor network (WSN) applications. The gathered information needs to be associated with a particular location in a specific time instant in order to appropiately control de surveillance area. Moreover, WSNs may be used for tracking certain objects in monitoring applications, which also requires the incorporation of location information of the sensor nodes into the tracking algorithms. These requisites ma...

Global network centrality of university rankings

Science.gov (United States)

Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

2017-10-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

Collaborative 3D Target Tracking in Distributed Smart Camera Networks for Wide-Area Surveillance

Directory of Open Access Journals (Sweden)

Xenofon Koutsoukos

2013-05-01

Full Text Available With the evolution and fusion of wireless sensor network and embedded camera technologies, distributed smart camera networks have emerged as a new class of systems for wide-area surveillance applications. Wireless networks, however, introduce a number of constraints to the system that need to be considered, notably the communication bandwidth constraints. Existing approaches for target tracking using a camera network typically utilize target handover mechanisms between cameras, or combine results from 2D trackers in each camera into 3D target estimation. Such approaches suffer from scale selection, target rotation, and occlusion, drawbacks typically associated with 2D tracking. In this paper, we present an approach for tracking multiple targets directly in 3D space using a network of smart cameras. The approach employs multi-view histograms to characterize targets in 3D space using color and texture as the visual features. The visual features from each camera along with the target models are used in a probabilistic tracker to estimate the target state. We introduce four variations of our base tracker that incur different computational and communication costs on each node and result in different tracking accuracy. We demonstrate the effectiveness of our proposed trackers by comparing their performance to a 3D tracker that fuses the results of independent 2D trackers. We also present performance analysis of the base tracker along Quality-of-Service (QoS and Quality-of-Information (QoI metrics, and study QoS vs. QoI trade-offs between the proposed tracker variations. Finally, we demonstrate our tracker in a real-life scenario using a camera network deployed in a building.

Automated target recognition and tracking using an optical pattern recognition neural network

Science.gov (United States)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Dynamic tracking performance of indoor global positioning system: An experimental and theoretical study

Directory of Open Access Journals (Sweden)

Gang Zhao

2015-10-01

Full Text Available The automation level has been improved rapidly with the introduction of large-scale measurement technologies, such as indoor global positioning system, into the production process among the fields of car, ship, and aerospace due to their excellent measurement characteristics. In fact, the objects are usually in motion during the real measurement process; however, the dynamic measurement characteristics of indoor global positioning system are much limited and still in exploration. In this research, we focused on the dynamic tracking performance of indoor global positioning system and then successfully built a mathematical model based on its measurement principles. We first built single and double station system models with the consideration of measurement objects’ movement. Using MATLAB simulation, we realized the dynamic measurement characteristics of indoor global positioning system. In the real measurement process, the experimental results also support the mathematical model that we built, which proves a great success in dynamic measurement characteristics. We envision that this dynamic tracking performance of indoor global positioning system would shed light on the dynamic measurement of a motion object and therefore make contribution to the automation production.

Global synchronization of a class of delayed complex networks

International Nuclear Information System (INIS)

Li Ping; Yi Zhang; Zhang Lei

2006-01-01

Global synchronization of a class of complex networks with time-varying delays is investigated in this paper. Some sufficient conditions are derived. These conditions show that the synchronization of delayed complex networks can be determined by their topologies. In addition, these conditions are simply represented in terms of the networks coupling matrix and are easy to be checked. A typical example of complex networks with chaotic nodes is employed to illustrate the obtained global synchronization results

Global Synoptic Climatology Network (GSCN)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Dataset DSI-9290 is the result of a joint effort to create a Global Synoptic Climatology Network among the Meteorological Service of Canada (Downsview, Ontario and...

Orbit and clock determination of BDS regional navigation satellite system based on IGS M-GEX and WHU BETS tracking network

Science.gov (United States)

GENG, T.; Zhao, Q.; Shi, C.; Shum, C.; Guo, J.; Su, X.

2013-12-01

BeiDou Navigation Satellite System (BDS) began to provide the regional open service on December 27th 2012 and will provide the global open service by the end of 2020. Compared to GPS, the space segment of BDS Regional System consists of 5 Geostationary Earth Orbit satellites (GEO), 5 Inclined Geosynchronous Orbit satellites (IGSO) and 4 Medium Earth orbit (MEO) satellites. Since 2011, IGS Multiple-GNSS Experiment (M-GEX) focuses on tracking the newly available GNSS signals. This includes all signals from the modernized satellites of the GPS and GLONASS systems, as well as signals of the BDS, Galileo and QZSS systems. Up to now, BDS satellites are tracked by around 25 stations with a variety of different antennas and receivers from different GNSS manufacture communities in M-GEX network. Meanwhile, there are 17 stations with Unicore Communications Incorporation's GPS/BDS receivers in BeiDou Experimental Tracking Stations (BETS) network by Wuhan University. In addition, 5 BDS satellites have been tracking by the International Laser Ranging Service (ILRS). BDS performance is expected to be further studied by the GNSS communities. Following an introduction of the BDS system and above different tracking network, this paper discusses the achieved BDS characterization and performance assessment. Firstly, the BDS signal and measurement quality are analyzed with different antennas and receivers in detail compared to GPS. This includes depth of coverage for satellite observation, carrier-to-noise-density ratios, code noise and multipath, carrier phase errors. Secondly, BDS Precise Orbit Determination (POD) is processed. Different arc lengths and sets of orbit parameters are tested using Position And Navigation Data Analysis software (PANDA) which is developed at the Wuhan University. GEO, IGSO and MEO satellites orbit quality will be assessed using overlap comparison, 2-day orbit fit and external validations with Satellite Laser Range (SLR). Then BDS satellites are equipped

Region stability analysis and tracking control of memristive recurrent neural network.

Science.gov (United States)

Bao, Gang; Zeng, Zhigang; Shen, Yanjun

2018-02-01

Memristor is firstly postulated by Leon Chua and realized by Hewlett-Packard (HP) laboratory. Research results show that memristor can be used to simulate the synapses of neurons. This paper presents a class of recurrent neural network with HP memristors. Firstly, it shows that memristive recurrent neural network has more compound dynamics than the traditional recurrent neural network by simulations. Then it derives that n dimensional memristive recurrent neural network is composed of [Formula: see text] sub neural networks which do not have a common equilibrium point. By designing the tracking controller, it can make memristive neural network being convergent to the desired sub neural network. At last, two numerical examples are given to verify the validity of our result. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive filtering for hidden node detection and tracking in networks.

Science.gov (United States)

Hamilton, Franz; Setzer, Beverly; Chavez, Sergio; Tran, Hien; Lloyd, Alun L

2017-07-01

The identification of network connectivity from noisy time series is of great interest in the study of network dynamics. This connectivity estimation problem becomes more complicated when we consider the possibility of hidden nodes within the network. These hidden nodes act as unknown drivers on our network and their presence can lead to the identification of false connections, resulting in incorrect network inference. Detecting the parts of the network they are acting on is thus critical. Here, we propose a novel method for hidden node detection based on an adaptive filtering framework with specific application to neuronal networks. We consider the hidden node as a problem of missing variables when model fitting and show that the estimated system noise covariance provided by the adaptive filter can be used to localize the influence of the hidden nodes and distinguish the effects of different hidden nodes. Additionally, we show that the sequential nature of our algorithm allows for tracking changes in the hidden node influence over time.

The global transmission network of HIV-1.

Science.gov (United States)

Wertheim, Joel O; Leigh Brown, Andrew J; Hepler, N Lance; Mehta, Sanjay R; Richman, Douglas D; Smith, Davey M; Kosakovsky Pond, Sergei L

2014-01-15

Human immunodeficiency virus type 1 (HIV-1) is pandemic, but its contemporary global transmission network has not been characterized. A better understanding of the properties and dynamics of this network is essential for surveillance, prevention, and eventual eradication of HIV. Here, we apply a simple and computationally efficient network-based approach to all publicly available HIV polymerase sequences in the global database, revealing a contemporary picture of the spread of HIV-1 within and between countries. This approach automatically recovered well-characterized transmission clusters and extended other clusters thought to be contained within a single country across international borders. In addition, previously undescribed transmission clusters were discovered. Together, these clusters represent all known modes of HIV transmission. The extent of international linkage revealed by our comprehensive approach demonstrates the need to consider the global diversity of HIV, even when describing local epidemics. Finally, the speed of this method allows for near-real-time surveillance of the pandemic's progression.

Dynamical networks: Finding, measuring, and tracking neural population activity using network science

Directory of Open Access Journals (Sweden)

Mark D. Humphries

2017-12-01

Full Text Available Systems neuroscience is in a headlong rush to record from as many neurons at the same time as possible. As the brain computes and codes using neuron populations, it is hoped these data will uncover the fundamentals of neural computation. But with hundreds, thousands, or more simultaneously recorded neurons come the inescapable problems of visualizing, describing, and quantifying their interactions. Here I argue that network science provides a set of scalable, analytical tools that already solve these problems. By treating neurons as nodes and their interactions as links, a single network can visualize and describe an arbitrarily large recording. I show that with this description we can quantify the effects of manipulating a neural circuit, track changes in population dynamics over time, and quantitatively define theoretical concepts of neural populations such as cell assemblies. Using network science as a core part of analyzing population recordings will thus provide both qualitative and quantitative advances to our understanding of neural computation.

Event-triggered cooperative target tracking in wireless sensor networks

Directory of Open Access Journals (Sweden)

Lu Kelin

2016-10-01

Full Text Available Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measurements. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership measurements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.

Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

Science.gov (United States)

Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

2014-11-11

The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

Towards a global quantum network

Science.gov (United States)

Simon, Christoph

2017-11-01

The creation of a global quantum network is now a realistic proposition thanks to developments in satellite and fibre links and quantum memory. Applications will range from secure communication and fundamental physics experiments to a future quantum internet.

Studies on the Belle II L1 CDC track trigger's z-vertex resolution with neural networks

Energy Technology Data Exchange (ETDEWEB)

Skambraks, Sebastian; Neuhaus, Sara; Chen, Yang [Technische Universitaet Muenchen (Germany); Abudinen, Fernando; Kiesling, Christian [Max-Planck-Institut fuer Physik, Muenchen (Germany)

2015-07-01

We present the use of a neural network ensemble for the first level (L1) track trigger subsystem of Belle II. Our method employs hit and drift time information from the Central Drift Chamber (CDC). Estimating the z-coordinates of the vertex positions improves the signal to background ratio in the recorded data. Especially beam induced background can clearly be rejected, allowing to relax the 2D trigger conditions and thus enhancing the physics gain for low multiplicity events (e.g. tau pair production). Neural networks enable an improvement of the z-vertex resolution compared to linear least squares track fitting. As general function approximators, they are capable of learning nonlinearities solely from a training dataset. We propose a combined setup, integrating the benefits of the linear fit and enriching it with the nonlinear prediction capabilities of the neural networks. The precise z-vertices of single tracks are estimated by an ensemble of local expert neural networks, specialized to sectors in the track parameter phase space. A comparison is presented, demonstrating the differences of the linear fit and the neural network approach.

Multinational Firms and the Management of Global Networks

DEFF Research Database (Denmark)

De Marchi, Valentina; Maria, Eleonora Di; Ponte, Stefano

2014-01-01

This paper aims at enriching the literature on international business (IB) studies to include insights from Global Value Chain (GVC) analysis to better explain how MNCs can orchestrate a global network organization. A first important contribution of the GVC literature is that it shifts the focus...... from single firms to their value chains, providing instruments to study how activities are split and organized among different firms at the industry level, and how MNCs can implement different governing mechanisms within a network-based setting. The GVC literature also highlights that retailers (as...... can manage their network relationships in a global scenario. Finally, through their focus on upgrading, GVC studies suggest that knowledge flows and innovation dynamics taking place within value chains are as important as those taking place within the MNC’s organizational border. We conclude...

IMPLICATIONS OF SOCIAL RESPONSIBILITY DISCLOSURE ON GLOBAL PRODUCTION NETWORK

OpenAIRE

Le Bo; Dan Shen; Jin Jun Bo

2014-01-01

This paper aims to discuss effectiveness of social responsibility disclosure in promoting global production network. Through a critical review on the theoretical development from supply chain to global production network, the global supply chain management of Apple Inc., as a case, is investigated, with focus on corporate and NGOs’ social disclosure on the environmental and labor rights' issues of its suppliers in China. The paper concludes that effectiveness of corporate social disclosure on...

Running a network on a shoestring: the Global Invasive Species Information Network

Science.gov (United States)

Jarnevich, Catherine S.; Simpson, Annie; Graham, James J; Newman, Gregory J.; Bargeron, Chuck T.

2015-01-01

The Global Invasive Species Information Network (GISIN) was conceptualized in 2004 to aggregate and disseminate invasive species data in a standardized way. A decade later the GISIN community has implemented a data portal and three of six GISIN data aggregation models in the GISIN data exchange Protocol, including invasive species status information, resource URLs, and occurrence data. The portal is based on a protocol developed by representatives from 15 countries and 27 organizations of the global invasive species information management community. The GISIN has 19 data providers sharing 34,343 species status records, 1,693,073 occurrences, and 15,601 resource URLs. While the GISIN's goal is to be global, much of its data and funding are provided by the United States. Several initiatives use the GISIN as their information backbone, such as the Great Lakes Early Detection Network (GLEDN) and the North American Invasive Species Network (NAISN). Here we share several success stories and organizational challenges that remain.

Four Challenges That Global Health Networks Face

Directory of Open Access Journals (Sweden)

Jeremy Shiffman

2017-04-01

Full Text Available Global health networks, webs of individuals and organizations with a shared concern for a particular condition, have proliferated over the past quarter century. They differ in their effectiveness, a factor that may help explain why resource allocations vary across health conditions and do not correspond closely with disease burden. Drawing on findings from recently concluded studies of eight global health networks—addressing alcohol harm, early childhood development (ECD, maternal mortality, neonatal mortality, pneumonia, surgically-treatable conditions, tobacco use, and tuberculosis—I identify four challenges that networks face in generating attention and resources for the conditions that concern them. The first is problem definition: generating consensus on what the problem is and how it should be addressed. The second is positioning: portraying the issue in ways that inspire external audiences to act. The third is coalition-building: forging alliances with these external actors, particularly ones outside the health sector. The fourth is governance: establishing institutions to facilitate collective action. Research indicates that global health networks that effectively tackle these challenges are more likely to garner support to address the conditions that concern them. In addition to the effectiveness of networks, I also consider their legitimacy, identifying reasons both to affirm and to question their right to exert power.

CDC Tracking Network: Working Towards a Healthier Planet for Healthy People

Centers for Disease Control (CDC) Podcasts

2009-09-14

This is an engaging video podcast geared to raise awareness of environmental public health and our nation's need for the Tracking Network.  Created: 9/14/2009 by National Center for Environmental Health (NCEH).   Date Released: 9/14/2009.

Language Choice & Global Learning Networks

Directory of Open Access Journals (Sweden)

Dennis Sayers

1995-05-01

Full Text Available How can other languages be used in conjunction with English to further intercultural and multilingual learning when teachers and students participate in computer-based global learning networks? Two portraits are presented of multilingual activities in the Orillas and I*EARN learning networks, and are discussed as examples of the principal modalities of communication employed in networking projects between distant classes. Next, an important historical precedent --the social controversy which accompanied the introduction of telephone technology at the end of the last century-- is examined in terms of its implications for language choice in contemporary classroom telecomputing projects. Finally, recommendations are offered to guide decision making concerning the role of language choice in promoting collaborative critical inquiry.

Global operations networks in motion: Managing configurations and capabilities

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Wæhrens, Brian Vejrum; Jørgensen, Claus

2010-01-01

In the past, the ‘Made in the World’ label, although capturing what may lie ahead, seemed awkward and futuristic. Today, it has become a reality. An ample array of global products are built up of numerous components and modules manufactured by global networks of differentiated partners rather than...... within the boundaries of one national entity. The purpose of this paper is to contribute to bridging the empirical gap in the area of global operations networks and provide insights into how they change over time. The paper is based on the cases of three Danish companies and their global operations...

Drift chamber tracking with a VLSI neural network

International Nuclear Information System (INIS)

Lindsey, C.S.; Denby, B.; Haggerty, H.; Johns, K.

1992-10-01

We have tested a commercial analog VLSI neural network chip for finding in real time the intercept and slope of charged particles traversing a drift chamber. Voltages proportional to the drift times were input to the Intel ETANN chip and the outputs were recorded and later compared off line to conventional track fits. We will discuss the chamber and test setup, the chip specifications, and results of recent tests. We'll briefly discuss possible applications in high energy physics detector triggers

Evolution of the global virtual water trade network.

Science.gov (United States)

Dalin, Carole; Konar, Megan; Hanasaki, Naota; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2012-04-17

Global freshwater resources are under increasing pressure from economic development, population growth, and climate change. The international trade of water-intensive products (e.g., agricultural commodities) or virtual water trade has been suggested as a way to save water globally. We focus on the virtual water trade network associated with international food trade built with annual trade data and annual modeled virtual water content. The evolution of this network from 1986 to 2007 is analyzed and linked to trade policies, socioeconomic circumstances, and agricultural efficiency. We find that the number of trade connections and the volume of water associated with global food trade more than doubled in 22 years. Despite this growth, constant organizational features were observed in the network. However, both regional and national virtual water trade patterns significantly changed. Indeed, Asia increased its virtual water imports by more than 170%, switching from North America to South America as its main partner, whereas North America oriented to a growing intraregional trade. A dramatic rise in China's virtual water imports is associated with its increased soy imports after a domestic policy shift in 2000. Significantly, this shift has led the global soy market to save water on a global scale, but it also relies on expanding soy production in Brazil, which contributes to deforestation in the Amazon. We find that the international food trade has led to enhanced savings in global water resources over time, indicating its growing efficiency in terms of global water use.

Tracking the global maximum power point of PV arrays under partial shading conditions

Science.gov (United States)

Fennich, Meryem

This thesis presents the theoretical and simulation studies of the global maximum power point tracking (MPPT) for photovoltaic systems under partial shading. The main goal is to track the maximum power point of the photovoltaic module so that the maximum possible power can be extracted from the photovoltaic panels. When several panels are connected in series with some of them shaded partially either due to clouds or shadows from neighboring buildings, several local maxima appear in the power vs. voltage curve. A power increment based MPPT algorithm is effective in identifying the global maximum from the several local maxima. Several existing MPPT algorithms are explored and the state-of-the-art power increment method is simulated and tested for various partial shading conditions. The current-voltage and power-voltage characteristics of the PV model are studied under different partial shading conditions, along with five different cases demonstrating how the MPPT algorithm performs when shading switches from one state to another. Each case is supplemented with simulation results. The method of tracking the Global MPP is based on controlling the DC-DC converter connected to the output of the PV array. A complete system simulation including the PV array, the direct current to direct current (DC-DC) converter and the MPPT is presented and tested using MATLAB software. The simulation results show that the MPPT algorithm works very well with the buck converter, while the boost converter needs further changes and implementation.

Using Sunlight and Cell Networks to Bring Fleeting Tracking to Small Scale Fisheries

Science.gov (United States)

Garren, M.; Selbie, H.; Suchomel, D.; McDonald, W.; Solomon, D.

2016-12-01

Traditionally, the efforts of small scale fisheries have not been easily incorporated into the global picture of fishing effort and activity. That means that the activities of the vast majority ( 90%) of fishing vessels in the world have remained unquantified and largely opaque. With newly developed technology that harnesses solar power and cost-effective cellular networks to transmit data, it is becoming possible to provide vessel tracking systems on a large scale for vessels of all sizes. Furthermore, capitalizing on the relatively inexpensive cellular networks to transfer the data enables data of much higher granularity to be captured. By recording a vessel's position every few seconds, instead of minutes to hours as is typical of most satellite-based systems, we are able to resolve a diverse array of behaviors happening at sea including when and where fishing occurred and what type of fishing gear was used. This high granularity data is both incredibly useful and also a challenge to manage and mine. New approaches for handling and processing this continuous data stream of vessel positions are being developed to extract the most informative and actionable pieces of information for a variety of audiences including governing agencies, industry supply chains seeking transparency, non-profit organizations supporting conservation efforts, academic researchers and the fishers and boat owners.

Using the Global Positioning System for Earth Orbiter and Deep Space Tracking

Science.gov (United States)

Lichten, Stephen M.

1994-01-01

The Global Positioning System (GPS) can play a major role in supporting orbit and trajectory determination for spacecraft in a wide range of applications, including low-Earth, high-Earth, and even deep space (interplanetary) tracking. This paper summarizes recent results demonstrating these unique and far-ranging applications of GPS.

Combined discriminative global and generative local models for visual tracking

Science.gov (United States)

Zhao, Liujun; Zhao, Qingjie; Chen, Yanming; Lv, Peng

2016-03-01

It is a challenging task to develop an effective visual tracking algorithm due to factors such as pose variation, rotation, and so on. Combined discriminative global and generative local appearance models are proposed to address this problem. Specifically, we develop a compact global object representation by extracting the low-frequency coefficients of the color and texture of the object based on two-dimensional discrete cosine transform. Then, with the global appearance representation, we learn a discriminative metric classifier in an online fashion to differentiate the target object from its background, which is very important to robustly indicate the changes in appearance. Second, we develop a new generative local model that exploits the scale invariant feature transform and its spatial geometric information. To make use of the advantages of the global discriminative model and the generative local model, we incorporate them into Bayesian inference framework. In this framework, the complementary models help the tracker locate the target more accurately. Furthermore, we use different mechanisms to update global and local templates to capture appearance changes. The experimental results demonstrate that the proposed approach performs favorably against state-of-the-art methods in terms of accuracy.

Tracking the dynamic variations in a social network formed through shared interests

Directory of Open Access Journals (Sweden)

Gerold Pedemonte

2009-06-01

Full Text Available We tracked the dynamics of a social network formed by a shared interest in movies. Users-, movie ratings-, and rental date-data from the Netflix Prize dataset were used to construct a series of date-filtered social networks, wherein viewers were linked when they rented the same movie and gave the same rating. We obtained a nearly constant high clustering coefficient (0.60 – 0.85, and a low average path length (1.4 – 2.3 indicating a static 'small-world' network despite the dynamic behavior of the borrowers.

Global asymptotic stability of delayed Cohen-Grossberg neural networks

International Nuclear Information System (INIS)

Wu Wei; Cui Baotong; Huang Min

2007-01-01

In this letter, the global asymptotic stability of a class of Cohen-Grossberg neural networks with time-varying delays is discussed. A new set of sufficient conditions for the neural networks are proposed to guarantee the global asymptotic convergence. Our criteria represent an extension of the existing results in literatures. An example is also presented to compare our results with the previous results

Clustering and fault tolerance for target tracking using wireless sensor networks

International Nuclear Information System (INIS)

Bhatti, S.; Khanzada, S.; Memon, S.

2012-01-01

Over the last few years, the deployment of WSNs (Wireless Sensor Networks) has been fostered in diverse applications. WSN has great potential for a variety of domains ranging from scientific experiments to commercial applications. Due to the deployment of WSNs in dynamic and unpredictable environments. They have potential to cope with variety of faults. This paper proposes an energy-aware fault-tolerant clustering protocol for target tracking applications termed as the FITf (Fault Tolerant Target Tracking) protocol The identification of RNs (Redundant Nodes) makes SN (Sensor Node) fault tolerance plausible and the clustering endorsed recovery of sensors supervised by a faulty CH (Cluster Head). The FfTT protocol intends two steps of reducing energy consumption: first, by identifying RNs in the network; secondly, by restricting the numbers of SNs sending data to the CH. Simulations validate the scalability and low power consumption of the FITf protocol in comparison with LEACH protocol. (author)

Neural network consistent empirical physical formula construction for neutron–gamma discrimination in gamma ray tracking

International Nuclear Information System (INIS)

Yildiz, Nihat; Akkoyun, Serkan

2013-01-01

Highlights: ► Detector responses in neutron–gamma discrimination were estimated by neural networks. ► Novel consistent neural network empirical physical formulas (EPFs) were constructed for detector responses. ► The EPFs are of explicit mathematical functional form. ► The EPFs can be used to derive various physical functions relevant to neutron–gamma discrimination in gamma ray tracking. -- Abstract: Gamma ray tracking is an efficient detection technique in studying exotic nuclei which lies far from beta stability line. To achieve very powerful and extraordinary resolution ability, new detectors based on gamma ray tracking are currently being developed. To reach this achievement, the neutron–gamma discrimination in these detectors is also an important task. In this paper, by suitable layered feedforward neural networks (LFNNs), we have constructed novel and consistent empirical physical formulas (EPFs) for some highly nonlinear detector counts measured in neutron–gamma discrimination. The detector counts data used in the discrimination was actually borrowed from our previous paper. The counts used here had been originally measured versus the following parameters: energy deposited in the first interaction points, difference in the incoming direction of initial gamma rays, and finally figure of merit values of the clusters determined by tracking. The LFNN–EPFs are of explicit mathematical functional form. Therefore, by various suitable operations of mathematical analysis, these LFNN–EPFs can be used to derivate further physical functions which might be potentially relevant to neutron–gamma discrimination performance of gamma ray tracking.

Neural mechanisms tracking popularity in real-world social networks.

Science.gov (United States)

Zerubavel, Noam; Bearman, Peter S; Weber, Jochen; Ochsner, Kevin N

2015-12-08

Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (target) while whole-brain functional MRI data were collected. Independent functional localizer tasks were used to identify brain systems supporting affective valuation (ventromedial prefrontal cortex, ventral striatum, amygdala) and social cognition (dorsomedial prefrontal cortex, precuneus, temporoparietal junction), respectively. During the face-viewing task, activity in both types of neural systems tracked targets' sociometric popularity, even when controlling for potential confounds. The target popularity-social cognition system relationship was mediated by valuation system activity, suggesting that observing popular individuals elicits value signals that facilitate understanding their mental states. The target popularity-valuation system relationship was strongest for popular perceivers, suggesting enhanced sensitivity to differences among other group members' popularity. Popular group members also demonstrated greater interpersonal sensitivity by more accurately predicting how their own personalities were perceived by other individuals in the social network. These data offer insights into the mechanisms by which status guides social behavior.

Global value chains: Building blocks and network dynamics

Science.gov (United States)

Tsekeris, Theodore

2017-12-01

The paper employs measures and tools from complex network analysis to enhance the understanding and interpretation of structural characteristics pertaining to the Global Value Chains (GVCs) during the period 1995-2011. The analysis involves the country, sector and country-sector value chain networks to identify main drivers of structural change. The results indicate significant intertemporal changes, mirroring the increased globalization in terms of network size, strength and connectivity. They also demonstrate higher clustering and increased concentration of the most influential countries and country-sectors relative to all others in the GVC network, with the geographical dimension to prevail over the sectoral dimension in the formation of value chains. The regionalization and less hierarchical organization drive country-sector production sharing, while the sectoral value chain network has become more integrated and more competitive over time. The findings suggest that the impact of country-sector policies and/or shocks may vary with the own-group and network-wide influence of each country, take place in multiple geographical scales, as GVCs have a block structure, and involve time dynamics.

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

Science.gov (United States)

Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

An Efficient Approach for Node Localisation and Tracking in Wireless Sensor Networks

CSIR Research Space (South Africa)

Mwila, Martin

2014-08-01

Full Text Available -1 An Efficient Approach for Node Localisation and Tracking in Wireless Sensor Networks Martin K. Mwila Submitted in partial fulfilment of the requirements for the degree Magister Technologiae: Electrical Engineering in the Department of Electrical Engineering...

The complex network of global cargo ship movements.

Science.gov (United States)

Kaluza, Pablo; Kölzsch, Andrea; Gastner, Michael T; Blasius, Bernd

2010-07-06

Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

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Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Global robust stability of delayed recurrent neural networks

International Nuclear Information System (INIS)

Cao Jinde; Huang Deshuang; Qu Yuzhong

2005-01-01

This paper is concerned with the global robust stability of a class of delayed interval recurrent neural networks which contain time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. A new sufficient condition is presented for the existence, uniqueness, and global robust stability of equilibria for interval neural networks with time delays by constructing Lyapunov functional and using matrix-norm inequality. An error is corrected in an earlier publication, and an example is given to show the effectiveness of the obtained results

Links that speak: the global language network and its association with global fame.

Science.gov (United States)

Ronen, Shahar; Gonçalves, Bruno; Hu, Kevin Z; Vespignani, Alessandro; Pinker, Steven; Hidalgo, César A

2014-12-30

Languages vary enormously in global importance because of historical, demographic, political, and technological forces. However, beyond simple measures of population and economic power, there has been no rigorous quantitative way to define the global influence of languages. Here we use the structure of the networks connecting multilingual speakers and translated texts, as expressed in book translations, multiple language editions of Wikipedia, and Twitter, to provide a concept of language importance that goes beyond simple economic or demographic measures. We find that the structure of these three global language networks (GLNs) is centered on English as a global hub and around a handful of intermediate hub languages, which include Spanish, German, French, Russian, Portuguese, and Chinese. We validate the measure of a language's centrality in the three GLNs by showing that it exhibits a strong correlation with two independent measures of the number of famous people born in the countries associated with that language. These results suggest that the position of a language in the GLN contributes to the visibility of its speakers and the global popularity of the cultural content they produce.

Global Land Surface Temperature From the Along-Track Scanning Radiometers

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Ghent, D. J.; Corlett, G. K.; Göttsche, F.-M.; Remedios, J. J.

2017-11-01

The Leicester Along-Track Scanning Radiometer (ATSR) and Sea and Land Surface Temperature Radiometer (SLSTR) Processor for LAnd Surface Temperature (LASPLAST) provides global land surface temperature (LST) products from thermal infrared radiance data. In this paper, the state-of-the-art version of LASPLAST, as deployed in the GlobTemperature project, is described and applied to data from the Advanced Along-Track Scanning Radiometer (AATSR). The LASPLAST retrieval formulation for LST is a nadir-only, two-channel, split-window algorithm, based on biome classification, fractional vegetation, and across-track water vapor dependences. It incorporates globally robust retrieval coefficients derived using highly sampled atmosphere profiles. LASPLAST benefits from appropriate spatial resolution auxiliary information and a new probabilistic-based cloud flagging algorithm. For the first time for a satellite-derived LST product, pixel-level uncertainties characterized in terms of random, locally correlated, and systematic components are provided. The new GlobTemperature GT_ATS_2P Version 1.0 product has been validated for 1 year of AATSR data (2009) against in situ measurements acquired from "gold standard reference" stations: Gobabeb, Namibia, and Evora, Portugal; seven Surface Radiation Budget stations, and the Atmospheric Radiation Measurement station at Southern Great Plains. These data show average absolute biases for the GT_ATS_2P Version 1.0 product of 1.00 K in the daytime and 1.08 K in the nighttime. The improvements in data provenance including better accuracy, fully traceable retrieval coefficients, quantified uncertainty, and more detailed information in the new harmonized format of the GT_ATS_2P product will allow for more significant exploitation of the historical LST data record from the ATSRs and a valuable near-real-time service from the Sea and Land Surface Temperature Radiometers (SLSTRs).

Identification of global oil trade patterns: An empirical research based on complex network theory

International Nuclear Information System (INIS)

Ji, Qiang; Zhang, Hai-Ying; Fan, Ying

2014-01-01

Highlights: • A global oil trade core network is analyzed using complex network theory. • The global oil export core network displays a scale-free behaviour. • The current global oil trade network can be divided into three trading blocs. • The global oil trade network presents a ‘robust and yet fragile’ characteristic. - Abstract: The Global oil trade pattern becomes increasingly complex, which has become one of the most important factors affecting every country’s energy strategy and economic development. In this paper, a global oil trade core network is constructed to analyze the overall features, regional characteristics and stability of the oil trade using complex network theory. The results indicate that the global oil export core network displays a scale-free behaviour, in which the trade position of nodes presents obvious heterogeneity and the ‘hub nodes’ play a ‘bridge’ role in the formation process of the trade network. The current global oil trade network can be divided into three trading blocs, including the ‘South America-West Africa-North America’ trading bloc, the ‘Middle East–Asian–Pacific region’ trading bloc, and ‘the former Soviet Union–North Africa–Europe’ trading bloc. Geopolitics and diplomatic relations are the two main reasons for this regional oil trade structure. Moreover, the global oil trade network presents a ‘robust but yet fragile’ characteristic, and the impacts of trade interruption always tend to spread throughout the whole network even if the occurrence of export disruptions is localised

Alignment of global supply networks based on strategic groups of supply chains

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Nikos G. Moraitakis

2017-09-01

Full Text Available Background: From a supply chain perspective, often big differences exist between global raw material suppliers’ approaches to supply their respective local markets. The progressing complexity of large centrally managed global supply networks and their often-unknown upstream ramifications increase the likelihood of undetected bottlenecks and inefficiencies. It is therefore necessary to develop an approach to strategically master the upstream complexity of such networks from a holistic supply chain perspective in order to align regional competitive priorities and supply chain structures. The objective of this research is hence to develop an approach for the supply-chain-based alignment of complex global supply networks. Method: We review existing literature from the fields of supply chain and network management, strategic sourcing, and strategic management. Based on the literature review and theoretical and practical considerations we deduce a conceptual approach to consider upstream supply chain structures in supply network alignment initiatives. Results: On the basis of these considerations and current empirical literature we transfer strategic group theory to the supply network management context. The proposed approach introduces strategic groups of supply chains as a segmentation criterion for complex global supply networks which enables the network-wide alignment of competitive priorities. Conclusion: Supply-chain-based segmentation of global supply network structures can effectively reduce the complexity, firms face when aiming to strategically align their supply chains on a holistic level. The results of this research are applicable for certain types of global supply networks and can be used for network alignment and strategy development. The approach can furthermore generate insights useable for negotiation support with suppliers.

Association of structural global brain network properties with intelligence in normal aging.

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Florian U Fischer

Full Text Available 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.

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

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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

An Energy-Efficient Target Tracking Framework in Wireless Sensor Networks

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Zhijun Yu

2009-01-01

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

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

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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

Solidarity Action in Global Labor Networks. Four Cases of Workplace Organizing at Foreign Affiliates in the Global South

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Peter Wad

2014-03-01

Full Text Available Globalization transforms workforces of transnational corporation from predominantly home countrydominated workforces into foreign-dominated, multinational workforces. Thus, the national grounding of trade unions as the key form of labor organizing is challenged by new multinational compositions and cross-border relocations of corporate employment affecting working conditions of employees and trade unions in local places. We assume that economic globalization is characterized by expanding global corporate network of vertically and horizontally integrated (equity-based and disintegrated (nonequity-based value chains. We also assume that globalization can both impede and enable labor empowerment. Based on these premises the key question is, how can labor leverage effective power against management in global corporate networks? This question is split into two subquestions: a How can labor theoretically reorganize from national unions and industrial relations institutions into global labor networks that allow prolabor improvement in global workplaces? b How and why has labor in a globalized economy secured the core International Labor Organization (ILO international labor right to organize companies and conduct collective bargaining? The Global Labor Network perspective is adopted as an analytical framework. Empirically, a comparative case methodology is applied comprising four more or less successful industrial disputes where labor achieved the right to organize and undertake collective bargaining. The disputes took place in affiliated factories of foreign transnational corporations located in Malaysia, the Philippines, Sri Lanka, and Turkey. The conclusion is that the combination of global labor capabilities and global labor strategizing must generate strategic labor power that adequately matches the weaknesses of the counterpart’s global corporate network in order to achieve prolabor outcomes. The most efficient solidarity action was leveraged

Automated tracking for advanced satellite laser ranging systems

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McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

1996-06-01

NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.

Global efficiency of structural networks mediates cognitive control in Mild Cognitive Impairment

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Rok Berlot

2016-12-01

Full Text Available 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 localised white matter tract damage and disruption of global network architecture to cognitive control, in older age and Mild Cognitive Impairment (MCI.Methods: 25 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. Conclusions: 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

A Novel Global MPP Tracking of Photovoltaic System based on Whale Optimization Algorithm

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Santhan Kumar Cherukuri

2016-11-01

Full Text Available To harvest maximum amount of solar energy and to attain higher efficiency, photovoltaic generation (PVG systems are to be operated at their maximum power  point (MPP under both variable climatic and partial shaded condition (PSC. From literature most of conventional MPP tracking (MPPT methods are able to guarantee MPP successfully under uniform shading condition but fails to get global MPP as they may trap at local MPP under PSC, which adversely deteriorates the efficiency of Photovoltaic Generation (PVG system. In this paper a novel MPPT based on Whale Optimization Algorithm (WOA is proposed to analyze analytic modeling of PV system considering both series and shunt resistances for MPP tracking under PSC. The proposed algorithm is tested on 6S, 3S2P and 2S3P Photovoltaic array configurations for different shading patterns and results are presented. To compare the performance, GWO and PSO MPPT algorithms are also simulated and results are also presented.  From the results it is noticed that proposed MPPT method is superior to other MPPT methods with reference to accuracy and tracking speed. Article History: Received July 23rd 2016; Received in revised form September 15th 2016; Accepted October 1st 2016; Available online How to Cite This Article: Kumar, C.H.S and Rao, R.S. (2016 A Novel Global MPP Tracking of Photovoltaic System based on Whale Optimization Algorithm. Int. Journal of Renewable Energy Development, 5(3, 225-232. http://dx.doi.org/10.14710/ijred.5.3.225-232

Global exponential stability for nonautonomous cellular neural networks with delays

International Nuclear Information System (INIS)

Zhang Qiang; Wei Xiaopeng; Xu Jin

2006-01-01

In this Letter, by utilizing Lyapunov functional method and Halanay inequalities, we analyze global exponential stability of nonautonomous cellular neural networks with delay. Several new sufficient conditions ensuring global exponential stability of the network are obtained. The results given here extend and improve the earlier publications. An example is given to demonstrate the effectiveness of the obtained results

Polycentrism in Global Health Governance Scholarship; Comment on “Four Challenges That Global Health Networks Face”

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Jale Tosun

2018-01-01

Full Text Available Drawing on an in-depth analysis of eight global health networks, a recent essay in this journal argued that global health networks face four challenges to their effectiveness: problem definition, positioning, coalition-building, and governance. While sharing the argument of the essay concerned, in this commentary, we argue that these analytical concepts can be used to explicate a concept that has implicitly been used in global health governance scholarship for quite a few years. While already prominent in the discussion of climate change governance, for instance, global health governance scholarship could make progress by looking at global health governance as being polycentric. Concisely, polycentric forms of governance mix scales, mechanisms, and actors. Drawing on the essay, we propose a polycentric approach to the study of global health governance that incorporates coalitionbuilding tactics, internal governance and global political priority as explanatory factors.

Real-time object tracking system based on field-programmable gate array and convolution neural network

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Congyi Lyu

2016-12-01

Full Text Available Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit- or graphics processing unit-based computers are not good choices due to the high weight and power consumption. To address the problem, this article proposed a real-time object tracking system based on field-programmable gate array, convolution neural network, and visual servo technology. The time-consuming image processing algorithms, such as distortion correction, color space convertor, and Sobel edge, Harris corner features detector, and convolution neural network were redesigned using the programmable gates in field-programmable gate array. Based on the field-programmable gate array-based image processing, an image-based visual servo controller was designed to drive a two degree of freedom manipulator to track the target in real time. Finally, experiments on the proposed system were performed to illustrate the effectiveness of the real-time object tracking system.

Links that speak: The global language network and its association with global fame

Science.gov (United States)

Ronen, Shahar; Gonçalves, Bruno; Hu, Kevin Z.; Vespignani, Alessandro; Pinker, Steven; Hidalgo, César A.

2014-01-01

Languages vary enormously in global importance because of historical, demographic, political, and technological forces. However, beyond simple measures of population and economic power, there has been no rigorous quantitative way to define the global influence of languages. Here we use the structure of the networks connecting multilingual speakers and translated texts, as expressed in book translations, multiple language editions of Wikipedia, and Twitter, to provide a concept of language importance that goes beyond simple economic or demographic measures. We find that the structure of these three global language networks (GLNs) is centered on English as a global hub and around a handful of intermediate hub languages, which include Spanish, German, French, Russian, Portuguese, and Chinese. We validate the measure of a language’s centrality in the three GLNs by showing that it exhibits a strong correlation with two independent measures of the number of famous people born in the countries associated with that language. These results suggest that the position of a language in the GLN contributes to the visibility of its speakers and the global popularity of the cultural content they produce. PMID:25512502

A game theory approach to target tracking in sensor networks.

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Gu, Dongbing

2011-02-01

In this paper, we investigate a moving-target tracking problem with sensor networks. Each sensor node has a sensor to observe the target and a processor to estimate the target position. It also has wireless communication capability but with limited range and can only communicate with neighbors. The moving target is assumed to be an intelligent agent, which is "smart" enough to escape from the detection by maximizing the estimation error. This adversary behavior makes the target tracking problem more difficult. We formulate this target estimation problem as a zero-sum game in this paper and use a minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore, we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via modeling the information received from neighbors as measurements in the minimax filter. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result.

Multiple Object Tracking Using the Shortest Path Faster Association Algorithm

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Zhenghao Xi

2014-01-01

Full Text Available To solve the persistently multiple object tracking in cluttered environments, this paper presents a novel tracking association approach based on the shortest path faster algorithm. First, the multiple object tracking is formulated as an integer programming problem of the flow network. Then we relax the integer programming to a standard linear programming problem. Therefore, the global optimum can be quickly obtained using the shortest path faster algorithm. The proposed method avoids the difficulties of integer programming, and it has a lower worst-case complexity than competing methods but better robustness and tracking accuracy in complex environments. Simulation results show that the proposed algorithm takes less time than other state-of-the-art methods and can operate in real time.

Global Radiological Source Sorting, Tracking, and Monitoring Project: Phase I Final Report

International Nuclear Information System (INIS)

Walker, Randy M.; Hill, David E.; Gorman, Bryan L.

2010-01-01

As a proof of concept tested in an operational context, the Global Radiological Source Sorting, Tracking, and Monitoring (GRadSSTraM) Project successfully demonstrated that radio frequency identification (RFID) and Web 2.0* technologies can be deployed to track controlled shipments between the United States and the European Union. Between November 2009 and May 2010, a total of 19 shipments were successfully shipped from Oak Ridge National Laboratory (ORNL) by the U.S. Postal Service (USPS) and tracked to their delivery at England's National Physical Laboratory (NPL) by the United Kingdom Royal Mail. However, the project can only be viewed as a qualified success as notable shortcomings were observed. Although the origin and terminus of all RFID-enabled shipments were recorded and no shipments were lost, not all the waypoints between ORNL and NPL were incorporated into the pilot. Given limited resources, the project team was able to install RFID listeners/actuators at three waypoints between the two endpoints. Although it is likely that all shipments followed the same route between ORNL and NPL, it cannot be determined beyond question that all 19 shipments were routed on identical itineraries past the same three waypoints. The pilot also raises the distinct possibility that unattended RFID tracking alone, without positive confirmation that a tagged item has been properly recorded by an RFID reader, does not meet a rigorous standard for shipping controlled items. Indeed, the proof of concept test strongly suggests that a multifaceted approach to tracking may be called for, including tracking methods that are capable of reading and accepting multiple inputs for individual items (e.g., carrier-provided tracking numbers, Universal Product Codes (UPCs), and RFID tags). For controlled items, another apparent requirement is a confirmation feature, human or otherwise, which can certify that an item's RFID tag, UPC, or tracking number has been recorded.

TRUSTWORTHY OPTIMIZED CLUSTERING BASED TARGET DETECTION AND TRACKING FOR WIRELESS SENSOR NETWORK

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C. Jehan

2016-06-01

Full Text Available In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN. The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the identification of clusters and cluster heads using OGSAFCM. Here, kernel fuzzy c-means (KFCM and gravitational search algorithm (GSA are combined to create clusters. At first, oppositional gravitational search algorithm (OGSA is used to optimize the initial clustering center and then the KFCM algorithm is availed to guide the classification and the cluster formation process. In the OGSA, the concept of the opposition based population initialization in the basic GSA to improve the convergence profile. The identified clusters are changed dynamically. The second step deals with the data transmission to the cluster heads. The third step deals with the transmission of aggregated data to the base station as well as the detection of target. From the experimental results, the proposed scheme efficiently and efficiently identifies the target. As a result the tracking error is minimized.

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

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Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks

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Dao-Wei Bi

2007-07-01

Full Text Available A primary criterion of wireless sensor network is energy efficiency. Focused onthe energy problem of target tracking in wireless sensor networks, this paper proposes acluster-based dynamic energy management mechanism. Target tracking problem isformulated by the multi-sensor detection model as well as energy consumption model. Adistributed adaptive clustering approach is investigated to form a reasonable routingframework which has uniform cluster head distribution. Dijkstra’s algorithm is utilized toobtain optimal intra-cluster routing. Target position is predicted by particle filter. Thepredicted target position is adopted to estimate the idle interval of sensor nodes. Hence,dynamic awakening approach is exploited to prolong sleep time of sensor nodes so that theoperation energy consumption of wireless sensor network can be reduced. The sensornodes around the target wake up on time and act as sensing candidates. With the candidatesensor nodes and predicted target position, the optimal sensor node selection is considered.Binary particle swarm optimization is proposed to minimize the total energy consumptionduring collaborative sensing and data reporting. Experimental results verify that theproposed clustering approach establishes a low-energy communication structure while theenergy efficiency of wireless sensor networks is enhanced by cluster-based dynamic energymanagement.

Adaptive approach to global synchronization of directed networks with fast switching topologies

International Nuclear Information System (INIS)

Qin Buzhi; Lu Xinbiao

2010-01-01

Global synchronization of directed networks with switching topologies is investigated. It is found that if there exists at least one directed spanning tree in the network with the fixed time-average topology and the time-average topology is achieved sufficiently fast, the network will reach global synchronization for appreciate coupling strength. Furthermore, this appreciate coupling strength may be obtained by local adaptive approach. A sufficient condition about the global synchronization is given. Numerical simulations verify the effectiveness of the adaptive strategy.

Event-triggered Kalman-consensus filter for two-target tracking sensor networks.

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Su, Housheng; Li, Zhenghao; Ye, Yanyan

2017-11-01

This paper is concerned with the problem of event-triggered Kalman-consensus filter for two-target tracking sensor networks. According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained. Based on the Kalman-consensus filter protocol, all sensors which only depend on its neighbors' information can track their corresponding targets. Furthermore, utilizing Lyapunov method and matrix theory, some sufficient conditions are presented for ensuring the stability of the system. Finally, a simulation example is presented to verify the effectiveness of the proposed event-triggered protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Local and global responses in complex gene regulation networks

Science.gov (United States)

Tsuchiya, Masa; Selvarajoo, Kumar; Piras, Vincent; Tomita, Masaru; Giuliani, Alessandro

2009-04-01

An exacerbated sensitivity to apparently minor stimuli and a general resilience of the entire system stay together side-by-side in biological systems. This apparent paradox can be explained by the consideration of biological systems as very strongly interconnected network systems. Some nodes of these networks, thanks to their peculiar location in the network architecture, are responsible for the sensitivity aspects, while the large degree of interconnection is at the basis of the resilience properties of the system. One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. Here we address, on a data analysis perspective, the discrimination between local and global scale regulations, this goal was achieved by means of the examination of two biological systems: innate immune response in macrophages and oscillating growth dynamics in yeast. Our aim was to reconcile the ‘hard-wired’ local view of gene regulation with a global continuous and scalable one borrowed from statistical physics. This reconciliation is based on the network paradigm in which the local ‘hard-wired’ activities correspond to the activation of specific crucial nodes in the regulation network, while the scalable continuous responses can be equated to the collective oscillations of the network after a perturbation.

Sensor Network-Based Localization for Continuous Tracking Applications: Implementation and Performance Evaluation

Directory of Open Access Journals (Sweden)

Franco Davoli

2008-10-01

Full Text Available The increasing interest in systems able to provide users with immersive services (e.g., domotics, context-aware applications, and immersive distance learning tools has encouraged the development of cheap and effective platforms aimed at tracking objects and people within a certain space. In this context, wireless sensor networks (WSNs can play a very important role, since specialized sensors can be fruitfully exploited in order to generate/receive signals by means of which the WSN can derive the position of nodes joined to the objects to be tracked. The paper presents an original localization platform that exploits a single-hop WSN, based on a Microchip MCU and a Cypress RF device, to track its moving nodes. Specifically, the nodes of the network are divided into three sets: the first set consists of anchor nodes that, according to the commands from the sink (the central node of the WSN, generate ultrasonic pulses. These pulses are received by the second set of (moving nodes, which estimate the pulse time trip and communicate it to the sink. Finally, the last set is constituted by general purpose nodes that collect any kind of data from the surrounding field. The sink gathers all the data, computes the position of moving nodes, and transfers information to external users on the Internet. The algorithms adopted to manage the network and to localize moving nodes are discussed. A working prototype based upon the hardware platform, software, and protocol described in this paper has been deployed and tested, and some results are shown. Simulation results of the localization system are presented to show system scalability.

Global Lunar Gravity Field Determination Using Historical and Recent Tracking Data in Preparation for SELENE

Science.gov (United States)

Goossens, S.; Matsumoto, K.; Namiki, N.; Hanada, H.; Iwata, T.; Tsuruta, S.; Kawano, N.; Sasaki, S.

2006-12-01

In the near future, a number of satellite missions are planned to be launched to the Moon. These missions include initiatives by China, India, the USA, as well as the Japanese SELENE mission. These missions will gather a wealth of lunar data which will improve the knowledge of the Moon. One of the main topics to be addressed will be the lunar gravity field. Especially SELENE will contribute to improving the knowledge of the gravity field, by applying 4-way Doppler tracking between the main satellite and a relay satellite, and by applying a separate differential VLBI experiment. These will improve the determination of the global gravity field, especially over the far side and at the lower degrees (mostly for degrees lower than 30), as is shown by extensive simulations of the SELENE mission. This work focuses on the determination of the global lunar gravity field from all available tracking data to this date. In preparation for the SELENE mission, analysis using Lunar Prospector tracking data, as well as Clementine data and historical data from the Apollo and Lunar Orbiter projects is being conducted at NAOJ. Some SMART-1 tracking data are also included. The goal is to combine the good-quality data from the existing lunar missions up to this date with the tracking data from SELENE in order to derive a new lunar gravity field model. The focus therefore currently lies on processing the available data and extracting lunar gravity field information from them. It is shown that the historical tracking data contribute especially to the lower degrees of the global lunar gravity field model. Due to the large gap in tracking data coverage over the far side for the historical data, the higher degrees are almost fully determined by the a priori information in the form of a Kaula rule. The combination with SELENE data is thus expected to improve the estimate for the lower degrees even further, including coverage of the far side. Since historical tracking data are from orbits with

The Role of Functional Interdependencies in Global Operations Networks

DEFF Research Database (Denmark)

Slepniov, Dmitrij; Wæhrens, Brian Vejrum

2011-01-01

The existing studies do not adequately address the complex interplay between co-evolving production, innovation and service networks. The widening geographical and cognitive gap between these networks means that managing their interfaces in global operations context is becoming strategically...

Surveillance systems to track progress toward global polio eradication - worldwide, 2012-2013.

Science.gov (United States)

Levitt, Alexandra; Diop, Ousmane M; Tangermann, Rudolf H; Paladin, Fem; Kamgang, Jean Baptiste; Burns, Cara C; Chenoweth, Paul J; Goel, Ajay; Wassilak, Steven G F

2014-04-25

In 2012, the World Health Assembly of the World Health Organization (WHO) declared completion of polio eradication a programmatic emergency. Polio cases are detected through surveillance of acute flaccid paralysis (AFP) cases and subsequent testing of stool specimens for polioviruses (PVs) at WHO-accredited laboratories within the Global Polio Laboratory Network (GPLN). AFP surveillance is supplemented by environmental surveillance, testing sewage samples from selected sites for PVs. Virologic surveillance, including genomic sequencing to identify isolates by genotype and measure divergence between isolates, guides Global Polio Eradication Initiative (GPEI) activities by confirming the presence of PV, tracking chains of PV transmission, and highlighting gaps in AFP surveillance quality. This report provides AFP surveillance quality indicators at national and subnational levels during 2012-2013 for countries that experienced PV cases during 2009-2013 in the WHO African Region (AFR) and Eastern Mediterranean Region (EMR), the remaining polio-endemic regions. It also summarizes the results of environmental surveillance and reviews indicators assessing the timeliness of reporting of PV isolation and of virus strain characterization globally. Regional-level performance indicators for timely reporting of PV isolation were met in five of six WHO regions in 2012 and 2013. Of 30 AFR and EMR countries that experienced cases of PV (wild poliovirus [WPV], circulating vaccine-derived poliovirus [cVDPV], or both) during 2009-2013, national performance indicator targets for AFP surveillance and collection of adequate specimens were met in 27 (90%) countries in 2012 and 22 (73%) in 2013. In 17 (57%) countries, ≥80% of the population lived in subnational areas meeting both AFP performance indicators in 2012, decreasing to 13 (43%) in 2013. To achieve polio eradication and certify interruption of PV transmission, intensive efforts to strengthen and maintain AFP surveillance are

Global Interconnectedness - Local Authorities and Transnational Networking

Directory of Open Access Journals (Sweden)

Hans Krause Hansen

2006-09-01

Full Text Available This article argues that, in their continuous and proclaimed efforts at "modernizing" themselves, public sector organizations, also at the sub-national level, increasingly envision the new media as an object of policy making and intervention. At the same time, this focus on the new media facilitates transborder networking, taking the shape of globalizing webs that connect the actors internationally through pro- cesses af mediation and with implications for relations af authority and modes of governance. As such, these webs both constitute and facilitate a form of everyday political globalization which is on the rise. Empirically, our account is based on studies of two local authorities, the cities of Vina del Mar in Chile and Bremen in Germany, as two of the transnational networks that connect them.

Efficient Dynamic Adaptation Strategies for Object Tracking Tree in Wireless Sensor Network

Directory of Open Access Journals (Sweden)

CHEN, M.

2012-12-01

Full Text Available Most object tracking trees are established using the predefined mobility profile. However, when the real object's movement behaviors and query rates are different from the predefined mobility profile and query rates, the update cost and query cost of object tracking tree may increase. To upgrade the object tracking tree, the sink needs to send very large messages to collect the real movement information from the network, introducing a very large message overhead, which is referred to as adaptation cost. The Sub Root Message-Tree Adaptive procedure was proposed to dynamically collect the real movement information under the sub-tree and reconstruct the sub-tree to provide good performance based on the collected information. The simulation results indicates that the Sub Root Message-Tree Adaptive procedure is sufficient to achieve good total cost and lower adaptation cost.

Polycentrism in Global Health Governance Scholarship Comment on "Four Challenges That Global Health Networks Face".

Science.gov (United States)

Tosun, Jale

2017-05-23

Drawing on an in-depth analysis of eight global health networks, a recent essay in this journal argued that global health networks face four challenges to their effectiveness: problem definition, positioning, coalition-building, and governance. While sharing the argument of the essay concerned, in this commentary, we argue that these analytical concepts can be used to explicate a concept that has implicitly been used in global health governance scholarship for quite a few years. While already prominent in the discussion of climate change governance, for instance, global health governance scholarship could make progress by looking at global health governance as being polycentric. Concisely, polycentric forms of governance mix scales, mechanisms, and actors. Drawing on the essay, we propose a polycentric approach to the study of global health governance that incorporates coalitionbuilding tactics, internal governance and global political priority as explanatory factors. © 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.

Positioning and tracking control system analysis for mobile free space optical network

Science.gov (United States)

Li, Yushan; Refai, Hazem; Sluss, , James J., Jr.; Verma, Pramode; LoPresti, Peter

2005-08-01

Free Space Optical (FSO) communication has evolved to be applied to the mobile network, because it can provide up to 2.5Gbps or higher data rate wireless communication. One of the key challenges with FSO systems is to maintain the Line of Sight (LOS) between transmitter and receiver. In this paper, the feasibility and performance of applying the FSO technology to the mobile network is explored, and the design plan of the attitude positioning and tracking control system of the FSO transceiver is investigated. First, the system architecture is introduced, the requirements for the control system are analyzed, the involved reference frames and frame transformation are presented. Second, the control system bandwidth is used to evaluate the system performance in controlling a positioning system consisting of a gimbal and a steering mirror, some definitions to describe the positioning accuracy and tracking capacity are given. The attitude control of a FSO transceiver is split into 2 similar channels: pitch and yaw. Using an equivalent linear control system model, the simulations are carried out, with and without the presence of uncertainties that includes GPS data errors and sensor measurement errors. Finally, based on the simulation results in the pitch channel, the quantitative evaluation on the performance of the control system is given, including positioning accuracy, tracking capability and uncertainty tolerance.

A radar-enabled collaborative sensor network integrating COTS technology for surveillance and tracking.

Science.gov (United States)

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R; Demirer, R Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.

Ecological network analysis on global virtual water trade.

Science.gov (United States)

Yang, Zhifeng; Mao, Xufeng; Zhao, Xu; Chen, Bin

2012-02-07

Global water interdependencies are likely to increase with growing virtual water trade. To address the issues of the indirect effects of water trade through the global economic circulation, we use ecological network analysis (ENA) to shed insight into the complicated system interactions. A global model of virtual water flow among agriculture and livestock production trade in 1995-1999 is also built as the basis for network analysis. Control analysis is used to identify the quantitative control or dependency relations. The utility analysis provides more indicators for describing the mutual relationship between two regions/countries by imitating the interactions in the ecosystem and distinguishes the beneficiary and the contributor of virtual water trade system. Results show control and utility relations can well depict the mutual relation in trade system, and direct observable relations differ from integral ones with indirect interactions considered. This paper offers a new way to depict the interrelations between trade components and can serve as a meaningful start as we continue to use ENA in providing more valuable implications for freshwater study on a global scale.

Fuel economy and torque tracking in camless engines through optimization of neural networks

International Nuclear Information System (INIS)

Ashhab, Moh'd Sami S.

2008-01-01

The feed forward controller of a camless internal combustion engine is modeled by inverting a multi-input multi-output feed forward artificial neural network (ANN) model of the engine. The engine outputs, pumping loss and cylinder air charge, are related to the inputs, intake valve lift and closing timing, by the artificial neural network model, which is trained with historical input-output data. The controller selects the intake valve lift and closing timing that will mimimize the pumping loss and achieve engine torque tracking. Lower pumping loss means better fuel economy, whereas engine torque tracking gurantees the driver's torque demand. The inversion of the ANN is performed with the complex method constrained optimization. How the camless engine inverse controller can be augmented with adaptive techniques to maintain accuracy even when the engine parts degrade is discussed. The simulation results demonstrate the effectiveness of the developed camless engine controller

Extended neural network-based scheme for real-time force tracking with magnetorheological dampers

DEFF Research Database (Denmark)

Weber, Felix; Bhowmik, Subrata; Høgsberg, Jan Becker

2014-01-01

This paper validates numerically and experimentally a new neural network-based real-time force tracking scheme for magnetorheological (MR) dampers on a five-storey shear frame with MR damper. The inverse model is trained with absolute values of measured velocity and force because the targeted...... the pre-yield to the post-yield region. A control-oriented approach is presented to compensate for these drawbacks. The resulting control force tracking scheme is validated for the emulation of viscous damping, clipped viscous damping with negative stiffness, and friction damping with negative stiffness...

Global and local targeted immunization in networks with community structure

International Nuclear Information System (INIS)

Yan, Shu; Tang, Shaoting; Pei, Sen; Zheng, Zhiming; Fang, Wenyi

2015-01-01

Immunization plays an important role in the field of epidemic spreading in complex networks. In previous studies, targeted immunization has been proved to be an effective strategy. However, when extended to networks with community structure, it is unknown whether the superior strategy is to vaccinate the nodes who have the most connections in the entire network (global strategy), or those in the original community where epidemic starts to spread (local strategy). In this work, by using both analytic approaches and simulations, we observe that the answer depends on the closeness between communities. If communities are tied closely, the global strategy is superior to the local strategy. Otherwise, the local targeted immunization is advantageous. The existence of a transitional value of closeness implies that we should adopt different strategies. Furthermore, we extend our investigation from two-community networks to multi-community networks. We consider the mode of community connection and the location of community where epidemic starts to spread. Both simulation results and theoretical predictions show that local strategy is a better option for immunization in most cases. But if the epidemic begins from a core community, global strategy is superior in some cases. (paper)

Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Yin Wang

2015-12-01

Full Text Available There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select the node for the next hop with the highest potential bandwidth capacity to resume communication. Key to this strategy is that each node merely maintains two parameters that contain its historical bandwidth varying trend and then predict its near future bandwidth capacity. Then, the forwarding node selects the next hop with the highest potential bandwidth capacity. Simulations demonstrate that our approach significantly increases the data received by the sink node and decreases the delay on video transmission in Wireless Multimedia Sensor Network environments.

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

Science.gov (United States)

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.

Acquisition management of the Global Transportation Network

Science.gov (United States)

2001-08-02

This report discusses the acquisition management of the Global transportation Network by the U.S. Transportation Command. This report is one in a series of audit reports addressing DoD acquisition management of information technology systems. The Glo...

Distributed Tracking in Distributed Sensor Networks

Science.gov (United States)

1988-05-26

Glocal Track 6-17 6-12: Case II: Initial Glocal Track 6-18 6-13: Local Tracking Results with Multiple Model Approach 6-19 6-14: Model Probability History...3480.0- 2290.0e iee. onee -5800 -4600.8 -3400.8 -2208.8 -1886 X (Mi) Figure 6-11: Case 1: Initial Glocal Track 6-17 460. 420. 38 . 3488.9 1st 3498.9

Maintenance of time and frequency in the Jet Propulsion Laboratory's Deep Space Network using the Global Positioning System

Science.gov (United States)

Clements, P. A.; Borutzki, S. E.; Kirk, A.

1984-01-01

The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, must maintain time and frequency within specified limits in order to accurately track the spacecraft engaged in deep space exploration. Various methods are used to coordinate the clocks among the three tracking complexes. These methods include Loran-C, TV Line 10, Very Long Baseline Interferometry (VLBI), and the Global Positioning System (GPS). Calculations are made to obtain frequency offsets and Allan variances. These data are analyzed and used to monitor the performance of the hydrogen masers that provide the reference frequencies for the DSN Frequency and Timing System (DFT). Areas of discussion are: (1) a brief history of the GPS timing receivers in the DSN, (2) a description of the data and information flow, (3) data on the performance of the DSN master clocks and GPS measurement system, and (4) a description of hydrogen maser frequency steering using these data.

Global asymptotical ω-periodicity of a fractional-order non-autonomous neural networks.

Science.gov (United States)

Chen, Boshan; Chen, Jiejie

2015-08-01

We study the global asymptotic ω-periodicity for a fractional-order non-autonomous neural networks. Firstly, based on the Caputo fractional-order derivative it is shown that ω-periodic or autonomous fractional-order neural networks cannot generate exactly ω-periodic signals. Next, by using the contraction mapping principle we discuss the existence and uniqueness of S-asymptotically ω-periodic solution for a class of fractional-order non-autonomous neural networks. Then by using a fractional-order differential and integral inequality technique, we study global Mittag-Leffler stability and global asymptotical periodicity of the fractional-order non-autonomous neural networks, which shows that all paths of the networks, starting from arbitrary points and responding to persistent, nonconstant ω-periodic external inputs, asymptotically converge to the same nonconstant ω-periodic function that may be not a solution. Copyright © 2015 Elsevier Ltd. All rights reserved.

International collaboration in science: The global map and the network

NARCIS (Netherlands)

Leydesdorff, L.; Wagner, C.S.; Park, H.W.; Adams, J.

2013-01-01

The network of international co-authorship relations has been dominated by certain European nations and the USA, but this network is rapidly expanding at the global level. Between 40 and 50 countries appear in the center of the international network in 2011, and almost all (201) nations are nowadays

Core Support to Global Development Network (GND) - Phase II ...

International Development Research Centre (IDRC) Digital Library (Canada)

The Global Development Network (GDN) was launched by the World Bank in 1999 on the premise that good policy research, properly applied, can accelerate development and improve people's lives. Working mainly through regional networks, GDN supports economic and, increasingly, social science research in and on ...

A Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking

Directory of Open Access Journals (Sweden)

R. Murat Demirer

2012-01-01

Full Text Available The feasibility of using Commercial Off-The-Shelf (COTS sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost ( < $50 US miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.

A Wireless Sensor Network with Soft Computing Localization Techniques for Track Cycling Applications.

Science.gov (United States)

Gharghan, Sadik Kamel; Nordin, Rosdiadee; Ismail, Mahamod

2016-08-06

In this paper, we propose two soft computing localization techniques for wireless sensor networks (WSNs). The two techniques, Neural Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN), focus on a range-based localization method which relies on the measurement of the received signal strength indicator (RSSI) from the three ZigBee anchor nodes distributed throughout the track cycling field. The soft computing techniques aim to estimate the distance between bicycles moving on the cycle track for outdoor and indoor velodromes. In the first approach the ANFIS was considered, whereas in the second approach the ANN was hybridized individually with three optimization algorithms, namely Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Backtracking Search Algorithm (BSA). The results revealed that the hybrid GSA-ANN outperforms the other methods adopted in this paper in terms of accuracy localization and distance estimation accuracy. The hybrid GSA-ANN achieves a mean absolute distance estimation error of 0.02 m and 0.2 m for outdoor and indoor velodromes, respectively.

Global 4-H Network: Laying the Groundwork for Global Extension Opportunities

Science.gov (United States)

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…

Novel results for global robust stability of delayed neural networks

International Nuclear Information System (INIS)

Yucel, Eylem; Arik, Sabri

2009-01-01

This paper investigates the global robust convergence properties of continuous-time neural networks with discrete time delays. By employing suitable Lyapunov functionals, some sufficient conditions for the existence, uniqueness and global robust asymptotic stability of the equilibrium point are derived. The conditions can be easily verified as they can be expressed in terms of the network parameters only. Some numerical examples are also given to compare our results with previous robust stability results derived in the literature.

On the track of fish batches in three distribution networks

DEFF Research Database (Denmark)

Randrup, Maria; Wu, Haiping; Jørgensen, Bo M.

2012-01-01

Three fish products sampled in retail shops were traced back to their origin and fish from the same batch were tracked forward towards the retailer, thereby simulating a recall situation. The resulting distribution networks were very complex, but to the extent that companies were willing to provi...... of discovering a fault as early as possible in order to minimise the costs of a recall. The localisation of distributed products during a recall operation can be facilitated by a well-constructed traceability system....

Technology on the Move: Recent and Forthcoming Innovations for Tracking Migratory Birds

DEFF Research Database (Denmark)

Bridge, Eli S.; Thorup, Kasper; Bowlin, Melissa S.

2011-01-01

networks, solar geolocation, radar, and information technology are improving our understanding of when and where birds go during their annual cycles and informing numerous scientific disciplines, including evolutionary biology, population ecology, and global change. The recent developments described......Basic questions about the life histories of migratory birds have confounded scientists for generations, yet we are nearing an era of historic discovery as new tracking technologies make it possible to determine the timing and routes of an increasing number of bird migrations. Tracking small flying...

Development of global cortical networks in early infancy.

Science.gov (United States)

Homae, Fumitaka; Watanabe, Hama; Otobe, Takayuki; Nakano, Tamami; Go, Tohshin; Konishi, Yukuo; Taga, Gentaro

2010-04-07

Human cognition and behaviors are subserved by global networks of neural mechanisms. Although the organization of the brain is a subject of interest, the process of development of global cortical networks in early infancy has not yet been clarified. In the present study, we explored developmental changes in these networks from several days to 6 months after birth by examining spontaneous fluctuations in brain activity, using multichannel near-infrared spectroscopy. We set up 94 measurement channels over the frontal, temporal, parietal, and occipital regions of the infant brain. The obtained signals showed complex time-series properties, which were characterized as 1/f fluctuations. To reveal the functional connectivity of the cortical networks, we calculated the temporal correlations of continuous signals between all the pairs of measurement channels. We found that the cortical network organization showed regional dependency and dynamic changes in the course of development. In the temporal, parietal, and occipital regions, connectivity increased between homologous regions in the two hemispheres and within hemispheres; in the frontal regions, it decreased progressively. Frontoposterior connectivity changed to a "U-shaped" pattern within 6 months: it decreases from the neonatal period to the age of 3 months and increases from the age of 3 months to the age of 6 months. We applied cluster analyses to the correlation coefficients and showed that the bilateral organization of the networks begins to emerge during the first 3 months of life. Our findings suggest that these developing networks, which form multiple clusters, are precursors of the functional cerebral architecture.

New developments of the R & D silicon tracking for linear collider on ...

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics; Volume 69; Issue 6. New developments of the R & D silicon tracking for linear collider on silicon trackers. A Savoy-Navarro on behalf of the SiLC R&D Collaboration. Data Acquisition and Global Detector Network Volume 69 Issue 6 December 2007 pp 1199-1206 ...

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

OpenAIRE

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...

Globalizing Social Justice Education: The Case of The Global Solidarity Network Study e-Broad Program

Science.gov (United States)

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…

In Search of a Network Organization for Innovation: A Multilevel Analysis on Transnational Corporations' Global Innovation

DEFF Research Database (Denmark)

Hu, Yimei

2013-01-01

4 explores how transnational corporations perceive and design an internal network organization to facilitate global innovation. Based on a multiple case study of three Danish transnational corporations’ global R&D organization, this paper shows three types of network organization design...... explores how an SME develops a network organization consisting of both interfirm innovation networks and an internal network organization to facilitate its global innovation strategy. Regarding the intraorganizational network organization, market mechanism is adopted to optimize internal resource...... corporations perceive/design a network organization to facilitate their global innovation? • To what extent and how can we manage a network organization? Research focus of the dissertation is on transnational corporations’ network organization for innovation. The first research question aims to clarify...

Managerial capabilities of the home base in an intra-organisational global network

DEFF Research Database (Denmark)

Mykhaylenko, Alona

of the HB change in the process of its global intra-organisational network evolution. In particular, the four papers constituting this thesis investigate how global intra-organisational networks evolve, how the types of network management capabilities of the HB change along with such network evolution....... This investigation was conducted through a retrospective longitudinal case study of one Danish original equipment manufacturer and its three subsidiaries in China, Slovakia, and the US. The findings, first of all, support, extend, and modify the revised Uppsala globalisation model with regard to the types...

Global stability of stochastic high-order neural networks with discrete and distributed delays

International Nuclear Information System (INIS)

Wang Zidong; Fang Jianan; Liu Xiaohui

2008-01-01

High-order neural networks can be considered as an expansion of Hopfield neural networks, and have stronger approximation property, faster convergence rate, greater storage capacity, and higher fault tolerance than lower-order neural networks. In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with discrete and distributed time-delays. Based on an Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived, which guarantee the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the stochastic high-order delayed neural networks under consideration are globally asymptotically stable in the mean square if two linear matrix inequalities (LMIs) are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also shown that the main results in this paper cover some recently published works. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria

Global track finder for Belle II experiment

Energy Technology Data Exchange (ETDEWEB)

Trusov, Viktor; Feindt, Michael; Heck, Martin; Kuhr, Thomas; Goldenzweig, Pablo [Karlsruhe Institute of Technology, IEKP (Germany); Collaboration: Belle II-Collaboration

2015-07-01

We present an implementation of a method based on the Legendre transformation for reconstruction charged particle tracks in the central drift chamber of the Belle II experiment. The method is designed for fast track finding and restoring circular patterns of track hits in transverse plane. It is done by searching for common tangents to drift circles of hits in the conformal space. With known transverse trajectories longitudinal momentum estimation performed by assigning stereo hits followed by determination of the track parameters. The method includes algorithms responsible for track quality estimation and reduction of rate of fakes. The work is targeting at increasing the efficiency and reducing the execution time because the computing power available to the experiment is limited. The algorithm is developed within the Belle II software environment with using Monte-Carlo simulation for probing its efficiency.

The Global Climatology Network Precipitation data

International Nuclear Information System (INIS)

Peterson, T.C.; Easterling, D.R.; Eischeid, J.K.

1993-01-01

Several years ago, in response to growing concern about global climate change, the US National Climatic Data Center and the Carbon Dioxide Information Analysis Center undertook an effort to create a baseline global land surface climate data set called the Global Historical Climatology Network (GHCN, Vose et al., 1992). GHCN was created by merging several large existing climate data sets into one data base. Fifteen separate data sets went into the creation of the GHCN version 1.0. GHCN version 1.0 was released in 1992. It has 7,533 precipitation stations, but the number of stations varies with time. A slight majority (55%) have records in excess of 50 years, and a significant proportion (13%) have records in excess of 100 years. The longest period of record for any given station is 291 years (1697--1987 for Kew, United Kingdom)

From global agenda-setting to domestic implementation: successes and challenges of the global health network on tobacco control.

Science.gov (United States)

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.

Tracking socioeconomic vulnerability using network analysis: insights from an avian influenza outbreak in an ostrich production network.

Directory of Open Access Journals (Sweden)

Christine Moore

Full Text Available BACKGROUND: The focus of management in many complex systems is shifting towards facilitation, adaptation, building resilience, and reducing vulnerability. Resilience management requires the development and application of general heuristics and methods for tracking changes in both resilience and vulnerability. We explored the emergence of vulnerability in the South African domestic ostrich industry, an animal production system which typically involves 3-4 movements of each bird during its lifetime. This system has experienced several disease outbreaks, and the aim of this study was to investigate whether these movements have contributed to the vulnerability of this system to large disease outbreaks. METHODOLOGY/PRINCIPAL FINDINGS: The ostrich production system requires numerous movements of birds between different farm types associated with growth (i.e. Hatchery to juvenile rearing farm to adult rearing farm. We used 5 years of movement records between 2005 and 2011 prior to an outbreak of Highly Pathogenic Avian Influenza (H5N2. These data were analyzed using a network analysis in which the farms were represented as nodes and the movements of birds as links. We tested the hypothesis that increasing economic efficiency in the domestic ostrich industry in South Africa made the system more vulnerable to outbreak of Highly Pathogenic Avian Influenza (H5N2. Our results indicated that as time progressed, the network became increasingly vulnerable to pathogen outbreaks. The farms that became infected during the outbreak displayed network qualities, such as significantly higher connectivity and centrality, which predisposed them to be more vulnerable to disease outbreak. CONCLUSIONS/SIGNIFICANCE: Taken in the context of previous research, our results provide strong support for the application of network analysis to track vulnerability, while also providing useful practical implications for system monitoring and management.

China's evolving role in global production networks: Implications for Trump's trade war

OpenAIRE

Athukorala, Prema-chandra

2017-01-01

This paper examines China's evolving role in global production networks and its implications for assessing the potential impact of the "trade war" declared by President Trump. The analysis, which is based on a systematic disaggregation of trade based on global production sharing into components and final assembly, suggests that the Sino-US trade gap is a structural phenomenon driven by the pivotal role played by China within East Asia cantered production networks. The global competitiveness o...

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments.

Science.gov (United States)

Jia, Yunjian; Zhou, Zhenyu; Chen, Fei; Duan, Peng; Guo, Zhen; Mumtaz, Shahid

2017-01-13

Tracking people's behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi)-based tracking method. To show the feasibility, we target tracking people's access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC)-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people's access behaviors can be correctly tracked within a one-second delay.

Global spatio-temporal patterns in human migration: a complex network perspective.

Science.gov (United States)

Davis, Kyle F; D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca

2013-01-01

Migration is a powerful adaptive strategy for humans to navigate hardship and pursue a better quality of life. As a universal vehicle facilitating exchanges of ideas, culture, money and goods, international migration is a major contributor to globalization. Consisting of countries linked by multiple connections of human movements, global migration constitutes a network. Despite the important role of human migration in connecting various communities in different parts of the world, the topology and behavior of the international migration network and its changes through time remain poorly understood. Here we show that the global human migration network became more interconnected during the latter half of the twentieth century and that migrant destination choice partly reflects colonial and postcolonial histories, language, religion, and distances. From 1960 to 2000 we found a steady increase in network transitivity (i.e. connectivity between nodes connected to the same node), a decrease in average path length and an upward shift in degree distribution, all of which strengthened the 'small-world' behavior of the migration network. Furthermore, we found that distinct groups of countries preferentially interact to form migration communities based largely on historical, cultural and economic factors.

Global spatio-temporal patterns in human migration: a complex network perspective.

Directory of Open Access Journals (Sweden)

Kyle F Davis

Full Text Available Migration is a powerful adaptive strategy for humans to navigate hardship and pursue a better quality of life. As a universal vehicle facilitating exchanges of ideas, culture, money and goods, international migration is a major contributor to globalization. Consisting of countries linked by multiple connections of human movements, global migration constitutes a network. Despite the important role of human migration in connecting various communities in different parts of the world, the topology and behavior of the international migration network and its changes through time remain poorly understood. Here we show that the global human migration network became more interconnected during the latter half of the twentieth century and that migrant destination choice partly reflects colonial and postcolonial histories, language, religion, and distances. From 1960 to 2000 we found a steady increase in network transitivity (i.e. connectivity between nodes connected to the same node, a decrease in average path length and an upward shift in degree distribution, all of which strengthened the 'small-world' behavior of the migration network. Furthermore, we found that distinct groups of countries preferentially interact to form migration communities based largely on historical, cultural and economic factors.

Global Practical Stabilization and Tracking for an Underactuated Ship - A Combined Averaging and Backstepping Approach

Directory of Open Access Journals (Sweden)

Kristin Y. Pettersen

1999-10-01

Full Text Available We solve both the global practical stabilization and tracking problem for an underactuated ship, using a combined integrator backstepping and averaging approach. Exponential convergence to an arbitrarily small neighbourhood of the origin and of the reference trajectory, respectively, is proved. Simulation results are included.

Distributed radar network for real-time tracking of bullet trajectory

Science.gov (United States)

Zhang, Yimin; Li, Xin; Jin, Yuanwei; Amin, Moeness G.; Eydgahi, Ali

2009-05-01

Gunshot detection, sniper localization, and bullet trajectory prediction are of significant importance in military and homeland security applications. While the majority of existing work is based on acoustic and electro-optical sensors, this paper develops a framework of networked radar systems that uses distributed radar sensor networks to achieve the aforementioned objectives. The use of radio frequency radar systems allows the achievement of subtime- of-flight tracking response, enabling to response before the bullet reaches its target and, as such, effectively leading to the reduction of injuries and casualties in military and homeland security operations. The focus of this paper is to examine the MIMO radar concept with concurrent transmission of low-correlation waveforms from multiple radar sets to ensure wide surveillance coverage and maintain a high waveform repetition frequency for long coherent time interval required to achieve return signal concentration.

Globally exponential stability of neural network with constant and variable delays

International Nuclear Information System (INIS)

Zhao Weirui; Zhang Huanshui

2006-01-01

This Letter presents new sufficient conditions of globally exponential stability of neural networks with delays. We show that these results generalize recently published globally exponential stability results. In particular, several different globally exponential stability conditions in the literatures which were proved using different Lyapunov functionals are generalized and unified by using the same Lyapunov functional and the technique of inequality of integral. A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed neural networks. Those conditions are less restrictive than those given in the earlier references

Neural networks for tracking of unknown SISO discrete-time nonlinear dynamic systems.

Science.gov (United States)

Aftab, Muhammad Saleheen; Shafiq, Muhammad

2015-11-01

This article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operating as controller and estimator. A Lyapunov function based back propagation learning algorithm is used for online adjustment of the controller and estimator parameters. The controller and estimator error convergence and closed-loop system stability analysis is performed by Lyapunov stability theory. Moreover, two simulation examples and one real-time experiment are investigated as case studies. The achieved results successfully validate the controller performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Defense Science Board Task Force on Military Satellite Communication and Tactical Networking. Executive Summary

Science.gov (United States)

2017-03-01

Interface Processor BCT Brigade Combat Team BFT Blue Force Tracking BLOS Beyond Line-of-Sight C2 Command And Control C2E Communications in...Satellite Communications and Tactical Networking Appendix D-2 GIG Global Information Grid GMR Ground Mobile Radio GPS Global Positioning System...System SIPRNet Secret Internet Protocol Router Network SITREPS Situational Reports SMART -T Secure Mobile Anti-Jam Reliable Tactical Terminal SMC Space

A network-based frequency analysis of Inclusive Wealth to track sustainable development in world countries.

Science.gov (United States)

Ahmad, Nasir; Derrible, Sybil; Managi, Shunsuke

2018-07-15

Using human (HC), natural (NC), and produced (PC) capital from Inclusive Wealth as representatives of the triple bottom line of sustainability and utilizing elements of network science, we introduce a Network-based Frequency Analysis (NFA) method to track sustainable development in world countries from 1990 to 2014. The method compares every country with every other and links them when values are close. The country with the most links becomes the main trend, and the performance of every other country is assessed based on its 'orbital' distance from the main trend. Orbital speeds are then calculated to evaluate country-specific dynamic trends. Overall, we find an optimistic trend for HC only, indicating positive impacts of global initiatives aiming towards socio-economic development in developing countries like the Millennium Development Goals and 'Agenda 21'. However, we also find that the relative performance of most countries has not changed significantly in this period, regardless of their gradual development. Specifically, we measure a decrease in produced and natural capital for most countries, despite an increase in GDP, suggesting unsustainable development. Furthermore, we develop a technique to cluster countries and project the results to 2050, and we find a significant decrease in NC for nearly all countries, suggesting an alarming depletion of natural resources worldwide. Copyright © 2018 Elsevier Ltd. All rights reserved.

Global terrestrial water storage connectivity revealed using complex climate network analyses

Science.gov (United States)

Sun, A. Y.; Chen, J.; Donges, J.

2015-07-01

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Network master planning for a global manufacturing company

OpenAIRE

Heinz, Michael Pierre

2006-01-01

Production in global, intra-organisational networks is becoming more common. In this context, the allocation of production quantities to constrained manufacturing capacity is a challenging process. Due to a volatile environment it is argued to be impossible to achieve a ‘clean’ system design with dedicated resources which exactly meets future demand. Thus, recursive ‘Network Master Planning’ (NMP) becomes necessary. The aim of this research is to generate an understanding of th...

Networks of global bird invasion altered by regional trade ban.

Science.gov (United States)

Reino, Luís; Figueira, Rui; Beja, Pedro; Araújo, Miguel B; Capinha, César; Strubbe, Diederik

2017-11-01

Wildlife trade is a major pathway for introduction of invasive species worldwide. However, how exactly wildlife trade influences invasion risk, beyond the transportation of individuals to novel areas, remains unknown. We analyze the global trade network of wild-caught birds from 1995 to 2011 as reported by CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora). We found that before the European Union ban on imports of wild-caught birds, declared in 2005, invasion risk was closely associated with numbers of imported birds, diversity of import sources, and degree of network centrality of importer countries. After the ban, fluxes of global bird trade declined sharply. However, new trade routes emerged, primarily toward the Nearctic, Afrotropical, and Indo-Malay regions. Although regional bans can curtail invasion risk globally, to be fully effective and prevent rerouting of trade flows, bans should be global.

Architectural Design for the Global Legal Information Network

Science.gov (United States)

Kalpakis, Konstantinos

1999-01-01

In this report, we provide a summary of our activities regarding the goals, requirements analysis, design, and prototype implementation for the Global Legal Information Network, a joint effort between the Law Library of Congress and NASA.

Using The Global Positioning System For Earth Orbiter and Deep Space Network

Science.gov (United States)

Lichten, Stephen M.; Haines, Bruce J.; Young, Lawrence E.; Dunn, Charles; Srinivasan, Jeff; Sweeney, Dennis; Nandi, Sumita; Spitzmesser, Don

1994-01-01

The Global Positioning System (GPS) can play a major role in supporting orbit and trajectory determination for spacecraft in a wide range of applications, including low-Earth, high-earth, and even deep space (interplanetary) tracking.

On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

Science.gov (United States)

Rubaai, Ahmed

1996-01-01

A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

International Children's Palliative Care Network: A Global Action Network for Children With Life-Limiting Conditions.

Science.gov (United States)

Marston, Joan; Boucher, Sue; Downing, Julia

2018-02-01

The International Children's Palliative Care Network (ICPCN) is a global network of individuals and organizations working together to reach the estimated 21 million children with life-limiting conditions and life-threatening illnesses. The drive to establish the ICPCN was born from the recognition of the gaps in service provision for children's palliative care and the need to collaborate, network, and share resources. Established in 2005 during a meeting in Seoul, South Korea, the ICPCN has developed over the years into an established network with a global membership. The history of the organization is described, including some of the key events since its inception. Working in collaboration with others, ICPCN has five key focus areas: Communication; Advocacy; Research; Education; and Strategic development, and is the only international charity working globally for the rights of children with palliative care needs. Activities in these areas are discussed, along with the inter-connection between the five areas. Without the ICPCN, palliative care for children would not have developed as far as it has over the years and the organization is committed to ongoing work in this area until all children requiring palliative care have access to quality services, wherever they live around the world. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

The Global Network of Isotopes in Precipitation after 55 years: assessing past, present and future developments

Science.gov (United States)

Terzer, Stefan; Araguas-Araguas, Luis; Wassenaar, Leonard I.; Aggarwal, Pradeep K.

2015-04-01

The Global Network of Isotopes in Precipitation (GNIP) is a global observation programme operated by the International Atomic Energy Agency (IAEA), in cooperation with the World Meteorological Organization (WMO) and more than 100 contributing institutions worldwide. GNIP has been the primary repository for baseline stable (δ18O, δ2H) and radioactive (3H) isotope data since its foundation in 1960. The impetus for GNIP was the monitoring of radioactive fallout from atmospheric thermonuclear testing and resulting tritium levels of precipitation, but tritium together with stable isotopes was recognized as a key to understanding hydrological processes. Later, new applications were developed focusing on hydrometeorology and paleoclimatic research. Increasingly, GNIP data are being used more widely in ecological and forensic investigations, e.g. for tracking of migratory animals. The GNIP database comprises more than 135,000 isotopic records (δ18O: 63,000; δ2H: 55,000; 3H: 63,000) of monthly composite precipitation samples from more than 1,000 stations worldwide. About 300 stations are currently active for stable isotopes and ca. 100 for tritium. Data for most of the active stations is available up to 2013. Several national isotopic observation networks (e.g. in Austria, Australia, China or the United States of America) exist besides GNIP, complementing precipitation isotope data at national levels. The spatially and temporally discrete nature of the GNIP dataset induces coverage gaps. Recently, highly-resolved gridded datasets were established to help overcome this deficiency through geostatistical prediction models. These 'isoscape' (isotopic landscapes) are based on combinations of multiple regression and interpolation methods, with a range of parameterization available at regional and global levels. Attempts to bridge the gap between 'one-size-fits-all' global parameterization and improved predictions at regional and local levels led to the establishment of a

Robust Individual-Cell/Object Tracking via PCANet Deep Network in Biomedicine and Computer Vision

Directory of Open Access Journals (Sweden)

Bineng Zhong

2016-01-01

Full Text Available Tracking individual-cell/object over time is important in understanding drug treatment effects on cancer cells and video surveillance. A fundamental problem of individual-cell/object tracking is to simultaneously address the cell/object appearance variations caused by intrinsic and extrinsic factors. In this paper, inspired by the architecture of deep learning, we propose a robust feature learning method for constructing discriminative appearance models without large-scale pretraining. Specifically, in the initial frames, an unsupervised method is firstly used to learn the abstract feature of a target by exploiting both classic principal component analysis (PCA algorithms with recent deep learning representation architectures. We use learned PCA eigenvectors as filters and develop a novel algorithm to represent a target by composing of a PCA-based filter bank layer, a nonlinear layer, and a patch-based pooling layer, respectively. Then, based on the feature representation, a neural network with one hidden layer is trained in a supervised mode to construct a discriminative appearance model. Finally, to alleviate the tracker drifting problem, a sample update scheme is carefully designed to keep track of the most representative and diverse samples during tracking. We test the proposed tracking method on two standard individual cell/object tracking benchmarks to show our tracker's state-of-the-art performance.

The Global Alzheimer's Association Interactive Network.

Science.gov (United States)

Toga, Arthur W; Neu, Scott C; Bhatt, Priya; Crawford, Karen L; Ashish, Naveen

2016-01-01

The Global Alzheimer's Association Interactive Network (GAAIN) is consolidating the efforts of independent Alzheimer's disease data repositories around the world with the goals of revealing more insights into the causes of Alzheimer's disease, improving treatments, and designing preventative measures that delay the onset of physical symptoms. We developed a system for federating these repositories that is reliant on the tenets that (1) its participants require incentives to join, (2) joining the network is not disruptive to existing repository systems, and (3) the data ownership rights of its members are protected. We are currently in various phases of recruitment with over 55 data repositories in North America, Europe, Asia, and Australia and can presently query >250,000 subjects using GAAIN's search interfaces. GAAIN's data sharing philosophy, which guided our architectural choices, is conducive to motivating membership in a voluntary data sharing network. Copyright © 2016 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Atmosphere surface storm track response to resolved ocean mesoscale in two sets of global climate model experiments

Science.gov (United States)

Small, R. Justin; Msadek, Rym; Kwon, Young-Oh; Booth, James F.; Zarzycki, Colin

2018-05-01

It has been hypothesized that the ocean mesoscale (particularly ocean fronts) can affect the strength and location of the overlying extratropical atmospheric storm track. In this paper, we examine whether resolving ocean fronts in global climate models indeed leads to significant improvement in the simulated storm track, defined using low level meridional wind. Two main sets of experiments are used: (i) global climate model Community Earth System Model version 1 with non-eddy-resolving standard resolution or with ocean eddy-resolving resolution, and (ii) the same but with the GFDL Climate Model version 2. In case (i), it is found that higher ocean resolution leads to a reduction of a very warm sea surface temperature (SST) bias at the east coasts of the U.S. and Japan seen in standard resolution models. This in turn leads to a reduction of storm track strength near the coastlines, by up to 20%, and a better location of the storm track maxima, over the western boundary currents as observed. In case (ii), the change in absolute SST bias in these regions is less notable, and there are modest (10% or less) increases in surface storm track, and smaller changes in the free troposphere. In contrast, in the southern Indian Ocean, case (ii) shows most sensitivity to ocean resolution, and this coincides with a larger change in mean SST as ocean resolution is changed. Where the ocean resolution does make a difference, it consistently brings the storm track closer in appearance to that seen in ERA-Interim Reanalysis data. Overall, for the range of ocean model resolutions used here (1° versus 0.1°) we find that the differences in SST gradient have a small effect on the storm track strength whilst changes in absolute SST between experiments can have a larger effect. The latter affects the land-sea contrast, air-sea stability, surface latent heat flux, and the boundary layer baroclinicity in such a way as to reduce storm track activity adjacent to the western boundary in the N

The Global Geodetic Observing System: Space Geodesy Networks for the Future

Science.gov (United States)

Pearlman, Michael; Pavlis, Erricos; Ma, Chopo; Altamini, Zuheir; Noll, Carey; Stowers, David

2011-01-01

Ground-based networks of co-located space geodetic techniques (VLBI, SLR, GNSS. and DORIS) are the basis for the development and maintenance of the International Terrestrial Reference frame (ITRF), which is our metric of reference for measurements of global change, The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) has established a task to develop a strategy to design, integrate and maintain the fundamental geodetic network and supporting infrastructure in a sustainable way to satisfy the long-term requirements for the reference frame. The GGOS goal is an origin definition at 1 mm or better and a temporal stability on the order of 0.1 mm/y, with similar numbers for the scale and orientation components. These goals are based on scientific requirements to address sea level rise with confidence, but other applications are not far behind. Recent studies including one by the US National Research Council has strongly stated the need and the urgency for the fundamental space geodesy network. Simulations are underway to examining accuracies for origin, scale and orientation of the resulting ITRF based on various network designs and system performance to determine the optimal global network to achieve this goal. To date these simulations indicate that 24 - 32 co-located stations are adequate to define the reference frame and a more dense GNSS and DORIS network will be required to distribute the reference frame to users anywhere on Earth. Stations in the new global network will require geologically stable sites with good weather, established infrastructure, and local support and personnel. GGOS wil seek groups that are interested in participation. GGOS intends to issues a Call for Participation of groups that would like to contribute in the network implementation and operation. Some examples of integrated stations currently in operation or under development will be presented. We will examine necessary conditions and challenges in

Performance-oriented asymptotic tracking control of hydraulic systems with radial basis function network disturbance observer

Directory of Open Access Journals (Sweden)

Jian Hu

2016-05-01

Full Text Available Uncertainties, including parametric uncertainties and uncertain nonlinearities, always exist in positioning servo systems driven by a hydraulic actuator, which would degrade their tracking accuracy. In this article, an integrated control scheme, which combines adaptive robust control together with radial basis function neural network–based disturbance observer, is proposed for high-accuracy motion control of hydraulic systems. Not only parametric uncertainties but also uncertain nonlinearities (i.e. nonlinear friction, external disturbances, and/or unmodeled dynamics are taken into consideration in the proposed controller. The above uncertainties are compensated, respectively, by adaptive control and radial basis function neural network, which are ultimately integrated together by applying feedforward compensation technique, in which the global stabilization of the controller is ensured via a robust feedback path. A new kind of parameter and weight adaptation law is designed on the basis of Lyapunov stability theory. Furthermore, the proposed controller obtains an expected steady performance even if modeling uncertainties exist, and extensive simulation results in various working conditions have proven the high performance of the proposed control scheme.

Estimation of Subdaily Polar Motion with the Global Positioning System During the Spoch '92 Campaign

Science.gov (United States)

Ibanez-Meier, R.; Freedman, A. P.; Herring, T. A.; Gross, R. S.; Lichten, S. M.; Lindqwister, U. J.

1994-01-01

Data collected over six days from a worldwide Global Positioning System (GPS) tracking network during the Epoch '92 campaign are used to estimate variations of the Earth's pole position every 30 minutes.

GPS-based satellite tracking system for precise positioning

Science.gov (United States)

Yunck, T. P.; Melbourne, W. G.; Thornton, C. L.

1985-01-01

NASA is developing a Global Positioning System (GPS) based measurement system to provide precise determination of earth satellite orbits, geodetic baselines, ionospheric electron content, and clock offsets between worldwide tracking sites. The system will employ variations on the differential GPS observing technique and will use a network of nine fixed ground terminals. Satellite applications will require either a GPS flight receiver or an on-board GPS beacon. Operation of the system for all but satellite tracking will begin by 1988. The first major satellite application will be a demonstration of decimeter accuracy in determining the altitude of TOPEX in the early 1990's. By then the system is expected to yield long-baseline accuracies of a few centimeters and instantaneous time synchronization to 1 ns.

Global similarity and local divergence in human and mouse gene co-expression networks

Directory of Open Access Journals (Sweden)

Koonin Eugene V

2006-09-01

Full Text Available Abstract Background A genome-wide comparative analysis of human and mouse gene expression patterns was performed in order to evaluate the evolutionary divergence of mammalian gene expression. Tissue-specific expression profiles were analyzed for 9,105 human-mouse orthologous gene pairs across 28 tissues. Expression profiles were resolved into species-specific coexpression networks, and the topological properties of the networks were compared between species. Results At the global level, the topological properties of the human and mouse gene coexpression networks are, essentially, identical. For instance, both networks have topologies with small-world and scale-free properties as well as closely similar average node degrees, clustering coefficients, and path lengths. However, the human and mouse coexpression networks are highly divergent at the local level: only a small fraction ( Conclusion The dissonance between global versus local network divergence suggests that the interspecies similarity of the global network properties is of limited biological significance, at best, and that the biologically relevant aspects of the architectures of gene coexpression are specific and particular, rather than universal. Nevertheless, there is substantial evolutionary conservation of the local network structure which is compatible with the notion that gene coexpression networks are subject to purifying selection.

Conducting network penetration and espionage in a global environment

CERN Document Server

Middleton, Bruce

2014-01-01

When it's all said and done, penetration testing remains the most effective way to identify security vulnerabilities in computer networks. Conducting Network Penetration and Espionage in a Global Environment provides detailed guidance on how to perform effective penetration testing of computer networks-using free, open source, and commercially available tools, including Backtrack, Metasploit, Wireshark, Nmap, Netcat, and Nessus. It also considers exploits and other programs using Python, PERL, BASH, PHP, Ruby, and Windows PowerShell.The book taps into Bruce Middleton's decades of experience wi

65 Years of influenza surveillance by a WHO-coordinated global network.

Science.gov (United States)

Ziegler, Thedi; Mamahit, Awandha; Cox, Nancy J

2018-05-04

The 1918 devastating influenza pandemic left a lasting impact on influenza experts and the public, and the importance of global influenza surveillance was soon recognized. The WHO Global Influenza Surveillance Network (GISN) was founded in 1952 and renamed to Global Influenza Surveillance and Response System in 2011 upon the adoption by the World Health Assembly, of the Pandemic Influenza Preparedness Framework for the Sharing of Influenza Viruses and Access to Vaccines and Other Benefits ("PIP Framework"). The importance of influenza surveillance had been recognized and promoted by experts prior to the years leading up to the establishment of WHO. In the 65 years of its existence, the Network has grown to comprise 143 National Influenza Centers recognized by WHO, 6 WHO Collaborating Centers, 4 Essential Regulatory Laboratories, and 13 H5 Reference Laboratories. The Network has proven its excellence throughout these 65 years, providing detailed information on circulating seasonal influenza viruses, as well as immediate response to the influenza pandemics in 1957, 1968, and 2009, and to threats caused by animal influenza viruses and by zoonotic transmission of coronaviruses. For its central role in global public health, the Network has been highly recognized by its many partners and by international bodies. Several generations of world renown influenza scientists have brought the Network to where it is now and they will take it forward to the future, as influenza will remain a pre-eminent threat to humans and to animals. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Correlation and network topologies in global and local stock indices

Science.gov (United States)

Nobi, Ashadun; Lee, Sungmin; Kim, Doo Hwan; Lee, Jae Woo

2014-07-01

We examined how the correlation and network structure of the global indices and local Korean indices have changed during years 2000-2012. The average correlations of the global indices increased with time, while the local indices showed a decreasing trend except for drastic changes during the crises. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities identified the change in the market state due to a crisis in both markets. The dynamic change of the Jaccard index can be used as an indicator of systemic risk or precursors of the crisis.

Globally homochiral assembly of two-dimensional molecular networks triggered by co-absorbers.

Science.gov (United States)

Chen, Ting; Yang, Wen-Hong; Wang, Dong; Wan, Li-Jun

2013-01-01

Understanding the chirality induction and amplification processes, and the construction of globally homochiral surfaces, represent essential challenges in surface chirality studies. Here we report the induction of global homochirality in two-dimensional enantiomorphous networks of achiral molecules via co-assembly with chiral co-absorbers. The scanning tunnelling microscopy investigations and molecular mechanics simulations demonstrate that the point chirality of the co-absorbers transfers to organizational chirality of the assembly units via enantioselective supramolecular interactions, and is then hierarchically amplified to the global homochirality of two-dimensional networks. The global homochirality of the network assembly shows nonlinear dependence on the enantiomeric excess of chiral co-absorber in the solution phase, demonstrating, for the first time, the validation of the 'majority rules' for the homochirality control of achiral molecules at the liquid/solid interface. Such an induction and nonlinear chirality amplification effect promises a new approach towards two-dimensional homochirality control and may reveal important insights into asymmetric heterogeneous catalysis, chiral separation and chiral crystallization.

Alignment of global supply networks based on strategic groups of supply chains

OpenAIRE

Nikos G. Moraitakis; Jiazhen Huo; Hans-Christian Pfohl

2017-01-01

Background: From a supply chain perspective, often big differences exist between global raw material suppliers’ approaches to supply their respective local markets. The progressing complexity of large centrally managed global supply networks and their often-unknown upstream ramifications increase the likelihood of undetected bottlenecks and inefficiencies. It is therefore necessary to develop an approach to strategically master the upstream complexity of such networks from a holistic su...

Competition between global and local online social networks

Science.gov (United States)

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-01

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Competition between global and local online social networks.

Science.gov (United States)

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-27

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Operating a global seismic network - perspectives from the USGS GSN

Science.gov (United States)

Gee, L. S.; Derr, J. S.; Hutt, C. R.; Bolton, H.; Ford, D.; Gyure, G. S.; Storm, T.; Leith, W.

2007-05-01

The Global Seismographic Network (GSN) is a permanent digital network of state-of-the-art seismological and geophysical sensors connected by a global telecommunications network, serving as a multi-use scientific facility used for seismic monitoring for response applications, basic and applied research in solid earthquake geophysics, and earth science education. A joint program of the U.S. Geological Survey (USGS), the National Science Foundation, and Incorporated Research Institutions in Seismology (IRIS), the GSN provides near- uniform, worldwide monitoring of the Earth through 144 modern, globally distributed seismic stations. The USGS currently operates 90 GSN or GSN-affiliate stations. As a US government program, the USGS GSN is evaluated on several performance measures including data availability, data latency, and cost effectiveness. The USGS-component of the GSN, like the GSN as a whole, is in transition from a period of rapid growth to steady- state operations. The program faces challenges of aging equipment and increased operating costs at the same time that national and international earthquake and tsunami monitoring agencies place an increased reliance on GSN data. Data acquisition of the USGS GSN is based on the Quanterra Q680 datalogger, a workhorse system that is approaching twenty years in the field, often in harsh environments. An IRIS instrumentation committee recently selected the Quanterra Q330 HR as the "next generation" GSN data acquisition system, and the USGS will begin deploying the new equipment in the middle of 2007. These new systems will address many of the issues associated with the ageing Q680 while providing a platform for interoperability across the GSN.. In order to address the challenge of increasing operational costs, the USGS employs several tools. First, the USGS benefits from the contributions of local host institutions. The station operators are the first line of defense when a station experiences problems, changing boards

Advanced Tracking of Vehicles

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Li, K.-J.; Pakalnis, Stardas

2005-01-01

efficient tracking techniques. More specifically, while almost all commercially available tracking solutions simply offer time-based sampling of positions, this paper's techniques aim to offer a guaranteed tracking accuracy for each vehicle at the lowest possible costs, in terms of network traffic...

A simple model of global cascades on random networks

Science.gov (United States)

Watts, Duncan J.

2002-04-01

The origin of large but rare cascades that are triggered by small initial shocks is a phenomenon that manifests itself as diversely as cultural fads, collective action, the diffusion of norms and innovations, and cascading failures in infrastructure and organizational networks. This paper presents a possible explanation of this phenomenon in terms of a sparse, random network of interacting agents whose decisions are determined by the actions of their neighbors according to a simple threshold rule. Two regimes are identified in which the network is susceptible to very large cascadesherein called global cascadesthat occur very rarely. When cascade propagation is limited by the connectivity of the network, a power law distribution of cascade sizes is observed, analogous to the cluster size distribution in standard percolation theory and avalanches in self-organized criticality. But when the network is highly connected, cascade propagation is limited instead by the local stability of the nodes themselves, and the size distribution of cascades is bimodal, implying a more extreme kind of instability that is correspondingly harder to anticipate. In the first regime, where the distribution of network neighbors is highly skewed, it is found that the most connected nodes are far more likely than average nodes to trigger cascades, but not in the second regime. Finally, it is shown that heterogeneity plays an ambiguous role in determining a system's stability: increasingly heterogeneous thresholds make the system more vulnerable to global cascades; but an increasingly heterogeneous degree distribution makes it less vulnerable.

Nonlinear Autoregressive Network with the Use of a Moving Average Method for Forecasting Typhoon Tracks

OpenAIRE

Tienfuan Kerh; Shin-Hung Wu

2017-01-01

Forecasting of a typhoon moving path may help to evaluate the potential negative impacts in the neighbourhood areas along the moving path. This study proposed a work of using both static and dynamic neural network models to link a time series of typhoon track parameters including longitude and latitude of the typhoon central location, cyclonic radius, central wind speed, and typhoon moving speed. Based on the historical records of 100 typhoons, the performances of neural network models are ev...

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

Science.gov (United States)

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.

The relation between global migration and trade networks

Science.gov (United States)

Sgrignoli, Paolo; Metulini, Rodolfo; Schiavo, Stefano; Riccaboni, Massimo

2015-01-01

In this paper we develop a methodology to analyze and compare multiple global networks, focusing our analysis on the relation between human migration and trade. First, we identify the subset of products for which the presence of a community of migrants significantly increases trade intensity, where to assure comparability across networks we apply a hypergeometric filter that lets us identify those links which intensity is significantly higher than expected. Next, proposing a new way to define country neighbors based on the most intense links in the trade network, we use spatial econometrics techniques to measure the effect of migration on international trade, while controlling for network interdependences. Overall, we find that migration significantly boosts trade across countries and we are able to identify product categories for which this effect is particularly strong.

Global Historical Climatology Network - Daily (GHCN-Daily), Version 3

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Global Historical Climatology Network - Daily (GHCN-Daily) dataset integrates daily climate observations from approximately 30 different data sources. Version 3...

A Global Network Alignment Method Using Discrete Particle Swarm Optimization.

Science.gov (United States)

Huang, Jiaxiang; Gong, Maoguo; Ma, Lijia

2016-10-19

Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations. The particle statuses and status updating rules are redefined in a discrete form by using permutation. A seed-and-extend strategy is employed to guide the searching for the superior alignment. The proposed initialization method "seeds" matches with high sequence similarity into the alignment, which guarantees the functional coherence of the mapping nodes. A greedy local search method is designed as the "extension" procedure to iteratively optimize the edge conservations. PSONA is compared with several state-of-art methods on ten network pairs combined by five species. The experimental results demonstrate that the proposed aligner can map the proteins with high functional coherence and can be used as a booster to effectively refine the well-studied aligners.

Collaboration tools for the global accelerator network Workshop Report

CERN Document Server

Agarwal, D; Olson, J

2002-01-01

The concept of a ''Global Accelerator Network'' (GAN) has been put forward as a means for inter-regional collaboration in the operation of internationally constructed and operated frontier accelerator facilities. A workshop was held to allow representatives of the accelerator community and of the collaboratory development community to meet and discuss collaboration tools for the GAN environment. This workshop, called the Collaboration Tools for the Global Accelerator Network (GAN) Workshop, was held on August 26, 2002 at Lawrence Berkeley National Laboratory. The goal was to provide input about collaboration tools in general and to provide a strawman for the GAN collaborative tools environment. The participants at the workshop represented accelerator physicists, high-energy physicists, operations, technology tool developers, and social scientists that study scientific collaboration.

Collaboration tools for the global accelerator network: Workshop Report

International Nuclear Information System (INIS)

Agarwal, Deborah; Olson, Gary; Olson, Judy

2002-01-01

The concept of a ''Global Accelerator Network'' (GAN) has been put forward as a means for inter-regional collaboration in the operation of internationally constructed and operated frontier accelerator facilities. A workshop was held to allow representatives of the accelerator community and of the collaboratory development community to meet and discuss collaboration tools for the GAN environment. This workshop, called the Collaboration Tools for the Global Accelerator Network (GAN) Workshop, was held on August 26, 2002 at Lawrence Berkeley National Laboratory. The goal was to provide input about collaboration tools in general and to provide a strawman for the GAN collaborative tools environment. The participants at the workshop represented accelerator physicists, high-energy physicists, operations, technology tool developers, and social scientists that study scientific collaboration

Representation of global and national conservation priorities by Colombia's Protected Area Network.

Science.gov (United States)

Forero-Medina, German; Joppa, Lucas

2010-10-12

How do national-level actions overlap with global priorities for conservation? Answering this question is especially important in countries with high and unique biological diversity like Colombia. Global biodiversity schemes provide conservation guidance at a large scale, while national governments gazette land for protection based on a combination of criteria at regional or local scales. Information on how a protected area network represents global and national conservation priorities is crucial for finding gaps in coverage and for future expansion of the system. We evaluated the agreement of Colombia's protected area network with global conservation priorities, and the extent to which the network reflects the country's biomes, species richness, and common environmental and physical conditions. We used this information to identify priority biomes for conservation. We find the dominant strategy in Colombia has been a proactive one, allocating the highest proportion of protected land on intact, difficult to access and species rich areas like the Amazon. Threatened and unique areas are disproportionately absent from Colombia's protected lands. We highlight six biomes in Colombia as conservation priorities that should be considered in any future expansion of Colombia's protected area network. Two of these biomes have less than 3% of their area protected and more than 70% of their area transformed for human use. One has less than 3% protected and high numbers of threatened vertebrates. Three biomes fall in both categories. Expansion of Colombia's Protected Area Network should consider the current representativeness of the network. We indicate six priority biomes that can contribute to improving the representation of threatened species and biomes in Colombia.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

Science.gov (United States)

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-05-30

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

Directory of Open Access Journals (Sweden)

Gaining Han

2017-05-01

Full Text Available The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS, the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

Global Talent Management in Multinational Corporations and the Role of Social Networks

NARCIS (Netherlands)

Ruel, Hubertus Johannes Maria; Bondarouk, Tatiana; Dresselhaus, Lena; Olivas-Lujan, M.R.; Bondarouk, T.V.

2013-01-01

Purpose — Current global business challenges and circumstances are responsible for the need for global talent management (GTM) within multinational corporations (MNCs). Social media and networks are becoming key channels for global communication and collaboration. For GTM in MNCs, an effective usage

Competition, transmission and pattern evolution: A network analysis of global oil trade

International Nuclear Information System (INIS)

Zhang, Hai-Ying; Ji, Qiang; Fan, Ying

2014-01-01

This paper studies the competition among oil importers using complex network theory, combined with several alternative measures of competition intensity, to analyze the evolution of the pattern and transmission of oil-trading competition. The results indicate that oil trade has formed a global competition pattern and that the role played by the Asian-Pacific region in the evolution of this competition pattern is becoming increasingly prominent. In addition, global competition intensity has continued to rise, and non-OECD countries have become the main driving force for this increase in global competition intensity. The large oil importers are the most significant parts of the global oil-trading competition pattern. They are not only the major participants in the competition for oil resources but also play important roles in the transmission of oil-trading competition. China and the United States especially display the feature of globalization, whose impacts of transmission reach across the whole oil-trading competition network. Finally, a “5C” (changeability, contestability, cooperation, commitment and circumstances) policy framework is put forward to maintain the stability of oil trade and improve the energy security of oil importers in various aspects. - Highlights: • An oil-trading competition network is constructed using complex network theory. • Oil trade has formed a global competition pattern and its intensity has kept rising. • The status of the Asian-Pacific region in the competition pattern becomes prominent. • Large oil importers play important roles in transmitting the trading competition. • A “5C” policy framework is put forward to cope with the intensive competition

Sierra Stars Observatory Network: An Accessible Global Network

Science.gov (United States)

Williams, Richard; Beshore, Edward

2011-03-01

The Sierra Stars Observatory Network (SSON) is a unique partnership among professional observatories that provides its users with affordable high-quality calibrated image data. SSON comprises observatories in the Northern and Southern Hemisphere and is in the process of expanding to a truly global network capable of covering the entire sky 24 hours a day in the near future. The goal of SSON is to serve the needs of science-based projects and programs. Colleges, universities, institutions, and individuals use SSON for their education and research projects. The mission of SSON is to promote and expand the use of its facilities among the thousands of colleges and schools worldwide that do not have access to professional-quality automated observatory systems to use for astronomy education and research. With appropriate leadership and guidance educators can use SSON to help teach astronomy and do meaningful scientific projects. The relatively small cost of using SSON for this type of work makes it affordable and accessible for educators to start using immediately. Remote observatory services like SSON need to evolve to better support education and research initiatives of colleges, institutions and individual investigators. To meet these needs, SSON is developing a sophisticated interactive scheduling system to integrate among the nodes of the observatory network. This will enable more dynamic observations, including immediate priority interrupts, acquiring moving objects using ephemeris data, and more.

The role of “network of cities” in construction of global urban culture

OpenAIRE

Baycan-Levent, Tüzin; Kundak, Seda; Gülümser, Aliye Ahu

2004-01-01

The globalization process has led to an increased interaction between cities and to a new urban system/network in which they need to be competitive and complementary at the same time. “Network of cities”, such as World Cities, Eurocities or Sister Cities are among the well known examples of interaction and cooperation of the cities at the regional and global level. The cities of different regions and countries tend to share their experiences and their cultures within these networks in order t...

Computers and networks in the age of globalization

DEFF Research Database (Denmark)

Bloch Rasmussen, Leif; Beardon, Colin; Munari, Silvio

In modernity, an individual identity was constituted from civil society, while in a globalized network society, human identity, if it develops at all, must grow from communal resistance. A communal resistance to an abstract conceptualized world, where there is no possibility for perception and ex...

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

Directory of Open Access Journals (Sweden)

Ji She

2016-12-01

Full Text Available Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance.

A Non-Intrusive Cyber Physical Social Sensing Solution to People Behavior Tracking: Mechanism, Prototype, and Field Experiments

Directory of Open Access Journals (Sweden)

Yunjian Jia

2017-01-01

Full Text Available Tracking people’s behaviors is a main category of cyber physical social sensing (CPSS-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS and Bluetooth. In this article, we propose a non-intrusive wireless fidelity (Wi-Fi-based tracking method. To show the feasibility, we target tracking people’s access behaviors in Wi-Fi networks, which has drawn a lot of interest from the academy and industry recently. Existing methods used for acquiring access traces either provide very limited visibility into media access control (MAC-level transmission dynamics or sometimes are inflexible and costly. In this article, we present a passive CPSS system operating in a non-intrusive, flexible, and simplified manner to overcome above limitations. We have implemented the prototype on the off-the-shelf personal computer, and performed real-world deployment experiments. The experimental results show that the method is feasible, and people’s access behaviors can be correctly tracked within a one-second delay.

Global Nuclear Safety and Security Network

International Nuclear Information System (INIS)

Guo Lingquan

2013-01-01

The objectives of the Regulatory Network are: - to contribute to the effectiveness of nuclear regulatory systems; - to contribute to continuous enhancements, and - to achieve and promote radiation and nuclear safety and security by: • Enhancing the effectiveness and efficiency of international cooperation in the regulation of nuclear and radiation safety of facilities and activities; • Enabling adequate access by regulators to relevant safety and security information; • Promoting dissemination of information on safety and security issues as well as information of good practices for addressing and resolving these issues; • Enabling synergies among different web based networks with a view to strengthening and enhancing the global nuclear safety framework and serving the specific needs of regulators and international organizations; • Providing additional information to the public on international regulatory cooperation in safety and security matters

Correlation and network topologies in global and local stock indices

DEFF Research Database (Denmark)

Nobi, A.; Lee, S.; Kim, D. H.

2014-01-01

the crises. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities identified the change in the market state due to a crisis in both markets. The dynamic change of the Jaccard index can be used as an indicator of systemic risk......We examined how the correlation and network structure of the global indices and local Korean indices have changed during years 2000-2012. The average correlations of the global indices increased with time, while the local indices showed a decreasing trend except for drastic changes during...... or precursors of the crisis. (C) 2014 Elsevier B.V. All rights reserved....

Global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms

International Nuclear Information System (INIS)

Wang Jian; Lu Junguo

2008-01-01

In this paper, we study the global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms. By constructing a suitable Lyapunov functional and utilizing some inequality techniques, we obtain a sufficient condition for the uniqueness and global exponential stability of the equilibrium solution for a class of fuzzy cellular neural networks with delays and reaction-diffusion terms. The result imposes constraint conditions on the network parameters independently of the delay parameter. The result is also easy to check and plays an important role in the design and application of globally exponentially stable fuzzy neural circuits

SONG-China Project: A Global Automated Observation Network

Science.gov (United States)

Yang, Z. Z.; Lu, X. M.; Tian, J. F.; Zhuang, C. G.; Wang, K.; Deng, L. C.

2017-09-01

Driven by advancements in technology and scientific objectives, data acquisition in observational astronomy has been changed greatly in recent years. Fully automated or even autonomous ground-based network of telescopes has now become a tendency for time-domain observational projects. The Stellar Observations Network Group (SONG) is an international collaboration with the participation and contribution of the Chinese astronomy community. The scientific goal of SONG is time-domain astrophysics such as asteroseismology and open cluster research. The SONG project aims to build a global network of 1 m telescopes equipped with high-precision and high-resolution spectrographs, and two-channel lucky-imaging cameras. It is the Chinese initiative to install a 50 cm binocular photometry telescope at each SONG node sharing the network platform and infrastructure. This work is focused on design and implementation in technology and methodology of SONG/50BiN, a typical ground-based network composed of multiple sites and a variety of instruments.

A global interaction network maps a wiring diagram of cellular function

Science.gov (United States)

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network

Science.gov (United States)

Kölzsch, A.; Blasius, B.

2011-12-01

The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global shipping. This is the first stage of the invasion process where it is still possible to intervene with regulating measures. We compile a selection of widely used and newly developed network properties and apply these to analyse the structure and spread characteristics of the directed and weighted global cargo ship network (GCSN). Our results reveal that the GCSN is highly efficient, shows small world characteristics and is positive assortative, indicating that quick spread of invasive organisms between ports is likely. The GCSN shows strong community structure and contains two large communities, the Atlantic and Pacific trading groups. Ports that appear as connector hubs and are of high centralities are the Suez and Panama Canal, Singapore and Shanghai. Furthermore, from robustness analyses and the network's percolation behaviour, we evaluate differences of onboard and in-port ballast water treatment, set them into context with previous studies and advise bioinvasion management strategies.

Global synchronization of general delayed complex networks with stochastic disturbances

International Nuclear Information System (INIS)

Tu Li-Lan

2011-01-01

In this paper, global synchronization of general delayed complex networks with stochastic disturbances, which is a zero-mean real scalar Wiener process, is investigated. The networks under consideration are continuous-time networks with time-varying delay. Based on the stochastic Lyapunov stability theory, Ito's differential rule and the linear matrix inequality (LMI) optimization technique, several delay-dependent synchronous criteria are established, which guarantee the asymptotical mean-square synchronization of drive networks and response networks with stochastic disturbances. The criteria are expressed in terms of LMI, which can be easily solved using the Matlab LMI Control Toolbox. Finally, two examples show the effectiveness and feasibility of the proposed synchronous conditions. (general)

Global asymptotic stability of Cohen-Grossberg neural networks with constant and variable delays

International Nuclear Information System (INIS)

Wu Wei; Cui Baotong; Huang Min

2007-01-01

Global asymptotic stability of Cohen-Grossberg neural networks with constant and variable delays is studied. Some sufficient conditions for the neural networks are proposed to guarantee the global asymptotic convergence by using different Lyapunov functionals. Our criteria represent an extension of the existing results in literatures. A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed Cohen-Grossberg neural networks. Those conditions are less restrictive than those given in the earlier reference

Railway Track Allocation: Models and Methods

DEFF Research Database (Denmark)

Lusby, Richard Martin; Larsen, Jesper; Ehrgott, Matthias

2011-01-01

Efficiently coordinating the movement of trains on a railway network is a central part of the planning process for a railway company. This paper reviews models and methods that have been proposed in the literature to assist planners in finding train routes. Since the problem of routing trains......, and train routing problems, group them by railway network type, and discuss track allocation from a strategic, tactical, and operational level....... on a railway network entails allocating the track capacity of the network (or part thereof) over time in a conflict-free manner, all studies that model railway track allocation in some capacity are considered relevant. We hence survey work on the train timetabling, train dispatching, train platforming...

Railway Track Allocation: Models and Methods

DEFF Research Database (Denmark)

Lusby, Richard Martin; Larsen, Jesper; Ehrgott, Matthias

Eciently coordinating the movement of trains on a railway network is a central part of the planning process for a railway company. This paper reviews models and methods that have been proposed in the literature to assist planners in nding train routes. Since the problem of routing trains......, and train routing problems, group them by railway network type, and discuss track allocation from a strategic, tactical, and operational level....... on a railway network entails allocating the track capacity of the network (or part thereof) over time in a con ict-free manner, all studies that model railway track allocation in some capacity are considered relevant. We hence survey work on the train timetabling, train dispatching, train platforming...

The tracking and locating system of the mining personnel based on the Zigbee wireless network platform

Energy Technology Data Exchange (ETDEWEB)

Xiao-jia, Xie; Li-jun, Cheng; Yong, Wang [Chongqing University, Chongqing (China). College of Resources and Environmental Science

2007-08-15

By comparing the advanced Zigbee wireless network system with active RFID, the Zigbee wireless network technology was introduced into the system for tracking and locating of coal miners. The system structure and function characteristics were also introduced. This system makes it convenient to mine administrators, control room personnel and security inspectors to obtain information on the working hours and location of mine workers in the mine. 6 refs., 2 figs., 3 tabs.

Approach on a global HTGR R and D network

International Nuclear Information System (INIS)

Lensa, W. von

1997-01-01

The present situation of nuclear power in general and of the innovative nuclear reactor systems in particular requires more comprehensive, coordinated R and D efforts on a broad international level to respond to today's requirements with respect to public and economic acceptance as well as to globalization trends and global environmental problems. HTGR technology development has already reached a high degree of maturity that will be complemented by the operation of the two new test reactors in Japan and China, representing technological milestones for the demonstration of HTGR safety characteristics and Nuclear Process Heat generation capabilities. It is proposed by the IAEA 'International Working Group on Gas-Cooled Reactors' to establish a 'Global HTGR R and D Network' on basic HTGR technology for the stable, long-term advancement of the specific HTGR features and as a basis for the future market introduction of this innovative reactor system. The background and the motivation for this approach are illustrated, as well as first proposals on the main objectives, the structure and the further procedures for the implementation of such a multinational working sharing R and D network. Modern telecooperation methods are foreseen as an interactive tool for effective communication and collaboration on a global scale. (author)

Scalable Track Detection in SAR CCD Images

Energy Technology Data Exchange (ETDEWEB)

Chow, James G [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Quach, Tu-Thach [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-03-01

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.

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

Science.gov (United States)

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.

Perancangan Dan Realisasi Sistem Transmisi Data GPS Menggunakan Teknologi SMS (Short Messaging Service Sebagai Aplikasi Sistem Personal Tracking

Directory of Open Access Journals (Sweden)

DECY NATALIANA

2017-06-01

Full Text Available Abstrak Berprinsip pada pengembangan teknologi dan aplikasi dari sistem penjejakan posisi (tracking, maka dibuatlah sistem personal tracking dengan mentransmisikan data GPS (Global Positioning System dengan menggunakan teknologi SMS (Short Messaging Service pada jaringan GSM (Global System for Mobile Communications sebagai media transmisinya.  Dengan sistem GPS akan diperoleh data garis lintang, serta garis bujur dari GPS receiver.  Data tersebut akan diteruskan oleh mikrokontroler untuk dikirim ke ponsel pengamat melalui komunikasi SMS.  Hasil pengujian menunjukkan bahwa device personal tracking berhasil mengirimkan data berupa IMEI, Tanggal satelit, waktu satelit, koordinat longitude, koordinat latitude, dan jumlah satelit yang berhasil ditangkap oleh device ke ponsel pengamat.  Dari data koordinat tersebut pengamat dapat memantau posisi device personal tracking berada dengan bantuan aplikasi pendukung yaitu Google Maps. Kata kunci: GPS, Personal Tracking, SMS, Google Maps.   Abstract Base on technology and application development of tracking, personal tracking system was made by transmiting GPS (Global Positioning System data using SMS (Short Messaging Service technology with GSM (Global System for Mobile Communications network as transmitter media.  BY GPS system, we can get datas such as latitude and longitude of GPS receiver.  Those datas will be processed by microcontroller to be sent from GSM/GPRS module to user cellular phone through SMS communication.  The test result showed that the device can be sending datas such as IMEI, UTC date, UTC time, longitude coordinate, latitude coordinate, and number sattelite which detected by device to user’s phonecell.  From those coordinate, user can be monitoring the device’s position with the Google Maps application. Keywords: GPS, Personal Tracking, SMS, Google Maps.

Global exponential stability of mixed discrete and distributively delayed cellular neural network

International Nuclear Information System (INIS)

Yao Hong-Xing; Zhou Jia-Yan

2011-01-01

This paper concernes analysis for the global exponential stability of a class of recurrent neural networks with mixed discrete and distributed delays. It first proves the existence and uniqueness of the balance point, then by employing the Lyapunov—Krasovskii functional and Young inequality, it gives the sufficient condition of global exponential stability of cellular neural network with mixed discrete and distributed delays, in addition, the example is provided to illustrate the applicability of the result. (general)

The global health network on alcohol control: successes and limits of evidence-based advocacy.

Science.gov (United States)

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.

Direct comparison of cardiac magnetic resonance feature tracking and 2D/3D echocardiography speckle tracking for evaluation of global left ventricular strain.

Science.gov (United States)

Obokata, Masaru; Nagata, Yasufumi; Wu, Victor Chien-Chia; Kado, Yuichiro; Kurabayashi, Masahiko; Otsuji, Yutaka; Takeuchi, Masaaki

2016-05-01

Cardiac magnetic resonance (CMR) feature tracking (FT) with steady-state free precession (SSFP) has advantages over traditional myocardial tagging to analyse left ventricular (LV) strain. However, direct comparisons of CMRFT and 2D/3D echocardiography speckle tracking (2/3DEST) for measurement of LV strain are limited. The aim of this study was to investigate the feasibility and reliability of CMRFT and 2D/3DEST for measurement of global LV strain. We enrolled 106 patients who agreed to undergo both CMR and 2D/3DE on the same day. SSFP images at multiple short-axis and three apical views were acquired. 2DE images from three levels of short-axis, three apical views, and 3D full-volume datasets were also acquired. Strain data were expressed as absolute values. Feasibility was highest in CMRFT, followed by 2DEST and 3DEST. Analysis time was shortest in 3DEST, followed by CMRFT and 2DEST. There was good global longitudinal strain (GLS) correlation between CMRFT and 2D/3DEST (r = 0.83 and 0.87, respectively) with the limit of agreement (LOA) ranged from ±3.6 to ±4.9%. Excellent global circumferential strain (GCS) correlation between CMRFT and 2D/3DEST was observed (r = 0.90 and 0.88) with LOA of ±6.8-8.5%. Global radial strain showed fair correlations (r = 0.69 and 0.82, respectively) with LOA ranged from ±12.4 to ±16.3%. CMRFT GCS showed least observer variability with highest intra-class correlation. Although not interchangeable, the high GLS and GCS correlation between CMRFT and 2D/3DEST makes CMRFT a useful modality for quantification of global LV strain in patients, especially those with suboptimal echo image quality. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

Global efficiency of local immunization on complex networks.

Science.gov (United States)

Hébert-Dufresne, Laurent; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J

2013-01-01

Epidemics occur in all shapes and forms: infections propagating in our sparse sexual networks, rumours and diseases spreading through our much denser social interactions, or viruses circulating on the Internet. With the advent of large databases and efficient analysis algorithms, these processes can be better predicted and controlled. In this study, we use different characteristics of network organization to identify the influential spreaders in 17 empirical networks of diverse nature using 2 epidemic models. We find that a judicious choice of local measures, based either on the network's connectivity at a microscopic scale or on its community structure at a mesoscopic scale, compares favorably to global measures, such as betweenness centrality, in terms of efficiency, practicality and robustness. We also develop an analytical framework that highlights a transition in the characteristic scale of different epidemic regimes. This allows to decide which local measure should govern immunization in a given scenario.

Global efficiency of local immunization on complex networks

Science.gov (United States)

Hébert-Dufresne, Laurent; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

2013-07-01

Epidemics occur in all shapes and forms: infections propagating in our sparse sexual networks, rumours and diseases spreading through our much denser social interactions, or viruses circulating on the Internet. With the advent of large databases and efficient analysis algorithms, these processes can be better predicted and controlled. In this study, we use different characteristics of network organization to identify the influential spreaders in 17 empirical networks of diverse nature using 2 epidemic models. We find that a judicious choice of local measures, based either on the network's connectivity at a microscopic scale or on its community structure at a mesoscopic scale, compares favorably to global measures, such as betweenness centrality, in terms of efficiency, practicality and robustness. We also develop an analytical framework that highlights a transition in the characteristic scale of different epidemic regimes. This allows to decide which local measure should govern immunization in a given scenario.

The Theoretical Aspects of the Development of Global Production Networks and Value Chains: the New Paradigm of Globalization

Directory of Open Access Journals (Sweden)

Cherkas Nataliia I.

2018-03-01

Full Text Available The article is aimed at systematizing the contemporary perceptions of the changing paradigms of globalization and international competition as a result of the spread of global networks and value chains. The development of global value chains (GVC occurred as a result of two distributions of globalization: (1 global competition is manifested at the level of sectors and companies (from the mid-nineteenth century (2 the concept of trade in tasks arises (at the end of XX century. The publication analyzes the impact of globalization on the international competitiveness of both the EU and the developing countries in the trade of final products and tasks. The model takes into consideration differences in wages, technology gap and trade costs, and provides for assessing the comparative advantages of individual sectors or segments of GVC. Features of the conception of global production networks have been identified as: «imports for production» and «imports for exports», which define international competitiveness on the basis of creation of the intrinsic value added. It is determined that the competitiveness of the economy is determined by the country’s positions in the GVC, and the increase in productivity of companies depends on their involvement in the segments (tasks with a high level of value added.

The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

Science.gov (United States)

Farrell, Steven; Anderson, Dustin; Calafiura, Paolo; Cerati, Giuseppe; Gray, Lindsey; Kowalkowski, Jim; Mudigonda, Mayur; Prabhat; Spentzouris, Panagiotis; Spiropoulou, Maria; Tsaris, Aristeidis; Vlimant, Jean-Roch; Zheng, Stephan

2017-08-01

Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC) is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM) and convolutional neural networks to find and fit tracks in toy detector data.

The HEP.TrkX Project: deep neural networks for HL-LHC online and offline tracking

Directory of Open Access Journals (Sweden)

Farrell Steven

2017-01-01

Full Text Available Particle track reconstruction in dense environments such as the detectors of the High Luminosity Large Hadron Collider (HL-LHC is a challenging pattern recognition problem. Traditional tracking algorithms such as the combinatorial Kalman Filter have been used with great success in LHC experiments for years. However, these state-of-the-art techniques are inherently sequential and scale poorly with the expected increases in detector occupancy in the HL-LHC conditions. The HEP.TrkX project is a pilot project with the aim to identify and develop cross-experiment solutions based on machine learning algorithms for track reconstruction. Machine learning algorithms bring a lot of potential to this problem thanks to their capability to model complex non-linear data dependencies, to learn effective representations of high-dimensional data through training, and to parallelize easily on high-throughput architectures such as GPUs. This contribution will describe our initial explorations into this relatively unexplored idea space. We will discuss the use of recurrent (LSTM and convolutional neural networks to find and fit tracks in toy detector data.

Global exponential stability of reaction-diffusion recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Liang Jinling; Cao Jinde

2003-01-01

Employing general Halanay inequality, we analyze the global exponential stability of a class of reaction-diffusion recurrent neural networks with time-varying delays. Several new sufficient conditions are obtained to ensure existence, uniqueness and global exponential stability of the equilibrium point of delayed reaction-diffusion recurrent neural networks. The results extend and improve the earlier publications. In addition, an example is given to show the effectiveness of the obtained result

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

Science.gov (United States)

Liu, Jun; Wang, Gang; Duan, Ling-Yu; Abdiyeva, Kamila; Kot, Alex C.

2018-04-01

Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition.

Global stability of a susceptible-infected-susceptible epidemic model on networks with individual awareness

International Nuclear Information System (INIS)

Li Ke-Zan; Xu Zhong-Pu; Zhu Guang-Hu; Ding Yong

2014-01-01

Recent research results indicate that individual awareness can play an important influence on epidemic spreading in networks. By local stability analysis, a significant conclusion is that the embedded awareness in an epidemic network can increase its epidemic threshold. In this paper, by using limit theory and dynamical system theory, we further give global stability analysis of a susceptible-infected-susceptible (SIS) epidemic model on networks with awareness. Results show that the obtained epidemic threshold is also a global stability condition for its endemic equilibrium, which implies the embedded awareness can enhance the epidemic threshold globally. Some numerical examples are presented to verify the theoretical results. (interdisciplinary physics and related areas of science and technology)

A Velocity-Level Bi-Criteria Optimization Scheme for Coordinated Path Tracking of Dual Robot Manipulators Using Recurrent Neural Network.

Science.gov (United States)

Xiao, Lin; Zhang, Yongsheng; Liao, Bolin; Zhang, Zhijun; Ding, Lei; Jin, Long

2017-01-01

A dual-robot system is a robotic device composed of two robot arms. To eliminate the joint-angle drift and prevent the occurrence of high joint velocity, a velocity-level bi-criteria optimization scheme, which includes two criteria (i.e., the minimum velocity norm and the repetitive motion), is proposed and investigated for coordinated path tracking of dual robot manipulators. Specifically, to realize the coordinated path tracking of dual robot manipulators, two subschemes are first presented for the left and right robot manipulators. After that, such two subschemes are reformulated as two general quadratic programs (QPs), which can be formulated as one unified QP. A recurrent neural network (RNN) is thus presented to solve effectively the unified QP problem. At last, computer simulation results based on a dual three-link planar manipulator further validate the feasibility and the efficacy of the velocity-level optimization scheme for coordinated path tracking using the recurrent neural network.

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

Science.gov (United States)

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.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

Science.gov (United States)

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Global robust exponential stability for interval neural networks with delay

International Nuclear Information System (INIS)

Cui Shihua; Zhao Tao; Guo Jie

2009-01-01

In this paper, new sufficient conditions for globally robust exponential stability of neural networks with either constant delays or time-varying delays are given. We show the sufficient conditions for the existence, uniqueness and global robust exponential stability of the equilibrium point by employing Lyapunov stability theory and linear matrix inequality (LMI) technique. Numerical examples are given to show the approval of our results.

Probabilistic Localization and Tracking of Malicious Insiders Using Hyperbolic Position Bounding in Vehicular Networks

Directory of Open Access Journals (Sweden)

Laurendeau Christine

2009-01-01

Full Text Available A malicious insider in a wireless network may carry out a number of devastating attacks without fear of retribution, since the messages it broadcasts are authenticated with valid credentials such as a digital signature. In attributing an attack message to its perpetrator by localizing the signal source, we can make no presumptions regarding the type of radio equipment used by a malicious transmitter, including the transmitting power utilized to carry out an exploit. Hyperbolic position bounding (HPB provides a mechanism to probabilistically estimate the candidate location of an attack message's originator using received signal strength (RSS reports, without assuming knowledge of the transmitting power. We specialize the applicability of HPB into the realm of vehicular networks and provide alternate HPB algorithms to improve localization precision and computational efficiency. We extend HPB for tracking the consecutive locations of a mobile attacker. We evaluate the localization and tracking performance of HPB in a vehicular scenario featuring a variable number of receivers and a known navigational layout. We find that HPB can position a transmitting device within stipulated guidelines for emergency services localization accuracy.

Operational aspects of CASA UNO '88-The first large scale international GPS geodetic network

Science.gov (United States)

Neilan, Ruth E.; Dixon, T. H.; Meehan, Thomas K.; Melbourne, William G.; Scheid, John A.; Kellogg, J. N.; Stowell, J. L.

1989-01-01

For three weeks, from January 18 to February 5, 1988, scientists and engineers from 13 countries and 30 international agencies and institutions cooperated in the most extensive GPS (Global Positioning System) field campaign, and the largest geodynamics experiment, in the world to date. This collaborative eperiment concentrated GPS receivers in Central and South America. The predicted rates of motions are on the order of 5-10 cm/yr. Global coverage of GPS observations spanned 220 deg of longitude and 125 deg of latitude using a total of 43 GPS receivers. The experiment was the first civilian effort at implementing an extended international GPS satellite tracking network. Covariance analyses incorporating the extended tracking network predicted significant improvement in precise orbit determination, allowing accurate long-baseline geodesy in the science areas.

Beyond the network effect: towards an alternative understanding of global urban organizations

NARCIS (Netherlands)

James, P.; Verrest, H.; Gupta, J.; Pfeffer, K.; Verrest, H.; Ros-Tonen, M.

2015-01-01

Global organizations providing network relations for cities are bourgeoning. Organizations such as Metropolis, UN-Habitat, ICLEI - Local Governments for Sustainability, the Global Compact Cities Programme, and the C40, as well as City-to-City arrangements, have become increasingly important to

The Pan-University Network for Global Health: framework for collaboration and review of global health needs.

Science.gov (United States)

Winchester, M S; BeLue, R; Oni, T; Wittwer-Backofen, U; Deobagkar, D; Onya, H; Samuels, T A; Matthews, S A; Stone, C; Airhihenbuwa, C

2016-04-21

In the current United Nations efforts to plan for post 2015-Millennium Development Goals, global partnership to address non-communicable diseases (NCDs) has become a critical goal to effectively respond to the complex global challenges of which inequity in health remains a persistent challenge. Building capacity in terms of well-equipped local researchers and service providers is a key to bridging the inequity in global health. Launched by Penn State University in 2014, the Pan University Network for Global Health responds to this need by bridging researchers at more than 10 universities across the globe. In this paper we outline our framework for international and interdisciplinary collaboration, as well the rationale for our research areas, including a review of these two themes. After its initial meeting, the network has established two central thematic priorities: 1) urbanization and health and 2) the intersection of infectious diseases and NCDs. The urban population in the global south will nearly double in 25 years (approx. 2 billion today to over 3.5 billion by 2040). Urban population growth will have a direct impact on global health, and this growth will be burdened with uneven development and the persistence of urban spatial inequality, including health disparities. The NCD burden, which includes conditions such as hypertension, stroke, and diabetes, is outstripping infectious disease in countries in the global south that are considered to be disproportionately burdened by infectious diseases. Addressing these two priorities demands an interdisciplinary and multi-institutional model to stimulate innovation and synergy that will influence the overall framing of research questions as well as the integration and coordination of research.

Global Maximum Power Point Tracking (MPPT of a Photovoltaic Module Array Constructed through Improved Teaching-Learning-Based Optimization

Directory of Open Access Journals (Sweden)

Kuei-Hsiang Chao

2016-11-01

Full Text Available The present study proposes a maximum power point tracking (MPPT method in which improved teaching-learning-based optimization (I-TLBO is applied to perform global MPPT of photovoltaic (PV module arrays under dissimilar shading situations to ensure the maximum power output of the module arrays. The proposed I-TLBO enables the automatic adjustment of teaching factors according to the self-learning ability of students. Incorporating smart-tracking and self-study strategies can effectively improve the tracking response speed and steady-state tracking performance. To evaluate the feasibility of the proposed I-TLBO, a HIP-2717 PV module array from Sanyo Electric was employed to compose various arrays with different serial and parallel configurations. The arrays were operated under different shading conditions to test the MPPT with double, triple, or quadruple peaks of power-voltage characteristic curves. Boost converters were employed with TMS320F2808 digital signal processors to test the proposed MPPT method. Empirical results confirm that the proposed method exhibits more favorable dynamic and static-state response tracking performance compared with that of conventional TLBO.

Coupling Strength and System Size Induce Firing Activity of Globally Coupled Neural Network

International Nuclear Information System (INIS)

Wei Duqu; Luo Xiaoshu; Zou Yanli

2008-01-01

We investigate how firing activity of globally coupled neural network depends on the coupling strength C and system size N. Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of parameters at which no firing activity occurs. It is found that for a given appropriate coupling strength, there is an intermediate range of system size where the firing activity of globally coupled SCFHN neural network is induced and enhanced. On the other hand, for a given intermediate system size level, there exists an optimal value of coupling strength such that the intensity of firing activity reaches its maximum. These phenomena imply that the coupling strength and system size play a vital role in firing activity of neural network

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

Science.gov (United States)

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.

Analysing the Outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center

OpenAIRE

Marjeta, Katri

2011-01-01

Marjeta, Katri. 2011. Analysing the outbound logistics process enhancements in Nokia-Siemens Networks Global Distribution Center. Master´s thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 57. Due to confidentiality issues, this work has been modified from its original form. The aim of this Master Thesis work is to describe and analyze the outbound logistics process enhancement projects executed in Nokia-Siemens Networks Global Distribution Center after the N...

The Transition from Alliance Networks to Multilateral Alliances in the Global Airline Industry

Directory of Open Access Journals (Sweden)

Sergio G. Lazzarini

2008-01-01

Full Text Available This study examines conditions in which alliance networks (informal webs of bilateral entanglements between firms may or may not evolve into multilateral alliances (broad, formal multiple-firm arrangements. I offer a theory to explain the formation of multilateral alliances based on both the resource profile and the structure of existing interfirm networks, and provide an initial test of that theory in the context of the global airline industry. Using data from 75 global airlines and their alliances, I propose a methodology to retrieve samples of alliance networks and then use regression analysis to assess how the resource profile and the structure of these networks influence their formalization into multilateral alliances. I find that multilateral alliances are more likely to emerge when alliance networks exhibit high resource diversity and network structure characterized by moderate density and high centralization. Apparently, while highly sparse networks reduce actors’ awareness of their potential joint collaboration, highly dense or embedded networks substitute for the need for formal controls accompanying multilateral agreements. The effect of centralization suggests that the formation of multilateral alliances tends to be triggered by leading actors directly connected to other network members.

AIRS Impact on the Analysis and Forecast Track of Tropical Cyclone Nargis in a Global Data Assimilation and Forecasting System

Science.gov (United States)

Reale, O.; Lau, W.K.; Susskind, J.; Brin, E.; Liu, E.; Riishojgaard, L. P.; Rosenburg, R.; Fuentes, M.

2009-01-01

Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. Moreover, the automated analyses of cyclones over the northern Indian Ocean, produced by operational global data assimilation systems (DASs), are generally of inferior quality than in other basins. In this work it is shown that the assimilation of Atmospheric Infrared Sounder (AIRS) temperature retrievals under partial cloudy conditions can significantly impact the representation of the cyclone Nargis (which caused devastating loss of life in Myanmar in May 2008) in a global DAS. Forecasts produced from these improved analyses by a global model produce substantially smaller track errors. The impact of the assimilation of clear-sky radiances on the same DAS and forecasting system is positive, but smaller than the one obtained by ingestion of AIRS retrievals, possibly due to poorer coverage.

Hardware realization of a fast neural network algorithm for real-time tracking in HEP experiments

International Nuclear Information System (INIS)

Leimgruber, F.R.; Pavlopoulos, P.; Steinacher, M.; Tauscher, L.; Vlachos, S.; Wendler, H.

1995-01-01

A fast pattern recognition system for HEP experiments, based on artificial neural network algorithms (ANN), has been realized with standard electronics. The multiplicity and location of tracks in an event are determined in less than 75 ns. Hardware modules of this first level trigger were extensively tested for performance and reliability with data from the CPLEAR experiment. (orig.)

Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures.

Science.gov (United States)

Cañete, Eduardo; Chen, Jaime; Díaz, Manuel; Llopis, Luis; Reyna, Ana; Rubio, Bartolomé

2015-06-26

Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency.

Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures

Directory of Open Access Journals (Sweden)

Eduardo Cañete

2015-06-01

Full Text Available Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency.

Novel global robust stability criterion for neural networks with delay

International Nuclear Information System (INIS)

Singh, Vimal

2009-01-01

A novel criterion for the global robust stability of Hopfield-type interval neural networks with delay is presented. An example illustrating the improvement of the present criterion over several recently reported criteria is given.

Local communities obstruct global consensus: Naming game on multi-local-world networks

Science.gov (United States)

Lou, Yang; Chen, Guanrong; Fan, Zhengping; Xiang, Luna

2018-02-01

Community structure is essential for social communications, where individuals belonging to the same community are much more actively interacting and communicating with each other than those in different communities within the human society. Naming game, on the other hand, is a social communication model that simulates the process of learning a name of an object within a community of humans, where the individuals can generally reach global consensus asymptotically through iterative pair-wise conversations. The underlying network indicates the relationships among the individuals. In this paper, three typical topologies, namely random-graph, small-world and scale-free networks, are employed, which are embedded with the multi-local-world community structure, to study the naming game. Simulations show that (1) the convergence process to global consensus is getting slower as the community structure becomes more prominent, and eventually might fail; (2) if the inter-community connections are sufficiently dense, neither the number nor the size of the communities affects the convergence process; and (3) for different topologies with the same (or similar) average node-degree, local clustering of individuals obstruct or prohibit global consensus to take place. The results reveal the role of local communities in a global naming game in social network studies.

Quantized Iterative Learning Consensus Tracking of Digital Networks With Limited Information Communication.

Science.gov (United States)

Xiong, Wenjun; Yu, Xinghuo; Chen, Yao; Gao, Jie

2017-06-01

This brief investigates the quantized iterative learning problem for digital networks with time-varying topologies. The information is first encoded as symbolic data and then transmitted. After the data are received, a decoder is used by the receiver to get an estimate of the sender's state. Iterative learning quantized communication is considered in the process of encoding and decoding. A sufficient condition is then presented to achieve the consensus tracking problem in a finite interval using the quantized iterative learning controllers. Finally, simulation results are given to illustrate the usefulness of the developed criterion.

Network Fictions and the Global Unhomely

Directory of Open Access Journals (Sweden)

Aris Mousoutzanis

2016-04-01

Full Text Available The paper suggests that the increasing proliferation of network fictions in literature, film, television and the internet may be interpreted through a theoretical framework that reconceptuallises the originally strictly psychoanalytic concept of the 'Unheimlich' (Freud’s idea of the ‘unhomely’ or ‘uncanny’ within the context of political, economic and cultural disources fo globalisation. ‘Network fictions’ are those texts consisting of multiple interlocking narratives set in various times and places that explore the interconnections of characters and events across different storylines: novels such as William Gibson’s 'Pattern Recognition' (2003, Hari Kunzro’s 'Transmission' (2005 and 'Gods Without Men' (2011, David Mitchell’s 'Cloud Atlas' (2004, or Rana Dasgupta’s 'Tokyo Cancelled' (2005 are some examples. My argument is that central to these fictions is a sense of a ‘global unhomely’. The sense of displacement, unhomeliness and global mobility that is conveyed in these fictions is fundamental to the experience of the 'Unheimlich'. In addition, the ability of the concept to convey a combined sense of the familiar and the strange is useful in exploring the ways in which these fictions engage with theoretical debates on globalisation that perceive the interaction between global flows and local cultures either in terms of homogenisation and uniformity or of heterogenisation and hybridity. Moreover, the repetitive temporality of the 'Unheimlich' is another distinctive aspect that allows a reading of the disjunctive, non-linear temporal structure of these fictions from this perspective. The ‘repetition compulsion’, however, that Freud considered to be an example of uncanniness was also theorised by him as a post-traumatic symptom, and this implicit association of uncanniness with post-traumatic experience also allows to interpret the persistent preoccupation of these fictions with suffering and disaster, as well as

A New Technique for Tracking the Global Maximum Power Point of PV Arrays Operating Under Partial-Shading Conditions

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2012-01-01

The power-voltage characteristic of photovoltaic (PV) arrays operating under partial-shading conditions exhibits multiple local maximum power points (MPPs). In this paper, a new method to track the global MPP is presented, which is based on controlling a dc/dc converter connected at the PV array...

Recurrent fuzzy neural network backstepping control for the prescribed output tracking performance of nonlinear dynamic systems.

Science.gov (United States)

Han, Seong-Ik; Lee, Jang-Myung

2014-01-01

This paper proposes a backstepping control system that uses a tracking error constraint and recurrent fuzzy neural networks (RFNNs) to achieve a prescribed tracking performance for a strict-feedback nonlinear dynamic system. A new constraint variable was defined to generate the virtual control that forces the tracking error to fall within prescribed boundaries. An adaptive RFNN was also used to obtain the required improvement on the approximation performances in order to avoid calculating the explosive number of terms generated by the recursive steps of traditional backstepping control. The boundedness and convergence of the closed-loop system was confirmed based on the Lyapunov stability theory. The prescribed performance of the proposed control scheme was validated by using it to control the prescribed error of a nonlinear system and a robot manipulator. © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Only (Dis-)Connect: Pentecostal Global Networking as Revelation and Concealment

OpenAIRE

Coleman, Simon

2013-01-01

Contemporary forms of Pentecostalism, such as that of the Faith Movement, are often represented as inherently global, constituting a religion ‘made to travel’ and to missionize across the world. I argue that while much attention has been paid to proselytization as a catalyst in encouraging transnational activities among such Christians, more analysis is needed of how Pentecostalists represent each other in the construction of global imaginaries. The imagined and enacted networks that result a...

Power and Networks in Worldwide Knowledge Coordination: The Case of Global Science

Science.gov (United States)

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 Asymptotic Stability of Switched Neural Networks with Delays

Directory of Open Access Journals (Sweden)

Zhenyu Lu

2015-01-01

Full Text Available This paper investigates the global asymptotic stability of a class of switched neural networks with delays. Several new criteria ensuring global asymptotic stability in terms of linear matrix inequalities (LMIs are obtained via Lyapunov-Krasovskii functional. And here, we adopt the quadratic convex approach, which is different from the linear and reciprocal convex combinations that are extensively used in recent literature. In addition, the proposed results here are very easy to be verified and complemented. Finally, a numerical example is provided to illustrate the effectiveness of the results.

Building dynamic capabilities in large global advertising agency networks: managing the shift from mass communication to digital interactivity

DEFF Research Database (Denmark)

Suheimat, Wisam; Prætorius, Thim; Brambini-Pedersen, Jan Vang

2018-01-01

Interactive digital technologies result in significant managerial challenges for the largest global advertising agency networks. This paper, based on original data from in-depth case research in three of the largest global advertising networks, investigates how advertising agency networks manage...

A global genetic interaction network maps a wiring diagram of cellular function.

Science.gov (United States)

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D; Pelechano, Vicent; Styles, Erin B; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F; Li, Sheena C; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; San Luis, Bryan-Joseph; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M; Moore, Claire L; Rosebrock, Adam P; Caudy, Amy A; Myers, Chad L; Andrews, Brenda; Boone, Charles

2016-09-23

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. Copyright © 2016, American Association for the Advancement of Science.

Global existence of periodic solutions of BAM neural networks with variable coefficients

International Nuclear Information System (INIS)

Guo Shangjiang; Huang Lihong; Dai Binxiang; Zhang Zhongzhi

2003-01-01

In this Letter, we study BAM (bidirectional associative memory) networks with variable coefficients. By some spectral theorems and a continuation theorem based on coincidence degree, we not only obtain some new sufficient conditions ensuring the existence, uniqueness, and global exponential stability of the periodic solution but also estimate the exponentially convergent rate. Our results are less restrictive than previously known criteria and can be applied to neural networks with a broad range of activation functions assuming neither differentiability nor strict monotonicity. Moreover, these conclusions are presented in terms of system parameters and can be easily verified for the globally Lipschitz and the spectral radius being less than 1. Therefore, our results should be useful in the design and applications of periodic oscillatory neural circuits for neural networks with delays

REMOTE OPERATIONS IN A GLOBAL ACCELERATOR NETWORK

International Nuclear Information System (INIS)

PEGGS, S.; SATOGATA, T.; AGARWAL, D.; RICE, D.

2003-01-01

The INTRODUCTION to this paper summarizes the history of the Global Accelerator Network (GAN) concept and the recent workshops that discussed the relationship between GAN and Remote Operations. The REMOTE OPERATIONS SCENARIOS section brings out the organizational philosophy embodied in GAN-like and to non-GAN-like scenarios. The set of major TOPICS RAISED AT THE WORKSHOPS are only partially resolved. COLLABORATION TOOLS are described and discussed, followed by examples of REMOTE ACCELERATOR CONTROL PROJECTS around the world

Remote operations in a global accelerator network

International Nuclear Information System (INIS)

Peggs, Steve; Satogata, Todd; Agarwal, Deborah; Rice, David

2003-01-01

The INTRODUCTION to this paper summarizes the history of the Global Accelerator Network (GAN) concept and the recent workshops that discussed the relationship between GAN and Remote Operations. The REMOTE OPERATIONS SCENARIOS section brings out the organizational philosophy embodied in GAN-like and to non-GAN-like scenarios. The set of major TOPICS RAISED AT THE WORKSHOPS are only partially resolved. COLLABORATION TOOLS are described and discussed, followed by examples of REMOTE ACCELERATOR CONTROL PROJECTS around the world

REMOTE OPERATIONS IN A GLOBAL ACCELERATOR NETWORK.

Energy Technology Data Exchange (ETDEWEB)

PEGGS,S.; SATOGATA,T.; AGARWAL,D.; RICE,D.

2003-05-12

The INTRODUCTION to this paper summarizes the history of the Global Accelerator Network (GAN) concept and the recent workshops that discussed the relationship between GAN and Remote Operations. The REMOTE OPERATIONS SCENARIOS section brings out the organizational philosophy embodied in GAN-like and to non-GAN-like scenarios. The set of major TOPICS RAISED AT THE WORKSHOPS are only partially resolved. COLLABORATION TOOLS are described and discussed, followed by examples of REMOTE ACCELERATOR CONTROL PROJECTS around the world.

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

Energy Technology Data Exchange (ETDEWEB)

Anderson-Teixeira, Kristina J. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Davies, Stuart J. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; National Museum of Natural History, Washington, DC (United States). Dept. of Botany; Bennett, Amy C. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Gonzalez-Akre, Erika B. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Muller-Landau, Helene C. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Joseph Wright, S. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Abu Salim, Kamariah [Univ. of Brunei Darussalam, Bandar Seri Begawan (Brunei). Faculty of Science. Environmental and Life Sciences; Almeyda Zambrano, Angélica M. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Stanford Univ., CA (United States). Stanford Woods Inst. for the Environment; Univ. of Alabama, Tuscaloosa, AL (United States). Dept. of Geography; Alonso, Alfonso [Smithsonian Conservation Biology Inst., Washington, DC (United States). National Zoological Park. Center for Conservation Education and Sustainability; Baltzer, Jennifer L. [Wilfrid Laurier Univ., Waterloo, ON (Canada). Dept. of Biology; Basset, Yves [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Bourg, Norman A. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Broadbent, Eben N. [Smithsonian Conservation Biology Inst. (SCBI), Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Stanford Univ., CA (United States). Stanford Woods Inst. for the Environment; Univ. of Alabama, Tuscaloosa, AL (United States). Dept. of Geography; Brockelman, Warren Y. [Mahidol Univ., Bangkok (Thailand). Dept. of Biology; Bunyavejchewin, Sarayudh [Dept. of National Parks, Wildlife and Plant Conservation, Bangkok (Thailand). Research Office; Burslem, David F. R. P. [Univ. of Aberdeen (United Kingdom). School of Biological Sciences; Butt, Nathalie [Univ. of Queensland, St. Lucia (Australia). School of Biological Sciences; Univ. of Oxford (United Kingdom). School of Geography and the Environment. Environmental Change Inst.; Cao, Min [Chinese Academy of Sciences (CAS), Kunming (China). Xishuangbanna Tropical Botanical Garden. Key Lab. of Tropical Forest Ecology; Cardenas, Dairon [Sinchi Amazonic Inst. of Scientific Research, Bogota (Colombia); Chuyong, George B. [Univ. of Buea (Cameroon). Dept. of Botany and Plant Physiology; Clay, Keith [Indiana Univ., Bloomington, IN (United States). Dept. of Biology; Cordell, Susan [USDA Forest Service, Hilo, HI (United States). Inst. of Pacific Islands Forestry; Dattaraja, Handanakere S. [Indian Inst. of Science, Bangalore (India). Centre for Ecological Sciences; Deng, Xiaobao [Chinese Academy of Sciences (CAS), Kunming (China). Xishuangbanna Tropical Botanical Garden. Key Lab. of Tropical Forest Ecology; Detto, Matteo [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Du, Xiaojun [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Duque, Alvaro [Univ. Nacional de Colombia, Medellin (Colombia). Dept. de Ciencias Forestales; Erikson, David L. [National Museum of Natural History, Washington, DC (United States). Dept. of Botany; Ewango, Corneille E. N. [Okapi Wildlife Reserve, Epulu (Democratic Republic of the Congo). Centre de Formation et de Recherche en Conservation Forestiere (CEFRECOF); Fischer, Gunter A. [Kadoorie Farm and Botanic Garden, Tai Po, Hong Kong (China); Fletcher, Christine [Forest Research Inst. Malaysia (FRIM), Selangor (Malaysia); Foster, Robin B. [The Field Museum, Chicago, IL (United States). Botany Dept.; Giardina, Christian P. [USDA Forest Service, Hilo, HI (United States). Inst. of Pacific Islands Forestry; Gilbert, Gregory S. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Univ. of California, Santa Cruz, CA (United States). Environmental Studies Dept.; Gunatilleke, Nimal [Univ. of Peradeniya (Sri Lanka). Faculty of Science. Dept. of Botany; Gunatilleke, Savitri [Univ. of Peradeniya (Sri Lanka). Faculty of Science. Dept. of Botany; Hao, Zhanqing [Chinese Academy of Sciences (CAS), Shenyang (China). State Key Lab. of Forest and Soil Ecology. Inst. of Applied Ecology; Hargrove, William W. [USDA-Forest Service Station Headquarters, Asheville, NC (United States). Eastern Forest Environmental Threat Assessment Center; Hart, Terese B. [Lukuru Wildlife Research Foundation, Kinshasa (Democratic Republic of the Congo). Tshuapa-Lomami-Lualaba Project; Hau, Billy C. H. [Univ. of Hong Kong (China). School of Biological Sciences. Kadoorie Inst.; He, Fangliang [Univ. of Alberta, Edmonton, AB (Canada). Dept. of Renewable Resources; Hoffman, Forrest M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Earth Sciences Group; Howe, Robert W. [Univ. of Wisconsin, Green Bay, WI (United States). Dept. of Natural and Applied Sciences; Hubbell, Stephen P. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Univ. of California, Los Angeles, CA (United States). Dept. of Ecology and Evolutionary Biology; Inman-Narahari, Faith M. [Univ. of Hawaii, Honolulu, HI (United States). College of Tropical Agriculture and Human Resources; Jansen, Patrick A. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Wageningen Univ. (Netherlands). Resource Ecology Group; Jiang, Mingxi [Chinese Academy of Sciences (CAS), Wuhan (China). Wuhan Botanical Garden; Johnson, Daniel J. [Indiana Univ., Bloomington, IN (United States). Dept. of Biology; Kanzaki, Mamoru [Kyoto Univ. (Japan). Graduate School of Agriculture; Kassim, Abdul Rahman [Forest Research Inst. Malaysia (FRIM), Selangor (Malaysia); Kenfack, David [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; National Museum of Natural History, Washington, DC (United States). Dept. of Botany; Kibet, Staline [National Museums of Kenya, Nairobi (Kenya); Univ. of Nairobi (Kenya). Land Resource Management and Agricultural Technology Dept.; Kinnaird, Margaret F. [Mpala Research Centre, Nanyuki (Kenya); Wildlife Conservation Society, New York, NY (United States). Global Conservation Programs; Korte, Lisa [Smithsonian Conservation Biology Inst., Washington, DC (United States). National Zoological Park. Center for Conservation Education and Sustainability; Kral, Kamil [Silva Tarouca Research Inst., Brno (Czech Republic). Dept. of Forest Ecology; Kumar, Jitendra [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Earth Sciences Group; Larson, Andrew J. [Univ. of Montana, Missoula, MT (United States). College of Forestry and Conservation. Dept. of Forest Management; Li, Yide [Chinese Academy of Forestry, Guangzhou (China). Research Inst. of Tropical Forestry; Li, Xiankun [Chinese Academy of Sciences (CAS), Guilin (China). Guangxi Inst. of Botany; Liu, Shirong [Chinese Academy of Forestry, Beijing (China). Research Inst. of Forest Ecology, Environment and Protection; Lum, Shawn K. Y. [Nanyang Technological Univ. (Singapore). National Inst. of Education. Natural Sciences and Science Education Academic Group; Lutz, James A. [Utah State Univ., Logan, UT (United States). Wildland Resources Dept.; Ma, Keping [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Maddalena, Damian M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computational Earth Sciences Group; Makana, Jean-Remy [Wildlife Conservation Society, Brazzaville (Democratic Republic of the Congo); Malhi, Yadvinder [Univ. of Oxford (United Kingdom). School of Geography and the Environment. Environmental Change Inst.; Marthews, Toby [Univ. of Oxford (United Kingdom). School of Geography and the Environment. Environmental Change Inst.; Mat Serudin, Rafizah [Univ. of Brunei Darussalam, Bandar Seri Begawan (Brunei). Faculty of Science. Environmental and Life Sciences; McMahon, Sean M. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Smithsonian Environmental Research Center, Edgewater, MD (United States). Forest Ecology Group; McShea, William J. [Smithsonian Conservation Biology Inst., Front Royal, VA (United States). National Zoological Park. Conservation Ecology Center; Memiaghe, Hervé R. [Inst. de Recherche en Ecologie Tropicale, Libreville (Gabon). Centre National de la Recherche Scientifique et Technologique; Mi, Xiangcheng [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Mizuno, Takashi [Kyoto Univ. (Japan). Graduate School of Agriculture; Morecroft, Michael [Natural England, Sheffield (United Kingdom); Myers, Jonathan A. [Washington Univ., St. Louis, MO (United States). Dept. of Biology; Novotny, Vojtech [New Guinea Binatang Research Centre, Madang (Papua New Guinea); Univ. of South Bohemia, Ceske Budejovice (Czech Republic). Academy of Sciences of the Czech Republic. Faculty of Science. Biology Centre; de Oliveira, Alexandre A. [Univ. of Sao Paulo (Brazil). Inst. of Biosciences. Ecology Dept.; Ong, Perry S. [Univ. of the Philippines Diliman, Quezon City (Philippines). Inst. of Biology; Orwig, David A. [Harvard Univ., Petersham, MA (United States). Harvard Forest; Ostertag, Rebecca [Univ. of Hawaii, Hilo, HI (United States). Dept. of Biology; den Ouden, Jan [Wageningen Univ. (Netherlands). Forest Ecology and Forest Management Group; Parker, Geoffrey G. [Smithsonian Environmental Research Center, Edgewater, MD (United States). Forest Ecology Group; Phillips, Richard P. [Indiana Univ., Bloomington, IN (United States). Dept. of Biology; Sack, Lawren [Univ. of California, Los Angeles, CA (United States). Dept. of Ecology and Evolutionary Biology; Sainge, Moses N. [Tropical Plant Exploration Group (TroPEG), Mundemba (Cameroon); Sang, Weiguo [Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Botany; Sri-ngernyuang, Kriangsak [Maejo Univ., Chiang Mai (Thailand). Faculty of Architecture and Environmental Design; Sukumar, Raman [Indian Inst. of Science, Bangalore (India). Centre for Ecological Sciences; Sun, I-Fang [National Dong Hwa Univ., Hualian (Taiwan). Dept. of Natural Resources and Environmental Studies; Sungpalee, Witchaphart [Maejo Univ., Chiang Mai (Thailand). Faculty of Architecture and Environmental Design; Suresh, Hebbalalu Sathyanarayana [Indian Inst. of Science, Bangalore (India). Centre for Ecological Sciences; Tan, Sylvester [Sarawak Forest Dept., Kuching (Malaysia); Thomas, Sean C. [Univ. of Toronto, ON (Canada). Faculty of Forestry; Thomas, Duncan W. [Washington State Univ., Vancouver, WA (United States). School of Biological Sciences; Thompson, Jill [Centre for Ecology and Hydrology, Penicuik, Scotland (United Kingdom); Univ. of Puerto Rico Rio Pedras, San Juan (Puerto Rico). Dept. of Environmental Science. Inst. for Tropical Ecosystem Studies; Turner, Benjamin L. [Smithsonian Tropical Research Inst. (STRI), Panama (Panama). Center for Tropical Forest Science. Forest Global Earth Observatory; Uriarte, Maria [Columbia Univ., New York, NY (United States). Dept. of Ecology, Evolution and Environmental Biology; Valencia, Renato [Pontifical Catholic Univ. of Ecuador, Quito (Ecuador). Dept. of Biological Sciences; Vallejo, Marta I. [Inst. Alexander von Humboldt, Bogota (Colombia); Vicentini, Alberto [National Inst. of Amazonian Research (INPA), Manaus (Brazil); Vrška, Tomáš [Silva Tarouca Research Inst., Brno (Czech Republic). Dept. of Forest Ecology; Wang, Xihua [East China Normal Univ. (ECNU), Shanghai (China). School of Ecological and Environmental Sciences; Wang, Xugao [Lukuru Wildlife Research Foundation, Kinshasa (Democratic Republic of the Congo). Tshuapa-Lomami-Lualaba Project; Weiblen, George [Univ. of Minnesota, St. Paul, MN (United States). Dept. of Plant Biology; Wolf, Amy [Univ. of Wisconsin, Green Bay, WI (United States). Dept. of Biology. Dept. of Natural and Applied Sciences; Xu, Han [Chinese Academy of Forestry, Guangzhou (China). Research Inst. of Tropical Forestry; Yap, Sandra [Univ. of the Philippines Diliman, Quezon City (Philippines). Inst. of Biology; Zimmerman, Jess [Univ. of Puerto Rico Rio Piedras, San Juan (Puerto Rico). Dept. of Environmental Science. Inst. for Tropical Ecosystem Studies

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 forest diversity and dynamics in a era of global change

Global Drums and Local Masquerades

Directory of Open Access Journals (Sweden)

Liwhu Betiang

2013-12-01

Full Text Available TV broadcasting has been in Nigeria for more than 50 years (1959-2009. Its development has brought about a series of local responses to global socioeconomic and political environments and “soft” stimuli. This conclusion is based on a critical, interpretive reading of the history, form, and content of television in Nigeria from Obafemi Awolowo’s Western Nigeria Television in Ibadan through the federal government’s reactive establishment of the national network: the Nigeria Television Authority, and later, states and private television stations. The ultimate deregulation of television broadcasting in 1992, perceived as Babangida’s “politically-correct” reaction to the pressures from the Bretton Woods institutions, opened up national media markets for global penetration, and fast-tracked media globalization and its effects in Nigeria. While television stations in Nigeria have multiplied in numerical terms, programming/content/form have followed the global market/technological determinism turning Nigerian TV into localized versions of commercialized western master-scripts with very little local ideological direction.

Global exponential stability for reaction-diffusion recurrent neural networks with multiple time varying delays

International Nuclear Information System (INIS)

Lou, X.; Cui, B.

2008-01-01

In this paper we consider the problem of exponential stability for recurrent neural networks with multiple time varying delays and reaction-diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functional, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis. (author)

The Global Environment Radiation Monitoring Network (GERMON)

International Nuclear Information System (INIS)

Zakheim, B.J.; Goellner, D.A.

1994-01-01

Following the Chernobyl accident in 1986, a group of experts from the World Health Organization (WHO) and the United Nations Environment Program (UNEP) met in France to discuss and develop the basic principles of a global environmental radiation monitoring network (GERMON). The basic functions of this network were to provide regular reports on environmental radiation levels and to be in a position to provide reliable and accurate radiation measurements on a quick and accurate radiation measurements on a quick turnaround basis in the event of a major radiation release. By 1992, although 58 countries had indicated an interest in becoming a part of the GERMON system, only 16 were providing data on a regular basis. This paper traces the history of GERMON from its inception in 1987 through its activities during 1993-4. It details the objectives of the network, describes functions, lists its participants, and presents obstacles in the current network. The paper examines the data requirements for radiological emergency preparedness and offers suggestions for the current system. The paper also describes the growing need for such a network. To add a domestic perspective, the authors present a summary of the environmental monitoring information system that was used by the NRC in 1986 in its analyses of the Chernobyl incident. Then we will use this 1986 experience to propose a method for the use of GERMON should a similar occasion arise in the future

An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

Science.gov (United States)

Leon, Barbara D.; Heller, Paul R.

1987-05-01

A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system

Towards smart mobility in urban spaces: Bus tracking and information application

Science.gov (United States)

Yue, Wong Seng; Chye, Koh Keng; Hoy, Cheong Wan

2017-10-01

Smart city can be defined as an urban space with complete and advanced infrastructure, intelligent networks and platforms, with millions of sensors among which people themselves and their mobile devices. Urban mobility is one of the global smart city project which offers traffic management in real-time, management of passenger transport means, tracking applications and logistics, car sharing services, car park management and more smart mobility services. Due to the frustrated waiting time for the arrival of buses and the difficulty of accessing shuttle bus-related information in a one-stop centre, bus tracking and information application (BTA) is one the proposed solutions to solve the traffic problems in urban spaces. This paper is aimed to design and develop a bus tracking and information application in a selected city in Selangor state, Malaysia. Next, this application also provides an alternative to design public transport tracking and information application for the urban places in Malaysia. Furthermore, the application also provides a smart solution for the management of public infrastructures and urban facilities in Malaysia in future.

Experimental observation of chimera and cluster states in a minimal globally coupled network

Energy Technology Data Exchange (ETDEWEB)

Hart, Joseph D. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Bansal, Kanika [Department of Mathematics, University at Buffalo, SUNY Buffalo, New York 14260 (United States); US Army Research Laboratory, Aberdeen Proving Ground, Maryland 21005 (United States); Murphy, Thomas E. [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742 (United States); Roy, Rajarshi [Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland 20742 (United States); Department of Physics, University of Maryland, College Park, Maryland 20742 (United States); Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742 (United States)

2016-09-15

A “chimera state” is a dynamical pattern that occurs in a network of coupled identical oscillators when the symmetry of the oscillator population is broken into synchronous and asynchronous parts. We report the experimental observation of chimera and cluster states in a network of four globally coupled chaotic opto-electronic oscillators. This is the minimal network that can support chimera states, and our study provides new insight into the fundamental mechanisms underlying their formation. We use a unified approach to determine the stability of all the observed partially synchronous patterns, highlighting the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization. Our approach is general in terms of network size and connectivity. We also find that chimera states often appear in regions of multistability between global, cluster, and desynchronized states.

UFIR Filtering for GPS-Based Tracking over WSNs with Delayed and Missing Data

Directory of Open Access Journals (Sweden)

Karen Uribe-Murcia

2018-01-01

Full Text Available In smart cities, vehicles tracking is organized to increase safety by localizing cars using the Global Positioning System (GPS. The GPS-based system provides accurate tracking but is also required to be reliable and robust. As a main estimator, we propose using the unbiased finite impulse response (UFIR filter, which meets these needs as being more robust than the Kalman filter (KF. The UFIR filter is developed for vehicle tracking in discrete-time state-space over wireless sensor networks (WSNs with time-stamped data discretely delayed on k-step-lags and missing data. The state-space model is represented in a way such that the UFIR filter, KF, and H∞ filter can be used universally. Applications are given for measurement data, which are cooperatively transferred from a vehicle to a central station through several nodes with k-step-lags. Better tracking performance of the UFIR filter is shown experimentally.

Forced disappearance in an era of globalization: biopolitics, shadow networks, and imagined worlds.

Science.gov (United States)

Rozema, Ralph

2011-01-01

In this article, I argue that the practice of forced disappearance of persons on the part of paramilitary groups has become linked to specific processes of globalization. Global flows related to biopolitics, global crime networks, and dehumanizing imaginations reproduced by mass media together constitute a driving force behind forced disappearances. Drawing on ethnographic fieldwork in the Colombian city of Medellín, I analyze how these global flows interact with local armed actors, helping create a climate conducive to forced disappearance. These mechanisms in Colombia show similarities to those in some African and Asian countries. Gaining insight into the mechanisms behind forced disappearance may help prevent it from occurring in the future. Enhancing social inclusion of residents, unraveling the transnational crime networks in which perpetrators are involved, and disseminating rehumanizing images of victims all contribute to curbing the practice of forced disappearance.

Towards a Global Hub and a Network for Collaborative Advancing of Space Weather Predictive Capabilities.

Science.gov (United States)

Kuznetsova, M. M.; Heynderickz, D.; Grande, M.; Opgenoorth, H. J.

2017-12-01

The COSPAR/ILWS roadmap on space weather published in 2015 (Advances in Space Research, 2015: DOI: 10.1016/j.asr.2015.03.023) prioritizes steps to be taken to advance understanding of space environment phenomena and to improve space weather forecasting capabilities. General recommendations include development of a comprehensive space environment specification, assessment of the state of the field on a 5-yr basis, standardization of meta-data and product metrics. To facilitate progress towards roadmap goals there is a need for a global hub for collaborative space weather capabilities assessment and development that brings together research, engineering, operational, educational, and end-user communities. The COSPAR Panel on Space Weather is aiming to build upon past progress and to facilitate coordination of established and new international space weather research and development initiatives. Keys to the success include creating flexible, collaborative, inclusive environment and engaging motivated groups and individuals committed to active participation in international multi-disciplinary teams focused on topics addressing emerging needs and challenges in the rapidly growing field of space weather. Near term focus includes comprehensive assessment of the state of the field and establishing an internationally recognized process to quantify and track progress over time, development of a global network of distributed web-based resources and interconnected interactive services required for space weather research, analysis, forecasting and education.

The global historical climatology network: Long-term monthly temperature, precipitation, and pressure data

International Nuclear Information System (INIS)

Vose, R.S.; Schmoyer, R.L.; Peterson, T.C.; Steurer, P.M.; Heim, R.R. Jr.; Karl, T.R.; Eischeid, J.K.

1992-01-01

Interest in global climate change has risen dramatically during the past several decades. In a similar fashion, the number of data sets available to study global change has also increased. Unfortunately, many different organizations and researchers have compiled these data sets, making it confusing and time consuming for individuals to acquire the most comprehensive data. In response to this rapid growth in the number of global data sets, DOE's Carbon Dioxide Information Analysis Center (CDIAC) and NOAA's National Climatic Data Center (NCDC) established the Global Historical Climatology Network (GHCN) project. The purpose of this project is to compile an improved data set of long-term monthly mean temperature, precipitation, sea level pressure, and station pressure for as dense a network of global stations as possible. Specifically, the GHCN project seeks to consolidate the numerous preexisting national-, regional-, and global-scale data sets into a single global data base; to subject the data to rigorous quality control; and to update, enhance, and distribute the data set at regular intervals. The purpose of this paper is to describe the compilation and contents of the GHCN data base (i.e., GHCN Version 1.0)

Global exponential stability of BAM neural networks with delays and impulses

International Nuclear Information System (INIS)

Li Yongkun

2005-01-01

Sufficient conditions are obtained for the existence and global exponential stability of a unique equilibrium of a class of two-layer heteroassociative networks called bidirectional associative memory (BAM) networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. An illustrative example is given to demonstrate the effectiveness of the obtained results

Virtual Global Accelerator Network (VGAN)(LCC-0083)

International Nuclear Information System (INIS)

Larsen, R

2003-01-01

The concept of a Global Accelerator Network (GAN) has been proposed by key members of ICFA as a cornerstone of a future International Linear Collider (LC). GAN would provide a tool for the participants of an international collaboration to participate in the actual running of the machine from different parts of the world. Some technical experts view the concept as technologically trivial, and instead point out the significant sociological, organizational and administrative problems that must be surmounted in creating a truly workable system. This note proposes that many real issues can be explored by building a simulator (VGAN) consisting of a virtual accelerator model, a global controls model, and a functioning human organizational model, a tool that would explore and resolve many real problems of GAN and the LC enterprise during the LC preliminary design and testing phase

SSC Tenant Meeting: NASA Near Earth Network (NEN) Overview

Science.gov (United States)

Carter, David; Larsen, David; Baldwin, Philip; Wilson, Cristy; Ruley, LaMont

2018-01-01

The Near Earth Network (NEN) consists of globally distributed tracking stations that are strategically located throughout the world which provide Telemetry, Tracking, and Commanding (TTC) services support to a variety of orbital and suborbital flight missions, including Low Earth Orbit (LEO), Geosynchronous Earth Orbit (GEO), highly elliptical, and lunar orbits. Swedish Space Corporation (SSC), which is one of the NEN Commercial Service Provider, has provided the NEN with TTC services support from its Alaska, Hawaii, Chile and Sweden. The presentation will give an overview of the NEN and its support from SSC.

Remote consultation and diagnosis in medical imaging using a global PACS backbone network

Science.gov (United States)

Martinez, Ralph; Sutaria, Bijal N.; Kim, Jinman; Nam, Jiseung

1993-10-01

A Global PACS is a national network which interconnects several PACS networks at medical and hospital complexes using a national backbone network. A Global PACS environment enables new and beneficial operations between radiologists and physicians, when they are located in different geographical locations. One operation allows the radiologist to view the same image folder at both Local and Remote sites so that a diagnosis can be performed. The paper describes the user interface, database management, and network communication software which has been developed in the Computer Engineering Research Laboratory and Radiology Research Laboratory. Specifically, a design for a file management system in a distributed environment is presented. In the remote consultation and diagnosis operation, a set of images is requested from the database archive system and sent to the Local and Remote workstation sites on the Global PACS network. Viewing the same images, the radiologists use pointing overlay commands, or frames to point out features on the images. Each workstation transfers these frames, to the other workstation, so that an interactive session for diagnosis takes place. In this phase, we use fixed frames and variable size frames, used to outline an object. The data pockets for these frames traverses the national backbone in real-time. We accomplish this feature by using TCP/IP protocol sockets for communications. The remote consultation and diagnosis operation has been tested in real-time between the University Medical Center and the Bowman Gray School of Medicine at Wake Forest University, over the Internet. In this paper, we show the feasibility of the operation in a Global PACS environment. Future improvements to the system will include real-time voice and interactive compressed video scenarios.

Situative Space Tracking within Smart Environments

DEFF Research Database (Denmark)

Surie, Dipak; Jäckel, Florian; Janlert, Lars-Erik

2010-01-01

This paper describes our efforts in modeling and tracking a human agent’s situation based on his/her possibilities to perceive and act upon objects (both physical and virtual) within smart environments. A Situative Space Model is proposed. WLAN signal-strength-based situative space tracking syste......-laboratory smart home environment where a global precision of 83.4% and a global recall of 88.6% were obtained.......This paper describes our efforts in modeling and tracking a human agent’s situation based on his/her possibilities to perceive and act upon objects (both physical and virtual) within smart environments. A Situative Space Model is proposed. WLAN signal-strength-based situative space tracking system...

Network advocacy and the emergence of global attention to newborn survival.

Science.gov (United States)

Shiffman, Jeremy

2016-04-01

Globally 2.9 million babies die each year before reaching 28 days of life. Over the past quarter century, neonatal mortality has declined at a slower pace than post-neonatal under-five mortality: in consequence newborns now comprise 44% of all deaths to children under five years. Despite high numbers of newborn deaths, global organizations and national governments paid little attention to the issue until 2000, and resources, while growing since then, remain inadequate. This study examines the factors behind these patterns of policy attention: the delayed emergence of attention, its sudden appearance in 2000, its growth thereafter, but the dearth of resources to date. Drawing on a framework on global health networks grounded in collective action theory, the study finds that a newborn survival network helped to shift perceptions about the problem's severity and tractability, contributing to the rise of global attention. Its efforts were facilitated by pressure on governments to achieve the child survival Millennium Development Goal and by growing awareness that the neonatal period constituted a growing percentage of under-five mortality, a fact the network publicized. The network's relatively recent emergence, its predominantly technical rather than political composition and strategies, and its inability to date to find a framing of the issue that has convinced national political leaders of the issue's urgency, in part explain the insufficiency of resources. However, since 2010 a number of non-health oriented inter-governmental organizations have begun to pay attention to the issue, and several countries with high neonatal mortality have created national plans, developments which augur well for the future. The study points to two broader implications concerning how neglected global health issues come to attract attention: priority emerges from a confluence of factors, rather than any single cause; and growth in priority may depend on the creation of a broader

Shifting Tides in Global Higher Education: Agency, Autonomy, and Governance in the Global Network. Global Studies in Education, Volume 9

Science.gov (United States)

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…

Global stability of an SIR model with differential infectivity on complex networks

Science.gov (United States)

Yuan, Xinpeng; Wang, Fang; Xue, Yakui; Liu, Maoxing

2018-06-01

In this paper, an SIR model with birth and death on complex networks is analyzed, where infected individuals are divided into m groups according to their infection and contact between human is treated as a scale-free social network. We obtain the basic reproduction number R0 as well as the effects of various immunization schemes. The results indicate that the disease-free equilibrium is locally and globally asymptotically stable in some conditions, otherwise disease-free equilibrium is unstable and exists an unique endemic equilibrium that is globally asymptotically stable. Our theoretical results are confirmed by numerical simulations and a promising way for infectious diseases control is suggested.

Tracing the Slow Food Movement: local foodscapes and global networks

NARCIS (Netherlands)

Hendrikx, B.; Dormans, S.E.M.; Lagendijk, A.

2012-01-01

Over the last two decades alternative food practices have mushroomed across the globe. This proliferation has changed local food scapes, infusing localities with new ideas and ways of food production, circulation and consumption. It has also created global networks of innovation and

Route planning with transportation network maps: an eye-tracking study.

Science.gov (United States)

Grison, Elise; Gyselinck, Valérie; Burkhardt, Jean-Marie; Wiener, Jan Malte

2017-09-01

Planning routes using transportation network maps is a common task that has received little attention in the literature. Here, we present a novel eye-tracking paradigm to investigate psychological processes and mechanisms involved in such a route planning. In the experiment, participants were first presented with an origin and destination pair before we presented them with fictitious public transportation maps. Their task was to find the connecting route that required the minimum number of transfers. Based on participants' gaze behaviour, each trial was split into two phases: (1) the search for origin and destination phase, i.e., the initial phase of the trial until participants gazed at both origin and destination at least once and (2) the route planning and selection phase. Comparisons of other eye-tracking measures between these phases and the time to complete them, which depended on the complexity of the planning task, suggest that these two phases are indeed distinct and supported by different cognitive processes. For example, participants spent more time attending the centre of the map during the initial search phase, before directing their attention to connecting stations, where transitions between lines were possible. Our results provide novel insights into the psychological processes involved in route planning from maps. The findings are discussed in relation to the current theories of route planning.

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

Science.gov (United States)

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

The Continuing Growth of Global Cooperation Networks in Research: A Conundrum for National Governments.

Directory of Open Access Journals (Sweden)

Caroline S Wagner

Full Text Available Global collaboration continues to grow as a share of all scientific cooperation, measured as coauthorships of peer-reviewed, published papers. The percent of all scientific papers that are internationally coauthored has more than doubled in 20 years, and they account for all the growth in output among the scientifically advanced countries. Emerging countries, particularly China, have increased their participation in global science, in part by doubling their spending on R&D; they are increasingly likely to appear as partners on internationally coauthored scientific papers. Given the growth of connections at the international level, it is helpful to examine the phenomenon as a communications network and to consider the network as a new organization on the world stage that adds to and complements national systems. When examined as interconnections across the globe over two decades, a global network has grown denser but not more clustered, meaning there are many more connections but they are not grouping into exclusive 'cliques'. This suggests that power relationships are not reproducing those of the political system. The network has features an open system, attracting productive scientists to participate in international projects. National governments could gain efficiencies and influence by developing policies and strategies designed to maximize network benefits-a model different from those designed for national systems.

Global Stability of Complex-Valued Genetic Regulatory Networks with Delays on Time Scales

Directory of Open Access Journals (Sweden)

Wang Yajing

2016-01-01

Full Text Available In this paper, the global exponential stability of complex-valued genetic regulatory networks with delays is investigated. Besides presenting conditions guaranteeing the existence of a unique equilibrium pattern, its global exponential stability is discussed. Some numerical examples for different time scales.

Weighted Optimization-Based Distributed Kalman Filter for Nonlinear Target Tracking in Collaborative Sensor Networks.

Science.gov (United States)

Chen, Jie; Li, Jiahong; Yang, Shuanghua; Deng, Fang

2017-11-01

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the innovation or residual errors of the states. However, the method requires large time window of data to achieve reliable covariance measurement, making it impractical for nonlinear systems which are rapidly changing. To deal with the problem, a weighted optimization-based distributed KF algorithm (WODKF) is proposed in this paper. The algorithm enlarges the data size of each sensor by the received measurements and state estimates from its connected sensors instead of the time window. A new cost function is set as the weighted sum of the bias and oscillation of the state to estimate the "best" estimate of the model noise covariance. The bias and oscillation of the state of each sensor are estimated by polynomial fitting a time window of state estimates and measurements of the sensor and its neighbors weighted by the measurement noise covariance. The best estimate of the model noise covariance is computed by minimizing the weighted cost function using the exhaustive method. The sensor selection method is in addition to the algorithm to decrease the computation load of the filter and increase the scalability of the sensor network. The existence, suboptimality and stability analysis of the algorithm are given. The local probability data association method is used in the proposed algorithm for the multitarget tracking case. The algorithm is demonstrated in simulations on tracking examples for a random signal, one nonlinear target, and four nonlinear targets. Results show the feasibility and superiority of WODKF against other filtering algorithms for a large class of systems.

Monthly Summaries of the Global Historical Climatology Network - Daily (GHCN-D)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Monthly Summaries of Global Historical Climatology Network (GHCN)-Daily is a dataset derived from GHCN-Daily. The data are produced by computing simple averages or...

Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network

NARCIS (Netherlands)

Kölzsch, A.; Blasius, B.

2011-01-01

The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global

European network for research in global change (ENRICH)

Energy Technology Data Exchange (ETDEWEB)

Ghazi, A [European Commission, Bruxelles (Belgium). DG XII/JRC

1996-12-31

While approaching the beginning of the twenty first century, the scientific community is faced with the formidable tasks of monitoring and detecting, understanding and predicting changes in the Earth System and its interactions with human beings. A crucial challenge is to make scientific research results accessible and usable for those involved in the decision making process related to the concept of Sustainable Development. Major international scientific programmes under the umbrella of ICSU, such as the IGBP and WCRP, are dealing with these issues. Although there exist many well developed global change research programmes in several European countries and effective collaboration networks between research institutes, there is an urgent need for overall communication with a view to promoting wider international links ensuring complementarity, synergy and coherence. Recognizing the importance of promoting coherence in research and utilising research results for various European Union (EU) policies, the European Commissioner responsible for Science, Research and Development wrote in March 1992 to all the EU Research Ministers to propose an initiative in this domain. In a rapid response, a group of Senior Experts from the EU Member States was set up in April 1992. This Group established a Task Force to develop the concept of the European Network for Research In Global CHange (ENRICH) which was approved in July 1993

European network for research in global change (ENRICH)

Energy Technology Data Exchange (ETDEWEB)

Ghazi, A. [European Commission, Bruxelles (Belgium). DG XII/JRC

1995-12-31

While approaching the beginning of the twenty first century, the scientific community is faced with the formidable tasks of monitoring and detecting, understanding and predicting changes in the Earth System and its interactions with human beings. A crucial challenge is to make scientific research results accessible and usable for those involved in the decision making process related to the concept of Sustainable Development. Major international scientific programmes under the umbrella of ICSU, such as the IGBP and WCRP, are dealing with these issues. Although there exist many well developed global change research programmes in several European countries and effective collaboration networks between research institutes, there is an urgent need for overall communication with a view to promoting wider international links ensuring complementarity, synergy and coherence. Recognizing the importance of promoting coherence in research and utilising research results for various European Union (EU) policies, the European Commissioner responsible for Science, Research and Development wrote in March 1992 to all the EU Research Ministers to propose an initiative in this domain. In a rapid response, a group of Senior Experts from the EU Member States was set up in April 1992. This Group established a Task Force to develop the concept of the European Network for Research In Global CHange (ENRICH) which was approved in July 1993

Ocean Tracking Network (OTN): Development of Oceanographic Data Integration with Animal Movement

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Bajona, L.

2016-02-01

OTN is a $168-million ocean research and technology development platform headquartered at Dalhousie University, Canada. Using acoustic and satellite telemetry to globally document the movements and survival of aquatic animals, and their environmental correlates. The OTN Mission: to foster conservation and sustainability of valued species by generating knowledge on the movement patterns of aquatic species in their changing environment. OTN's ever-expanding global network of acoustic receivers listening for over 90 different key animal species is providing for the data needed in working in collaboration with researchers for the development of oceanographic data integration with animal movement. Presented here is Data Management's work to date, status and challenges in OTN's move towards a community standard to enable sharing between projects nationally and internationally; permitting inter-operability with other large national (e.g. CHONe, ArcticNET) and international (IOOS, IMOS) networks. This work includes co-development of Animal Acoustic Telemetry (AAT) metadata standard and implementation using an ERDDAP data server (NOAA, Environmental Research Division's Data Access Program) facilitating ingestion for modelers (eg. netcdf).

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

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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.

Global robust exponential stability analysis for interval recurrent neural networks

International Nuclear Information System (INIS)

Xu Shengyuan; Lam, James; Ho, Daniel W.C.; Zou Yun

2004-01-01

This Letter investigates the problem of robust global exponential stability analysis for interval recurrent neural networks (RNNs) via the linear matrix inequality (LMI) approach. The values of the time-invariant uncertain parameters are assumed to be bounded within given compact sets. An improved condition for the existence of a unique equilibrium point and its global exponential stability of RNNs with known parameters is proposed. Based on this, a sufficient condition for the global robust exponential stability for interval RNNs is obtained. Both of the conditions are expressed in terms of LMIs, which can be checked easily by various recently developed convex optimization algorithms. Examples are provided to demonstrate the reduced conservatism of the proposed exponential stability condition

Earthquake Monitoring with the MyShake Global Smartphone Seismic Network

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Inbal, A.; Kong, Q.; Allen, R. M.; Savran, W. H.

2017-12-01

Smartphone arrays have the potential for significantly improving seismic monitoring in sparsely instrumented urban areas. This approach benefits from the dense spatial coverage of users, as well as from communication and computational capabilities built into smartphones, which facilitate big seismic data transfer and analysis. Advantages in data acquisition with smartphones trade-off with factors such as the low-quality sensors installed in phones, high noise levels, and strong network heterogeneity, all of which limit effective seismic monitoring. Here we utilize network and array-processing schemes to asses event detectability with the MyShake global smartphone network. We examine the benefits of using this network in either triggered or continuous modes of operation. A global database of ground motions measured on stationary phones triggered by M2-6 events is used to establish detection probabilities. We find that the probability of detecting an M=3 event with a single phone located 20 nearby phones closely match the regional catalog locations. We use simulated broadband seismic data to examine how location uncertainties vary with user distribution and noise levels. To this end, we have developed an empirical noise model for the metropolitan Los-Angeles (LA) area. We find that densities larger than 100 stationary phones/km2 are required to accurately locate M 2 events in the LA basin. Given the projected MyShake user distribution, that condition may be met within the next few years.

Tensor network decompositions in the presence of a global symmetry

International Nuclear Information System (INIS)

Singh, Sukhwinder; Pfeifer, Robert N. C.; Vidal, Guifre

2010-01-01

Tensor network decompositions offer an efficient description of certain many-body states of a lattice system and are the basis of a wealth of numerical simulation algorithms. We discuss how to incorporate a global symmetry, given by a compact, completely reducible group G, in tensor network decompositions and algorithms. This is achieved by considering tensors that are invariant under the action of the group G. Each symmetric tensor decomposes into two types of tensors: degeneracy tensors, containing all the degrees of freedom, and structural tensors, which only depend on the symmetry group. In numerical calculations, the use of symmetric tensors ensures the preservation of the symmetry, allows selection of a specific symmetry sector, and significantly reduces computational costs. On the other hand, the resulting tensor network can be interpreted as a superposition of exponentially many spin networks. Spin networks are used extensively in loop quantum gravity, where they represent states of quantum geometry. Our work highlights their importance in the context of tensor network algorithms as well, thus setting the stage for cross-fertilization between these two areas of research.

Global Production Networks and International Inequality: Making a Case for a Meso-Level Turn in Macro-Comparative Sociology

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Mathew Mahutga

2015-08-01

Full Text Available In this article, I extend recent macro-comparative empirical research on the developmental implications of global production networks. I draw from theories of commodity/value chains, global production networks and economic sociology to identify three contending theoretical perspectives for exactly how the developmental returns to network participants should be distributed-cooperation, exploitation and differential gains-and derive testable hypotheses for each. Adding to recent empirical advances for measuring the average network position of firms at the country level, I evaluate these hypotheses by way of dynamic panel regression models of hourly wage rates in the garment and transportation equipment industries. The results suggest that macro-sociological theories linking underdevelopment to the structure of the world-economy, as well as theories of the distribution of the gains from network participation, miss important variation at the industry level. Cooperation provides a poor account of the distribution of the gains from network participation. Instead, both industries appear to distribute the gains from network participation differentially across network participants. However, the extent of this inequality increases, and the garment industry transitions to exploitation, when global production networks become entrenched organizational logics. Variation in the distribution of the returns to network participation is explicable only by accounting for production-network governance as it varies across industries and over time. I conclude by highlighting the analytical utility to macro-comparative sociology of a turn toward the mesa-level of global industries.

AN INITIATIVE FOR CONSTRUCTION OF NEW-GENERATION LUNAR GLOBAL CONTROL NETWORK USING MULTI-MISSION DATA

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K. Di

2017-07-01

Full Text Available A lunar global control network provides geodetic datum and control points for mapping of the lunar surface. The widely used Unified Lunar Control Network 2005 (ULCN2005 was built based on a combined photogrammetric solution of Clementine images acquired in 1994 and earlier photographic data. In this research, we propose an initiative for construction of a new-generation lunar global control network using multi-mission data newly acquired in the 21st century, which have much better resolution and precision than the old data acquired in the last century. The new control network will be based on a combined photogrammetric solution of an extended global image and laser altimetry network. The five lunar laser ranging retro-reflectors, which can be identified in LROC NAC images and have cm level 3D position accuracy, will be used as absolute control points in the least squares photogrammetric adjustment. Recently, a new radio total phase ranging method has been developed and used for high-precision positioning of Chang’e-3 lander; this shall offer a new absolute control point. Systematic methods and key techniques will be developed or enhanced, including rigorous and generic geometric modeling of orbital images, multi-scale feature extraction and matching among heterogeneous multi-mission remote sensing data, optimal selection of images at areas of multiple image coverages, and large-scale adjustment computation, etc. Based on the high-resolution new datasets and developed new techniques, the new generation of global control network is expected to have much higher accuracy and point density than the ULCN2005.

Multitarget tracking in cluttered environment for a multistatic passive radar system under the DAB/DVB network

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Shi, Yi Fang; Park, Seung Hyo; Song, Taek Lyul

2017-12-01

The target tracking using multistatic passive radar in a digital audio/video broadcast (DAB/DVB) network with illuminators of opportunity faces two main challenges: the first challenge is that one has to solve the measurement-to-illuminator association ambiguity in addition to the conventional association ambiguity between the measurements and targets, which introduces a significantly complex three-dimensional (3-D) data association problem among the target-measurement illuminator, this is because all the illuminators transmit the same carrier frequency signals and signals transmitted by different illuminators but reflected via the same target become indistinguishable; the other challenge is that only the bistatic range and range-rate measurements are available while the angle information is unavailable or of very poor quality. In this paper, the authors propose a new target tracking algorithm directly in three-dimensional (3-D) Cartesian coordinates with the capability of track management using the probability of target existence as a track quality measure. The proposed algorithm is termed sequential processing-joint integrated probabilistic data association (SP-JIPDA), which applies the modified sequential processing technique to resolve the additional association ambiguity between measurements and illuminators. The SP-JIPDA algorithm sequentially operates the JIPDA tracker to update each track for each illuminator with all the measurements in the common measurement set at each time. For reasons of fair comparison, the existing modified joint probabilistic data association (MJPDA) algorithm that addresses the 3-D data association problem via "supertargets" using gate grouping and provides tracks directly in 3-D Cartesian coordinates, is enhanced by incorporating the probability of target existence as an effective track quality measure for track management. Both algorithms deal with nonlinear observations using the extended Kalman filtering. A simulation study is

Challenges for modeling global gene regulatory networks during development: insights from Drosophila.

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Wilczynski, Bartek; Furlong, Eileen E M

2010-04-15

Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Global Horizontal Control Network of Shanghai Synchrotron Radiation Facility

International Nuclear Information System (INIS)

Yu Chenghao; Ke Ming; Du Hanwen; Yin Lixin; Zhao Zhentang; Dong Lan; Huang Kaixi

2009-01-01

As a national big scientific engineering, Shanghai Synchrotron Radiation Facility (SSRF) has rigid requirement to the components with sub-millimeter accuracy. In the process of survey and positioning global control network is a connecting link, which determines the position relationship between building and accelerator devices, and provides high accuracy datum to local control network. Within the designing process, building and devices are very restrict. While among observation, it's hard to be observed and abound with disadvantages. With continuous optimization and careful operation, super-high accuracy of 0.3 mm within 400 m circumference was achieved and slab's periodic movement could be seen through 3 times measurement. (authors)

Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.

Directory of Open Access Journals (Sweden)

Helmut Schmidt

2014-11-01

Full Text Available Graph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz and low-alpha (6-9 Hz bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80% predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic

Global network structure of dominance hierarchy of ant workers.

Science.gov (United States)

Shimoji, Hiroyuki; Abe, Masato S; Tsuji, Kazuki; Masuda, Naoki

2014-10-06

Dominance hierarchy among animals is widespread in various species and believed to serve to regulate resource allocation within an animal group. Unlike small groups, however, detection and quantification of linear hierarchy in large groups of animals are a difficult task. Here, we analyse aggression-based dominance hierarchies formed by worker ants in Diacamma sp. as large directed networks. We show that the observed dominance networks are perfect or approximate directed acyclic graphs, which are consistent with perfect linear hierarchy. The observed networks are also sparse and random but significantly different from networks generated through thinning of the perfect linear tournament (i.e. all individuals are linearly ranked and dominance relationship exists between every pair of individuals). These results pertain to global structure of the networks, which contrasts with the previous studies inspecting frequencies of different types of triads. In addition, the distribution of the out-degree (i.e. number of workers that the focal worker attacks), not in-degree (i.e. number of workers that attack the focal worker), of each observed network is right-skewed. Those having excessively large out-degrees are located near the top, but not the top, of the hierarchy. We also discuss evolutionary implications of the discovered properties of dominance networks. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Internationalizing Medical Education: The Special Track Curriculum 'Global Health' at Justus Liebig University Giessen.

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Knipper, Michael; Baumann, Adrian; Hofstetter, Christine; Korte, Rolf; Krawinkel, Michael

2015-01-01

Internationalizing higher education is considered to be a major goal for universities in Germany and many medical students aspire to include international experiences into their academic training. However, the exact meaning of "internationalizing" medical education is still poorly defined, just as is the possible pedagogic impact and effects. Against this background, this article presents the special track curriculum on global health (in German: Schwerpunktcurriculum Global Health, short: SPC) at Justus Liebig University Giessen, which was established in 2011 as a comprehensive teaching program to integrate international perspectives and activities systematically into the clinical years of the medical curriculum. The report of the structure, content, didactic principles and participants' evaluations of the SPC is embedded into a larger discussion of the pedagogic value of a broad and interdisciplinary perspective on "global health" in medical education, that explicitly includes attention for health inequities, social determinants of health and the cultural dimensions of medicine and health abroad and "at home" (e.g. in relation to migration). We conclude that if properly defined, the emerging field of "global health" represents a didactically meaningful approach for adding value to medical education through internationalizing the curriculum, especially in regard to themes that despite of their uncontested value are often rather weak within medical education. The concrete curricular structures, however, have always to be developed locally. The "SPC" at Giessen University Medical School is only one possible way of addressing these globally relevant issues in one particular local academic setting.

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

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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

Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating

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Liu, Chenguang; Cheng, Heng-Da; Zhang, Yingtao; Wang, Yuxuan; Xian, Min

2016-01-01

This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.

Spike propagation in driven chain networks with dominant global inhibition

International Nuclear Information System (INIS)

Chang Wonil; Jin, Dezhe Z.

2009-01-01

Spike propagation in chain networks is usually studied in the synfire regime, in which successive groups of neurons are synaptically activated sequentially through the unidirectional excitatory connections. Here we study the dynamics of chain networks with dominant global feedback inhibition that prevents the synfire activity. Neural activity is driven by suprathreshold external inputs. We analytically and numerically demonstrate that spike propagation along the chain is a unique dynamical attractor in a wide parameter regime. The strong inhibition permits a robust winner-take-all propagation in the case of multiple chains competing via the inhibition.

Neural Network Based Maximum Power Point Tracking Control with Quadratic Boost Converter for PMSG—Wind Energy Conversion System

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Ramji Tiwari

2018-02-01

Full Text Available This paper proposes an artificial neural network (ANN based maximum power point tracking (MPPT control strategy for wind energy conversion system (WECS implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O method and Back propagation network (BPN method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC. The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

Design concepts for a Global Telemetered Seismograph Network

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Peterson, Jon; Orsini, Nicholas A.

1982-01-01

This study represents a first step in developing an integrated, real-time global seismic data acquisition system a Global Telemetered Seismograph Network (GTSN). The principal objective of the GTSN will be to acquire reliable, high-quality, real-time seismic data for rapid location and analysis of seismic events. A secondary, but important, objective of the GTSN is to augment the existing off-line seismic data base available for research. The deployment of the GTSN will involve a variety of interrelated activities development of the data acquisition and receiving equipment, establishment of satellite and terrestrial communication links, site selection and preparation, training of station personnel, equipment installation, and establishment of support facilities. It is a complex program and the development of a sound management plan will be essential. The purpose of this study is not to fix design goals or dictate avenues of approach but to develop working concepts that may be used as a framework for program planning.The international exchange of seismic data has been an important factor in the progress that has been made during the past two decades in our understanding of earthquakes and global tectonics. The seismic data base available for analysis and research is derived principally from the Global Seismograph Network (GSN), which is funded and managed by the U.S. Geological Survey (USGS). The GSN comprises some 120 seismograph stations located in more than 60 countries of the world. Established during the 1960 s with the installation of the World-Wide Standardized Seismograph Network (WWSSN) , the GSN has been augmented in recent years by the installation of more advanced data systems, such as the Seismic Research Observatories (SRO), the modified High-Gain LongPeriod (ASRO) seismographs, and the digital WWSSN (DWWSSN). The SRO, ASRO, and DWWSSN stations have the common, distinctive feature of digital data recording, so they are known collectively as the Global

The scaling structure of the global road network.

Science.gov (United States)

Strano, Emanuele; Giometto, Andrea; Shai, Saray; Bertuzzo, Enrico; Mucha, Peter J; Rinaldo, Andrea

2017-10-01

Because of increasing global urbanization and its immediate consequences, including changes in patterns of food demand, circulation and land use, the next century will witness a major increase in the extent of paved roads built worldwide. To model the effects of this increase, it is crucial to understand whether possible self-organized patterns are inherent in the global road network structure. Here, we use the largest updated database comprising all major roads on the Earth, together with global urban and cropland inventories, to suggest that road length distributions within croplands are indistinguishable from urban ones, once rescaled to account for the difference in mean road length. Such similarity extends to road length distributions within urban or agricultural domains of a given area. We find two distinct regimes for the scaling of the mean road length with the associated area, holding in general at small and at large values of the latter. In suitably large urban and cropland domains, we find that mean and total road lengths increase linearly with their domain area, differently from earlier suggestions. Scaling regimes suggest that simple and universal mechanisms regulate urban and cropland road expansion at the global scale. As such, our findings bear implications for global road infrastructure growth based on land-use change and for planning policies sustaining urban expansions.

Gravity model improvement using the DORIS tracking system on the SPOT 2 satellite

Science.gov (United States)

Nerem, R. S.; Lerch, F. J.; Williamson, R. G.; Klosko, S. M.; Robbins, J. W.; Patel, G. B.

1994-01-01

A high-precision radiometric satellite tracking system, Doppler Orbitography and Radio-positioning Integrated by Satellite system (DORIS), has recently been developed by the French space agency, Centre National d'Etudes Spatiales (CNES). DORIS was designed to provide tracking support for missions such as the joint United States/French TOPEX/Poseidon. As part of the flight testing process, a DORIS package was flown on the French SPOT 2 satellite. A substantial quantity of geodetic quality tracking data was obtained on SPOT 2 from an extensive international DORIS tracking network. These data were analyzed to assess their accuracy and to evaluate the gravitational modeling enhancements provided by these data in combination with the Goddard Earth Model-T3 (GEM-T3) gravitational model. These observations have noise levels of 0.4 to 0.5 mm/s, with few residual systematic effects. Although the SPOT 2 satellite experiences high atmospheric drag forces, the precision and global coverage of the DORIS tracking data have enabled more extensive orbit parameterization to mitigate these effects. As a result, the SPOT 2 orbital errors have been reduced to an estimated radial accuracy in the 10-20 cm RMS range. The addition of these data, which encompass many regions heretofore lacking in precision satellite tracking, has significantly improved GEM-T3 and allowed greatly improved orbit accuracies for Sun-synchronous satellites like SPOT 2 (such as ERS 1 and EOS). Comparison of the ensuing gravity model with other contemporary fields (GRIM-4C2, TEG2B, and OSU91A) provides a means to assess the current state of knowledge of the Earth's gravity field. Thus, the DORIS experiment on SPOT 2 has provided a strong basis for evaluating this new orbit tracking technology and has demonstrated the important contribution of the DORIS network to the success of the TOPEX/Poseidon mission.

Global exponential stability of inertial memristor-based neural networks with time-varying delays and impulses.

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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.

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

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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.

A System to Produce Precise Global GPS Network Solutions for all Geodetic GPS Stations in the World

Science.gov (United States)

Blewitt, G.; Kreemer, C. W.

2010-12-01

We have developed an end-to-end system that automatically seeks and routinely retrieves geodetic GPS data from ~5000 stations (currently) around the globe, reduces the data into unique, daily global network solutions, and produces high precision time series for station coordinates ready for time-series analysis, geophysical modeling and interpretation. Moreover, “carrier range” data are produced for all stations, enabling epoch-by-epoch tracking of individual station motions by precise point positioning for investigation of sub-daily processes, such as post-seismic after-slip and ocean tidal loading. Solutions are computed in a global reference frame aligned to ITRF, and optionally in user-specified continental-scale reference frames that can filter out common-mode signals to enhance regional strain anomalies. We describe the elements of this system, the underlying signal processing theory, the products, operational statistics, and scientific applications of our system. The system is fundamentally based on precise point positioning using JPL's GIPSY OASIS II software, coupled with ambiguity resolution and a global network adjustment of ~300,000 parameters per day using our newly developed Ambizap3 software. The system is designed to easily and efficiently absorb stations that deliver data very late, by recycling prior computations in the network adjustment, such that the resulting network solution is identical to starting from scratch. Thus, it becomes possible to trawl continuously the Internet for late arriving data, or for newly discovered data, and seamlessly update all GPS station time series using the new information content. As new stations are added to the processing archive, automated e-mail requests are made to H.-G. Scherneck's server at Chalmers University to compute ocean loading coefficients used by the station motion model. Rinex file headers are parsed and compared with alias tables in order to infer the correct receiver type and antenna

Coherence resonance in globally coupled neuronal networks with different neuron numbers

International Nuclear Information System (INIS)

Ning Wei-Lian; Zhang Zheng-Zhen; Zeng Shang-You; Luo Xiao-Shu; Hu Jin-Lin; Zeng Shao-Wen; Qiu Yi; Wu Hui-Si

2012-01-01

Because a brain consists of tremendous neuronal networks with different neuron numbers ranging from tens to tens of thousands, we study the coherence resonance due to ion channel noises in globally coupled neuronal networks with different neuron numbers. We confirm that for all neuronal networks with different neuron numbers there exist the array enhanced coherence resonance and the optimal synaptic conductance to cause the maximal spiking coherence. Furthermoremore, the enhancement effects of coupling on spiking coherence and on optimal synaptic conductance are almost the same, regardless of the neuron numbers in the neuronal networks. Therefore for all the neuronal networks with different neuron numbers in the brain, relative weak synaptic conductance (0.1 mS/cm 2 ) is sufficient to induce the maximal spiking coherence and the best sub-threshold signal encoding. (interdisciplinary physics and related areas of science and technology)

Global exponential stability and periodicity of reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions

International Nuclear Information System (INIS)

Lu Junguo

2008-01-01

In this paper, the global exponential stability and periodicity for a class of reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions are addressed by constructing suitable Lyapunov functionals and utilizing some inequality techniques. We first prove global exponential converge to 0 of the difference between any two solutions of the original reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions, the existence and uniqueness of equilibrium is the direct results of this procedure. This approach is different from the usually used one where the existence, uniqueness of equilibrium and stability are proved in two separate steps. Furthermore, we prove periodicity of the reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions. Sufficient conditions ensuring the global exponential stability and the existence of periodic oscillatory solutions for the reaction-diffusion delayed recurrent neural networks with Dirichlet boundary conditions are given. These conditions are easy to check and have important leading significance in the design and application of reaction-diffusion recurrent neural networks with delays. Finally, two numerical examples are given to show the effectiveness of the obtained results

Structure and relationships within global manufacturing virtual networks

Directory of Open Access Journals (Sweden)

José Ramón Vilana

2009-04-01

Full Text Available Global Manufacturing Virtual Networks (GMVNs are dynamically changing organizations formed by Original Equipment Manufacturers (OEMs, Contract Manufacturers (CMs, turn-key and component suppliers, R+D centres and distributors. These networks establish a new type of vertical and horizontal relations between independent companies or even competitors where it is not needed to maintain internal manufacturing resources but to manage and share the network resources. The fluid relations that exist within the GMVNs allow them a very permeable organization easy to connect and disconnect from one to each other as well as to choose a set of partners with specific attributes. The result is a highly flexible system characterized by low barriers to entry and exit, geographic flexibility, low costs, rapid technological diffusion, high diversification through contract manufacturers and exceptional economies of scale. Anyhow, there are three major drawbacks in the GMVNs that should be considered at the beginning of this type of collaborations: 1 the risk of contract manufacturers to develop their own end-products in competition with their customers; 2 the technology transfer between competitors OEMs through other members of the GMVN and 3 the lose of process expertise by the OEMs the more they outsource manufacturing processes to the network.

A global, multi-disciplinary, multi-sectorial initiative to combat leptospirosis: Global Leptospirosis Environmental Action Network (GLEAN).

Science.gov (United States)

Durski, Kara N; Jancloes, Michel; Chowdhary, Tej; Bertherat, Eric

2014-06-05

Leptospirosis has emerged as a major public health problem in both animals and humans. The true burden of this epidemic and endemic disease is likely to be grossly under-estimated due to the non-specific clinical presentations of the disease and the difficulty of laboratory confirmation. The complexity that surrounds the transmission dynamics, particularly in epidemic situations, requires a coordinated, multi-disciplinary effort. Therefore, the Global Leptospirosis Environmental Action Network (GLEAN) was developed to improve global and local strategies of how to predict, prevent, detect, and intervene in leptospirosis outbreaks in order to prevent and control leptospirosis in high-risk populations.

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

Science.gov (United States)

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.

PRiFi Networking for Tracking-Resistant Mobile Computing

Science.gov (United States)

2017-11-01

conjunction with other relevant services, including Tor for tracking-resistant inter-organizational communication, distributed protocols for the...is a hardened, fully deployable PriFi implementation that can be used in conjunction with other relevant services, including Tor for tracking

Ion track based tunable device as humidity sensor: a neural network approach

Science.gov (United States)

Sharma, Mamta; Sharma, Anuradha; Bhattacherjee, Vandana

2013-01-01

Artificial Neural Network (ANN) has been applied in statistical model development, adaptive control system, pattern recognition in data mining, and decision making under uncertainty. The nonlinear dependence of any sensor output on the input physical variable has been the motivation for many researchers to attempt unconventional modeling techniques such as neural networks and other machine learning approaches. Artificial neural network (ANN) is a computational tool inspired by the network of neurons in biological nervous system. It is a network consisting of arrays of artificial neurons linked together with different weights of connection. The states of the neurons as well as the weights of connections among them evolve according to certain learning rules.. In the present work we focus on the category of sensors which respond to electrical property changes such as impedance or capacitance. Recently, sensor materials have been embedded in etched tracks due to their nanometric dimensions and high aspect ratio which give high surface area available for exposure to sensing material. Various materials can be used for this purpose to probe physical (light intensity, temperature etc.), chemical (humidity, ammonia gas, alcohol etc.) or biological (germs, hormones etc.) parameters. The present work involves the application of TEMPOS structures as humidity sensors. The sample to be studied was prepared using the polymer electrolyte (PEO/NH4ClO4) with CdS nano-particles dispersed in the polymer electrolyte. In the present research we have attempted to correlate the combined effects of voltage and frequency on impedance of humidity sensors using a neural network model and results have indicated that the mean absolute error of the ANN Model for the training data was 3.95% while for the validation data it was 4.65%. The corresponding values for the LR model were 8.28% and 8.35% respectively. It was also demonstrated the percentage improvement of the ANN Model with respect to the

Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

Science.gov (United States)

Deco, Gustavo; Hagmann, Patric; Hudetz, Anthony G; Tononi, Giulio

2014-12-01

The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Semi-supervised tracking of extreme weather events in global spatio-temporal climate datasets

Science.gov (United States)

Kim, S. K.; Prabhat, M.; Williams, D. N.

2017-12-01

Deep neural networks have been successfully applied to solve problem to detect extreme weather events in large scale climate datasets and attend superior performance that overshadows all previous hand-crafted methods. Recent work has shown that multichannel spatiotemporal encoder-decoder CNN architecture is able to localize events in semi-supervised bounding box. Motivated by this work, we propose new learning metric based on Variational Auto-Encoders (VAE) and Long-Short-Term-Memory (LSTM) to track extreme weather events in spatio-temporal dataset. We consider spatio-temporal object tracking problems as learning probabilistic distribution of continuous latent features of auto-encoder using stochastic variational inference. For this, we assume that our datasets are i.i.d and latent features is able to be modeled by Gaussian distribution. In proposed metric, we first train VAE to generate approximate posterior given multichannel climate input with an extreme climate event at fixed time. Then, we predict bounding box, location and class of extreme climate events using convolutional layers given input concatenating three features including embedding, sampled mean and standard deviation. Lastly, we train LSTM with concatenated input to learn timely information of dataset by recurrently feeding output back to next time-step's input of VAE. Our contribution is two-fold. First, we show the first semi-supervised end-to-end architecture based on VAE to track extreme weather events which can apply to massive scaled unlabeled climate datasets. Second, the information of timely movement of events is considered for bounding box prediction using LSTM which can improve accuracy of localization. To our knowledge, this technique has not been explored neither in climate community or in Machine Learning community.

Tracking Objects with Networked Scattered Directional Sensors

Science.gov (United States)

Plarre, Kurt; Kumar, P. R.

2007-12-01

We study the problem of object tracking using highly directional sensors—sensors whose field of vision is a line or a line segment. A network of such sensors monitors a certain region of the plane. Sporadically, objects moving in straight lines and at a constant speed cross the region. A sensor detects an object when it crosses its line of sight, and records the time of the detection. No distance or angle measurements are available. The task of the sensors is to estimate the directions and speeds of the objects, and the sensor lines, which are unknown a priori. This estimation problem involves the minimization of a highly nonconvex cost function. To overcome this difficulty, we introduce an algorithm, which we call "adaptive basis algorithm." This algorithm is divided into three phases: in the first phase, the algorithm is initialized using data from six sensors and four objects; in the second phase, the estimates are updated as data from more sensors and objects are incorporated. The third phase is an optional coordinated transformation. The estimation is done in an "ad-hoc" coordinate system, which we call "adaptive coordinate system." When more information is available, for example, the location of six sensors, the estimates can be transformed to the "real-world" coordinate system. This constitutes the third phase.

Promoting Simulation Globally: Networking with Nursing Colleagues Across Five Continents.

Science.gov (United States)

Alfes, Celeste M; Madigan, Elizabeth A

Simulation education is gaining momentum internationally and may provide the opportunity to enhance clinical education while disseminating evidence-based practice standards for clinical simulation and learning. There is a need to develop a cohesive leadership group that fosters support, networking, and sharing of simulation resources globally. The Frances Payne Bolton School of Nursing at Case Western Reserve University has had the unique opportunity to establish academic exchange programs with schools of nursing across five continents. Although the joint and mutual simulation activities have been extensive, each international collaboration has also provided insight into the innovations developed by global partners.

Artificial Neural Network based control for PV/T panel to track optimum thermal and electrical power

International Nuclear Information System (INIS)

Ben Ammar, Majed; Chaabene, Maher; Chtourou, Zied

2013-01-01

Highlights: ► We establish a state model of PV/T panel. ► We study the effect of mass flow rate on PV/T efficiency. ► A real time PV/T control algorithm is proposed. ► A model based optimal thermal and electrical power operation point is tracked. - Abstract: As solar energy is intermittent, many algorithms and electronics have been developed to track the maximum power generation from photovoltaic and thermal panels. Following technological advances, these panels are gathered into one unit: PV/T system. PV/T delivers simultaneously two kinds of power: electrical power and thermal power. Nevertheless, no control systems have been developed in order to track maximum power generation from PV/T system. This paper suggests a PV/T control algorithm based on Artificial Neural Network (ANN) to detect the optimal power operating point (OPOP) by considering PV/T model behavior. The OPOP computes the optimum mass flow rate of PV/T for a considered irradiation and ambient temperature. Simulation results demonstrate great concordance between OPOP model based calculation and ANN outputs.

Using online social networks to track a pandemic: A systematic review.

Science.gov (United States)

Al-Garadi, Mohammed Ali; Khan, Muhammad Sadiq; Varathan, Kasturi Dewi; Mujtaba, Ghulam; Al-Kabsi, Abdelkodose M

2016-08-01

The popularity and proliferation of online social networks (OSNs) have created massive social interaction among users that generate an extensive amount of data. An OSN offers a unique opportunity for studying and understanding social interaction and communication among far larger populations now more than ever before. Recently, OSNs have received considerable attention as a possible tool to track a pandemic because they can provide an almost real-time surveillance system at a less costly rate than traditional surveillance systems. A systematic literature search for studies with the primary aim of using OSN to detect and track a pandemic was conducted. We conducted an electronic literature search for eligible English articles published between 2004 and 2015 using PUBMED, IEEExplore, ACM Digital Library, Google Scholar, and Web of Science. First, the articles were screened on the basis of titles and abstracts. Second, the full texts were reviewed. All included studies were subjected to quality assessment. OSNs have rich information that can be utilized to develop an almost real-time pandemic surveillance system. The outcomes of OSN surveillance systems have demonstrated high correlations with the findings of official surveillance systems. However, the limitation in using OSN to track pandemic is in collecting representative data with sufficient population coverage. This challenge is related to the characteristics of OSN data. The data are dynamic, large-sized, and unstructured, thus requiring advanced algorithms and computational linguistics. OSN data contain significant information that can be used to track a pandemic. Different from traditional surveys and clinical reports, in which the data collection process is time consuming at costly rates, OSN data can be collected almost in real time at a cheaper cost. Additionally, the geographical and temporal information can provide exploratory analysis of spatiotemporal dynamics of infectious disease spread. However, on

Contributions of a global network of tree diversity experiments to sustainable forest plantations.

Science.gov (United States)

Verheyen, Kris; Vanhellemont, Margot; Auge, Harald; Baeten, Lander; Baraloto, Christopher; Barsoum, Nadia; Bilodeau-Gauthier, Simon; Bruelheide, Helge; Castagneyrol, Bastien; Godbold, Douglas; Haase, Josephine; Hector, Andy; Jactel, Hervé; Koricheva, Julia; Loreau, Michel; Mereu, Simone; Messier, Christian; Muys, Bart; Nolet, Philippe; Paquette, Alain; Parker, John; Perring, Mike; Ponette, Quentin; Potvin, Catherine; Reich, Peter; Smith, Andy; Weih, Martin; Scherer-Lorenzen, Michael

2016-02-01

The area of forest plantations is increasing worldwide helping to meet timber demand and protect natural forests. However, with global change, monospecific plantations are increasingly vulnerable to abiotic and biotic disturbances. As an adaption measure we need to move to plantations that are more diverse in genotypes, species, and structure, with a design underpinned by science. TreeDivNet, a global network of tree diversity experiments, responds to this need by assessing the advantages and disadvantages of mixed species plantations. The network currently consists of 18 experiments, distributed over 36 sites and five ecoregions. With plantations 1-15 years old, TreeDivNet can already provide relevant data for forest policy and management. In this paper, we highlight some early results on the carbon sequestration and pest resistance potential of more diverse plantations. Finally, suggestions are made for new, innovative experiments in understudied regions to complement the existing network.

Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

Science.gov (United States)

Keown, Christopher L; Datko, Michael C; Chen, Colleen P; Maximo, José Omar; Jahedi, Afrooz; Müller, Ralph-Axel

2017-01-01

Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

Investigation of global and local network properties of music perception with culturally different styles of music.

Science.gov (United States)

Li, Yan; Rui, Xue; Li, Shuyu; Pu, Fang

2014-11-01

Graph theoretical analysis has recently become a popular research tool in neuroscience, however, there have been very few studies on brain responses to music perception, especially when culturally different styles of music are involved. Electroencephalograms were recorded from ten subjects listening to Chinese traditional music, light music and western classical music. For event-related potentials, phase coherence was calculated in the alpha band and then constructed into correlation matrices. Clustering coefficients and characteristic path lengths were evaluated for global properties, while clustering coefficients and efficiency were assessed for local network properties. Perception of light music and western classical music manifested small-world network properties, especially with a relatively low proportion of weights of correlation matrices. For local analysis, efficiency was more discernible than clustering coefficient. Nevertheless, there was no significant discrimination between Chinese traditional and western classical music perception. Perception of different styles of music introduces different network properties, both globally and locally. Research into both global and local network properties has been carried out in other areas; however, this is a preliminary investigation aimed at suggesting a possible new approach to brain network properties in music perception. Copyright © 2014 Elsevier Ltd. All rights reserved.

Building a Global Ocean Science Education Network

Science.gov (United States)

Scowcroft, G. A.; Tuddenham, P. T.; Pizziconi, R.

2016-02-01

It is imperative for ocean science education to be closely linked to ocean science research. This is especially important for research that addresses global concerns that cross national boundaries, including climate related issues. The results of research on these critical topics must find its way to the public, educators, and students of all ages around the globe. To facilitate this, opportunities are needed for ocean scientists and educators to convene and identify priorities and strategies for ocean science education. On June 26 and 27, 2015 the first Global Ocean Science Education (GOSE) Workshop was convened in the United States at the University of Rhode Island Graduate School of Oceanography. The workshop, sponsored by the Consortium for Ocean Science Exploration and Engagement (COSEE) and the College of Exploration, had over 75 participants representing 15 nations. The workshop addressed critical global ocean science topics, current ocean science research and education priorities, advanced communication technologies, and leveraging international ocean research technologies. In addition, panels discussed elementary, secondary, undergraduate, graduate, and public education across the ocean basins with emphasis on opportunities for international collaboration. Special presentation topics included advancements in tropical cyclone forecasting, collaborations among Pacific Islands, ocean science for coastal resiliency, and trans-Atlantic collaboration. This presentation will focus on workshop outcomes as well as activities for growing a global ocean science education network. A summary of the workshop report will also be provided. The dates and location for the 2016 GOES Workshop will be announced. See http://www.coexploration.net/gose/index.html

Structuring energy supply and demand networks in a general equilibrium model to simulate global warming control strategies

International Nuclear Information System (INIS)

Hamilton, S.; Veselka, T.D.; Cirillo, R.R.

1991-01-01

Global warming control strategies which mandate stringent caps on emissions of greenhouse forcing gases can substantially alter a country's demand, production, and imports of energy products. Although there is a large degree of uncertainty when attempting to estimate the potential impact of these strategies, insights into the problem can be acquired through computer model simulations. This paper presents one method of structuring a general equilibrium model, the ENergy and Power Evaluation Program/Global Climate Change (ENPEP/GCC), to simulate changes in a country's energy supply and demand balance in response to global warming control strategies. The equilibrium model presented in this study is based on the principle of decomposition, whereby a large complex problem is divided into a number of smaller submodules. Submodules simulate energy activities and conversion processes such as electricity production. These submodules are linked together to form an energy supply and demand network. Linkages identify energy and fuel flows among various activities. Since global warming control strategies can have wide reaching effects, a complex network was constructed. The network represents all energy production, conversion, transportation, distribution, and utilization activities. The structure of the network depicts interdependencies within and across economic sectors and was constructed such that energy prices and demand responses can be simulated. Global warming control alternatives represented in the network include: (1) conservation measures through increased efficiency; and (2) substitution of fuels that have high greenhouse gas emission rates with fuels that have lower emission rates. 6 refs., 4 figs., 4 tabs

Meteorological applications of a surface network of Global Positioning System receivers

NARCIS (Netherlands)

Haan, de S.

2008-01-01

This thesis presents meteorological applications of water vapour observations from a surface network of Global Positioning System (GPS) receivers. GPS signals are delayed by the atmo¬sphere due to atmospheric refraction and bending. Mapped to the zenith, this delay is called Zenith Total Delay

Global product development interaction between local networks: A study of the Danish food industry

DEFF Research Database (Denmark)

Kristensen, Preben Sander

A study of the Danish foods industry shows that producers of food products largely ignore home marekt demand in their product development activities. They have built up and maintain development of end-user products in interaction with customers in distant sophisticated markets. Concurrently...... view of actors in the global end-user customer market and companies' euclidean view of actors in thelocal business-to-business market. In pr companies combine these two market views by interacting in networks: The global industrial network links various functions which again are each part of a local...... their development of end-user pr through global interaction. It is precisely by not interacting with home market end-user demand, but rather by deriving an industrial home market demand from changing end-user markets that the complex has avoided being insulated....

Global asymptotic stabilization of large-scale hydraulic networks using positive proportional controls

DEFF Research Database (Denmark)

Jensen, Tom Nørgaard; Wisniewski, Rafal

2014-01-01

An industrial case study involving a large-scale hydraulic network underlying a district heating system subject to structural changes is considered. The problem of controlling the pressure drop across the so-called end-user valves in the network to a designated vector of reference values under...... directional actuator constraints is addressed. The proposed solution consists of a set of decentralized positively constrained proportional control actions. The results show that the closed-loop system always has a globally asymptotically stable equilibrium point independently on the number of end......-users. Furthermore, by a proper design of controller gains the closed-loop equilibrium point can be designed to belong to an arbitrarily small neighborhood of the desired equilibrium point. Since there exists a globally asymptotically stable equilibrium point independently on the number of end-users in the system...

Nonlinear Motion Tracking by Deep Learning Architecture

Science.gov (United States)

Verma, Arnav; Samaiya, Devesh; Gupta, Karunesh K.

2018-03-01

In the world of Artificial Intelligence, object motion tracking is one of the major problems. The extensive research is being carried out to track people in crowd. This paper presents a unique technique for nonlinear motion tracking in the absence of prior knowledge of nature of nonlinear path that the object being tracked may follow. We achieve this by first obtaining the centroid of the object and then using the centroid as the current example for a recurrent neural network trained using real-time recurrent learning. We have tweaked the standard algorithm slightly and have accumulated the gradient for few previous iterations instead of using just the current iteration as is the norm. We show that for a single object, such a recurrent neural network is highly capable of approximating the nonlinearity of its path.

Global existence of periodic solutions on a simplified BAM neural network model with delays

International Nuclear Information System (INIS)

Zheng Baodong; Zhang Yazhuo; Zhang Chunrui

2008-01-01

A simplified n-dimensional BAM neural network model with delays is considered. Some results of Hopf bifurcations occurring at the zero equilibrium as the delay increases are exhibited. Global existence of periodic solutions are established using a global Hopf bifurcation result of Wu [Wu J. Symmetric functional-differential equations and neural networks with memory. Trans Am Math Soc 1998;350:4799-838], and a Bendixson criterion for higher dimensional ordinary differential equations due to Li and Muldowney [Li MY, Muldowney J. On Bendixson's criterion. J Differ Equations 1994;106:27-39]. Finally, computer simulations are performed to illustrate the analytical results found

Analyzing the impact of global financial crisis on the interconnectedness of Asian stock markets using network science

OpenAIRE

Jitendra Aswani

2015-01-01

As importance of Asian Stock Markets (ASM) has increased after the globalization, it is become significant to know how this network of ASM behaves on the onset of financial crises. For this study, the Global Financial Crisis is considered whose origin was in the developed country, US, unlike the Asian crisis of 1997. To evaluate the impact of financial crisis on the ASM, network theory is used as a tool here. Network modeling of stock markets is useful as it can help to avert the spillover of...

Internationalizing Medical Education: The Special Track Curriculum 'Global Health' at Justus Liebig University Giessen

Directory of Open Access Journals (Sweden)

Knipper, Michael

2015-11-01

Full Text Available Internationalizing higher education is considered to be a major goal for universities in Germany and many medical students aspire to include international experiences into their academic training. However, the exact meaning of “internationalizing” medical education is still poorly defined, just as is the possible pedagogic impact and effects. Against this background, this article presents the special track curriculum on global health (in German: , short: at Justus Liebig University Giessen, which was established in 2011 as a comprehensive teaching program to integrate international perspectives and activities systematically into the clinical years of the medical curriculum. The report of the structure, content, didactic principles and participants’ evaluations of the SPC is embedded into a larger discussion of the pedagogic value of a broad and interdisciplinary perspective on “global health” in medical education, that explicitly includes attention for health inequities, social determinants of health and the cultural dimensions of medicine and health abroad and “at home” (e.g. in relation to migration. We conclude that if properly defined, the emerging field of “global health” represents a didactically meaningful approach for adding value to medical education through internationalizing the curriculum, especially in regard to themes that despite of their uncontested value are often rather weak within medical education. The concrete curricular structures, however, have always to be developed locally. The “SPC” at Giessen University Medical School is only one possible way of addressing these globally relevant issues in one particular local academic setting.