A study protocol of the effectiveness of PEGASUS: a multi-centred study comparing an intervention to promote shared decision making about breast reconstruction with treatment as usual.

Science.gov (United States)

Harcourt, Diana; Paraskeva, Nicole; White, Paul; Powell, Jane; Clarke, Alex

2017-10-02

Increasingly, women elect breast reconstruction after mastectomy. However, their expectations of surgery are often not met, and dissatisfaction with outcome and ongoing psychosocial concerns and distress are common. We developed a patient-centered intervention, PEGASUS:(Patients' Expectations and Goals: Assisting Shared Understanding of Surgery) which supports shared decision making by helping women clarify their own, individual goals about reconstruction so that they can discuss these with their surgeon. Our acceptability/feasibility work has shown it is well received by patients and health professionals alike. We now need to establish whether PEGASUS improves patients' experiences of breast reconstruction decision making and outcomes. The purpose of this study is, therefore, to examine the effectiveness of PEGASUS, an intervention designed to support shared decision making about breast reconstruction. A multi-centered sequential study will compare the impact of PEGASUS with usual care, in terms of patient reported outcomes (self-reported satisfaction with the outcome of surgery, involvement in decision making and in the consultation) and health economics. Initially we will collect data from our comparison (usual care) group (90 women) who will complete standardized measures (Breast-Q, EQ5D -5 L and ICECAP- A) at the time of decision making, 3, 6 and 12 months after surgery. Health professionals will then be trained to use PEGASUS, which will be delivered to the intervention group (another 90 women completing the same measures at the time of decision making, and 3, 6 and 12 months after surgery). Health professionals and a purposefully selected sample of participants will be interviewed about whether their expectations of reconstruction were met, and their experiences of PEGASUS (if appropriate). PEGASUS may have the potential to provide health professionals with an easily accessible tool aiming to support shared decision making and improve patients

Non-inductively driven tokamak plasmas at near-unity βt in the Pegasus toroidal experiment

Science.gov (United States)

Reusch, J. A.; Bodner, G. M.; Bongard, M. W.; Burke, M. G.; Fonck, R. J.; Pachicano, J. L.; Perry, J. M.; Pierren, C.; Rhodes, A. T.; Richner, N. J.; Rodriguez Sanchez, C.; Schlossberg, D. J.; Weberski, J. D.

2018-05-01

A major goal of the spherical tokamak (ST) research program is accessing a state of low internal inductance ℓi, high elongation κ, and high toroidal and normalized beta ( βt and βN) without solenoidal current drive. Local helicity injection (LHI) in the Pegasus ST [Garstka et al., Nucl. Fusion 46, S603 (2006)] provides non-solenoidally driven plasmas that exhibit these characteristics. LHI utilizes compact, edge-localized current sources for plasma startup and sustainment. It results in hollow current density profiles with low ℓi. The low aspect ratio ( R0/a ˜1.2 ) of Pegasus allows access to high κ and high normalized plasma currents ( IN=Ip/a BT>14 ). Magnetic reconnection during LHI provides auxiliary ion heating. Together, these features provide access to very high βt plasmas. Equilibrium analyses indicate that βt up to ˜100% is achieved. These high βt discharges disrupt at the ideal no-wall β limit at βN˜7.

Relativistic electron diffraction at the UCLA Pegasus photoinjector laboratory

Energy Technology Data Exchange (ETDEWEB)

Musumeci, P. [UCLA Department of Physics and Astronomy, 475 Portola Plaza, Los Angeles, CA 90095-1547 (United States)], E-mail: musumeci@physics.ucla.edu; Moody, J.T.; Scoby, C.M. [UCLA Department of Physics and Astronomy, 475 Portola Plaza, Los Angeles, CA 90095-1547 (United States)

2008-10-15

Electron diffraction holds the promise to yield real-time resolution of atomic motion in an easily accessible environment like a university laboratory at a fraction of the cost of fourth-generation X-ray sources. Currently the limit in time-resolution for conventional electron diffraction is set by how short an electron pulse can be made. A very promising solution to maintain the highest possible beam intensity without excessive pulse broadening from space charge effects is to increase the electron energy to the MeV level where relativistic effects significantly reduce the space charge forces. Rf photoinjectors can in principle deliver up to 10{sup 7}-10{sup 8} electrons packed in bunches of {approx}100-fs length, allowing an unprecedented time resolution and enabling the study of irreversible phenomena by single-shot diffraction patterns. The use of rf photoinjectors as sources for ultrafast electron diffraction has been recently at the center of various theoretical and experimental studies. The UCLA Pegasus laboratory, commissioned in early 2007 as an advanced photoinjector facility, is the only operating system in the country, which has recently demonstrated electron diffraction using a relativistic beam from an rf photoinjector. Due to the use of a state-of-the-art ultrashort photoinjector driver laser system, the beam has been measured to be sub-100-fs long, at least a factor of 5 better than what measured in previous relativistic electron diffraction setups. Moreover, diffraction patterns from various metal targets (titanium and aluminum) have been obtained using the Pegasus beam. One of the main laboratory goals in the near future is to fully develop the rf photoinjector-based ultrafast electron diffraction technique with particular attention to the optimization of the working point of the photoinjector in a low-charge ultrashort pulse regime, and to the development of suitable beam diagnostics.

Relativistic electron diffraction at the UCLA Pegasus photoinjector laboratory

International Nuclear Information System (INIS)

Musumeci, P.; Moody, J.T.; Scoby, C.M.

2008-01-01

Electron diffraction holds the promise to yield real-time resolution of atomic motion in an easily accessible environment like a university laboratory at a fraction of the cost of fourth-generation X-ray sources. Currently the limit in time-resolution for conventional electron diffraction is set by how short an electron pulse can be made. A very promising solution to maintain the highest possible beam intensity without excessive pulse broadening from space charge effects is to increase the electron energy to the MeV level where relativistic effects significantly reduce the space charge forces. Rf photoinjectors can in principle deliver up to 10 7 -10 8 electrons packed in bunches of ∼100-fs length, allowing an unprecedented time resolution and enabling the study of irreversible phenomena by single-shot diffraction patterns. The use of rf photoinjectors as sources for ultrafast electron diffraction has been recently at the center of various theoretical and experimental studies. The UCLA Pegasus laboratory, commissioned in early 2007 as an advanced photoinjector facility, is the only operating system in the country, which has recently demonstrated electron diffraction using a relativistic beam from an rf photoinjector. Due to the use of a state-of-the-art ultrashort photoinjector driver laser system, the beam has been measured to be sub-100-fs long, at least a factor of 5 better than what measured in previous relativistic electron diffraction setups. Moreover, diffraction patterns from various metal targets (titanium and aluminum) have been obtained using the Pegasus beam. One of the main laboratory goals in the near future is to fully develop the rf photoinjector-based ultrafast electron diffraction technique with particular attention to the optimization of the working point of the photoinjector in a low-charge ultrashort pulse regime, and to the development of suitable beam diagnostics

Relativistic electron diffraction at the UCLA Pegasus photoinjector laboratory.

Science.gov (United States)

Musumeci, P; Moody, J T; Scoby, C M

2008-10-01

Electron diffraction holds the promise to yield real-time resolution of atomic motion in an easily accessible environment like a university laboratory at a fraction of the cost of fourth-generation X-ray sources. Currently the limit in time-resolution for conventional electron diffraction is set by how short an electron pulse can be made. A very promising solution to maintain the highest possible beam intensity without excessive pulse broadening from space charge effects is to increase the electron energy to the MeV level where relativistic effects significantly reduce the space charge forces. Rf photoinjectors can in principle deliver up to 10(7)-10(8) electrons packed in bunches of approximately 100-fs length, allowing an unprecedented time resolution and enabling the study of irreversible phenomena by single-shot diffraction patterns. The use of rf photoinjectors as sources for ultrafast electron diffraction has been recently at the center of various theoretical and experimental studies. The UCLA Pegasus laboratory, commissioned in early 2007 as an advanced photoinjector facility, is the only operating system in the country, which has recently demonstrated electron diffraction using a relativistic beam from an rf photoinjector. Due to the use of a state-of-the-art ultrashort photoinjector driver laser system, the beam has been measured to be sub-100-fs long, at least a factor of 5 better than what measured in previous relativistic electron diffraction setups. Moreover, diffraction patterns from various metal targets (titanium and aluminum) have been obtained using the Pegasus beam. One of the main laboratory goals in the near future is to fully develop the rf photoinjector-based ultrafast electron diffraction technique with particular attention to the optimization of the working point of the photoinjector in a low-charge ultrashort pulse regime, and to the development of suitable beam diagnostics.

Spatial Expansion and Automation of the Pegasus Thomson Scattering Diagnostic System

Science.gov (United States)

Bodner, G. M.; Bongard, M. W.; Fonck, R. J.; Reusch, J. A.; Schlossberg, D. J.; Winz, G. R.

2015-11-01

The Pegasus Thomson scattering diagnostic system has recently undergone modifications to increase the spatial range of the diagnostic and automate the Thomson data collection process. Two multichannel spectrometers have been added to the original configuration, providing a total of 24 data channels to view the plasma volume. The new system configuration allows for observation of three distinct regions of the plasma: the local helicity injection (LHI) source (R ~ 67-73.8 cm), the plasma edge (R ~ 51.5-57.6 cm), and the plasma core (R ~ 35-41.1 cm). Each spectrometer utilizes a volume-phase holographic (VPH) grating and a gated-intensified CCD camera. The edge and the LHI spectrometers have been fitted with low-temperature VPH gratings to cover Te = 10 - 100 eV, while the core spectrometer has been fitted with a high-temperature VPH grating to cover Te = 0 . 1 - 1 . 0 keV. The additional spectrometers have been calibrated to account for detector flatness, detector linearity, and vignetting. Operation of the Thomson system has been overhauled to utilize LabVIEW software to synchronize the major components of the Thomson system with the Pegasus shot cycle and to provide intra-shot beam alignment. Multi-point Thomson scattering measurements will be obtained in the aforementioned regions of LHI and Ohmic discharges and will be compared to Langmuir probe measurements. Work supported by US DOE grant DE-FG02-96ER54375.

Neural networks prove effective at NOx reduction

Energy Technology Data Exchange (ETDEWEB)

Radl, B.J. [Pegasus Technologies, Mentor, OH (USA)

2000-05-01

The availability of low cost computer hardware and software is opening up possibilities for the use of artificial intelligence concepts, notably neural networks, in power plant control applications, delivering lower costs, greater efficiencies and reduced emissions. One example of a neural network system is the NeuSIGHT combustion optimisation system, developed by Pegasus Technologies, a subsidiary of KFx Inc. It can help reduce NOx emissions, improve heat rate and enable either deferral or elimination of capital expenditures. on other NOx control technologies, such as low NOx burners, SNCR and SCR. This paper illustrates these benefits using three recent case studies. 4 figs.

Liner Stability Experiments at Pegasus: Diagnostics and Experimental Results

International Nuclear Information System (INIS)

Clark, D.A.; Morgan, D.V.; Rodriguez, G.

1998-01-01

A series of experiments to compare imploding liner performance with magneto-hydrodynamic (MHD) modeling has been performed at the Los Alamos National Laboratory Pegasus II pulse power machine. Liner instability growth originating from initial perturbations machined into the liner has been observed with high resolution. Three major diagnostics were used: radiography, Velocity Interferometer for a Surface of Any Reflector (VISAR), and fiber optic impact pins. For radiography, three flash x-ray units were mounted radially to observe liner shape at three different times during the implosion. Liner velocity was measured continuously with the VISAR for the entire distance traveled in two experiments. Optical impact pins provide a high-resolution measure of liner symmetry and shape near the end of travel. Liner performance has compared well with predictions

Enhanced Control for Local Helicity Injection on the Pegasus ST

Science.gov (United States)

Pierren, C.; Bongard, M. W.; Fonck, R. J.; Lewicki, B. T.; Perry, J. M.

2017-10-01

Local helicity injection (LHI) experiments on Pegasus rely upon programmable control of a 250 MVA modular power supply system that drives the electromagnets and helicity injection systems. Precise control of the central solenoid is critical to experimental campaigns that test the LHI Taylor relaxation limit and the coupling efficiency of LHI-produced plasmas to Ohmic current drive. Enhancement and expansion of the present control system is underway using field programmable gate array (FPGA) technology for digital logic and control, coupled to new 10 MHz optical-to-digital transceivers for semiconductor level device communication. The system accepts optical command signals from existing analog feedback controllers, transmits them to multiple devices in parallel H-bridges, and aggregates their status signals for fault detection. Present device-level multiplexing/de-multiplexing and protection logic is extended to include bridge-level protections with the FPGA. An input command filter protects against erroneous and/or spurious noise generated commands that could otherwise cause device failures. Fault registration and response times with the FPGA system are 25 ns. Initial system testing indicates an increased immunity to power supply induced noise, enabling plasma operations at higher working capacitor bank voltage. This can increase the applied helicity injection drive voltage, enable longer pulse lengths and improve Ohmic loop voltage control. Work supported by US DOE Grant DE-FG02-96ER54375.

Neural networks prove effective at NO{sub x} reduction

Energy Technology Data Exchange (ETDEWEB)

Radl, B.J. [Pegasus Technologies, Mentor, OH (United States)

2000-05-01

The virtues of the Pegasus NeuSIGHT combustion optimisation software are extolled. It has been installed at more than 25 power plants and operates mostly in closed loop control. The software uses the leading neural network technology from Computer associates. The system is said to reduce emissions of nitrogen oxides, increase plant efficiency and has the potential for saving millions of dollars in capital and operating costs. The value of the system is illustrated by case studies from three coal-fired power plants. The meaning of 'neural network' is explained.

Pegasus project. DLC coating and low viscosity oil reduce energy losses significantly

Energy Technology Data Exchange (ETDEWEB)

Doerwald, Dave; Jacobs, Ruud [Hauzer Techno Coating (Netherlands). Tribological Coatings

2012-03-15

Pegasus, the flying horse from Greek mythology, is a suitable name for the research project initiated by a German automotive OEM with participation of Hauzer Techno Coating and several automotive suppliers. It will enable future automotive vehicles to reduce fuel consumption without losing power. The project described in this article focuses on the rear differential, because reducing friction here can contribute considerably to efficiency improvement of the whole vehicle. Surfaces, coating and oil viscosity have been investigated and interesting conclusions have been reached. (orig.)

Ion Heating During Local Helicity Injection Plasma Startup in the Pegasus ST

Science.gov (United States)

Burke, M. G.; Barr, J. L.; Bongard, M. W.; Fonck, R. J.; Hinson, E. T.; Perry, J. M.; Reusch, J. A.

2015-11-01

Plasmas in the Pegasus ST are initiated either through standard, MHD stable, inductive current drive or non-solenoidal local helicity injection (LHI) current drive with strong reconnection activity, providing a rich environment to study ion dynamics. During LHI discharges, a large amount of impurity ion heating has been observed, with the passively measured impurity Ti as high as 800 eV compared to Ti ~ 60 eV and Te ~ 175 eV during standard inductive current drive discharges. In addition, non-thermal ion velocity distributions are observed and appear to be strongest near the helicity injectors. The ion heating is hypothesized to be a result of large-scale magnetic reconnection activity, as the amount of heating scales with increasing fluctuation amplitude of the dominant, edge localized, n =1 MHD mode. An approximate temporal scaling of the heating with the amplitude of higher frequency magnetic fluctuations has also been observed, with large amounts of power spectral density present at several impurity ion cyclotron frequencies. Recent experiments have focused on investigating the impurity ion heating scaling with the ion charge to mass ratio as well as the reconnecting field strength. The ion charge to mass ratio was modified by observing different impurity charge states in similar LHI plasmas while the reconnecting field strength was modified by changing the amount of injected edge current. Work supported by US DOE grant DE-FG02-96ER54375.

Epidemiology and genetics of common mental disorders in the general population: the PEGASUS-Murcia project

Science.gov (United States)

Navarro-Mateu, Fernando; Tormo, MJ; Vilagut, G; Alonso, J; Ruíz-Merino, G; Escámez, T; Salmerón, D; Júdez, J; Martínez, S; Navarro, C

2013-01-01

Background Multidisciplinary collaboration between clinicians, epidemiologists, neurogeneticists and statisticians on research projects has been encouraged to improve our knowledge of the complex mechanisms underlying the aetiology and burden of mental disorders. The PEGASUS-Murcia (Psychiatric Enquiry to General Population in Southeast Spain-Murcia) project was designed to assess the prevalence of common mental disorders and to identify the risk and protective factors, and it also included the collection of biological samples to study the gene–environmental interactions in the context of the World Mental Health Survey Initiative. Methods and analysis The PEGASUS-Murcia project is a new cross-sectional face-to-face interview survey based on a representative sample of non-institutionalised adults in the Region of Murcia (Mediterranean Southeast, Spain). Trained lay interviewers used the latest version of the computer-assisted personal interview of the Composite International Diagnostic Interview (CIDI 3.0) for use in Spain, specifically adapted for the project. Two biological samples of buccal mucosal epithelium will be collected from each interviewed participant, one for DNA extraction for genomic and epigenomic analyses and the other to obtain mRNA for gene expression quantification. Several quality control procedures will be implemented to assure the highest reliability and validity of the data. This article describes the rationale, sampling methods and questionnaire content as well as the laboratory methodology. Ethics and dissemination Informed consent will be obtained from all participants and a Regional Ethics Research Committee has approved the protocol. Results will be disseminated in peer-reviewed publications and presented at the national and the international conferences. Discussion Cross-sectional studies, which combine detailed personal information with biological data, offer new and exciting opportunities to study the gene�

Structural stability of interaction networks against negative external fields

Science.gov (United States)

Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.

2018-04-01

We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.

Mean field interaction in biochemical reaction networks

KAUST Repository

Tembine, Hamidou; Tempone, Raul; Vilanova, Pedro

2011-01-01

In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits

Mean field interaction in biochemical reaction networks

KAUST Repository

Tembine, Hamidou

2011-09-01

In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits and illustrate them with numerical examples. © 2011 IEEE.

Producing an Infrared Multiwavelength Galactic Plane Atlas Using Montage, Pegasus, and Amazon Web Services

Science.gov (United States)

Rynge, M.; Juve, G.; Kinney, J.; Good, J.; Berriman, B.; Merrihew, A.; Deelman, E.

2014-05-01

In this paper, we describe how to leverage cloud resources to generate large-scale mosaics of the galactic plane in multiple wavelengths. Our goal is to generate a 16-wavelength infrared Atlas of the Galactic Plane at a common spatial sampling of 1 arcsec, processed so that they appear to have been measured with a single instrument. This will be achieved by using the Montage image mosaic engine process observations from the 2MASS, GLIMPSE, MIPSGAL, MSX and WISE datasets, over a wavelength range of 1 μm to 24 μm, and by using the Pegasus Workflow Management System for managing the workload. When complete, the Atlas will be made available to the community as a data product. We are generating images that cover ±180° in Galactic longitude and ±20° in Galactic latitude, to the extent permitted by the spatial coverage of each dataset. Each image will be 5°x5° in size (including an overlap of 1° with neighboring tiles), resulting in an atlas of 1,001 images. The final size will be about 50 TBs. This paper will focus on the computational challenges, solutions, and lessons learned in producing the Atlas. To manage the computation we are using the Pegasus Workflow Management System, a mature, highly fault-tolerant system now in release 4.2.2 that has found wide applicability across many science disciplines. A scientific workflow describes the dependencies between the tasks and in most cases the workflow is described as a directed acyclic graph, where the nodes are tasks and the edges denote the task dependencies. A defining property for a scientific workflow is that it manages data flow between tasks. Applied to the galactic plane project, each 5 by 5 mosaic is a Pegasus workflow. Pegasus is used to fetch the source images, execute the image mosaicking steps of Montage, and store the final outputs in a storage system. As these workflows are very I/O intensive, care has to be taken when choosing what infrastructure to execute the workflow on. In our setup, we choose

Endogenous fields enhanced stochastic resonance in a randomly coupled neuronal network

International Nuclear Information System (INIS)

Deng, Bin; Wang, Lin; Wang, Jiang; Wei, Xi-le; Yu, Hai-tao

2014-01-01

Highlights: • We study effects of endogenous fields on stochastic resonance in a neural network. • Stochastic resonance can be notably enhanced by endogenous field feedback. • Endogenous field feedback delay plays a vital role in stochastic resonance. • The parameters of low-passed filter play a subtle role in SR. - Abstract: Endogenous field, evoked by structured neuronal network activity in vivo, is correlated with many vital neuronal processes. In this paper, the effects of endogenous fields on stochastic resonance (SR) in a randomly connected neuronal network are investigated. The network consists of excitatory and inhibitory neurons and the axonal conduction delays between neurons are also considered. Numerical results elucidate that endogenous field feedback results in more rhythmic macroscope activation of the network for proper time delay and feedback coefficient. The response of the network to the weak periodic stimulation can be notably enhanced by endogenous field feedback. Moreover, the endogenous field feedback delay plays a vital role in SR. We reveal that appropriately tuned delays of the feedback can either induce the enhancement of SR, appearing at every integer multiple of the weak input signal’s oscillation period, or the depression of SR, appearing at every integer multiple of half the weak input signal’s oscillation period for the same feedback coefficient. Interestingly, the parameters of low-passed filter which is used in obtaining the endogenous field feedback signal play a subtle role in SR

The wireshark field guide analyzing and troubleshooting network traffic

CERN Document Server

Shimonski, Robert

2013-01-01

The Wireshark Field Guide provides hackers, pen testers, and network administrators with practical guidance on capturing and interactively browsing computer network traffic. Wireshark is the world's foremost network protocol analyzer, with a rich feature set that includes deep inspection of hundreds of protocols, live capture, offline analysis and many other features. The Wireshark Field Guide covers the installation, configuration and use of this powerful multi-platform tool. The book give readers the hands-on skills to be more productive with Wireshark as they drill

A HERO'S LITTLE HORSE: DISCOVERY OF A DISSOLVING STAR CLUSTER IN PEGASUS

Energy Technology Data Exchange (ETDEWEB)

Kim, Dongwon; Jerjen, Helmut, E-mail: dongwon.kim@anu.edu.au, E-mail: helmut.jerjen@anu.edu.au [Research School of Astronomy and Astrophysics, The Australian National University, Mt Stromlo Observatory, via Cotter Road, Weston, ACT 2611 (Australia)

2015-01-20

We report the discovery of an ultra-faint stellar system in the constellation of Pegasus. This concentration of stars was detected by applying our overdensity detection algorithm to the Sloan Digital Sky Survey Data Release 10 and confirmed with deeper photometry from the Dark Energy Camera (DECam) at the 4 m Blanco telescope. The best-fitting model isochrone indicates that this stellar system, Kim 1, features an old (12 Gyr) and metal-poor ([Fe/H] ∼ -1.7) stellar population at a heliocentric distance of 19.8 ± 0.9 kpc. We measure a half-light radius of 6.9 ± 0.6 pc using a Plummer profile. The small physical size and the extremely low luminosity are comparable to the faintest known star clusters Segue 3, Koposov 1 and 2, and Muñoz 1. However, Kim 1 exhibits a lower star concentration and is lacking a well-defined center. It also has an unusually high ellipticity and irregular outer isophotes, which suggests that we are seeing an intermediate mass star cluster being stripped by the Galactic tidal field. An extended search for evidence of an associated stellar stream within the 3 deg{sup 2} DECam field remains inconclusive. The finding of Kim 1 is consistent with current overdensity detection limits and supports the hypothesis that there are still a substantial number of extreme low-luminosity star clusters undetected in the wider Milky Way halo.

Research collaboration in groups and networks: differences across academic fields.

Science.gov (United States)

Kyvik, Svein; Reymert, Ingvild

2017-01-01

The purpose of this paper is to give a macro-picture of collaboration in research groups and networks across all academic fields in Norwegian research universities, and to examine the relative importance of membership in groups and networks for individual publication output. To our knowledge, this is a new approach, which may provide valuable information on collaborative patterns in a particular national system, but of clear relevance to other national university systems. At the system level, conducting research in groups and networks are equally important, but there are large differences between academic fields. The research group is clearly most important in the field of medicine and health, while undertaking research in an international network is most important in the natural sciences. Membership in a research group and active participation in international networks are likely to enhance publication productivity and the quality of research.

Anomalous Ion Heating, Intrinsic and Induced Rotation in the Pegasus Toroidal Experiment

Science.gov (United States)

Burke, M. G.; Barr, J. L.; Bongard, M. W.; Fonck, R. J.; Hinson, E. T.; Perry, J. M.; Redd, A. J.; Thome, K. E.

2014-10-01

Pegasus plasmas are initiated through either standard, MHD stable, inductive current drive or non-solenoidal local helicity injection (LHI) current drive with strong reconnection activity, providing a rich environment to study ion dynamics. During LHI discharges, a large amount of anomalous impurity ion heating has been observed, with Ti ~ 800 eV but Te < 100 eV. The ion heating is hypothesized to be a result of large-scale magnetic reconnection activity, as the amount of heating scales with increasing fluctuation amplitude of the dominant, edge localized, n = 1 MHD mode. Chordal Ti spatial profiles indicate centrally peaked temperatures, suggesting a region of good confinement near the plasma core surrounded by a stochastic region. LHI plasmas are observed to rotate, perhaps due to an inward radial current generated by the stochastization of the plasma edge by the injected current streams. H-mode plasmas are initiated using a combination of high-field side fueling and Ohmic current drive. This regime shows a significant increase in rotation shear compared to L-mode plasmas. In addition, these plasmas have been observed to rotate in the counter-Ip direction without any external momentum sources. The intrinsic rotation direction is consistent with predictions from the saturated Ohmic confinement regime. Work supported by US DOE Grant DE-FG02-96ER54375.

Waferscale assembly of Field-Aligned nanotube Networks (FANs)

DEFF Research Database (Denmark)

Dimaki, Maria; Bøggild, Peter

2006-01-01

We demonstrate the integration of nanotube networks on 512 individual devices on a full 4-inch wafer in less than 60 seconds with a roughly 80% yield using dielectrophoresis. We present here investigations of the morphology and electrical resistance of such field aligned networks for different fr...

Predicting local field potentials with recurrent neural networks.

Science.gov (United States)

Kim, Louis; Harer, Jacob; Rangamani, Akshay; Moran, James; Parks, Philip D; Widge, Alik; Eskandar, Emad; Dougherty, Darin; Chin, Sang Peter

2016-08-01

We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.

The wireless networking system of Earthquake precursor mobile field observation

Science.gov (United States)

Wang, C.; Teng, Y.; Wang, X.; Fan, X.; Wang, X.

2012-12-01

The mobile field observation network could be real-time, reliably record and transmit large amounts of data, strengthen the physical signal observations in specific regions and specific period, it can improve the monitoring capacity and abnormal tracking capability. According to the features of scatter everywhere, a large number of current earthquake precursor observation measuring points, networking technology is based on wireless broadband accessing McWILL system, the communication system of earthquake precursor mobile field observation would real-time, reliably transmit large amounts of data to the monitoring center from measuring points through the connection about equipment and wireless accessing system, broadband wireless access system and precursor mobile observation management center system, thereby implementing remote instrument monitoring and data transmition. At present, the earthquake precursor field mobile observation network technology has been applied to fluxgate magnetometer array geomagnetic observations of Tianzhu, Xichang,and Xinjiang, it can be real-time monitoring the working status of the observational instruments of large area laid after the last two or three years, large scale field operation. Therefore, it can get geomagnetic field data of the local refinement regions and provide high-quality observational data for impending earthquake tracking forecast. Although, wireless networking technology is very suitable for mobile field observation with the features of simple, flexible networking etc, it also has the phenomenon of packet loss etc when transmitting a large number of observational data due to the wireless relatively weak signal and narrow bandwidth. In view of high sampling rate instruments, this project uses data compression and effectively solves the problem of data transmission packet loss; Control commands, status data and observational data transmission use different priorities and means, which control the packet loss rate within

Application of CMAC Neural Network to Solar Energy Heliostat Field Fault Diagnosis

Directory of Open Access Journals (Sweden)

Neng-Sheng Pai

2013-01-01

Full Text Available Solar energy heliostat fields comprise numerous sun tracking platforms. As a result, fault detection is a highly challenging problem. Accordingly, the present study proposes a cerebellar model arithmetic computer (CMAC neutral network for automatically diagnosing faults within the heliostat field in accordance with the rotational speed, vibration, and temperature characteristics of the individual heliostat transmission systems. As compared with radial basis function (RBF neural network and back propagation (BP neural network in the heliostat field fault diagnosis, the experimental results show that the proposed neural network has a low training time, good robustness, and a reliable diagnostic performance. As a result, it provides an ideal solution for fault diagnosis in modern, large-scale heliostat fields.

Progress on Thomson scattering in the Pegasus Toroidal Experiment

International Nuclear Information System (INIS)

Schlossberg, D J; Bongard, M W; Fonck, R J; Schoenbeck, N L; Winz, G R

2013-01-01

A novel Thomson scattering system has been implemented on the Pegasus Toroidal Experiment where typical densities of 10 19 m −3 and electron temperatures of 10 to 500 eV are expected. The system leverages technological advances in high-energy pulsed lasers, volume phase holographic (VPH) diffraction gratings, and gated image intensified (ICCD) cameras to provide a relatively low-maintenance, economical, robust diagnostic system. Scattering is induced by a frequency-doubled, Q-switched Nd:YAG laser (2 J at 532 nm, 7 ns FWHM pulse) directed to the plasma over a 7.7 m long beam path, and focused to 80%) and fast-gated ICCDs (gate > 2 ns, Gen III intensifier) with high-throughput (F/1.8), achromatic lensing. A stray light mitigation facility has been implemented, consisting of a multi-aperture optical baffle system and a simple beam dump. Successful stray light reduction has enabled detection of scattered signal, and Rayleigh scattering has been used to provide a relative calibration. Initial temperature measurements have been made and data analysis algorithms are under development

Progress on Thomson scattering in the Pegasus Toroidal Experiment

Science.gov (United States)

Schlossberg, D. J.; Bongard, M. W.; Fonck, R. J.; Schoenbeck, N. L.; Winz, G. R.

2013-11-01

A novel Thomson scattering system has been implemented on the Pegasus Toroidal Experiment where typical densities of 1019 m-3 and electron temperatures of 10 to 500 eV are expected. The system leverages technological advances in high-energy pulsed lasers, volume phase holographic (VPH) diffraction gratings, and gated image intensified (ICCD) cameras to provide a relatively low-maintenance, economical, robust diagnostic system. Scattering is induced by a frequency-doubled, Q-switched Nd:YAG laser (2 J at 532 nm, 7 ns FWHM pulse) directed to the plasma over a 7.7 m long beam path, and focused to VPH transmission gratings (eff. > 80%) and fast-gated ICCDs (gate > 2 ns, Gen III intensifier) with high-throughput (F/1.8), achromatic lensing. A stray light mitigation facility has been implemented, consisting of a multi-aperture optical baffle system and a simple beam dump. Successful stray light reduction has enabled detection of scattered signal, and Rayleigh scattering has been used to provide a relative calibration. Initial temperature measurements have been made and data analysis algorithms are under development.

AC Electric Field Communication for Human-Area Networking

Science.gov (United States)

Kado, Yuichi; Shinagawa, Mitsuru

We have proposed a human-area networking technology that uses the surface of the human body as a data transmission path and uses an AC electric field signal below the resonant frequency of the human body. This technology aims to achieve a “touch and connect” intuitive form of communication by using the electric field signal that propagates along the surface of the human body, while suppressing both the electric field radiating from the human body and mutual interference. To suppress the radiation field, the frequency of the AC signal that excites the transmitter electrode must be lowered, and the sensitivity of the receiver must be raised while reducing transmission power to its minimally required level. We describe how we are developing AC electric field communication technologies to promote the further evolution of a human-area network in support of ubiquitous services, focusing on three main characteristics, enabling-transceiver technique, application-scenario modeling, and communications quality evaluation. Special attention is paid to the relationship between electro-magnetic compatibility evaluation and regulations for extremely low-power radio stations based on Japan's Radio Law.

Non-equilibrium mean-field theories on scale-free networks

International Nuclear Information System (INIS)

Caccioli, Fabio; Dall'Asta, Luca

2009-01-01

Many non-equilibrium processes on scale-free networks present anomalous critical behavior that is not explained by standard mean-field theories. We propose a systematic method to derive stochastic equations for mean-field order parameters that implicitly account for the degree heterogeneity. The method is used to correctly predict the dynamical critical behavior of some binary spin models and reaction–diffusion processes. The validity of our non-equilibrium theory is further supported by showing its relation with the generalized Landau theory of equilibrium critical phenomena on networks

Mean field games for cognitive radio networks

KAUST Repository

Tembine, Hamidou; Tempone, Raul; Vilanova, Pedro

2012-01-01

In this paper we study mobility effect and power saving in cognitive radio networks using mean field games. We consider two types of users: primary and secondary users. When active, each secondary transmitter-receiver uses carrier sensing

Full-wave modeling of the O-X mode conversion in the Pegasus toroidal experiment

Energy Technology Data Exchange (ETDEWEB)

Koehn, A. [Institut fuer Plasmaforschung, Universitaet Stuttgart, D-70569 (Germany); Jacquot, J. [IRFM, CEA, F-13108 Saint-Paul-lez-Durance (France); Bongard, M. W.; Hinson, E. T.; Volpe, F. A. [Department of Engineering Physics, University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States); Gallian, S. [Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin 53706 (United States)

2011-08-15

The ordinary-extraordinary (O-X) mode conversion is modeled with the aid of a 2D full-wave code in the Pegasus toroidal experiment as a function of the launch angles. It is shown how the shape of the plasma density profile in front of the antenna can significantly influence the mode conversion efficiency and, thus, the generation of electron Bernstein waves (EBWs). It is therefore desirable to control the density profile in front of the antenna for successful operation of an EBW heating and current drive system. On the other hand, the conversion efficiency is shown to be resilient to vertical displacements of the plasma as large as {+-}10 cm.

Experiment of Wireless Sensor Network to Monitor Field Data

Directory of Open Access Journals (Sweden)

Kwang Sik Kim

2009-08-01

Full Text Available Recently the mobile wireless network has been drastically enhanced and one of the most efficient ways to realize the ubiquitous network will be to develop the converged network by integrating the mobile wireless network with other IP fixed network like NGN (Next Generation Network. So in this paper the term of the wireless ubiquitous network is used to describe this approach. In this paper, first, the wireless ubiquitous network architecture is described based on IMS which has been standardized by 3GPP (3rd Generation Partnership Program. Next, the field data collection system to match the satellite data using location information is proposed based on the concept of the wireless ubiquitous network architecture. The purpose of the proposed system is to provide more accurate analyzing method with the researchers in the remote sensing area.

PEGASUS: a multi-megawatt nuclear electric propulsion system

International Nuclear Information System (INIS)

Coomes, E.P.; Cuta, J.M.; Webb, B.J.; King, D.Q.

1985-06-01

With the Space Transportation System (STS), the advent of space station Columbus and the development of expertise at working in space that this will entail, the gateway is open to the final frontier. The exploration of this frontier is possible with state-of-the-art hydrogen/oxygen propulsion but would be greatly enhanced by the higher specific impulse of electric propulsion. This paper presents a concept that uses a multi-megawatt nuclear power plant to drive an electric propulsion system. The concept has been named PEGASUS, PowEr GenerAting System for Use in Space, and is intended as a ''work horse'' for general space transportation needs, both long- and short-haul missions. The recent efforts of the SP-100 program indicate that a power system capable of producing upwards of 1 megawatt of electric power should be available in the next decade. Additionally, efforts in other areas indicate that a power system with a constant power capability an order of magnitude greater could be available near the turn of the century. With the advances expected in megawatt-class space power systems, the high specific impulse propulsion systems must be reconsidered as potential propulsion systems. The power system is capable of meeting both the propulsion system and spacecraft power requirements

Neural networks improve performance of coal-fired boilers

Energy Technology Data Exchange (ETDEWEB)

Radl, B.J. [Pegasus Technologies Ltd., Painesville, OH (United States)

1999-03-01

Work sponsored by the US Department of Energy through its NICE{sup 3} programme, and co-funded by industry partners First Energy Corp. (host organisation and co-funder) and Pegasus Technologies (inventor, developer and supplier), has resulted in the development of online, real-time neural networks which help coal-fired utility boilers to dynamically adjust combustion setpoints. The payoff is a system which helps reduce NOx emissions up to 60%, while improving heat rate up to 2% overall. The system has avoided or postponed large capacity expenditures while meeting environmental compliance requirements. 3 figs., 1 tab.

Artificial Neural Network L* from different magnetospheric field models

Science.gov (United States)

Yu, Y.; Koller, J.; Zaharia, S. G.; Jordanova, V. K.

2011-12-01

The third adiabatic invariant L* plays an important role in modeling and understanding the radiation belt dynamics. The popular way to numerically obtain the L* value follows the recipe described by Roederer [1970], which is, however, slow and computational expensive. This work focuses on a new technique, which can compute the L* value in microseconds without losing much accuracy: artificial neural networks. Since L* is related to the magnetic flux enclosed by a particle drift shell, global magnetic field information needed to trace the drift shell is required. A series of currently popular empirical magnetic field models are applied to create the L* data pool using 1 million data samples which are randomly selected within a solar cycle and within the global magnetosphere. The networks, trained from the above L* data pool, can thereby be used for fairly efficient L* calculation given input parameters valid within the trained temporal and spatial range. Besides the empirical magnetospheric models, a physics-based self-consistent inner magnetosphere model (RAM-SCB) developed at LANL is also utilized to calculate L* values and then to train the L* neural network. This model better predicts the magnetospheric configuration and therefore can significantly improve the L*. The above neural network L* technique will enable, for the first time, comprehensive solar-cycle long studies of radiation belt processes. However, neural networks trained from different magnetic field models can result in different L* values, which could cause mis-interpretation of radiation belt dynamics, such as where the source of the radiation belt charged particle is and which mechanism is dominant in accelerating the particles. Such a fact calls for attention to cautiously choose a magnetospheric field model for the L* calculation.

Mean field methods for cortical network dynamics

DEFF Research Database (Denmark)

Hertz, J.; Lerchner, Alexander; Ahmadi, M.

2004-01-01

We review the use of mean field theory for describing the dynamics of dense, randomly connected cortical circuits. For a simple network of excitatory and inhibitory leaky integrate- and-fire neurons, we can show how the firing irregularity, as measured by the Fano factor, increases...... with the strength of the synapses in the network and with the value to which the membrane potential is reset after a spike. Generalizing the model to include conductance-based synapses gives insight into the connection between the firing statistics and the high- conductance state observed experimentally in visual...

A wireless sensor network design and evaluation for large structural strain field monitoring

International Nuclear Information System (INIS)

Qiu, Zixue; Wu, Jian; Yuan, Shenfang

2011-01-01

Structural strain changes under external environmental or mechanical loads are the main monitoring parameters in structural health monitoring or mechanical property tests. This paper presents a wireless sensor network designed for monitoring large structural strain field variation. First of all, a precision strain sensor node is designed for multi-channel strain gauge signal conditioning and wireless monitoring. In order to establish a synchronous strain data acquisition network, the cluster-star network synchronization method is designed in detail. To verify the functionality of the designed wireless network for strain field monitoring capability, a multi-point network evaluation system is developed for an experimental aluminum plate structure for load variation monitoring. Based on the precision wireless strain nodes, the wireless data acquisition network is deployed to synchronously gather, process and transmit strain gauge signals and monitor results under concentrated loads. This paper shows the efficiency of the wireless sensor network for large structural strain field monitoring

A network approach to the geometric structure of shallow cloud fields

Science.gov (United States)

Glassmeier, F.; Feingold, G.

2017-12-01

The representation of shallow clouds and their radiative impact is one of the largest challenges for global climate models. While the bulk properties of cloud fields, including effects of organization, are a very active area of research, the potential of the geometric arrangement of cloud fields for the development of new parameterizations has hardly been explored. Self-organized patterns are particularly evident in the cellular structure of Stratocumulus (Sc) clouds so readily visible in satellite imagery. Inspired by similar patterns in biology and physics, we approach pattern formation in Sc fields from the perspective of natural cellular networks. Our network analysis is based on large-eddy simulations of open- and closed-cell Sc cases. We find the network structure to be neither random nor characteristic to natural convection. It is independent of macroscopic cloud fields properties like the Sc regime (open vs closed) and its typical length scale (boundary layer height). The latter is a consequence of entropy maximization (Lewis's Law with parameter 0.16). The cellular pattern is on average hexagonal, where non-6 sided cells occur according to a neighbor-number distribution variance of about 2. Reflecting the continuously renewing dynamics of Sc fields, large (many-sided) cells tend to neighbor small (few-sided) cells (Aboav-Weaire Law with parameter 0.9). These macroscopic network properties emerge independent of the Sc regime because the different processes governing the evolution of closed as compared to open cells correspond to topologically equivalent network dynamics. By developing a heuristic model, we show that open and closed cell dynamics can both be mimicked by versions of cell division and cell disappearance and are biased towards the expansion of smaller cells. This model offers for the first time a fundamental and universal explanation for the geometric pattern of Sc clouds. It may contribute to the development of advanced Sc parameterizations

Epidemic spreading in weighted networks: an edge-based mean-field solution.

Science.gov (United States)

Yang, Zimo; Zhou, Tao

2012-05-01

Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

Mean field dynamics of networks of delay-coupled noisy excitable units

Energy Technology Data Exchange (ETDEWEB)

Franović, Igor, E-mail: franovic@ipb.ac.rs [Scientific Computing Laboratory, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade (Serbia); Todorović, Kristina; Burić, Nikola [Department of Physics and Mathematics, Faculty of Pharmacy, University of Belgrade, Vojvode Stepe 450, Belgrade (Serbia); Vasović, Nebojša [Department of Applied Mathematics, Faculty of Mining and Geology, University of Belgrade, PO Box 162, Belgrade (Serbia)

2016-06-08

We use the mean-field approach to analyze the collective dynamics in macroscopic networks of stochastic Fitzhugh-Nagumo units with delayed couplings. The conditions for validity of the two main approximations behind the model, called the Gaussian approximation and the Quasi-independence approximation, are examined. It is shown that the dynamics of the mean-field model may indicate in a self-consistent fashion the parameter domains where the Quasi-independence approximation fails. Apart from a network of globally coupled units, we also consider the paradigmatic setup of two interacting assemblies to demonstrate how our framework may be extended to hierarchical and modular networks. In both cases, the mean-field model can be used to qualitatively analyze the stability of the system, as well as the scenarios for the onset and the suppression of the collective mode. In quantitative terms, the mean-field model is capable of predicting the average oscillation frequency corresponding to the global variables of the exact system.

On Field Size and Success Probability in Network Coding

DEFF Research Database (Denmark)

Geil, Hans Olav; Matsumoto, Ryutaroh; Thomsen, Casper

2008-01-01

Using tools from algebraic geometry and Gröbner basis theory we solve two problems in network coding. First we present a method to determine the smallest field size for which linear network coding is feasible. Second we derive improved estimates on the success probability of random linear network...... coding. These estimates take into account which monomials occur in the support of the determinant of the product of Edmonds matrices. Therefore we finally investigate which monomials can occur in the determinant of the Edmonds matrix....

Hyper-X and Pegasus Launch Vehicle: A Three-Foot Model of the Hypersonic Experimental Research Vehic

Science.gov (United States)

1997-01-01

The configuration of the X-43A Hypersonic Experimental Research Vehicle, or Hyper-X, attached to a Pegasus launch vehicle is displayed in this three-foot-long model at NASA's Dryden Flight Research Center, Edwards, California. Hyper-X, the flight vehicle for which is designated as X-43A, is an experimental flight-research program seeking to demonstrate airframe-integrated, 'air-breathing' engine technologies that promise to increase payload capacity for future vehicles, including hypersonic aircraft (faster than Mach 5) and reusable space launchers. This multiyear program is currently underway at NASA Dryden Flight Research Center, Edwards, California. The Hyper-X schedule calls for its first flight later this year (2000). Hyper-X is a joint program, with Dryden sharing responsibility with NASA's Langley Research Center, Hampton, Virginia. Dryden's primary role is to fly three unpiloted X-43A research vehicles to validate engine technologies and hypersonic design tools as well as the hypersonic test facility at Langley. Langley manages the program and leads the technology development effort. The Hyper-X Program seeks to significantly expand the speed boundaries of air-breathing propulsion by being the first aircraft to demonstrate an airframe-integrated, scramjet-powered free flight. Scramjets (supersonic-combustion ramjets) are ramjet engines in which the airflow through the whole engine remains supersonic. Scramjet technology is challenging because only limited testing can be performed in ground facilities. Long duration, full-scale testing requires flight research. Scramjet engines are air-breathing, capturing their oxygen from the atmosphere. Current spacecraft, such as the Space Shuttle, are rocket powered, so they must carry both fuel and oxygen for propulsion. Scramjet technology-based vehicles need to carry only fuel. By eliminating the need to carry oxygen, future hypersonic vehicles will be able to carry heavier payloads. Another unique aspect of the X-43

Upper critical field of complex superconducting networks in the continuum limit

International Nuclear Information System (INIS)

Santhanam, P.; Chi, C.C.

1988-01-01

We propose a simple method for calculating the superconducting upper critical field of complex periodic two-dimensional networks in the continuum limit. Two specific lattices with space groups P4gm and C2mm are used to demonstrate this approach. We obtain the result that the ratio of the critical field of these networks to that of a uniform film is close to but larger than 2

Pegasus International, Inc. coating removal systems

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-02-01

The Pegasus Coating Removal System (PCRS) was demonstrated at Florida International University (FIU) where it was being evaluated for efficiency and cost. In conjunction with the FIU testing demonstration, a human factors assessment was conducted to assess the hazards and associated safety and health issues of concern for workers utilizing this technology. The PCRS is a chemical paste that is applied to the surface using a brush, roller, or airless sprayer. After the type of PCRS, thickness, and dwell time have been determined, a laminated backed material is placed on top of the chemical paste to slow down the drying process and to provide a mechanism to strip-off the chemical. After the dwell time is reached, the chemical substrate can be removed. Scrapers may be used to break-loose the layers as necessary or to break-loose the layers that are not removed when the laminated paper is picked up. Residue may also be cleaned off of the surface with a damp sponge with an agitating motion, absorbent sponges, or a vacuum, as needed. The paint and removal agent is then placed in drums for disposal at a later time. During the assessment sampling was conducted for organic vapors and general observational techniques were conducted for ergonomics. Recommendations for improved worker safety and health during application and removal of the PCRS include: (1) work practices that reflect avoidance of exposure or reducing the risk of exposure; (2) assuring all PPE and equipment are compatible with the chemicals being used; (3) work practices that reduce the worker`s need to walk on the slippery surface caused by the chemical or the use of special anti-slip soles; (4) careful control of overspray (if a spray application is used); and (5) the use of ergonomically designed long-handled tools to apply and remove the chemical (to alleviate some of the ergonomic concerns).

Delay-tolerant mobile network protocol for rice field monitoring using wireless sensor networks

Science.gov (United States)

Guitton, Alexandre; Andres, Frédéric; Cardoso, Jarbas Lopes; Kawtrakul, Asanee; Barbin, Silvio E.

2015-10-01

The monitoring of rice fields can improve productivity by helping farmers throughout the rice cultivation cycle, on various issues: when to harvest, when to treat the crops against disease, when to increase the water level, how to share observations and decisions made in a collaborative way, etc. In this paper, we propose an architecture to monitor a rice field by a wireless sensor network. Our architecture is based on static sensor nodes forming a disconnected network, and mobile nodes communicating with the sensor nodes in a delay-tolerant manner. The data collected by the static sensor nodes are transmitted to mobile nodes, which in turn transmit them to a gateway, connected to a database, for further analysis. We focus on the related architecture, as well as on the energy-efficient protocols intended to perform the data collection.

Protocol of Magnetic Field Area Network and its Applications

International Nuclear Information System (INIS)

Won, Yunjae; Kang, Shinjae; Lim, Seungok; Kahng, Hyunkook

2012-01-01

The social needs are increasing in the wireless communication technology based on sensors for the monitoring of natural disasters such as avalanche and storm, the management of underground conditions from ground sinking and landslide, the monitoring of pipes, wires buried under the ground, the management of building and bridge, and the monitoring of the pollutions such as soils and water. However, the conventional wireless communication systems based on EM (Electro Magnetic) waves have not supported reliable communication because of large signal strength attenuation around soil, water, and metals. In order to handle this problem, various efforts in the wireless communication area have been conducted. Magnetic Field Area Network (MFAN) supports the reliable communication service without large signal attenuation around water, soil, and metal. Therefore, Magnetic Field Area Network (MFAN) is expected to be one of promising solutions to the limit of the conventional technologies such as Radio Frequency Indentification (RFID) and Wireless Sensor Network (WSN)

Protocol of Magnetic Field Area Network and its Applications

Energy Technology Data Exchange (ETDEWEB)

Won, Yunjae; Kang, Shinjae; Lim, Seungok [Korea Electronics Technology Institute, Seoul (Korea, Republic of); Kahng, Hyunkook [Korea Univ., Seoul (Korea, Republic of)

2012-03-15

The social needs are increasing in the wireless communication technology based on sensors for the monitoring of natural disasters such as avalanche and storm, the management of underground conditions from ground sinking and landslide, the monitoring of pipes, wires buried under the ground, the management of building and bridge, and the monitoring of the pollutions such as soils and water. However, the conventional wireless communication systems based on EM (Electro Magnetic) waves have not supported reliable communication because of large signal strength attenuation around soil, water, and metals. In order to handle this problem, various efforts in the wireless communication area have been conducted. Magnetic Field Area Network (MFAN) supports the reliable communication service without large signal attenuation around water, soil, and metal. Therefore, Magnetic Field Area Network (MFAN) is expected to be one of promising solutions to the limit of the conventional technologies such as Radio Frequency Indentification (RFID) and Wireless Sensor Network (WSN)

Neural attractor network for application in visual field data classification

International Nuclear Information System (INIS)

Fink, Wolfgang

2004-01-01

The purpose was to introduce a novel method for computer-based classification of visual field data derived from perimetric examination, that may act as a ' counsellor', providing an independent 'second opinion' to the diagnosing physician. The classification system consists of a Hopfield-type neural attractor network that obtains its input data from perimetric examination results. An iterative relaxation process determines the states of the neurons dynamically. Therefore, even 'noisy' perimetric output, e.g., early stages of a disease, may eventually be classified correctly according to the predefined idealized visual field defect (scotoma) patterns, stored as attractors of the network, that are found with diseases of the eye, optic nerve and the central nervous system. Preliminary tests of the classification system on real visual field data derived from perimetric examinations have shown a classification success of over 80%. Some of the main advantages of the Hopfield-attractor-network-based approach over feed-forward type neural networks are: (1) network architecture is defined by the classification problem; (2) no training is required to determine the neural coupling strengths; (3) assignment of an auto-diagnosis confidence level is possible by means of an overlap parameter and the Hamming distance. In conclusion, the novel method for computer-based classification of visual field data, presented here, furnishes a valuable first overview and an independent 'second opinion' in judging perimetric examination results, pointing towards a final diagnosis by a physician. It should not be considered a substitute for the diagnosing physician. Thanks to the worldwide accessibility of the Internet, the classification system offers a promising perspective towards modern computer-assisted diagnosis in both medicine and tele-medicine, for example and in particular, with respect to non-ophthalmic clinics or in communities where perimetric expertise is not readily available

Field-effect Flow Control in Polymer Microchannel Networks

Science.gov (United States)

Sniadecki, Nathan; Lee, Cheng S.; Beamesderfer, Mike; DeVoe, Don L.

2003-01-01

A new Bio-MEMS electroosmotic flow (EOF) modulator for plastic microchannel networks has been developed. The EOF modulator uses field-effect flow control (FEFC) to adjust the zeta potential at the Parylene C microchannel wall. By setting a differential EOF pumping rate in two of the three microchannels at a T-intersection with EOF modulators, the induced pressure at the intersection generated pumping in the third, field-free microchannel. The EOF modulators are able to change the magnitude and direction of the pressure pumping by inducing either a negative or positive pressure at the intersection. The flow velocity is tracked by neutralized fluorescent microbeads in the microchannels. The proof-of-concept of the EOF modulator described here may be applied to complex plastic ,microchannel networks where individual microchannel flow rates are addressable by localized induced-pressure pumping.

Classification of networks of automata by dynamical mean field theory

International Nuclear Information System (INIS)

Burda, Z.; Jurkiewicz, J.; Flyvbjerg, H.

1990-01-01

Dynamical mean field theory is used to classify the 2 24 =65,536 different networks of binary automata on a square lattice with nearest neighbour interactions. Application of mean field theory gives 700 different mean field classes, which fall in seven classes of different asymptotic dynamics characterized by fixed points and two-cycles. (orig.)

Focus on the emerging new fields of network physiology and network medicine

Science.gov (United States)

Ivanov, Plamen Ch; Liu, Kang K. L.; Bartsch, Ronny P.

2016-10-01

Despite the vast progress and achievements in systems biology and integrative physiology in the last decades, there is still a significant gap in understanding the mechanisms through which (i) genomic, proteomic and metabolic factors and signaling pathways impact vertical processes across cells, tissues and organs leading to the expression of different disease phenotypes and influence the functional and clinical associations between diseases, and (ii) how diverse physiological systems and organs coordinate their functions over a broad range of space and time scales and horizontally integrate to generate distinct physiologic states at the organism level. Two emerging fields, network medicine and network physiology, aim to address these fundamental questions. Novel concepts and approaches derived from recent advances in network theory, coupled dynamical systems, statistical and computational physics show promise to provide new insights into the complexity of physiological structure and function in health and disease, bridging the genetic and sub-cellular level with inter-cellular interactions and communications among integrated organ systems and sub-systems. These advances form first building blocks in the methodological formalism and theoretical framework necessary to address fundamental problems and challenges in physiology and medicine. This ‘focus on’ issue contains 26 articles representing state-of-the-art contributions covering diverse systems from the sub-cellular to the organism level where physicists have key role in laying the foundations of these new fields.

Cortical information flow in Parkinson's disease: a composite network/field model

Directory of Open Access Journals (Sweden)

Cliff C. Kerr

2013-04-01

Full Text Available The basal ganglia play a crucial role in the execution of movements, as demonstrated by the severe motor deficits that accompany Parkinson's disease (PD. Since motor commands originate in the cortex, an important question is how the basal ganglia influence cortical information flow, and how this influence becomes pathological in PD. To explore this, we developed a composite neuronal network/neural field model. The network model consisted of 4950 spiking neurons, divided into 15 excitatory and inhibitory cell populations in the thalamus and cortex. The field model consisted of the cortex, thalamus, striatum, subthalamic nucleus, and globus pallidus. Both models have been separately validated in previous work. Three field models were used: one with basal ganglia parameters based on data from healthy individuals, one based on data from individuals with PD, and one purely thalamocortical model. Spikes generated by these field models were then used to drive the network model. Compared to the network driven by the healthy model, the PD-driven network had lower firing rates, a shift in spectral power towards lower frequencies, and higher probability of bursting; each of these findings is consistent with empirical data on PD. In the healthy model, we found strong Granger causality in the beta and low gamma bands between cortical layers, but this was largely absent in the PD model. In particular, the reduction in Granger causality from the main "input" layer of the cortex (layer 4 to the main "output" layer (layer 5 was pronounced. This may account for symptoms of PD that seem to reflect deficits in information flow, such as bradykinesia. In general, these results demonstrate that the brain's large-scale oscillatory environment, represented here by the field model, strongly influences the information processing that occurs within its subnetworks. Hence, it may be preferable to drive spiking network models with physiologically realistic inputs rather than

PEGASUS: a preequilibrium and multi-step evaporation code for neutron cross section calculation

Energy Technology Data Exchange (ETDEWEB)

Nakagawa, Tsuneo; Sugi, Teruo [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Iijima, Shungo; Nishigori, Takeo

1999-06-01

The computer code PEGASUS was developed to calculate neutron-induced reaction cross sections on the basis of the closed form exciton model preequilibrium theory and the multi-step evaporation theory. The cross sections and emitted particle spectra are calculated for the compound elastic scattering, (n,{gamma}), (n,n`), (n,p), (n,{alpha}), (n,d), (n,t), (n,{sup 3}He), (n,2n), (n,n`p), (n,n`{alpha}), (n,n`d), (n,n`t), (n,2p) and (n,3n) reactions. The double differential cross sections of emitted particles are also calculated. The calculated results are written on a magnetic disk in the ENDF format. Parameter files and/or systematics formulas are provided for level densities, mass excess, radiation widths and inverse cross sections so that the input data to the code are made minimum. (author)

Mean-field level analysis of epidemics in directed networks

Energy Technology Data Exchange (ETDEWEB)

Wang, Jiazeng [School of Mathematical Sciences, Peking University, Beijing 100871 (China); Liu, Zengrong [Mathematics Department, Shanghai University, Shanghai 200444 (China)], E-mail: wangjiazen@yahoo.com.cn, E-mail: zrongliu@online.sh.cn

2009-09-04

The susceptible-infected-removed spreading model in a directed graph is studied. The mean-field level rate equations are built with the degree-degree connectivity correlation element and the (in, out)-degree distribution. And the outbreak threshold is obtained analytically-it is determined by the combination of connectivity probability and the degree distribution. Furthermore, the methods of calculating the degree-degree correlations in directed networks are presented. The numerical results of the discrete epidemic processes in networks verify our analyses.

Mean-field level analysis of epidemics in directed networks

International Nuclear Information System (INIS)

Wang, Jiazeng; Liu, Zengrong

2009-01-01

The susceptible-infected-removed spreading model in a directed graph is studied. The mean-field level rate equations are built with the degree-degree connectivity correlation element and the (in, out)-degree distribution. And the outbreak threshold is obtained analytically-it is determined by the combination of connectivity probability and the degree distribution. Furthermore, the methods of calculating the degree-degree correlations in directed networks are presented. The numerical results of the discrete epidemic processes in networks verify our analyses.

The challenge of social networking in the field of environment and health.

Science.gov (United States)

van den Hazel, Peter; Keune, Hans; Randall, Scott; Yang, Aileen; Ludlow, David; Bartonova, Alena

2012-06-28

The fields of environment and health are both interdisciplinary and trans-disciplinary, and until recently had little engagement in social networking designed to cross disciplinary boundaries. The EU FP6 project HENVINET aimed to establish integrated social network and networking facilities for multiple stakeholders in environment and health. The underlying assumption is that increased social networking across disciplines and sectors will enhance the quality of both problem knowledge and problem solving, by facilitating interactions. Inter- and trans-disciplinary networks are considered useful for this purpose. This does not mean that such networks are easily organized, as openness to such cooperation and exchange is often difficult to ascertain. Different methods may enhance network building. Using a mixed method approach, a diversity of actions were used in order to investigate the main research question: which kind of social networking activities and structures can best support the objective of enhanced inter- and trans-disciplinary cooperation and exchange in the fields of environment and health. HENVINET applied interviews, a role playing session, a personal response system, a stakeholder workshop and a social networking portal as part of the process of building an interdisciplinary and trans-disciplinary network. The interviews provided support for the specification of requirements for an interdisciplinary and trans-disciplinary network. The role playing session, the personal response system and the stakeholder workshop were assessed as useful tools in forming such network, by increasing the awareness by different disciplines of other's positions. The social networking portal was particularly useful in delivering knowledge, but the role of the scientist in social networking is not yet clear. The main challenge in the field of environment and health is not so much a lack of scientific problem knowledge, but rather the ability to effectively communicate, share

AN/VRC 118 Mid-Tier Networking Vehicular Radio (MNVR) and Joint Enterprise Network Manager (JENM) Early Fielding Report

Science.gov (United States)

2017-01-18

requirements. The Army intends to conduct the MNVR Initial Operational Test and Evaluation ( IOT &E) with the new radio in FY21 to support a fielding decision...improve the commander’s ability to conduct mission command over the MNVR WNW mid-tier network. Network Usage During the 2016 MNVR Operational...its reliability requirement in a loaded network simulating full brigade usage . Based on the results of developmental test, the Army made

A brief review of advances in complex networks of nuclear science and technology field

International Nuclear Information System (INIS)

Fang Jinqing

2010-01-01

A brief review of advances in complex networks of nuclear science and technology field at home and is given and summarized. These complex networks include: nuclear energy weapon network, network centric warfare, beam transport networks, continuum percolation evolving network associated with nuclear reactions, global nuclear power station network, (nuclear) chemistry reaction networks, radiological monitoring and anti-nuclear terror networks, and so on. Some challenge issues and development prospects of network science are pointed out finally. (authors)

Mean field games for cognitive radio networks

KAUST Repository

Tembine, Hamidou

2012-06-01

In this paper we study mobility effect and power saving in cognitive radio networks using mean field games. We consider two types of users: primary and secondary users. When active, each secondary transmitter-receiver uses carrier sensing and is subject to long-term energy constraint. We formulate the interaction between primary user and large number of secondary users as an hierarchical mean field game. In contrast to the classical large-scale approaches based on stochastic geometry, percolation theory and large random matrices, the proposed mean field framework allows one to describe the evolution of the density distribution and the associated performance metrics using coupled partial differential equations. We provide explicit formulas and algorithmic power management for both primary and secondary users. A complete characterization of the optimal distribution of energy and probability of success is given.

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

Science.gov (United States)

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Noisy mean field game model for malware propagation in opportunistic networks

KAUST Repository

Tembine, Hamidou

2012-01-01

In this paper we present analytical mean field techniques that can be used to better understand the behavior of malware propagation in opportunistic large networks. We develop a modeling methodology based on stochastic mean field optimal control that is able to capture many aspects of the problem, especially the impact of the control and heterogeneity of the system on the spreading characteristics of malware. The stochastic large process characterizing the evolution of the total number of infected nodes is examined with a noisy mean field limit and compared to a deterministic one. The stochastic nature of the wireless environment make stochastic approaches more realistic for such types of networks. By introducing control strategies, we show that the fraction of infected nodes can be maintained below some threshold. In contrast to most of the existing results on mean field propagation models which focus on deterministic equations, we show that the mean field limit is stochastic if the second moment of the number of object transitions per time slot is unbounded with the size of the system. This allows us to compare one path of the fraction of infected nodes with the stochastic trajectory of its mean field limit. In order to take into account the heterogeneity of opportunistic networks, the analysis is extended to multiple types of nodes. Our numerical results show that the heterogeneity can help to stabilize the system. We verify the results through simulation showing how to obtain useful approximations in the case of very large systems. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

Non-Inductively Driven Tokamak Plasmas at Near-Unity Toroidal Beta in the Pegasus Toroidal Experiment

Science.gov (United States)

Reusch, Joshua

2017-10-01

A major goal of the spherical tokamak research program is accessing a state of low internal inductance li, high elongation κ, high toroidal and normalized beta (βt and βN) , and low collisionality without solenoidal current drive. A new local helicity injection (LHI) system in the lower divertor region of the ultra-low aspect ratio Pegasus ST provides non-solenoidally driven plasmas that exhibit most of these characteristics. LHI utilizes compact, edge-localized current sources (Ainj 4 cm2, Iinj 8 kA, Vinj 1.5 kV) for plasma startup and sustainment, and can sustain more than 200 kA of plasma current. Plasma growth via LHI is enhanced by a transition from a regime of high kink-like MHD activity to one of reduced MHD activity at higher frequencies and presumably shorter wavelengths. The strong edge current drive provided by LHI results in a hollow current density profile with low li. The low aspect ratio (R0 / a 1.2) of Pegasus allows ready access to high κ and MHD stable operation at very high normalized plasma currents (IN =Ip /aBT> 15). Thomson scattering measurements indicate Te 100 eV and ne 1 ×19 m-3. The impurity Ti evolution is correlated in time with high frequency magnetic fluctuations, implying substantial reconnection ion heating is driven by the applied helicity injection. Doppler spectroscopy indicates Ti >=Te and that the anomalous ion heating scales consistently with two fluid reconnection theory. Taken together, these features provide access to very high βt plasmas. Equilibrium analyses indicate βt up to 100% and βN 6.5 is achieved. At increasingly low BT, the discharge disrupts at the no-wall ideal stability limit. In these high βt discharges, a minimum |B| well forms over 50% of the plasma volume. This unique magnetic configuration may be of interest for testing predictions of stabilizing drift wave turbulence and/or improving energetic particle confinement. This work supported by US DOE Grants DE-FG02-96ER54375 and DE-SC0006928.

Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

DEFF Research Database (Denmark)

Hagen, Espen; Dahmen, David; Stavrinou, Maria L

2016-01-01

on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network......With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical...... and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...

The genesis and evolution of the African Field Epidemiology Network

African Journals Online (AJOL)

The genesis and evolution of the African Field Epidemiology Network. David Mukanga, Mufuta Tshimanga, Frederick Wurapa, David Serwada, George Pariyo, Fred Wabwire-Mangen, Sheba Gitta, Stella Chungong, Murray Trostle, Peter Nsubuga ...

Mean field theory of epidemic spreading with effective contacts on networks

International Nuclear Information System (INIS)

Wu, Qingchu; Chen, Shufang

2015-01-01

We present a general approach to the analysis of the susceptible-infected-susceptible model with effective contacts on networks, where each susceptible node will be infected with a certain probability only for effective contacts. In the network, each node has a given effective contact number. By using the one-vertex heterogenous mean-field (HMF) approximation and the pair HMF approximation, we obtain conditions for epidemic outbreak on degree-uncorrelated networks. Our results suggest that the epidemic threshold is closely related to the effective contact and its distribution. However, when the effective contact is only dependent of node degree, the epidemic threshold can be established by the degree distribution of networks.

Hofstadter's Butterfly and Phase Transition of Checkerboard Superconducting Network in a Magnetic Field

International Nuclear Information System (INIS)

Hou Jingmin; Tian, Li-Jim

2010-01-01

We study the magnetic effect of the checkerboard superconducting wire network. Based on the de Gennes-Alexader theory, we obtain difference equations for superconducting order parameter in the wire network. Through solving these difference equations, we obtain the eigenvalues, linked to the coherence length, as a function of magnetic field. The diagram of eigenvalues shows a fractal structure, being so-called Hofstadter's butterfly. We also calculate and discuss the dependence of the transition temperature of the checkerboard superconducting wire network on the applied magnetic field, which is related to up-edge of the Hofstadter's butterfly spectrum. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure

International Nuclear Information System (INIS)

Yang Xuhua; Sun Bao; Wang Bo; Sun Youxian

2010-01-01

Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper. (general)

Performance and stability limits at near-unity aspect ratio in the Pegasus Toroidal Experiment

International Nuclear Information System (INIS)

Fonck, R.J.

2002-01-01

The Pegasus Toroidal Experiment is a mid-sized extremely-low aspect ratio (A) spherical torus (ST). It has the dual roles of exploring limits of ST behavior as A approaches 1 and studying the physics of ST plasmas in the tokamak-spheromak overlap regime. Major parameters are R 0.25 - 0.45 m, A 1.1 - 1.4, I p ≤ 0.15MA, and B t p =aB t is similar to that observed for NBI-heated START discharges. Achievable plasma current apparently is subject to a 'soft' limit of I p =I t f ≤ 1. Access to higher-current plasmas appears to be restricted by the appearance of large internal MHD activity, including m/n=2/1 and 3/2 modes. Recent experiments have begun to access ideal stability limits, with disruptions observed as q 95 approaches 5, in agreement with numerical predictions. (author)

Mean field approximation for biased diffusion on Japanese inter-firm trading network.

Science.gov (United States)

Watanabe, Hayafumi

2014-01-01

By analysing the financial data of firms across Japan, a nonlinear power law with an exponent of 1.3 was observed between the number of business partners (i.e. the degree of the inter-firm trading network) and sales. In a previous study using numerical simulations, we found that this scaling can be explained by both the money-transport model, where a firm (i.e. customer) distributes money to its out-edges (suppliers) in proportion to the in-degree of destinations, and by the correlations among the Japanese inter-firm trading network. However, in this previous study, we could not specifically identify what types of structure properties (or correlations) of the network determine the 1.3 exponent. In the present study, we more clearly elucidate the relationship between this nonlinear scaling and the network structure by applying mean-field approximation of the diffusion in a complex network to this money-transport model. Using theoretical analysis, we obtained the mean-field solution of the model and found that, in the case of the Japanese firms, the scaling exponent of 1.3 can be determined from the power law of the average degree of the nearest neighbours of the network with an exponent of -0.7.

A stochastic-field description of finite-size spiking neural networks.

Science.gov (United States)

Dumont, Grégory; Payeur, Alexandre; Longtin, André

2017-08-01

Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity-the density of active neurons per unit time-is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks; this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics.

Optimal information transfer in enzymatic networks: A field theoretic formulation

Science.gov (United States)

Samanta, Himadri S.; Hinczewski, Michael; Thirumalai, D.

2017-07-01

Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus [Hinczewski and Thirumalai, Phys. Rev. X 4, 041017 (2014), 10.1103/PhysRevX.4.041017]. We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudointermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudointermediate. Surprisingly, in these examples the minimum error computed using simulations that take nonlinearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second-order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in

Field applications of the channel network model, CHAN3D

International Nuclear Information System (INIS)

Khademi, B.; Gylling, B.; Moreno, L.; Neretnieks, I.

1998-01-01

The Channel Network model and its computer implementation, CHAN3D, was developed to simulate fluid flow and transport of solutes in fractured media. The model has been used to interpret field experiments of flow and transport in small and in large scale. It may also be used for safety assessments of repositories for nuclear and other hazardous wastes. In this case, CHAN3D has been coupled to a compartment model, NUCTRAN, to describe the near field of the repository. The model is based on field observations, which indicate that the flow and solute transport take place in a three-dimensional network of connected channels. The channels have very different properties and they are generated in the model from observed stochastic distributions. This allows us to represent the large heterogeneity of the flow distribution commonly observed in fractured media. Solute transport is modelled considering advection and rock interactions such as matrix diffusion and sorption within the interior of the rock. Objects such as fracture zones, tunnels and release sources can be incorporated in the model

Using a Control System Ethernet Network as a Field Bus

CERN Document Server

De Van, William R; Lawson, Gregory S; Wagner, William H; Wantland, David M; Williams, Ernest

2005-01-01

A major component of a typical accelerator distributed control system (DCS) is a dedicated, large-scale local area communications network (LAN). The SNS EPICS-based control system uses a LAN based on the popular IEEE-802.3 set of standards (Ethernet). Since the control system network infrastructure is available throughout the facility, and since Ethernet-based controllers are readily available, it is tempting to use the control system LAN for "fieldbus" communications to low-level control devices (e.g. vacuum controllers; remote I/O). These devices may or may not be compatible with the high-level DCS protocols. This paper presents some of the benefits and risks of combining high-level DCS communications with low-level "field bus" communications on the same network, and describes measures taken at SNS to promote compatibility between devices connected to the control system network.

Self-sustained firing activities of the cortical network with plastic rules in weak AC electrical fields

International Nuclear Information System (INIS)

Qin Ying-Mei; Wang Jiang; Men Cong; Zhao Jia; Wei Xi-Le; Deng Bin

2012-01-01

Both external and endogenous electrical fields widely exist in the environment of cortical neurons. The effects of a weak alternating current (AC) field on a neural network model with synaptic plasticity are studied. It is found that self-sustained rhythmic firing patterns, which are closely correlated with the cognitive functions, are significantly modified due to the self-organizing of the network in the weak AC field. The activities of the neural networks are affected by the synaptic connection strength, the external stimuli, and so on. In the presence of learning rules, the synaptic connections can be modulated by the external stimuli, which will further enhance the sensitivity of the network to the external signal. The properties of the external AC stimuli can serve as control parameters in modulating the evolution of the neural network. (interdisciplinary physics and related areas of science and technology)

Performance and stability limits at near-unity aspect ratio in the pegasus toroidal experiment

International Nuclear Information System (INIS)

Fonck, R.; Diem, S.; Garstka, G.; Kissick, M.; Lewicki, B.; Ostrander, C.; Probert, P.; Reinke, M.; Sontag, A.; Tritz, K.; Unterberg, E.

2003-01-01

The Pegasus Toroidal Experiment is a mid-sized extremely-low aspect ratio (A) spherical torus (ST). It has the dual roles of exploring limits of ST behavior as A approaches 1 and studying the physics of ST plasmas in the tokamak-spheromak overlap regime. Major parameters are R 0.25 - 0.45 m, A 1.1 - 1.4, I p T 20% have been obtained, and the operational space of beta vs I p /aB T is similar to that observed for NBI-heated START discharges. Achievable plasma current is subject to an apparent limit of I p /I tf ∼ 1. Access to higher-current plasmas appears to be restricted by the appearance of large internal MHD activity, including m/n=2/1 and 3/2 modes. Recent experiments have begun to access ideal stability limits, with disruptions observed as q 95 approaches 5, in agreement with numerical predictions for external kink mode onset. (author)

Project on effects of gas in underground storage facilities for radioactive waste (Pegasus project)

International Nuclear Information System (INIS)

Haijtink, B.; McMenamin, T.

1993-01-01

Whereas the subject of gas generation and gas release from radioactive waste repositories has gained in interest on the international scene, the Commission of the European Communities has increased its research efforts on this issue. In particular, in the fourth five-year R and D programme on management and storage of radioactive waste (1990-94), a framework has been set up in which research efforts on the subject of gas generation and migration, supported by the CEC, are brought together and coordinated. In this project, called Pegasus, about 20 organizations and research institutes are involved. The project covers theoretical and experimental studies of the processes of gas formation and possible gas release from the different waste types, LLW, ILW and HLW, under typical repository conditions in suitable geological formations such as clay, salt and granite. In this report the present status of the various research activities are described and 13 papers have been selected

Quantum dynamics in transverse-field Ising models from classical networks

Directory of Open Access Journals (Sweden)

Markus Schmitt, Markus Heyl

2018-02-01

Full Text Available The efficient representation of quantum many-body states with classical resources is a key challenge in quantum many-body theory. In this work we analytically construct classical networks for the description of the quantum dynamics in transverse-field Ising models that can be solved efficiently using Monte Carlo techniques. Our perturbative construction encodes time-evolved quantum states of spin-1/2 systems in a network of classical spins with local couplings and can be directly generalized to other spin systems and higher spins. Using this construction we compute the transient dynamics in one, two, and three dimensions including local observables, entanglement production, and Loschmidt amplitudes using Monte Carlo algorithms and demonstrate the accuracy of this approach by comparisons to exact results. We include a mapping to equivalent artificial neural networks, which were recently introduced to provide a universal structure for classical network wave functions.

Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

Science.gov (United States)

Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

2018-01-01

This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

Social network analysis of Iranian researchers in the field of violence.

Science.gov (United States)

Salamati, Payman; Soheili, Faramarz

2016-10-01

The social network analysis (SNA) is a paradigm for analyzing structural patterns in social re- lations, testing knowledge sharing process and identifying bottlenecks of information flow. The purpose of this study was to determine the status of research in the fleld of violence in Iran using SNA. Research population included all the papers with at least one Iranian affiliation published in violence fleld indexed in SCIE, PubMed and Scopus databases. The co-word maps, co-authorship network and structural holes were drawn using related software. In the next step, the active authors and some measures of our network including degree centrality (DC), closeness, eigenvector, betweeness, density, diameter, compactness and size of the main component were assessed. Likewise, the trend of the published articles was evaluated based on the number of documents and their citations from 1972 to 2014. Five hundred and seventy one records were obtained. The five main clusters and hot spots were mental health, violence, war, psychiatric disorders and suicide. The co-authorship network was complex, tangled and scale free. The top nine authors with cut point role and top ten active authors were identified. The mean (standard deviation) of normalized DC, closeness, eigenvector and betweeness were 0.449 (0.805), 0.609 (0.214), 2.373 (7.353) and 0.338 (1.122), respectively. The density, diameter and mean compactness of our co-authorship network were 0.0494, 3.955 and 0.125, respectively. The main component consisted of 216 nodes that formed 17% of total size of the network. Both the number of the documents and their citations has increased in the field of violence in the recent years. Although the number of the documents has recently increased in the field of violence, the information flow is slow and there are not many relations among the authors in the network. However, the active authors have ability to influence the flow of knowledge within the network.

An introduction to neural networks surgery, a field of neuromodulation which is based on advances in neural networks science and digitised brain imaging.

Science.gov (United States)

Sakas, D E; Panourias, I G; Simpson, B A

2007-01-01

Operative Neuromodulation is the field of altering electrically or chemically the signal transmission in the nervous system by implanted devices in order to excite, inhibit or tune the activities of neurons or neural networks and produce therapeutic effects. The present article reviews relevant literature on procedures or devices applied either in contact with the cerebral cortex or cranial nerves or in deep sites inside the brain in order to treat various refractory neurological conditions such as: a) chronic pain (facial, somatic, deafferentation, phantom limb), b) movement disorders (Parkinson's disease, dystonia, Tourette syndrome), c) epilepsy, d) psychiatric disease, e) hearing deficits, and f) visual loss. These data indicate that in operative neuromodulation, a new field emerges that is based on neural networks research and on advances in digitised stereometric brain imaging which allow precise localisation of cerebral neural networks and their relay stations; this field can be described as Neural networks surgery because it aims to act extrinsically or intrinsically on neural networks and to alter therapeutically the neural signal transmission with the use of implantable electrical or electronic devices. The authors also review neurotechnology literature relevant to neuroengineering, nanotechnologies, brain computer interfaces, hybrid cultured probes, neuromimetics, neuroinformatics, neurocomputation, and computational neuromodulation; the latter field is dedicated to the study of the biophysical and mathematical characteristics of electrochemical neuromodulation. The article also brings forward particularly interesting lines of research such as the carbon nanofibers electrode arrays for simultaneous electrochemical recording and stimulation, closed-loop systems for responsive neuromodulation, and the intracortical electrodes for restoring hearing or vision. The present review of cerebral neuromodulatory procedures highlights the transition from the

Field effect control of electro-osmotic flow in microfluidic networks

NARCIS (Netherlands)

van der Wouden, E.J.

2006-01-01

This thesis describes the development of a Field Effect Flow Control (FEFC) system for the control of Electro Osmotic Flow (EOF) in microfluidic networks. For this several aspects of FEFC have been reviewed and a process to fabricate microfluidic channels with integrated electrodes has been

Field-theoretic approach to fluctuation effects in neural networks

International Nuclear Information System (INIS)

Buice, Michael A.; Cowan, Jack D.

2007-01-01

A well-defined stochastic theory for neural activity, which permits the calculation of arbitrary statistical moments and equations governing them, is a potentially valuable tool for theoretical neuroscience. We produce such a theory by analyzing the dynamics of neural activity using field theoretic methods for nonequilibrium statistical processes. Assuming that neural network activity is Markovian, we construct the effective spike model, which describes both neural fluctuations and response. This analysis leads to a systematic expansion of corrections to mean field theory, which for the effective spike model is a simple version of the Wilson-Cowan equation. We argue that neural activity governed by this model exhibits a dynamical phase transition which is in the universality class of directed percolation. More general models (which may incorporate refractoriness) can exhibit other universality classes, such as dynamic isotropic percolation. Because of the extremely high connectivity in typical networks, it is expected that higher-order terms in the systematic expansion are small for experimentally accessible measurements, and thus, consistent with measurements in neocortical slice preparations, we expect mean field exponents for the transition. We provide a quantitative criterion for the relative magnitude of each term in the systematic expansion, analogous to the Ginsburg criterion. Experimental identification of dynamic universality classes in vivo is an outstanding and important question for neuroscience

Workshop on Thermal Field Theory to Neural Networks

CERN Document Server

Veneziano, Gabriele; Aurenche, Patrick

1996-01-01

Tanguy Altherr was a Fellow in the Theory Division at CERN, on leave from LAPP (CNRS) Annecy. At the time of his accidental death in July 1994, he was only 31.A meeting was organized at CERN, covering the various aspects of his scientific interests: thermal field theory and its applications to hot or dense media, neural networks and its applications to high energy data analysis. Speakers were among his closest collaborators and friends.

Robust segmentation of medical images using competitive hop field neural network as a clustering tool

International Nuclear Information System (INIS)

Golparvar Roozbahani, R.; Ghassemian, M. H.; Sharafat, A. R.

2001-01-01

This paper presents the application of competitive Hop field neural network for medical images segmentation. Our proposed approach consists of Two steps: 1) translating segmentation of the given medical image into an optimization problem, and 2) solving this problem by a version of Hop field network known as competitive Hop field neural network. Segmentation is considered as a clustering problem and its validity criterion is based on both intra set distance and inter set distance. The algorithm proposed in this paper is based on gray level features only. This leads to near optimal solutions if both intra set distance and inter set distance are considered at the same time. If only one of these distances is considered, the result of segmentation process by competitive Hop field neural network will be far from optimal solution and incorrect even for very simple cases. Furthermore, sometimes the algorithm receives at unacceptable states. Both these problems may be solved by contributing both in tera distance and inter distances in the segmentation (optimization) process. The performance of the proposed algorithm is tested on both phantom and real medical images. The promising results and the robustness of algorithm to system noises show near optimal solutions

Mean-field approach to evolving spatial networks, with an application to osteocyte network formation

Science.gov (United States)

Taylor-King, Jake P.; Basanta, David; Chapman, S. Jonathan; Porter, Mason A.

2017-07-01

We consider evolving networks in which each node can have various associated properties (a state) in addition to those that arise from network structure. For example, each node can have a spatial location and a velocity, or it can have some more abstract internal property that describes something like a social trait. Edges between nodes are created and destroyed, and new nodes enter the system. We introduce a "local state degree distribution" (LSDD) as the degree distribution at a particular point in state space. We then make a mean-field assumption and thereby derive an integro-partial differential equation that is satisfied by the LSDD. We perform numerical experiments and find good agreement between solutions of the integro-differential equation and the LSDD from stochastic simulations of the full model. To illustrate our theory, we apply it to a simple model for osteocyte network formation within bones, with a view to understanding changes that may take place during cancer. Our results suggest that increased rates of differentiation lead to higher densities of osteocytes, but with a smaller number of dendrites. To help provide biological context, we also include an introduction to osteocytes, the formation of osteocyte networks, and the role of osteocytes in bone metastasis.

Mean-field modeling approach for understanding epidemic dynamics in interconnected networks

International Nuclear Information System (INIS)

Zhu, Guanghu; Fu, Xinchu; Tang, Qinggan; Li, Kezan

2015-01-01

Modern systems (e.g., social, communicant, biological networks) are increasingly interconnected each other formed as ‘networks of networks’. Such complex systems usually possess inconsistent topologies and permit agents distributed in different subnetworks to interact directly/indirectly. Corresponding dynamics phenomena, such as the transmission of information, power, computer virus and disease, would exhibit complicated and heterogeneous tempo-spatial patterns. In this paper, we focus on the scenario of epidemic spreading in interconnected networks. We intend to provide a typical mean-field modeling framework to describe the time-evolution dynamics, and offer some mathematical skills to study the spreading threshold and the global stability of the model. Integrating the research with numerical analysis, we are able to quantify the effects of networks structure and epidemiology parameters on the transmission dynamics. Interestingly, we find that the diffusion transition in the whole network is governed by a unique threshold, which mainly depends on the most heterogenous connection patterns of network substructures. Further, the dynamics is highly sensitive to the critical values of cross infectivity with switchable phases.

Radiofrequency Field Distribution Assessment in Indoor Areas Covered by Wireless Local Area Network

Directory of Open Access Journals (Sweden)

HELBET, R.

2009-02-01

Full Text Available Electromagnetic environment becomes day by day more congested. Radio communication systems in the short range are now part of everyday life, and there is a need to also assess the pollution level due to their emission if we take into account human health and protection. There is consistent scientific evidence that environmental electromagnetic field may cause undesirable biological effects or even health hazards. Present paper aims at giving a view on exposure level due to wireless local area networks (WLAN emission solely, as part of environmental radiofrequency pollution. Highly accurate measurements were made indoor by using a frequency-selective measurement system and identifying the correct settings for an error-minimum assessment. We focused on analysis of the electric flux density distribution inside a room, in the far field of the emitting antennas, in case of a single network communication channel. We analyze the influence the network configuration parameters have on the field level. Distance from the source and traffic rate are also important parameters that affect the exposure level. Our measurements indicate that in the immediate vicinity of the WLAN stations the average field may reach as much as 13% from the present accepted reference levels given in the human exposure standards.

Quantum communication network utilizing quadripartite entangled states of optical field

International Nuclear Information System (INIS)

Shen Heng; Su Xiaolong; Jia Xiaojun; Xie Changde

2009-01-01

We propose two types of quantum dense coding communication networks with optical continuous variables, in which a quadripartite entangled state of the optical field with totally three-party correlations of quadrature amplitudes is utilized. In the networks, the exchange of information between any two participants can be manipulated by one or two of the remaining participants. The channel capacities for a variety of communication protocols are numerically calculated. Due to the fact that the quadripartite entangled states applied in the communication systems have been successfully prepared already in the laboratory, the proposed schemes are experimentally accessible at present.

Chimeralike states in networks of bistable time-delayed feedback oscillators coupled via the mean field.

Science.gov (United States)

Ponomarenko, V I; Kulminskiy, D D; Prokhorov, M D

2017-08-01

We study the collective dynamics of oscillators in a network of identical bistable time-delayed feedback systems globally coupled via the mean field. The influence of delay and inertial properties of the mean field on the collective behavior of globally coupled oscillators is investigated. A variety of oscillation regimes in the network results from the presence of bistable states with substantially different frequencies in coupled oscillators. In the physical experiment and numerical simulation we demonstrate the existence of chimeralike states, in which some of the oscillators in the network exhibit synchronous oscillations, while all other oscillators remain asynchronous.

Shortwave surface radiation network for observing small-scale cloud inhomogeneity fields

Science.gov (United States)

Lakshmi Madhavan, Bomidi; Kalisch, John; Macke, Andreas

2016-03-01

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of 99 silicon photodiode pyranometers was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. In this paper, we provide the details of this unique setup of the pyranometer network, data processing, quality control, and uncertainty assessment under variable conditions. Some exemplary days with clear, broken cloudy, and overcast skies were explored to assess the spatiotemporal observations from the network along with other collocated radiation and sky imager measurements available during the HOPE period.

How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

Science.gov (United States)

Grabska-Barwińska, Agnieszka; Latham, Peter E

2014-06-01

We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.

Noisy mean field game model for malware propagation in opportunistic networks

KAUST Repository

Tembine, Hamidou; Vilanova, Pedro; Debbah, Mé roú ane

2012-01-01

nodes is examined with a noisy mean field limit and compared to a deterministic one. The stochastic nature of the wireless environment make stochastic approaches more realistic for such types of networks. By introducing control strategies, we show

Field and long-term demonstration of a wide area quantum key distribution network.

Science.gov (United States)

Wang, Shuang; Chen, Wei; Yin, Zhen-Qiang; Li, Hong-Wei; He, De-Yong; Li, Yu-Hu; Zhou, Zheng; Song, Xiao-Tian; Li, Fang-Yi; Wang, Dong; Chen, Hua; Han, Yun-Guang; Huang, Jing-Zheng; Guo, Jun-Fu; Hao, Peng-Lei; Li, Mo; Zhang, Chun-Mei; Liu, Dong; Liang, Wen-Ye; Miao, Chun-Hua; Wu, Ping; Guo, Guang-Can; Han, Zheng-Fu

2014-09-08

A wide area quantum key distribution (QKD) network deployed on communication infrastructures provided by China Mobile Ltd. is demonstrated. Three cities and two metropolitan area QKD networks were linked up to form the Hefei-Chaohu-Wuhu wide area QKD network with over 150 kilometers coverage area, in which Hefei metropolitan area QKD network was a typical full-mesh core network to offer all-to-all interconnections, and Wuhu metropolitan area QKD network was a representative quantum access network with point-to-multipoint configuration. The whole wide area QKD network ran for more than 5000 hours, from 21 December 2011 to 19 July 2012, and part of the network stopped until last December. To adapt to the complex and volatile field environment, the Faraday-Michelson QKD system with several stability measures was adopted when we designed QKD devices. Through standardized design of QKD devices, resolution of symmetry problem of QKD devices, and seamless switching in dynamic QKD network, we realized the effective integration between point-to-point QKD techniques and networking schemes.

Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

Science.gov (United States)

La, Hung Manh; Sheng, Weihua

2013-04-01

In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

Magnetic fields in a residential neighbourhood by network analysis and field calculation

International Nuclear Information System (INIS)

Mader, D.L.

1992-01-01

A magnetic field research facility has been used for validation of a method to compute 60-Hz magnetic fields in a residential neighbourhood. Network analysis is used to solve for currents in a mathematical model of the electric power distribution system including grounding conductors and metallic water supply pipes. Then, magnetic fields are calculated using the currents and the locations of all conductors. The critical role of joint resistance was highlighted by this study as follows. With initial estimates of resistances in the model, a fitting algorithm was able to obtain excellent agreement between the model and measurements, and provide confidence in its predictive capability. Simulations are then done to illustrate the effects of a poor joint, multiple unbalanced loads, heavy balanced loads, a heavy feeder line going through the neighbourhood, injection of current into the local neutral from an adjacent neighbourhood, use of plastic water pipes instead of metal, wet soil, increasing the distance from the power line, changing from twisted wires to an open secondary bus, and primary current loops caused by poor joints in the interconnected system neutral. 8 refs., 24 figs., 8 tabs

Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

Science.gov (United States)

Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

2016-12-01

With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

The Channel Network model and field applications

International Nuclear Information System (INIS)

Khademi, B.; Moreno, L.; Neretnieks, I.

1999-01-01

The Channel Network model describes the fluid flow and solute transport in fractured media. The model is based on field observations, which indicate that flow and transport take place in a three-dimensional network of connected channels. The channels are generated in the model from observed stochastic distributions and solute transport is modeled taking into account advection and rock interactions, such as matrix diffusion and sorption within the rock. The most important site-specific data for the Channel Network model are the conductance distribution of the channels and the flow-wetted surface. The latter is the surface area of the rock in contact with the flowing water. These parameters may be estimated from hydraulic measurements. For the Aespoe site, several borehole data sets are available, where a packer distance of 3 meters was used. Numerical experiments were performed in order to study the uncertainties in the determination of the flow-wetted surface and conductance distribution. Synthetic data were generated along a borehole and hydraulic tests with different packer distances were simulated. The model has previously been used to study the Long-term Pumping and Tracer Test (LPT2) carried out in the Aespoe Hard Rock Laboratory (HRL) in Sweden, where the distance travelled by the tracers was of the order hundreds of meters. Recently, the model has been used to simulate the tracer tests performed in the TRUE experiment at HRL, with travel distance of the order of tens of meters. Several tracer tests with non-sorbing and sorbing species have been performed

Reconstruction of coupling architecture of neural field networks from vector time series

Science.gov (United States)

Sysoev, Ilya V.; Ponomarenko, Vladimir I.; Pikovsky, Arkady

2018-04-01

We propose a method of reconstruction of the network coupling matrix for a basic voltage-model of the neural field dynamics. Assuming that the multivariate time series of observations from all nodes are available, we describe a technique to find coupling constants which is unbiased in the limit of long observations. Furthermore, the method is generalized for reconstruction of networks with time-delayed coupling, including the reconstruction of unknown time delays. The approach is compared with other recently proposed techniques.

Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks

Science.gov (United States)

Gul, M. Shahzeb Khan; Gunturk, Bahadir K.

2018-05-01

Light field imaging extends the traditional photography by capturing both spatial and angular distribution of light, which enables new capabilities, including post-capture refocusing, post-capture aperture control, and depth estimation from a single shot. Micro-lens array (MLA) based light field cameras offer a cost-effective approach to capture light field. A major drawback of MLA based light field cameras is low spatial resolution, which is due to the fact that a single image sensor is shared to capture both spatial and angular information. In this paper, we present a learning based light field enhancement approach. Both spatial and angular resolution of captured light field is enhanced using convolutional neural networks. The proposed method is tested with real light field data captured with a Lytro light field camera, clearly demonstrating spatial and angular resolution improvement.

A network of spiking neurons that can represent interval timing: mean field analysis.

Science.gov (United States)

Gavornik, Jeffrey P; Shouval, Harel Z

2011-04-01

Despite the vital importance of our ability to accurately process and encode temporal information, the underlying neural mechanisms are largely unknown. We have previously described a theoretical framework that explains how temporal representations, similar to those reported in the visual cortex, can form in locally recurrent cortical networks as a function of reward modulated synaptic plasticity. This framework allows networks of both linear and spiking neurons to learn the temporal interval between a stimulus and paired reward signal presented during training. Here we use a mean field approach to analyze the dynamics of non-linear stochastic spiking neurons in a network trained to encode specific time intervals. This analysis explains how recurrent excitatory feedback allows a network structure to encode temporal representations.

Low and High-Frequency Field Potentials of Cortical Networks ...

Science.gov (United States)

Neural networks grown on microelectrode arrays (MEAs) have become an important, high content in vitro assay for assessing neuronal function. MEA experiments typically examine high- frequency (HF) (>200 Hz) spikes, and bursts which can be used to discriminate between different pharmacological agents/chemicals. However, normal brain activity is additionally composed of integrated low-frequency (0.5-100 Hz) field potentials (LFPs) which are filtered out of MEA recordings. The objective of this study was to characterize the relationship between HF and LFP neural network signals, and to assess the relative sensitivity of LFPs to selected neurotoxicants. Rat primary cortical cultures were grown on glass, single-well MEA chips. Spontaneous activity was sampled at 25 kHz and recorded (5 min) (Multi-Channel Systems) from mature networks (14 days in vitro). HF (spike, mean firing rate, MFR) and LF (power spectrum, amplitude) components were extracted from each network and served as its baseline (BL). Next, each chip was treated with either 1) a positive control, bicuculline (BIC, 25μM) or domoic acid (DA, 0.3μM), 2) or a negative control, acetaminophen (ACE, 100μM) or glyphosate (GLY, 100μM), 3) a solvent control (H2O or DMSO:EtOH), or 4) a neurotoxicant, (carbaryl, CAR 5, 30μM ; lindane, LIN 1, 10μM; permethrin, PERM 25, 50μM; triadimefon, TRI 5, 65μM). Post treatment, 5 mins of spontaneous activity was recorded and analyzed. As expected posit

Vector network analyzer ferromagnetic resonance spectrometer with field differential detection

Science.gov (United States)

Tamaru, S.; Tsunegi, S.; Kubota, H.; Yuasa, S.

2018-05-01

This work presents a vector network analyzer ferromagnetic resonance (VNA-FMR) spectrometer with field differential detection. This technique differentiates the S-parameter by applying a small binary modulation field in addition to the DC bias field to the sample. By setting the modulation frequency sufficiently high, slow sensitivity fluctuations of the VNA, i.e., low-frequency components of the trace noise, which limit the signal-to-noise ratio of the conventional VNA-FMR spectrometer, can be effectively removed, resulting in a very clean FMR signal. This paper presents the details of the hardware implementation and measurement sequence as well as the data processing and analysis algorithms tailored for the FMR spectrum obtained with this technique. Because the VNA measures a complex S-parameter, it is possible to estimate the Gilbert damping parameter from the slope of the phase variation of the S-parameter with respect to the bias field. We show that this algorithm is more robust against noise than the conventional algorithm based on the linewidth.

Exploring the field of public construction clients by a graphical network analysis

OpenAIRE

Eisma, P.R.; Volker, L.

2014-01-01

Because public construction clients form the majority of construction clients and procure over 40% of the construction output in most countries, they are important actors in the construction industry. Yet, the field of research on clients is still underdeveloped. In order to identify the research gaps in this field, a graphical network analysis of existing literature is performed. The analysis is based on a query executed in the scientific database Scopus resulting in around 3,300 publication...

Strain on field effect transistors with single–walled–carbon nanotube network on flexible substrate

Energy Technology Data Exchange (ETDEWEB)

Kim, T. G. [Samsung Advanced Institute of Technology, Research center for Time-domain Nano-functional Device, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Department of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713 (Korea, Republic of); Kim, U. J.; Lee, E. H. [Samsung Advanced Institute of Technology, Frontier Research Laboratory, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Hwang, J. S. [School of Advanced Materials Science and Engineering, SKKU Advanced Institute of Nanotechnology, Sungkyunkwan University, Suwon, Gyeonggi 440-746 (Korea, Republic of); Hwang, S. W., E-mail: swnano.hwang@samsung.com, E-mail: sangsig@korea.ac.kr [Samsung Advanced Institute of Technology, Research center for Time-domain Nano-functional Device, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Samsung Advanced Institute of Technology, Frontier Research Laboratory, Giheung, Yong-In, Gyeonggi 446-712 (Korea, Republic of); Kim, S., E-mail: swnano.hwang@samsung.com, E-mail: sangsig@korea.ac.kr [Department of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713 (Korea, Republic of)

2013-12-07

We have systematically analyzed the effect of strain on the electrical properties of flexible field effect transistors with a single-walled carbon nanotube (SWCNT) network on a polyethersulfone substrate. The strain was applied and estimated at the microscopic scale (<1 μm) by using scanning electron microscope (SEM) equipped with indigenously designed special bending jig. Interestingly, the strain estimated at the microscopic scale was found to be significantly different from the strain calculated at the macroscopic scale (centimeter-scale), by a factor of up to 4. Further in-depth analysis using SEM indicated that the significant difference in strain, obtained from two different measurement scales (microscale and macroscale), could be attributed to the formation of cracks and tears in the SWCNT network, or at the junction of SWCNT network and electrode during the strain process. Due to this irreversible morphological change, the electrical properties, such as on current level and field effect mobility, lowered by 14.3% and 4.6%, respectively.

A computational fluid dynamics simulation of the hypersonic flight of the Pegasus(TM) vehicle using an artificial viscosity model and a nonlinear filtering method. M.S. Thesis

Science.gov (United States)

Mendoza, John Cadiz

1995-01-01

The computational fluid dynamics code, PARC3D, is tested to see if its use of non-physical artificial dissipation affects the accuracy of its results. This is accomplished by simulating a shock-laminar boundary layer interaction and several hypersonic flight conditions of the Pegasus(TM) launch vehicle using full artificial dissipation, low artificial dissipation, and the Engquist filter. Before the filter is applied to the PARC3D code, it is validated in one-dimensional and two-dimensional form in a MacCormack scheme against the Riemann and convergent duct problem. For this explicit scheme, the filter shows great improvements in accuracy and computational time as opposed to the nonfiltered solutions. However, for the implicit PARC3D code it is found that the best estimate of the Pegasus experimental heat fluxes and surface pressures is the simulation utilizing low artificial dissipation and no filter. The filter does improve accuracy over the artificially dissipative case but at a computational expense greater than that achieved by the low artificial dissipation case which has no computational time penalty and shows better results. For the shock-boundary layer simulation, the filter does well in terms of accuracy for a strong impingement shock but not as well for weaker shock strengths. Furthermore, for the latter problem the filter reduces the required computational time to convergence by 18.7 percent.

Network as transconcept: elements for a conceptual demarcation in the field of public health.

Science.gov (United States)

Amaral, Carlos Eduardo Menezes; Bosi, Maria Lúcia Magalhães

2016-08-22

The main proposal to set up an articulated mode of operation of health services has been the concept of network, which has been appropriated in different ways in the field of public health, as it is used in other disciplinary fields or even taking it from common sense. Amid the diversity of uses and concepts, we recognize the need for rigorous conceptual demarcation about networks in the field of health. Such concern aims to preserve the strategic potential of this concept in the research and planning in the field, overcoming uncertainties and distortions still observed in its discourse-analytic circulation in public health. To this end, we will introduce the current uses of network in different disciplinary fields, emphasizing dialogues with the field of public health. With this, we intend to stimulate discussions about the development of empirical dimensions and analytical models that may allow us to understand the processes produced within and around health networks. RESUMO A principal proposta para configurar um modo articulado de funcionamento dos serviços de saúde tem sido o conceito de rede, que vem sendo apropriado de diferentes formas no campo da saúde coletiva, conforme seu emprego em outros campos disciplinares ou mesmo tomando-o do senso comum. Em meio à pluralidade de usos e concepções, reconhecemos a necessidade de rigorosa demarcação conceitual acerca de redes no campo da saúde. Tal preocupação visa a preservar o potencial estratégico desse conceito na investigação e planificação no campo, superando precariedades e distorções ainda observadas em sua circulação discursivo-analítica na saúde coletiva. Para tanto, apresentaremos os usos correntes de rede em diferentes campos disciplinares, destacando interlocuções com o campo da saúde coletiva. Com isso, pretendemos estimular o debate acerca do desenvolvimento de dimensões empíricas e modelos de análise que permitam compreender os processos produzidos no interior e ao redor

Mean-field analysis of orientation selectivity in inhibition-dominated networks of spiking neurons.

Science.gov (United States)

Sadeh, Sadra; Cardanobile, Stefano; Rotter, Stefan

2014-01-01

Mechanisms underlying the emergence of orientation selectivity in the primary visual cortex are highly debated. Here we study the contribution of inhibition-dominated random recurrent networks to orientation selectivity, and more generally to sensory processing. By simulating and analyzing large-scale networks of spiking neurons, we investigate tuning amplification and contrast invariance of orientation selectivity in these networks. In particular, we show how selective attenuation of the common mode and amplification of the modulation component take place in these networks. Selective attenuation of the baseline, which is governed by the exceptional eigenvalue of the connectivity matrix, removes the unspecific, redundant signal component and ensures the invariance of selectivity across different contrasts. Selective amplification of modulation, which is governed by the operating regime of the network and depends on the strength of coupling, amplifies the informative signal component and thus increases the signal-to-noise ratio. Here, we perform a mean-field analysis which accounts for this process.

Group field theory and tensor networks: towards a Ryu–Takayanagi formula in full quantum gravity

Science.gov (United States)

Chirco, Goffredo; Oriti, Daniele; Zhang, Mingyi

2018-06-01

We establish a dictionary between group field theory (thus, spin networks and random tensors) states and generalized random tensor networks. Then, we use this dictionary to compute the Rényi entropy of such states and recover the Ryu–Takayanagi formula, in two different cases corresponding to two different truncations/approximations, suggested by the established correspondence.

Modeling Geoelectric Fields and Geomagnetically Induced Currents Around New Zealand to Explore GIC in the South Island's Electrical Transmission Network

Science.gov (United States)

Divett, T.; Ingham, M.; Beggan, C. D.; Richardson, G. S.; Rodger, C. J.; Thomson, A. W. P.; Dalzell, M.

2017-10-01

Transformers in New Zealand's South Island electrical transmission network have been impacted by geomagnetically induced currents (GIC) during geomagnetic storms. We explore the impact of GIC on this network by developing a thin-sheet conductance (TSC) model for the region, a geoelectric field model, and a GIC network model. (The TSC is composed of a thin-sheet conductance map with underlying layered resistivity structure.) Using modeling approaches that have been successfully used in the United Kingdom and Ireland, we applied a thin-sheet model to calculate the electric field as a function of magnetic field and ground conductance. We developed a TSC model based on magnetotelluric surveys, geology, and bathymetry, modified to account for offshore sediments. Using this representation, the thin sheet model gave good agreement with measured impedance vectors. Driven by a spatially uniform magnetic field variation, the thin-sheet model results in electric fields dominated by the ocean-land boundary with effects due to the deep ocean and steep terrain. There is a strong tendency for the electric field to align northwest-southeast, irrespective of the direction of the magnetic field. Applying this electric field to a GIC network model, we show that modeled GIC are dominated by northwest-southeast transmission lines rather than east-west lines usually assumed to dominate.

Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

Science.gov (United States)

Cuntz, Hermann; Lansner, Anders; Panzeri, Stefano; Einevoll, Gaute T.

2015-01-01

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP). Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best “LFP proxy”, we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents) with “ground-truth” LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D) network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo. PMID:26657024

Computing the Local Field Potential (LFP from Integrate-and-Fire Network Models.

Directory of Open Access Journals (Sweden)

Alberto Mazzoni

2015-12-01

Full Text Available Leaky integrate-and-fire (LIF network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local field potential (LFP. Given that LFPs are generated by spatially separated currents across the neuronal membrane, they cannot be computed directly from quantities defined in models of point-like LIF neurons. Here, we explore the best approximation for predicting the LFP based on standard output from point-neuron LIF networks. To search for this best "LFP proxy", we compared LFP predictions from candidate proxies based on LIF network output (e.g, firing rates, membrane potentials, synaptic currents with "ground-truth" LFP obtained when the LIF network synaptic input currents were injected into an analogous three-dimensional (3D network model of multi-compartmental neurons with realistic morphology, spatial distributions of somata and synapses. We found that a specific fixed linear combination of the LIF synaptic currents provided an accurate LFP proxy, accounting for most of the variance of the LFP time course observed in the 3D network for all recording locations. This proxy performed well over a broad set of conditions, including substantial variations of the neuronal morphologies. Our results provide a simple formula for estimating the time course of the LFP from LIF network simulations in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo.

PlumpyField – Network of local producers of RUF (contributed paper)

International Nuclear Information System (INIS)

Belete, Hilina

2014-01-01

Full text: Expanding coverage for the 35 million children in the world suffering from Moderate Acute Malnutrition (MAM) will require sustainably scaling up regional procurement of lipid-based RUSF products. Momentum is now building to achieve this aim through ten local ready-to-use food (RUF) producers in the PlumpyField Network, which was established by the French company Nutriset in 2005. These independently-owned factories, located in Sub-Saharan Africa, Asia, and the Caribbean, currently produce one-third of the world’s RUF supply. Overcoming substantial obstacles, they have achieved the same high quality standards of producers in Europe and the U.S., with increasingly competitive pricing. Being part of a mutually supportive and interactive network of RUF producers from around the world provides unique learning and partnership opportunities, from sharing insights on peanut supply chain development, increasingly complex quality challenges, to pooled procurement. This network system has been instrumental to the success of local production for the members of the PlumpyField Network. Historically, local producers achieving economies of scale and reliable local and international supply chains (i.e. for peanuts, oil, sugar, milk etc.) takes several years, making the cost of locally-procured products more expensive in the short term. However, there are numerous positive outcomes and externalities that cannot be ignored, such as decreased lead times (especially crucial to reach children with acute malnutrition), lower shipping costs, economic development, and maturation of the food processing and microbiological laboratory sectors. UNICEF and WFP have become leaders in local and regional procurement as they continually optimize their strategies to best meet global needs. Local production is often an important stimulant of public-private partnerships, including procurement of RUF by local governments for government-run acute malnutrition programs, furthering

Fulcrum Network Codes

DEFF Research Database (Denmark)

2015-01-01

Fulcrum network codes, which are a network coding framework, achieve three objectives: (i) to reduce the overhead per coded packet to almost 1 bit per source packet; (ii) to operate the network using only low field size operations at intermediate nodes, dramatically reducing complexity...... in the network; and (iii) to deliver an end-to-end performance that is close to that of a high field size network coding system for high-end receivers while simultaneously catering to low-end ones that can only decode in a lower field size. Sources may encode using a high field size expansion to increase...... the number of dimensions seen by the network using a linear mapping. Receivers can tradeoff computational effort with network delay, decoding in the high field size, the low field size, or a combination thereof....

Field Trial of 40 Gb/s Optical Transport Network using Open WDM Interfaces

DEFF Research Database (Denmark)

Fagertun, Anna Manolova; Ruepp, Sarah Renée; Petersen, Martin Nordal

2013-01-01

An experimental field-trail deployment of a 40Gb/s open WDM interface in an operational network is presented, in cross-carrier interconnection scenario. Practical challenges of integration and performance measures for both native and alien channels are outlined....

Quantum dot-based local field imaging reveals plasmon-based interferometric logic in silver nanowire networks.

Science.gov (United States)

Wei, Hong; Li, Zhipeng; Tian, Xiaorui; Wang, Zhuoxian; Cong, Fengzi; Liu, Ning; Zhang, Shunping; Nordlander, Peter; Halas, Naomi J; Xu, Hongxing

2011-02-09

We show that the local electric field distribution of propagating plasmons along silver nanowires can be imaged by coating the nanowires with a layer of quantum dots, held off the surface of the nanowire by a nanoscale dielectric spacer layer. In simple networks of silver nanowires with two optical inputs, control of the optical polarization and phase of the input fields directs the guided waves to a specific nanowire output. The QD-luminescent images of these structures reveal that a complete family of phase-dependent, interferometric logic functions can be performed on these simple networks. These results show the potential for plasmonic waveguides to support compact interferometric logic operations.

Random field Ising chain and neutral networks with synchronous dynamics

International Nuclear Information System (INIS)

Skantzos, N.S.; Coolen, A.C.C.

2001-01-01

We first present an exact solution of the one-dimensional random-field Ising model in which spin-updates are made fully synchronously, i.e. in parallel (in contrast to the more conventional Glauber-type sequential rules). We find transitions where the support of local observables turns from a continuous interval into a Cantor set and we show that synchronous and sequential random-field models lead asymptotically to the same physical states. We then proceed to an application of these techniques to recurrent neural networks where 1D short-range interactions are combined with infinite-range ones. Due to the competing interactions these models exhibit phase diagrams with first-order transitions and regions with multiple locally stable solutions for the macroscopic order parameters

Local Helicity Injection Systems for Non-solenoidal Startup in the PEGASUS Toroidal Experiment

Science.gov (United States)

Perry, J. M.; Barr, J. L.; Bongard, M. W.; Fonck, R. J.; Hinson, E. T.; Lewicki, B. T.; Redd, A. J.

2013-10-01

Local helicity injection is being developed in the PEGASUS Toroidal Experiment for non-solenoidal startup in spherical tokamaks. The effective loop voltage due to helicity injection scales with the area of the injectors, requiring the development of electron current injectors with areas much larger than the 2 cm2 plasma arc injectors used to date. Solid and gas-effused metallic electrodes were found to be unusable due to reduced injector area utilization from localized cathode spots and narrow operational regimes. An integrated array of 8 compact plasma arc sources is thus being developed for high current startup. It employs two monolithic power systems, for the plasma arc sources and the bias current extraction system. The array effectively eliminates impurity fueling from plasma-material interaction by incorporating a local scraper-limiter and conical-frustum bias electrodes to mitigate the effects of cathode spots. An energy balance model of helicity injection indicates that the resulting 20 cm2 of total injection area should provide sufficient current drive to reach 0.3 MA. At that level, helicity injection drive exceeds that from poloidal induction, which is the relevant operational regime for large-scale spherical tokamaks. Future placement of the injector array near an expanded boundary divertor region will test simultaneous optimization of helicity drive and the Taylor relaxation current limit. Work supported by US DOE Grant DE-FG02-96ER54375.

Synchronized High-Speed Vision Sensor Network for Expansion of Field of View

Directory of Open Access Journals (Sweden)

Akihito Noda

2018-04-01

Full Text Available We propose a 500-frames-per-second high-speed vision (HSV sensor network that acquires frames at a timing that is precisely synchronized across the network. Multiple vision sensor nodes, individually comprising a camera and a PC, are connected via Ethernet for data transmission and for clock synchronization. A network of synchronized HSV sensors provides a significantly expanded field-of-view compared with that of each individual HSV sensor. In the proposed system, the shutter of each camera is controlled based on the clock of the PC locally provided inside the node, and the shutters are globally synchronized using the Precision Time Protocol (PTP over the network. A theoretical analysis and experiment results indicate that the shutter trigger skew among the nodes is a few tens of microseconds at most, which is significantly smaller than the frame interval of 1000-fps-class high-speed cameras. Experimental results obtained with the proposed system comprising four nodes demonstrated the ability to capture the propagation of a small displacement along a large-scale structure.

Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

Science.gov (United States)

Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

2009-01-01

Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

Cascading a systolic array and a feedforward neural network for navigation and obstacle avoidance using potential fields

Science.gov (United States)

Plumer, Edward S.

1991-01-01

A technique is developed for vehicle navigation and control in the presence of obstacles. A potential function was devised that peaks at the surface of obstacles and has its minimum at the proper vehicle destination. This function is computed using a systolic array and is guaranteed not to have local minima. A feedfoward neural network is then used to control the steering of the vehicle using local potential field information. In this case, the vehicle is a trailer truck backing up. Previous work has demonstrated the capability of a neural network to control steering of such a trailer truck backing to a loading platform, but without obstacles. Now, the neural network was able to learn to navigate a trailer truck around obstacles while backing toward its destination. The network is trained in an obstacle free space to follow the negative gradient of the field, after which the network is able to control and navigate the truck to its target destination in a space of obstacles which may be stationary or movable.

Feasibility of artificial geomagnetic field generation by a superconducting ring network

International Nuclear Information System (INIS)

Motojima, Osamu; Yanagi, Nagato

2008-05-01

The geomagnetic field shields the Earth from a large proportion of incoming radiation, and has thus played a key role in sustaining life on Earth. Paleomagnetic measurements have shown that the geomagnetic field undergoes many reversals of polarity. Continuous observations of the field intensity have revealed a weakening of approximately 10% over the last 150 years. If we assume that this trend indicates the onset of polarity reversal, the geomagnetic field, particularly the dipole component, may weaken sufficiently over the next thousand years to expose the atmosphere and nearby space to significantly increased levels of cosmic and solar radiation. This may have a serious impact on vital infrastructure such as satellites, air traffic, and electricity networks, as well as on global climate changes, indicating that measures should better be taken in an attempt to support the limited protection provided by the remaining higher-order multipole fields and atmosphere. Here we show that a series of planet-encircling superconducting rings can provide an artificial geomagnetic field equivalent to 10% of the present-day field necessary to prevent adverse effects. A feasible system consists of 12 latitudinal high-temperature superconducting rings, each carrying 6.4 MA current with a modest 1 GW of power requirement. (author)

EARLY DETECTION OF NEAR-FIELD TSUNAMIS USING UNDERWATER SENSOR NETWORKS

Directory of Open Access Journals (Sweden)

L. E. Freitag

2012-01-01

Full Text Available We propose a novel approach for near-field tsunami detection, specifically for the area near the city of Padang, Indonesia. Padang is located on the western shore of Sumatra, directly across from the Mentawai segment of the Sunda Trench, where accumulated strain has not been released since the great earthquake of 1797. Consequently, the risk of a major tsunamigenic earthquake on this segment is high. Currently, no ocean-bottom pressure sensors are deployed in the Mentawai basin to provide a definitive tsunami warning for Padang. Timely warnings are essential to initiate evacuation procedures and minimize loss of human life. Our approach augments existing technology with a network of underwater sensors to detect tsunamis generated by an earthquake or landslide fast enough to provide at least 15 minutes of warning. Data from the underwater sensor network would feed into existing decision support systems that accept input from land and sea-based sensors and provide warning information to city and regional authorities.

Pegasus(Registered trademark) Wing-Glove Experiment to Document Hypersonic Crossflow Transition: Measurement System and Selected Flight Results

Science.gov (United States)

Bertelrud, Arild; delaTova, Geva; Hamory, Philip J.; Young, Ronald; Noffz, Gregory K.; Dodson, Michael; Graves, Sharon S.; Diamond, John K.; Bartlett, James E.; Noack, Robert;

Network Neurodegeneration in Alzheimer’s Disease via MRI based Shape Diffeomorphometry and High Field Atlasing

Directory of Open Access Journals (Sweden)

Michael I Miller

2015-05-01

Full Text Available This paper examines MRI analysis of neurodegeneration in Alzheimer’s Disease (AD in a network of structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing in which the entorhinal cortex is partitioned into nine subareas. The morphometry markers for three groups of subjects (controls, preclinical AD and symptomatic AD are indexed to template coordinates measured with respect to these nine subareas. The location and timing of changes are examined within the subareas as it pertains to the classic Braak and Braak staging by comparing the three groups. We demonstrate that the earliest preclinical changes in the population occur in the lateral most sulcal extent in the entorhinal cortex (alluded to as trans entorhinal cortex by Braak and Braak, and then proceeds medially which is consistent with the Braak and Braak staging. We use high field 11T atlasing to demonstrate that the network changes are occurring at the junctures of the substructures in this medial temporal lobe network. Temporal progression of the disease through the network is also examined via changepoint analysis demonstrating earliest changes in entorhinal cortex. The differential expression of rate of atrophy with progression signaling the changepoint time across the network is demonstrated to be signaling in the intermediate caudal subarea of the entorhinal cortex, which has been noted to be proximal to the hippocampus. This coupled to the findings of the nearby basolateral involvement in amygdala demonstrates the selectivity of neurodegeneration in early AD.

Graphene-based field effect transistor in two-dimensional paper networks

Energy Technology Data Exchange (ETDEWEB)

Cagang, Aldrine Abenoja; Abidi, Irfan Haider; Tyagi, Abhishek [Department of Chemical and Biomolecular Engineering, Hong Kong University of Science and Technology, Clear Water Bay (Hong Kong); Hu, Jie; Xu, Feng [Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an 710049 (China); The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an 710049 (China); Lu, Tian Jian [Bioinspired Engineering and Biomechanics Center (BEBC), Xi' an Jiaotong University, Xi' an 710049 (China); Luo, Zhengtang, E-mail: keztluo@ust.hk [Department of Chemical and Biomolecular Engineering, Hong Kong University of Science and Technology, Clear Water Bay (Hong Kong)

2016-04-21

We demonstrate the fabrication of a graphene-based field effect transistor (GFET) incorporated in a two-dimensional paper network format (2DPNs). Paper serves as both a gate dielectric and an easy-to-fabricate vessel for holding the solution with the target molecules in question. The choice of paper enables a simpler alternative approach to the construction of a GFET device. The fabricated device is shown to behave similarly to a solution-gated GFET device with electron and hole mobilities of ∼1256 cm{sup 2} V{sup −1} s{sup −1} and ∼2298 cm{sup 2} V{sup −1} s{sup −1} respectively and a Dirac point around ∼1 V. When using solutions of ssDNA and glucose it was found that the added molecules induce negative electrolytic gating effects shifting the conductance minimum to the right, concurrent with increasing carrier concentrations which results to an observed increase in current response correlated to the concentration of the solution used. - Highlights: • A graphene-based field effect transistor sensor was fabricated for two-dimensional paper network formats. • The constructed GFET on 2DPN was shown to behave similarly to solution-gated GFETs. • Electrolyte gating effects have more prominent effect over adsorption effects on the behavior of the device. • The GFET incorporated on 2DPN was shown to yield linear response to presence of glucose and ssDNA soaked inside the paper.

Graphene-based field effect transistor in two-dimensional paper networks

International Nuclear Information System (INIS)

Cagang, Aldrine Abenoja; Abidi, Irfan Haider; Tyagi, Abhishek; Hu, Jie; Xu, Feng; Lu, Tian Jian; Luo, Zhengtang

2016-01-01

We demonstrate the fabrication of a graphene-based field effect transistor (GFET) incorporated in a two-dimensional paper network format (2DPNs). Paper serves as both a gate dielectric and an easy-to-fabricate vessel for holding the solution with the target molecules in question. The choice of paper enables a simpler alternative approach to the construction of a GFET device. The fabricated device is shown to behave similarly to a solution-gated GFET device with electron and hole mobilities of ∼1256 cm 2  V −1  s −1 and ∼2298 cm 2  V −1  s −1 respectively and a Dirac point around ∼1 V. When using solutions of ssDNA and glucose it was found that the added molecules induce negative electrolytic gating effects shifting the conductance minimum to the right, concurrent with increasing carrier concentrations which results to an observed increase in current response correlated to the concentration of the solution used. - Highlights: • A graphene-based field effect transistor sensor was fabricated for two-dimensional paper network formats. • The constructed GFET on 2DPN was shown to behave similarly to solution-gated GFETs. • Electrolyte gating effects have more prominent effect over adsorption effects on the behavior of the device. • The GFET incorporated on 2DPN was shown to yield linear response to presence of glucose and ssDNA soaked inside the paper.

Quantum perceptron over a field and neural network architecture selection in a quantum computer.

Science.gov (United States)

da Silva, Adenilton José; Ludermir, Teresa Bernarda; de Oliveira, Wilson Rosa

2016-04-01

In this work, we propose a quantum neural network named quantum perceptron over a field (QPF). Quantum computers are not yet a reality and the models and algorithms proposed in this work cannot be simulated in actual (or classical) computers. QPF is a direct generalization of a classical perceptron and solves some drawbacks found in previous models of quantum perceptrons. We also present a learning algorithm named Superposition based Architecture Learning algorithm (SAL) that optimizes the neural network weights and architectures. SAL searches for the best architecture in a finite set of neural network architectures with linear time over the number of patterns in the training set. SAL is the first learning algorithm to determine neural network architectures in polynomial time. This speedup is obtained by the use of quantum parallelism and a non-linear quantum operator. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantum phase transition of the transverse-field quantum Ising model on scale-free networks.

Science.gov (United States)

Yi, Hangmo

2015-01-01

I investigate the quantum phase transition of the transverse-field quantum Ising model in which nearest neighbors are defined according to the connectivity of scale-free networks. Using a continuous-time quantum Monte Carlo simulation method and the finite-size scaling analysis, I identify the quantum critical point and study its scaling characteristics. For the degree exponent λ=6, I obtain results that are consistent with the mean-field theory. For λ=4.5 and 4, however, the results suggest that the quantum critical point belongs to a non-mean-field universality class. Further simulations indicate that the quantum critical point remains mean-field-like if λ>5, but it continuously deviates from the mean-field theory as λ becomes smaller.

Radial Peripapillary Capillary Network Visualized Using Wide-Field Montage Optical Coherence Tomography Angiography.

Science.gov (United States)

Mase, Tomoko; Ishibazawa, Akihiro; Nagaoka, Taiji; Yokota, Harumasa; Yoshida, Akitoshi

2016-07-01

We quantitatively analyzed the features of a radial peripapillary capillary (RPC) network visualized using wide-field montage optical coherence tomography (OCT) angiography in healthy human eyes. Twenty eyes of 20 healthy subjects were recruited. En face 3 × 3-mm OCT angiograms of multiple locations in the posterior pole were acquired using the RTVue XR Avanti, and wide-field montage images of the RPC were created. To evaluate the RPC density, the montage images were binarized and skeletonized. The correlation between the RPC density and the retinal nerve fiber layer (RNFL) thickness measured by an OCT circle scan was investigated. The RPC at the temporal retina was detected as far as 7.6 ± 0.7 mm from the edge of the optic disc but not around the perifoveal area within 0.9 ± 0.1 mm of the fovea. Capillary-free zones beside the first branches of the arterioles were significantly (P optic disc edge were 13.6 ± 0.8, 11.9 ± 0.9, and 10.4 ± 0.9 mm-1. The RPC density also was correlated significantly (r = 0.64, P network. The RPC is present in the superficial peripapillary retina in proportion to the RNFL thickness, supporting the idea that the RPC may be the vascular network primarily responsible for RNFL nourishment.

Wireless networks of opportunity in support of secure field operations

Science.gov (United States)

Stehle, Roy H.; Lewis, Mark

1997-02-01

Under funding from the Defense Advanced Research Projects Agency (DARPA) for joint military and law enforcement technologies, demonstrations of secure information transfer in support of law enforcement and military operations other than war, using wireless and wired technology, were held in September 1996 at several locations in the United States. In this paper, the network architecture, protocols, and equipment supporting the demonstration's scenarios are presented, together with initial results, including lessons learned and desired system enhancements. Wireless networks of opportunity encompassed in-building (wireless-LAN), campus-wide (Metricom Inc.), metropolitan (AMPS cellular, CDPD), and national (one- and two-way satellite) systems. Evolving DARPA-sponsored packet radio technology was incorporated. All data was encrypted, using multilevel information system security initiative (MISSI)FORTEZZA technology, for carriage over unsecured and unclassified commercial networks. The identification and authentication process inherent in the security system permitted logging for database accesses and provided an audit trail useful in evidence gathering. Wireless and wireline communications support, to and between modeled crisis management centers, was demonstrated. Mechanisms for the guarded transport of data through the secret-high military tactical Internet were included, to support joint law enforcement and crisis management missions. A secure World Wide Web (WWW) browser forms the primary, user-friendly interface for information retrieval and submission. The WWW pages were structured to be sensitive to the bandwidth, error rate, and cost of the communications medium in use (e.g., the use of and resolution for graphical data). Both still and motion compressed video were demonstrated, along with secure voice transmission from laptop computers in the field. Issues of network bandwidth, airtime costs, and deployment status are discussed.

Phase transitions in scale-free neural networks: Departure from the standard mean-field universality class

International Nuclear Information System (INIS)

Aldana, Maximino; Larralde, Hernan

2004-01-01

We investigate the nature of the phase transition from an ordered to a disordered state that occurs in a family of neural network models with noise. These models are closely related to the majority voter model, where a ferromagneticlike interaction between the elements prevails. Each member of the family is distinguished by the network topology, which is determined by the probability distribution of the number of incoming links. We show that for homogeneous random topologies, the phase transition belongs to the standard mean-field universality class, characterized by the order parameter exponent β=1/2. However, for scale-free networks we obtain phase transition exponents ranging from 1/2 to infinity. Furthermore, we show the existence of a phase transition even for values of the scale-free exponent in the interval (1.5,2], where the average network connectivity diverges

The Study of Indoor and Field Trials on 2×8 MIMO Architecture in TD-LTE Network

Directory of Open Access Journals (Sweden)

Xiang Zhang

2013-01-01

the networks are based on frequency division duplexing (FDD. In this paper, measurement methods of four MIMO transmission modes (TMs in time division-LTE (TD-LTE are studied and analyzed. Link level simulation is carried out to evaluate the downlink throughput for different signal-to-noise ratios and parameter settings. Furthermore, indoor and field tests are also presented in the paper to investigate how real-world propagation affects the capacity and the error performance of MIMO transmission scheme. For the indoor test, radio channel emulators are applied to generate realistic wireless fading channel, while in the field trials, a live TD-LTE experiment cellular network is built, which contains several evolved nodeBs (eNBs and a precommercial user equipment (UE. It is shown from both simulation and tests results that MIMO deployment gives a substantial performance improvement compared with the third generation wireless networks.

Deep recurrent conditional random field network for protein secondary prediction

DEFF Research Database (Denmark)

Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

2017-01-01

Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

Analysis of The Game Mechanism in The Field of Network Security between China and the US and The Prospect of The Future

Directory of Open Access Journals (Sweden)

Wang Xiang

2016-12-01

Full Text Available In the field of Sino-US relations, the network space plays a very important role during a very short period of time. In recent years, the intensity and frequency of Chinese and American network security game has increased significantly, which has increased the instability of Sino-US relations. This paper reviews the network security game events between China and the US in recent years, and points out that network security has become a high risk problem in the relationship between China and the US and it has become the factors affecting the whole area. Network security issues need cooperation between China and the US to develop guidelines for the conduct of Cyberspace. As regards the prospect of Sino-US cyber security relations in the future, this paper argues that the strength and strategy in the Internet field of China and the US lead to the likelihood that China and the US fall into the “prisoner’s dilemma”. China and the US have to control the network security game to prevent damage to the overall situation of Sino-US relations; this is very urgent. Strengthening the network security fields of cooperation between China and the US is an inevitable choice both in terms of necessity and possibility.

DeepCotton: in-field cotton segmentation using deep fully convolutional network

Science.gov (United States)

Li, Yanan; Cao, Zhiguo; Xiao, Yang; Cremers, Armin B.

2017-09-01

Automatic ground-based in-field cotton (IFC) segmentation is a challenging task in precision agriculture, which has not been well addressed. Nearly all the existing methods rely on hand-crafted features. Their limited discriminative power results in unsatisfactory performance. To address this, a coarse-to-fine cotton segmentation method termed "DeepCotton" is proposed. It contains two modules, fully convolutional network (FCN) stream and interference region removal stream. First, FCN is employed to predict initially coarse map in an end-to-end manner. The convolutional networks involved in FCN guarantee powerful feature description capability, simultaneously, the regression analysis ability of neural network assures segmentation accuracy. To our knowledge, we are the first to introduce deep learning to IFC segmentation. Second, our proposed "UP" algorithm composed of unary brightness transformation and pairwise region comparison is used for obtaining interference map, which is executed to refine the coarse map. The experiments on constructed IFC dataset demonstrate that our method outperforms other state-of-the-art approaches, either in different common scenarios or single/multiple plants. More remarkable, the "UP" algorithm greatly improves the property of the coarse result, with the average amplifications of 2.6%, 2.4% on accuracy and 8.1%, 5.5% on intersection over union for common scenarios and multiple plants, separately.

KMTNET: A Network of 1.6 m Wide-Field Optical Telescopes Installed at Three Southern Observatories

Science.gov (United States)

Kim, Seung-Lee; Lee, Chung-Uk; Park, Byeong-Gon; Kim, Dong-Jin; Cha, Sang-Mok; Lee, Yongseok; Han, Cheongho; Chun, Moo-Young; Yuk, Insoo

2016-02-01

The Korea Microlensing Telescope Network (KMTNet) is a wide-field photometric system installed by the Korea Astronomy and Space Science Institute (KASI). Here, we present the overall technical specifications of the KMTNet observation system, test observation results, data transfer and image processing procedure, and finally, the KMTNet science programs. The system consists of three 1.6 m wide-field optical telescopes equipped with mosaic CCD cameras of 18k by 18k pixels. Each telescope provides a 2.0 by 2.0 square degree field of view. We have finished installing all three telescopes and cameras sequentially at the Cerro-Tololo Inter-American Observatory (CTIO) in Chile, the South African Astronomical Observatory (SAAO) in South Africa, and the Siding Spring Observatory (SSO) in Australia. This network of telescopes, which is spread over three different continents at a similar latitude of about -30 degrees, enables 24-hour continuous monitoring of targets observable in the Southern Hemisphere. The test observations showed good image quality that meets the seeing requirement of less than 1.0 arcsec in I-band. All of the observation data are transferred to the KMTNet data center at KASI via the international network communication and are processed with the KMTNet data pipeline. The primary scientific goal of the KMTNet is to discover numerous extrasolar planets toward the Galactic bulge by using the gravitational microlensing technique, especially earth-mass planets in the habitable zone. During the non-bulge season, the system is used for wide-field photometric survey science on supernovae, asteroids, and external galaxies.

Circulating persistent current and induced magnetic field in a fractal network

Energy Technology Data Exchange (ETDEWEB)

Saha, Srilekha [Condensed Matter Physics Division, Saha Institute of Nuclear Physics, Sector-I, Block-AF, Bidhannagar, Kolkata 700 064 (India); Maiti, Santanu K., E-mail: santanu.maiti@isical.ac.in [Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 Barrackpore Trunk Road, Kolkata 700 108 (India); Karmakar, S.N. [Condensed Matter Physics Division, Saha Institute of Nuclear Physics, Sector-I, Block-AF, Bidhannagar, Kolkata 700 064 (India)

2016-04-29

We present the overall conductance as well as the circulating currents in individual loops of a Sierpinski gasket (SPG) as we apply bias voltage via the side attached electrodes. SPG being a self-similar structure, its manifestation on loop currents and magnetic fields is examined in various generations of this fractal and it has been observed that for a given configuration of the electrodes, the physical quantities exhibit certain regularity as we go from one generation to another. Also a notable feature is the introduction of anisotropy in hopping causes an increase in magnitude of overall transport current. These features are a subject of interest in this article. - Highlights: • Voltage driven circular current is analyzed in a fractal network. • Current induced magnetic field is strong enough to flip a spin. • Anisotropy in hopping enhances overall transport current.

The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory.

Science.gov (United States)

Li, Man; Wang, Yanhui; Jia, Limin

2017-01-01

Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.

The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory.

Directory of Open Access Journals (Sweden)

Man Li

Full Text Available Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.

New method for the exact determination of the effective conductivity and the local field in RLC networks

International Nuclear Information System (INIS)

Zekri, L.; Zekri, N.; Bouamrane, R.

1999-10-01

We present a new numerical method for determining exactly the effective conductivity and the local field for random RLC networks. This method is compared to a real space renormalization group method and the Frank and Lobb method. Although our method is slower than the Frank and Lobb method, it also computes exactly the local field for large size systems. We also show that the renormalization group method fails in determining the local field. (author)

High-conductance states in a mean-field cortical network model

CERN Document Server

Lerchner, A; Hertz, J

2004-01-01

Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1 due to the tendency of spikes being clustered into bursts. We show that this behavior emerges naturally in a balanced cortical network model with random connectivity and conductance-based synapses. We employ mean field theory with correctly colored noise to describe temporal correlations in the neuronal activity. Our results illuminate the connection between two independent experimental findings: high conductance states of cortical neurons in their natural environment, and variable non-Poissonian spike statistics with Fano factors greater than 1.

Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

Science.gov (United States)

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-02-04

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

Directory of Open Access Journals (Sweden)

Yong Cui

2015-02-01

Full Text Available In the wireless sensor networks (WSNs for electric field measurement system under the High-Voltage Direct Current (HVDC transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes’ neighbor lists based on the Received Signal Strength Indicator (RSSI values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Statistical mechanics of a multiconnected Hopfield neural-network model in a transverse field

International Nuclear Information System (INIS)

Ma, Y.; Gong, C.

1995-01-01

The Hopfield neural-network model with p-spin interactions in the presence of a transverse field is introduced and solved exactly in the limit p→∞. In the phase diagrams drawn as a function of the temperature, the important results such as reentrance are found, and the effects of the quantum fluctuations on the phase transitions, the retrieval phase, and the storage ratio α are examined

Hyper-X Research Vehicle - Artist Concept Mounted on Pegasus Rocket Attached to B-52 Launch Aircraft

Science.gov (United States)

1997-01-01

only fuel. By eliminating the need to carry oxygen, future hypersonic vehicles will be able to carry heavier payloads. Another unique aspect of the X-43A vehicle is the airframe integration. The body of the vehicle itself forms critical elements of the engine. The forebody acts as part of the intake for airflow and the aft section serves as the nozzle. The X-43A vehicles were manufactured by Micro Craft, Inc., Tullahoma, Tennessee. Orbital Sciences Corporation, Chandler, Arizona, built the Pegasus rocket booster used to launch the X-43 vehicles. For the Dryden research flights, the Pegasus rocket booster and attached X-43 will be air launched by Dryden's B-52 'Mothership.' After release from the B-52, the booster will accelerate the X-43A vehicle to the established test conditions (Mach 7 to 10) at an altitude of approximately 100,000 feet where the X-43 will separate from the booster and fly under its own power and preprogrammed control.

Intelligent networked teleoperation control

CERN Document Server

Li, Zhijun; Su, Chun-Yi

2015-01-01

This book describes a unified framework for networked teleoperation systems involving multiple research fields: networked control systems for linear and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral teleoperation and cooperative teleoperation. It closely examines networked control as a field at the intersection of systems & control and robotics and presents a number of experimental case studies on testbeds for robotic systems, including networked haptic devices, robotic network systems and sensor network systems. The concepts and results outlined are easy to understand, even for readers fairly new to the subject. As such, the book offers a valuable reference work for researchers and engineers in the fields of systems & control and robotics.

Modulation of cortical-subcortical networks in Parkinson’s disease by applied field effects

OpenAIRE

Hess, Christopher W.

2013-01-01

Studies suggest that endogenous field effects may play a role in neuronal oscillations and communication. Non-invasive transcranial electrical stimulation with low-intensity currents can also have direct effects on the underlying cortex as well as distant network effects. While Parkinson’s disease (PD) is amenable to invasive neuromodulation in the basal ganglia by deep brain stimulation (DBS), techniques of non-invasive neuromodulation like transcranial direct current stimulation (tDCS) and ...

High-conductance states in a mean-field cortical network model

DEFF Research Database (Denmark)

Lerchner, Alexander; Ahmadi, Mandana; Hertz, John

2004-01-01

cortical network model with random connectivity and conductance-based synapses. We employ mean-field theory with correctly colored noise to describe temporal correlations in the neuronal activity. Our results illuminate the connection between two independent experimental findings: high-conductance states......Measured responses from visual cortical neurons show that spike times tend to be correlated rather than exactly Poisson distributed. Fano factors vary and are usually greater than 1, indicating a tendency toward spikes being clustered. We show that this behavior emerges naturally in a balanced...... of cortical neurons in their natural environment, and variable non-Poissonian spike statistics with Fano factors greater than 1. (C) 2004 Elsevier B.V. All rights reserved....

Secure transfer of surveillance data over Internet using Virtual Private Network technology. Field trial between STUK and IAEA

International Nuclear Information System (INIS)

Smartt, H.; Martinez, R.; Caskey, S.; Honkamaa, T.; Ilander, T.; Poellaenen, R.; Jeremica, N.; Ford, G.

2000-01-01

One of the primary concerns of employing remote monitoring technologies for IAEA safeguards applications is the high cost of data transmission. Transmitting data over the Internet has been shown often to be less expensive than other data transmission methods. However, data security of the Internet is often considered to be at a low level. Virtual Private Networks has emerged as a solution to this problem. A field demonstration was implemented to evaluate the use of Virtual Private Networks (via the Internet) as a means for data transmission. Evaluation points included security, reliability and cost. The existing Finnish Remote Environmental Monitoring System, located at the STUK facility in Helsinki, Finland, served as the field demonstration system. Sandia National Laboratories (SNL) established a Virtual Private Network between STUK (Radiation and Nuclear Safety Authority) Headquarters in Helsinki, Finland, and IAEA Headquarters in Vienna, Austria. Data from the existing STUK Remote Monitoring System was viewed at the IAEA via this network. The Virtual Private Network link was established in a proper manner, which guarantees the data security. Encryption was verified using a network sniffer. No problems were? encountered during the test. In the test system, fixed costs were higher than in the previous system, which utilized telephone lines. On the other hand transmission and operating costs are very low. Therefore, with low data amounts, the test system is not cost-effective, but if the data amount is tens of Megabytes per day the use of Virtual Private Networks and Internet will be economically justifiable. A cost-benefit analysis should be performed for each site due to significant variables. (orig.)

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

Directory of Open Access Journals (Sweden)

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.

A Comparative Field Monitoring of Column Shortenings in Tall Buildings Using Wireless and Wired Sensor Network Systems

Directory of Open Access Journals (Sweden)

Sungho Lee

2016-01-01

Full Text Available A comparative field measurement for column shortening of tall buildings is presented in this study, with a focus on the reliability and stability of a wireless sensor network. A wireless sensor network was used for monitoring the column shortenings of a 58-story building under construction. The wireless sensor network, which was composed of sensor and master nodes, employed the ultra-high-frequency band and CDMA communication methods. To evaluate the reliability and stability of the wireless sensor network system, the column shortenings were also measured using a conventional wired monitoring system. Two vibration wire gauges were installed in each of the selected 7 columns and 3 walls. Measurements for selected columns and walls were collected for 270 days after casting of the concrete. The results measured by the wireless sensor network were compared with the results of the conventional method. The strains and column shortenings measured using both methods showed good agreement for all members. It was verified that the column shortenings of tall buildings could be monitored using the wireless sensor network system with its reliability and stability.

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights

Directory of Open Access Journals (Sweden)

Wilten eNicola

2016-02-01

Full Text Available A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF. The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks

Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights.

Science.gov (United States)

Nicola, Wilten; Tripp, Bryan; Scott, Matthew

2016-01-01

A fundamental question in computational neuroscience is how to connect a network of spiking neurons to produce desired macroscopic or mean field dynamics. One possible approach is through the Neural Engineering Framework (NEF). The NEF approach requires quantities called decoders which are solved through an optimization problem requiring large matrix inversion. Here, we show how a decoder can be obtained analytically for type I and certain type II firing rates as a function of the heterogeneity of its associated neuron. These decoders generate approximants for functions that converge to the desired function in mean-squared error like 1/N, where N is the number of neurons in the network. We refer to these decoders as scale-invariant decoders due to their structure. These decoders generate weights for a network of neurons through the NEF formula for weights. These weights force the spiking network to have arbitrary and prescribed mean field dynamics. The weights generated with scale-invariant decoders all lie on low dimensional hypersurfaces asymptotically. We demonstrate the applicability of these scale-invariant decoders and weight surfaces by constructing networks of spiking theta neurons that replicate the dynamics of various well known dynamical systems such as the neural integrator, Van der Pol system and the Lorenz system. As these decoders are analytically determined and non-unique, the weights are also analytically determined and non-unique. We discuss the implications for measured weights of neuronal networks.

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks.

Science.gov (United States)

González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

2017-01-09

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

Temporal network epidemiology

CERN Document Server

Holme, Petter

2017-01-01

This book covers recent developments in epidemic process models and related data on temporally varying networks. It is widely recognized that contact networks are indispensable for describing, understanding, and intervening to stop the spread of infectious diseases in human and animal populations; “network epidemiology” is an umbrella term to describe this research field. More recently, contact networks have been recognized as being highly dynamic. This observation, also supported by an increasing amount of new data, has led to research on temporal networks, a rapidly growing area. Changes in network structure are often informed by epidemic (or other) dynamics, in which case they are referred to as adaptive networks. This volume gathers contributions by prominent authors working in temporal and adaptive network epidemiology, a field essential to understanding infectious diseases in real society.

Performance of Overlaid MIMO Cellular Networks with TAS/MRC under Hybrid-Access Small Cells and Poisson Field Interference

KAUST Repository

AbdelNabi, Amr A.

2018-02-12

This paper presents new approaches to characterize the achieved performance of hybrid control-access small cells in the context of two-tier multi-input multi-output (MIMO) cellular networks with random interference distributions. The hybrid scheme at small cells (such as femtocells) allows for sharing radio resources between the two network tiers according to the densities of small cells and their associated users, as well as the observed interference power levels in the two network tiers. The analysis considers MIMO transceivers at all nodes, for which antenna arrays can be utilized to implement transmit antenna selection (TAS) and receive maximal ratio combining (MRC) under MIMO point-to-point channels. Moreover, it tar-gets network-level models of interference sources inside each tier and between the two tiers, which are assumed to follow Poisson field processes. To fully capture the occasions for Poisson field distribution on MIMO spatial domain. Two practical scenarios of interference sources are addressed including highly-correlated or uncorrelated transmit antenna arrays of the serving macrocell base station. The analysis presents new analytical approaches that can characterize the downlink outage probability performance in any tier. Furthermore, the outage performance in high signal-to-noise (SNR) regime is also obtained, which can be useful to deduce diversity and/or coding gains.

Performance of Overlaid MIMO Cellular Networks with TAS/MRC under Hybrid-Access Small Cells and Poisson Field Interference

KAUST Repository

AbdelNabi, Amr A.; Al-Qahtani, Fawaz S.; Radaydeh, Redha Mahmoud Mesleh; Shaqfeh, Mohammad; Manna, Raed F.

2018-01-01

This paper presents new approaches to characterize the achieved performance of hybrid control-access small cells in the context of two-tier multi-input multi-output (MIMO) cellular networks with random interference distributions. The hybrid scheme at small cells (such as femtocells) allows for sharing radio resources between the two network tiers according to the densities of small cells and their associated users, as well as the observed interference power levels in the two network tiers. The analysis considers MIMO transceivers at all nodes, for which antenna arrays can be utilized to implement transmit antenna selection (TAS) and receive maximal ratio combining (MRC) under MIMO point-to-point channels. Moreover, it tar-gets network-level models of interference sources inside each tier and between the two tiers, which are assumed to follow Poisson field processes. To fully capture the occasions for Poisson field distribution on MIMO spatial domain. Two practical scenarios of interference sources are addressed including highly-correlated or uncorrelated transmit antenna arrays of the serving macrocell base station. The analysis presents new analytical approaches that can characterize the downlink outage probability performance in any tier. Furthermore, the outage performance in high signal-to-noise (SNR) regime is also obtained, which can be useful to deduce diversity and/or coding gains.

Social network data analytics

CERN Document Server

Aggarwal, Charu C

2011-01-01

Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Pr

Simultaneous fitting of a potential-energy surface and its corresponding force fields using feedforward neural networks

Science.gov (United States)

Pukrittayakamee, A.; Malshe, M.; Hagan, M.; Raff, L. M.; Narulkar, R.; Bukkapatnum, S.; Komanduri, R.

2009-04-01

An improved neural network (NN) approach is presented for the simultaneous development of accurate potential-energy hypersurfaces and corresponding force fields that can be utilized to conduct ab initio molecular dynamics and Monte Carlo studies on gas-phase chemical reactions. The method is termed as combined function derivative approximation (CFDA). The novelty of the CFDA method lies in the fact that although the NN has only a single output neuron that represents potential energy, the network is trained in such a way that the derivatives of the NN output match the gradient of the potential-energy hypersurface. Accurate force fields can therefore be computed simply by differentiating the network. Both the computed energies and the gradients are then accurately interpolated using the NN. This approach is superior to having the gradients appear in the output layer of the NN because it greatly simplifies the required architecture of the network. The CFDA permits weighting of function fitting relative to gradient fitting. In every test that we have run on six different systems, CFDA training (without a validation set) has produced smaller out-of-sample testing error than early stopping (with a validation set) or Bayesian regularization (without a validation set). This indicates that CFDA training does a better job of preventing overfitting than the standard methods currently in use. The training data can be obtained using an empirical potential surface or any ab initio method. The accuracy and interpolation power of the method have been tested for the reaction dynamics of H+HBr using an analytical potential. The results show that the present NN training technique produces more accurate fits to both the potential-energy surface as well as the corresponding force fields than the previous methods. The fitting and interpolation accuracy is so high (rms error=1.2 cm-1) that trajectories computed on the NN potential exhibit point-by-point agreement with corresponding

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

Science.gov (United States)

Sochi, Taha

2016-09-01

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

Institutional and scientific co-operation, networking and capacity building in the field of food safety and quality

NARCIS (Netherlands)

Boekel, van M.A.J.S.; Meerdink, G.; Banati, D.; Marvin, H.J.P.; Kuiper, H.A.; Houtman, C.B.

2002-01-01

This paper explains the situation in Hungary and The Netherlands regarding scientific co-operation, networking and capacity building in the field of food quality and safety. Specific details are given about institutional co-operation including exchanges between staff and students, collaborative

Response of Cultured Neuronal Network Activity After High-Intensity Power Frequency Magnetic Field Exposure

Directory of Open Access Journals (Sweden)

Atsushi Saito

2018-03-01

Full Text Available High-intensity and low frequency (1–100 kHz time-varying electromagnetic fields stimulate the human body through excitation of the nervous system. In power frequency range (50/60 Hz, a frequency-dependent threshold of the external electric field-induced neuronal modulation in cultured neuronal networks was used as one of the biological indicator in international guidelines; however, the threshold of the magnetic field-induced neuronal modulation has not been elucidated. In this study, we exposed rat brain-derived neuronal networks to a high-intensity power frequency magnetic field (hPF-MF, and evaluated the modulation of synchronized bursting activity using a multi-electrode array (MEA-based extracellular recording technique. As a result of short-term hPF-MF exposure (50–400 mT root-mean-square (rms, 50 Hz, sinusoidal wave, 6 s, the synchronized bursting activity was increased in the 400 mT-exposed group. On the other hand, no change was observed in the 50–200 mT-exposed groups. In order to clarify the mechanisms of the 400 mT hPF-MF exposure-induced neuronal response, we evaluated it after blocking inhibitory synapses using bicuculline methiodide (BMI; subsequently, increase in bursting activity was observed with BMI application, and the response of 400 mT hPF-MF exposure disappeared. Therefore, it was suggested that the response of hPF-MF exposure was involved in the inhibitory input. Next, we screened the inhibitory pacemaker-like neuronal activity which showed autonomous 4–10 Hz firing with CNQX and D-AP5 application, and it was confirmed that the activity was reduced after 400 mT hPF-MF exposure. Comparison of these experimental results with estimated values of the induced electric field (E-field in the culture medium revealed that the change in synchronized bursting activity occurred over 0.3 V/m, which was equivalent to the findings of a previous study that used the external electric fields. In addition, the results suggested that

The effect of an exogenous magnetic field on neural coding in deep spiking neural networks.

Science.gov (United States)

Guo, Lei; Zhang, Wei; Zhang, Jialei

2018-01-01

A ten-layer feed forward network is constructed in the presence of an exogenous alternating magnetic field. Specifically, our results indicate that for rate coding, the firing rate is significantly increased in the presence of an exogenous alternating magnetic field and particularly with increasing enhancement of the alternating magnetic field amplitude. For temporal coding, the interspike intervals of the spiking sequence are decreased and the distribution of the interspike intervals of the spiking sequence tends to be uniform in the presence of alternating magnetic field.

The Governmentality of Meta-governance : Identifying Theoretical and Empirical Challenges of Network Governance in the Political Field of Security and Beyond

OpenAIRE

Larsson, Oscar

2015-01-01

Meta-governance recently emerged in the field of governance as a new approach which claims that its use enables modern states to overcome problems associated with network governance. This thesis shares the view that networks are an important feature of contemporary politics which must be taken seriously, but it also maintains that networks pose substantial analytical and political challenges. It proceeds to investigate the potential possibilities and problems associated with meta-governance o...

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Eva González-Parada

2017-01-01

Full Text Available Autonomous mobile nodes in mobile wireless sensor networks (MWSN allow self-deployment and self-healing. In both cases, the goals are: (i to achieve adequate coverage; and (ii to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

Solid state magnetic field sensors for micro unattended ground networks using spin dependent tunneling

Science.gov (United States)

Tondra, Mark; Nordman, Catherine A.; Lange, Erik H.; Reed, Daniel; Jander, Albrect; Akou, Seraphin; Daughton, James

2001-09-01

Micro Unattended Ground Sensor Networks will likely employ magnetic sensors, primarily for discrimination of objects as opposed to initial detection. These magnetic sensors, then, must fit within very small cost, size, and power budgets to be compatible with the envisioned sensor suites. Also, a high degree of sensitivity is required to minimize the number of sensor cells required to survey a given area in the field. Solid state magnetoresistive sensors, with their low cost, small size, and ease of integration, are excellent candidates for these applications assuming that their power and sensitivity performance are acceptable. SDT devices have been fabricated into prototype magnetic field sensors suitable for use in micro unattended ground sensor networks. They are housed in tiny SOIC 8-pin packages and mounted on a circuit board with required voltage regulation, signal amplification and conditioning, and sensor control and communications functions. The best sensitivity results to date are 289 pT/rt. Hz at 1 Hz, and and 7 pT/rt. Hz at f > 10 kHz. Expected near term improvements in performance would bring these levels to approximately 10 pT/rt Hz at 1 Hz and approximately 1 pT/rt. Hz at > 1 kHz.

Composite Extension Finite Fields for Low Overhead Network Coding

DEFF Research Database (Denmark)

Heide, Janus; Roetter, Daniel Enrique Lucani

2015-01-01

Although Network Coding (NC) has been proven to increase throughput and reliability in communication networks, its adoption is typically hindered by the additional complexity it introduces at various nodes in the network and the overhead to signal the coding coefficients associated with each code...

Telecommunication networks

CERN Document Server

Iannone, Eugenio

2011-01-01

Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

Social networks

CERN Document Server

Etaner-Uyar, A Sima

2014-01-01

The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many

Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model

Directory of Open Access Journals (Sweden)

Dan Liu

2018-04-01

Full Text Available This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN and a continuous pairwise Conditional Random Field (CRF model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model.

Science.gov (United States)

Liu, Dan; Liu, Xuejun; Wu, Yiguang

2018-04-24

This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

Networks of networks the last frontier of complexity

CERN Document Server

Scala, Antonio

2014-01-01

The present work is meant as a reference to provide an organic and comprehensive view of the most relevant results in the exciting new field of Networks of Networks (NetoNets). Seminal papers have recently been published posing the basis to study what happens when different networks interact, thus providing evidence for the emergence of new, unexpected behaviors and vulnerabilities. From those seminal works, the awareness on the importance understanding Networks of Networks (NetoNets) has spread to the entire community of Complexity Science. The reader will benefit from the experience of some of the most well-recognized leaders in this field. The contents have been aggregated under four headings; General Theory, Phenomenology, Applications and Risk Assessment. The reader will be impressed by the different applications of the general paradigm that span from physiology, to financial risk, to transports. We are currently making the first steps to reduce the distance between the language and the way of thinking o...

Patent citation network in nanotechnology (1976-2004)

International Nuclear Information System (INIS)

Li Xin; Chen Hsinchun; Huang Zan; Roco, Mihail C.

2007-01-01

The patent citation networks are described using critical node, core network, and network topological analysis. The main objective is understanding of the knowledge transfer processes between technical fields, institutions and countries. This includes identifying key influential players and subfields, the knowledge transfer patterns among them, and the overall knowledge transfer efficiency. The proposed framework is applied to the field of nanoscale science and engineering (NSE), including the citation networks of patent documents, submitting institutions, technology fields, and countries. The NSE patents were identified by keywords 'full-text' searching of patents at the United States Patent and Trademark Office (USPTO). The analysis shows that the United States is the most important citation center in NSE research. The institution citation network illustrates a more efficient knowledge transfer between institutions than a random network. The country citation network displays a knowledge transfer capability as efficient as a random network. The technology field citation network and the patent document citation network exhibit a less efficient knowledge diffusion capability than a random network. All four citation networks show a tendency to form local citation clusters

Using a fully convolutional neural network for detecting locations of weeds in images from cereal fields

DEFF Research Database (Denmark)

Dyrmann, Mads; Skovsen, Søren; Sørensen, René A.

2018-01-01

been evaluated on an Nvidia Titan X, on which it is able to process a 5MPx image in 0.02s, making the method suitable for real-time field operation. For mechanical weed control, this network is sufficient. However, for chemical weed control, we also need to know the weed species in order to choose...

Networked web-cameras monitor congruent seasonal development of birches with phenological field observations

Science.gov (United States)

Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Kubin, Eero; Linkosalmi, Maiju; Melih Tanis, Cemal; Nadir Arslan, Ali

2017-04-01

Ecosystems' potential to provide services, e.g. to sequester carbon is largely driven by the phenological cycle of vegetation. Timing of phenological events is required for understanding and predicting the influence of climate change on ecosystems and to support various analyses of ecosystem functioning. We established a network of cameras for automated monitoring of phenological activity of vegetation in boreal ecosystems of Finland. Cameras were mounted on 14 sites, each site having 1-3 cameras. In this study, we used cameras at 11 of these sites to investigate how well networked cameras detect phenological development of birches (Betula spp.) along the latitudinal gradient. Birches are interesting focal species for the analyses as they are common throughout Finland. In our cameras they often appear in smaller quantities within dominant species in the images. Here, we tested whether small scattered birch image elements allow reliable extraction of color indices and changes therein. We compared automatically derived phenological dates from these birch image elements to visually determined dates from the same image time series, and to independent observations recorded in the phenological monitoring network from the same region. Automatically extracted season start dates based on the change of green color fraction in the spring corresponded well with the visually interpreted start of season, and field observed budburst dates. During the declining season, red color fraction turned out to be superior over green color based indices in predicting leaf yellowing and fall. The latitudinal gradients derived using automated phenological date extraction corresponded well with gradients based on phenological field observations from the same region. We conclude that already small and scattered birch image elements allow reliable extraction of key phenological dates for birch species. Devising cameras for species specific analyses of phenological timing will be useful for

No Man is an Island: Social Distance, Network Flow, and Other-Regarding Behaviors in a Natural Field Experiment

Directory of Open Access Journals (Sweden)

XIAOYE LI

2012-01-01

Full Text Available A natural field experiment is designed to explore the impacts of social distanceand network flow on other-regarding behaviors. A greater degree ofcommunication between the voluntary organization and volunteers was found toreduce their social distance and thereby improve volunteering commitment. Theimprovement was even more notable if the party initiating communication was thevoluntary organization. Two other practical means of lessening social distancewere for volunteers to learn more about other volunteers, and for informationtobe dispersed throughout the organization more rapidly. Additionally, this studyshows a reversed “U-shaped” relationship between network flow and volunteeringcommitment.

Complex Networks

CERN Document Server

Evsukoff, Alexandre; González, Marta

2013-01-01

In the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know th...

Strong geomagnetic activity forecast by neural networks under dominant southern orientation of the interplanetary magnetic field

Czech Academy of Sciences Publication Activity Database

Valach, F.; Bochníček, Josef; Hejda, Pavel; Revallo, M.

2014-01-01

Roč. 53, č. 4 (2014), s. 589-598 ISSN 0273-1177 R&D Projects: GA AV ČR(CZ) IAA300120608; GA MŠk OC09070 Institutional support: RVO:67985530 Keywords : geomagnetic activity * interplanetary magnetic field * artificial neural network * ejection of coronal mass * X-ray flares Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 1.358, year: 2014

Internal fracture heterogeneity in discrete fracture network modelling: Effect of correlation length and textures with connected and disconnected permeability field

Science.gov (United States)

Frampton, A.; Hyman, J.; Zou, L.

2017-12-01

Analysing flow and transport in sparsely fractured media is important for understanding how crystalline bedrock environments function as barriers to transport of contaminants, with important applications towards subsurface repositories for storage of spent nuclear fuel. Crystalline bedrocks are particularly favourable due to their geological stability, low advective flow and strong hydrogeochemical retention properties, which can delay transport of radionuclides, allowing decay to limit release to the biosphere. There are however many challenges involved in quantifying and modelling subsurface flow and transport in fractured media, largely due to geological complexity and heterogeneity, where the interplay between advective and dispersive flow strongly impacts both inert and reactive transport. A key to modelling transport in a Lagrangian framework involves quantifying pathway travel times and the hydrodynamic control of retention, and both these quantities strongly depend on heterogeneity of the fracture network at different scales. In this contribution, we present recent analysis of flow and transport considering fracture networks with single-fracture heterogeneity described by different multivariate normal distributions. A coherent triad of fields with identical correlation length and variance are created but which greatly differ in structure, corresponding to textures with well-connected low, medium and high permeability structures. Through numerical modelling of multiple scales in a stochastic setting we quantify the relative impact of texture type and correlation length against network topological measures, and identify key thresholds for cases where flow dispersion is controlled by single-fracture heterogeneity versus network-scale heterogeneity. This is achieved by using a recently developed novel numerical discrete fracture network model. Furthermore, we highlight enhanced flow channelling for cases where correlation structure continues across

First field trial of Virtual Network Operator oriented network on demand (NoD) service provisioning over software defined multi-vendor OTN networks

Science.gov (United States)

Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Chen, Haoran; Zhu, Ruijie; Zhou, Quanwei; Yu, Chenbei; Cui, Rui

2017-01-01

A Virtual Network Operator (VNO) is a provider and reseller of network services from other telecommunications suppliers. These network providers are categorized as virtual because they do not own the underlying telecommunication infrastructure. In terms of business operation, VNO can provide customers with personalized services by leasing network infrastructure from traditional network providers. The unique business modes of VNO lead to the emergence of network on demand (NoD) services. The conventional network provisioning involves a series of manual operation and configuration, which leads to high cost in time. Considering the advantages of Software Defined Networking (SDN), this paper proposes a novel NoD service provisioning solution to satisfy the private network need of VNOs. The solution is first verified in the real software defined multi-domain optical networks with multi-vendor OTN equipment. With the proposed solution, NoD service can be deployed via online web portals in near-real time. It reinvents the customer experience and redefines how network services are delivered to customers via an online self-service portal. Ultimately, this means a customer will be able to simply go online, click a few buttons and have new services almost instantaneously.

Initial Thomson Scattering Survey of Local Helicity Injection and Ohmic Plasmas at the Pegasus Toroidal Experiment

Science.gov (United States)

Schlossberg, D. J.; Bodner, G. M.; Bongard, M. W.; Fonck, R. J.; Winz, G. R.

2014-10-01

A multipoint Thomson scattering diagnostic has recently been installed on the Pegasus ST. The system utilizes a frequency-doubled Nd:YAG laser (λ0 ~ 532 nm), spectrometers with volume phase holographic gratings, and a gated, intensified CCD camera. It provides measurements of Te and ne at 8 spatial locations for each spectrometer once per discharge. A new multiple aperture and beam dump system has been implemented to mitigate interference from stray light. This system has provided initial measurements in the core region of plasmas initiated by local helicity injection (LHI), as well as conventional Ohmic L- and H-mode discharges. Multi-shot averages of low-density (ne ~ 3 ×1018 m-3) , Ip ~ 0 . 1 MA LHI discharges show central Te ~ 75 eV at the end of the helicity injection phase. Ip ~ 0 . 13 MA Ohmic plasmas at moderate densities (ne ~ 2 ×1019 m-3) have core Te ~ 150 eV in L-mode. Generally, these plasmas do not reach transport equilibrium in the short 25 ms pulse length available. After an L-H transition, strong spectral broadening indicates increasing Te, to values above the range of the present spectrometer system with a high-dispersion VPH grating. Near-term system upgrades will focus on deploying a second spectrometer, with a lower-dispersion grating capable of measuring the 0.1-1.0 keV range. The second spectrometer system will also increase the available number of spatial channels, enabling study of H-mode pedestal structure. Work supported by US DOE Grant DE-FG02-96ER54375.

8th Conference on Complex Networks

CERN Document Server

Menezes, Ronaldo; Sinatra, Roberta; Zlatic, Vinko

2017-01-01

This book collects the works presented at the 8th International Conference on Complex Networks (CompleNet) 2017 in Dubrovnik, Croatia, on March 21-24, 2017. CompleNet aims at bringing together researchers and practitioners working in areas related to complex networks. The past two decades has witnessed an exponential increase in the number of publications within this field. From biological systems to computer science, from economic to social systems, complex networks are becoming pervasive in many fields of science. It is this interdisciplinary nature of complex networks that CompleNet aims at addressing. The last decades have seen the emergence of complex networks as the language with which a wide range of complex phenomena in fields as diverse as physics, computer science, and medicine (to name a few) can be properly described and understood. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as network controllability, social structure, online behavior, recommend...

Technologies for Home Networking

DEFF Research Database (Denmark)

A broad overview of the home networking field, ranging from wireless technologies to practical applications. In the future, it is expected that private networks (e.g. home networks) will become part of the global network ecosystem, participating in sharing their own content, running IP...

Network coding at different layers in wireless networks

CERN Document Server

2016-01-01

This book focuses on how to apply network coding at different layers in wireless networks – including MAC, routing, and TCP – with special focus on cognitive radio networks. It discusses how to select parameters in network coding (e.g., coding field, number of packets involved, and redundant information ration) in order to be suitable for the varying wireless environments. The book explores how to deploy network coding in MAC to improve network performance and examines joint network coding with opportunistic routing to improve the successful rate of routing. In regards to TCP and network coding, the text considers transport layer protocol working with network coding to overcome the transmission error rate, particularly with how to use the ACK feedback of TCP to enhance the efficiency of network coding. The book pertains to researchers and postgraduate students, especially whose interests are in opportunistic routing and TCP in cognitive radio networks.

Hybrid Access Femtocells in Overlaid MIMO Cellular Networks with Transmit Selection under Poisson Field Interference

KAUST Repository

Abdel Nabi, Amr A

2017-09-21

This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.

Hybrid Access Femtocells in Overlaid MIMO Cellular Networks with Transmit Selection under Poisson Field Interference

KAUST Repository

Abdel Nabi, Amr A; Al-Qahtani, Fawaz S.; Radaydeh, Redha Mahmoud Mesleh; Shaqfeh, Mohammed

2017-01-01

This paper analyzes the performance of hybrid control-access schemes for small cells (such as femtocells) in the context of two-tier overlaid cellular networks. The proposed hybrid access schemes allow for sharing the same downlink resources between the small-cell network and the original macrocell network, and their mode of operations are characterized considering post-processed signal-to-interference-plus-noise ratios (SINRs) or pre-processed interference-aware operation. The work presents a detailed treatment of achieved performance of a desired user that benefits from MIMO arrays configuration through the use of transmit antenna selection (TAS) and maximal ratio combining (MRC) in the presence of Poisson field interference processes on spatial links. Furthermore, based on the interference awareness at the desired user, two TAS approaches are treated, which are the signal-to-noise (SNR)-based selection and SINR-based selection. The analysis is generalized to address the cases of highly-correlated and un-correlated aggregated interference on different transmit channels. In addition, the effect of delayed TAS due to imperfect feedback and the impact of arbitrary TAS processing are investigated. The analytical results are validated by simulations, to clarify some of the main outcomes herein.

Visualization maps for the evolution of research hotspots in the field of regional health information networks.

Science.gov (United States)

Wang, Yanjun; Zheng, Jianzhong; Zhang, Ailian; Zhou, Wei; Dong, Haiyuan

2018-03-01

The aim of this study was to reveal research hotspots in the field of regional health information networks (RHINs) and use visualization techniques to explore their evolution over time and differences between countries. We conducted a literature review for a 50-year period and compared the prevalence of certain index terms during the periods 1963-1993 and 1994-2014 and in six countries. We applied keyword frequency analysis, keyword co-occurrence analysis, multidimensional scaling analysis, and network visualization technology. The total number of keywords was found to increase with time. From 1994 to 2014, the research priorities shifted from hospital planning to community health planning. The number of keywords reflecting information-based research increased. The density of the knowledge network increased significantly, and partial keywords condensed into knowledge groups. All six countries focus on keywords including Information Systems; Telemedicine; Information Service; Medical Records Systems, Computerized; Internet; etc.; however, the level of development and some research priorities are different. RHIN research has generally increased in popularity over the past 50 years. The research hotspots are evolving and are at different levels of development in different countries. Knowledge network mapping and perceptual maps provide useful information for scholars, managers, and policy-makers.

Flower development as an interplay between dynamical physical fields and genetic networks.

Science.gov (United States)

Barrio, Rafael Ángel; Hernández-Machado, Aurora; Varea, C; Romero-Arias, José Roberto; Alvarez-Buylla, Elena

2010-10-27

In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN) underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels.

A comparative study between nonlinear regression and artificial neural network approaches for modelling wild oat (Avena fatua) field emergence

Science.gov (United States)

Non-linear regression techniques are used widely to fit weed field emergence patterns to soil microclimatic indices using S-type functions. Artificial neural networks present interesting and alternative features for such modeling purposes. In this work, a univariate hydrothermal-time based Weibull m...

Competing edge networks

International Nuclear Information System (INIS)

Parsons, Mark; Grindrod, Peter

2012-01-01

We introduce a model for a pair of nonlinear evolving networks, defined over a common set of vertices, subject to edgewise competition. Each network may grow new edges spontaneously or through triad closure. Both networks inhibit the other's growth and encourage the other's demise. These nonlinear stochastic competition equations yield to a mean field analysis resulting in a nonlinear deterministic system. There may be multiple equilibria; and bifurcations of different types are shown to occur within a reduced parameter space. This situation models competitive communication networks such as BlackBerry Messenger displacing SMS; or instant messaging displacing emails. -- Highlights: ► A model for edgewise-competing evolving network pairs is introduced. ► Defined competition equations yield to a mean field analysis. ► Multiple equilibrium states and different bifurcation types can occur. ► The system is sensitive to sparse initial conditions and near unstable equilibriums.

Critical Fluctuations in Spatial Complex Networks

Science.gov (United States)

Bradde, Serena; Caccioli, Fabio; Dall'Asta, Luca; Bianconi, Ginestra

2010-05-01

An anomalous mean-field solution is known to capture the nontrivial phase diagram of the Ising model in annealed complex networks. Nevertheless, the critical fluctuations in random complex networks remain mean field. Here we show that a breakdown of this scenario can be obtained when complex networks are embedded in geometrical spaces. Through the analysis of the Ising model on annealed spatial networks, we reveal, in particular, the spectral properties of networks responsible for critical fluctuations and we generalize the Ginsburg criterion to complex topologies.

Technical Network

CERN Multimedia

2007-01-01

In order to optimise the management of the Technical Network (TN), to facilitate understanding of the purpose of devices connected to the TN and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive e-mails from IT/CS asking them to add the corresponding information in the network database at "network-cern-ch". Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

Interaction of Aquifer and River-Canal Network near Well Field.

Science.gov (United States)

Ghosh, Narayan C; Mishra, Govinda C; Sandhu, Cornelius S S; Grischek, Thomas; Singh, Vikrant V

2015-01-01

The article presents semi-analytical mathematical models to asses (1) enhancements of seepage from a canal and (2) induced flow from a partially penetrating river in an unconfined aquifer consequent to groundwater withdrawal in a well field in the vicinity of the river and canal. The nonlinear exponential relation between seepage from a canal reach and hydraulic head in the aquifer beneath the canal reach is used for quantifying seepage from the canal reach. Hantush's (1967) basic solution for water table rise due to recharge from a rectangular spreading basin in absence of pumping well is used for generating unit pulse response function coefficients for water table rise in the aquifer. Duhamel's convolution theory and method of superposition are applied to obtain water table position due to pumping and recharge from different canal reaches. Hunt's (1999) basic solution for river depletion due to constant pumping from a well in the vicinity of a partially penetrating river is used to generate unit pulse response function coefficients. Applying convolution technique and superposition, treating the recharge from canal reaches as recharge through conceptual injection wells, river depletion consequent to variable pumping and recharge is quantified. The integrated model is applied to a case study in Haridwar (India). The well field consists of 22 pumping wells located in the vicinity of a perennial river and a canal network. The river bank filtrate portion consequent to pumping is quantified. © 2014, National GroundWater Association.

Imaging the Flow Networks from a Harmonic Pumping in a Karstic Field with an Inversion Algorithm

Science.gov (United States)

Fischer, P.; Lecoq, N.; Jardani, A.; Jourde, H.; Wang, X.; Chedeville, S.; Cardiff, M. A.

2017-12-01

Identifying flow paths within karstic fields remains a complex task because of the high dependency of the hydraulic responses to the relative locations between the observation boreholes and the karstic conduits and interconnected fractures that control the main flows of the hydrosystem. In this context, harmonic pumping is a new investigation tool that permits to inform on the flow paths connectivity between the boreholes. We have shown that the amplitude and phase offset values in the periodic responses of a hydrosystem to a harmonic pumping test characterize three different type of flow behavior between the measurement boreholes and the pumping borehole: a direct connectivity response (conduit flow), an indirect connectivity (conduit and short matrix flows), and an absence of connectivity (matrix). When the hydraulic responses to study are numerous and complex, the interpretation of the flow paths requires an inverse modeling. Therefore, we have recently developed a Cellular Automata-based Deterministic Inversion (CADI) approach that permits to infer the spatial distribution of field hydraulic conductivities in a structurally constrained model. This method distributes hydraulic conductivities along linear structures (i.e. karst conduits) and iteratively modifies the structural geometry of this conduits network to progressively match the observed responses to the modeled ones. As a result, this method produces a conductivity model that is composed of a discrete conduit network embedded in the background matrix, capable of producing the same flow behavior as the investigated hydrologic system. We applied the CADI approach in order to reproduce, in a model, the amplitude and phase offset values of a set of periodic responses generated from harmonic pumping tests conducted in different boreholes at the Terrieu karstic field site (Southern France). This association of oscillatory responses with the CADI method provides an interpretation of the flow paths within the

On-the-field performance of quintuple-play long-reach OFDM-based WDM-PON optical access networks.

Science.gov (United States)

Llorente, Roberto; Morant, Maria; Pellicer, Eloy; Herman, Milan; Nagy, Zsolt; Alves, Tiago; Cartaxo, Adolfo; Herrera, Javier; Correcher, Jose; Quinlan, Terence; Walker, Stuart; Rodrigues, Cláudio; Cluzeaud, Pierre; Schmidt, Axel; Piesiewicz, Radoslaw; Sambaraju, Rakesh

2014-03-24

In this paper the on-the-field performance of a WDM-PON optical access providing quintuple-play services using orthogonal frequency division multiplexing (OFDM) modulation is evaluated in a real fiber-to-the-home (FTTH) network deployed by Towercom operator in Bratislava (Slovakia). A bundle of quintuple-play services comprising full-standard OFDM-based signals (LTE, WiMAX, UWB and DVB-T) and an ad-hoc OFDM-GbE signal is transmitted in coexistence per single user. Both downstream and upstream transmission performances are evaluated in different on-the-field long-reach optical link distance configurations. Four wavelength multi-user transmission of quintuple-play OFDM services is demonstrated exceeding 60.8 km reach in standard single mode fiber.

Transport properties of field effect transistors with randomly networked single walled carbon nanotubes grown by plasma enhanced chemical vapour deposition

International Nuclear Information System (INIS)

Kim, Un Jeong; Park, Wanjun

2009-01-01

The transport properties of randomly networked single walled carbon nanotube (SWNT) transistors with different channel lengths of L c = 2-10 μm were investigated. Randomly networked SWNTs were directly grown for the two different densities of ρ ∼ 25 μm -2 and ρ ∼ 50 μm -2 by water plasma enhanced chemical vapour deposition. The field effect transport is governed mainly by formation of the current paths that is related to the nanotube density. On the other hand, the off-state conductivity deviates from linear dependence for both nanotube density and channel length. The field effect mobility of holes is estimated as 4-13 cm 2 V -1 s -1 for the nanotube transistors based on the simple MOS theory. The mobility is increased for the higher density without meaningful dependence on the channel lengths.

Modulation of Cortical-subcortical Networks in Parkinson’s Disease by Applied Field Effects

Directory of Open Access Journals (Sweden)

Christopher William Hess

2013-09-01

Full Text Available Studies suggest that endogenous field effects may play a role in neuronal oscillations and communication. Non-invasive transcranial electrical stimulation with low-intensity currents can also have direct effects on the underlying cortex as well as distant network effects. While Parkinson's disease (PD is amenable to invasive neuromodulation in the basal ganglia by deep brain stimulation, techniques of non-invasive neuromodulation like transcranial direct current stimulation (tDCS and transcranial alternating current stimulation (tACS are being investigated as possible therapies. tDCS and tACS have the potential to influence the abnormal cortical-subcortical network activity that occurs in PD through sub-threshold changes in cortical excitability or through entrainment or disruption of ongoing rhythmic cortical activity. This may allow for the targeting of specific features of the disease involving abnormal oscillatory activity, as well as the enhancement of potential cortical compensation for basal ganglia dysfunction and modulation of cortical plasticity in neurorehabilitation. However, little is currently known about how cortical stimulation will affect subcortical structures, the size of any effect, and the factors of stimulation that will influence these effects.

Field assessment of bacterial communities and total trihalomethanes: Implications for drinking water networks.

Science.gov (United States)

Montoya-Pachongo, Carolina; Douterelo, Isabel; Noakes, Catherine; Camargo-Valero, Miller Alonso; Sleigh, Andrew; Escobar-Rivera, Juan-Carlos; Torres-Lozada, Patricia

2018-03-01

Operation and maintenance (O&M) of drinking water distribution networks (DWDNs) in tropical countries simultaneously face the control of acute and chronic risks due to the presence of microorganisms and disinfection by-products, respectively. In this study, results from a detailed field characterization of microbiological, chemical and infrastructural parameters of a tropical-climate DWDN are presented. Water physicochemical parameters and the characteristics of the network were assessed to evaluate the relationship between abiotic and microbiological factors and their association with the presence of total trihalomethanes (TTHMs). Illumina sequencing of the bacterial 16s rRNA gene revealed significant differences in the composition of biofilm and planktonic communities. The highly diverse biofilm communities showed the presence of methylotrophic bacteria, which suggest the presence of methyl radicals such as THMs within this habitat. Microbiological parameters correlated with water age, pH, temperature and free residual chlorine. The results from this study are necessary to increase the awareness of O&M practices in DWDNs required to reduce biofilm formation and maintain appropriate microbiological and chemical water quality, in relation to biofilm detachment and DBP formation. Copyright © 2017 Elsevier B.V. All rights reserved.

Technical Network

CERN Multimedia

2007-01-01

In order to optimize the management of the Technical Network (TN), to ease the understanding and purpose of devices connected to the TN, and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive email notifications from IT/CS asking them to add the corresponding information in the network database. Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

Science.gov (United States)

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Advanced network programming principles and techniques : network application programming with Java

CERN Document Server

Ciubotaru, Bogdan

2013-01-01

Answering the need for an accessible overview of the field, this text/reference presents a manageable introduction to both the theoretical and practical aspects of computer networks and network programming. Clearly structured and easy to follow, the book describes cutting-edge developments in network architectures, communication protocols, and programming techniques and models, supported by code examples for hands-on practice with creating network-based applications. Features: presents detailed coverage of network architectures; gently introduces the reader to the basic ideas underpinning comp

EXTERNALITIES IN EXCHANGE NETWORKS AN ADAPTATION OF EXISTING THEORIES OF EXCHANGE NETWORKS

NARCIS (Netherlands)

Dijkstra, Jacob

2009-01-01

The present paper extends the focus of network exchange research to externalities in exchange networks. Externalities of exchange are defined as direct effects on an actor's utility, of an exchange in which this actor is not involved. Existing theories in the field of network exchange do not inform

On/off ratio enhancement in single-walled carbon nanotube field-effect transistor by controlling network density via sonication

Science.gov (United States)

Jang, Ho-Kyun; Choi, Jun Hee; Kim, Do-Hyun; Kim, Gyu Tae

2018-06-01

Single-walled carbon nanotube (SWCNT) is generally used as a networked structure in the fabrication of a field-effect transistor (FET) since it is known that one-third of SWCNT is electrically metallic and the remains are semiconducting. In this case, the presence of metallic paths by metallic SWCNT (m-SWCNT) becomes a significant technical barrier which hinders the networks from achieving a semiconducting behavior, resulting in a low on/off ratio. Here, we report on an easy method of controlling the on/off ratio of a FET where semiconducting SWCNT (s-SWCNT) and m-SWCNT constitute networks between source and drain electrodes. A FET with SWCNT networks was simply sonicated under water to control the on/off ratio and network density. As a result, the FET having an almost metallic behavior due to the metallic paths by m-SWCNT exhibited a p-type semiconducting behavior. The on/off ratio ranged from 1 to 9.0 × 104 along sonication time. In addition, theoretical calculations based on Monte-Carlo method and circuit simulation were performed to understand and explain the phenomenon of a change in the on/off ratio and network density by sonication. On the basis of experimental and theoretical results, we found that metallic paths contributed to a high off-state current which leads to a low on/off ratio and that sonication formed sparse SWCNT networks where metallic paths of m-SWCNT were removed, resulting in a high on/off ratio. This method can open a chance to save the device which has been considered as a failed one due to a metallic behavior by a high network density leading to a low on/off ratio.

Urban exposure to ELF magnetic field due to high-, medium- and low-voltage electricity supply networks

International Nuclear Information System (INIS)

Bottura, V.; Cappio Borlino, M.; Carta, N.; Cerise, L.; Imperial, E.

2009-01-01

The regional environment protection agency (ARPA) of the Aosta Valley region in north Italy performed a survey of magnetic field triggered by the power supply network in high, medium and low voltages on the entire area of Aosta town. The electrical distribution system for houses was not however taken into account. The aim of the survey was to evaluate the global population exposure and not simply the assessment of the legal exposure limit compliance. (authors)

Flower development as an interplay between dynamical physical fields and genetic networks.

Directory of Open Access Journals (Sweden)

Rafael Ángel Barrio

Full Text Available In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

Directory of Open Access Journals (Sweden)

Mohammad S. Islam

2017-01-01

Full Text Available Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs for robust movement decoding of Parkinson’s disease (PD and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.

Temporal networks

Science.gov (United States)

Holme, Petter; Saramäki, Jari

2012-10-01

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

Reliable Communication in Wireless Meshed Networks using Network Coding

DEFF Research Database (Denmark)

Pahlevani, Peyman; Paramanathan, Achuthan; Hundebøll, Martin

2012-01-01

The advantages of network coding have been extensively studied in the field of wireless networks. Integrating network coding with existing IEEE 802.11 MAC layer is a challenging problem. The IEEE 802.11 MAC does not provide any reliability mechanisms for overheard packets. This paper addresses...... this problem and suggests different mechanisms to support reliability as part of the MAC protocol. Analytical expressions to this problem are given to qualify the performance of the modified network coding. These expressions are confirmed by numerical result. While the suggested reliability mechanisms...

Solution-Processed Donor-Acceptor Polymer Nanowire Network Semiconductors For High-Performance Field-Effect Transistors

Science.gov (United States)

Lei, Yanlian; Deng, Ping; Li, Jun; Lin, Ming; Zhu, Furong; Ng, Tsz-Wai; Lee, Chun-Sing; Ong, Beng S.

2016-01-01

Organic field-effect transistors (OFETs) represent a low-cost transistor technology for creating next-generation large-area, flexible and ultra-low-cost electronics. Conjugated electron donor-acceptor (D-A) polymers have surfaced as ideal channel semiconductor candidates for OFETs. However, high-molecular weight (MW) D-A polymer semiconductors, which offer high field-effect mobility, generally suffer from processing complications due to limited solubility. Conversely, the readily soluble, low-MW D-A polymers give low mobility. We report herein a facile solution process which transformed a lower-MW, low-mobility diketopyrrolopyrrole-dithienylthieno[3,2-b]thiophene (I) into a high crystalline order and high-mobility semiconductor for OFETs applications. The process involved solution fabrication of a channel semiconductor film from a lower-MW (I) and polystyrene blends. With the help of cooperative shifting motion of polystyrene chain segments, (I) readily self-assembled and crystallized out in the polystyrene matrix as an interpenetrating, nanowire semiconductor network, providing significantly enhanced mobility (over 8 cm2V−1s−1), on/off ratio (107), and other desirable field-effect properties that meet impactful OFET application requirements. PMID:27091315

Artificial neural networks in NDT

International Nuclear Information System (INIS)

Abdul Aziz Mohamed

2001-01-01

Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

Interconnected networks

CERN Document Server

2016-01-01

This volume provides an introduction to and overview of the emerging field of interconnected networks which include multi layer or multiplex networks, as well as networks of networks. Such networks present structural and dynamical features quite different from those observed in isolated networks. The presence of links between different networks or layers of a network typically alters the way such interconnected networks behave – understanding the role of interconnecting links is therefore a crucial step towards a more accurate description of real-world systems. While examples of such dissimilar properties are becoming more abundant – for example regarding diffusion, robustness and competition – the root of such differences remains to be elucidated. Each chapter in this topical collection is self-contained and can be read on its own, thus making it also suitable as reference for experienced researchers wishing to focus on a particular topic.

Domain wall networks on solitons

International Nuclear Information System (INIS)

Sutcliffe, Paul

2003-01-01

Domain wall networks on the surface of a soliton are studied in a simple theory. It consists of two complex scalar fields, in 3+1 dimensions, with a global U(1)xZ n symmetry, where n>2. Solutions are computed numerically in which one of the fields forms a Q ball and the other field forms a network of domain walls localized on the surface of the Q ball. Examples are presented in which the domain walls lie along the edges of a spherical polyhedron, forming junctions at its vertices. It is explained why only a small restricted class of polyhedra can arise as domain wall networks

Optimization of potential field method parameters through networks for swarm cooperative manipulation tasks

Directory of Open Access Journals (Sweden)

Rocco Furferi

2016-10-01

Full Text Available An interesting current research field related to autonomous robots is mobile manipulation performed by cooperating robots (in terrestrial, aerial and underwater environments. Focusing on the underwater scenario, cooperative manipulation of Intervention-Autonomous Underwater Vehicles (I-AUVs is a complex and difficult application compared with the terrestrial or aerial ones because of many technical issues, such as underwater localization and limited communication. A decentralized approach for cooperative mobile manipulation of I-AUVs based on Artificial Neural Networks (ANNs is proposed in this article. This strategy exploits the potential field method; a multi-layer control structure is developed to manage the coordination of the swarm, the guidance and navigation of I-AUVs and the manipulation task. In the article, this new strategy has been implemented in the simulation environment, simulating the transportation of an object. This object is moved along a desired trajectory in an unknown environment and it is transported by four underwater mobile robots, each one provided with a seven-degrees-of-freedom robotic arm. The simulation results are optimized thanks to the ANNs used for the potentials tuning.

Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

Directory of Open Access Journals (Sweden)

Hossein Bashashati

2017-07-01

Full Text Available Classification of EEG signals in self-paced Brain Computer Interfaces (BCI is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF. NNCRF is a combination of a neural network and conditional random field (CRF. As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF, and to two classical classifiers (Logistic Regression and Support Vector Machines. The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC of the BCI system.

Accounting for time- and space-varying changes in the gravity field to improve the network adjustment of relative-gravity data

Science.gov (United States)

Kennedy, Jeffrey R.; Ferre, Ty P.A.

2015-01-01

The relative gravimeter is the primary terrestrial instrument for measuring spatially and temporally varying gravitational fields. The background noise of the instrument—that is, non-linear drift and random tares—typically requires some form of least-squares network adjustment to integrate data collected during a campaign that may take several days to weeks. Here, we present an approach to remove the change in the observed relative-gravity differences caused by hydrologic or other transient processes during a single campaign, so that the adjusted gravity values can be referenced to a single epoch. The conceptual approach is an example of coupled hydrogeophysical inversion, by which a hydrologic model is used to inform and constrain the geophysical forward model. The hydrologic model simulates the spatial variation of the rate of change of gravity as either a linear function of distance from an infiltration source, or using a 3-D numerical groundwater model. The linear function can be included in and solved for as part of the network adjustment. Alternatively, the groundwater model is used to predict the change of gravity at each station through time, from which the accumulated gravity change is calculated and removed from the data prior to the network adjustment. Data from a field experiment conducted at an artificial-recharge facility are used to verify our approach. Maximum gravity change due to hydrology (observed using a superconducting gravimeter) during the relative-gravity field campaigns was up to 2.6 μGal d−1, each campaign was between 4 and 6 d and one month elapsed between campaigns. The maximum absolute difference in the estimated gravity change between two campaigns, two months apart, using the standard network adjustment method and the new approach, was 5.5 μGal. The maximum gravity change between the same two campaigns was 148 μGal, and spatial variation in gravity change revealed zones of preferential infiltration and areas of relatively

Computer-communication networks

CERN Document Server

Meditch, James S

1983-01-01

Computer- Communication Networks presents a collection of articles the focus of which is on the field of modeling, analysis, design, and performance optimization. It discusses the problem of modeling the performance of local area networks under file transfer. It addresses the design of multi-hop, mobile-user radio networks. Some of the topics covered in the book are the distributed packet switching queuing network design, some investigations on communication switching techniques in computer networks and the minimum hop flow assignment and routing subject to an average message delay constraint

Bidirectional Long Short-Term Memory Network with a Conditional Random Field Layer for Uyghur Part-Of-Speech Tagging

Directory of Open Access Journals (Sweden)

Maihemuti Maimaiti

2017-11-01

Full Text Available Uyghur is an agglutinative and a morphologically rich language; natural language processing tasks in Uyghur can be a challenge. Word morphology is important in Uyghur part-of-speech (POS tagging. However, POS tagging performance suffers from error propagation of morphological analyzers. To address this problem, we propose a few models for POS tagging: conditional random fields (CRF, long short-term memory (LSTM, bidirectional LSTM networks (BI-LSTM, LSTM networks with a CRF layer, and BI-LSTM networks with a CRF layer. These models do not depend on stemming and word disambiguation for Uyghur and combine hand-crafted features with neural network models. State-of-the-art performance on Uyghur POS tagging is achieved on test data sets using the proposed approach: 98.41% accuracy on 15 labels and 95.74% accuracy on 64 labels, which are 2.71% and 4% improvements, respectively, over the CRF model results. Using engineered features, our model achieves further improvements of 0.2% (15 labels and 0.48% (64 labels. The results indicate that the proposed method could be an effective approach for POS tagging in other morphologically rich languages.

Proceedings of the African Field Epidemiology Network (AFENET) Scientific Conference 17-22 November 2013 Addis Ababa, Ethiopia: plenaries and oral presentations

OpenAIRE

Gitta, Sheba Nakacubo; Mwesiga, Allan; Kamadjeu, Raoul; Stanley, Claire; Borchert, Jeff; Mensah, George; Bejtullahu, Armand; Kamadjeu, Raoul; Kebede, Amha; Berhane, Yemane; Jocker, Mathew Lado; Ebontane, Ndode Corlins; Feyissa, Daba; Yeshitila, Kidanie; Mehari, Goitom

2015-01-01

Biennially, trainees and graduates of Field Epidemiology and Laboratory Training Programs (FELTPs) are presented with a platform to share investigations and projects undertaken during their two-year training in Applied Epidemiology. The African Field Epidemiology Network (AFENET) Scientific Conference, is a perfect opportunity for public health professionals from various sectors and organizations to come together to discuss issues that impact on public health in Africa. This year's conference...

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

PTSD symptomics: network analyses in the field of psychotraumatology.

Science.gov (United States)

Armour, Cherie; Fried, Eiko I; Olff, Miranda

2017-01-01

Recent years have seen increasing attention on posttraumatic stress disorder (PTSD) research. While research has largely focused on the dichotomy between patients diagnosed with mental disorders and healthy controls - in other words, investigations at the level of diagnoses - recent work has focused on psychopathology symptoms. Symptomics research in the area of PTSD has been scarce so far, although several studies have focused on investigating the network structures of PTSD symptoms. The present special issue of EJPT adds to the literature by curating additional PTSD network studies, each looking at a different aspect of PTSD. We hope that this special issue encourages researchers to conceptualize and model PTSD data from a network perspective, which arguably has the potential to inform and improve the efficacy of therapeutic interventions.

Spatial networks

Science.gov (United States)

Barthélemy, Marc

2011-02-01

Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

7th Workshop on Complex Networks

CERN Document Server

Gonçalves, Bruno; Menezes, Ronaldo; Sinatra, Roberta

2016-01-01

The last decades have seen the emergence of Complex Networks as the language with which a wide range of complex phenomena in fields as diverse as Physics, Computer Science, and Medicine (to name just a few) can be properly described and understood. This book provides a view of the state of the art in this dynamic field and covers topics ranging from network controllability, social structure, online behavior, recommendation systems, and network structure. This book includes the peer-reviewed list of works presented at the 7th Workshop on Complex Networks CompleNet 2016 which was hosted by the Université de Bourgogne, France, from March 23-25, 2016. The 28 carefully reviewed and selected contributions in this book address many topics related to complex networks and have been organized in seven major groups: (1) Theory of Complex Networks, (2) Multilayer networks, (3) Controllability of networks, (4) Algorithms for networks, (5) Community detection, (6) Dynamics and spreading phenomena on networks, (7) Applicat...

Neural Networks: Implementations and Applications

OpenAIRE

Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

1996-01-01

Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

Creative Network Communities in the Translocal Space of Digital Networks

Directory of Open Access Journals (Sweden)

Rasa Smite

2013-01-01

Full Text Available What should sociological research be in the age of Web 2.0? Considering that the task of “network sociology” is not only empirical research but also the interpretation of tendencies of the network culture, this research explores the rise of network communities within Eastern and Western Europe in the early Internet era. I coined the term creative networks to distinguish these early creative and social activities from today’s popular social networking. Thus I aimed to interpret the meaning of social action; the motivation of creative community actors, their main fields of activities and social organization forms; and the potential that these early developments contain for the future sustainability of networks. Data comprise interviews with networking experts and founders and members of various networks. Investigating respondents’ motivations for creating online networks and communities, and interpreting those terms, allows for comparing the creative networks of the 1990s with today’s social networks and for drawing conclusions.

[Jacqueline Wilson. Tracy Beakeri sari] / Krista Kivisalu

Index Scriptorium Estoniae

Kivisalu, Krista, 1968-

2016-01-01

Tutvustus: Wilson, Jacqueline. Tracy Beakeri lugu. [Tallinn] : Pegasus, 2015 ; Wilson, Jacqueline. Pühadeüllatus. [Tallinn] : Pegasus, c2015 ; Wilson, Jacqueline. Julgusmäng. [Tallinn] : Pegasus, c2015

PTSD symptomics: network analyses in the field of psychotraumatology

Science.gov (United States)

Armour, Cherie; Fried, Eiko I.; Olff, Miranda

2017-01-01

ABSTRACT Recent years have seen increasing attention on posttraumatic stress disorder (PTSD) research. While research has largely focused on the dichotomy between patients diagnosed with mental disorders and healthy controls — in other words, investigations at the level of diagnoses — recent work has focused on psychopathology symptoms. Symptomics research in the area of PTSD has been scarce so far, although several studies have focused on investigating the network structures of PTSD symptoms. The present special issue of EJPT adds to the literature by curating additional PTSD network studies, each looking at a different aspect of PTSD. We hope that this special issue encourages researchers to conceptualize and model PTSD data from a network perspective, which arguably has the potential to inform and improve the efficacy of therapeutic interventions. PMID:29250305

Social Networks and Externalities from Gift Exchange: Evidence from A Field Experiment.

Science.gov (United States)

Currie, Janet; Lin, Wanchuan; Meng, Juanjuan

2013-11-01

This paper asks whether gift exchange generates externalities for people outside of the bilateral relationship between the gift giver and recipient, and whether the nature of this relationship is affected by social networks. We examine this question in the context of a field experiment in urban Chinese hospital outpatient clinics. We first show that when patients give a small gift, doctors reciprocate with better service and a fewer unnecessary prescriptions of antibiotics. We then show that gift giving creates externalities for third parties. If two patients, A and B are perceived as unrelated, B receives worse care when A gives a gift. However, if A identifies B as a friend, then both A and B benefit from A's gift giving. Hence, we show that gift giving can create positive or negative externalities, depending on the giver's social distance to the third party.

A balanced memory network.

Directory of Open Access Journals (Sweden)

Yasser Roudi

2007-09-01

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

Simulation of tungsten armour cracking due to small ELMs in ITER

International Nuclear Information System (INIS)

Pestchanyi, S.; Garkusha, I.; Landman, I.

2010-01-01

Simulations of tungsten armour cracking under small ELM-like plasma heat load, which does not cause surface melting, have been performed using the PEGASUS-3D code. A dedicated series of experiments have been performed in the QSPA-Kh50 facility for measurements of the unknown tungsten thermophysical properties and for verification of the PEGASUS-3D simulation results. The simulations revealed that a cellular crack network with average mesh size Λ ∼ 0.5 mm formed after first ELMs and the pattern does not change further. With increasing number of repetitive ELMs loads, the average crack width Δ(n) has a maximum value Δ m . The ratio of Δ m /Λ is equal to the tungsten thermal expansion at the maximum surface temperature. Δ(n) tends to this value exponentially. The number of ELMs n m needed for Δ stabilization depends on the ELMs energy density and time duration, n m ∼ 300 for the simulated ELMs of 0.45 MJ/m 2 and 0.25 ms duration. The PEGASUS-3D code is prepared for simulations of tungsten armour damage under action of ELMs of various energy deposition and time duration. These parameters of ELMs depend on ITER regimes of operation and on how successful will be the efforts on ELMs mitigation.

Electromagnetic Fields and Public Health: Mobile Phones

Science.gov (United States)

... waves through a network of fixed antennas called base stations. Radiofrequency waves are electromagnetic fields, and unlike ionizing radiation ... waves through a network of fixed antennas called base stations. Radiofrequency waves are electromagnetic fields, and unlike ionizing radiation ...

Networked Thermodynamic Boundary Layer Profiling with AERIs during the PECAN Field Campaign

Science.gov (United States)

Gero, P. J.; Turner, D. D.; Hackel, D.; Phillips, C.; Smith, N.; Wagner, T.

2015-12-01

The Plains Elevated Convection at Night (PECAN) campaign was a large-scale field experiment in the Great Plains region of the U.S. that was conducted in June-July 2015. Nocturnal storms provide the majority of the precipitation in the Great Plains, yet the initiation and evolution of nocturnal convection is not understood to the same level as daytime surface-based convection, and thus provides significant challenges for operational weather forecasters. PECAN's objectives were to study elevated nocturnal convection initiation and the lifecycle of nocturnal convection. Specific research areas that were studied were the evolution of mesoscale convective systems, the structure and evolution of nocturnal low-level jets, atmospheric bores, and elevated convection initiation. A broad range of fixed and mobile observing systems were deployed by several agencies and organizations in a domain centered around Kansas. The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based instrument that measures downwelling infrared radiance from the atmosphere. AERI observations can be used to obtain vertical profiles of tropospheric temperature and water vapor in the lowest 3 km of the troposphere, as well as measurements of the concentration of various trace gases and microphysical and optical properties of clouds and aerosols. A network of eight AERIs was deployed in the domain during PECAN, with six at fixed sites and two in mobile facilities. One of the goals of the campaign was a demonstration of the use of real-time high-temporal-resolution boundary layer profiles from the network of AERIs for characterizing the mesoscale environment and its evolution during the weather events sampled during PECAN. If successful, a future network could be implemented across CONUS and thermodynamic profiles in the boundary layer data assimilated to help improve numerical weather prediction. We present an overview of the AERI deployments, a summary of the technique used to retrieve

A contribution from dielectric analysis to the study of the formation of multi-wall carbon nanotubes percolated networks in epoxy resin under an electric field

International Nuclear Information System (INIS)

Risi, Celso L.S.; Hattenhauer, Irineu; Ramos, Airton; Coelho, Luiz A.F.; Pezzin, Sérgio H.

2015-01-01

The formation of percolation networks in epoxy matrix nanocomposites reinforced with multi-wall carbon nanotubes (MWNT) during the curing process, at different MWNT contents, was studied by using a parallel plate cell subjected to a 300 V/cm AC electric field at 1 kHz. The percolation was verified by the electrical current output measured during and after the resin curing. The behavior of electric dipoles was characterized by impedance spectroscopy and followed the Debye first order dispersion model, by which an average relaxation time of 6.0 × 10 −4 s and a cut-off frequency of 1.7 kHz were experimentally found. By applying the theory of percolation, a critical probability, p c , equal to 0.038 vol% and an exponent of conductivity of 2.0 were found. Both aligned and random samples showed dipole relaxation times typical of interfacial and/or charge-hopping polarization, while the permittivity exhibited an exponential decrease with frequency. This behavior can be related to the increased ability to trap electrical charges due to the formation of the carbon nanotubes network. Optical and electron microscopies confirm the theoretical prediction that the application of an electric field during cure helps the process of MWNT debundling in epoxy resin. - Highlights: • We report the formation of percolating networks of MWNTs under AC electric field. • MWNT/epoxy dielectric properties were measured by impedance spectroscopy. • Lower percolation thresholds were obtained for composites with aligned CNTs. • Application of AC electric field helps the debundling of CNTs. • CNT/Epoxy with percolated networks presents interfacial and hopping polarizations

Vector Network Coding

OpenAIRE

Ebrahimi, Javad; Fragouli, Christina

2010-01-01

We develop new algebraic algorithms for scalar and vector network coding. In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying them with L X L coding matrices that play a similar role as coding coefficients in scalar coding. Our algorithms for scalar network jointly optimize the employed field size while selecting the coding coefficients. Similarly, for vector co...

Network function virtualization concepts and applicability in 5G networks

CERN Document Server

Zhang, Ying

2018-01-01

A horizontal view of newly emerged technologies in the field of network function virtualization (NFV), introducing the open source implementation efforts that bring NFV from design to reality This book explores the newly emerged technique of network function virtualization (NFV) through use cases, architecture, and challenges, as well as standardization and open source implementations. It is the first systematic source of information about cloud technologies' usage in the cellular network, covering the interplay of different technologies, the discussion of different design choices, and its impact on our future cellular network. Network Function Virtualization: Concepts and Applicability in 5G Networks reviews new technologies that enable NFV, such as Software Defined Networks (SDN), network virtualization, and cloud computing. It also provides an in-depth investigation of the most advanced open source initiatives in this area, including OPNFV, Openstack, and Opendaylight. Finally, this book goes beyond li...

Control of collective network chaos.

Science.gov (United States)

Wagemakers, Alexandre; Barreto, Ernest; Sanjuán, Miguel A F; So, Paul

2014-06-01

Under certain conditions, the collective behavior of a large globally-coupled heterogeneous network of coupled oscillators, as quantified by the macroscopic mean field or order parameter, can exhibit low-dimensional chaotic behavior. Recent advances describe how a small set of "reduced" ordinary differential equations can be derived that captures this mean field behavior. Here, we show that chaos control algorithms designed using the reduced equations can be successfully applied to imperfect realizations of the full network. To systematically study the effectiveness of this technique, we measure the quality of control as we relax conditions that are required for the strict accuracy of the reduced equations, and hence, the controller. Although the effects are network-dependent, we show that the method is effective for surprisingly small networks, for modest departures from global coupling, and even with mild inaccuracy in the estimate of network heterogeneity.

Neural network modeling for near wall turbulent flow

International Nuclear Information System (INIS)

Milano, Michele; Koumoutsakos, Petros

2002-01-01

A neural network methodology is developed in order to reconstruct the near wall field in a turbulent flow by exploiting flow fields provided by direct numerical simulations. The results obtained from the neural network methodology are compared with the results obtained from prediction and reconstruction using proper orthogonal decomposition (POD). Using the property that the POD is equivalent to a specific linear neural network, a nonlinear neural network extension is presented. It is shown that for a relatively small additional computational cost nonlinear neural networks provide us with improved reconstruction and prediction capabilities for the near wall velocity fields. Based on these results advantages and drawbacks of both approaches are discussed with an outlook toward the development of near wall models for turbulence modeling and control

Assessment of Foetal Exposure to the Homogeneous Magnetic Field Harmonic Spectrum Generated by Electricity Transmission and Distribution Networks

Directory of Open Access Journals (Sweden)

Serena Fiocchi

2015-04-01

Full Text Available During the last decades studies addressing the effects of exposure to Extremely Low Frequency Electromagnetic Fields (ELF-EMF have pointed out a possible link between those fields emitted by power lines and childhood leukaemia. They have also stressed the importance of also including in the assessment the contribution of frequency components, namely harmonics, other than the fundamental one. Based on the spectrum of supply voltage networks allowed by the European standard for electricity quality assessment, in this study the exposure of high-resolution three-dimensional models of foetuses to the whole harmonic content of a uniform magnetic field with a fundamental frequency of 50 Hz, was assessed. The results show that the main contribution in terms of induced electric fields to the foetal exposure is given by the fundamental frequency component. The harmonic components add some contributions to the overall level of electric fields, however, due to the extremely low permitted amplitude of the harmonic components with respect to the fundamental, their amplitudes are low. The level of the induced electric field is also much lower than the limits suggested by the guidelines for general public exposure, when the amplitude of the incident magnetic field is set at the maximum permitted level.

Microsoft Windows networking essentials

CERN Document Server

Gibson, Darril

2011-01-01

The core concepts and technologies of Windows networking Networking can be a complex topic, especially for those new to the field of IT. This focused, full-color book takes a unique approach to teaching Windows networking to beginners by stripping down a network to its bare basics, thereby making each topic clear and easy to understand. Focusing on the new Microsoft Technology Associate (MTA) program, this book pares down to just the essentials, showing beginners how to gain a solid foundation for understanding networking concepts upon which more advanced topics and technologies can be built.

Social Networks and Externalities from Gift Exchange: Evidence from A Field Experiment☆

Science.gov (United States)

Currie, Janet; Lin, Wanchuan; Meng, Juanjuan

2016-01-01

This paper asks whether gift exchange generates externalities for people outside of the bilateral relationship between the gift giver and recipient, and whether the nature of this relationship is affected by social networks. We examine this question in the context of a field experiment in urban Chinese hospital outpatient clinics. We first show that when patients give a small gift, doctors reciprocate with better service and a fewer unnecessary prescriptions of antibiotics. We then show that gift giving creates externalities for third parties. If two patients, A and B are perceived as unrelated, B receives worse care when A gives a gift. However, if A identifies B as a friend, then both A and B benefit from A’s gift giving. Hence, we show that gift giving can create positive or negative externalities, depending on the giver’s social distance to the third party. PMID:26949272

Electric field induced localization phenomena in a ladder network with superlattice configuration: Effect of backbone environment

Energy Technology Data Exchange (ETDEWEB)

Dutta, Paramita; Karmakar, S. N. [Condensed Matter Physics Division, Saha Institute of Nuclear Physics, Sector-I, Block-AF, Bidhannagar, Kolkata-700 064 (India); Maiti, Santanu K., E-mail: santanu.maiti@isical.ac.in [Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 Barrackpore Trunk Road, Kolkata-700 108 (India)

2014-09-15

Electric field induced localization properties of a tight-binding ladder network in presence of backbone sites are investigated. Based on Green's function formalism we numerically calculate two-terminal transport together with density of states for different arrangements of atomic sites in the ladder and its backbone. Our results lead to a possibility of getting multiple mobility edges which essentially plays a switching action between a completely opaque to fully or partly conducting region upon the variation of system Fermi energy, and thus, support in fabricating mesoscopic or DNA-based switching devices.

Securing Mobile Networks in an Operational Setting

Science.gov (United States)

Ivancic, William D.; Stewart, David H.; Bell, Terry L.; Paulsen, Phillip E.; Shell, Dan

2004-01-01

This paper describes a network demonstration and three month field trial of mobile networking using mobile-IPv4. The network was implemented as part of the US Coast Guard operational network which is a ".mil" network and requires stringent levels of security. The initial demonstrations took place in November 2002 and a three month field trial took place from July through September of 2003. The mobile network utilized encryptors capable of NSA-approved Type 1 algorithms, mobile router from Cisco Systems and 802.11 and satellite wireless links. This paper also describes a conceptual architecture for wide-scale deployment of secure mobile networking in operational environments where both private and public infrastructure is used. Additional issues presented include link costs, placement of encryptors and running routing protocols over layer-3 encryption devices.

Synthetic biological networks

International Nuclear Information System (INIS)

Archer, Eric; Süel, Gürol M

2013-01-01

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

[Raamat] / Elina Kalm

Index Scriptorium Estoniae

Kalm, Elina

2007-01-01

Tutvustus: Stroud, Jonathan. Samarkandi amulett / tlk. Bibi Raid. Tallinn : Pegasus, 2005 ; Stroud, Jonathan. Golemi silm / tlk. Bibi Raid. Tallinn : Pegasus, 2007 ; Stroud, Jonathan. Ptolemaiose värav / tlk. Bibi Raid. Tallinn : Pegasus, 2007. (Bartimaeuse triloogia ; 1-3)

Enabling software defined networking experiments in networked critical infrastructures

Directory of Open Access Journals (Sweden)

Béla Genge

2014-05-01

Full Text Available Nowadays, the fact that Networked Critical Infrastructures (NCI, e.g., power plants, water plants, oil and gas distribution infrastructures, and electricity grids, are targeted by significant cyber threats is well known. Nevertheless, recent research has shown that specific characteristics of NCI can be exploited in the enabling of more efficient mitigation techniques, while novel techniques from the field of IP networks can bring significant advantages. In this paper we explore the interconnection of NCI communication infrastructures with Software Defined Networking (SDN-enabled network topologies. SDN provides the means to create virtual networking services and to implement global networking decisions. It relies on OpenFlow to enable communication with remote devices and has been recently categorized as the “Next Big Technology”, which will revolutionize the way decisions are implemented in switches and routers. Therefore, the paper documents the first steps towards enabling an SDN-NCI and presents the impact of a Denial of Service experiment over traffic resulting from an XBee sensor network which is routed across an emulated SDN network.

Competing edge networks

Science.gov (United States)

Parsons, Mark; Grindrod, Peter

2012-06-01

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

Troubleshooting of Software Defined Networks

OpenAIRE

Sistek, Haris

2015-01-01

Network troubleshooting is a field where automation is sorely needed. While the network has grown in many other ways since 1960s, the tools we use to troubleshoot and manage it have stayed very much the same. Could we use the programmability of SDN to automate this problem? In this thesis work, we developed a prototype that would systematically troubleshoot the network with automation. The prototype automatically captures network behaviour, matches it against a network policy and creates its ...

Basic Geomagnetic Network of the Republic of Croatia 2004 – 2012, with Geomagnetic Field Maps for 2009.5 epoch

Directory of Open Access Journals (Sweden)

Mario Brkić

2013-12-01

Full Text Available After more than half a century, scientific book Basic Geomagnetic Network of the Republic of Croatia 2004 – 2012, with Geomagnetic Field Maps for 2009.5 epoch describes the recent geomagnetic field on Croatian territory. A review of research in the past decade as well as the original solutions makes the book a document of contribution to geodesy and geomagnetism in Croatia.The book’s introduction gives an overview of two centuries of history and the strategic, security, economic and scientific significance of knowing the geomagnetic field on the Croatian territory. All the activities related to the updating of the geomagnetic information, which took place in the last decade, signified a big step toward the countries where geomagnetic survey is a mature scientific and technical discipline, and a scientific contribution to understanding of the nature of the Earth's magnetism.The declination, inclination and total intensity maps (along with the normal annual changes for the epoch 2009.5 are given in the Appendix. The book Basic Geomagnetic Network of the Republic of Croatia 2004 – 2012, with Geomagnetic Field Maps for 2009.5 epoch (ISBN 978-953-293-521-9 is published by the State Geodetic Administration of the Republic of Croatia. Beside editor in chief, M. Brkić, the authors are: E. Vujić, D. Šugar, E. Jungwirth, D. Markovinović, M. Rezo, M. Pavasović, O. Bjelotomić, M. Šljivarić, M. Varga and V. Poslončec-Petrić. The book contains 48 pages and 3 maps, and is published in 200 copies. CIP record is available in digital catalogue of the National and University Library in Zagreb under number 861937.

Network Warrior

CERN Document Server

Donahue, Gary

2011-01-01

Pick up where certification exams leave off. With this practical, in-depth guide to the entire network infrastructure, you'll learn how to deal with real Cisco networks, rather than the hypothetical situations presented on exams like the CCNA. Network Warrior takes you step by step through the world of routers, switches, firewalls, and other technologies based on the author's extensive field experience. You'll find new content for MPLS, IPv6, VoIP, and wireless in this completely revised second edition, along with examples of Cisco Nexus 5000 and 7000 switches throughout. Topics include: An

Photospheric network from study of manganese lines

Energy Technology Data Exchange (ETDEWEB)

Elste, G; Teske, R G [Michigan Univ., Ann Arbor (USA). Dept. of Astronomy

1978-10-01

Area scans with the multi-channel magnetograph at the Kitt Peak McMath Telescope provided simultaneous measures of equivalent widths in two Mn lines, continuum intensity and longitudinal magnetic field component. Observations were carried out with apertures of 2.5 X 3.5 seconds arc and 1 X 1 seconds arc. For the network elements, which were identified using the magnetic field as tracer, the authors developed relationships between Isub(continuum), Wsub(lambda), Vsub(Doppler) and longitudinal field strength. With a minimum of assumptions it is possible to write from these observed relations an expression connecting true temperature perturbation in the line forming layers of the network to true longitudinal field strength. The results provide some constraints upon possible network models.

Wireless Sensor Network Handles Image Data

Science.gov (United States)

2008-01-01

To relay data from remote locations for NASA s Earth sciences research, Goddard Space Flight Center contributed to the development of "microservers" (wireless sensor network nodes), which are now used commercially as a quick and affordable means to capture and distribute geographical information, including rich sets of aerial and street-level imagery. NASA began this work out of a necessity for real-time recovery of remote sensor data. These microservers work much like a wireless office network, relaying information between devices. The key difference, however, is that instead of linking workstations within one office, the interconnected microservers operate miles away from one another. This attribute traces back to the technology s original use: The microservers were originally designed for seismology on remote glaciers and ice streams in Alaska, Greenland, and Antarctica-acquiring, storing, and relaying data wirelessly between ground sensors. The microservers boast three key attributes. First, a researcher in the field can establish a "managed network" of microservers and rapidly see the data streams (recovered wirelessly) on a field computer. This rapid feedback permits the researcher to reconfigure the network for different purposes over the course of a field campaign. Second, through careful power management, the microservers can dwell unsupervised in the field for up to 2 years, collecting tremendous amounts of data at a research location. The third attribute is the exciting potential to deploy a microserver network that works in synchrony with robotic explorers (e.g., providing ground truth validation for satellites, supporting rovers as they traverse the local environment). Managed networks of remote microservers that relay data unsupervised for up to 2 years can drastically reduce the costs of field instrumentation and data rec

Network value and optimum analysis on the mode of networked marketing in TV media

Directory of Open Access Journals (Sweden)

Xiao Dongpo

2012-12-01

Full Text Available Purpose: With the development of the networked marketing in TV media, it is important to do the research on network value and optimum analysis in this field.Design/methodology/approach: According to the research on the mode of networked marketing in TV media and Correlation theory, the essence of media marketing is creating, spreading and transferring values. The Participants of marketing value activities are in network, and value activities proceed in networked form. Network capability is important to TV media marketing activities.Findings: This article raises the direction of research of analysis and optimization about network based on the mode of networked marketing in TV media by studying TV media marketing Development Mechanism , network analysis and network value structure.

Tactical Network Load Balancing in Multi-Gateway Wireless Sensor Networks

Science.gov (United States)

2013-12-01

communication technology ARPANET Advanced Research Projects Agency Network ASN autonomous sensor network CBR constant bit rate CDMA code...transmission energy NFC near field communication OV1 operational view xxii PA power amplifier RFC request for comment RFID radio frequency identification...fact that the integrated chip (IC) technology boom during the past 20+ years has miniaturized IC hardware while increasing computational capability

Cascades on a stochastic pulse-coupled network

Science.gov (United States)

Wray, C. M.; Bishop, S. R.

2014-09-01

While much recent research has focused on understanding isolated cascades of networks, less attention has been given to dynamical processes on networks exhibiting repeated cascades of opposing influence. An example of this is the dynamic behaviour of financial markets where cascades of buying and selling can occur, even over short timescales. To model these phenomena, a stochastic pulse-coupled oscillator network with upper and lower thresholds is described and analysed. Numerical confirmation of asynchronous and synchronous regimes of the system is presented, along with analytical identification of the fixed point state vector of the asynchronous mean field system. A lower bound for the finite system mean field critical value of network coupling probability is found that separates the asynchronous and synchronous regimes. For the low-dimensional mean field system, a closed-form equation is found for cascade size, in terms of the network coupling probability. Finally, a description of how this model can be applied to interacting agents in a financial market is provided.

Node-to-node field calibration of wireless distributed air pollution sensor network.

Science.gov (United States)

Kizel, Fadi; Etzion, Yael; Shafran-Nathan, Rakefet; Levy, Ilan; Fishbain, Barak; Bartonova, Alena; Broday, David M

2018-02-01

Low-cost air quality sensors offer high-resolution spatiotemporal measurements that can be used for air resources management and exposure estimation. Yet, such sensors require frequent calibration to provide reliable data, since even after a laboratory calibration they might not report correct values when they are deployed in the field, due to interference with other pollutants, as a result of sensitivity to environmental conditions and due to sensor aging and drift. Field calibration has been suggested as a means for overcoming these limitations, with the common strategy involving periodical collocations of the sensors at an air quality monitoring station. However, the cost and complexity involved in relocating numerous sensor nodes back and forth, and the loss of data during the repeated calibration periods make this strategy inefficient. This work examines an alternative approach, a node-to-node (N2N) calibration, where only one sensor in each chain is directly calibrated against the reference measurements and the rest of the sensors are calibrated sequentially one against the other while they are deployed and collocated in pairs. The calibration can be performed multiple times as a routine procedure. This procedure minimizes the total number of sensor relocations, and enables calibration while simultaneously collecting data at the deployment sites. We studied N2N chain calibration and the propagation of the calibration error analytically, computationally and experimentally. The in-situ N2N calibration is shown to be generic and applicable for different pollutants, sensing technologies, sensor platforms, chain lengths, and sensor order within the chain. In particular, we show that chain calibration of three nodes, each calibrated for a week, propagate calibration errors that are similar to those found in direct field calibration. Hence, N2N calibration is shown to be suitable for calibration of distributed sensor networks. Copyright © 2017 Elsevier Ltd. All

Pegasus

Science.gov (United States)

Murdin, P.

2000-11-01

(the Winged Horse; abbrev. Peg, gen. Pegasi; area 1121 sq. deg.) A northern constellation that extends from Cygnus, Lacerta and Andromeda almost to the celestial equator, and culminates at midnight in early September. It is named after the winged horse in Greek mythology that sprang from the body of Medusa, the Gorgon, when she was beheaded by Perseus, and later was tamed by the hero Bellerophon. ...

Multilayer Brain Networks

Science.gov (United States)

Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

Resilient In-Network Aggregation for Vehicular Networks

NARCIS (Netherlands)

Dietzel, Stefan

2015-01-01

Applications for vehicular ad hoc networks (VANETs) are an active field of re- search with the potential to significantly contribute to driver safety, traffic efficiency, and comfort. Messages are typically exchanged and forwarded between vehicles using wireless communication, thereby creating a

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Directory of Open Access Journals (Sweden)

Ion Stiharu

2010-08-01

Full Text Available Computer numerically controlled (CNC machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA-based sensor node.

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

Science.gov (United States)

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

Mapping the Field of Educational Administration Research: A Journal Citation Network Analysis

Science.gov (United States)

Wang, Yinying; Bowers, Alex J.

2016-01-01

Purpose: The purpose of this paper is to uncover how knowledge is exchanged and disseminated in the educational administration research literature through the journal citation network. Design/ Methodology/Approach: Drawing upon social network theory and citation network studies in other disciplines, the authors constructed an educational…

Label-free detection of DNA hybridization using carbon nanotube network field-effect transistors

Science.gov (United States)

Star, Alexander; Tu, Eugene; Niemann, Joseph; Gabriel, Jean-Christophe P.; Joiner, C. Steve; Valcke, Christian

2006-01-01

We report carbon nanotube network field-effect transistors (NTNFETs) that function as selective detectors of DNA immobilization and hybridization. NTNFETs with immobilized synthetic oligonucleotides have been shown to specifically recognize target DNA sequences, including H63D single-nucleotide polymorphism (SNP) discrimination in the HFE gene, responsible for hereditary hemochromatosis. The electronic responses of NTNFETs upon single-stranded DNA immobilization and subsequent DNA hybridization events were confirmed by using fluorescence-labeled oligonucleotides and then were further explored for label-free DNA detection at picomolar to micromolar concentrations. We have also observed a strong effect of DNA counterions on the electronic response, thus suggesting a charge-based mechanism of DNA detection using NTNFET devices. Implementation of label-free electronic detection assays using NTNFETs constitutes an important step toward low-cost, low-complexity, highly sensitive and accurate molecular diagnostics. hemochromatosis | SNP | biosensor

Psychology and social networks: a dynamic network theory perspective.

Science.gov (United States)

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

2014-04-01

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

Towards the integration of social network analysis in an inter-organizational networks perspective

DEFF Research Database (Denmark)

Bergenholtz, Carsten; Waldstrøm, Christian

This conceptual paper deals with the issue of studying inter-organizational networks while applying social network analysis (SNA). SNA is a widely recognized technique in network research, particularly within intra-organizational settings, while there seems to be a significant gap in the inter......-organizational setting. Based on a literature review of both SNA as a methodology and/or theory and the field of inter-organizational networks, the aim is to gain an overview in order to provide a clear setting for SNA in inter-organizational research....

Network-assisted crop systems genetics: network inference and integrative analysis.

Science.gov (United States)

Lee, Tak; Kim, Hyojin; Lee, Insuk

2015-04-01

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

Activities of the senspol and NICOLE network concerning field investigation at contaminated sites

Energy Technology Data Exchange (ETDEWEB)

Ree, C.C.D.F. von [GeoDelft, AB Delft (Netherlands); Alcock, S. [Cranfield Univ. of Silsoe, Bedfordshire (United Kingdom)

2003-07-01

At a European level several networks can be identified aimed at developments and exchange of knowledge relevant to sustainable management of the subsurface. Based on the common interests in the field of site characterisation and monitoring the SENSPOL and NICOLE networks have established links resulting in cooperation in several project-activities. In this presentation two projects will be addressed: - Seville technicalmeeting (Aznacollar mining site). - Bridging gaps between sensor developers and (end) users in a pragmatic approach (GAPS-project). The goal of the Seville technical meeting was to apply the latest sensing technologies at a site contaminated by metal mining activities, to properly evaluate the advances and limitations in the monitoring of contaminated sites for sustainable land management and to determine further steps to commercial exploitation. Some 17 different instruments have been brought including: - Electrochemical sensors using different forms of anodic stripping voltammetry and constant current chronopotentiometry combined with several types of screen printed electrodes. - An amperometric biosensor using screen printed electrodes, which measures toxicity by inhibition effects on urease and its sensitive to Hg(II), Ag(I), Cu(I) and to a lesser extent to Pb(II), Zn(II) and Cd(II) and a selectrochemical DNA biosensor measuring overall toxicity. - A luminescent bacterial sensors for measuring the bioavailable fraction of Cd, Pb, Zn, Cu, As, and Hg, and a bioluminescent fiber optic sensor for Hg and As. - Toxicity testing instruments (Checklight 'ToxScreen Multi-Shot Test, ToxAlert {sup registered} 100 and ToxAlert {sup registered} 10) - A fieldprobe for pH, EC, TDS measurement - A lead automatic analyser AQUAMET using a ion-selective electrode. - Pulse-neutron borehole device in which interaction of neutrons with the surrounding medium can be used to monitor changes. In a two-day field session on the mining site participants were provided

Conception of a course for professional training and education in the field of computer and mobile forensics, part III: network forensics and penetration testing

Science.gov (United States)

Kröger, Knut; Creutzburg, Reiner

2014-02-01

IT security and computer forensics are important components in the information technology. From year to year, incidents and crimes increase that target IT systems or were done with their help. More and more companies and authorities have security problems in their own IT infrastructure. To respond to these incidents professionally, it is important to have well trained staff. The fact that many agencies and companies work with very sensitive data make it necessary to further train the own employees in the field of network forensics and penetration testing. Motivated by these facts, this paper - a continuation of a paper of January 2012 [1], which showed the conception of a course for professional training and education in the field of computer and mobile forensics - addresses the practical implementation important relationships of network forensic and penetration testing.

Untangle network security

CERN Document Server

El-Bawab, Abd El-Monem A

2014-01-01

If you are a security engineer or a system administrator and want to secure your server infrastructure with the feature-rich Untangle, this book is for you. For individuals who want to start their career in the network security field, this book would serve as a perfect companion to learn the basics of network security and how to implement it using Untangle NGFW.

Decentralised electrical distribution network in power plants

International Nuclear Information System (INIS)

Mannila, P.; Lehtonen, M.

2000-02-01

A centralised network is a dominating network solution in today's power plants. In this study a centralised and a decentralised network were designed in order to compare them economically and technically. The emphasis of this study was on economical aspects, but also the most important technical aspects were included. The decentralised network requires less space and less cabling since there is no switchgear building and distribution transformers are placed close to the consumption in the field of a power plant. MV-motors and distribution transformers build up a ring. Less cabling and an absent switchgear building cause considerable savings. Component costs of both of the networks were estimated by using data from fulfilled power plant projects and turned out to be smaller for the decentralised network. Simulations for the decentralised network were done in order to find a way to carry out earth fault protection and location. It was found out that in high resistance earthed system the fault distance can be estimated by a relatively simple method. The decentralised network uses a field bus, which offers many new features to the automation system of a power plant. Diversified information can be collected from the protection devices in order to schedule only the needed maintenance duties at the right time. Through the field bus it is also possible to control remotely a power plant. The decentralised network is built up from ready-to-install modules. These modules are tested by the module manufacturer decreasing the need for field testing dramatically. The work contribution needed in the electrification and the management of a power plant project reduces also due the modules. During the lifetime of a power plant, maintenance is easier and more economical. (orig.)

5th International Workshop on Complex Networks and their Applications

CERN Document Server

Gaito, Sabrina; Quattrociocchi, Walter; Sala, Alessandra

2017-01-01

This book highlights cutting-edge research in the field of network science, offering scientists, researchers and graduate students a unique opportunity to catch up on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the fifth International Workshop on Complex Networks & their Applications (COMPLEX NETWORKS 2016), which took place in Milan during the last week of November 2016. The carefully selected papers are divided into 11 sections reflecting the diversity and richness of research areas in the field. More specifically, the following topics are covered: Network models; Network measures; Community structure; Network dynamics; Diffusion, epidemics and spreading processes; Resilience and control; Network visualization; Social and political networks; Networks in finance and economics; Biological and ecological networks; and Network analysis.

CompTIA Network+ Lab Manual

CERN Document Server

Skandier, Toby

2012-01-01

Gain street-smart skills in network administration Think of the most common and challenging tasks that network administrators face, then read this book and find out how to perform those tasks, step by step. CompTIA Network + Lab Manual provides an inside look into the field of network administration as though you were actually on the job. You'll find a variety of scenarios and potential roadblocks, as well as clearly mapped sections to help you prepare for the CompTIA Network+ Exam N10-005. Learn how to design, implement, configure, maintain, secure, and troubleshoot a network with this street

Organization Virtual or Networked?

Directory of Open Access Journals (Sweden)

Rūta Tamošiūnaitė

2013-08-01

Full Text Available Purpose—to present distinction between “virtual organization” and “networked organization”; giving their definitions.Design/methodology/approach—review of previous researches, systemic analyses of their findings and synthesis of distinctive characteristics of ”virtual organization” and “networked organization.”Findings—the main result of the research is key diverse features separating ”virtual organization” and ”networked organization.” Definitions of “virtual organization” and “networked organization” are presented.Originality/Value—distinction between “virtual organization” and “networked organization” creates possibilities to use all advantages of those types of organizations and gives foundation for deeper researches in this field.Research type: general review.

Computer network time synchronization the network time protocol on earth and in space

CERN Document Server

Mills, David L

2010-01-01

Carefully coordinated, reliable, and accurate time synchronization is vital to a wide spectrum of fields-from air and ground traffic control, to buying and selling goods and services, to TV network programming. Ill-gotten time could even lead to the unimaginable and cause DNS caches to expire, leaving the entire Internet to implode on the root servers.Written by the original developer of the Network Time Protocol (NTP), Computer Network Time Synchronization: The Network Time Protocol on Earth and in Space, Second Edition addresses the technological infrastructure of time dissemination, distrib

Wireless network pricing

CERN Document Server

Huang, Jianwei

2013-01-01

Today's wireless communications and networking practices are tightly coupled with economic considerations, to the extent that it is almost impossible to make a sound technology choice without understanding the corresponding economic implications. This book aims at providing a foundational introduction on how microeconomics, and pricing theory in particular, can help us to understand and build better wireless networks. The book can be used as lecture notes for a course in the field of network economics, or a reference book for wireless engineers and applied economists to understand how pricing

Linking behavior in the physics education research coauthorship network

Science.gov (United States)

Anderson, Katharine A.; Crespi, Matthew; Sayre, Eleanor C.

2017-06-01

There is considerable long-term interest in understanding the dynamics of collaboration networks, and how these networks form and evolve over time. Most of the work done on the dynamics of social networks focuses on well-established communities. Work examining emerging social networks is rarer, simply because data are difficult to obtain in real time. In this paper, we use thirty years of data from an emerging scientific community to look at that crucial early stage in the development of a social network. We show that when the field was very young, islands of individual researchers labored in relative isolation, and the coauthorship network was disconnected. Thirty years later, rather than a cluster of individuals, we find a true collaborative community, bound together by a robust collaboration network. However, this change did not take place gradually—the network remained a loose assortment of isolated individuals until the mid 2000s, when those smaller parts suddenly knit themselves together into a single whole. In the rest of this paper, we consider the role of three factors in these observed structural changes: growth, changes in social norms, and the introduction of institutions such as field-specific conferences and journals. We have data from the very earliest years of the field, a period which includes the introduction of two different institutions: the first field-specific conference, and the first field-specific journals. We also identify two relevant behavioral shifts: a discrete increase in coauthorship coincident with the first conference, and a shift among established authors away from collaborating with outsiders, towards collaborating with each other. The interaction of these factors gives us insight into the formation of collaboration networks more broadly.

Vulnerability and controllability of networks of networks

International Nuclear Information System (INIS)

Liu, Xueming; Peng, Hao; Gao, Jianxi

2015-01-01

Network science is a highly interdisciplinary field ranging from natural science to engineering technology and it has been applied to model complex systems and used to explain their behaviors. Most previous studies have been focus on isolated networks, but many real-world networks do in fact interact with and depend on other networks via dependency connectivities, forming “networks of networks” (NON). The interdependence between networks has been found to largely increase the vulnerability of interacting systems, when a node in one network fails, it usually causes dependent nodes in other networks to fail, which, in turn, may cause further damage on the first network and result in a cascade of failures with sometimes catastrophic consequences, e.g., electrical blackouts caused by the interdependence of power grids and communication networks. The vulnerability of a NON can be analyzed by percolation theory that can be used to predict the critical threshold where a NON collapses. We review here the analytic framework for analyzing the vulnerability of NON, which yields novel percolation laws for n-interdependent networks and also shows that percolation theory of a single network studied extensively in physics and mathematics in the last 50 years is a specific limited case of the more general case of n interacting networks. Understanding the mechanism behind the cascading failure in NON enables us finding methods to decrease the vulnerability of the natural systems and design of more robust infrastructure systems. By examining the vulnerability of NON under targeted attack and studying the real interdependent systems, we find two methods to decrease the systems vulnerability: (1) protect the high-degree nodes, and (2) increase the degree correlation between networks. Furthermore, the ultimate proof of our understanding of natural and technological systems is reflected in our ability to control them. We also review the recent studies and challenges on the

Design of Hybrid Mobile Communication Networks for Planetary Exploration

Science.gov (United States)

Alena, Richard L.; Ossenfort, John; Lee, Charles; Walker, Edward; Stone, Thom

2004-01-01

The Mobile Exploration System Project (MEX) at NASA Ames Research Center has been conducting studies into hybrid communication networks for future planetary missions. These networks consist of space-based communication assets connected to ground-based Internets and planetary surface-based mobile wireless networks. These hybrid mobile networks have been deployed in rugged field locations in the American desert and the Canadian arctic for support of science and simulation activities on at least six occasions. This work has been conducted over the past five years resulting in evolving architectural complexity, improved component characteristics and better analysis and test methods. A rich set of data and techniques have resulted from the development and field testing of the communication network during field expeditions such as the Haughton Mars Project and NASA Mobile Agents Project.

Synchronization in oscillatory networks

CERN Document Server

Osipov, Grigory V; Zhou, Changsong

2007-01-01

The formation of collective behavior in large ensembles or networks of coupled oscillatory elements is one of the oldest and most fundamental aspects of dynamical systems theory. Potential and present applications span a vast spectrum of fields ranging from physics, chemistry, geoscience, through life- and neurosciences to engineering, the economic and the social sciences. This work systematically investigates a large number of oscillatory network configurations that are able to describe many real systems such as electric power grids, lasers or the heart muscle - to name but a few. This book is conceived as an introduction to the field for graduate students in physics and applied mathematics as well as being a compendium for researchers from any field of application interested in quantitative models.

Network Coding Fundamentals and Applications

CERN Document Server

Medard, Muriel

2011-01-01

Network coding is a field of information and coding theory and is a method of attaining maximum information flow in a network. This book is an ideal introduction for the communications and network engineer, working in research and development, who needs an intuitive introduction to network coding and to the increased performance and reliability it offers in many applications. This book is an ideal introduction for the research and development communications and network engineer who needs an intuitive introduction to the theory and wishes to understand the increased performance and reliabil

Inversion of a lateral log using neural networks

International Nuclear Information System (INIS)

Garcia, G.; Whitman, W.W.

1992-01-01

In this paper a technique using neural networks is demonstrated for the inversion of a lateral log. The lateral log is simulated by a finite difference method which in turn is used as an input to a backpropagation neural network. An initial guess earth model is generated from the neural network, which is then input to a Marquardt inversion. The neural network reacts to gross and subtle data features in actual logs and produces a response inferred from the knowledge stored in the network during a training process. The neural network inversion of lateral logs is tested on synthetic and field data. Tests using field data resulted in a final earth model whose simulated lateral is in good agreement with the actual log data

RMBNToolbox: random models for biochemical networks

Directory of Open Access Journals (Sweden)

Niemi Jari

2007-05-01

Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.

Simulation of tungsten armour cracking due to small ELMs in ITER

Energy Technology Data Exchange (ETDEWEB)

Pestchanyi, S., E-mail: sergey.pestchanyi@ihm.fzk.de [Forschungszentrum Karlsruhe, IHM (Germany); Garkusha, I. [Institute of Plasma Physics of the NSC KIPT, Kharkov 61108 (Ukraine); Landman, I. [Forschungszentrum Karlsruhe, IHM (Germany)

2010-12-15

Simulations of tungsten armour cracking under small ELM-like plasma heat load, which does not cause surface melting, have been performed using the PEGASUS-3D code. A dedicated series of experiments have been performed in the QSPA-Kh50 facility for measurements of the unknown tungsten thermophysical properties and for verification of the PEGASUS-3D simulation results. The simulations revealed that a cellular crack network with average mesh size {Lambda} {approx} 0.5 mm formed after first ELMs and the pattern does not change further. With increasing number of repetitive ELMs loads, the average crack width {Delta}(n) has a maximum value {Delta}{sub m}. The ratio of {Delta}{sub m}/{Lambda} is equal to the tungsten thermal expansion at the maximum surface temperature. {Delta}(n) tends to this value exponentially. The number of ELMs n{sub m} needed for {Delta} stabilization depends on the ELMs energy density and time duration, n{sub m} {approx} 300 for the simulated ELMs of 0.45 MJ/m{sup 2} and 0.25 ms duration. The PEGASUS-3D code is prepared for simulations of tungsten armour damage under action of ELMs of various energy deposition and time duration. These parameters of ELMs depend on ITER regimes of operation and on how successful will be the efforts on ELMs mitigation.

Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

Science.gov (United States)

Jalili, Mahdi

2018-03-01

I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

Romanian seismic network

International Nuclear Information System (INIS)

Ionescu, Constantin; Rizescu, Mihaela; Popa, Mihaela; Grigore, Adrian

2000-01-01

The research in the field of seismology in Romania is mainly carried out by the National Institute for Earth Physics (NIEP). The NIEP activities are mainly concerned with the fundamental research financed by research contracts from public sources and the maintenance and operation of the Romanian seismic network. A three stage seismic network is now operating under NIEP, designed mainly to monitor the Vrancea seismic region in a magnitude range from microearthquakes to strong events: - network of 18 short-period seismometers (S13); - Teledyne Geotech Instruments (Texas); - network of 7 stations with local digital recording (PCM-5000) on magnetic tape, made up of, S13 geophone (T=2 s) on vertical component and SH1 geophone (T=5 s) on horizontal components; - network of 28 SMA-1 accelerometers and 30 digital accelerometers (Kinemetrics - K2) installed in the free field conditions in the framework of the joint German-Romanian cooperation program (CRC); the K2 instruments cover a magnitude range from 1.4 to 8.0. Since 1994, MLR (Muntele Rosu) station has become part of the GEOFON network and was provided with high performance broad band instruments. At Bucharest and Timisoara data centers, an automated and networked seismological system performs the on-line digital acquisition and processing of the telemetered data. Automatic processing includes discrimination between local and distant seismic events, earthquake location and magnitude computation, and source parameter determination for local earthquakes. The results are rapidly distributed via Internet, to several seismological services in Europe and USA, to be used in the association/confirmation procedures. Plans for new developments of the network include the upgrade from analog to digital telemetry and new stations for monitoring local seismicity. (authors)

3rd International Winter School and Conference on Network Science

CERN Document Server

Barzel, Baruch; Puzis, Rami

2017-01-01

This book contains original research chapters related to the interdisciplinary field of complex networks spanning biological and environmental networks, social, technological, and economic networks. Many natural phenomena can be modeled as networks where nodes are the primitive compounds and links represent their interactions, similarities, or distances of sorts. Complex networks have an enormous impact on research in various fields like biology, social sciences, engineering, and cyber-security to name a few. The topology of a network often encompasses important information on the functionality and dynamics of the system or the phenomenon it represents. Network science is an emerging interdisciplinary discipline that provides tools and insights to researchers in a variety of domains. NetSci-X is the central winter conference within the field and brings together leading researchers and innovators to connect, meet, and establish interdisciplinary channels for collaboration. It is the largest and best known even...

Endogenous Cortical Oscillations Constrain Neuromodulation by Weak Electric Fields

Science.gov (United States)

Schmidt, Stephen L.; Iyengar, Apoorva K.; Foulser, A. Alban; Boyle, Michael R.; Fröhlich, Flavio

2014-01-01

Background Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation modality that may modulate cognition by enhancing endogenous neocortical oscillations with the application of sine-wave electric fields. Yet, the role of endogenous network activity in enabling and shaping the effects of tACS has remained unclear. Objective We combined optogenetic stimulation and multichannel slice electrophysiology to elucidate how the effect of weak sine-wave electric field depends on the ongoing cortical oscillatory activity. We hypothesized that the structure of the response to stimulation depended on matching the stimulation frequency to the endogenous cortical oscillation. Methods We studied the effect of weak sine-wave electric fields on oscillatory activity in mouse neocortical slices. Optogenetic control of the network activity enabled the generation of in vivo like cortical oscillations for studying the temporal relationship between network activity and sine-wave electric field stimulation. Results Weak electric fields enhanced endogenous oscillations but failed to induce a frequency shift of the ongoing oscillation for stimulation frequencies that were not matched to the endogenous oscillation. This constraint on the effect of electric field stimulation imposed by endogenous network dynamics was limited to the case of weak electric fields targeting in vivo-like network dynamics. Together, these results suggest that the key mechanism of tACS may be enhancing but not overriding of intrinsic network dynamics. Conclusion Our results contribute to understanding the inconsistent tACS results from human studies and propose that stimulation precisely adjusted in frequency to the endogenous oscillations is key to rational design of non-invasive brain stimulation paradigms. PMID:25129402

Contemporary Network Proteomics and Its Requirements

Science.gov (United States)

Goh, Wilson Wen Bin; Wong, Limsoon; Sng, Judy Chia Ghee

2013-01-01

The integration of networks with genomics (network genomics) is a familiar field. Conventional network analysis takes advantage of the larger coverage and relative stability of gene expression measurements. Network proteomics on the other hand has to develop further on two critical factors: (1) expanded data coverage and consistency, and (2) suitable reference network libraries, and data mining from them. Concerning (1) we discuss several contemporary themes that can improve data quality, which in turn will boost the outcome of downstream network analysis. For (2), we focus on network analysis developments, specifically, the need for context-specific networks and essential considerations for localized network analysis. PMID:24833333

Information Potential Fields Navigation in Wireless Ad-Hoc Sensor Networks

Directory of Open Access Journals (Sweden)

Yong Qi

2011-05-01

Full Text Available As wireless sensor networks (WSNs are increasingly being deployed in some important applications, it becomes imperative that we consider application requirements in in-network processes. We intend to use a WSN to aid information querying and navigation within a dynamic and real-time environment. We propose a novel method that relies on the heat diffusion equation to finish the navigation process conveniently and easily. From the perspective of theoretical analysis, our proposed work holds the lower constraint condition. We use multiple scales to reach the goal of accurate navigation. We present a multi-scale gradient descent method to satisfy users’ requirements in WSNs. Formula derivations and simulations show that the method is accurately and efficiently able to solve typical sensor network configuration information navigation problems. Simultaneously, the structure of heat diffusion equation allows more flexibility and adaptability in searching algorithm designs.

Vector Network Coding Algorithms

OpenAIRE

Ebrahimi, Javad; Fragouli, Christina

2010-01-01

We develop new algebraic algorithms for scalar and vector network coding. In vector network coding, the source multicasts information by transmitting vectors of length L, while intermediate nodes process and combine their incoming packets by multiplying them with L x L coding matrices that play a similar role as coding c in scalar coding. Our algorithms for scalar network jointly optimize the employed field size while selecting the coding coefficients. Similarly, for vector coding, our algori...

Proceedings of the African Field Epidemiology Network (AFENET) Scientific Conference 17-22 November 2013 Addis Ababa, Ethiopia: plenaries and oral presentations.

Science.gov (United States)

Gitta, Sheba Nakacubo; Mwesiga, Allan; Kamadjeu, Raoul

2015-01-01

Biennially, trainees and graduates of Field Epidemiology and Laboratory Training Programs (FELTPs) are presented with a platform to share investigations and projects undertaken during their two-year training in Applied Epidemiology. The African Field Epidemiology Network (AFENET) Scientific Conference, is a perfect opportunity for public health professionals from various sectors and organizations to come together to discuss issues that impact on public health in Africa. This year's conference was organized by the Ethiopian Health and Nutrition Research Institute in collaboration with the Ethiopia Ministry of Health, Ethiopian Public Health Association (EPHA), Ethiopia Field Epidemiology Training Program (EFETP), Addis Ababa University (AAU), Training Programs in Epidemiology and Public Health Interventions Network (TEPHINET) and AFENET. Participants at this year's conference numbered 400 from over 20 countries including; Angola, Burkina Faso, Cameroon, Central African Republic, Democratic Republic of the Congo, Ethiopia, Ghana, Indonesia, Kenya, Mozambique, Namibia, Nigeria, Rwanda, South Africa, Sudan, Tanzania, Uganda, Yemen and Zimbabwe. The topics covered in the 144 oral presentations included: global health security, emergency response, public health informatics, vaccine preventable diseases, immunization, outbreak investigation, Millennium Development Goals, Non-Communicable Diseases, and public health surveillance. The theme for the 5th AFENET Scientific Conference was; "Addressing Public Health Priorities in Africa through FELTPs." Previous AFENET Scientific conferences have been held in: Accra, Ghana (2005), Kampala, Uganda (2007), Mombasa, Kenya (2009) and Dar es Salaam, Tanzania (2011).

Far-field tsunami of 2017 Mw 8.1 Tehuantepec, Mexico earthquake recorded by Chilean tide gauge network: Implications for tsunami warning systems

Science.gov (United States)

González-Carrasco, J. F.; Benavente, R. F.; Zelaya, C.; Núñez, C.; Gonzalez, G.

2017-12-01

The 2017 Mw 8.1, Tehuantepec earthquake generated a moderated tsunami, which was registered in near-field tide gauges network activating a tsunami threat state for Mexico issued by PTWC. In the case of Chile, the forecast of tsunami waves indicate amplitudes less than 0.3 meters above the tide level, advising an informative state of threat, without activation of evacuation procedures. Nevertheless, during sea level monitoring of network we detect wave amplitudes (> 0.3 m) indicating a possible change of threat state. Finally, NTWS maintains informative level of threat based on mathematical filtering analysis of sea level records. After 2010 Mw 8.8, Maule earthquake, the Chilean National Tsunami Warning System (NTWS) has increased its observational capabilities to improve early response. Most important operational efforts have focused on strengthening tide gauge network for national area of responsibility. Furthermore, technological initiatives as Integrated Tsunami Prediction and Warning System (SIPAT) has segmented the area of responsibility in blocks to focus early warning and evacuation procedures on most affected coastal areas, while maintaining an informative state for distant areas of near-field earthquake. In the case of far-field events, NTWS follow the recommendations proposed by Pacific Tsunami Warning Center (PTWC), including a comprehensive monitoring of sea level records, such as tide gauges and DART (Deep-Ocean Assessment and Reporting of Tsunami) buoys, to evaluate the state of tsunami threat in the area of responsibility. The main objective of this work is to analyze the first-order physical processes involved in the far-field propagation and coastal impact of tsunami, including implications for decision-making of NTWS. To explore our main question, we construct a finite-fault model of the 2017, Mw 8.1 Tehuantepec earthquake. We employ the rupture model to simulate a transoceanic tsunami modeled by Neowave2D. We generate synthetic time series at

Assessment of voltage dips based on field measurements in MV networks

NARCIS (Netherlands)

Weldemariam, L.E.; Papathanasiou, F.; Cuk, V.; Cobben, J.F.G.; Kling, W.L.

Voltage dip is considered as the PQ problem related to the highest financial losses for the customers. It occurs unpredictably mainly due to short-circuit faults in the networks. Network operators and customers want to know more about the occurrence and the potential impact of voltage dips. PQ

Linking behavior in the physics education research coauthorship network

Directory of Open Access Journals (Sweden)

Katharine A. Anderson

2017-05-01

Full Text Available There is considerable long-term interest in understanding the dynamics of collaboration networks, and how these networks form and evolve over time. Most of the work done on the dynamics of social networks focuses on well-established communities. Work examining emerging social networks is rarer, simply because data are difficult to obtain in real time. In this paper, we use thirty years of data from an emerging scientific community to look at that crucial early stage in the development of a social network. We show that when the field was very young, islands of individual researchers labored in relative isolation, and the coauthorship network was disconnected. Thirty years later, rather than a cluster of individuals, we find a true collaborative community, bound together by a robust collaboration network. However, this change did not take place gradually—the network remained a loose assortment of isolated individuals until the mid 2000s, when those smaller parts suddenly knit themselves together into a single whole. In the rest of this paper, we consider the role of three factors in these observed structural changes: growth, changes in social norms, and the introduction of institutions such as field-specific conferences and journals. We have data from the very earliest years of the field, a period which includes the introduction of two different institutions: the first field-specific conference, and the first field-specific journals. We also identify two relevant behavioral shifts: a discrete increase in coauthorship coincident with the first conference, and a shift among established authors away from collaborating with outsiders, towards collaborating with each other. The interaction of these factors gives us insight into the formation of collaboration networks more broadly.

Network Survivability

DEFF Research Database (Denmark)

Marzo, José L.; Stidsen, Thomas Riis; Ruepp, Sarah Renée

2010-01-01

– are vital to modern services such as mobile telephony, online banking and VoIP. This book examines communication networking from a mathematical viewpoint. The contributing authors took part in the European COST action 293 – a four-year program of multidisciplinary research on this subject. In this book...... they offer introductory overviews and state-of-the-art assessments of current and future research in the fields of broadband, optical, wireless and ad hoc networks. Particular topics of interest are design, optimization, robustness and energy consumption. The book will be of interest to graduate students......, researchers and practitioners in the areas of networking, theoretical computer science, operations research, distributed computing and mathematics....

Neural network prediction of carbonate lithofacies from well logs, Big Bow and Sand Arroyo Creek fields, Southwest Kansas

Science.gov (United States)

Qi, L.; Carr, T.R.

2006-01-01

In the Hugoton Embayment of southwestern Kansas, St. Louis Limestone reservoirs have relatively low recovery efficiencies, attributed to the heterogeneous nature of the oolitic deposits. This study establishes quantitative relationships between digital well logs and core description data, and applies these relationships in a probabilistic sense to predict lithofacies in 90 uncored wells across the Big Bow and Sand Arroyo Creek fields. In 10 wells, a single hidden-layer neural network based on digital well logs and core described lithofacies of the limestone depositional texture was used to train and establish a non-linear relationship between lithofacies assignments from detailed core descriptions and selected log curves. Neural network models were optimized by selecting six predictor variables and automated cross-validation with neural network parameters and then used to predict lithofacies on the whole data set of the 2023 half-foot intervals from the 10 cored wells with the selected network size of 35 and a damping parameter of 0.01. Predicted lithofacies results compared to actual lithofacies displays absolute accuracies of 70.37-90.82%. Incorporating adjoining lithofacies, within-one lithofacies improves accuracy slightly (93.72%). Digital logs from uncored wells were batch processed to predict lithofacies and probabilities related to each lithofacies at half-foot resolution corresponding to log units. The results were used to construct interpolated cross-sections and useful depositional patterns of St. Louis lithofacies were illustrated, e.g., the concentration of oolitic deposits (including lithofacies 5 and 6) along local highs and the relative dominance of quartz-rich carbonate grainstone (lithofacies 1) in the zones A and B of the St. Louis Limestone. Neural network techniques are applicable to other complex reservoirs, in which facies geometry and distribution are the key factors controlling heterogeneity and distribution of rock properties. Future work

Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

DEFF Research Database (Denmark)

Mazzoni, Alberto; Linden, Henrik; Cuntz, Hermann

2015-01-01

Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local f...... in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo....

Advanced Applications of Neural Networks and Artificial Intelligence: A Review

OpenAIRE

Koushal Kumar; Gour Sundar Mitra Thakur

2012-01-01

Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

Thin Watts-Strogatz networks.

Science.gov (United States)

de Moura, Alessandro P S

2006-01-01

A modified version of the Watts-Strogatz (WS) network model is proposed, in which the number of shortcuts scales with the network size N as Nalpha, with alpha infinity, whereas in the original WS model, this ratio is constant. We call such networks "thin Watts-Strogatz networks." We show that even though the fraction of shortcuts becomes vanishingly small for large networks, they still cause a kind of small-world effect, in the sense that the length L of the network increases sublinearly with the size. We develop a mean-field theory for these networks, which predicts that the length scales as N1-alpha ln N for large N. We also study how a search using only local information works in thin WS networks. We find that the search performance is enhanced compared to the regular network, and we predict that the search time tau scales as N1-alpha/2. These theoretical results are tested using numerical simulations. We comment on the possible relevance of thin WS networks for the design of high-performance low-cost communication networks.

A general evolving model for growing bipartite networks

International Nuclear Information System (INIS)

Tian, Lixin; He, Yinghuan; Liu, Haijun; Du, Ruijin

2012-01-01

In this Letter, we propose and study an inner evolving bipartite network model. Significantly, we prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. Furthermore, the joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks. Numerical simulations and empirical results are given to verify the theoretical results. -- Highlights: ► We proposed a general evolving bipartite network model which was based on priority connection, reconnection and breaking edges. ► We prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. ► The joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. ► The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks.

Wireless network security theories and applications

CERN Document Server

Chen, Lei; Zhang, Zihong

2013-01-01

Wireless Network Security Theories and Applications discusses the relevant security technologies, vulnerabilities, and potential threats, and introduces the corresponding security standards and protocols, as well as provides solutions to security concerns. Authors of each chapter in this book, mostly top researchers in relevant research fields in the U.S. and China, presented their research findings and results about the security of the following types of wireless networks: Wireless Cellular Networks, Wireless Local Area Networks (WLANs), Wireless Metropolitan Area Networks (WMANs), Bluetooth

Multilayer network modeling creates opportunities for novel network statistics. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

Science.gov (United States)

Muldoon, Sarah Feldt

2018-03-01

As described in the review by Gosak et al., the field of network science has had enormous success in providing new insights into the structure and function of biological systems [1]. In the complex networks framework, system elements are network nodes, and connections between nodes represent some form of interaction between system elements [2]. The flexibility to define network nodes and edges to represent different aspects of biological systems has been employed to model numerous diverse systems at multiple scales.

Supply network science: Emergence of a new perspective on a classical field

Science.gov (United States)

Brintrup, Alexandra; Ledwoch, Anna

2018-03-01

Supply networks emerge as companies procure goods from one another to produce their own products. Due to a chronic lack of data, studies on these emergent structures have long focussed on local neighbourhoods, assuming simple, chain-like structures. However, studies conducted since 2001 have shown that supply chains are indeed complex networks that exhibit similar organisational patterns to other network types. In this paper, we present a critical review of theoretical and model based studies which conceptualise supply chains from a network science perspective, showing that empirical data do not always support theoretical models that were developed, and argue that different industrial settings may present different characteristics. Consequently, a need that arises is the development and reconciliation of interpretation across different supply network layers such as contractual relations, material flow, financial links, and co-patenting, as these different projections tend to remain in disciplinary siloes. Other gaps include a lack of null models that show whether the observed properties are meaningful, a lack of dynamical models that can inform how layers evolve and adopt to changes, and a lack of studies that investigate how local decisions enable emergent outcomes. We conclude by asking the network science community to help bridge these gaps by engaging with this important area of research.

Exploring network structure, dynamics, and function using networkx

Energy Technology Data Exchange (ETDEWEB)

Hagberg, Aric [Los Alamos National Laboratory; Swart, Pieter [Los Alamos National Laboratory; S Chult, Daniel [COLGATE UNIV

2008-01-01

NetworkX is a Python language package for exploration and analysis of networks and network algorithms. The core package provides data structures for representing many types of networks, or graphs, including simple graphs, directed graphs, and graphs with parallel edges and self loops. The nodes in NetworkX graphs can be any (hashable) Python object and edges can contain arbitrary data; this flexibility mades NetworkX ideal for representing networks found in many different scientific fields. In addition to the basic data structures many graph algorithms are implemented for calculating network properties and structure measures: shortest paths, betweenness centrality, clustering, and degree distribution and many more. NetworkX can read and write various graph formats for eash exchange with existing data, and provides generators for many classic graphs and popular graph models, such as the Erdoes-Renyi, Small World, and Barabasi-Albert models, are included. The ease-of-use and flexibility of the Python programming language together with connection to the SciPy tools make NetworkX a powerful tool for scientific computations. We discuss some of our recent work studying synchronization of coupled oscillators to demonstrate how NetworkX enables research in the field of computational networks.

Epidemic spreading on interconnected networks.

Science.gov (United States)

Saumell-Mendiola, Anna; Serrano, M Ángeles; Boguñá, Marián

2012-08-01

Many real networks are not isolated from each other but form networks of networks, often interrelated in nontrivial ways. Here, we analyze an epidemic spreading process taking place on top of two interconnected complex networks. We develop a heterogeneous mean-field approach that allows us to calculate the conditions for the emergence of an endemic state. Interestingly, a global endemic state may arise in the coupled system even though the epidemics is not able to propagate on each network separately and even when the number of coupling connections is small. Our analytic results are successfully confronted against large-scale numerical simulations.

1st International Conference on Network Analysis

CERN Document Server

Kalyagin, Valery; Pardalos, Panos

2013-01-01

This volume contains a selection of contributions from the "First International Conference in Network Analysis," held at the University of Florida, Gainesville, on December 14-16, 2011. The remarkable diversity of fields that take advantage of Network Analysis makes the endeavor of gathering up-to-date material in a single compilation a useful, yet very difficult, task. The purpose of this volume is to overcome this difficulty by collecting the major results found by the participants and combining them in one easily accessible compilation. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network is bringing together researchers, practitioners and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The contributions not only come from different fields, but also cover a broad range of topics relevant to the...

Dynamic Mobile RobotNavigation Using Potential Field Based Immune Network

Directory of Open Access Journals (Sweden)

Guan-Chun Luh

2007-04-01

Full Text Available This paper proposes a potential filed immune network (PFIN for dynamic navigation of mobile robots in an unknown environment with moving obstacles and fixed/moving targets. The Velocity Obstacle method is utilized to determine imminent obstacle collision of a robot moving in the time-varying environment. The response of the overall immune network is derived by the aid of fuzzy system. Simulation results are presented to verify the effectiveness of the proposed methodology in unknown environments with single and multiple moving obstacles

Charge transport in transparent single-wall carbon nanotube networks

International Nuclear Information System (INIS)

Jaiswal, Manu; Wang, Wei; Fernando, K A Shiral; Sun Yaping; Menon, Reghu

2007-01-01

We report the electric-field effects and magnetotransport in transparent networks of single-wall carbon nanotubes (SWNT). The temperature dependence of conductance of the network indicates a 2D Mott variable-range hopping (VRH) transport mechanism. Electric field and temperature are shown to have similar effects on the carrier hops and identical exponents for the conductance of the network are obtained from the high electric field and temperature dependences. A power-law temperature dependence with an exponent 3/2 for the threshold field is obtained and explained as a result of the competing contributions from electric field and phonons to the carrier hop. A negative magnetoresistance (MR) is observed at low temperatures, which arises from a forward interference scattering mechanism in the weak scattering limit, consistent with the VRH transport

Modeling of waste/near field interactions for a waste repository in bedded salt: the Dynamic Network (DNET) model

International Nuclear Information System (INIS)

Cranwell, R.M.

1983-01-01

The Fuel Cycle Risk Analysis Division of Sandia National Laboratories has been funded by the US Nuclear Regulatory Commission to develop a methodology for use in assessing the long-term risk from the disposal of radioactive wastes in deep geologic formations. As part of this program, the Dynamic Network (DNET) model was developed to investigate waste/near field interactions associated with the disposal of radioactive wastes in bedded salt formations. The model is a quasi-multi-dimensional network model with capabilities for simulating processes such as fluid flow, heat transport, salt dissolution, salt creep, and the effects of thermal expansion and subsedence on the rock units surrounding the repository. The use of DNET has been demonstrated in the analysis of a hypothetical disposal site containing a bedded salt formation as the host medium for the repository. An example of this demonstration analysis is discussed. Furthermore, the outcome of sensitivity analyses performed on the DNET model are presented

Designing reliable wireless sensor network for nuclear power plant

International Nuclear Information System (INIS)

Fujiwara, Takeshi; Takahashi, Hiroyuki

2007-01-01

This study proposes an innovative method for the monitoring the nuclear power plant. In this field, false detection of the trouble, both 'false negative' and 'false positive' will become a serious problem. In the other hand, since nuclear power plant is such a complicated system, wireless is required for implementing into real field. Considering these backgrounds, we propose a new reliable health monitoring system for nuclear power plant. This is based on an idea, 'a network on a network', such as 'wireless global network' on 'local network with self-maintenance function.' (author)

Recent Progress in Some Active Topics on Complex Networks

International Nuclear Information System (INIS)

Gu, J; Zhu, Y; Wang, Q A; Guo, L; Jiang, J; Chi, L; Li, W; Cai, X

2015-01-01

Complex networks have been extensively studied across many fields, especially in interdisciplinary areas. It has since long been recognized that topological structures and dynamics are important aspects for capturing the essence of complex networks. The recent years have also witnessed the emergence of several new elements which play important roles in network study. By combining the results of different research orientations in our group, we provide here a review of the recent advances in regards to spectral graph theory, opinion dynamics, interdependent networks, graph energy theory and temporal networks. We hope this will be helpful for the newcomers of those fields to discover new intriguing topics. (paper)

Networks with fourfold connectivity in two dimensions.

Science.gov (United States)

Tessier, Frédéric; Boal, David H; Discher, Dennis E

2003-01-01

The elastic properties of planar, C4-symmetric networks under stress and at nonzero temperature are determined by simulation and mean field approximations. Attached at fourfold coordinated junction vertices, the networks are self-avoiding in that their elements (or bonds) may not intersect each other. Two different models are considered for the potential energy of the elements: either Hooke's law springs or flexible tethers (square well potential). For certain ranges of stress and temperature, the properties of the networks are captured by one of several models: at large tensions, the networks behave like a uniform system of square plaquettes, while at large compressions or high temperatures, they display many characteristics of an ideal gas. Under less severe conditions, mean field models with more general shapes (parallelograms) reproduce many essential features of both networks. Lastly, the spring network expands without limit at a two-dimensional tension equal to the force constant of the spring; however, it does not appear to collapse under compression, except at zero temperature.

A Bayesian Approach to Measurement Bias in Networking Studies

NARCIS (Netherlands)

Zhu, Ling; Robinson, Scott E.; Torenvlied, René

2014-01-01

The study of managerial networking has been growing in the field of public administration; a field that analyzes how managers in open system organizations interact with different external actors and organizations. Coincident with this interest in managerial networking is the use of self-reported

The handbook of optical communication networks

CERN Document Server

Ilyas, Mohammad

2003-01-01

The Handbook of Optical Communication Networks presents comprehensive, up-to-date technical information on integrated, state-of-the-art optical networks. Beginning with an in-depth intoduction to the field, top international authorities explore every major aspect of optical networks, from basic concepts to research grade material. Their discussions cover all of the essential topics, including protocols, resource management, routing and wavelength assignment in WDM networks, connection management, survivability, enabling technologies, and future trends.

Information and control in networks

CERN Document Server

Bernhardsson, Bo; Rantzer, Anders

2014-01-01

Information and Control in Networks demonstrates the way in which system dynamics and information flows intertwine as they evolve, and the central role played by information in the control of complex networked systems. It is a milestone on the road to that convergence from traditionally independent development of control theory and information theory which has emerged strongly in the last fifteen years, and is now a very active research field. In addition to efforts in control and information theory, the text is witness to strong research in such diverse fields as computer science, mathematics, and statistics. Aspects that are given specialist treatment include: ·                 data-rate theorems; ·                 computation and control over communication networks; ·                 decentralized stochastic control; ·                 Gaussian networks and Gaussian–Markov random fields; and ·                 routability ...

Simulation of Stimuli-Responsive Polymer Networks

Directory of Open Access Journals (Sweden)

Thomas Gruhn

2013-11-01

Full Text Available The structure and material properties of polymer networks can depend sensitively on changes in the environment. There is a great deal of progress in the development of stimuli-responsive hydrogels for applications like sensors, self-repairing materials or actuators. Biocompatible, smart hydrogels can be used for applications, such as controlled drug delivery and release, or for artificial muscles. Numerical studies have been performed on different length scales and levels of details. Macroscopic theories that describe the network systems with the help of continuous fields are suited to study effects like the stimuli-induced deformation of hydrogels on large scales. In this article, we discuss various macroscopic approaches and describe, in more detail, our phase field model, which allows the calculation of the hydrogel dynamics with the help of a free energy that considers physical and chemical impacts. On a mesoscopic level, polymer systems can be modeled with the help of the self-consistent field theory, which includes the interactions, connectivity, and the entropy of the polymer chains, and does not depend on constitutive equations. We present our recent extension of the method that allows the study of the formation of nano domains in reversibly crosslinked block copolymer networks. Molecular simulations of polymer networks allow the investigation of the behavior of specific systems on a microscopic scale. As an example for microscopic modeling of stimuli sensitive polymer networks, we present our Monte Carlo simulations of a filament network system with crosslinkers.

RELATIONSHIPS BETWEEN FLUID VORTICITY, KINETIC HELICITY, AND MAGNETIC FIELD ON SMALL-SCALES (QUIET-NETWORK) ON THE SUN

Energy Technology Data Exchange (ETDEWEB)

Sangeetha, C. R.; Rajaguru, S. P., E-mail: crsangeetha@iiap.res.in [Indian Institute of Astrophysics, Bangalore-34 (India)

2016-06-20

We derive horizontal fluid motions on the solar surface over large areas covering the quiet-Sun magnetic network from local correlation tracking of convective granules imaged in continuum intensity and Doppler velocity by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory . From these we calculate the horizontal divergence, the vertical component of vorticity, and the kinetic helicity of fluid motions. We study the correlations between fluid divergence and vorticity, and between vorticity (kinetic helicity) and the magnetic field. We find that the vorticity (kinetic helicity) around small-scale fields exhibits a hemispherical pattern (in sign) similar to that followed by the magnetic helicity of large-scale active regions (containing sunspots). We identify this pattern to be a result of the Coriolis force acting on supergranular-scale flows (both the outflows and inflows), consistent with earlier studies using local helioseismology. Furthermore, we show that the magnetic fields cause transfer of vorticity from supergranular inflow regions to outflow regions, and that they tend to suppress the vortical motions around them when magnetic flux densities exceed about 300 G (from HMI). We also show that such an action of the magnetic fields leads to marked changes in the correlations between fluid divergence and vorticity. These results are speculated to be of importance to local dynamo action (if present) and to the dynamical evolution of magnetic helicity at the small-scale.

Critical exponents for diluted resistor networks.

Science.gov (United States)

Stenull, O; Janssen, H K; Oerding, K

1999-05-01

An approach by Stephen [Phys. Rev. B 17, 4444 (1978)] is used to investigate the critical properties of randomly diluted resistor networks near the percolation threshold by means of renormalized field theory. We reformulate an existing field theory by Harris and Lubensky [Phys. Rev. B 35, 6964 (1987)]. By a decomposition of the principal Feynman diagrams, we obtain diagrams which again can be interpreted as resistor networks. This interpretation provides for an alternative way of evaluating the Feynman diagrams for random resistor networks. We calculate the resistance crossover exponent phi up to second order in epsilon=6-d, where d is the spatial dimension. Our result phi=1+epsilon/42+4epsilon(2)/3087 verifies a previous calculation by Lubensky and Wang, which itself was based on the Potts-model formulation of the random resistor network.

Supporting networks for realizing rights

DEFF Research Database (Denmark)

Wilson, Fiona

2005-01-01

The chapter explores how DFID, the British bi-lateral aid donor, adopted an innovative rights' based approach that rested on supporting in existing networks in Peru. Focus is put on the history and challenges of DFID's engagement with three networks in particular: in the fields of health, local...

Electromagnetic field computation by network methods

CERN Document Server

Felsen, Leopold B; Russer, Peter

2009-01-01

This monograph proposes a systematic and rigorous treatment of electromagnetic field representations in complex structures. The book presents new strong models by combining important computational methods. This is the last book of the late Leopold Felsen.

Mobile ad hoc networking

CERN Document Server

John Wiley & Sons

2004-01-01

"Assimilating the most up-to-date information on research and development activities in this rapidly growing area, Mobile Ad Hoc Networking covers physical, data link, network, and transport layers, as well as application, security, simulation, and power management issues in sensor, local area, personal, and mobile ad hoc networks. Each of the book's sixteen chapters has been written by a top expert and discusses in-depth the most important topics in the field. Mobile Ad Hoc Networking is an excellent reference and guide for professionals seeking an in-depth examination of topics that also provides a comprehensive overview of the current state-of-the-art."--Jacket.

Networking systems design and development

CERN Document Server

Chao, Lee

2009-01-01

Effectively integrating theory and hands-on practice, Networking Systems Design and Development provides students and IT professionals with the knowledge and skills needed to design, implement, and manage fully functioning network systems using readily available Linux networking tools. Recognizing that most students are beginners in the field of networking, the text provides step-by-step instruction for setting up a virtual lab environment at home. Grounded in real-world applications, this book provides the ideal blend of conceptual instruction and lab work to give students and IT professional

ANN Based Approach for Estimation of Construction Costs of Sports Fields

Directory of Open Access Journals (Sweden)

Michał Juszczyk

2018-01-01

Full Text Available Cost estimates are essential for the success of construction projects. Neural networks, as the tools of artificial intelligence, offer a significant potential in this field. Applying neural networks, however, requires respective studies due to the specifics of different kinds of facilities. This paper presents the proposal of an approach to the estimation of construction costs of sports fields which is based on neural networks. The general applicability of artificial neural networks in the formulated problem with cost estimation is investigated. An applicability of multilayer perceptron networks is confirmed by the results of the initial training of a set of various artificial neural networks. Moreover, one network was tailored for mapping a relationship between the total cost of construction works and the selected cost predictors which are characteristic of sports fields. Its prediction quality and accuracy were assessed positively. The research results legitimatize the proposed approach.

Creating, generating and comparing random network models with NetworkRandomizer.

Science.gov (United States)

Tosadori, Gabriele; Bestvina, Ivan; Spoto, Fausto; Laudanna, Carlo; Scardoni, Giovanni

2016-01-01

Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cytoscape platform, which aims at creating randomised networks and randomising existing, real networks. Since there is a lack of tools that allow performing such operations, our app aims at enabling researchers to exploit different, well known random network models that could be used as a benchmark for validating real, biological datasets. We also propose a novel methodology for creating random weighted networks, i.e. the multiplication algorithm, starting from real, quantitative data. Finally, the app provides a statistical tool that compares real versus randomly computed attributes, in order to validate the numerical findings. In summary, our app aims at creating a standardised methodology for the validation of the results in the context of the Cytoscape platform.

Telecommunication Networks

DEFF Research Database (Denmark)

Olsen, Rasmus Løvenstein; Balachandran, Kartheepan; Hald, Sara Ligaard

2014-01-01

In this chapter, we look into the role of telecommunication networks and their capability of supporting critical infrastructure systems and applications. The focus is on smart grids as the key driving example, bearing in mind that other such systems do exist, e.g., water management, traffic control......, etc. First, the role of basic communication is examined with a focus on critical infrastructures. We look at heterogenic networks and standards for smart grids, to give some insight into what has been done to ensure inter-operability in this direction. We then go to the physical network, and look...... threats to the critical infrastructure. Finally, before our conclusions and outlook, we give a brief overview of some key activities in the field and what research directions are currently investigated....

Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network

Science.gov (United States)

Liu, Ziyi; Gao, Junfeng; Yang, Guoguo; Zhang, Huan; He, Yong

2016-01-01

We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods. PMID:26864172

Rational function systems and electrical networks with multiparameters

CERN Document Server

Lu, KaiSheng

2012-01-01

To overcome the problems of system theory and network theory over real field, this book uses matrices over the field F(z) of rational functions in multiparameters describing coefficient matrices of systems and networks and makes systems and network description over F(z) and researches their structural properties: reducible condition of a class of matrices over F(z) and their characteristic polynomial; type1 matrix and two basic properties; variable replacement conditions for independent parameters; structural controllability and observability of linear systems over F(z); separability, reducibi

Snow Roads at McMurdo Station, Antarctica

Science.gov (United States)

2010-05-01

is minimized distribution of low strength areas (also called “ holidays ”). Holidays are actually areas of pulverized snow that are missed or inade...quately processed. Though holidays usually occur sporadically, any single flaw may extend through the entire thickness of an unelevated road. The...Pegasus Road and the LDB pad. A few additional sites were chosen for comparison (Williams Field, virgin snow, etc.). Williams Field Road densities

Data and Network Science for Noisy Heterogeneous Systems

Science.gov (United States)

Rider, Andrew Kent

2013-01-01

Data in many growing fields has an underlying network structure that can be taken advantage of. In this dissertation we apply data and network science to problems in the domains of systems biology and healthcare. Data challenges in these fields include noisy, heterogeneous data, and a lack of ground truth. The primary thesis of this work is that…

Unraveling spurious properties of interaction networks with tailored random networks.

Directory of Open Access Journals (Sweden)

Stephan Bialonski

Full Text Available We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

Weighted Networks at the Polish Market

Science.gov (United States)

Chmiel, A. M.; Sienkiewicz, J.; Suchecki, K.; Hołyst, J. A.

During the last few years various models of networks [1,2] have become a powerful tool for analysis of complex systems in such distant fields as Internet [3], biology [4], social groups [5], ecology [6] and public transport [7]. Modeling behavior of economical agents is a challenging issue that has also been studied from a network point of view. The examples of such studies are models of financial networks [8], supply chains [9, 10], production networks [11], investment networks [12] or collective bank bankrupcies [13, 14]. Relations between different companies have been already analyzed using several methods: as networks of shareholders [15], networks of correlations between stock prices [16] or networks of board directors [17]. In several cases scaling laws for network characteristics have been observed.

Large scale network-centric distributed systems

CERN Document Server

Sarbazi-Azad, Hamid

2014-01-01

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

Complex Networks IX

CERN Document Server

Coronges, Kate; Gonçalves, Bruno; Sinatra, Roberta; Vespignani, Alessandro; Proceedings of the 9th Conference on Complex Networks; CompleNet 2018

2018-01-01

This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) 2018 in Boston, MA in March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.

Networks and learning: communities, practices and the metaphor of networks–a commentary

Directory of Open Access Journals (Sweden)

Bruce Ingraham

2004-12-01

Full Text Available In issue 12(1, Jones (2004 in his article ‘Networks and learning: communities, practices and the metaphor of networks' sets out to address three inter-related sets of issues: … firstly that learning technology needs to take account of the wider debate about networks and secondly that research in this field needs to address the theoretical and practical issues raised by advances in the field of networks. A third point is that the idea of the network acts as a powerful metaphor even if we are able to discount any particular theory generated in its support. The network metaphor can act as a unifying concept allowing us to bring together apparently disparate elements of the field.

How to desynchronize quorum-sensing networks

Science.gov (United States)

Russo, Giovanni

2017-04-01

In this paper we investigate how so-called quorum-sensing networks can be desynchronized. Such networks, which arise in many important application fields, such as systems biology, are characterized by the fact that direct communication between network nodes is superimposed to communication with a shared, environmental variable. In particular, we provide a new sufficient condition ensuring that the trajectories of these quorum-sensing networks diverge from their synchronous evolution. Then, we apply our result to study two applications.

Audio coding in wireless acoustic sensor networks

DEFF Research Database (Denmark)

Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt

2015-01-01

In this paper, we consider the problem of source coding for a wireless acoustic sensor network where each node in the network makes its own noisy measurement of the sound field, and communicates with other nodes in the network by sending and receiving encoded versions of the measurements. To make...

Occupational exposure to radiofrequency fields in antenna towers

International Nuclear Information System (INIS)

Alanko, T.; Hietanen, M.

2007-01-01

Exposure of workers to radiofrequency fields was assessed in two medium-sized antenna towers. Towers had transmitting antennas from different networks, e.g. mobile phone networks, radio and digital TV sub-stations and amateur radio. The levels of radiofrequency fields were measured close to the ladders of the towers. All measured values were below ICNIRP occupational reference levels. (authors)

EXPERIENCE NETWORKING UNIVERSITY OF EDUCATION TRAINING MASTERS SAFETY OF LIFE

Directory of Open Access Journals (Sweden)

Elvira Mikhailovna Rebko

2016-02-01

Full Text Available The article discloses experience networking of universities (Herzen State Pedagogical University and Sakhalin State University in the development and implementation of joint training programs for master’s education in the field of life safety «Social security in the urban environment». The novelty of the work is to create a schematic design of basic educational training program for master’s education in the mode of networking, and to identify effective instructional techniques and conditions of networking.Purpose – present the results of the joint development of a network of the basic educational program (BEP, to identify the stages of networking, to design a generalized scheme of development and implementation of a network of educational training program for master’s education in the field of life safety.Results generalized model of networking partner institutions to develop and implement the basic educational program master.Practical implications: the education process for Master of Education in the field of health and safety in Herzen State Pedagogical University and Sakhalin State University.

Scientific Collaboration in Chinese Nursing Research: A Social Network Analysis Study.

Science.gov (United States)

Hou, Xiao-Ni; Hao, Yu-Fang; Cao, Jing; She, Yan-Chao; Duan, Hong-Mei

2016-01-01

Collaboration has become very important in research and in technological progress. Coauthorship networks in different fields have been intensively studied as an important type of collaboration in recent years. Yet there are few published reports about collaboration in the field of nursing. This article aimed to reveal the status and identify the key features of collaboration in the field of nursing in China. Using data from the top 10 nursing journals in China from 2003 to 2013, we constructed a nursing scientific coauthorship network using social network analysis. We found that coauthorship was a common phenomenon in the Chinese nursing field. A coauthorship network with 228 subnetworks formed by 1428 nodes was constructed. The network was relatively loose, and most subnetworks were of small scales. Scholars from Shanghai and from military medical system were at the center of the Chinese nursing scientific coauthorship network. We identified the authors' positions and influences according to the research output and centralities of each author. We also analyzed the microstructure and the evolution over time of the maximum subnetwork.

Mapping the evolution of scientific fields.

Science.gov (United States)

Herrera, Mark; Roberts, David C; Gulbahce, Natali

2010-05-04

Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985-2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

EMPLOYING SENSOR NETWORK TO GUIDE FIREFIGHTERS IN DANGEROUS AREA

DEFF Research Database (Denmark)

Koohi, Hamidreza; Nadernejad, Ehsan; Fathi, Mahmoud

2010-01-01

In this paper, we intend to focus on the sensor network applications in firefighting. A distributed algorithm is developed for the sensor network to guide firefighters through a burning area. The sensor network models the danger of the area under coverage as obstacles, and has the property to adapt...... itself against possible changes. The protocol developed, will integrate the artificial potential field of the sensors with the information of the intended place of moving firefighter so that it guides the firefighter step by step through the sensor network by choosing the safest path in dangerous zones....... This protocol is simulated by Visual-Sense and the simulation results are available. Keyword: Firefighter, Sensor Network, Potential Field, Area’s Danger, Navigation...

Development of IT-based data communication network technology

International Nuclear Information System (INIS)

Hong, Seok Boong; Jeong, K. I.; Yoo, Y. R.

2010-10-01

- Developing broadband high-reliability real-time communications technology for NPP - Developing reliability and performance validation technology for communications network - Developing security technology for NPP communications network - Developing field communications network for harsh environment of NPP - International standard registration(Oct. 28, 2009, IEC 61500

Flux lattice commensurability and the resistive transition of wire networks

International Nuclear Information System (INIS)

Wilks, C.W.

1992-01-01

The commensurability of one structure with one length scale with that of another with a different length scale is a familiar problem. For a superconducting wire network in a magnetic field the two competing length scales are that of the network and that of the magnetic flux lattice. The superconducting to normal state phase boundary, Tc(H), of a periodic network shows periodic oscillations with a period of H 0 = Φ 0 /A where Φ 0 = hc/2e and A is the area of the elementary tile. These oscillations are due to flux quantization around the individual tiles of the network. In addition, within each period, there is structure at H = (p/q)H 0 (p,q integers) which is due to the vortices forming energetically favorable commensurate arrangements on top of the underlying lattice. The authors have studied the broadening of the zero field resistive transition with the application of a magnetic field for networks of various geometries. This was done by either directly measuring the resistive transitions at the commensurate fields or by using a technique that utilizes phase boundary measurements and yields the field induced width of the resistive transition as a continued function of the field. There is a striking dependence of the field induced width on whether or not the field is commensurate with the network. The broadening at the commensurate flux filling is well described by thermally activated vortex motion using the formalism of Ambegoakar and Halperin which allows us to extract numbers for the pinning potentials at the various commensurate states. The authors have found that the size of the discontinuity in the slope of the phase boundary at a commensurate filling is related to the strength of the lattice and therefore to the broadening of the transition at that filling so that by just looking at the phase boundary of a network one can gauge the relative broadening of the resistive transitions at the commensurate flux fillings

A Quantum Cryptography Communication Network Based on Software Defined Network

Directory of Open Access Journals (Sweden)

Zhang Hongliang

2018-01-01

Full Text Available With the development of the Internet, information security has attracted great attention in today’s society, and quantum cryptography communication network based on quantum key distribution (QKD is a very important part of this field, since the quantum key distribution combined with one-time-pad encryption scheme can guarantee the unconditional security of the information. The secret key generated by quantum key distribution protocols is a very valuable resource, so making full use of key resources is particularly important. Software definition network (SDN is a new type of network architecture, and it separates the control plane and the data plane of network devices through OpenFlow technology, thus it realizes the flexible control of the network resources. In this paper, a quantum cryptography communication network model based on SDN is proposed to realize the flexible control of quantum key resources in the whole cryptography communication network. Moreover, we propose a routing algorithm which takes into account both the hops and the end-to-end availible keys, so that the secret key generated by QKD can be used effectively. We also simulate this quantum cryptography communication network, and the result shows that based on SDN and the proposed routing algorithm the performance of this network is improved since the effective use of the quantum key resources.

An Analysis of the Structure and Evolution of Networks

Science.gov (United States)

Hua, Guangying

2011-01-01

As network research receives more and more attention from both academic researchers and practitioners, network analysis has become a fast growing field attracting many researchers from diverse fields such as physics, computer science, and sociology. This dissertation provides a review of theory and research on different real data sets from the…

On network representations of antennas inside resonating environments

Directory of Open Access Journals (Sweden)

F. Gronwald

2007-06-01

Full Text Available We discuss network representations of dipole antennas within electromagnetic cavities. It is pointed out that for a given configuration these representations are not unique. For an efficient evaluation a network representation should be chosen such that it involves as few network elements as possible. The field theoretical analogue of this circumstance is the possibility to express electromagnetic cavities' Green's functions by representations which exhibit different convergence properties. An explicit example of a dipole antenna within a rectangular cavity clarifies the corresponding interrelation between network theory and electromagnetic field theory. As an application, current spectra are calculated for the case that the antenna is nonlinearly loaded and subject to a two-tone excitation.

Eight challenges for network epidemic models

Directory of Open Access Journals (Sweden)

Lorenzo Pellis

2015-03-01

Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.

The Global Network of Biofuel Sustainability Standards-setters

DEFF Research Database (Denmark)

Henriksen, Lasse Folke

2015-01-01

the relevance of incorporating in the current attributional conception of hybridity a network element, taking seriously the role of network structure in shaping regulatory fields. Social Network Analysis as an analytical tool holds great potential for further research into the structural features of hybrid...

Quantized hopfield networks for reliability optimization

International Nuclear Information System (INIS)

Nourelfath, Mustapha; Nahas, Nabil

2003-01-01

The use of neural networks in the reliability optimization field is rare. This paper presents an application of a recent kind of neural networks in a reliability optimization problem for a series system with multiple-choice constraints incorporated at each subsystem, to maximize the system reliability subject to the system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. Our design of neural network to solve efficiently this problem is based on a quantized Hopfield network. This network allows us to obtain optimal design solutions very frequently and much more quickly than others Hopfield networks

Bayesian prediction and adaptive sampling algorithms for mobile sensor networks online environmental field reconstruction in space and time

CERN Document Server

Xu, Yunfei; Dass, Sarat; Maiti, Tapabrata

2016-01-01

This brief introduces a class of problems and models for the prediction of the scalar field of interest from noisy observations collected by mobile sensor networks. It also introduces the problem of optimal coordination of robotic sensors to maximize the prediction quality subject to communication and mobility constraints either in a centralized or distributed manner. To solve such problems, fully Bayesian approaches are adopted, allowing various sources of uncertainties to be integrated into an inferential framework effectively capturing all aspects of variability involved. The fully Bayesian approach also allows the most appropriate values for additional model parameters to be selected automatically by data, and the optimal inference and prediction for the underlying scalar field to be achieved. In particular, spatio-temporal Gaussian process regression is formulated for robotic sensors to fuse multifactorial effects of observations, measurement noise, and prior distributions for obtaining the predictive di...

Community-Based Research Networks: Development and Lessons Learned in an Emerging Field.

Science.gov (United States)

Stoecker, Randy; Ambler, Susan H.; Cutforth, Nick; Donohue, Patrick; Dougherty, Dan; Marullo, Sam; Nelson, Kris S.; Stutts, Nancy B.

2003-01-01

Compares seven multi-institutional community-based research networks in Appalachia; Colorado; District of Columbia; Minneapolis-St. Paul; Philadelphia; Richmond, Virginia; and Trenton, New Jersey. After reviewing the histories of the networks, conducts a comparative SWOT analysis, showing their common and unique strengths, weaknesses,…

Expanding the TRI Network for Doctoral Researchers in the Fields of Terrorism, Political Violence and Armed Conflict to the United States of America and Russia

OpenAIRE

Alex P. Schmid; Gordon Clubb; Jason Rineheart; Yulia  Netesova

2011-01-01

In September 2011, the Terrorism Research Initiative (TRI) announced the creation of a post-graduate terrorism research network in the United Kingdom. The idea was to compile a list of post-graduates conducting research in the UK in the overlapping fields of terrorism, political violence, and armed conflict. While much research is conducted in these three overlapping fields, those involved in research are often unsure what is going on outside their own university department. They also wonder ...

Pinning adaptive synchronization of a class of uncertain complex dynamical networks with multi-link against network deterioration

International Nuclear Information System (INIS)

Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong

2015-01-01

For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method

Multi-field coupled sensing network for health monitoring of composite bolted joint

Science.gov (United States)

Wang, Yishou; Qing, Xinlin; Dong, Liang; Banerjee, Sourav

2016-04-01

Advanced fiber reinforced composite materials are becoming the main structural materials of next generation of aircraft because of their high strength and stiffness to weight ratios, and excellent designability. As key components of large composite structures, joints play important roles to ensure the integrity of the composite structures. However, it is very difficult to analyze the strength and failure modes of composite joints due to their complex nonlinear coupling factors. Therefore, there is a need to monitor, diagnose, evaluate and predict the structure state of composite joints. This paper proposes a multi-field coupled sensing network for health monitoring of composite bolted joints. Major work of this paper includes: 1) The concept of multifunctional sensor layer integrated with eddy current sensors, Rogowski coil and arrayed piezoelectric sensors; 2) Development of the process for integrating the eddy current sensor foil, Rogowski coil and piezoelectric sensor array in multifunctional sensor layer; 3) A new concept of smart composite joint with multifunctional sensing capability. The challenges for building such a structural state sensing system and some solutions to address the challenges are also discussed in the study.

Network protocol 'EPAP'; Network protokoru 'EPAP'

Energy Technology Data Exchange (ETDEWEB)

Kobori, T.; Fujita, F.; Iwamoto, S. [Fuji Electric Co. Ltd., Toyo (Japan)

2000-10-10

The Ethernet, a standard of information networks, has begun to be applied to the control local area network (LAN). To apply the Ethernet to the field level, Fuji Electric has newly developed the communication protocol 'Ethernet precision access protocol (EPAP)' in which a command/response method is structured on the user datagram protocol (UDP) to realize real time and high reliability. Further, we have implemented the EPAP on the bus interface module of the open PIO. This paper outlines the EPAP and its implementation. (author)

Optical Access Networks

Science.gov (United States)

Zheng, Jun; Ansari, Nirwan

2005-01-01

have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or are now underway this hot area. The purpose of this feature issue is to expose the networking community to the latest research breakthroughs and progresses in the area of optical access networks. Scope of Contributions This feature issue aims to present a collection of papers that focus on the state-of-the-art research in various networking aspects of optical access networks. Original papers are solicited from all researchers involved in area of optical access networks. Topics of interest include but not limited to: Optical access network architectures and protocols Passive optical networks (BPON, EPON, GPON, etc.) Active optical networks Multiple access control Multiservices and QoS provisioning Network survivability Field trials and standards Performance modeling and analysis Manuscript Submission To submit to this special issue, follow the normal procedure for submission to JON, indicating ``Optical Access Networks feature' in the ``Comments' field of the online submission form. For all other questions relating to this feature issue, please send an e-mail to jon@osa.org, subject line ``Optical Access Networks' Additional information can be found on the JON website: http://www.osa-jon.org/submission/. Submission Deadline: 1 June 2005

Cable networks, services, and management

CERN Document Server

2015-01-01

Cable Networks, Services, and Management is the first book to cover cable networks, services, and their management, in-depth, for network operators, engineers, researchers, and students. Thirteen experts in various fields have contributed their knowledge of network architectures and services, Operations, Administration, Maintenance, Provisioning, Troubleshooting (OAMPT) for residential and business services, cloud, Software Defined Networks (SDN), as well as virtualization concepts and their applications as part of the future directions of cable networks. The book begins by introducing architecture and services for Data Over Cable Service Interface Specification (DOCSIS) 3.0/ 3.1, Converged Cable Access Platform (CCAP), Content Distribution Networks (CDN, IP TV, and Packet Cable and Wi-Fi for Residential Services. Topics that are discussed in proceeding chapters include: operational systems and management architectures, service orders, provisioning, fault manageme t, performance management, billing systems a...

KSC ADVANCED GROUND BASED FIELD MILL V1

Data.gov (United States)

National Aeronautics and Space Administration — The Advanced Ground Based Field Mill (AGBFM) network consists of 34 (31 operational) field mills located at Kennedy Space Center (KSC), Florida. The field mills...

4th International Conference on Computer Engineering and Networks

CERN Document Server

2015-01-01

This book aims to examine innovation in the fields of computer engineering and networking. The book covers important emerging topics in computer engineering and networking, and it will help researchers and engineers improve their knowledge of state-of-art in related areas. The book presents papers from the 4th International Conference on Computer Engineering and Networks (CENet2014) held July 19-20, 2014 in Shanghai, China.  ·       Covers emerging topics for computer engineering and networking ·       Discusses how to improve productivity by using the latest advanced technologies ·       Examines innovation in the fields of computer engineering and networking  

An Examination of Research Collaboration in Psychometrics Utilizing Social Network Analysis Methods

Science.gov (United States)

DiCrecchio, Nicole C.

2016-01-01

Co-authorship networks have been studied in many fields as a way to understand collaboration patterns. However, a comprehensive exploration of the psychometrics field has not been conducted. Also, few studies on co-author networks have included longitudinal analyses as well as data on the characteristics of authors in the network. Including both…

Communication and Networking in Smart Grids

CERN Document Server

Xiao, Yang

2012-01-01

Appropriate for researchers, practitioners, and students alike, Communication and Networking in Smart Grids presents state-of-the-art approaches and novel technologies for communication networks in smart grids. It explains how contemporary grid networks are developed and deployed and presents a collection of cutting-edge advances to help improve current practice. Prominent researchers working on smart grids and in related fields around the world explain the fundamental aspects and applications of smart grids. Describing the role that communication and networking will play in future smart grids

Optical networks a practical perspective

CERN Document Server

Ramaswami, Rajiv

2001-01-01

This fully updated and expanded second edition of Optical Networks: A Practical Perspective succeeds the first as the authoritative source for information on optical networking technologies and techniques. Written by two of the field's most respected individuals, it covers componentry and transmission in detail but also emphasizes the practical networking issues that affect organizations as they evaluate, deploy, or develop optical solutions. This book captures all the hard-to-find information on architecture, control and management, and other communications topics that

Managing Networks

DEFF Research Database (Denmark)

Jørgensen, Heidi; Vintergaard, Christian

Logically it seems that companies pursuing different business strategies wouldalso manage their relationships with other firms accordingly. Nevertheless, due tothe lack of research in the field of network strategies, this link still remainsinadequately examined. Based on the well-known framework...... isprovided, that the relation between a company's strategy, structure and processesin fact have a considerable influence on its pattern of network behaviour. Threecase studies from the Danish biotech industry exemplify and illustrate how acompany's strategy is directly correlated with how it manages its...... of networkbehaviour, knowing how to manage this relation becomes essential, especiallyduring the development of new strategies....

Competitive Liner Shipping Network Design

DEFF Research Database (Denmark)

Karsten, Christian Vad

.The contributions of this thesis cover modeling, methodology, and applications.The developed methods address operational (cargo routing), tactical (speed optimization and service selection), and strategic (network design) planning problems faced by liner shipping companies. Ultimately, the proposed methods help...... take the container transportation times that can be realized in the network nor the number of transshipments into consideration. This is mainly because the optimization problem is based on other transportation networks where these constraints are not decisive to the quality of the network. Furthermore......, the problem in itself is challenging to optimize due to its size and complexity. However, the field has seen crucial progress and is mature to include handling of competitiveness in the actual design of the network.As a liner shipping network is an organic entity, which is constantly changed to reflect...

Polymer-Sorted Semiconducting Carbon Nanotube Networks for High-Performance Ambipolar Field-Effect Transistors

Science.gov (United States)

2014-01-01

Efficient selection of semiconducting single-walled carbon nanotubes (SWNTs) from as-grown nanotube samples is crucial for their application as printable and flexible semiconductors in field-effect transistors (FETs). In this study, we use atactic poly(9-dodecyl-9-methyl-fluorene) (a-PF-1-12), a polyfluorene derivative with asymmetric side-chains, for the selective dispersion of semiconducting SWNTs with large diameters (>1 nm) from plasma torch-grown SWNTs. Lowering the molecular weight of the dispersing polymer leads to a significant improvement of selectivity. Combining dense semiconducting SWNT networks deposited from an enriched SWNT dispersion with a polymer/metal-oxide hybrid dielectric enables transistors with balanced ambipolar, contact resistance-corrected mobilities of up to 50 cm2·V–1·s–1, low ohmic contact resistance, steep subthreshold swings (0.12–0.14 V/dec) and high on/off ratios (106) even for short channel lengths (<10 μm). These FETs operate at low voltages (<3 V) and show almost no current hysteresis. The resulting ambipolar complementary-like inverters exhibit gains up to 61. PMID:25493421

Communication via an entangled coherent quantum network

Energy Technology Data Exchange (ETDEWEB)

El Allati, A; Hassouni, Y [Faculte des Sciences, Departement de Physique, Laboratoire de Physique Theorique URAC 13, Universite Mohammed V Agdal Rabat, Avenue Ibn Battouta, B.P. 1014, Rabat (Morocco); Metwally, N, E-mail: Nmetwally@gmail.com [Mathematics Department, College of Science, University of Bahrain, PO Box 32038 (Bahrain)

2011-06-01

A quantum network (QN) is constructed via maximum entangled coherent states. The possibility of using this network to achieve quantum communication between multi-participants is investigated. We showed that the probability of the successful teleportation of an unknown state depends on the size of the used network. As the number of participants increases, the success probability does not depend on the intensity of the field. Implementing a quantum teleportation protocol via a noisy QN is discussed. The unknown state can be teleported perfectly with small values of the field intensity and larger values of the noise strength. The success probability of this suggested protocol increases abruptly for larger values of the noise strength and gradually for small values. For small-size QNs, the fidelity of the teleported state decreases smoothly, whereas it decreases abruptly for larger-sized networks.

Interdisciplinary and physics challenges of network theory

Science.gov (United States)

Bianconi, Ginestra

2015-09-01

Network theory has unveiled the underlying structure of complex systems such as the Internet or the biological networks in the cell. It has identified universal properties of complex networks, and the interplay between their structure and dynamics. After almost twenty years of the field, new challenges lie ahead. These challenges concern the multilayer structure of most of the networks, the formulation of a network geometry and topology, and the development of a quantum theory of networks. Making progress on these aspects of network theory can open new venues to address interdisciplinary and physics challenges including progress on brain dynamics, new insights into quantum technologies, and quantum gravity.

An evolving network model with community structure

International Nuclear Information System (INIS)

Li Chunguang; Maini, Philip K

2005-01-01

Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

Josephson junction arrays and superconducting wire networks

International Nuclear Information System (INIS)

Lobb, C.J.

1992-01-01

Techniques used to fabricate integrated circuits make it possible to construct superconducting networks containing as many as 10 6 wires or Josephson junctions. Such networks undergo phase transitions from resistive high-temperature states to ordered low-resistance low-temperature states. The nature of the phase transition depends strongly on controllable parameters such as the strength of the superconductivity in each wire or junction and the external magnetic field. This paper will review the physics of these phase transitions, starting with the simplest zero-magnetic field case. This leads to a Kosterlitz-Thouless transition when the junctions or wires are weak, and a simple mean-field fransition when the junctions or wires are strong. Rich behavior, resulting from frustration, occurs in the presence of a magnetic field. (orig.)

Fuzzy neural network theory and application

CERN Document Server

Liu, Puyin

2004-01-01

This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to he

Focal mechanisms in the southern Aegean from temporary seismic networks – implications for the regional stress field and ongoing deformation processes

OpenAIRE

Friederich, W.; Brüstle, A.; Küperkoch, L.; Meier, T.; Lamara, S.; Working Group, Egelados

2014-01-01

The lateral variation of the stress field in the southern Aegean plate and the subducting Hellenic slab is determined from recordings of seismicity obtained with the CYCNET and EGELADOS networks in the years from 2002 to 2007. First motions from 7000 well-located microearthquakes were analysed to produce 540 well-constrained focal mechanisms. They were complemented by another 140 derived by waveform matching of records from larger events. Most of these earth...

Stochastic network calculus

CERN Document Server

Jiang, Yuming

2009-01-01

This book is devoted to a comprehensive treatment of this important field, a grand challenge for future networking research. It covers results from the authors as well as other researchers. Topics covered include Independent Case Analysis and its applications.

Classifying Wheat Hyperspectral Pixels of Healthy Heads and Fusarium Head Blight Disease Using a Deep Neural Network in the Wild Field

Directory of Open Access Journals (Sweden)

Xiu Jin

2018-03-01

Full Text Available Classification of healthy and diseased wheat heads in a rapid and non-destructive manner for the early diagnosis of Fusarium head blight disease research is difficult. Our work applies a deep neural network classification algorithm to the pixels of hyperspectral image to accurately discern the disease area. The spectra of hyperspectral image pixels in a manually selected region of interest are preprocessed via mean removal to eliminate interference, due to the time interval and the environment. The generalization of the classification model is considered, and two improvements are made to the model framework. First, the pixel spectra data are reshaped into a two-dimensional data structure for the input layer of a Convolutional Neural Network (CNN. After training two types of CNNs, the assessment shows that a two-dimensional CNN model is more efficient than a one-dimensional CNN. Second, a hybrid neural network with a convolutional layer and bidirectional recurrent layer is reconstructed to improve the generalization of the model. When considering the characteristics of the dataset and models, the confusion matrices that are based on the testing dataset indicate that the classification model is effective for background and disease classification of hyperspectral image pixels. The results of the model show that the two-dimensional convolutional bidirectional gated recurrent unit neural network (2D-CNN-BidGRU has an F1 score and accuracy of 0.75 and 0.743, respectively, for the total testing dataset. A comparison of all the models shows that the hybrid neural network of 2D-CNN-BidGRU is the best at preventing over-fitting and optimize the generalization. Our results illustrate that the hybrid structure deep neural network is an excellent classification algorithm for healthy and Fusarium head blight diseased classification in the field of hyperspectral imagery.

Introduction into bi-partite networks in python

OpenAIRE

Kasberger, Stefan

2016-01-01

This essay and the related computation delivers a comprehensive introduction into the concept of bipartite networks, a class of networks whose nodes are divided into two sets and only the connection between two nodes in different sets is allowed (Easley and Kleinberg, 2010). The analysis and visualization is done in the programming language Python and offers easy to understand first steps in both fields, network analyses and python programming. As data a collaboration network of github users ...

Advances in network systems architectures, security, and applications

CERN Document Server

Awad, Ali; Furtak, Janusz; Legierski, Jarosław

2017-01-01

This book provides the reader with a comprehensive selection of cutting–edge algorithms, technologies, and applications. The volume offers new insights into a range of fundamentally important topics in network architectures, network security, and network applications. It serves as a reference for researchers and practitioners by featuring research contributions exemplifying research done in the field of network systems. In addition, the book highlights several key topics in both theoretical and practical aspects of networking. These include wireless sensor networks, performance of TCP connections in mobile networks, photonic data transport networks, security policies, credentials management, data encryption for network transmission, risk management, live TV services, and multicore energy harvesting in distributed systems. .

Spatial anomaly detection in sensor networks using neighborhood information

NARCIS (Netherlands)

Bosman, H.H.W.J.; Iacca, G.; Tejada, A.; Wörtche, H.J.; Liotta, A.

2016-01-01

The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capabil- ity, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challenge now is to extract meaningful information from

Spatial anomaly detection in sensor networks using neighborhood information

NARCIS (Netherlands)

Bosman, H.H.W.J.; Iacca, G.; Tejada, A.; Wörtche, H.J.; Liotta, A.

The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capability, has now matured after a decade-long research effort and technological advances in electronics and networked systems. An important remaining challenge now is to extract meaningful information from

Topology Optimisation of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Thike Aye Min

2016-01-01

Full Text Available Wireless sensor networks are widely used in a variety of fields including industrial environments. In case of a clustered network the location of cluster head affects the reliability of the network operation. Finding of the optimum location of the cluster head, therefore, is critical for the design of a network. This paper discusses the optimisation approach, based on the brute force algorithm, in the context of topology optimisation of a cluster structure centralised wireless sensor network. Two examples are given to verify the approach that demonstrate the implementation of the brute force algorithm to find an optimum location of the cluster head.

Quantum state transfer and network engineering

International Nuclear Information System (INIS)

Nikolopoulos, Georgios M.; Jex, Igor

2014-01-01

Presents the basics of large-scale quantum information processing and networking. Covers most aspects of the problems of state transfer and quantum network engineering. Reflects the interdisciplinary nature of the field. Presents various theoretical approaches as well as possible implementations and related experiments. Faithful communication is a necessary precondition for large-scale quantum information processing and networking, irrespective of the physical platform. Thus, the problems of quantum-state transfer and quantum-network engineering have attracted enormous interest over the last years, and constitute one of the most active areas of research in quantum information processing. The present volume introduces the reader to fundamental concepts and various aspects of this exciting research area, including links to other related areas and problems. The implementation of state-transfer schemes and the engineering of quantum networks are discussed in the framework of various quantum optical and condensed matter systems, emphasizing the interdisciplinary character of the research area. Each chapter is a review of theoretical or experimental achievements on a particular topic, written by leading scientists in the field. The volume aims at both newcomers as well as experienced researchers.

Expanding Usability of Virtual Network Laboratory in IT Engineering Education

Directory of Open Access Journals (Sweden)

Dalibor M Dobrilovic

2013-02-01

Full Text Available This paper deals with importance of virtual network laboratories usage in IT engineering education. It presents the particular virtual network laboratory model developed for usage in Computer Networks course as well. This virtual network laboratory, called VNLab, is based on virtualization technology. It has been successfully tested in educational process of Computer Network course for IT undergraduate students. Its usability for network related courses is analyzed by comparison of recommended curricula’s of world organizations such as IEEE, ACM and AIS. This paper is focused on expanding the usability of this virtual network laboratory to other non-network related courses. The primary expansion field is in domain of IT System Administration, IT Systems and Data Security and Operating Systems as well. The possible learning scenarios, learning tools and concepts for making this system applicable in these three additional fields are presented by the analyses of compatibility with recommended learning topics and outcomes by IEEE, ACM and AIS.

Vortex pinning vs superconducting wire network: origin of periodic oscillations induced by applied magnetic fields in superconducting films with arrays of nanomagnets

International Nuclear Information System (INIS)

Gomez, A; Del Valle, J; Gonzalez, E M; Vicent, J L; Chiliotte, C E; Carreira, S J; Bekeris, V; Prieto, J L; Schuller, Ivan K

2014-01-01

Hybrid magnetic arrays embedded in superconducting films are ideal systems to study the competition between different physical (such as the coherence length) and structural length scales such as are available in artificially produced structures. This interplay leads to oscillation in many magnetically dependent superconducting properties such as the critical currents, resistivity and magnetization. These effects are generally analyzed using two distinct models based on vortex pinning or wire network. In this work, we show that for magnetic dot arrays, as opposed to antidot (i.e. holes) arrays, vortex pinning is the main mechanism for field induced oscillations in resistance R(H), critical current I c (H), magnetization M(H) and ac-susceptibility χ ac (H) in a broad temperature range. Due to the coherence length divergence at T c , a crossover to wire network behaviour is experimentally found. While pinning occurs in a wide temperature range up to T c , wire network behaviour is only present in a very narrow temperature window close to T c . In this temperature interval, contributions from both mechanisms are operational but can be experimentally distinguished. (papers)

Adaptive Networks Theory, Models and Applications

CERN Document Server

Gross, Thilo

2009-01-01

With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. Some of those phenomena include robust self-organization towards dynamical criticality, formation of complex global topologies based on simple, local rules, and the spontaneous division of "labor" in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. These are just a few. This book is a state-of-the-art survey of those unique networks. In it, leading researchers set out to define the future scope and direction of some of the most advanced developments in the vast field of complex network science and its applications.

Field trials of 100G and beyond: an operator's point of view

Science.gov (United States)

Vorbeck, S.; Schneiders, M.; Weiershausen, W.; Mayer, H.; Schippel, A.; Wagner, P.; Ehrhardt, A.; Braun, R.; Breuer, D.; Drafz, U.; Fritzsche, D.

2011-01-01

In this article we present a summary of the latest 100 Gbps field trials in the network of Deutsche Telekom AG with industry partners. We cover a brown field approach as alien wavelength on existing systems, a green field high speed overlay network approach and a high speed interface router-router coupling.

Constructing an Intelligent Patent Network Analysis Method

Directory of Open Access Journals (Sweden)

Chao-Chan Wu

2012-11-01

Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

Advanced Networks in Motion Mobile Sensorweb

Science.gov (United States)

Ivancic, William D.; Stewart, David H.

2011-01-01

Advanced mobile networking technology applicable to mobile sensor platforms was developed, deployed and demonstrated. A two-tier sensorweb design was developed. The first tier utilized mobile network technology to provide mobility. The second tier, which sits above the first tier, utilizes 6LowPAN (Internet Protocol version 6 Low Power Wireless Personal Area Networks) sensors. The entire network was IPv6 enabled. Successful mobile sensorweb system field tests took place in late August and early September of 2009. The entire network utilized IPv6 and was monitored and controlled using a remote Web browser via IPv6 technology. This paper describes the mobile networking and 6LowPAN sensorweb design, implementation, deployment and testing as well as wireless systems and network monitoring software developed to support testing and validation.

Synchronization in node of complex networks consist of complex chaotic system

Energy Technology Data Exchange (ETDEWEB)

Wei, Qiang, E-mail: qiangweibeihua@163.com [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024 (China); Xie, Cheng-jun [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Liu, Hong-jun [School of Information Engineering, Weifang Vocational College, Weifang, 261041 (China); Li, Yan-hui [The Library, Weifang Vocational College, Weifang, 261041 (China)

2014-07-15

A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

Advances in neural networks computational and theoretical issues

CERN Document Server

Esposito, Anna; Morabito, Francesco

2015-01-01

This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and  bio-inspired memristor-based networks.  Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive, and context-aware Information Communication Technologies.

Swelling characteristics of acrylic acid polyelectrolyte hydrogel in a dc electric field

Science.gov (United States)

Jabbari, Esmaiel; Tavakoli, Javad; Sarvestani, Alireza S.

2007-10-01

A novel application of environmentally sensitive polyelectrolytes is in the fabrication of BioMEMS devices as sensors and actuators. Poly(acrylic acid) (PAA) gels are anionic polyelectrolyte networks that exhibit volume expansion in aqueous physiological environments. When an electric field is applied to PAA polyelectrolyte gels, the fixed anionic polyelectrolyte charges and the requirement of electro-neutrality in the network generate an osmotic pressure, above that in the absence of the electric field, to expand the network. The objective of this research was to investigate the effect of an externally applied dc electric field on the volume expansion of the PAA polyelectrolyte gel in a simulated physiological solution of phosphate buffer saline (PBS). For swelling studies in the electric field, two platinum-coated plates, as electrodes, were wrapped in a polyethylene sheet to protect the plates from corrosion and placed vertically in a vessel filled with PBS. The plates were placed on a rail such that the distance between the two plates could be adjusted. The PAA gel was synthesized by free radical crosslinking of acrylic acid monomer with ethylene glycol dimethacrylate (EGDMA) crosslinker. Our results demonstrate that volume expansion depends on the intensity of the electric field, the PAA network density, network homogeneity, and the position of the gel in the field relative to positive/negative electrodes. Our model predictions for PAA volume expansion, based on the dilute electrolyte concentration in the gel network, is in excellent agreement with the experimental findings in the high-electric-field regime (250-300 Newton/Coulomb).

An Overview of Computer Network security and Research Technology

OpenAIRE

Rathore, Vandana

2016-01-01

The rapid development in the field of computer networks and systems brings both convenience and security threats for users. Security threats include network security and data security. Network security refers to the reliability, confidentiality, integrity and availability of the information in the system. The main objective of network security is to maintain the authenticity, integrity, confidentiality, availability of the network. This paper introduces the details of the technologies used in...

Network models in economics and finance

CERN Document Server

Pardalos, Panos; Rassias, Themistocles

2014-01-01

Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis  that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.

Mobile social networking an innovative approach

CERN Document Server

Zhang, Daqing

2014-01-01

The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.

Network Coding Over The 232

DEFF Research Database (Denmark)

Pedersen, Morten Videbæk; Heide, Janus; Vingelmann, Peter

2013-01-01

Creating efficient finite field implementations has been an active research topic for several decades. Many appli- cations in areas such as cryptography, signal processing, erasure coding and now also network coding depend on this research to deliver satisfactory performance. In this paper we...... from a benchmark application written in C++. These results are finally compared to different binary and binary extension field implementations. The results show that the prime field implementation offers a large field size while maintaining a very good performance. We believe that using prime fields...

Designing Security-Hardened Microkernels For Field Devices

Science.gov (United States)

Hieb, Jeffrey; Graham, James

Distributed control systems (DCSs) play an essential role in the operation of critical infrastructures. Perimeter field devices are important DCS components that measure physical process parameters and perform control actions. Modern field devices are vulnerable to cyber attacks due to their increased adoption of commodity technologies and that fact that control networks are no longer isolated. This paper describes an approach for creating security-hardened field devices using operating system microkernels that isolate vital field device operations from untrusted network-accessible applications. The approach, which is influenced by the MILS and Nizza architectures, is implemented in a prototype field device. Whereas, previous microkernel-based implementations have been plagued by poor inter-process communication (IPC) performance, the prototype exhibits an average IPC overhead for protected device calls of 64.59 μs. The overall performance of field devices is influenced by several factors; nevertheless, the observed IPC overhead is low enough to encourage the continued development of the prototype.

YoungRad-seminar. Proceedings. Seminar for young scientists in the fields of radiophysics, radiochemistry, radioecology, radiation protection and related fields

International Nuclear Information System (INIS)

Straelberg, E.; Sidhu, R.; Petersen, R.; Salminen, S.

2007-09-01

To provide an inspiring working environment for young students and scientists, it is important that they at an early stage can take part in a network of scientists working in their fields of interest. However, within each of the five Nordic countries the network of people involved in the fields of radiophysics, radiochemistry, radioecology, radiation protection and other related fields is rather small. Educational networking is a key factor in keeping young researchers motivated to continue working within these fields, and to recruit new students. For that reason the first YoungRad-seminar was held in Helsinki 14-15 December 2006. 43 young participants including MSc and PhD students at universities, researchers at different institutes and personnel from Nordic authorities took part in the seminar. All Nordic countries except Iceland were represented. The seminar was divided into four sessions including oral and poster presentations. In addition two senior researchers were invited to speak about Nordic radioecology and NKS. This report contains the abstracts and presentations made at the seminar. (au)

YoungRad-seminar. Proceedings. Seminar for young scientists in the fields of radiophysics, radiochemistry, radioecology, radiation protection and related fields

Energy Technology Data Exchange (ETDEWEB)

Straelberg, E; Sidhu, R [Institute for Energy Technology (Norway); Petersen, R [Technological Univ. of Denmark (Denmark); Salminen, S [Univ. of Helsinki (Finland)

2007-09-15

To provide an inspiring working environment for young students and scientists, it is important that they at an early stage can take part in a network of scientists working in their fields of interest. However, within each of the five Nordic countries the network of people involved in the fields of radiophysics, radiochemistry, radioecology, radiation protection and other related fields is rather small. Educational networking is a key factor in keeping young researchers motivated to continue working within these fields, and to recruit new students. For that reason the first YoungRad-seminar was held in Helsinki 14-15 December 2006. 43 young participants including MSc and PhD students at universities, researchers at different institutes and personnel from Nordic authorities took part in the seminar. All Nordic countries except Iceland were represented. The seminar was divided into four sessions including oral and poster presentations. In addition two senior researchers were invited to speak about Nordic radioecology and NKS. This report contains the abstracts and presentations made at the seminar. (au)

The development of the INGV tectonomagnetic network in the frame of the MEM Project

Directory of Open Access Journals (Sweden)

F. Masci

2007-08-01

Full Text Available In the middle of 1989, the INGV (Italian Istituto Nazionale di Geofisica e Vulcanologia installed in Central Italy a network of magnetic stations in order to investigate possible relationship of the local magnetic field with earthquakes occurrences. Actually the network consists of four stations, where the total magnetic field intensity data are being collected using proton precession magnetometers. Here we are report on the actual state and the future developments of the network. In the frame of the MEM (Magnetic and Electric fields Monitoring Project, new stations will be added to the network by the end of 2007. The results of the test campaigns carried out in the sites chosen to widen the network are also discussed. Moreover, the 2006 complete data set of the network is also reported. Concerning the data analysis, a new approach is also discussed that takes into account the inductive effects on the local geomagnetic field by means of the inter-station transfer functions time variations analysis.

Wireless local area network. A new technology of network

International Nuclear Information System (INIS)

Wu Yunjun; Zhao Zongtao

2003-01-01

This paper introduces Wireless Local Area Network (WLAN), including the concept, history, characters and the foreground of its development, it also narrates in detail the several key techniques used to implement IEEE802.11 WLAN, and ideas on key technology of future progress in wireless LAN field have also been presented. (authors)

Applying Neural Networks to Hyperspectral and Multispectral Field Data for Discrimination of Cruciferous Weeds in Winter Crops

Directory of Open Access Journals (Sweden)

Ana-Isabel de Castro

2012-01-01

Full Text Available In the context of detection of weeds in crops for site-specific weed control, on-ground spectral reflectance measurements are the first step to determine the potential of remote spectral data to classify weeds and crops. Field studies were conducted for four years at different locations in Spain. We aimed to distinguish cruciferous weeds in wheat and broad bean crops, using hyperspectral and multispectral readings in the visible and near-infrared spectrum. To identify differences in reflectance between cruciferous weeds, we applied three classification methods: stepwise discriminant (STEPDISC analysis and two neural networks, specifically, multilayer perceptron (MLP and radial basis function (RBF. Hyperspectral and multispectral signatures of cruciferous weeds, and wheat and broad bean crops can be classified using STEPDISC analysis, and MLP and RBF neural networks with different success, being the MLP model the most accurate with 100%, or higher than 98.1%, of classification performance for all the years. Classification accuracy from hyperspectral signatures was similar to that from multispectral and spectral indices, suggesting that little advantage would be obtained by using more expensive airborne hyperspectral imagery. Therefore, for next investigations, we recommend using multispectral remote imagery to explore whether they can potentially discriminate these weeds and crops.

Google matrix analysis of directed networks

Science.gov (United States)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2015-10-01

In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

Diffusion of the vertical field into the tape-wound magnet

International Nuclear Information System (INIS)

Gottardi, N.; Mast, F.; Preis, H.; Suess, R.

1981-07-01

A computer program was developed to calculate eddy currents in electrically conducting structures of general geometry in order to determine their magnetic fields. The program is based on the finite element network method (FEN), in which the structure considered is divided into directed, finite elements. Each element is then treated as a branch of a three-dimensional RL network. After R and L in all of the network branches have been calculated, the network differential equations represented in matrix form is solved. The time behaviour and distribution of the eddy currents then follow directly from the solution vector of the transient branch currents. The FEN is tested in the case of vertical field diffusion through the toroidal field coils of ZEPHYR. For this purpose an electrical model of the coil configurations was constructed on a scale of 1:5. The scaling laws applied are described. A detailed description of the measuring method used is given. The results of the calculations and measurements are compared for various frequencies of the vertical field. (orig./HT)

Handbook of social network technologies and applications

CERN Document Server

Furht, Borko

2010-01-01

Social networking is a concept that has existed for a long time; however, with the explosion of the Internet, social networking has become a tool for people to connect and communicate in ways that were impossible in the past. The recent development of Web 2.0 has provided many new applications, such as Myspace, Facebook, and LinkedIn. The purpose of ""Handbook of Social Networks: Technologies and Applications"" is to provide comprehensive guidelines on the current and future trends in social network technologies and applications in the field of Web-based Social Networks. This handbook includes

Small-Firm Networks: hybrid arrangement or organizational form?

OpenAIRE

Verschoore, Jorge Renato; Balestrin, Alsones; Perucia, Alexandre

2014-01-01

In the field of organizations, one relevant question is whether or not to consider networks as organizational forms. On the one hand, Williamson (1985) says that networks are hybrid arrangements. On the other, authors like Powell (1990) argue that networks constitute themselves as organizational forms. Given this dilemma, the present article proposes the analysis of organizational characteristics of small-firm networks (SFN). To reach such objective, twelve SFNs in distinct stages of developm...

On the rationality of network development : the case of the Belgian highway network

OpenAIRE

Vanoutrive, Thomas; Damme, Van, Ilja; De Block, Greet

2016-01-01

Abstract: The development of transport networks has been explained, predicted and planned using a variety of methodological approaches. These range from narrative historical accounts to the application of models borrowed from the natural sciences, the latter being predominant in the field of transport economics. Probably the most remarkable example is the mimicking of highway networks by slime mould in Petri dishes. The aim of this paper is to examine and compare methods used to hypothesise o...

Application of artificial neural network for development of an algorithm for TLD badge system in the mixed field dosimetry of X and gamma radiation in terms of Hp(10)

International Nuclear Information System (INIS)

Srivastava, K.; Bakshi, A.K.; Geetha, V.; Kher, R.K.; Dhar, V.K.

2005-01-01

ICRU has introduced new operational quantities for individual monitoring. Therefore it is required to develop an algorithm that gives direct response of the TLD badge in terms of the operational quantities. For this purpose and also to improve the precision in the mixed fields dosimetry, two methods were studied i)- analytical method by developing an algorithm based on of higher order polynomial fit of the data points for known delivered doses and ii) use of Artificial Neural Network (ANN). Study on the response of the TLD badge system based on CaSO 4 : Dy Teflon TLD discs in the mixed fields of X and gamma radiation in terms of operational quantity Hp(10) was carried out using the prevalent algorithm, algorithm developed using higher order polynomial and neural network predicted algorithm for different proportion of dose delivered by X and gamma radiations. It was found that the uncertainties in the dose response for few fields are beyond the acceptable limit for prevalent algorithm and within the acceptable limit for other two algorithms. Algorithm based on ANN gives higher precision in the mixed field of two radiations compared to other two algorithms. (author)

Airborne Tactical Data Network Gateways: Evaluating EPLRS' Ability to Integrate With Wireless Meshed Networks

National Research Council Canada - National Science Library

Bey, Christopher S

2005-01-01

... and 802.16 standards and prevalent developing meshed network routing protocols. Finally, this thesis evaluates fielded and emergent technologies to see if they are suitable to build and to sustain...

Analysis of a solar collector field water flow network

Science.gov (United States)

Rohde, J. E.; Knoll, R. H.

1976-01-01

A number of methods are presented for minimizing the water flow variation in the solar collector field for the Solar Building Test Facility at the Langley Research Center. The solar collector field investigated consisted of collector panels connected in parallel between inlet and exit collector manifolds to form 12 rows. The rows were in turn connected in parallel between the main inlet and exit field manifolds to complete the field. The various solutions considered included various size manifolds, manifold area change, different locations for the inlets and exits to the manifolds, and orifices or flow control valves. Calculations showed that flow variations of less than 5 percent were obtainable both inside a row between solar collector panels and between various rows.

Integrated field modelling[Oil and gas fields

Energy Technology Data Exchange (ETDEWEB)

Nazarian, Bamshad

2002-07-01

This research project studies the feasibility of developing and applying an integrated field simulator to simulate the production performance of an entire oil or gas field. It integrates the performance of the reservoir, the wells, the chokes, the gathering system, the surface processing facilities and whenever applicable, gas and water injection systems. The approach adopted for developing the integrated simulator is to couple existing commercial reservoir and process simulators using available linking technologies. The simulators are dynamically linked and customised into a single hybrid application that benefits from the concept of open software architecture. The integrated field simulator is linked to an optimisation routine developed based on the genetic algorithm search strategies. This enables optimisation of the system at field level, from the reservoir to the process. Modelling the wells and the gathering network is achieved by customising the process simulator. This study demonstrated that the integrated simulation improves current capabilities to simulate the performance of the entire field and optimise its design. This is achieved by evaluating design options including spread and layout of the wells and gathering system, processing alternatives, reservoir development schemes and production strategies. Effectiveness of the integrated simulator is demonstrated and tested through several field-level case studies that discuss and investigate technical problems relevant to offshore field development. The case studies cover topics such as process optimisation, optimum tie-in of satellite wells into existing process facilities, optimal well location and field layout assessment of a high pressure high temperature deepwater oil field. Case study results confirm the viability of the total field simulator by demonstrating that the field performance simulation and optimal design were obtained in an automated process with treasonable computation time. No significant

Surrogate-assisted identification of influences of network construction on evolving weighted functional networks

Science.gov (United States)

Stahn, Kirsten; Lehnertz, Klaus

2017-12-01

We aim at identifying factors that may affect the characteristics of evolving weighted networks derived from empirical observations. To this end, we employ various chains of analysis that are often used in field studies for a data-driven derivation and characterization of such networks. As an example, we consider fully connected, weighted functional brain networks before, during, and after epileptic seizures that we derive from multichannel electroencephalographic data recorded from epilepsy patients. For these evolving networks, we estimate clustering coefficient and average shortest path length in a time-resolved manner. Lastly, we make use of surrogate concepts that we apply at various levels of the chain of analysis to assess to what extent network characteristics are dominated by properties of the electroencephalographic recordings and/or the evolving weighted networks, which may be accessible more easily. We observe that characteristics are differently affected by the unavoidable referencing of the electroencephalographic recording, by the time-series-analysis technique used to derive the properties of network links, and whether or not networks were normalized. Importantly, for the majority of analysis settings, we observe temporal evolutions of network characteristics to merely reflect the temporal evolutions of mean interaction strengths. Such a property of the data may be accessible more easily, which would render the weighted network approach—as used here—as an overly complicated description of simple aspects of the data.

Animal Telemetry Network (ATN)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These data (updated daily) are from the Animal Telemetry Network (ATN) program. Begun as one of the field projects in the international Census of Marine Life, the...

Hydrologic behavior of fracture networks

International Nuclear Information System (INIS)

Long, J.C.S.; Endo, H.K.; Karasaki, K.; Pyrak, L.; MacLean, P.; Witherspoon, P.A.

1985-01-01

This paper reviews recent research on the nature of flow and transport in discontinuous fracture networks. The hydrologic behavior of these networks has been examined using two- and three-dimensional numerical models. The numerical models represent random realizations of fracture networks based on statistical field measurements of fracture geometry and equivalent hydraulic aperture. The authors have compared the flux and mechanical transported behavior of these networks to the behavior of equivalent continua. In this way they were able to determine whether a given fracture network could be modeled as an equivalent porous media in both flux and advective transport studies. They have examined departures from porous media behavior both as a function of interconnectivity and heterogeneity. Parameter studies have revealed behavior patterns such as: given a fracture frequency that can be measured in the field, porous media like behavior and the magnitude of permeability are both enhanced if the fractures are longer and the standard deviation of fracture permeabilities is smaller. The behavior of well tests in fractured networks has been modeled and compared to a new analytical well test solution which accounts for the early time dominance of the fractures intersecting the well. Finally, a three-dimensional fracture flow model has been constructed which assumes fractures are randomly located discs. This model has been constructed which assumes fractures are randomly located discs. This model uses a semi-analytical solution for flow such that it is relatively easy to use the model as a tool for stochastic analysis. 13 references, 12 figures

Critical behavior of the contact process on small-world networks

Science.gov (United States)

Ferreira, Ronan S.; Ferreira, Silvio C.

2013-11-01

We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.

Security in wireless sensor networks

CERN Document Server

Oreku, George S

2016-01-01

This monograph covers different aspects of sensor network security including new emerging technologies. The authors present a mathematical approach to the topic and give numerous practical examples as well as case studies to illustrate the theory. The target audience primarily comprises experts and practitioners in the field of sensor network security, but the book may also be beneficial for researchers in academia as well as for graduate students.

Similarity facilitates relationships on social networks: a field experiment on facebook.

Science.gov (United States)

Martin, Angélique; Jacob, Céline; Guéguen, Nicolas

2013-08-01

People interact more readily with someone with whom they think they have something in common, but the effect of an incidental similarity has never been examined on social networks. Facebook users were contacted by a stranger who also possessed a Facebook page and who asked them to become his friend. The request message contained one item of similarity, two items of similarity, or none. Compliance to the request was the dependent variable. Increased compliance to the request was found when comparing the two similarity conditions with the control no-similarity condition. However, no difference was found between the two similarity conditions. Similarity appears to foster relationships on social networks.

Separation prediction in two dimensional boundary layer flows using artificial neural networks

International Nuclear Information System (INIS)

Sabetghadam, F.; Ghomi, H.A.

2003-01-01

In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

Modeling geomagnetic induced currents in Australian power networks

Science.gov (United States)

Marshall, R. A.; Kelly, A.; Van Der Walt, T.; Honecker, A.; Ong, C.; Mikkelsen, D.; Spierings, A.; Ivanovich, G.; Yoshikawa, A.

2017-07-01

Geomagnetic induced currents (GICs) have been considered an issue for high-latitude power networks for some decades. More recently, GICs have been observed and studied in power networks located in lower latitude regions. This paper presents the results of a model aimed at predicting and understanding the impact of geomagnetic storms on power networks in Australia, with particular focus on the Queensland and Tasmanian networks. The model incorporates a "geoelectric field" determined using a plane wave magnetic field incident on a uniform conducting Earth, and the network model developed by Lehtinen and Pirjola (1985). Model results for two intense geomagnetic storms of solar cycle 24 are compared with transformer neutral monitors at three locations within the Queensland network and one location within the Tasmanian network. The model is then used to assess the impacts of the superintense geomagnetic storm of 29-31 October 2003 on the flow of GICs within these networks. The model results show good correlation with the observations with coefficients ranging from 0.73 to 0.96 across the observing sites. For Queensland, modeled GIC magnitudes during the superstorm of 29-31 October 2003 exceed 40 A with the larger GICs occurring in the south-east section of the network. Modeled GICs in Tasmania for the same storm do not exceed 30 A. The larger distance spans and general east-west alignment of the southern section of the Queensland network, in conjunction with some relatively low branch resistance values, result in larger modeled GICs despite Queensland being a lower latitude network than Tasmania.

Friendly network robotics; Friendly network robotics

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-03-01

A working group (WG) study was conducted aiming at realizing human type robots. The following six working groups in the basement field were organized to study in terms mostly of items of technical development and final technical targets: platform, and remote attendance control in the basement field, maintenance of plant, etc., home service, disaster/construction, and entertainment in the application field. In the platform WG, a robot of human like form is planning which walks with two legs and works with two arms, and the following were discussed: a length of 160cm, weight of 110kg, built-in LAN, actuator specifications, modulated structure, intelligent driver, etc. In the remote attendance control WG, remote control using working function, stabilized movement, stabilized control, and network is made possible. Studied were made on the decision on a remote control cockpit by open architecture added with function and reformable, problems on the development of the standard language, etc. 77 ref., 82 figs., 21 tabs.

Self-Healing Networks: Redundancy and Structure

Science.gov (United States)

Quattrociocchi, Walter; Caldarelli, Guido; Scala, Antonio

2014-01-01

We introduce the concept of self-healing in the field of complex networks modelling; in particular, self-healing capabilities are implemented through distributed communication protocols that exploit redundant links to recover the connectivity of the system. We then analyze the effect of the level of redundancy on the resilience to multiple failures; in particular, we measure the fraction of nodes still served for increasing levels of network damages. Finally, we study the effects of redundancy under different connectivity patterns—from planar grids, to small-world, up to scale-free networks—on healing performances. Small-world topologies show that introducing some long-range connections in planar grids greatly enhances the resilience to multiple failures with performances comparable to the case of the most resilient (and least realistic) scale-free structures. Obvious applications of self-healing are in the important field of infrastructural networks like gas, power, water, oil distribution systems. PMID:24533065

Understanding Knowledge Network, Learning and Connectivism

Science.gov (United States)

AlDahdouh, Alaa A.; Osório, António J.; Caires, Susana

2015-01-01

Behaviorism, Cognitivism, Constructivism and other growing theories such as Actor-Network and Connectivism are circulating in the educational field. For each, there are allies who stand behind research evidence and consistency of observation. Meantime, those existing theories dominate the field until the background is changed or new concrete…

How to construct the statistic network? An association network of herbaceous

Directory of Open Access Journals (Sweden)

WenJun Zhang

2012-06-01

Full Text Available In present study I defined a new type of network, the statistic network. The statistic network is a weighted and non-deterministic network. In the statistic network, a connection value, i.e., connection weight, represents connection strength and connection likelihood between two nodes and its absolute value falls in the interval (0,1]. The connection value is expressed as a statistical measure such as correlation coefficient, association coefficient, or Jaccard coefficient, etc. In addition, all connections of the statistic network can be statistically tested for their validity. A connection is true if the connection value is statistically significant. If all connection values of a node are not statistically significant, it is an isolated node. An isolated node has not any connection to other nodes in the statistic network. Positive and negative connection values denote distinct connectiontypes (positive or negative association or interaction. In the statistic network, two nodes with the greater connection value will show more similar trend in the change of their states. At any time we can obtain a sample network of the statistic network. A sample network is a non-weighted and deterministic network. Thestatistic network, in particular the plant association network that constructed from field sampling, is mostly an information network. Most of the interspecific relationships in plant community are competition and cooperation. Therefore in comparison to animal networks, the methodology of statistic network is moresuitable to construct plant association networks. Some conclusions were drawn from this study: (1 in the plant association network, most connections are weak and positive interactions. The association network constructed from Spearman rank correlation has most connections and isolated taxa are fewer. From net linear correlation,linear correlation, to Spearman rank correlation, the practical number of connections and connectance in the

Mode Choice Modeling Using Artificial Neural Networks

OpenAIRE

Edara, Praveen Kumar

2003-01-01

Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data becom...

Enabling Wireless Cooperation in User Provided Networks

OpenAIRE

Rolla, Vitor Guerra

2015-01-01

Tese de doutoramento em Ciências e Tecnologias da Informação, apresentada ao Departamento de Engenharia Informática da Faculdade de Ciências e Tecnologia da Universidade de Coimbra This doctoral thesis investigates user provided networks. Such networks have become important research subjects in the field of informatics engineering due to the recent popularity of smart phones. User provided networks are independent from traditional Internet service providers. Communication and informati...