WorldWideScience

Sample records for single network archtecture

  1. Single promoters as regulatory network motifs

    Science.gov (United States)

    Zopf, Christopher; Maheshri, Narendra

    2012-02-01

    At eukaryotic promoters, chromatin can influence the relationship between a gene's expression and transcription factor (TF) activity. This additional complexity might allow single promoters to exhibit dynamical behavior commonly attributed to regulatory motifs involving multiple genes. We investigate the role of promoter chromatin architecture in the kinetics of gene activation using a previously described set of promoter variants based on the phosphate-regulated PHO5 promoter in S. cerevisiae. Accurate quantitative measurement of transcription activation kinetics is facilitated by a controllable and observable TF input to a promoter of interest leading to an observable expression output in single cells. We find the particular architecture of these promoters can result in a significant delay in activation, filtering of noisy TF signals, and a memory of previous activation -- dynamical behaviors reminiscent of a feed-forward loop but only requiring a single promoter. We suggest this is a consequence of chromatin transactions at the promoter, likely passing through a long-lived ``primed'' state between its inactive and competent states. Finally, we show our experimental setup can be generalized as a ``gene oscilloscope'' to probe the kinetics of heterologous promoter architectures.

  2. Single-shot secure quantum network coding on butterfly network with free public communication

    Science.gov (United States)

    Owari, Masaki; Kato, Go; Hayashi, Masahito

    2018-01-01

    Quantum network coding on the butterfly network has been studied as a typical example of quantum multiple cast network. We propose a secure quantum network code for the butterfly network with free public classical communication in the multiple unicast setting under restricted eavesdropper’s power. This protocol certainly transmits quantum states when there is no attack. We also show the secrecy with shared randomness as additional resource when the eavesdropper wiretaps one of the channels in the butterfly network and also derives the information sending through public classical communication. Our protocol does not require verification process, which ensures single-shot security.

  3. Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

    Directory of Open Access Journals (Sweden)

    Jibing Wu

    Full Text Available Heterogeneous information networks (e.g. bibliographic networks and social media networks that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

  4. Single Frequency Network Based Distributed Passive Radar Technology

    Directory of Open Access Journals (Sweden)

    Wan Xian-rong

    2015-01-01

    Full Text Available The research and application of passive radar are heading from single transmitter-receiver pair to multiple transmitter-receiver pairs. As an important class of the illuminators of opportunity, most of modern digital broadcasting and television systems work on Single Frequency Network (SFN, which intrinsically determines that the passive radar based on such illuminators must be distributed and networked. In consideration of the remarkable working and processing mode of passive radar under SFN configuration, this paper proposes the concept of SFN-based Distributed Passive Radar (SDPR. The main characteristics and key problems of SDPR are first described. Then several potential solutions are discussed for part of the key technologies. The feasibility of SDPR is demonstrated by preliminary experimental results. Finally, the concept of four network convergence that includes the broadcast based passive radar network is conceived, and its application prospects are discussed.

  5. Automatic network fingerprinting through single-node motifs.

    Directory of Open Access Journals (Sweden)

    Christoph Echtermeyer

    Full Text Available Complex networks have been characterised by their specific connectivity patterns (network motifs, but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009. Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

  6. Kernel Function Tuning for Single-Layer Neural Networks

    Czech Academy of Sciences Publication Activity Database

    Vidnerová, Petra; Neruda, Roman

    -, accepted 28.11. 2017 (2018) ISSN 2278-0149 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : single-layer neural networks * kernel methods * kernel function * optimisation Subject RIV: IN - Informatics, Computer Science http://www.ijmerr.com/

  7. Addressing congestion on single allocation hub-and-spoke networks

    Directory of Open Access Journals (Sweden)

    Ricardo Saraiva de Camargo

    2012-12-01

    Full Text Available When considering hub-and-spoke networks with single allocation, the absence of alternative routes makes this kind of systems specially vulnerable to congestion effects. In order to improve the design of such networks, congestion costs must be addressed. This article deploys two different techniques for addressing congestion on single allocation hub-and-spoke networks: the Generalized Benders Decomposition and the Outer Approximation method. Both methods are able to solve large scale instances. Computational experiments show how the adoption of advanced solution strategies, such as Pareto-optimal cut generation on the Master Problem branch-and-bound tree, may be decisive. They also demonstrate that the solution effort is not only associated with the size of the instances, but also with their combination of the installation and congestion costs.

  8. A Single-Walled Carbon Nanotube Network Gas Sensing Device

    Directory of Open Access Journals (Sweden)

    I-Ju Teng

    2011-08-01

    Full Text Available The goal of this research was to develop a chemical gas sensing device based on single-walled carbon nanotube (SWCNT networks. The SWCNT networks are synthesized on Al2O3-deposted SiO2/Si substrates with 10 nm-thick Fe as the catalyst precursor layer using microwave plasma chemical vapor deposition (MPCVD. The development of interconnected SWCNT networks can be exploited to recognize the identities of different chemical gases by the strength of their particular surface adsorptive and desorptive responses to various types of chemical vapors. The physical responses on the surface of the SWCNT networks cause superficial changes in the electric charge that can be converted into electronic signals for identification. In this study, we tested NO2 and NH3 vapors at ppm levels at room temperature with our self-made gas sensing device, which was able to obtain responses to sensitivity changes with a concentration of 10 ppm for NO2 and 24 ppm for NH3.

  9. Improving the Reliability of Network Metrics in Structural Brain Networks by Integrating Different Network Weighting Strategies into a Single Graph

    Directory of Open Access Journals (Sweden)

    Stavros I. Dimitriadis

    2017-12-01

    Full Text Available Structural brain networks estimated from diffusion MRI (dMRI via tractography have been widely studied in healthy controls and patients with neurological and psychiatric diseases. However, few studies have addressed the reliability of derived network metrics both node-specific and network-wide. Different network weighting strategies (NWS can be adopted to weight the strength of connection between two nodes yielding structural brain networks that are almost fully-weighted. Here, we scanned five healthy participants five times each, using a diffusion-weighted MRI protocol and computed edges between 90 regions of interest (ROI from the Automated Anatomical Labeling (AAL template. The edges were weighted according to nine different methods. We propose a linear combination of these nine NWS into a single graph using an appropriate diffusion distance metric. We refer to the resulting weighted graph as an Integrated Weighted Structural Brain Network (ISWBN. Additionally, we consider a topological filtering scheme that maximizes the information flow in the brain network under the constraint of the overall cost of the surviving connections. We compared each of the nine NWS and the ISWBN based on the improvement of: (a intra-class correlation coefficient (ICC of well-known network metrics, both node-wise and per network level; and (b the recognition accuracy of each subject compared to the remainder of the cohort, as an attempt to access the uniqueness of the structural brain network for each subject, after first applying our proposed topological filtering scheme. Based on a threshold where the network level ICC should be >0.90, our findings revealed that six out of nine NWS lead to unreliable results at the network level, while all nine NWS were unreliable at the node level. In comparison, our proposed ISWBN performed as well as the best performing individual NWS at the network level, and the ICC was higher compared to all individual NWS at the node

  10. Interpretable deep neural networks for single-trial EEG classification.

    Science.gov (United States)

    Sturm, Irene; Lapuschkin, Sebastian; Samek, Wojciech; Müller, Klaus-Robert

    2016-12-01

    In cognitive neuroscience the potential of deep neural networks (DNNs) for solving complex classification tasks is yet to be fully exploited. The most limiting factor is that DNNs as notorious 'black boxes' do not provide insight into neurophysiological phenomena underlying a decision. Layer-wise relevance propagation (LRP) has been introduced as a novel method to explain individual network decisions. We propose the application of DNNs with LRP for the first time for EEG data analysis. Through LRP the single-trial DNN decisions are transformed into heatmaps indicating each data point's relevance for the outcome of the decision. DNN achieves classification accuracies comparable to those of CSP-LDA. In subjects with low performance subject-to-subject transfer of trained DNNs can improve the results. The single-trial LRP heatmaps reveal neurophysiologically plausible patterns, resembling CSP-derived scalp maps. Critically, while CSP patterns represent class-wise aggregated information, LRP heatmaps pinpoint neural patterns to single time points in single trials. We compare the classification performance of DNNs to that of linear CSP-LDA on two data sets related to motor-imaginary BCI. We have demonstrated that DNN is a powerful non-linear tool for EEG analysis. With LRP a new quality of high-resolution assessment of neural activity can be reached. LRP is a potential remedy for the lack of interpretability of DNNs that has limited their utility in neuroscientific applications. The extreme specificity of the LRP-derived heatmaps opens up new avenues for investigating neural activity underlying complex perception or decision-related processes. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Dürr, Oliver; Sick, Beate

    2016-10-01

    Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning methods to high-content screening-based phenotype classification. We trained a deep learning classifier in the form of convolutional neural networks with approximately 40,000 publicly available single-cell images from samples treated with compounds from four classes known to lead to different phenotypes. The input data consisted of multichannel images. The construction of appropriate feature definitions was part of the training and carried out by the convolutional network, without the need for expert knowledge or handcrafted features. We compare our results against the recent state-of-the-art pipeline in which predefined features are extracted from each cell using specialized software and then fed into various machine learning algorithms (support vector machine, Fisher linear discriminant, random forest) for classification. The performance of all classification approaches is evaluated on an untouched test image set with known phenotype classes. Compared to the best reference machine learning algorithm, the misclassification rate is reduced from 8.9% to 6.6%. © 2016 Society for Laboratory Automation and Screening.

  12. Structural Controllability of Temporal Networks with a Single Switching Controller

    Science.gov (United States)

    Yao, Peng; Hou, Bao-Yu; Pan, Yu-Jian; Li, Xiang

    2017-01-01

    Temporal network, whose topology evolves with time, is an important class of complex networks. Temporal trees of a temporal network describe the necessary edges sustaining the network as well as their active time points. By a switching controller which properly selects its location with time, temporal trees are used to improve the controllability of the network. Therefore, more nodes are controlled within the limited time. Several switching strategies to efficiently select the location of the controller are designed, which are verified with synthetic and empirical temporal networks to achieve better control performance. PMID:28107538

  13. DEEP ATTRACTOR NETWORK FOR SINGLE-MICROPHONE SPEAKER SEPARATION.

    Science.gov (United States)

    Chen, Zhuo; Luo, Yi; Mesgarani, Nima

    2017-03-01

    Despite the overwhelming success of deep learning in various speech processing tasks, the problem of separating simultaneous speakers in a mixture remains challenging. Two major difficulties in such systems are the arbitrary source permutation and unknown number of sources in the mixture. We propose a novel deep learning framework for single channel speech separation by creating attractor points in high dimensional embedding space of the acoustic signals which pull together the time-frequency bins corresponding to each source. Attractor points in this study are created by finding the centroids of the sources in the embedding space, which are subsequently used to determine the similarity of each bin in the mixture to each source. The network is then trained to minimize the reconstruction error of each source by optimizing the embeddings. The proposed model is different from prior works in that it implements an end-to-end training, and it does not depend on the number of sources in the mixture. Two strategies are explored in the test time, K-means and fixed attractor points, where the latter requires no post-processing and can be implemented in real-time. We evaluated our system on Wall Street Journal dataset and show 5.49% improvement over the previous state-of-the-art methods.

  14. Memory under stress: from single systems to network changes.

    Science.gov (United States)

    Schwabe, Lars

    2017-02-01

    Stressful events have profound effects on learning and memory. These effects are mainly mediated by catecholamines and glucocorticoid hormones released from the adrenals during stressful encounters. It has been known for long that both catecholamines and glucocorticoids influence the functioning of the hippocampus, a critical hub for episodic memory. However, areas implicated in other forms of memory, such as the insula or the dorsal striatum, can be affected by stress as well. Beyond changes in single memory systems, acute stress triggers the reconfiguration of large scale neural networks which sets the stage for a shift from thoughtful, 'cognitive' control of learning and memory toward more reflexive, 'habitual' processes. Stress-related alterations in amygdala connectivity with the hippocampus, dorsal striatum, and prefrontal cortex seem to play a key role in this shift. The bias toward systems proficient in threat processing and the implementation of well-established routines may facilitate coping with an acute stressor. Overreliance on these reflexive systems or the inability to shift flexibly between them, however, may represent a risk factor for psychopathology in the long-run. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  15. Generalized single-hidden layer feedforward networks for regression problems.

    Science.gov (United States)

    Wang, Ning; Er, Meng Joo; Han, Min

    2015-06-01

    In this paper, traditional single-hidden layer feedforward network (SLFN) is extended to novel generalized SLFN (GSLFN) by employing polynomial functions of inputs as output weights connecting randomly generated hidden units with corresponding output nodes. The significant contributions of this paper are as follows: 1) a primal GSLFN (P-GSLFN) is implemented using randomly generated hidden nodes and polynomial output weights whereby the regression matrix is augmented by full or partial input variables and only polynomial coefficients are to be estimated; 2) a simplified GSLFN (S-GSLFN) is realized by decomposing the polynomial output weights of the P-GSLFN into randomly generated polynomial nodes and tunable output weights; 3) both P- and S-GSLFN are able to achieve universal approximation if the output weights are tuned by ridge regression estimators; and 4) by virtue of the developed batch and online sequential ridge ELM (BR-ELM and OSR-ELM) learning algorithms, high performance of the proposed GSLFNs in terms of generalization and learning speed is guaranteed. Comprehensive simulation studies and comparisons with standard SLFNs are carried out on real-world regression benchmark data sets. Simulation results demonstrate that the innovative GSLFNs using BR-ELM and OSR-ELM are superior to standard SLFNs in terms of accuracy, training speed, and structure compactness.

  16. Interacting with Networks : How Does Structure Relate to Controllability in Single-Leader, Consensus Networks?

    NARCIS (Netherlands)

    Egerstedt, Magnus; Martini, Simone; Cao, Ming; Camlibel, Kanat; Bicchi, Antonio

    As networked dynamical systems appear around us at an increasing rate, questions concerning how to manage and control such systems are becoming more important. Examples include multiagent robotics, distributed sensor networks, interconnected manufacturing chains, and data networks. In response to

  17. Leveraging percolation theory to single out influential spreaders in networks

    Science.gov (United States)

    Radicchi, Filippo; Castellano, Claudio

    2016-06-01

    Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of a meme in social media. Despite many recent efforts, the formulation of an accurate method to optimally identify influential nodes in complex network topologies remains an unsolved challenge. Here, we present the exact solution of the problem for the specific, but highly relevant, case of the susceptible-infected-removed (SIR) model for epidemic spreading at criticality. By exploiting the mapping between bond percolation and the static properties of the SIR model, we prove that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality. By means of simulations on synthetic networks and on a very extensive set of real-world networks, we show that the nonbacktracking centrality is a highly reliable metric to identify top influential spreaders also in generic graphs not embedded in space and for noncritical spreading.

  18. Reliability in Single, Double and N2R Ring Network Structures

    DEFF Research Database (Denmark)

    Jørgensen, T.; Pedersen, L.; Pedersen, Jens Myrup

    This paper studies the properties of single, double and N2R ring network structures during link errors. The structure of the network infrastructure must be redesigned in order to fulfil the requirements of services using the Internet in the future; hence, N2R structures have been suggested. N2R s...

  19. Restorability on 3-connected WDM Networks Under Single and Dual Physical Link Failures

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Jensen, Michael; Riaz, Tahir

    2013-01-01

    This work studies the influence the network interconnection has over restoration techniques. The way physical links are distributed to interconnect network nodes has a great impact on parameters such as path distances when failures occur and restoration is applied. The work focuses on single and ...... to network planning, the trade-off network length vs. performance of the different topological options is studied. The results show how 3-connected graphs could provide a reasonable trade-off between costs, link failure rates, and restored path parameters....

  20. Recurrent Neural Network for Single Machine Power System Stabilizer

    Directory of Open Access Journals (Sweden)

    Widi Aribowo

    2010-04-01

    Full Text Available In this paper, recurrent neural network (RNN is used to design power system stabilizer (PSS due to its advantage on the dependence not only on present input but also on past condition. A RNN-PSS is able to capture the dynamic response of a system without any delays caused by external feedback, primarily by the internal feedback loop in recurrent neuron. In this paper, RNNPSS consists of a RNN-identifier and a RNN-controller. The RNN-Identifier functions as the tracker of dynamics characteristics of the plant, while the RNN-controller is used to damp the system’s low frequency oscillations. Simulation results using MATLAB demonstrate that the RNNPSS can successfully damp out oscillation and improve the performance of the system.

  1. Reverse-engineering of gene networks for regulating early blood development from single-cell measurements.

    Science.gov (United States)

    Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai

    2017-12-28

    Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate

  2. Optimized Charging Scheduling with Single Mobile Charger for Wireless Rechargeable Sensor Networks

    Directory of Open Access Journals (Sweden)

    Qihua Wang

    2017-11-01

    Full Text Available Due to the rapid development of wireless charging technology, the recharging issue in wireless rechargeable sensor network (WRSN has been a popular research problem in the past few years. The weakness of previous work is that charging route planning is not reasonable. In this work, a dynamic optimal scheduling scheme aiming to maximize the vacation time ratio of a single mobile changer for WRSN is proposed. In the proposed scheme, the wireless sensor network is divided into several sub-networks according to the initial topology of deployed sensor networks. After comprehensive analysis of energy states, working state and constraints for different sensor nodes in WRSN, we transform the optimized charging path problem of the whole network into the local optimization problem of the sub networks. The optimized charging path with respect to dynamic network topology in each sub-network is obtained by solving an optimization problem, and the lifetime of the deployed wireless sensor network can be prolonged. Simulation results show that the proposed scheme has good and reliable performance for a small wireless rechargeable sensor network.

  3. [Controlling arachidonic acid metabolic network: from single- to multi-target inhibitors of key enzymes].

    Science.gov (United States)

    Liu, Ying; Chen, Zheng; Shang, Er-chang; Yang, Kun; Wei, Deng-guo; Zhou, Lu; Jiang, Xiao-lu; He, Chong; Lai, Lu-hua

    2009-03-01

    Inflammatory diseases are common medical conditions seen in disorders of human immune system. There is a great demand for anti-inflammatory drugs. There are major inflammatory mediators in arachidonic acid metabolic network. Several enzymes in this network have been used as key targets for the development of anti-inflammatory drugs. However, specific single-target inhibitors can not sufficiently control the network balance and may cause side effects at the same time. Most inflammation induced diseases come from the complicated coupling of inflammatory cascades involving multiple targets. In order to treat these complicated diseases, drugs that can intervene multi-targets at the same time attracted much attention. The goal of this review is mainly focused on the key enzymes in arachidonic acid metabolic network, such as phospholipase A2, cyclooxygenase, 5-lipoxygenase and eukotriene A4 hydrolase. Advance in single target and multi-targe inhibitors is summarized.

  4. On the approximation by single hidden layer feedforward neural networks with fixed weights

    OpenAIRE

    Guliyev, Namig J.; Ismailov, Vugar E.

    2017-01-01

    International audience; Feedforward neural networks have wide applicability in various disciplines of science due to their universal approximation property. Some authors have shown that single hidden layer feedforward neural networks (SLFNs) with fixed weights still possess the universal approximation property provided that approximated functions are univariate. But this phenomenon does not lay any restrictions on the number of neurons in the hidden layer. The more this number, the more the p...

  5. Stochastic gene expression in single cells: exploring the importance of noise in genetic networks

    Science.gov (United States)

    van Oudenaarden, Alexander

    2003-03-01

    Cells are intrinsically noisy biochemical reactors. This leads to random cell to cell variation (noise) in gene expression levels. First, I will address the source of this noise at the level of transcription and translation of a single gene. Our experimental results demonstrate that the intrinsic noise of a single gene is predominantly controlled at the translational level, and that increased translational efficiency leads to increased noise strength. This observation is consistent with a theoretical model in which proteins are randomly produced in sharp bursts followed by periods of slow decay. Second, I will explore the importance of genetic noise for a naturally occuring network: the lac operon. The classic lactose utilization network of E. coli has been under investigation for several decades and, in its simplest form the network may be modeled as a single positive feedback module. However, this simplicity is deceptive, as even this basic network is capable of complex metabolic behavior, including adaptation, amplification, and graded-to-binary response conversion. I will present single cell measurements on the expression of key genes in lactose uptake network and explore the importance of genetic noise on the regulation of these genes.

  6. Single bumps in a 2-population homogenized neuronal network model

    Science.gov (United States)

    Kolodina, Karina; Oleynik, Anna; Wyller, John

    2018-05-01

    We investigate existence and stability of single bumps in a homogenized 2-population neural field model, when the firing rate functions are given by the Heaviside function. The model is derived by means of the two-scale convergence technique of Nguetseng in the case of periodic microvariation in the connectivity functions. The connectivity functions are periodically modulated in both the synaptic footprint and in the spatial scale. The bump solutions are constructed by using a pinning function technique for the case where the solutions are independent of the local variable. In the weakly modulated case the generic picture consists of two bumps (one narrow and one broad bump) for each admissible set of threshold values for firing. In addition, a new threshold value regime for existence of bumps is detected. Beyond the weakly modulated regime the number of bumps depends sensitively on the degree of heterogeneity. For the latter case we present a configuration consisting of three coexisting bumps. The linear stability of the bumps is studied by means of the spectral properties of a Fredholm integral operator, block diagonalization of this operator and the Fourier decomposition method. In the weakly modulated regime, one of the bumps is unstable for all relative inhibition times, while the other one is stable for small and moderate values of this parameter. The latter bump becomes unstable as the relative inhibition time exceeds a certain threshold. In the case of the three coexisting bumps detected in the regime of finite degree of heterogeneity, we have at least one stable bump (and maximum two stable bumps) for small and moderate values of the relative inhibition time.

  7. Computing single step operators of logic programming in radial basis function neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia)

    2014-07-10

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

  8. Computing single step operators of logic programming in radial basis function neural networks

    Science.gov (United States)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

    2014-07-01

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (Tp:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

  9. Computing single step operators of logic programming in radial basis function neural networks

    International Nuclear Information System (INIS)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

    2014-01-01

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T p :I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks

  10. Control Method of Single-phase Inverter Based Grounding System in Distribution Networks

    DEFF Research Database (Denmark)

    Wang, Wen; Yan, L.; Zeng, X.

    2016-01-01

    of neutral-to-ground voltage is critical for the safety of distribution networks. An active grounding system based on single-phase inverter is proposed to achieve this objective. Relationship between output current of the system and neutral-to-ground voltage is derived to explain the principle of neutral...

  11. Enhancing network performance under single link failure with AS-disjoint BGP extension

    DEFF Research Database (Denmark)

    Manolova, Anna Vasileva; Romeral, S.; Ruepp, Sarah Renée

    2009-01-01

    In this paper we propose an enhancement of the BGP protocol for obtaining AS-disjoint paths in GMPLS multi-domain networks. We evaluate the benefits of having AS-disjoint paths under single inter-domain link failure for two main applications: routing of future connection requests during routing...... protocol re-convergence and applying multi-domain restoration as survivability mechanism in case of a single link failure. The proposed BGP modification is a simple and effective solution for disjoint path selection in connection-oriented multi-domain networks. Our results show that applying the proper...... failure notification method combined with our proposal reduces the blocking of new connection requests under protocol re-convergence. Furthermore. we show that our proposal is a valuable complementary process for increasing the network resilience....

  12. Multi-Channel Distributed Coordinated Function over Single Radio in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Kok-Keong (Jonathan Loo

    2011-01-01

    Full Text Available Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

  13. Multi-channel distributed coordinated function over single radio in wireless sensor networks.

    Science.gov (United States)

    Campbell, Carlene E-A; Loo, Kok-Keong Jonathan; Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

    2011-01-01

    Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

  14. Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

    Science.gov (United States)

    Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

    2018-03-06

    Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

  15. Inference of a Probabilistic Boolean Network from a Single Observed Temporal Sequence

    Directory of Open Access Journals (Sweden)

    Le Yu

    2007-05-01

    Full Text Available The inference of gene regulatory networks is a key issue for genomic signal processing. This paper addresses the inference of probabilistic Boolean networks (PBNs from observed temporal sequences of network states. Since a PBN is composed of a finite number of Boolean networks, a basic observation is that the characteristics of a single Boolean network without perturbation may be determined by its pairwise transitions. Because the network function is fixed and there are no perturbations, a given state will always be followed by a unique state at the succeeding time point. Thus, a transition counting matrix compiled over a data sequence will be sparse and contain only one entry per line. If the network also has perturbations, with small perturbation probability, then the transition counting matrix would have some insignificant nonzero entries replacing some (or all of the zeros. If a data sequence is sufficiently long to adequately populate the matrix, then determination of the functions and inputs underlying the model is straightforward. The difficulty comes when the transition counting matrix consists of data derived from more than one Boolean network. We address the PBN inference procedure in several steps: (1 separate the data sequence into “pure” subsequences corresponding to constituent Boolean networks; (2 given a subsequence, infer a Boolean network; and (3 infer the probabilities of perturbation, the probability of there being a switch between constituent Boolean networks, and the selection probabilities governing which network is to be selected given a switch. Capturing the full dynamic behavior of probabilistic Boolean networks, be they binary or multivalued, will require the use of temporal data, and a great deal of it. This should not be surprising given the complexity of the model and the number of parameters, both transitional and static, that must be estimated. In addition to providing an inference algorithm

  16. Inference of a Probabilistic Boolean Network from a Single Observed Temporal Sequence

    Directory of Open Access Journals (Sweden)

    Xiao Yufei

    2007-01-01

    Full Text Available The inference of gene regulatory networks is a key issue for genomic signal processing. This paper addresses the inference of probabilistic Boolean networks (PBNs from observed temporal sequences of network states. Since a PBN is composed of a finite number of Boolean networks, a basic observation is that the characteristics of a single Boolean network without perturbation may be determined by its pairwise transitions. Because the network function is fixed and there are no perturbations, a given state will always be followed by a unique state at the succeeding time point. Thus, a transition counting matrix compiled over a data sequence will be sparse and contain only one entry per line. If the network also has perturbations, with small perturbation probability, then the transition counting matrix would have some insignificant nonzero entries replacing some (or all of the zeros. If a data sequence is sufficiently long to adequately populate the matrix, then determination of the functions and inputs underlying the model is straightforward. The difficulty comes when the transition counting matrix consists of data derived from more than one Boolean network. We address the PBN inference procedure in several steps: (1 separate the data sequence into "pure" subsequences corresponding to constituent Boolean networks; (2 given a subsequence, infer a Boolean network; and (3 infer the probabilities of perturbation, the probability of there being a switch between constituent Boolean networks, and the selection probabilities governing which network is to be selected given a switch. Capturing the full dynamic behavior of probabilistic Boolean networks, be they binary or multivalued, will require the use of temporal data, and a great deal of it. This should not be surprising given the complexity of the model and the number of parameters, both transitional and static, that must be estimated. In addition to providing an inference algorithm, this paper

  17. NONLINEAR SYSTEM MODELING USING SINGLE NEURON CASCADED NEURAL NETWORK FOR REAL-TIME APPLICATIONS

    Directory of Open Access Journals (Sweden)

    S. Himavathi

    2012-04-01

    Full Text Available Neural Networks (NN have proved its efficacy for nonlinear system modeling. NN based controllers and estimators for nonlinear systems provide promising alternatives to the conventional counterpart. However, NN models have to meet the stringent requirements on execution time for its effective use in real time applications. This requires the NN model to be structurally compact and computationally less complex. In this paper a parametric method of analysis is adopted to determine the compact and faster NN model among various neural network architectures. This work proves through analysis and examples that the Single Neuron Cascaded (SNC architecture is distinct in providing compact and simpler models requiring lower execution time. The unique structural growth of SNC architecture enables automation in design. The SNC Network is shown to combine the advantages of both single and multilayer neural network architectures. Extensive analysis on selected architectures and their models for four benchmark nonlinear theoretical plants and a practical application are tested. A performance comparison of the NN models is presented to demonstrate the superiority of the single neuron cascaded architecture for online real time applications.

  18. Single-frequency receivers as master permanent stations in GNSS networks: precision and accuracy of the positioning in mixed networks

    Science.gov (United States)

    Dabove, Paolo; Manzino, Ambrogio Maria

    2015-04-01

    The use of GPS/GNSS instruments is a common practice in the world at both a commercial and academic research level. Since last ten years, Continuous Operating Reference Stations (CORSs) networks were born in order to achieve the possibility to extend a precise positioning more than 15 km far from the master station. In this context, the Geomatics Research Group of DIATI at the Politecnico di Torino has carried out several experiments in order to evaluate the achievable precision obtainable with different GNSS receivers (geodetic and mass-market) and antennas if a CORSs network is considered. This work starts from the research above described, in particular focusing the attention on the usefulness of single frequency permanent stations in order to thicken the existing CORSs, especially for monitoring purposes. Two different types of CORSs network are available today in Italy: the first one is the so called "regional network" and the second one is the "national network", where the mean inter-station distances are about 25/30 and 50/70 km respectively. These distances are useful for many applications (e.g. mobile mapping) if geodetic instruments are considered but become less useful if mass-market instruments are used or if the inter-station distance between master and rover increases. In this context, some innovative GNSS networks were developed and tested, analyzing the performance of rover's positioning in terms of quality, accuracy and reliability both in real-time and post-processing approach. The use of single frequency GNSS receivers leads to have some limits, especially due to a limited baseline length, the possibility to obtain a correct fixing of the phase ambiguity for the network and to fix the phase ambiguity correctly also for the rover. These factors play a crucial role in order to reach a positioning with a good level of accuracy (as centimetric o better) in a short time and with an high reliability. The goal of this work is to investigate about the

  19. Coordinated single-phase control scheme for voltage unbalance reduction in low voltage network.

    Science.gov (United States)

    Pullaguram, Deepak; Mishra, Sukumar; Senroy, Nilanjan

    2017-08-13

    Low voltage (LV) distribution systems are typically unbalanced in nature due to unbalanced loading and unsymmetrical line configuration. This situation is further aggravated by single-phase power injections. A coordinated control scheme is proposed for single-phase sources, to reduce voltage unbalance. A consensus-based coordination is achieved using a multi-agent system, where each agent estimates the averaged global voltage and current magnitudes of individual phases in the LV network. These estimated values are used to modify the reference power of individual single-phase sources, to ensure system-wide balanced voltages and proper power sharing among sources connected to the same phase. Further, the high X / R ratio of the filter, used in the inverter of the single-phase source, enables control of reactive power, to minimize voltage unbalance locally. The proposed scheme is validated by simulating a LV distribution network with multiple single-phase sources subjected to various perturbations.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

  20. Neural-network-based single-sided non-enwrapping power loss tester

    CERN Document Server

    Passadis, K; Beckley, P

    2003-01-01

    It is preferable to be able to assess the power loss of electrical steels during production. When a single-sided tester is used, flux sensing is undertaken from one side only and hence some leakage flux above the strip may not captured by the sensing coils. Therefore, the disadvantage of a single-sided non-enwrapping tester lies in the measurement of the flux density in the material. A neural network was successfully used to 'predict' the correct level of flux density for accurate assessment of power loss.

  1. The network structure of adaptive governance - A single case study of a fish management area

    Directory of Open Access Journals (Sweden)

    Annica Charlotte Sandström

    2009-09-01

    Full Text Available The challenge of establishing adaptive management systems is a widely discussed topic in the literature on natural resource management. Adaptive management essentially focuses on achieving a governance process that is both sensitive to and has the capacity to continuously react to changes within the ecosystem being managed. The adoption of a network approach that perceives governance structures as social networks, searching for the kind of network features promoting this important feature, has been requested by researchers in the field. In particular, the possibilities associated with the application of a formal network approach, using the tools and concepts of social network analysis (SNA, have been identified as having significant potential for advancing this branch of research. This paper aims to address the relation between network structure and adaptability using an empirical approach. With the point of departure in a previously generated theoretical framework as well as related hypotheses, this paper presents a case study of a governance process within a fish management area in Sweden. The hypotheses state that, although higher levels of network density and centralisation promote the rule-forming process, the level of network heterogeneity is important for the existence and spread of ecological knowledge among the actors involved. According to the empirical results, restricted by the single-case study design, this assumption is still a well-working hypothesis. However, in order to advance our knowledge concerning these issues and test the validity of the hypotheses, more empirical work using a similar approach in multiple case study designs is needed.

  2. Pulling back error to the hidden-node parameter technology: Single-hidden-layer feedforward network without output weight

    OpenAIRE

    Yang, Yimin; Wu, Q. M. Jonathan; Huang, Guangbin; Wang, Yaonan

    2014-01-01

    According to conventional neural network theories, the feature of single-hidden-layer feedforward neural networks(SLFNs) resorts to parameters of the weighted connections and hidden nodes. SLFNs are universal approximators when at least the parameters of the networks including hidden-node parameter and output weight are exist. Unlike above neural network theories, this paper indicates that in order to let SLFNs work as universal approximators, one may simply calculate the hidden node paramete...

  3. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    Science.gov (United States)

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

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

    OpenAIRE

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

    2016-01-01

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

  5. Detecting Earthquakes over a Seismic Network using Single-Station Similarity Measures

    Science.gov (United States)

    Bergen, Karianne J.; Beroza, Gregory C.

    2018-03-01

    New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected move-out. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to two weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalog (including 95% of the catalog events), and less than 1% of these candidate events are false detections.

  6. Optical access network using centralized light source, single-mode fiber + broad wavelength window multimode fiber

    Science.gov (United States)

    Yam, Scott S.-H.; Kim, Jaedon; Gutierrez, David; Achten, Frank

    2006-08-01

    Access networks based on a single-mode fiber (SMF) using a centralized light source (CLS) have attracted much attention recently due to their wavelength management flexibility and potential for cost reduction at customers' premises. Future networks, in addition, are likely to contain segments of multimode fiber (MMF), whose core dimension is relatively large in comparison with its single-mode counterpart, substantially reducing fiber alignment constraints and the subsequent network construction and installation cost. In this study, a CLS-based passive optical network (PON) is proposed, which will use a new generation of high-performance MMF optimized for a broad wavelength transmission window spanning from 1300to1550 nm, with a bandwidth distance product (BDP) of 40 Gbit/s-km. The proposed architecture is implemented in a test bed, and its performance is verified by bit error ratio (BER) measurement. Results show that we can implement high-performance CLS-based PONs containing both an SMF and an MMF infrastructure, simultaneously.

  7. Factors affecting growth in infants with single ventricle physiology: a report from the Pediatric Heart Network Infant Single Ventricle Trial.

    Science.gov (United States)

    Williams, Richard V; Zak, Victor; Ravishankar, Chitra; Altmann, Karen; Anderson, Jeffrey; Atz, Andrew M; Dunbar-Masterson, Carolyn; Ghanayem, Nancy; Lambert, Linda; Lurito, Karen; Medoff-Cooper, Barbara; Margossian, Renee; Pemberton, Victoria L; Russell, Jennifer; Stylianou, Mario; Hsu, Daphne

    2011-12-01

    To describe growth patterns in infants with single ventricle physiology and determine factors influencing growth. Data from 230 subjects enrolled in the Pediatric Heart Network Infant Single Ventricle Enalapril Trial were used to assess factors influencing change in weight-for-age z-score (z) from study enrollment (0.7 ± 0.4 months) to pre-superior cavopulmonary connection (SCPC; 5.1 ± 1.8 months, period 1) and pre-SCPC to final study visit (14.1 ± 0.9 months, period 2). Predictor variables included patient characteristics, feeding regimen, clinical center, and medical factors during neonatal (period 1) and SCPC hospitalizations (period 2). Univariate regression analysis was performed, followed by backward stepwise regression and bootstrapping reliability to inform a final multivariable model. Weights were available for 197 of 230 subjects for period 1 and 173 of 197 subjects for period 2. For period 1, greater gestational age, younger age at study enrollment, tube feeding at neonatal hospitalization discharge, and clinical center were associated with a greater negative z (poorer growth) in multivariable modeling (adjusted R(2) = 0.39, P SCPC and greater daily caloric intake were associated with greater positive z (better growth; R(2) = 0.10, P = .002). Aggressive nutritional support and earlier SCPC are modifiable factors associated with a favorable change in weight-for-age z-score. Copyright © 2011 Mosby, Inc. All rights reserved.

  8. Factors Impacting Growth in Infants with Single Ventricle Physiology: A Report from Pediatric Heart Network Infant Single Ventricle Trial

    Science.gov (United States)

    Williams, Richard V.; Zak, Victor; Ravishankar, Chitra; Altmann, Karen; Anderson, Jeffrey; Atz, Andrew M.; Dunbar-Masterson, Carolyn; Ghanayem, Nancy; Lambert, Linda; Lurito, Karen; Medoff-Cooper, Barbara; Margossian, Renee; Pemberton, Victoria L.; Russell, Jennifer; Stylianou, Mario; Hsu, Daphne

    2011-01-01

    Objectives To describe growth patterns in infants with single ventricle physiology and determine factors influencing growth. Study design Data from 230 subjects enrolled in the Pediatric Heart Network Infant Single Ventricle Enalapril Trial were used to assess factors influencing change in weight-for-age z-score (Δz) from study enrollment (0.7 ± 0.4 months) to pre-superior cavopulmonary connection (SCPC) (5.1 ± 1.8 months, period 1), and pre-SCPC to final study visit (14.1 ± 0.9 months, period 2). Predictor variables included patient characteristics, feeding regimen, clinical center, and medical factors during neonatal (period 1) and SCPC hospitalizations (period 2). Univariate regression analysis was performed, followed by backward stepwise regression and bootstrapping reliability to inform a final multivariable model. Results Weights were available for 197/230 subjects for period 1 and 173/197 for period 2. For period 1, greater gestational age, younger age at study enrollment, tube feeding at neonatal discharge, and clinical center were associated with a greater negative Δz (poorer growth) in multivariable modeling (adjusted R2 = 0.39, p SCPC and greater daily caloric intake were associated with greater positive Δz (better growth) (R2 = 0.10, p = 0.002). Conclusions Aggressive nutritional support and earlier SCPC are modifiable factors associated with a favorable change in weight-for-age z-score. PMID:21784436

  9. Sexual Networking and Partner Characteristics Among Single, African, Caribbean, and Black Youth in Windsor, Ontario.

    Science.gov (United States)

    Kerr, Jelani; Maticka-Tyndale, Eleanor; Bynum, Shalanda; Mihan, Robert

    2017-10-01

    The disproportionate HIV burden shared by African, Caribbean, and Black (ACB) populations in Canada has not been explained by unique sexual behaviors in this population. This study investigates partner selection and sexual networking as potential contributors to HIV vulnerability. The study examines variations in the characteristics of sexual partners and sexual networking across groups based on differences in ethno-religious identity, gender, and length of Canadian residency among single, 16- to 27-year old, heterosexual-identified, ACB individuals living in Windsor, Ontario, Canada. Respondent-driven sampling maximized the representativeness of the sample of 250 (45 % male; 55 % female) youth with penile-vaginal intercourse experience who completed surveys. Logistic regression and analysis of variance compared groups with respect to number of lifetime partners, concurrency of sexual relationships, non-relational and age disparate partnering, and intra-ethnic sexual networking. For vulnerability associated with number of partners, concurrency and non-relational sex, women, newcomers to Canada, and African-Muslim participants were at lower vulnerability for HIV infection than their comparator groups. For vulnerability associated with sexual networking within a group with higher HIV prevalence, women and newcomers to Canada were at higher vulnerability to HIV infection than their comparator groups. There were insufficient data on age disparate partnering to support analysis. These results point to the importance of considering characteristics of partners and sexual networking both in further research and in developing policies and programs to curtail the spread of HIV and other sexually transmitted infections.

  10. Clearing the Skies: A deep network architecture for single-image rain streaks removal.

    Science.gov (United States)

    Fu, Xueyang; Huang, Jiabin; Ding, Xinghao; Liao, Yinghao; Paisley, John

    2017-04-06

    We introduce a deep network architecture called DerainNet for removing rain streaks from an image. Based on the deep convolutional neural network (CNN), we directly learn the mapping relationship between rainy and clean image detail layers from data. Because we do not possess the ground truth corresponding to real-world rainy images, we synthesize images with rain for training. In contrast to other common strategies that increase depth or breadth of the network, we use image processing domain knowledge to modify the objective function and improve deraining with a modestly-sized CNN. Specifically, we train our DerainNet on the detail (high-pass) layer rather than in the image domain. Though DerainNet is trained on synthetic data, we find that the learned network translates very effectively to real-world images for testing. Moreover, we augment the CNN framework with image enhancement to improve the visual results. Compared with state-of-the-art single image deraining methods, our method has improved rain removal and much faster computation time after network training.

  11. SINCERITIES: Inferring gene regulatory networks from time-stamped single cell transcriptional expression profiles.

    Science.gov (United States)

    Papili Gao, Nan; Ud-Dean, S M Minhaz; Gandrillon, Olivier; Gunawan, Rudiyanto

    2017-09-14

    Single cell transcriptional profiling opens up a new avenue in studying the functional role of cell-to-cell variability in physiological processes. The analysis of single cell expression profiles creates new challenges due to the distributive nature of the data and the stochastic dynamics of gene transcription process. The reconstruction of gene regulatory networks (GRNs) using single cell transcriptional profiles is particularly challenging, especially when directed gene-gene relationships are desired. We developed SINCERITIES (SINgle CEll Regularized Inference using TIme-stamped Expression profileS) for the inference of GRNs from single cell transcriptional profiles. We focused on time-stamped cross-sectional expression data, commonly generated from transcriptional profiling of single cells collected at multiple time points after cell stimulation. SINCERITIES recovers directed regulatory relationships among genes by employing regularized linear regression (ridge regression), using temporal changes in the distributions of gene expressions. Meanwhile, the modes of the gene regulations (activation and repression) come from partial correlation analyses between pairs of genes. We demonstrated the efficacy of SINCERITIES in inferring GRNs using in silico time-stamped single cell expression data and single cell transcriptional profiles of THP-1 monocytic human leukemia cells. The case studies showed that SINCERITIES could provide accurate GRN predictions, significantly better than other GRN inference algorithms such as TSNI, GENIE3 and JUMP3. Moreover, SINCERITIES has a low computational complexity and is amenable to problems of extremely large dimensionality. Finally, an application of SINCERITIES to single cell expression data of T2EC chicken erythrocytes pointed to BATF as a candidate novel regulator of erythroid development. The MATLAB and R version of SINCERITIES is freely available from the following websites: http://www.cabsel.ethz.ch/tools/sincerities.html and

  12. Abnormal Ventral and Dorsal Attention Network Activity During Single and Dual Target Detection in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Amy M. Jimenez

    2016-03-01

    Full Text Available Early visual perception and attention are impaired in schizophrenia, and these deficits can be observed on target detection tasks. These tasks activate distinct ventral and dorsal brain networks which support stimulus-driven and goal-directed attention, respectively. We used single and dual target rapid serial visual presentation (RSVP tasks during fMRI with an ROI approach to examine regions within these networks associated with target detection and the attentional blink (AB in 21 schizophrenia outpatients and 25 healthy controls. In both tasks, letters were targets and numbers were distractors. For the dual target task, the second target (T2 was presented at 3 different lags after the first target (T1 (lag1=100ms, lag3=300ms, lag7=700ms. For both single and dual target tasks, patients identified fewer targets than controls. For the dual target task, both groups showed the expected AB effect with poorer performance at lag 3 than at lags 1 or 7, and there was no group by lag interaction. During the single target task, patients showed abnormally increased deactivation of the temporo-parietal junction (TPJ, a key region of the ventral network. When attention demands were increased during the dual target task, patients showed overactivation of the posterior intraparietal cortex, a key dorsal network region, along with failure to deactivate TPJ. Results suggest inefficient and faulty suppression of salience-oriented processing regions, resulting in increased sensitivity to stimuli in general, and difficulty distinguishing targets from non-targets.

  13. Evaluation of deep neural networks for single image super-resolution in a maritime context

    Science.gov (United States)

    Nieuwenhuizen, Robert P. J.; Kruithof, Maarten; Schutte, Klamer

    2017-10-01

    High resolution imagery is of crucial importance for the performance on visual recognition tasks. Super-resolution (SR) reconstruction algorithms aim to enhance the image resolution beyond the capability of the image sensor being used. Traditional SR algorithms approach this inverse problem using physical models for the image formation combined with a regularization function to prevent instabilities in the solution. Recently deep neural networks have been put forward as an alternative approach to the SR reconstruction problem. They learn a mapping from low resolution images to their high resolution counterparts from pairs of training images, which allows them to capture more specific information about the space of possible solutions than traditional regularization functions. These networks have achieved state-of-the-art performance on single image SR for sets of generic test images. Here we investigate whether the same performance can be realized when these neural networks for single image SR are applied specifically in the maritime domain. In particular we investigate their ability to reconstruct undersampled images of ships at sea, and demonstrate that the performance is similar to what is achieved on generic test images. In addition we quantify the gain in performance that is achieved when the networks are trained specifically on images of ships, which allows the networks to capture more prior knowledge about the space of possible solutions. Finally we show that the performance deteriorates when the resolution of test images is limited by image blur, for example due to diffraction, rather than undersampling. This highlights the importance of using representative training data that account for the part of the image formation process that limits the resolution in the sensor data.

  14. Broadcast Secrecy via Key-Chain-Based Encryption in Single-Hop Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ostry Diethelm

    2011-01-01

    Full Text Available Broadcast is used in wireless sensor networks for operations such as software updates, network queries, and command dissemination. Applications such as battlefield control and natural resource management require not only authentication of broadcast messages, but also secrecy against eavesdroppers. In this paper we design, implement, and evaluate a novel scheme that meets the requirements of secrecy, authenticity, integrity, and freshness of broadcast messages in the context of a single-hop wireless sensor network. Our contributions are three-fold: first, we propose the use of time-varying keys (based on a key-chain for broadcast encryption, emphasising advantages such as non-forgeability, protection against old-key compromise, and allowance for dynamic data. Second, we extend the basic key-chain mechanism to incorporate limited protection against key loss, allowing legitimate receivers to recover even if they have lost a small number of keys. Third, we prototype our scheme by incorporating it into Deluge, the network programming protocol distributed with TinyOS, and quantify its cost in terms of time, space, and power consumption on a TelosB mote platform. Our scheme represents a practical, efficient and scalable means of delivering broadcast data secretly to a large number of low-power sensor nodes.

  15. Using single-index ODEs to study dynamic gene regulatory network

    Science.gov (United States)

    Zhang, Qi; Yu, Yao; Zhang, Jun

    2018-01-01

    With the development of biotechnology, high-throughput studies on protein-protein, protein-gene, and gene-gene interactions become possible and attract remarkable attention. To explore the interactions in dynamic gene regulatory networks, we propose a single-index ordinary differential equation (ODE) model and develop a variable selection procedure. We employ the smoothly clipped absolute deviation penalty (SCAD) penalized function for variable selection. We analyze a yeast cell cycle gene expression data set to illustrate the usefulness of the single-index ODE model. In real data analysis, we group genes into functional modules using the smoothing spline clustering approach. We estimate state functions and their first derivatives for functional modules using penalized spline-based nonparametric mixed-effects models and the spline method. We substitute the estimates into the single-index ODE models, and then use the penalized profile least-squares procedure to identify network structures among the models. The results indicate that our model fits the data better than linear ODE models and our variable selection procedure identifies the interactions that may be missed by linear ODE models but confirmed in biological studies. In addition, Monte Carlo simulation studies are used to evaluate and compare the methods. PMID:29474376

  16. Electrical contacts to nanorod networks at different length scales: From macroscale ensembles to single nanorod chains

    KAUST Repository

    Lavieville, Romain

    2013-11-01

    The nature of metal-semiconductor interfaces at the nanoscale is an important issue in micro- and nanoelectronic engineering. The study of charge transport through chains of CdSe semiconductor nanorods linked by Au particles represents an ideal model system for this matter, because the metal semiconductor interface is an intrinsic feature of the nanosystem. Here we show the controlled fabrication of all-inorganic hybrid metal-semiconductor networks with different size, in which the semiconductor nanorods are linked by Au domains at their tips. We demonstrate different approaches to selectively contact the networks and single nanorod chains with planar electrodes, and we investigate their charge transport at room temperature. © 2013 Elsevier B.V. All rights reserved.

  17. Gas sensors based on deposited single-walled carbon nanotube networks for DMMP detection

    International Nuclear Information System (INIS)

    Wang Yanyan; Zhou Zhihua; Yang Zhi; Chen Xiaohang; Xu Dong; Zhang Yafei

    2009-01-01

    Sensors based on single-walled carbon nanotube (SWNT) networks were fabricated and their sensitive properties for the nerve agent stimulant dimethyl methylphosphonate (DMMP) vapor were investigated at room temperature. The SWNT networks were deposited on oxidized silicon surface functionalized with 3-aminopropyltrimethysilane (APS). Combining with a traditional silicon process, SWNT-based gas sensors were made at a wafer scale. The effects of the density of deposited SWNTs on the sensor response were studied. The excellent response is obtained under a density of 30-40 tubes μm -2 . The sensors exhibit high resistance response, fast response time, rapid recovery and good reproducibility for DMMP vapor. The deposited SWNT sensors will be potentially extended to large-scale fabrication.

  18. Network single-walled carbon nanotube biosensors for fast and highly sensitive detection of proteins.

    Science.gov (United States)

    Hu, Pingán; Zhang, Jia; Wen, Zhenzhong; Zhang, Can

    2011-08-19

    Detection of proteins is powerfully assayed in the diagnosis of diseases. A strategy for the development of an ultrahigh sensitivity biosensor based on a network single-walled carbon nanotube (SWNT) field-effect transistor (FET) has been demonstrated. Metallic SWNTs (m-SWNTs) in the network nanotube FET were selectively removed or cut via a carefully controlled procedure of electrical break-down (BD), and left non-conducting m-SWNTs which magnified the Schottky barrier (SB) area. This nanotube FET exhibited ultrahigh sensitivity and fast response to biomolecules. The lowest detection limit of 0.5 pM was achieved by exploiting streptavidin (SA) or a biotin/SA pair as the research model, and BD-treated nanotube biosensors had a 2 × 10(4)-fold lower minimum detectable concentration than the device without BD treatment. The response time is in the range of 0.3-3 min.

  19. A single hidden layer feedforward network with only one neuron in the hidden layer can approximate any univariate function

    OpenAIRE

    Guliyev, Namig; Ismailov, Vugar

    2016-01-01

    The possibility of approximating a continuous function on a compact subset of the real line by a feedforward single hidden layer neural network with a sigmoidal activation function has been studied in many papers. Such networks can approximate an arbitrary continuous function provided that an unlimited number of neurons in a hidden layer is permitted. In this paper, we consider constructive approximation on any finite interval of $\\mathbb{R}$ by neural networks with only one neuron in the hid...

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

    Science.gov (United States)

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

    2016-01-01

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

  1. Binary Factorization in Hopfield-Like Neural Networks: Single-Step Approximation and Computer Simulations

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Sirota, A.M.; Húsek, Dušan; Muraviev, I. P.

    2004-01-01

    Roč. 14, č. 2 (2004), s. 139-152 ISSN 1210-0552 R&D Projects: GA ČR GA201/01/1192 Grant - others:BARRANDE(EU) 99010-2/99053; Intellectual computer Systems(EU) Grant 2.45 Institutional research plan: CEZ:AV0Z1030915 Keywords : nonlinear binary factor analysis * feature extraction * recurrent neural network * Single-Step approximation * neurodynamics simulation * attraction basins * Hebbian learning * unsupervised learning * neuroscience * brain function modeling Subject RIV: BA - General Mathematics

  2. Single Allocation Hub-and-spoke Networks Design Based on Ant Colony Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Pingle

    2014-10-01

    Full Text Available Capacitated single allocation hub-and-spoke networks can be abstracted as a mixed integer linear programming model equation with three variables. Introducing an improved ant colony algorithm, which has six local search operators. Meanwhile, introducing the "Solution Pair" concept to decompose and optimize the composition of the problem, the problem can become more specific and effectively meet the premise and advantages of using ant colony algorithm. Finally, location simulation experiment is made according to Australia Post data to demonstrate this algorithm has good efficiency and stability for solving this problem.

  3. Accurate analytic solution of chemical master equations for gene regulation networks in a single cell

    Science.gov (United States)

    Huang, Guan-Rong; Saakian, David B.; Hu, Chin-Kun

    2018-01-01

    Studying gene regulation networks in a single cell is an important, interesting, and hot research topic of molecular biology. Such process can be described by chemical master equations (CMEs). We propose a Hamilton-Jacobi equation method with finite-size corrections to solve such CMEs accurately at the intermediate region of switching, where switching rate is comparable to fast protein production rate. We applied this approach to a model of self-regulating proteins [H. Ge et al., Phys. Rev. Lett. 114, 078101 (2015), 10.1103/PhysRevLett.114.078101] and found that as a parameter related to inducer concentration increases the probability of protein production changes from unimodal to bimodal, then to unimodal, consistent with phenotype switching observed in a single cell.

  4. In vivo flow mapping in complex vessel networks by single image correlation.

    Science.gov (United States)

    Sironi, Laura; Bouzin, Margaux; Inverso, Donato; D'Alfonso, Laura; Pozzi, Paolo; Cotelli, Franco; Guidotti, Luca G; Iannacone, Matteo; Collini, Maddalena; Chirico, Giuseppe

    2014-12-05

    We describe a novel method (FLICS, FLow Image Correlation Spectroscopy) to extract flow speeds in complex vessel networks from a single raster-scanned optical xy-image, acquired in vivo by confocal or two-photon excitation microscopy. Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details. The flow velocity is obtained by computing the Cross Correlation Function (CCF) of the intensity fluctuations detected in pairs of columns of the image. The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity. The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution.

  5. Three-Level Z-Source Inverters Using a Single LC Impedance Network

    DEFF Research Database (Denmark)

    Loh, Poh Chiang; Lim, Sok Wei; Gao, Feng

    2007-01-01

    Three-level Z-source inverters are recent single-stage topological solutions proposed for buck-boost energy conversion with all favorable advantages of three-level switching retained. Despite their effectiveness in achieving voltage buck-boost conversion, existing three-level Z-source inverters use...... three-level Z-source inverters, whose output voltage can be stepped down or up using only a single LC impedance network connected between the dc input source and either a neutral-point-clamped (NPC) or dc-link cascaded inverter circuitry. Through careful design of their modulation scheme, both inverters...... can conveniently be implemented using a generic "alternative phase opposition disposition" carrier-based modulator with the appropriate triplen offset and time advance/delay added. The designed inverters, having a reduced passive component count, are lastly tested in simulation and experimentally...

  6. Three-Level Z-Source Inverters Using a Single LC Impedance Network

    DEFF Research Database (Denmark)

    Loh, Poh Chiang; Lim, Sok Wei; Gao, Feng

    2007-01-01

    Three-level Z-source inverters are recent single-stage topological solutions proposed for buck-boost energy conversion with all favorable advantages of three-level switching retained. Despite their effectiveness in achieving voltage buck-boost conversion, existing three-level Z-source inverters use...... three-level Z-source inverters, whose output voltage can be stepped down or up using only a single LC impedance network connected between the dc input source and either a neutral-point-clamped (NPC) or dc-link cascaded inverter circuitry. Through careful design of their modulation scheme, both inverters...... can function with the minimum of six device commutations per half carrier cycle (similar to that needed by a traditional buck three-level NPC inverter), while producing the correct volt-sec average and inductive voltage boosting at their ac output terminals. Physically, the designed modulation scheme...

  7. Ionospheric modifications detected by a dense network of single frequency GNSS receivers

    Science.gov (United States)

    Mrak, S.; Semeter, J. L.

    2017-12-01

    It has been predicted that the region of totality during a total solar eclipse can launch atmospheric gravity waves with large enough amplitude to cause traveling ionospheric disturbances (TIDs). We report initial results from a remote sensing campaign involving a dense hybrid network of single- and dual-frequency GNSS receivers deployed underneath the 21 August 2017 solar eclipse. The campaign took place in central Missouri, involving 84 Trimble dual-frequency receivers, complemented by 2 additional 50 Hz dual-frequency receivers and 15 single-frequency receivers, together constructing 100 receivers with average mutual separation of less than 25 km and with a time resolution of 1 second or better. The initial results show a crescent shaped enhancement bulge in front of region of totality, extending all the way from Canada to Gulf of Mexico. In addition, in the path of totality is noticed a great depletion region, followed by a pair of transverse waves propagating in west-east direction. In the following months, we will explore the transition region carried by the totality by a virtue of hyper dense network of GNSS receivers with 1 second resolution. In addition to TEC data decomposition we will explore effects of the totality on the raw measurements (phase, code and signal intensity), and to the navigation solution which is likely to be effected by a different propagation conditions with respect to other days.

  8. Robust Single Image Super-Resolution via Deep Networks with Sparse Prior.

    Science.gov (United States)

    Liu, Ding; Wang, Zhaowen; Wen, Bihan; Yang, Jianchao; Han, Wei; Huang, Thomas

    2016-05-06

    Single image super-resolution is an ill-posed problem which tries to recover a high-resolution image from its lowresolution observation. To regularize the solution of the problem, previous methods have focused on designing good priors for natural images such as sparse representation, or directly learning the priors from a large data set with models such as deep neural networks. In this paper, we argue that domain expertise from the conventional sparse coding model can be combined with the key ingredients of deep learning to achieve further improved results. We demonstrate that a sparse coding model particularly designed for super-resolution can be incarnated as a neural network with the merit of end-to-end optimization over training data. The network has a cascaded structure which boosts the SR performance for both fixed and incremental scaling factors. The proposed training and testing schemes can be extended for robust handling of images with additional degradation such as noise and blurring. A subjective assessment is conducted and analyzed in order to thoroughly evaluate various SR techniques. Our proposed model is tested on a wide range of images, and it significantly outperforms existing state-of-the-art methods for various scaling factors both quantitatively and perceptually.

  9. Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

    Science.gov (United States)

    Rodríguez, Ana R.; O'Neill, Kate M.; Swiatkowski, Przemyslaw; Patel, Mihir V.; Firestein, Bonnie L.

    2018-02-01

    Objective. This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks. Approach. We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ PSD-95 non-binding) expression cellularly and network-wide, respectively. Main results. Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity. Significance. Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

  10. Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock.

    Science.gov (United States)

    Park, James; Zhu, Haisun; O'Sullivan, Sean; Ogunnaike, Babatunde A; Weaver, David R; Schwaber, James S; Vadigepalli, Rajanikanth

    2016-01-01

    Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN). Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies toward understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

  11. Single-cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks involved In the Central Circadian Clock

    Directory of Open Access Journals (Sweden)

    James Park

    2016-10-01

    Full Text Available Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN. Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies towards understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

  12. A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

    Science.gov (United States)

    Zhu, Yanan; Ouyang, Qi; Mao, Youdong

    2017-07-21

    Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecular complexes. However, high-resolution cryo-EM reconstruction often requires hundreds of thousands of single-particle images. Particle extraction from experimental micrographs thus can be laborious and presents a major practical bottleneck in cryo-EM structural determination. Existing computational methods for particle picking often use low-resolution templates for particle matching, making them susceptible to reference-dependent bias. It is critical to develop a highly efficient template-free method for the automatic recognition of particle images from cryo-EM micrographs. We developed a deep learning-based algorithmic framework, DeepEM, for single-particle recognition from noisy cryo-EM micrographs, enabling automated particle picking, selection and verification in an integrated fashion. The kernel of DeepEM is built upon a convolutional neural network (CNN) composed of eight layers, which can be recursively trained to be highly "knowledgeable". Our approach exhibits an improved performance and accuracy when tested on the standard KLH dataset. Application of DeepEM to several challenging experimental cryo-EM datasets demonstrated its ability to avoid the selection of un-wanted particles and non-particles even when true particles contain fewer features. The DeepEM methodology, derived from a deep CNN, allows automated particle extraction from raw cryo-EM micrographs in the absence of a template. It demonstrates an improved performance, objectivity and accuracy. Application of this novel method is expected to free the labor involved in single-particle verification, significantly improving the efficiency of cryo-EM data processing.

  13. Accuracy improvement of optical vector network analyzer based on single-sideband modulation.

    Science.gov (United States)

    Xue, Min; Pan, Shilong; Zhao, Yongjiu

    2014-06-15

    An approach to suppress the measurement errors induced by the high-order sidebands of the optical single-sideband (OSSB) signal in the OSSB-based optical vector network analyzer (OVNA) is proposed and experimentally demonstrated. An analytical model for studying the measurement errors of the OSSB-based OVNA is established. Results show that the measurement errors introduced by the high-order sidebands can be obtained by suppressing the optical carrier in the OSSB signal. By subtracting these errors from the ordinary frequency responses measured by the OVNA, accurate frequency responses can be achieved. A proof-of-concept experiment is performed. The magnitude and phase responses of a fiber Bragg grating are measured with good coincidence by the OSSB signals with different modulation indices.

  14. Pore morphologies of root induced biopores from single pore to network scale investigated by XRCT

    Science.gov (United States)

    Peth, Stephan; Wittig, Marlen C.; Uteau Puschmann, Daniel; Pagenkemper, Sebastian; Haas, Christoph; Holthusen, Dörthe; Horn, Rainer

    2015-04-01

    Biopores are assumed to be an important factor for nutrient acquisition by providing biologically highly active soil-root interfaces to re-colonizing roots and controlling oxygen and water flows at the pedon scale and within the rhizosphere through the formation of branching channel networks which potentially enhance microbial turnover processes. Characteristic differences in pore morphologies are to be expected depending on the genesis of biopores which, for example, can be earthworm-induced or root-induced or subsequently modified by one of the two. Our understanding of biophysical interactions between plants and soil can be significantly improved by quantifying 3D biopore architectures across scales ranging from single biopores to pedon scale pore networks and linking pore morphologies to microscale measurements of transport processes (e.g. oxygen diffusion). While a few studies in the past have investigated biopore networks on a larger scale yet little is known on the micro-morphology of root-induces biopores and their associated rhizosphere. Also little data is available on lateral transport of oxygen through the rhizosphere which will strongly influence microbial turnover processes and consequently control the release and uptake of nutrients. This paper highlights results gathered within a research unit on nutrient acquisition from the subsoil. Here we focus on X-ray microtomography (XRCT) studies ranging from large soil columns (70 cm length and 20 cm diameter) to individual biopores and its surrounding rhizosphere. Samples were collected from sites with different preceding crops (fescue, chicory, alfalfa) and various cropping durations (1-3 years). We will present an approach for quantitative image analysis combined with micro-sensor measurements of oxygen diffusion and spatial gradients of O2 partial pressures to relate pore structure with transport functions. Implications of various biopore architectures for the accessibility of nutrient resources in

  15. A Terrestrial Microbial Fuel Cell for Powering a Single-Hop Wireless Sensor Network.

    Science.gov (United States)

    Zhang, Daxing; Zhu, Yingmin; Pedrycz, Witold; Guo, Yongxian

    2016-05-18

    Microbial fuel cells (MFCs) are envisioned as one of the most promising alternative renewable energy sources because they can generate electric current continuously while treating waste. Terrestrial Microbial Fuel Cells (TMFCs) can be inoculated and work on the use of soil, which further extends the application areas of MFCs. Energy supply, as a primary influential factor determining the lifetime of Wireless Sensor Network (WSN) nodes, remains an open challenge in sensor networks. In theory, sensor nodes powered by MFCs have an eternal life. However, low power density and high internal resistance of MFCs are two pronounced problems in their operation. A single-hop WSN powered by a TMFC experimental setup was designed and experimented with. Power generation performance of the proposed TMFC, the relationships between the performance of the power generation and the environment temperature, the water content of the soil by weight were measured by experiments. Results show that the TMFC can achieve good power generation performance under special environmental conditions. Furthermore, the experiments with sensor data acquisition and wireless transmission of the TMFC powering WSN were carried out. We demonstrate that the obtained experimental results validate the feasibility of TMFCs powering WSNs.

  16. A Terrestrial Microbial Fuel Cell for Powering a Single-Hop Wireless Sensor Network

    Science.gov (United States)

    Zhang, Daxing; Zhu, Yingmin; Pedrycz, Witold; Guo, Yongxian

    2016-01-01

    Microbial fuel cells (MFCs) are envisioned as one of the most promising alternative renewable energy sources because they can generate electric current continuously while treating waste. Terrestrial Microbial Fuel Cells (TMFCs) can be inoculated and work on the use of soil, which further extends the application areas of MFCs. Energy supply, as a primary influential factor determining the lifetime of Wireless Sensor Network (WSN) nodes, remains an open challenge in sensor networks. In theory, sensor nodes powered by MFCs have an eternal life. However, low power density and high internal resistance of MFCs are two pronounced problems in their operation. A single-hop WSN powered by a TMFC experimental setup was designed and experimented with. Power generation performance of the proposed TMFC, the relationships between the performance of the power generation and the environment temperature, the water content of the soil by weight were measured by experiments. Results show that the TMFC can achieve good power generation performance under special environmental conditions. Furthermore, the experiments with sensor data acquisition and wireless transmission of the TMFC powering WSN were carried out. We demonstrate that the obtained experimental results validate the feasibility of TMFCs powering WSNs. PMID:27213346

  17. Topiramate modulates trigeminal pain processing in thalamo-cortical networks in humans after single dose administration.

    Science.gov (United States)

    Hebestreit, Julia M; May, Arne

    2017-01-01

    Migraine is the sixth most common cause of disability in the world. Preventive migraine treatment is used to reduce frequency, severity and duration of attacks and therefore lightens the burden on the patients' quality of life and reduces disability. Topiramate is one of the preventive migraine treatments of proven efficacy. The mechanism of action underlying the preventive effect of topiramate in migraine remains largely unknown. Using functional magnetic resonance imaging (fMRI) we examined the central effects of a single dose of topiramate (100mg) on trigeminal pain in humans, compared to placebo (mannitol). In this prospective, within subject, randomized, placebo-controlled and double-blind study, 23 healthy participants received a standardized nociceptive trigeminal stimulation and control stimuli whilst being in the scanner. No differences in the subjective intensity ratings of the painful stimuli were observed between topiramate and placebo sessions. In contrast, topiramate significantly decreased the activity in the thalamus and other pain processing areas. Additionally, topiramate increased functional coupling between the thalamus and several brain regions such as the bilateral precuneus, posterior cingulate cortex and secondary somatosensory cortex. These data suggest that topiramate exhibits modulating effects on nociceptive processing in thalamo-cortical networks during trigeminal pain and that the preventive effect of topiramate on frequent migraine is probably mediated by an effect on thalamo-cortical networks.

  18. Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

    Science.gov (United States)

    Liebel, L.; Körner, M.

    2016-06-01

    In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

  19. Artificial Formation and Tuning of Glycoprotein Networks on Live Cell Membranes: A Single-Molecule Tracking Study.

    Science.gov (United States)

    Möckl, Leonhard; Lindhorst, Thisbe K; Bräuchle, Christoph

    2016-03-16

    We present a method to artificially induce network formation of membrane glycoproteins and show the precise tuning of their interconnection on living cells. For this, membrane glycans are first metabolically labeled with azido sugars and then tagged with biotin by copper-free click chemistry. Finally, these biotin-tagged membrane proteins are interconnected with streptavidin (SA) to form an artificial protein network in analogy to a lectin-induced lattice. The degree of network formation can be controlled by the concentration of SA, its valency, and the concentration of biotin on membrane proteins. This was verified by investigation of the spatiotemporal dynamics of the SA-protein networks employing single-molecule tracking. It was also proven that this network formation strongly influences the biologically relevant process of endocytosis as it is known from natural lattices on the cell surface. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. A Novel Neural Network Vector Control for Single-Phase Grid-Connected Converters with L, LC and LCL Filters

    Directory of Open Access Journals (Sweden)

    Xingang Fu

    2016-04-01

    Full Text Available This paper investigates a novel recurrent neural network (NN-based vector control approach for single-phase grid-connected converters (GCCs with L (inductor, LC (inductor-capacitor and LCL (inductor-capacitor-inductor filters and provides their comparison study with the conventional standard vector control method. A single neural network controller replaces two current-loop PI controllers, and the NN training approximates the optimal control for the single-phase GCC system. The Levenberg–Marquardt (LM algorithm was used to train the NN controller based on the complete system equations without any decoupling policies. The proposed NN approach can solve the decoupling problem associated with the conventional vector control methods for L, LC and LCL-filter-based single-phase GCCs. Both simulation study and hardware experiments demonstrate that the neural network vector controller shows much more improved performance than that of conventional vector controllers, including faster response speed and lower overshoot. Especially, NN vector control could achieve very good performance using low switch frequency. More importantly, the neural network vector controller is a damping free controller, which is generally required by a conventional vector controller for an LCL-filter-based single-phase grid-connected converter and, therefore, can overcome the inefficiency problem caused by damping policies.

  1. Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

    Science.gov (United States)

    Rai, Man Mohan

    2006-01-01

    Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more

  2. Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

    Science.gov (United States)

    Sadeh, Sadra; Rotter, Stefan

    2015-01-01

    The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not

  3. Ring resonator-based single-chip 1x8 optical beam forming network in LPCVD waveguide technology

    NARCIS (Netherlands)

    Zhuang, L.; Roeloffzen, C.G.H.; Heideman, Rene; Borreman, A.; Meijerink, Arjan; van Etten, Wim; Koonen, A.M.J.; Leijtens, X.J.M.; van den Boom, H.P.A.; Verdurmen, E.J.M.; Molina Vázquez, J.

    2006-01-01

    Optical ring resonators (ORRs) are good candidates to provide continuously tunable delay in beam forming networks (BFNs) for phased array antenna systems. Delay and splitting/combining elements can be integrated on a single optical chip to form an OBFN. A state-of-the-art 1×8 OBFN chip has been

  4. Single-chip ring resonator-based 1 x 8 optical beam forming network in CMOS-compatible waveguide technology

    NARCIS (Netherlands)

    Zhuang, L.; Roeloffzen, C.G.H.; Heideman, Rene; Borreman, A.; Meijerink, Arjan; van Etten, Wim

    2007-01-01

    Optical ring resonators (ORRs) are good candidates to provide continuously tunable delay in optical beam forming networks (OBFNs) for phased array antenna systems. Delay and splitting/combining elements can be integrated on a single optical chip to form an OBFN. A state-of-the-art ring resonator-

  5. SINGLE-IMAGE SUPER RESOLUTION FOR MULTISPECTRAL REMOTE SENSING DATA USING CONVOLUTIONAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    L. Liebel

    2016-06-01

    Full Text Available In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN, can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

  6. Integrative Single-Cell Transcriptomics Reveals Molecular Networks Defining Neuronal Maturation During Postnatal Neurogenesis.

    Science.gov (United States)

    Gao, Yu; Wang, Feifei; Eisinger, Brian E; Kelnhofer, Laurel E; Jobe, Emily M; Zhao, Xinyu

    2017-03-01

    In mammalian hippocampus, new neurons are continuously produced from neural stem cells throughout life. This postnatal neurogenesis may contribute to information processing critical for cognition, adaptation, learning, and memory, and is implicated in numerous neurological disorders. During neurogenesis, the immature neuron stage defined by doublecortin (DCX) expression is the most sensitive to regulation by extrinsic factors. However, little is known about the dynamic biology within this critical interval that drives maturation and confers susceptibility to regulatory signals. This study aims to test the hypothesis that DCX-expressing immature neurons progress through developmental stages via activity of specific transcriptional networks. Using single-cell RNA-seq combined with a novel integrative bioinformatics approach, we discovered that individual immature neurons can be classified into distinct developmental subgroups based on characteristic gene expression profiles and subgroup-specific markers. Comparisons between immature and more mature subgroups revealed novel pathways involved in neuronal maturation. Genes enriched in less mature cells shared significant overlap with genes implicated in neurodegenerative diseases, while genes positively associated with neuronal maturation were enriched for autism-related gene sets. Our study thus discovers molecular signatures of individual immature neurons and unveils potential novel targets for therapeutic approaches to treat neurodevelopmental and neurological diseases. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  7. PERLUASAN JANGKAUAN SIARAN STASIUN PEMANCAR DIGITAL TVRI JAWA BARAT DENGAN SISTEM SINGLE FREQUENCY NETWORK (SFN

    Directory of Open Access Journals (Sweden)

    Trya Agung Pahlevi

    2017-02-01

    Full Text Available Implementasi penyiaran televisi digital dengan menggunakan media teresterial telah menjadi kenyataan di Indonesia. Sistem penyiaran televisi digital (Digital Video Broadcast over Terrestrial / DVB-T memungkinkan untuk penggunaan Single Frequency Network (SFN, sehingga dapat memperluas wilayah jangkauan siaran dengan menggunakan satu kanal frekuensi. Penelitian yang dilakukan adalah merencanakan koordinat dan parameter teknis sistem SFN DVB-T di wilayah TVRI Jawa Barat, berdasarkan rekomendasi dari akta-akta akhir International Telecommunication Union (ITU dalam Sidang Regional Radiocommunication Conference (RRC-06, untuk mendapatkan jangkauan wilayah yang paling maksimal dan efisien. Simulasi perancangan menggunakan  perangkat lunak "Mobile RF" dan "CHIRplus_BC"dalam menentukan koordinat pemancar, parameter daya dan tinggi pemancar, serta keekonomian perancangan. Hasil akhir dari penelitian adalah dengan sistem SFN dapat meningkatkan wilayah jangkauan siaran dari kondisi awal 11.609.819 orang (persentase coverage population 55,51%, menjadi 12.060.282 orang (persentase coverage population 57,66% sampai dengan 17.563.586 orang (persentase coverage population 83,98%, dengan total jumlah pemirsa adalah 20.914.885  orang.

  8. Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

    Science.gov (United States)

    Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

    2017-05-01

    Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

  9. Detection of single and multilayer clouds in an artificial neural network approach

    Science.gov (United States)

    Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Hong, Gang; Chen, Yan

    2017-10-01

    Determining whether a scene observed with a satellite imager is composed of a thin cirrus over a water cloud or thick cirrus contiguous with underlying layers of ice and water clouds is often difficult because of similarities in the observed radiance values. In this paper an artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels and the retrieved total cloud visible optical depth, is trained to detect multilayer ice-over-water cloud systems as identified by matched April 2009 CloudSat and CALIPSO (CC) data. The CC lidar and radar profiles provide the vertical structure that serves as output truth for a multilayer ANN, or MLANN, algorithm. Applying the trained MLANN to independent July 2008 MODIS data resulted in a combined ML and single layer hit rate of 75% (72%) for nonpolar regions during the day (night). The results are comparable to or more accurate than currently available methods. Areas of improvement are identified and will be addressed in future versions of the MLANN.

  10. Accurate optical vector network analyzer based on optical single-sideband modulation and balanced photodetection.

    Science.gov (United States)

    Xue, Min; Pan, Shilong; Zhao, Yongjiu

    2015-02-15

    A novel optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation and balanced photodetection is proposed and experimentally demonstrated, which can eliminate the measurement error induced by the high-order sidebands in the OSSB signal. According to the analytical model of the conventional OSSB-based OVNA, if the optical carrier in the OSSB signal is fully suppressed, the measurement result is exactly the high-order-sideband-induced measurement error. By splitting the OSSB signal after the optical device-under-test (ODUT) into two paths, removing the optical carrier in one path, and then detecting the two signals in the two paths using a balanced photodetector (BPD), high-order-sideband-induced measurement error can be ideally eliminated. As a result, accurate responses of the ODUT can be achieved without complex post-signal processing. A proof-of-concept experiment is carried out. The magnitude and phase responses of a fiber Bragg grating (FBG) measured by the proposed OVNA with different modulation indices are superimposed, showing that the high-order-sideband-induced measurement error is effectively removed.

  11. Wideband optical vector network analyzer based on optical single-sideband modulation and optical frequency comb.

    Science.gov (United States)

    Xue, Min; Pan, Shilong; He, Chao; Guo, Ronghui; Zhao, Yongjiu

    2013-11-15

    A novel approach to increase the measurement range of the optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation is proposed and experimentally demonstrated. In the proposed system, each comb line in an optical frequency comb (OFC) is selected by an optical filter and used as the optical carrier for the OSSB-based OVNA. The frequency responses of an optical device-under-test (ODUT) are thus measured channel by channel. Because the comb lines in the OFC have fixed frequency spacing, by fitting the responses measured in all channels together, the magnitude and phase responses of the ODUT can be accurately achieved in a large range. A proof-of-concept experiment is performed. A measurement range of 105 GHz and a resolution of 1 MHz is achieved when a five-comb-line OFC with a frequency spacing of 20 GHz is applied to measure the magnitude and phase responses of a fiber Bragg grating.

  12. Modeling and Control of Heat Networks with Storage : the Single-Producer Multiple-Consumer Case

    NARCIS (Netherlands)

    Scholten, Tjeert Wobko; De Persis, Claudio; Tesi, Pietro

    2015-01-01

    In heat networks, energy storage is a viable approach to balance demand and supply. In such a network, a heat carrier is used in the form of water, where heat is injected and extracted through heat exchangers. The network can transport and store heated water in stratification tanks to shift loads in

  13. Modeling and control of heat networks with storage: The single-producer multiple-consumer case.

    NARCIS (Netherlands)

    Scholten, Tjardo; De Persis, Claudio; Tesi, Pietro

    2015-01-01

    In heat networks, energy storage is a viable approach to balance demand and supply. In such a network, a heat carrier is used in the form of water, where heat is injected and extracted through heat exchangers. The network can transport and store heated water in stratification tanks to shift loads in

  14. Interbacterial Adhesion Networks within Early Oral Biofilms of Single Human Hosts.

    Science.gov (United States)

    Palmer, Robert J; Shah, Nehal; Valm, Alex; Paster, Bruce; Dewhirst, Floyd; Inui, Taichi; Cisar, John O

    2017-06-01

    Specific interbacterial adhesion, termed coaggregation, is well established for three early colonizers of the plaque biofilm: streptococci, actinomyces, and veillonellae. However, little is known about interactions of other early colonizers and about the extent of interactions within the bacterial community from a single host. To address these gaps, subject-specific culture collections from two individuals were established using an intraoral biofilm retrieval device. Molecular taxonomy (Human Oral Microbe Identification Microarray [HOMIM]) analysis of biofilm samples confirmed the integrity and completeness of the collections. HOMIM analysis verified the isolation of Streptococcus gordonii and S. anginosus from only one subject, as well as isolation of a previously uncultivated streptococcal phylotype from the other subject. Strains representative of clonal diversity within each collection were further characterized. Greater than 70% of these streptococcal strains from each subject coaggregated with at least one other coisolate. One-third of the strains carry a known coaggregation mediator: receptor polysaccharide (RPS). Almost all nonstreptococcal isolates coaggregated with other coisolates. Importantly, certain Rothia strains demonstrated more coaggregations with their coisolated bacteria than did any Streptococcus or Actinomyces strain, and certain Haemophilus isolates participated in twice as many. Confocal microscopy of undisturbed biofilms showed that Rothia and Haemophilus each occur in small multispecies microcolonies. However, in confluent high-biomass regions, Rothia occurred in islands whereas Haemophilus was distributed throughout. Together, the data demonstrate that coaggregation networks within an individual's oral microflora are extensive and that Rothia and Haemophilus can be important initiators of cell-cell interactions in the early biofilm. IMPORTANCE Extensive involvement of specific interbacterial adhesion in dental plaque biofilm formation has

  15. Towards quantum networks of single spins: analysis of a quantum memory with an optical interface in diamond.

    Science.gov (United States)

    Blok, M S; Kalb, N; Reiserer, A; Taminiau, T H; Hanson, R

    2015-01-01

    Single defect centers in diamond have emerged as a powerful platform for quantum optics experiments and quantum information processing tasks. Connecting spatially separated nodes via optical photons into a quantum network will enable distributed quantum computing and long-range quantum communication. Initial experiments on trapped atoms and ions as well as defects in diamond have demonstrated entanglement between two nodes over several meters. To realize multi-node networks, additional quantum bit systems that store quantum states while new entanglement links are established are highly desirable. Such memories allow for entanglement distillation, purification and quantum repeater protocols that extend the size, speed and distance of the network. However, to be effective, the memory must be robust against the entanglement generation protocol, which typically must be repeated many times. Here we evaluate the prospects of using carbon nuclear spins in diamond as quantum memories that are compatible with quantum networks based on single nitrogen vacancy (NV) defects in diamond. We present a theoretical framework to describe the dephasing of the nuclear spins under repeated generation of NV spin-photon entanglement and show that quantum states can be stored during hundreds of repetitions using typical experimental coupling parameters. This result demonstrates that nuclear spins with weak hyperfine couplings are promising quantum memories for quantum networks.

  16. Channel capacity of TDD-OFDM-MIMO for multiple access points in a wireless single-frequency-network

    DEFF Research Database (Denmark)

    Takatori, Y.; Fitzek, Frank; Tsunekawa, K.

    2005-01-01

    MIMO data transmission scheme, which combines Single-Frequency-Network (SFN) with TDD-OFDM-MIMO applied for wireless LAN networks. In our proposal, we advocate to use SFN for multiple access points (MAP) MIMO data transmission. The goal of this approach is to achieve very high channel capacity in both...... LOS and non line of sight (NLOS) environments. The channel capacity of the proposed method is derived for the direct path environments and it confirms the effectiveness of the proposed scheme in the LOS scenario. Moreover, solid computer simulation results confirm the effectiveness of the proposed...

  17. Cloud Height Estimation with a Single Digital Camera and Artificial Neural Networks

    Science.gov (United States)

    Carretas, Filipe; Janeiro, Fernando M.

    2014-05-01

    Clouds influence the local weather, the global climate and are an important parameter in the weather prediction models. Clouds are also an essential component of airplane safety when visual flight rules (VFR) are enforced, such as in most small aerodromes where it is not economically viable to install instruments for assisted flying. Therefore it is important to develop low cost and robust systems that can be easily deployed in the field, enabling large scale acquisition of cloud parameters. Recently, the authors developed a low-cost system for the measurement of cloud base height using stereo-vision and digital photography. However, due to the stereo nature of the system, some challenges were presented. In particular, the relative camera orientation requires calibration and the two cameras need to be synchronized so that the photos from both cameras are acquired simultaneously. In this work we present a new system that estimates the cloud height between 1000 and 5000 meters. This prototype is composed by one digital camera controlled by a Raspberry Pi and is installed at Centro de Geofísica de Évora (CGE) in Évora, Portugal. The camera is periodically triggered to acquire images of the overhead sky and the photos are downloaded to the Raspberry Pi which forwards them to a central computer that processes the images and estimates the cloud height in real time. To estimate the cloud height using just one image requires a computer model that is able to learn from previous experiences and execute pattern recognition. The model proposed in this work is an Artificial Neural Network (ANN) that was previously trained with cloud features at different heights. The chosen Artificial Neural Network is a three-layer network, with six parameters in the input layer, 12 neurons in the hidden intermediate layer, and an output layer with only one output. The six input parameters are the average intensity values and the intensity standard deviation of each RGB channel. The output

  18. ESTABLISHED MODES AND STATIC CHARACTERISTICS OF THREE-PHASE ASYNCHRONOUS MOTOR POWERED WITH SINGLE PHASE NETWORK

    Directory of Open Access Journals (Sweden)

    V. S. Malyar

    2016-01-01

    Full Text Available A mathematical model is developed to study the operation of three-phase asynchronous motor with squirrel-cage rotor when the stator winding is powered from a single phase network. To create a rotating magnetic field one of the phases is fed through the capacitor. Due to the asymmetry of power feed not only transients, but the steady-state regimes are dynamic, so they are described by differential equations in any coordinate system. Their study cannot be carried out with sufficient adequacy on the basis of known equivalent circuits and require the use of dynamic parameters. In the mathematical model the state equations of the circuits of the stator and rotor are composed in the stationary three phase coordinate system. Calculation of the established mode is performed by solving the boundary problem that makes it possible to obtain the coordinate dependences over the period, without calculation of the transient process. In order to perform it, the original nonlinear differential equations are algebraized by approximating the variables with the use of cubic splines. The resulting nonlinear system of algebraic equations is a discrete analogue of the initial system of differential equations. It is solved by parameter continuation method. To calculate the static characteristics as a function of a certain variable, the system is analytically differentiated, and then numerically integrated over this variable. In the process of integration, Newton's refinement is performed at each step or at every few steps, making it possible to implement the integration in just a few steps using Euler's method. Jacobi matrices in both cases are the same. To account for the current displacement in the rods of the squirrel-cage rotor, each of them, along with the squirrel-cage rings, is divided in height into several elements. This results in several squirrel-cage rotor windings which are represented by three-phase windings with magnetic coupling between them.

  19. Quantitative measurement of alterations in DNA damage repair (DDR) pathways using single cell network profiling (SCNP).

    Science.gov (United States)

    Rosen, David B; Leung, Ling Y; Louie, Brent; Cordeiro, James A; Conroy, Andrew; Shapira, Iuliana; Fields, Scott Z; Cesano, Alessandra; Hawtin, Rachael E

    2014-06-25

    Homologous recombination repair (HRR) pathway deficiencies have significant implications for cancer predisposition and treatment strategies. Improved quantitative methods for functionally characterizing these deficiencies are required to accurately identify patients at risk of developing cancer and to identify mechanisms of drug resistance or sensitivity. Flow cytometry-based single cell network profiling (SCNP) was used to measure drug-induced activation of DNA damage response (DDR) proteins in cell lines with defined HRR pathway mutations (including ATM-/-, ATM+/-, BRCA1+/-, BRCA2-/-) and in primary acute myeloid leukemia (AML) samples. Both non-homologous end joining (NHEJ) and HRR pathways were examined by measuring changes in intracellular readouts (including p-H2AX, p-ATM, p-DNA-PKcs, p-53BP1, p-RPA2/32, p-BRCA1, p-p53, and p21) in response to exposure to mechanistically distinct genotoxins. The cell cycle S/G2/M phase CyclinA2 marker was used to normalize for proliferation rates. Etoposide induced proliferation-independent DNA damage and activation of multiple DDR proteins in primary AML cells and ATM +/+but not ATM -/- cell lines. Treatment with the PARPi AZD2281 +/- temozolomide induced DNA damage in CyclinA2+ cells in both primary AML cells and cell lines and distngiushed cell lines deficient (BRCA2-/-) or impaired (BRCA1+/-) in HRR activity from BRCA1+/+ cell lines based on p-H2AX induction. Application of this assay to primary AML samples identified heterogeneous patterns of repair activity including muted or proficient activation of NHEJ and HRR pathways and predominant activation of NHEJ in a subset of samples. SCNP identified functional DDR readouts in both NHEJ and HRR pathways, which can be applied to identify cells with BRCA1+/- haploinsuffiency and characterize differential DDR pathway functionality in primary clinical samples.

  20. Detection of a nerve agent simulant using single-walled carbon nanotube networks: dimethyl-methyl-phosphonate

    International Nuclear Information System (INIS)

    Kim, Yeonju; Lee, Seunghyun; Choi, Hyang Hee; Noh, Jin-Seo; Lee, Wooyoung

    2010-01-01

    Single-walled carbon nanotube (SWNT) networks were used to detect hazardous dimethyl-methyl-phosphonate (DMMP) gas in real time, employing two different metals as electrodes. Random networks of SWNTs were simply obtained by drop-casting a SWNT-containing solution onto a surface-oxidized Si substrate. Although the electrical responses to DMMP at room temperature were reversible for both metals, the Pd-contacting SWNT network sensors exhibited a higher response and a shorter response time than those of the Au-contacting SWNT network sensors at the same DMMP concentration, due to the stronger interactions between the SWNTs and Pd surface atoms. In Pd-contacting SWNT network sensors, the response increased linearly with increasing DMMP concentration and reproducible response curves were obtained for DMMP levels as low as 1 ppm. These results indicate that SWNT networks in contact with Pd electrodes can function as good DMMP sensors at room temperature with scalable and fast response and excellent recovery.

  1. Detection of a nerve agent simulant using single-walled carbon nanotube networks: dimethyl-methyl-phosphonate

    Science.gov (United States)

    Kim, Yeonju; Lee, Seunghyun; Choi, Hyang Hee; Noh, Jin-Seo; Lee, Wooyoung

    2010-12-01

    Single-walled carbon nanotube (SWNT) networks were used to detect hazardous dimethyl-methyl-phosphonate (DMMP) gas in real time, employing two different metals as electrodes. Random networks of SWNTs were simply obtained by drop-casting a SWNT-containing solution onto a surface-oxidized Si substrate. Although the electrical responses to DMMP at room temperature were reversible for both metals, the Pd-contacting SWNT network sensors exhibited a higher response and a shorter response time than those of the Au-contacting SWNT network sensors at the same DMMP concentration, due to the stronger interactions between the SWNTs and Pd surface atoms. In Pd-contacting SWNT network sensors, the response increased linearly with increasing DMMP concentration and reproducible response curves were obtained for DMMP levels as low as 1 ppm. These results indicate that SWNT networks in contact with Pd electrodes can function as good DMMP sensors at room temperature with scalable and fast response and excellent recovery.

  2. Label Space Reduction in MPLS Networks: How Much Can A Single Stacked Label Do?

    DEFF Research Database (Denmark)

    Solano, Fernando; Stidsen, Thomas K.; Fabregat, Ramon

    2008-01-01

    Most network operators have considered reducing LSR label spaces (number of labels used) as a way of simplifying management of underlaying virtual private networks (VPNs) and therefore reducing operational expenditure (OPEX). The IETF outlined the label merging feature in MPLS-allowing the config......Most network operators have considered reducing LSR label spaces (number of labels used) as a way of simplifying management of underlaying virtual private networks (VPNs) and therefore reducing operational expenditure (OPEX). The IETF outlined the label merging feature in MPLS...

  3. A Uniform Representation of Single and Multi-Stage Interconnection Networks Used in SIMD Machines.

    Science.gov (United States)

    1980-06-01

    This includes G, itself. Hence, the theorem . Q.E.D. Corollary 2: If G and G are equivalent for each p(P, there exists pCP such that: p p Proof: Proof...performs a bit-rearrangement permutation will be referred to as a bit network. Theorem 1 : There are n! b permutations of N - 2n elements. This set of...network, G, there are at most (n!) -_1 other networks that are equivalent to G. Proof: From Theorem 1, one has n! distinct bLU permutation networks that

  4. Force spectroscopy of hyaluronan by atomic force microscopy: from hydrogen-bonded networks toward single-chain behavior.

    Science.gov (United States)

    Giannotti, Marina I; Rinaudo, Marguerite; Vancso, G Julius

    2007-09-01

    The conformational behavior of hyaluronan (HA) polysaccharide chains in aqueous NaCl solution was characterized directly at the single-molecule level. This communication reports on one of the first single-chain atomic force microscopy (AFM) experiments performed at variable temperatures, investigating the influence of the temperature on the stability of the HA single-chain conformation. Through AFM single-molecule force spectroscopy, the temperature destabilization of a local structure was proven. This structure involved a hydrogen-bonded network along the polymeric chain, with hydrogen bonds between the polar groups of HA and possibly water, and a change from a nonrandom coil to a random coil behavior was observed when increasing the temperature from 29 +/- 1 to 46 +/- 1 degrees C. As a result of the applied force, this superstructure was found to break progressively at room temperature. The use of a hydrogen-bonding breaker solvent demonstrated the hydrogen-bonded water-bridged nature of the network structure of HA single chains in aqueous NaCl solution.

  5. Structure, function, and self-assembly of single network gyroid (I4132) photonic crystals in butterfly wing scales

    Science.gov (United States)

    Saranathan, Vinodkumar; Osuji, Chinedum O.; Mochrie, Simon G. J.; Noh, Heeso; Narayanan, Suresh; Sandy, Alec; Dufresne, Eric R.; Prum, Richard O.

    2010-01-01

    Complex three-dimensional biophotonic nanostructures produce the vivid structural colors of many butterfly wing scales, but their exact nanoscale organization is uncertain. We used small angle X-ray scattering (SAXS) on single scales to characterize the 3D photonic nanostructures of five butterfly species from two families (Papilionidae, Lycaenidae). We identify these chitin and air nanostructures as single network gyroid (I4132) photonic crystals. We describe their optical function from SAXS data and photonic band-gap modeling. Butterflies apparently grow these gyroid nanostructures by exploiting the self-organizing physical dynamics of biological lipid-bilayer membranes. These butterfly photonic nanostructures initially develop within scale cells as a core-shell double gyroid (Ia3d), as seen in block-copolymer systems, with a pentacontinuous volume comprised of extracellular space, cell plasma membrane, cellular cytoplasm, smooth endoplasmic reticulum (SER) membrane, and intra-SER lumen. This double gyroid nanostructure is subsequently transformed into a single gyroid network through the deposition of chitin in the extracellular space and the degeneration of the rest of the cell. The butterflies develop the thermodynamically favored double gyroid precursors as a route to the optically more efficient single gyroid nanostructures. Current approaches to photonic crystal engineering also aim to produce single gyroid motifs. The biologically derived photonic nanostructures characterized here may offer a convenient template for producing optical devices based on biomimicry or direct dielectric infiltration. PMID:20547870

  6. Application of higher harmonics in protection against single-phase earth faults in resonant grounded cable networks of medium voltage

    OpenAIRE

    Vinokurova, T. Yu.; Dobryagina, O. A.; Shagurina, E. S.; Shuin, V. A.

    2015-01-01

    Protections based by higher harmonics absolute measurements the zero sequence currents of the protected object connections against single-phase earth faults in resonant grounded cable networks of medium voltage industrial and urban energy supply systems have been widely applied in Russia since the late 60s of the 20th century. However, some operational problems connected with sufficient selectivity and sensitivity of these protection devices appeared with time. Sensitivity and selectivity of ...

  7. Single and Networked ZnO-CNT Hybrid Tetrapods for Selective Room-Temperature High-Performance Ammonia Sensors.

    Science.gov (United States)

    Schütt, Fabian; Postica, Vasile; Adelung, Rainer; Lupan, Oleg

    2017-07-12

    Highly porous hybrid materials with unique high-performance properties have attracted great interest from the scientific community, especially in the field of gas-sensing applications. In this work, tetrapodal-ZnO (ZnO-T) networks were functionalized with carbon nanotubes (CNTs) to form a highly efficient hybrid sensing material (ZnO-T-CNT) for ultrasensitive, selective, and rapid detection of ammonia (NH 3 ) vapor at room temperature. By functionalizing the ZnO-T networks with 2.0 wt % of CNTs by a simple dripping procedure, an increase of 1 order of magnitude in response (from about 37 to 330) was obtained. Additionally, the response and recovery times were improved (by decreasing them from 58 and 61 s to 18 and 35 s, respectively). The calculated lowest detection limit of 200 ppb shows the excellent potential of the ZnO-T-CNT networks as NH 3 vapor sensors. Room temperature operation of such networked ZnO-CNT hybrid tetrapods shows an excellent long-time stability of the fabricated sensors. Additionally, the gas-sensing mechanism was identified and elaborated based on the high porosity of the used three-dimensional networks and the excellent conductivity of the CNTs. On top of that, several single hybrid microtetrapod-based devices were fabricated (from samples with 2.0 wt % CNTs) with the help of the local metal deposition function of a focused ion beam/scanning electron microscopy instrument. The single microdevices are based on tetrapods with arms having a diameter of around 0.35 μm and show excellent NH 3 sensing performance with a gas response (I gas /I air ) of 6.4. Thus, the fabricated functional networked ZnO-CNT hybrid tetrapods will allow to detect ammonia and to quantify its concentration in automotive, environmental monitoring, chemical industry, and medical diagnostics.

  8. A highly crystalline single Au wire network as a high temperature transparent heater.

    Science.gov (United States)

    Rao, K D M; Kulkarni, Giridhar U

    2014-06-07

    A transparent conductor which can generate high temperatures finds important applications in optoelectronics. In this article, a wire network made of Au on quartz is shown to serve as an effective high temperature transparent heater. The heater has been fabricated by depositing Au onto a cracked sacrificial template. The highly interconnected Au wire network thus formed exhibited a transmittance of ∼87% in a wide spectral range with a sheet resistance of 5.4 Ω □(-1). By passing current through the network, it could be joule heated to ∼600 °C within a few seconds. The extraordinary thermal performance and stability owe much to the seamless junctions present in the wire network. Furthermore, the wire network gets self-annealed through joule heating as seen from its increased crystallinity. Interestingly, both transmittance and sheet resistance improved following annealing to 92% and 3.2 Ω □(-1), respectively.

  9. Loss-efficiency model of single and variable-speed compressors using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Liang [Institute of Refrigeration and Cryogenics, Shanghai Jiaotong University, Shanghai 200240 (China); China R and D Center, Carrier Corporation, No.3239 Shen Jiang Road, Shanghai 201206 (China); Zhao, Ling-Xiao; Gu, Bo [Institute of Refrigeration and Cryogenics, Shanghai Jiaotong University, Shanghai 200240 (China); Zhang, Chun-Lu [China R and D Center, Carrier Corporation, No.3239 Shen Jiang Road, Shanghai 201206 (China)

    2009-09-15

    Compressor is the critical component to the performance of a vapor-compression refrigeration system. The loss-efficiency model including the volumetric efficiency and the isentropic efficiency is widely used for representing the compressor performance. A neural network loss-efficiency model is developed to simulate the performance of positive displacement compressors like the reciprocating, screw and scroll compressors. With one more input, frequency, it can be easily extended to the variable speed compressors. The three-layer polynomial perceptron network is developed because the polynomial transfer function is found very effective in training and free of over-learning. The selection of input parameters of neural networks is also found critical to the network prediction accuracy. The proposed neural networks give less than 0.4% standard deviations and {+-}1.3% maximum deviations against the manufacturer data. (author)

  10. Wireless Sensor Network Congestion Control Based on Standard Particle Swarm Optimization and Single Neuron PID.

    Science.gov (United States)

    Yang, Xiaoping; Chen, Xueying; Xia, Riting; Qian, Zhihong

    2018-04-19

    Aiming at the problem of network congestion caused by the large number of data transmissions in wireless routing nodes of wireless sensor network (WSN), this paper puts forward an algorithm based on standard particle swarm⁻neural PID congestion control (PNPID). Firstly, PID control theory was applied to the queue management of wireless sensor nodes. Then, the self-learning and self-organizing ability of neurons was used to achieve online adjustment of weights to adjust the proportion, integral and differential parameters of the PID controller. Finally, the standard particle swarm optimization to neural PID (NPID) algorithm of initial values of proportion, integral and differential parameters and neuron learning rates were used for online optimization. This paper describes experiments and simulations which show that the PNPID algorithm effectively stabilized queue length near the expected value. At the same time, network performance, such as throughput and packet loss rate, was greatly improved, which alleviated network congestion and improved network QoS.

  11. An Efficient Data Collection Protocol Based on Multihop Routing and Single-Node Cooperation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Guoqiang Zheng

    2014-01-01

    Full Text Available Considering the constrained resource and energy in wireless sensor networks, an efficient data collection protocol named ESCDD which adopts the multihop routing technology and the single-node selection cooperative communication is proposed to make the communication protocol more simple and easy to realize for the large-scale multihop wireless sensor networks. ESCDD uses the greedy strategy and the control information based on RTS/CTS to select forwarding nodes. Then, the hops in the multihop data transmission are reduced. Based on the power control in physical layer and the control frame called CoTS in MAC layer, ESCDD chooses a single cooperative node to perform cooperative transmission. The receiving node adopts maximal ratio combining (MRC to recover original data. The energy consumption per hop is reduced. Furthermore, the total energy consumption in data collection process is shared by more nodes and the network lifetime is extended. Compared with GeRaF, EERNFS, and REEFG protocol, the simulation results show that ESCDD can effectively reduce the average delay of multihop data transmission, improve the successful delivery rate of data packets, significantly save the energy consumption of network nodes, and make the energy consumption more balanced.

  12. Molecular dynamics study on the evolution of interfacial dislocation network and mechanical properties of Ni-based single crystal superalloys

    Science.gov (United States)

    Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai

    2018-05-01

    The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.

  13. Single-chip MEMS 5 × 5 and 20 × 20 double-pole single-throw switch arrays for automating telecommunication networks

    International Nuclear Information System (INIS)

    Braun, S; Oberhammer, J; Stemme, G

    2008-01-01

    This paper reports on microelectromechanical (MEMS) switch arrays with 5 × 5 and 20 × 20 double-pole single-throw (DPST) switches embedded and packaged on a single chip, which are intended for automating main distribution frames in copper-wire telecommunication networks. Whenever a customer requests a change in his telecommunication services, the copper-wire network has to be reconfigured which is currently done manually by a costly physical re-routing of the connections in the main distribution frames. To reduce the costs, new methods for automating the network reconfiguration are sought after by the network providers. The presented devices comprise 5 × 5 or 20 × 20 double switches, which allow us to interconnect any of the 5 or 20 input lines to any of the 5 or 20 output lines. The switches are based on an electrostatic S-shaped film actuator with the switch contact on a flexible membrane, moving between a top and a bottom electrode. The devices are fabricated in two parts which are designed to be assembled using selective adhesive wafer bonding, resulting in a wafer-scale package of the switch array. The on-chip routing network consists of thick metal lines for low resistance and is embedded in bencocyclobutene (BCB) polymer layers. The packaged 5 × 5 switch arrays have a size of 6.7 × 6.4 mm 2 and the 20 × 20 arrays are 14 × 10 mm 2 large. The switch actuation voltages for closing/opening the switches averaged over an array were measured to be 21.2 V/15.3 V for the 5 × 5 array and 93.2 V/37.3 V for the 20 × 20 array, respectively. The total signal line resistances vary depending on the switch position within the array between 0.13 Ω and 0.56 Ω for the 5 × 5 array and between 0.08 Ω to 2.33 Ω for the 20 × 20 array, respectively. The average resistance of the switch contacts was determined to be 0.22 Ω with a standard deviation of 0.05 Ω

  14. Constructing a generalized network design model to study air distribution in ventilation networks in subway with a single-track tunnel

    Science.gov (United States)

    Lugin, IV

    2018-03-01

    In focus are the features of construction of the generalized design model for the network method to study air distribution in ventilation system in subway with the single-track tunnel. The generalizations, assumptions and simplifications included in the model are specified. The air distribution is calculated with regard to the influence of topology and air resistances of the ventilation network sections. The author studies two variants of the subway line: half-open and closed with dead end on the both sides. It is found that the total air exchange at a subway station depends on the station location within the line. The operating mode of fans remains unaltered in this case. The article shows that elimination of air leakage in the station ventilation room allows an increase in the air flow rate by 7–8% at the same energy consumption by fans. The influence of the stop of a train in the tunnel on the air distribution is illustrated.

  15. Kriging-Based Parameter Estimation Algorithm for Metabolic Networks Combined with Single-Dimensional Optimization and Dynamic Coordinate Perturbation.

    Science.gov (United States)

    Wang, Hong; Wang, Xicheng; Li, Zheng; Li, Keqiu

    2016-01-01

    The metabolic network model allows for an in-depth insight into the molecular mechanism of a particular organism. Because most parameters of the metabolic network cannot be directly measured, they must be estimated by using optimization algorithms. However, three characteristics of the metabolic network model, i.e., high nonlinearity, large amount parameters, and huge variation scopes of parameters, restrict the application of many traditional optimization algorithms. As a result, there is a growing demand to develop efficient optimization approaches to address this complex problem. In this paper, a Kriging-based algorithm aiming at parameter estimation is presented for constructing the metabolic networks. In the algorithm, a new infill sampling criterion, named expected improvement and mutual information (EI&MI), is adopted to improve the modeling accuracy by selecting multiple new sample points at each cycle, and the domain decomposition strategy based on the principal component analysis is introduced to save computing time. Meanwhile, the convergence speed is accelerated by combining a single-dimensional optimization method with the dynamic coordinate perturbation strategy when determining the new sample points. Finally, the algorithm is applied to the arachidonic acid metabolic network to estimate its parameters. The obtained results demonstrate the effectiveness of the proposed algorithm in getting precise parameter values under a limited number of iterations.

  16. Transcriptional Networks in Single Perivascular Cells Sorted from Human Adipose Tissue Reveal a Hierarchy of Mesenchymal Stem Cells.

    Science.gov (United States)

    Hardy, W Reef; Moldovan, Nicanor I; Moldovan, Leni; Livak, Kenneth J; Datta, Krishna; Goswami, Chirayu; Corselli, Mirko; Traktuev, Dmitry O; Murray, Iain R; Péault, Bruno; March, Keith

    2017-05-01

    Adipose tissue is a rich source of multipotent mesenchymal stem-like cells, located in the perivascular niche. Based on their surface markers, these have been assigned to two main categories: CD31 - /CD45 - /CD34 + /CD146 - cells (adventitial stromal/stem cells [ASCs]) and CD31 - /CD45 - /CD34 - /CD146 + cells (pericytes [PCs]). These populations display heterogeneity of unknown significance. We hypothesized that aldehyde dehydrogenase (ALDH) activity, a functional marker of primitivity, could help to better define ASC and PC subclasses. To this end, the stromal vascular fraction from a human lipoaspirate was simultaneously stained with fluorescent antibodies to CD31, CD45, CD34, and CD146 antigens and the ALDH substrate Aldefluor, then sorted by fluorescence-activated cell sorting. Individual ASCs (n = 67) and PCs (n = 73) selected from the extremities of the ALDH-staining spectrum were transcriptionally profiled by Fluidigm single-cell quantitative polymerase chain reaction for a predefined set (n = 429) of marker genes. To these single-cell data, we applied differential expression and principal component and clustering analysis, as well as an original gene coexpression network reconstruction algorithm. Despite the stochasticity at the single-cell level, covariation of gene expression analysis yielded multiple network connectivity parameters suggesting that these perivascular progenitor cell subclasses possess the following order of maturity: (a) ALDH br ASC (most primitive); (b) ALDH dim ASC; (c) ALDH br PC; (d) ALDH dim PC (least primitive). This order was independently supported by specific combinations of class-specific expressed genes and further confirmed by the analysis of associated signaling pathways. In conclusion, single-cell transcriptional analysis of four populations isolated from fat by surface markers and enzyme activity suggests a developmental hierarchy among perivascular mesenchymal stem cells supported by markers and coexpression

  17. Force Spectroscopy of Hyaluronan by AFM; From H-bonded Networks Towards Single Chain Behavior

    NARCIS (Netherlands)

    Giannotti, M.I.; Rinaudo, Marguerite; Vancso, Gyula J.

    2007-01-01

    The conformational behavior of hyaluronan (HA) polysaccharide chains in aqueous NaCl solution was characterized directly at the single-molecule level. This comunication reports on one of the first single-chain atomic force microscopy (AFM) experiments performed at variable temperatures,

  18. Spontaneous Neuronal Activity in Developing Neocortical Networks: From Single Cells to Large-Scale Interactions.

    Science.gov (United States)

    Luhmann, Heiko J; Sinning, Anne; Yang, Jenq-Wei; Reyes-Puerta, Vicente; Stüttgen, Maik C; Kirischuk, Sergei; Kilb, Werner

    2016-01-01

    Neuronal activity has been shown to be essential for the proper formation of neuronal circuits, affecting developmental processes like neurogenesis, migration, programmed cell death, cellular differentiation, formation of local and long-range axonal connections, synaptic plasticity or myelination. Accordingly, neocortical areas reveal distinct spontaneous and sensory-driven neuronal activity patterns already at early phases of development. At embryonic stages, when immature neurons start to develop voltage-dependent channels, spontaneous activity is highly synchronized within small neuronal networks and governed by electrical synaptic transmission. Subsequently, spontaneous activity patterns become more complex, involve larger networks and propagate over several neocortical areas. The developmental shift from local to large-scale network activity is accompanied by a gradual shift from electrical to chemical synaptic transmission with an initial excitatory action of chloride-gated channels activated by GABA, glycine and taurine. Transient neuronal populations in the subplate (SP) support temporary circuits that play an important role in tuning early neocortical activity and the formation of mature neuronal networks. Thus, early spontaneous activity patterns control the formation of developing networks in sensory cortices, and disturbances of these activity patterns may lead to long-lasting neuronal deficits.

  19. Single-phase and two-phase flow properties of mesaverde tight sandstone formation; random-network modeling approach

    Science.gov (United States)

    Bashtani, Farzad; Maini, Brij; Kantzas, Apostolos

    2016-08-01

    3D random networks are constructed in order to represent the tight Mesaverde formation which is located in north Wyoming, USA. The porous-space is represented by pore bodies of different shapes and sizes which are connected to each other by pore throats of varying length and diameter. Pore bodies are randomly distributed in space and their connectivity varies based on the connectivity number distribution which is used in order to generate the network. Network representations are then validated using publicly available mercury porosimetry experiments. The network modeling software solves the fundamental equations of two-phase immiscible flow incorporating wettability and contact angle variability. Quasi-static displacement is assumed. Single phase macroscopic properties (porosity, permeability) are calculated and whenever possible are compared to experimental data. Using this information drainage and imbibition capillary pressure, and relative permeability curves are predicted and (whenever possible) compared to experimental data. The calculated information is grouped and compared to available literature information on typical behavior of tight formations. Capillary pressure curve for primary drainage process is predicted and compared to experimental mercury porosimetry in order to validate the virtual porous media by history matching. Relative permeability curves are also calculated and presented.

  20. Single-point reactive power control method on voltage rise mitigation in residential networks with high PV penetration

    DEFF Research Database (Denmark)

    Hasheminamin, Maryam; Agelidis, Vassilios; Ahmadi, Abdollah

    2018-01-01

    Voltage rise (VR) due to reverse power flow is an important obstacle for high integration of Photovoltaic (PV) into residential networks. This paper introduces and elaborates a novel methodology of an index-based single-point-reactive power-control (SPRPC) methodology to mitigate voltage rise by ...... system with high r/x ratio. Efficacy, effectiveness and cost study of SPRPC is compared to droop control to evaluate its advantages....... by absorbing adequate reactive power from one selected point. The proposed index utilizes short circuit analysis to select the best point to apply this Volt/Var control method. SPRPC is supported technically and financially by distribution network operator that makes it cost effective, simple and efficient...

  1. Analysis Of Using Firewall And Single Honeypot In Training Attack On Wireless Network

    Science.gov (United States)

    Mohd. Diansyah, Tengku.; Faisal, Ilham; Perdana, Adidtya; Octaviani Sembiring, Boni; Hidayati Sinaga, Tantri

    2017-12-01

    Security issues become one of the important aspects of a network, especially a network security on the server. These problems underlie the need to build a system that can detect threats from parties who do not have access rights (hackers) that are by building a security system honeypot. A Honeypot is a diversion of intruders' attention, in order for intruders to think that it has managed to break down and retrieve data from a network, when in fact the data is not important and the location is isolated. A way to trap or deny unauthorized use of effort in an information system. One type of honeypot is honeyd. Honeyd is a low interaction honeypot that has a smaller risk compared to high interaction types because the interaction with the honeypot does not directly involve the real system. The purpose of the implementation of honeypot and firewall, firewall is used on Mikrotik. Can be used as an administrative tool to view reports of Honeyd generated activity and administrators can also view reports that are stored in the logs in order to assist in determining network security policies.

  2. Precision requirements for single-layer feed-forward neural networks

    NARCIS (Netherlands)

    Annema, Anne J.; Hoen, K.; Hoen, Klaas; Wallinga, Hans

    1994-01-01

    This paper presents a mathematical analysis of the effect of limited precision analog hardware for weight adaptation to be used in on-chip learning feedforward neural networks. Easy-to-read equations and simple worst-case estimations for the maximum tolerable imprecision are presented. As an

  3. Modeling and Control of Heat Networks With Storage : The Single-Producer Multiple-Consumer Case

    NARCIS (Netherlands)

    Scholten, Tjardo; De Persis, Claudio; Tesi, Pietro

    In heat networks, energy storage in the form of hot water in a tank is a viable approach to balancing supply and demand. In order to store a desired amount of energy, both the volume and temperature of the water in the tank need to converge to desired setpoints. To this end, we provide a provably

  4. The replacement principle in networked economies with single-peaked preferences

    DEFF Research Database (Denmark)

    Szwagrzak, Karol

    2016-01-01

    We study the transfer of a resource from a group of suppliers to a group of demanders through links in a network. The analysis is relevant to situations where institutional constraints bar the use of the price mechanism: the allocation of workloads under fixed salaries, a commodity under disequil...

  5. Search for supersymmetry in events with a single lepton, jets, and missing transverse momentum using a neural network

    CERN Document Server

    Chatterjee, Avishek

    A search for supersymmetry in proton-proton collisions at $\\sqrt{s} = 7$ TeV is presented, focusing on events with a single isolated lepton, energetic jets, and large missing transverse momentum. The analyzed data corresponds to a total integrated luminosity of 4.98 fb$^{−1}$ recorded by the CMS experiment. The search uses an artificial neural network to suppress Standard Model backgrounds, and estimates residual backgrounds using a fully data-driven method. The analysis is performed in both the muon and electron channels, and the combined result is interpreted in terms of limits on the CMSSM parameter space, as well as a simplified model.

  6. A method to detect single and multiple delamination problems using a combined neural network technique and genetic algorithm optimization

    Science.gov (United States)

    Le, Hieu The

    This thesis develops a new method to detect delaminations in composite laminates using a combination of finite element method, artificial neural networks, and genetic algorithms. Next, this newly developed method is applied to successfully solve delamination detection problems. Delaminations in a composite laminate with various sizes and locations are considered in the present studies. The improved layerwise shear deformation theory is implemented into the finite element method and used to calculate responses of laminates with single and multiple delaminations. Mappings between the natural frequencies and delamination characteristics are first determined from the developed models. These data are then used to train artificial neural networks of multiplayer perceptron using back-propagation. These trained artificial neural networks are in turn used as an approximate tool to calculate the responses of the delaminated laminates and to feed the data to the delamination detection process. Two different approaches for handling the neural network models are applied in the work and are presented for comparison. The delamination detection problem is formulated as an optimization problem with mixed type design variables. A genetic algorithm, which is a guided probabilistic search technique based on the simulation of Darwin's principle of evolution and natural selection, is developed to solve this optimization problem. Single through-the-width delamination, single internal delamination, and multiple through-the-width delaminations are separately considered for detection study. At last, the application is extended to the most challenging problem, which is the detection of general delamination. Various factors affecting the detection process such as the finite element convergence factor and the laminate geometry factor are also examined. Case studies are made and the findings are summarized in detail in each chapter of the dissertation. It is found that the newly developed

  7. Low-cost coherent receiver for long-reach optical access network using single-ended detection.

    Science.gov (United States)

    Zhang, Xuebing; Li, Zhaohui; Li, Jianping; Yu, Changyuan; Lau, Alan Pak Tao; Lu, Chao

    2014-09-15

    A low-cost coherent receiver using two 2×3 optical hybrids and single-ended detection is proposed for long-reach optical access network. This structure can detect the two polarization components of polarization division multiplexing (PDM) signals. Polarization de-multiplexing and signal-to-signal beat interference (SSBI) cancellation are realized by using only three photodiodes. Simulation results for 40 Gb/s PDM-OFDM transmissions indicate that the low-cost coherent receiver has 3.2 dB optical signal-to-noise ratio difference compared with the theoretical value.

  8. Parallel algorithms and archtectures for computational structural mechanics

    Science.gov (United States)

    Patrick, Merrell; Ma, Shing; Mahajan, Umesh

    1989-01-01

    The determination of the fundamental (lowest) natural vibration frequencies and associated mode shapes is a key step used to uncover and correct potential failures or problem areas in most complex structures. However, the computation time taken by finite element codes to evaluate these natural frequencies is significant, often the most computationally intensive part of structural analysis calculations. There is continuing need to reduce this computation time. This study addresses this need by developing methods for parallel computation.

  9. Web-based Novel Archtecture For Intelligent Tutoring | Japheth ...

    African Journals Online (AJOL)

    Journal of Computer Science and Its Application. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 19, No 1 (2012) >. Log in or Register to get access to full text downloads.

  10. Archtecture According to Children : Tree House World / Pille Runnel

    Index Scriptorium Estoniae

    Runnel, Pille, 1974-

    2015-01-01

    Linnalaste ja -noorte teemalisest näitusest "Niisama linnas" ("Chilling Around the Town") Eesti Rahva Muuseumis 16. mai 2014-11.01 2015. Teostuse on leidnud ka onnikavandite võistlusele auto-onni idee saatnud 10-aastase poisi Artur Soo unistus - "Onn ratastel OÜ" - vanasse veoautosse ehitatud onn

  11. A high resolution optical vector network analyzer based on a wideband and wavelength-tunable optical single-sideband modulator.

    Science.gov (United States)

    Tang, Zhenzhou; Pan, Shilong; Yao, Jianping

    2012-03-12

    A high resolution optical vector network analyzer (OVNA) implemented based on a wideband and wavelength-tunable optical single-sideband (OSSB) modulator is proposed and experimentally demonstrated. The OSSB modulation is achieved using a phase modulator and a tunable optical filter with a passband having two steep edges and a flat top. Wideband and wavelength-tunable OSSB modulation is achieved. The incorporation of the OSSB modulator into the OVNA is experimentally evaluated. The measurement of the magnitude and phase response of an ultra-narrow-band fiber Bragg grating (FBG) and that of the stimulated Brillouin scattering (SBS) in a single-mode fiber is performed. A measurement resolution as high as 78 kHz is achieved.

  12. Optimal power allocation of a single transmitter-multiple receivers channel in a cognitive sensor network

    KAUST Repository

    Ayala Solares, Jose Roberto

    2012-08-01

    The optimal transmit power of a wireless sensor network with one transmitter and multiple receivers in a cognitive radio environment while satisfying independent peak, independent average, sum of peak and sum of average transmission rate constraints is derived. A suboptimal scheme is proposed to overcome the frequency of outages for the independent peak transmission rate constraint. In all cases, numerical results are provided for Rayleigh fading channels. © 2012 IEEE.

  13. Carbon nanotubes: artificial nanomaterials to engineer single neurons and neuronal networks.

    Science.gov (United States)

    Fabbro, Alessandra; Bosi, Susanna; Ballerini, Laura; Prato, Maurizio

    2012-08-15

    In the past decade, nanotechnology applications to the nervous system have often involved the study and the use of novel nanomaterials to improve the diagnosis and therapy of neurological diseases. In the field of nanomedicine, carbon nanotubes are evaluated as promising materials for diverse therapeutic and diagnostic applications. Besides, carbon nanotubes are increasingly employed in basic neuroscience approaches, and they have been used in the design of neuronal interfaces or in that of scaffolds promoting neuronal growth in vitro. Ultimately, carbon nanotubes are thought to hold the potential for the development of innovative neurological implants. In this framework, it is particularly relevant to document the impact of interfacing such materials with nerve cells. Carbon nanotubes were shown, when modified with biologically active compounds or functionalized in order to alter their charge, to affect neurite outgrowth and branching. Notably, purified carbon nanotubes used as scaffolds can promote the formation of nanotube-neuron hybrid networks, able per se to affect neuron integrative abilities, network connectivity, and synaptic plasticity. We focus this review on our work over several years directed to investigate the ability of carbon nanotube platforms in providing a new tool for nongenetic manipulations of neuronal performance and network signaling.

  14. Improvement of Electrical Conductivity of Single-Walled Carbon Nano tube Network Using Particle Irradiation

    International Nuclear Information System (INIS)

    Lim, Suntaek; Kim, Gonho

    2010-01-01

    Substitution for Indium Tin Oxide of transparent electrode Applications : Flat panel displays, Touch panel, Solar cell, EM wave shielding... For very low energy of 20 eV and 90 eV, argon ion irradiations, the surface of SWCNT bundles were sputtered and thinned the diameter of the bundle. With increasing the incident ion energy as 7.5 keV, SWCNT bundles were networked by amorphization of cross welded CNTs. → Less damage can be obtained from higher energy of irradiated particle due to less collision cross section. For 10 MeV proton and 800 keV electron irradiations, there are no severe damages. Electron irradiation is more effective on network with less damage than that of ion irradiation. → Network process can be proceeded with the generation of free carbon, the migration of free carbon on CNT and reconstruction of the cross linked CNTs, which processes require the latent energy on CNT body after collision. It can be controlled by the energy and dose of irradiation particle

  15. Artificial neural networks that use single-photon emission tomography to identify patients with probable Alzheimer's disease

    International Nuclear Information System (INIS)

    Dawson, M.R.W.; Dobbs, A.; Hooper, H.R.; McEwan, A.J.B.; Triscott, J.; Cooney, J.

    1994-01-01

    Single-photon emission tomographic (SPET) images using technetium-99m labelled hexamethylpropylene amine oxime were obtained from 97 patients diagnosed as having Alzheimer's disease, as well as from a comparison group of 64 normal subjects. Multiple linear regression was used to predict subject type (Alzheimer's vs comparison) using scintillation counts from 14 different brain regions as predictors. These results were disappointing: the regression equation accounted for only 33.5% of the variance between subjects. However, the same data were also used to train parallel distributed processing (PDP) networks of different sizes to classify subjects. In general, the PDP networks accounted for substantially more (up to 95%) of the variance in the data, and in many instances were able to distinguish perfectly between the two subjects. These results suggest two conclusions. First, SPET images do provide sufficient information to distinguish patients with Alzheimer's disease from a normal comparison group. Second, to access this diagnostic information, it appears that one must take advantage of the ability of PDP networks to detect higher-order nonlinear relationships among the predictor variables. (orig.)

  16. Replica Node Detection Using Enhanced Single Hop Detection with Clonal Selection Algorithm in Mobile Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    L. S. Sindhuja

    2016-01-01

    Full Text Available Security of Mobile Wireless Sensor Networks is a vital challenge as the sensor nodes are deployed in unattended environment and they are prone to various attacks. One among them is the node replication attack. In this, the physically insecure nodes are acquired by the adversary to clone them by having the same identity of the captured node, and the adversary deploys an unpredictable number of replicas throughout the network. Hence replica node detection is an important challenge in Mobile Wireless Sensor Networks. Various replica node detection techniques have been proposed to detect these replica nodes. These methods incur control overheads and the detection accuracy is low when the replica is selected as a witness node. This paper proposes to solve these issues by enhancing the Single Hop Detection (SHD method using the Clonal Selection algorithm to detect the clones by selecting the appropriate witness nodes. The advantages of the proposed method include (i increase in the detection ratio, (ii decrease in the control overhead, and (iii increase in throughput. The performance of the proposed work is measured using detection ratio, false detection ratio, packet delivery ratio, average delay, control overheads, and throughput. The implementation is done using ns-2 to exhibit the actuality of the proposed work.

  17. Evaluation of Railway Networks with Single Track Operation Using the UIC 406 Capacity Method

    DEFF Research Database (Denmark)

    Landex, Alex

    2009-01-01

    Many capacity analyses using the UIC 406 capacity method for double track lines have been carried out and presented international, but few capacity analyses applying the capacity method to single track lines have been presented. Therefore, the differences between capacity analyses of double track...

  18. Infrared analysis of urinary calculi by a single reflection accessory and a neural network interpretation algorithm

    NARCIS (Netherlands)

    Volmer, M; de Vries, JCM; Goldschmidt, HMJ

    Background: Preparation of KBr tablets, used for Fourier transform infrared (FT-IR) analysis of urinary calculus composition, is time-consuming and often hampered by pellet breakage. We developed a new F:T-IR method for urinary calculus analysis. This method makes use of a Golden Gate Single

  19. The effect of amine protonation on the electrical properties of spin-assembled single-walled carbon nanotube networks

    International Nuclear Information System (INIS)

    Opatkiewicz, Justin P; LeMieux, Melburne C; Bao Zhenan; Patil, Nishant P; Wei Hai; Mitra, Subhasish

    2011-01-01

    Amine-terminated self-assembled monolayers (SAMs) have been shown to selectively adsorb semiconducting single-walled carbon nanotubes (sc-SWNTs). Previous studies have shown that when deposited by spin coating, the resulting nanotube networks (SWNTnts) can be strongly influenced by the charge state of the amine (primary, secondary, and tertiary). When the amine surfaces were exposed to varying pH solutions, the conductivity and overall quality of the resulting fabricated networks were altered. Atomic force microscopy (AFM) topography had shown that the density of the SWNTnts was reduced as the amine protonation decreased, indicating that the electrostatic attraction between the SWNTs in solution and the surface influenced the adsorption. Simultaneously, μ-Raman analysis had suggested that when exposed to more basic conditions, the resulting networks were enhanced with sc-SWNTs. To directly confirm this enhancement, Ti/Pd contacts were deposited and devices were tested in air. Key device characteristics were found to match the enhancement trends previously observed by spectroscopy. For the primary and secondary amines, on/off current ratios were commensurate with the Raman trends in metallic contribution, while no trends were observed on the tertiary amine (due to weaker interactions). Finally, differing SWNT solution volumes were used to compensate for adsorption differences and yielded identical SWNTnt densities on the various pH-treated samples to eliminate the influence of network density. These results further the understanding of the amine-SWNT interaction during the spin coating process. Overall, we provide a convenient route to provide SWNT-based TFTs with highly tunable electronic charge transport through better understanding of the influence of these specific interactions.

  20. Single-ended prediction of listening effort using deep neural networks.

    Science.gov (United States)

    Huber, Rainer; Krüger, Melanie; Meyer, Bernd T

    2018-03-01

    The effort required to listen to and understand noisy speech is an important factor in the evaluation of noise reduction schemes. This paper introduces a model for Listening Effort prediction from Acoustic Parameters (LEAP). The model is based on methods from automatic speech recognition, specifically on performance measures that quantify the degradation of phoneme posteriorgrams produced by a deep neural net: Noise or artifacts introduced by speech enhancement often result in a temporal smearing of phoneme representations, which is measured by comparison of phoneme vectors. This procedure does not require a priori knowledge about the processed speech, and is therefore single-ended. The proposed model was evaluated using three datasets of noisy speech signals with listening effort ratings obtained from normal hearing and hearing impaired subjects. The prediction quality was compared to several baseline models such as the ITU-T standard P.563 for single-ended speech quality assessment, the American National Standard ANIQUE+ for single-ended speech quality assessment, and a single-ended SNR estimator. In all three datasets, the proposed new model achieved clearly better prediction accuracies than the baseline models; correlations with subjective ratings were above 0.9. So far, the model is trained on the specific noise types used in the evaluation. Future work will be concerned with overcoming this limitation by training the model on a variety of different noise types in a multi-condition way in order to make it generalize to unknown noise types. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. Single- and dual-carrier microwave noise abatement in the deep space network. [microwave antennas

    Science.gov (United States)

    Bathker, D. A.; Brown, D. W.; Petty, S. M.

    1975-01-01

    The NASA/JPL Deep Space Network (DSN) microwave ground antenna systems are presented which simultaneously uplink very high power S-band signals while receiving very low level S- and X-band downlinks. Tertiary mechanisms associated with elements give rise to self-interference in the forms of broadband noise burst and coherent intermodulation products. A long-term program to reduce or eliminate both forms of interference is described in detail. Two DSN antennas were subjected to extensive interference testing and practical cleanup program; the initial performance, modification details, and final performance achieved at several planned stages are discussed. Test equipment and field procedures found useful in locating interference sources are discussed. Practices deemed necessary for interference-free operations in the DSN are described. Much of the specific information given is expected to be easily generalized for application in a variety of similar installations. Recommendations for future investigations and individual element design are given.

  2. Investigating single-word syntactic primes in naming tasks: a recurrent network approach.

    Science.gov (United States)

    Farrar, W T

    1998-04-01

    Three experiments compared the qualitative pattern of participants' word-naming performance in a syntactic priming task with the qualitative pattern of performance generated by a recurrent network model. Experiments 1 and 2 demonstrated that when participants had a 600-ms response deadline, the appropriateness of a syntactic prime affected their naming times for high-frequency words but not low-frequency words. However, Experiment 2 also demonstrated that participants made the most pronunciation errors when naming inconsistent low-frequency words (e.g., pint) that were preceded by an inappropriate prime. The results of Experiment 3 suggest that participants' naming times to both high- and low-frequency words are affected by syntactic primes when there is no response deadline. The implication of these findings for the study of syntactic priming in English and other languages is discussed.

  3. Visualization of single-wall carbon nanotube (SWNT) networks in conductive polystyrene nanocomposites by charge contrast imaging

    International Nuclear Information System (INIS)

    Loos, Joachim; Alexeev, Alexander; Grossiord, Nadia; Koning, Cor E.; Regev, Oren

    2005-01-01

    The morphology of conductive nanocomposites consisting of low concentration of single-wall carbon nanotubes (SWNT) and polystyrene (PS) has been studied using atomic force microscopy (AFM), transmission electron microscopy (TEM) and, in particular, scanning electron microscopy (SEM). Application of charge contrast imaging in SEM allows visualization of the overall SWNT dispersion within the polymer matrix as well as the identification of individual or bundled SWNTs at high resolution. The contrast mechanism involved will be discussed. In conductive nanocomposites the SWNTs are homogeneously dispersed within the polymer matrix and form a network. Beside fairly straight SWNTs, strongly bended SWNTs have been observed. However, for samples with SWNT concentrations below the percolation threshold, the common overall charging behavior of an insulating material is observed preventing the detailed morphological investigation of the sample

  4. Mixed-scale channel networks including Kingfisher-beak-shaped 3D microfunnels for efficient single particle entrapment

    Science.gov (United States)

    Lee, Yunjeong; Lim, Yeongjin; Shin, Heungjoo

    2016-06-01

    Reproducible research results for nanofluidics and their applications require viable fabrication technologies to produce nanochannels integrated with microchannels that can guide fluid flow and analytes into/out of the nanochannels. We present the simple fabrication of mixed-scale polydimethylsiloxane (PDMS) channel networks consisting of nanochannels and microchannels via a single molding process using a monolithic mixed-scale carbon mold. The monolithic carbon mold is fabricated by pyrolyzing a polymer mold patterned by photolithography. During pyrolysis, the polymer mold shrinks by ~90%, which enables nanosized carbon molds to be produced without a complex nanofabrication process. Because of the good adhesion between the polymer mold and the Si substrate, non-uniform volume reduction occurs during pyrolysis resulting in the formation of curved carbon mold side walls. These curved side walls and the relatively low surface energy of the mold provide efficient demolding of the PDMS channel networks. In addition, the trigonal prismatic shape of the polymer is converted into to a Kingfisher-beak-shaped carbon structure due to the non-uniform volume reduction. The transformation of this mold architecture produces a PDMS Kingfisher-beak-shaped 3D microfunnel that connects the microchannel and the nanochannel smoothly. The smooth reduction in the cross-sectional area of the 3D microfunnels enables efficient single microparticle trapping at the nanochannel entrance; this is beneficial for studies of cell transfection.Reproducible research results for nanofluidics and their applications require viable fabrication technologies to produce nanochannels integrated with microchannels that can guide fluid flow and analytes into/out of the nanochannels. We present the simple fabrication of mixed-scale polydimethylsiloxane (PDMS) channel networks consisting of nanochannels and microchannels via a single molding process using a monolithic mixed-scale carbon mold. The monolithic

  5. A network model to correlate conformational change and the impedance spectrum of single proteins

    Science.gov (United States)

    Alfinito, Eleonora; Pennetta, Cecilia; Reggiani, Lino

    2008-02-01

    Integrated nanodevices based on proteins or biomolecules are attracting increasing interest in today's research. In fact, it has been shown that proteins such as azurin and bacteriorhodopsin manifest some electrical properties that are promising for the development of active components of molecular electronic devices. Here we focus on two relevant kinds of protein: bovine rhodopsin, prototype of G-protein-coupled-receptor (GPCR) proteins, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer's disease. Both these proteins exert their function starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different impedance spectra associated with the different configurations. The distinct types of conformational change of rhodopsin and AChE agree with their dissimilar electrical responses. In particular, for rhodopsin the model predicts variations of the impedance spectra up to about 30%, while for AChE the same variations are limited to about 10%, which supports the existence of a dynamical equilibrium between its native and complexed states.

  6. Wrinkling instabilities in compressed networks of polymer supported single-wall carbon nanotubes

    Science.gov (United States)

    Harris, John; Iyer, Swathi; Huh, Ji Yeon; Fagan, Jeffrey A.; Chun, Jun Young; Hudson, Steven D.; Obrzut, Jan; Stafford, Christopher M.; Hobbie, Erik K.

    2011-03-01

    Strain-induced structural and electronic changes in polymer supported membranes of purified single-wall carbon nanotubes (SWCNTs) are evaluated through the wrinkling instabilities that develop under both uniaxial and isotropic compression. Nanotubes that have been purified by length or electronic type using density-gradient ultracentrifugation are assembled as surfactant-free thin membranes on prestrained polydimethylsiloxane (PDMS) substrates, and the strain response is measured using a broad range of techniques. The small-strain behavior is inferred from kinetic changes in the wrinkling topography of the SWCNT membranes during the slow drying of pre-swelled polymer supports. The measurements suggest a remarkable degree of strain softening that strongly couples to the anisotropic sheet resistance of the films, which we in turn relate to the microscale anisotropy that develops through excluded volume interactions. Supported by the NSF through CMMI-0969155 and the DOE through DE-FG36-08GO88160.

  7. Treatment Recommendations for Single-Unit Crowns: Findings from The National Dental Practice-Based Research Network

    Science.gov (United States)

    McCracken, Michael S.; Louis, David R.; Litaker, Mark S.; Minyé, Helena M.; Mungia, Rahma; Gordan, Valeria V.; Marshall, Don G.; Gilbert, Gregg H.

    2016-01-01

    Background Objectives were to: (1) quantify practitioner variation in likelihood to recommend a crown; and (2) test whether certain dentist, practice, and clinical factors are significantly associated with this likelihood. Methods Dentists in the National Dental Practice-Based Research Network completed a questionnaire about indications for single-unit crowns. In four clinical scenarios, practitioners ranked their likelihood of recommending a single-unit crown. These responses were used to calculate a dentist-specific “Crown Factor” (CF; range 0–12). A higher score implies a higher likelihood to recommend a crown. Certain characteristics were tested for statistically significant associations with the CF. Results 1,777 of 2,132 eligible dentists responded (83%). Practitioners were most likely to recommend crowns for teeth that were fractured, cracked, endodontically-treated, or had a broken restoration. Practitioners overwhelmingly recommended crowns for posterior teeth treated endodontically (94%). Practice owners, Southwest practitioners, and practitioners with a balanced work load were more likely to recommend crowns, as were practitioners who use optical scanners for digital impressions. Conclusions There is substantial variation in the likelihood of recommending a crown. While consensus exists in some areas (posterior endodontic treatment), variation dominates in others (size of an existing restoration). Recommendations varied by type of practice, network region, practice busyness, patient insurance status, and use of optical scanners. Practical Implications Recommendations for crowns may be influenced by factors unrelated to tooth and patient variables. A concern for tooth fracture -- whether from endodontic treatment, fractured teeth, or large restorations -- prompted many clinicians to recommend crowns. PMID:27492046

  8. Task-dependent changes in cross-level coupling between single neurons and oscillatory activity in multiscale networks.

    Directory of Open Access Journals (Sweden)

    Ryan T Canolty

    Full Text Available Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC or under direct neural control through a brain-machine interface (Brain Control, BC. In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10-45 Hz during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to

  9. Treatment recommendations for single-unit crowns: Findings from The National Dental Practice-Based Research Network.

    Science.gov (United States)

    McCracken, Michael S; Louis, David R; Litaker, Mark S; Minyé, Helena M; Mungia, Rahma; Gordan, Valeria V; Marshall, Don G; Gilbert, Gregg H

    2016-11-01

    The objectives of this study were to quantify practitioner variation in likelihood to recommend a crown and test whether certain dentist, practice, and clinical factors are associated significantly with this likelihood. Dentists in The National Dental Practice-Based Research Network completed a questionnaire about indications for single-unit crowns. In 4 clinical scenarios, practitioners ranked their likelihood of recommending a single-unit crown. The authors used these responses to calculate a dentist-specific crown factor (range, 0-12). A higher score implied a higher likelihood of recommending a crown. The authors tested certain characteristics for statistically significant associations with the crown factor. A total of 1,777 of 2,132 eligible dentists (83%) responded. Practitioners were most likely to recommend crowns for teeth that were fractured, cracked, or endodontically treated or had a broken restoration. Practitioners overwhelmingly recommended crowns for posterior teeth treated endodontically (94%). Practice owners, practitioners in the Southwest, and practitioners with a balanced workload were more likely to recommend crowns, as were practitioners who used optical scanners for digital impressions. There is substantial variation in the likelihood of recommending a crown. Although consensus exists in some areas (posterior endodontic treatment), variation dominates in others (size of an existing restoration). Recommendations varied according to type of practice, network region, practice busyness, patient insurance status, and use of optical scanners. Recommendations for crowns may be influenced by factors unrelated to tooth and patient variables. A concern for tooth fracture-whether from endodontic treatment, fractured teeth, or large restorations-prompted many clinicians to recommend crowns. Copyright © 2016 American Dental Association. Published by Elsevier Inc. All rights reserved.

  10. Integrated genome-wide association, coexpression network, and expression single nucleotide polymorphism analysis identifies novel pathway in allergic rhinitis

    Science.gov (United States)

    2014-01-01

    Background Allergic rhinitis is a common disease whose genetic basis is incompletely explained. We report an integrated genomic analysis of allergic rhinitis. Methods We performed genome wide association studies (GWAS) of allergic rhinitis in 5633 ethnically diverse North American subjects. Next, we profiled gene expression in disease-relevant tissue (peripheral blood CD4+ lymphocytes) collected from subjects who had been genotyped. We then integrated the GWAS and gene expression data using expression single nucleotide (eSNP), coexpression network, and pathway approaches to identify the biologic relevance of our GWAS. Results GWAS revealed ethnicity-specific findings, with 4 genome-wide significant loci among Latinos and 1 genome-wide significant locus in the GWAS meta-analysis across ethnic groups. To identify biologic context for these results, we constructed a coexpression network to define modules of genes with similar patterns of CD4+ gene expression (coexpression modules) that could serve as constructs of broader gene expression. 6 of the 22 GWAS loci with P-value ≤ 1x10−6 tagged one particular coexpression module (4.0-fold enrichment, P-value 0.0029), and this module also had the greatest enrichment (3.4-fold enrichment, P-value 2.6 × 10−24) for allergic rhinitis-associated eSNPs (genetic variants associated with both gene expression and allergic rhinitis). The integrated GWAS, coexpression network, and eSNP results therefore supported this coexpression module as an allergic rhinitis module. Pathway analysis revealed that the module was enriched for mitochondrial pathways (8.6-fold enrichment, P-value 4.5 × 10−72). Conclusions Our results highlight mitochondrial pathways as a target for further investigation of allergic rhinitis mechanism and treatment. Our integrated approach can be applied to provide biologic context for GWAS of other diseases. PMID:25085501

  11. Design architecture for multi-zone HVAC control systems from existing single-zone systems using wireless sensor networks

    Science.gov (United States)

    Redfern, Andrew; Koplow, Michael; Wright, Paul

    2007-01-01

    Most residential heating, ventilating, and air-conditioning (HVAC) systems utilize a single zone for conditioning air throughout the entire house. While inexpensive, these systems lead to wide temperature distributions and inefficient cooling due to the difference in thermal loads in different rooms. The end result is additional cost to the end user because the house is over conditioned. To reduce the total amount of energy used in a home and to increase occupant comfort there is a need for a better control system using multiple temperature zones. Typical multi-zone systems are costly and require extensive infrastructure to function. Recent advances in wireless sensor networks (WSNs) have enabled a low cost drop-in wireless vent register control system. The register control system is controlled by a master controller unit, which collects sensor data from a distributed wireless sensor network. Each sensor node samples local settings (occupancy, light, humidity and temperature) and reports the data back to the master control unit. The master control unit compiles the incoming data and then actuates the vent resisters to control the airflow throughout the house. The control system also utilizes a smart thermostat with a movable set point to enable the user to define their given comfort levels. The new system can reduce the run time of the HVAC system and thus decreasing the amount of energy used and increasing the comfort of the home occupations.

  12. Design and Implementation of an Enhanced 802.11 MAC Architecture for Single-Hop Wireless Networks

    Directory of Open Access Journals (Sweden)

    Ralph Bernasconi

    2007-01-01

    Full Text Available Due to its extreme simplicity and flexibility, the IEEE 802.11 standard is the dominant technology to implement both infrastructure-based WLANs and single-hop ad hoc networks. In spite of its popularity, there is a vast literature demonstrating the shortcomings of using the 802.11 technology in such environments, such as dramatic degradation of network capacity as contention increases and vulnerability to external interferences. Therefore, the design of enhancements and optimizations for the original 802.11 MAC protocol has been a very active research area in the last years. However, all these modifications to the 802.11 MAC protocol were validated only through simulations and/or analytical investigations. In this paper, we present a very unique work as we have designed a flexible hardware/software platform, fully compatible with current implementations of the IEEE 802.11 technology, which we have used to concretely implement and test an enhanced 802.11 backoff algorithm. Our experimental results clearly show that the enhanced mechanism outperforms the standard 802.11 MAC protocol in real scenarios.

  13. Dually cross-linked single network poly(acrylic acid) hydrogels with superior mechanical properties and water absorbency.

    Science.gov (United States)

    Zhong, Ming; Liu, Yi-Tao; Liu, Xiao-Ying; Shi, Fu-Kuan; Zhang, Li-Qin; Zhu, Mei-Fang; Xie, Xu-Ming

    2016-06-28

    Poly(acrylic acid) (PAA) hydrogels with superior mechanical properties, based on a single network structure with dual cross-linking, are prepared by one-pot free radical polymerization. The network structure of the PAA hydrogels is composed of dual cross-linking: a dynamic and reversible ionic cross-linking among the PAA chains enabled by Fe(3+) ions, and a sparse covalent cross-linking enabled by a covalent cross-linker (Bis). Under deformation, the covalently cross-linked PAA chains remain intact to maintain their original configuration, while the Fe(3+)-enabled ionic cross-linking among the PAA chains is broken to dissipate energy and then recombined. It is found that the mechanical properties of the PAA hydrogels are significantly influenced by the contents of covalent cross-linkers, Fe(3+) ions and water, which can be adjusted within a substantial range and thus broaden the applications of the hydrogels. Meanwhile, the PAA hydrogels have excellent recoverability based on the dynamic and reversible ionic cross-linking enabled by Fe(3+) ions. Moreover, the swelling capacity of the PAA hydrogels is as high as 1800 times in deionized water due to the synergistic effects of ionic and covalent cross-linkings. The combination of balanced mechanical properties, efficient recoverability, high swelling capacity and facile preparation provides a new method to obtain high-performance hydrogels.

  14. Breadth-First Search-Based Single-Phase Algorithms for Bridge Detection in Wireless Sensor Networks

    Science.gov (United States)

    Akram, Vahid Khalilpour; Dagdeviren, Orhan

    2013-01-01

    Wireless sensor networks (WSNs) are promising technologies for exploring harsh environments, such as oceans, wild forests, volcanic regions and outer space. Since sensor nodes may have limited transmission range, application packets may be transmitted by multi-hop communication. Thus, connectivity is a very important issue. A bridge is a critical edge whose removal breaks the connectivity of the network. Hence, it is crucial to detect bridges and take preventions. Since sensor nodes are battery-powered, services running on nodes should consume low energy. In this paper, we propose energy-efficient and distributed bridge detection algorithms for WSNs. Our algorithms run single phase and they are integrated with the Breadth-First Search (BFS) algorithm, which is a popular routing algorithm. Our first algorithm is an extended version of Milic's algorithm, which is designed to reduce the message length. Our second algorithm is novel and uses ancestral knowledge to detect bridges. We explain the operation of the algorithms, analyze their proof of correctness, message, time, space and computational complexities. To evaluate practical importance, we provide testbed experiments and extensive simulations. We show that our proposed algorithms provide less resource consumption, and the energy savings of our algorithms are up by 5.5-times. PMID:23845930

  15. A Simple Network to Remove Interference in Surface EMG Signal from Single Gene Affected Phenylketonuria Patients for Proper Diagnosis

    Science.gov (United States)

    Mohanty, Madhusmita; Basu, Mousumi; Pattanayak, Deba Narayan; Mohapatra, Sumant Kumar

    2018-04-01

    Recently Autosomal Recessive Single Gene (ARSG) diseases are highly effective to the children within the age of 5-10 years. One of the most ARSG disease is a Phenylketonuria (PKU). This single gene disease is associated with mutations in the gene that encodes the enzyme phenylalanine hydroxylase (PAH, Gene 612349). Through this mutation process, PAH of the gene affected patient can not properly manufacture PAH as a result the patients suffer from decreased muscle tone which shows abnormality in EMG signal. Here the extraction of the quality of the PKU affected EMG (PKU-EMG) signal is a keen interest, so it is highly necessary to remove the added ECG signal as well as the biological and instrumental noises. In the Present paper we proposed a method for detection and classification of the PKU affected EMG signal. Here Discrete Wavelet Transformation is implemented for extraction of the features of the PKU affected EMG signal. Adaptive Neuro-Fuzzy Inference System (ANFIS) network is used for the classification of the signal. Modified Particle Swarm Optimization (MPSO) and Modified Genetic Algorithm (MGA) are used to train the ANFIS network. Simulation result shows that the proposed method gives better performance as compared to existing approaches. Also it gives better accuracy of 98.02% for the detection of PKU-EMG signal. The advantages of the proposed model is to use MGA and MPSO to train the parameters of ANFIS network for classification of ECG and EMG signal of PKU affected patients. The proposed method obtained the high SNR (18.13 ± 0.36 dB), SNR (0.52 ± 1.62 dB), RE (0.02 ± 0.32), MSE (0.64 ± 2.01), CC (0.99 ± 0.02), RMSE (0.75 ± 0.35) and MFRE (0.01 ± 0.02), RMSE (0.75 ± 0.35) and MFRE (0.01 ± 0.02). From authors knowledge, this is the first time a composite method is used for diagnosis of PKU affected patients. The accuracy (98.02%), sensitivity (100%) and specificity (98.59%) helps for proper clinical treatment. It can help for readers

  16. A Simple Network to Remove Interference in Surface EMG Signal from Single Gene Affected Phenylketonuria Patients for Proper Diagnosis

    Science.gov (United States)

    Mohanty, Madhusmita; Basu, Mousumi; Pattanayak, Deba Narayan; Mohapatra, Sumant Kumar

    2018-01-01

    Recently Autosomal Recessive Single Gene (ARSG) diseases are highly effective to the children within the age of 5-10 years. One of the most ARSG disease is a Phenylketonuria (PKU). This single gene disease is associated with mutations in the gene that encodes the enzyme phenylalanine hydroxylase (PAH, Gene 612349). Through this mutation process, PAH of the gene affected patient can not properly manufacture PAH as a result the patients suffer from decreased muscle tone which shows abnormality in EMG signal. Here the extraction of the quality of the PKU affected EMG (PKU-EMG) signal is a keen interest, so it is highly necessary to remove the added ECG signal as well as the biological and instrumental noises. In the Present paper we proposed a method for detection and classification of the PKU affected EMG signal. Here Discrete Wavelet Transformation is implemented for extraction of the features of the PKU affected EMG signal. Adaptive Neuro-Fuzzy Inference System (ANFIS) network is used for the classification of the signal. Modified Particle Swarm Optimization (MPSO) and Modified Genetic Algorithm (MGA) are used to train the ANFIS network. Simulation result shows that the proposed method gives better performance as compared to existing approaches. Also it gives better accuracy of 98.02% for the detection of PKU-EMG signal. The advantages of the proposed model is to use MGA and MPSO to train the parameters of ANFIS network for classification of ECG and EMG signal of PKU affected patients. The proposed method obtained the high SNR (18.13 ± 0.36 dB), SNR (0.52 ± 1.62 dB), RE (0.02 ± 0.32), MSE (0.64 ± 2.01), CC (0.99 ± 0.02), RMSE (0.75 ± 0.35) and MFRE (0.01 ± 0.02), RMSE (0.75 ± 0.35) and MFRE (0.01 ± 0.02). From authors knowledge, this is the first time a composite method is used for diagnosis of PKU affected patients. The accuracy (98.02%), sensitivity (100%) and specificity (98.59%) helps for proper clinical treatment. It can help for readers

  17. Network type sp3 boron-based single-ion conducting polymer electrolytes for lithium ion batteries

    Science.gov (United States)

    Deng, Kuirong; Wang, Shuanjin; Ren, Shan; Han, Dongmei; Xiao, Min; Meng, Yuezhong

    2017-08-01

    Electrolytes play a vital role in modulating lithium ion battery performance. An outstanding electrolyte should possess both high ionic conductivity and unity lithium ion transference number. Here, we present a facile method to fabricate a network type sp3 boron-based single-ion conducting polymer electrolyte (SIPE) with high ionic conductivity and lithium ion transference number approaching unity. The SIPE was synthesized by coupling of lithium bis(allylmalonato)borate (LiBAMB) and pentaerythritol tetrakis(2-mercaptoacetate) (PETMP) via one-step photoinitiated in situ thiol-ene click reaction in plasticizers. Influence of kinds and content of plasticizers was investigated and the optimized electrolytes show both outstanding ionic conductivity (1.47 × 10-3 S cm-1 at 25 °C) and high lithium transference number of 0.89. This ionic conductivity is among the highest ionic conductivity exhibited by SIPEs reported to date. Its electrochemical stability window is up to 5.2 V. More importantly, Li/LiFePO4 cells with the prepared single-ion conducting electrolytes as the electrolyte as well as the separator display highly reversible capacity and excellent rate capacity under room temperature. It also demonstrates excellent long-term stability and reliability as it maintains capacity of 124 mA h g-1 at 1 C rate even after 500 cycles without obvious decay.

  18. Simple Adaptive Single Differential Coherence Detection of BPSK Signals in IEEE 802.15.4 Wireless Sensor Networks.

    Science.gov (United States)

    Zhang, Gaoyuan; Wen, Hong; Wang, Longye; Xie, Ping; Song, Liang; Tang, Jie; Liao, Runfa

    2017-12-26

    In this paper, we propose an adaptive single differential coherent detection (SDCD) scheme for the binary phase shift keying (BPSK) signals in IEEE 802.15.4 Wireless Sensor Networks (WSNs). In particular, the residual carrier frequency offset effect (CFOE) for differential detection is adaptively estimated, with only linear operation, according to the changing channel conditions. It was found that the carrier frequency offset (CFO) and chip signal-to-noise ratio (SNR) conditions do not need a priori knowledge. This partly benefits from that the combination of the trigonometric approximation sin - 1 ( x ) ≈ x and a useful assumption, namely, the asymptotic or high chip SNR, is considered for simplification of the full estimation scheme. Simulation results demonstrate that the proposed algorithm can achieve an accurate estimation and the detection performance can completely meet the requirement of the IEEE 802.15.4 standard, although with a little loss of reliability and robustness as compared with the conventional optimal single-symbol detector.

  19. Exploiting a Reference Genome in Terms of Duplications: The Network of Paralogs and Single Copy Genes in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Mara Sangiovanni

    2013-12-01

    Full Text Available Arabidopsis thaliana became the model organism for plant studies because of its small diploid genome, rapid lifecycle and short adult size. Its genome was the first among plants to be sequenced, becoming the reference in plant genomics. However, the Arabidopsis genome is characterized by an inherently complex organization, since it has undergone ancient whole genome duplications, followed by gene reduction, diploidization events and extended rearrangements, which relocated and split up the retained portions. These events, together with probable chromosome reductions, dramatically increased the genome complexity, limiting its role as a reference. The identification of paralogs and single copy genes within a highly duplicated genome is a prerequisite to understand its organization and evolution and to improve its exploitation in comparative genomics. This is still controversial, even in the widely studied Arabidopsis genome. This is also due to the lack of a reference bioinformatics pipeline that could exhaustively identify paralogs and singleton genes. We describe here a complete computational strategy to detect both duplicated and single copy genes in a genome, discussing all the methodological issues that may strongly affect the results, their quality and their reliability. This approach was used to analyze the organization of Arabidopsis nuclear protein coding genes, and besides classifying computationally defined paralogs into networks and single copy genes into different classes, it unraveled further intriguing aspects concerning the genome annotation and the gene relationships in this reference plant species. Since our results may be useful for comparative genomics and genome functional analyses, we organized a dedicated web interface to make them accessible to the scientific community.

  20. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  1. Missed connections: A case study of the social networks of physics doctoral students in a single department

    Science.gov (United States)

    Knaub, Alexis Victoria

    Gender disparity is an issue among the many science, technology, engineering, and mathematics (STEM) fields. Although many previous studies examine gender issues in STEM as an aggregate discipline, there are unique issues to each of the fields that are considered STEM fields. Some fields, such as physics, have fewer women graduating with degrees than other fields. This suggests that women's experiences vary by STEM field. The majority of previous research also examines gender and other disparities at either the nationwide or individual level. This project entailed social network analysis through survey and interview data to examine a single physics department's doctoral students in order to provide a comprehensive look at student social experiences. In addition to examining gender, other demographic variables were studied to see if the results are truly associated with gender; these variables include race/ethnicity, year in program, student type, relationship status, research type, undergraduate institute, and subfield. Data were examined to determine if there are relationships to social connections and outcome variables such as persistence in completing the degree and the time to degree. Data collected on faculty were used to rank faculty members; data such as h-indices and number of students graduate over the past 5 years were collected. Fifty-five (55) of 110 possible participants completed the survey; forty-three are male, and twelve are female. Twenty-eight of the fifty-five survey participants were interview; twenty-three are male, and five are female. Findings for peer networks include that peer networks are established during the first year and do not change drastically as one progresses in the program. Geographic location within the campus affects socializing with peers. Connections to fellow students are not necessarily reciprocated; the maximum percentage of reciprocated connections is 60%. The number of connections one has varies by network purpose

  2. Tensions of network security and collaborative work practice: understanding a single sign-on deployment in a regional hospital.

    Science.gov (United States)

    Heckle, Rosa R; Lutters, Wayne G

    2011-08-01

    Healthcare providers and their IT staff, working in an effort to balance appropriate accessibility with stricter security mandates, are considering the use of a single network sign-on approach for authentication and password management. Single sign-on (SSO) promises to improve usability of authentication for multiple-system users, increase compliance, and help curb system maintenance costs. However, complexities are introduced when SSO is placed within a collaborative environment. These complexities include unanticipated workflow implications that introduce greater security vulnerability for the individual user. OBJECTIVES AND METHODOLOGY: In this work, we examine the challenges of implementing a single sign-on authentication technology in a hospital environment. The aim of the study was to document the factors that affected SSO adoption within the context of use. The ultimate goal is to better inform the design of usable authentication systems within collaborative healthcare work sites. The primary data collection techniques used are ethnographically informed - observation, contextual interviews, and document review. The study included a cross-section of individuals from various departments and varying rolls. These participants were a mix of both clinical and administrative staff, as well as the Information Technology group. The field work revealed fundamental mis-matches between the technology and routine work practices that will significantly impact its effective adoption. While single sign-on was effective in the administrative offices, SSO was not a good fit for collaborative areas. The collaborative needs of the clinical staff unearthed tensions in its implementation. An analysis of the findings revealed that the workflow, activities, and physical environment of the clinical areas create increased security vulnerabilities for the individual user. The clinical users were cognizant of these vulnerabilities and this created resistance to the implementation due

  3. Pt nanoparticle modified single walled carbon nanotube network electrodes for electrocatalysis: control of the specific surface area over three orders of magnitude

    NARCIS (Netherlands)

    Miller, T.S.; Sansuk, S.; Lai, Stanley; Macpherson, J.V.; Unwin, P.R.

    2015-01-01

    The electrodeposition of Pt nanoparticles (NPs) on two-dimensional single walled carbon nanotube (SWNT) network electrodes is investigated as a means of tailoring electrode surfaces with a well-defined amount of electrocatalytic material. Both Pt NP deposition and electrocatalytic studies are

  4. Retrofitting of heat exchanger networks involving streams with variable heat capacity: Application of single and multi-objective optimization

    International Nuclear Information System (INIS)

    Sreepathi, Bhargava Krishna; Rangaiah, G.P.

    2015-01-01

    Heat exchanger network (HEN) retrofitting improves the energy efficiency of the current process by reducing external utilities. In this work, HEN retrofitting involving streams having variable heat capacity is studied. For this, enthalpy values of a stream are fitted to a continuous cubic polynomial instead of a stepwise approach employed in the previous studies [1,2]. The former methodology is closer to reality as enthalpy or heat capacity changes gradually instead of step changes. Using the polynomial fitting formulation, single objective optimization (SOO) and multi-objective optimization (MOO) of a HEN retrofit problem are investigated. The results obtained show an improvement in the utility savings, and MOO provides many Pareto-optimal solutions to choose from. Also, Pareto-optimal solutions involving area addition in existing heat exchangers only (but no new exchangers and no structural modifications) are found and provided for comparison with those involving new exchangers and structural modifications as well. - Highlights: • HEN retrofitting involving streams with variable heat capacities is studied. • A continuous approach to handle variable heat capacity is proposed and tested. • Better and practical solutions are obtained for HEN retrofitting in process plants. • Pareto-optimal solutions provide many alternate choices for HEN retrofitting

  5. Single-molecule kinetic analysis of HP1-chromatin binding reveals a dynamic network of histone modification and DNA interactions.

    Science.gov (United States)

    Bryan, Louise C; Weilandt, Daniel R; Bachmann, Andreas L; Kilic, Sinan; Lechner, Carolin C; Odermatt, Pascal D; Fantner, Georg E; Georgeon, Sandrine; Hantschel, Oliver; Hatzimanikatis, Vassily; Fierz, Beat

    2017-10-13

    Chromatin recruitment of effector proteins involved in gene regulation depends on multivalent interaction with histone post-translational modifications (PTMs) and structural features of the chromatin fiber. Due to the complex interactions involved, it is currently not understood how effectors dynamically sample the chromatin landscape. Here, we dissect the dynamic chromatin interactions of a family of multivalent effectors, heterochromatin protein 1 (HP1) proteins, using single-molecule fluorescence imaging and computational modeling. We show that the three human HP1 isoforms are recruited and retained on chromatin by a dynamic exchange between histone PTM and DNA bound states. These interactions depend on local chromatin structure, the HP1 isoforms as well as on PTMs on HP1 itself. Of the HP1 isoforms, HP1α exhibits the longest residence times and fastest binding rates due to DNA interactions in addition to PTM binding. HP1α phosphorylation further increases chromatin retention through strengthening of multivalency while reducing DNA binding. As DNA binding in combination with specific PTM recognition is found in many chromatin effectors, we propose a general dynamic capture mechanism for effector recruitment. Multiple weak protein and DNA interactions result in a multivalent interaction network that targets effectors to a specific chromatin modification state, where their activity is required. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network

    Directory of Open Access Journals (Sweden)

    Trong-Ngoc Le

    2016-01-01

    Full Text Available Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN, which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the “ground truth.” Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively.

  7. Single neural adaptive controller and neural network identifier based on PSO algorithm for spherical actuators with 3D magnet array

    Science.gov (United States)

    Yan, Liang; Zhang, Lu; Zhu, Bo; Zhang, Jingying; Jiao, Zongxia

    2017-10-01

    Permanent magnet spherical actuator (PMSA) is a multi-variable featured and inter-axis coupled nonlinear system, which unavoidably compromises its motion control implementation. Uncertainties such as external load and friction torque of ball bearing and manufacturing errors also influence motion performance significantly. Therefore, the objective of this paper is to propose a controller based on a single neural adaptive (SNA) algorithm and a neural network (NN) identifier optimized with a particle swarm optimization (PSO) algorithm to improve the motion stability of PMSA with three-dimensional magnet arrays. The dynamic model and computed torque model are formulated for the spherical actuator, and a dynamic decoupling control algorithm is developed. By utilizing the global-optimization property of the PSO algorithm, the NN identifier is trained to avoid locally optimal solution and achieve high-precision compensations to uncertainties. The employment of the SNA controller helps to reduce the effect of compensation errors and convert the system to a stable one, even if there is difference between the compensations and uncertainties due to external disturbances. A simulation model is established, and experiments are conducted on the research prototype to validate the proposed control algorithm. The amplitude of the parameter perturbation is set to 5%, 10%, and 15%, respectively. The strong robustness of the proposed hybrid algorithm is validated by the abundant simulation data. It shows that the proposed algorithm can effectively compensate the influence of uncertainties and eliminate the effect of inter-axis couplings of the spherical actuator.

  8. Effect of tetrahedral amorphous carbon coating on the resistivity and wear of single-walled carbon nanotube network

    Energy Technology Data Exchange (ETDEWEB)

    Iyer, Ajai, E-mail: ajai.iyer@aalto.fi; Etula, Jarkko; Liu, Xuwen; Koskinen, Jari [Department of Materials Science and Engineering, School of Chemical Technology, Aalto University, P.O. Box 16200, 00076 Espoo (Finland); Kaskela, Antti; Kauppinen, Esko I. [NanoMaterials Group, Department of Applied Physics, School of Science, Aalto University, P.O. Box 15100, 00076 Espoo (Finland); Novikov, Serguei [Department of Micro and Nanosciences, Aalto University, P.O. Box 13500, 00076 Aalto (Finland)

    2016-05-14

    Single walled carbon nanotube networks (SWCNTNs) were coated by tetrahedral amorphous carbon (ta-C) to improve the mechanical wear properties of the composite film. The ta-C deposition was performed by using pulsed filtered cathodic vacuum arc method resulting in the generation of C+ ions in the energy range of 40–60 eV which coalesce to form a ta-C film. The primary disadvantage of this process is a significant increase in the electrical resistance of the SWCNTN post coating. The increase in the SWCNTN resistance is attributed primarily to the intrinsic stress of the ta-C coating which affects the inter-bundle junction resistance between the SWCNTN bundles. E-beam evaporated carbon was deposited on the SWCNTNs prior to the ta-C deposition in order to protect the SWCNTN from the intrinsic stress of the ta-C film. The causes of changes in electrical resistance and the effect of evaporated carbon thickness on the changes in electrical resistance and mechanical wear properties have been studied.

  9. Detecting shifts in gene regulatory networks during time-course experiments at single-time-point temporal resolution.

    Science.gov (United States)

    Takenaka, Yoichi; Seno, Shigeto; Matsuda, Hideo

    2015-10-01

    Comprehensively understanding the dynamics of biological systems is one of the greatest challenges in biology. Vastly improved biological technologies have provided vast amounts of information that must be understood by bioinformatics and systems biology researchers. Gene regulations have been frequently modeled by ordinary differential equations or graphical models based on time-course gene expression profiles. The state-of-the-art computational approaches for analyzing gene regulations assume that their models are same throughout time-course experiments. However, these approaches cannot easily analyze transient changes at a time point, such as diauxic shift. We propose a score that analyzes the gene regulations at each time point. The score is based on the information gains of information criterion values. The method detects the shifts in gene regulatory networks (GRNs) during time-course experiments with single-time-point resolution. The effectiveness of the method is evaluated on the diauxic shift from glucose to lactose in Escherichia coli. Gene regulation shifts were detected at two time points: the first corresponding to the time at which the growth of E. coli ceased and the second corresponding to the end of the experiment, when the nutrient sources (glucose and lactose) had become exhausted. According to these results, the proposed score and method can appropriately detect the time of gene regulation shifts. The method based on the proposed score provides a new tool for analyzing dynamic biological systems. Because the score value indicates the strength of gene regulation at each time point in a gene expression profile, it can potentially infer hidden GRNs from time-course experiments.

  10. Spiral-type heteropolyhedral coordination network based on single-crystal LiSrPO4: implications for luminescent materials.

    Science.gov (United States)

    Lin, Chun Che; Shen, Chin-Chang; Liu, Ru-Shi

    2013-11-04

    Novel structures of luminescent materials, which are used as light sources for next-generation illumination, are continuously being improved for use in white-light-emitting diodes. Activator-doped known structures are reported as habitual down-conversion phosphors in solid-state lightings and displays. Consequently, the intrinsic qualities of the existent compounds produce deficiencies that limit their applications. Herein we report a spiral-network single-crystal orthophosphate (LiSrPO4) prepared in a platinum crucible with LiCl flux through crystal-growth reactions of SrCl2 and Li3PO4 in air. It crystallizes in a hexagonal system with a=5.0040(2) and c=24.6320(16) Å, V=534.15(5) Å(3), and Z=6 in the space group P6(5). The unit cell is comprised of LiO4 and PO4 tetrahedrons that form a three-dimensional LiPO4(2-) anionic framework with a helical channel structure along the c axis in which the Sr(2+) cation is accommodated. The optical band gap of this composition is about 3.65 eV, as determined by using UV/Vis absorption and diffuse reflection spectra. We used the crystal-growth method to synthesize blue- and red-emitting crystals that exhibited pure color, low reabsorption, a large Stokes shift, and efficient conversion of ultraviolet excitation light into visible light. Emphasis was placed on the development of gratifying structure-related properties of rare-earth luminescent materials and their applications. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Study of Single Top Quark Production Using Bayesian Neural Networks With D0 Detector at the Tevatron

    Energy Technology Data Exchange (ETDEWEB)

    Joshi, Jyoti [Panjab Univ., Chandigarh (India)

    2012-01-01

    Top quark, the heaviest and most intriguing among the six known quarks, can be created via two independent production mechanisms in {\\pp} collisions. The primary mode, strong {\\ttbar} pair production from a $gtt$ vertex, was used by the {\\d0} and CDF collaborations to establish the existence of the top quark in March 1995. The second mode is the electroweak production of a single top quark or antiquark, which has been observed recently in March 2009. Since single top quarks are produced at hadron colliders through a $Wtb$ vertex, thereby provide a direct probe of the nature of $Wtb$ coupling and of the Cabibbo-Kobayashi-Maskawa matrix element, $V_{tb}$. So this mechanism provides a sensitive probe for several, standard model and beyond standard model, parameters such as anomalous $Wtb$ couplings. In this thesis, we measure the cross section of the electroweak produced top quark in three different production modes, $s+t$, $s$ and $t$-channels using a technique based on the Bayesian neural networks. This technique is applied for analysis of the 5.4 $fb^{-1}$ of data collected by the {\\d0} detector. From a comparison of the Bayesian neural networks discriminants between data and the signal-background model using Bayesian statistics, the cross sections of the top quark produced through the electroweak mechanism have been measured as: \\[\\sigma(p\\bar{p}→tb+X,tqb+X) = 3.11^{+0.77}_{-0.71}\\;\\rm pb\\] \\[\\sigma(p\\bar{p}→tb+X) = 0.72^{+0.44}_{-0.43}\\;\\rm pb\\] \\[\\sigma(p\\bar{p}→tqb+X) = 2.92^{+0.87}_{-0.73}\\;\\rm pb\\] % The $s+t$-channel has a gaussian significance of $4.7\\sigma$, the $s$-channel $0.9\\sigma$ and the $t$-channel~$4.7\\sigma$. The results are consistent with the standard model predictions within one standard deviation. By combining these results with the results for two other analyses (using different MVA techniques) improved results \\[\\sigma(p\\bar{p}→tb+X,tqb+X) = 3.43^{+0.73}_{-0.74}\\;\\rm pb\\] \\[\\sigma

  12. Neural network-based preprocessing to estimate the parameters of the X-ray emission of a single-temperature thermal plasma

    Science.gov (United States)

    Ichinohe, Y.; Yamada, S.; Miyazaki, N.; Saito, S.

    2018-04-01

    We present data preprocessing based on an artificial neural network to estimate the parameters of the X-ray emission spectra of a single-temperature thermal plasma. The method finds appropriate parameters close to the global optimum. The neural network is designed to learn the parameters of the thermal plasma (temperature, abundance, normalization and redshift) of the input spectra. After training using 9000 simulated X-ray spectra, the network has grown to predict all the unknown parameters with uncertainties of about a few per cent. The performance dependence on the network structure has been studied. We applied the neural network to an actual high-resolution spectrum obtained with Hitomi. The predicted plasma parameters agree with the known best-fitting parameters of the Perseus cluster within uncertainties of ≲10 per cent. The result shows that neural networks trained by simulated data might possibly be used to extract a feature built in the data. This would reduce human-intensive preprocessing costs before detailed spectral analysis, and would help us make the best use of the large quantities of spectral data that will be available in the coming decades.

  13. First demonstration of single-mode MCF transport network with crosstalk-aware in-service optical channel control

    DEFF Research Database (Denmark)

    Pulverer, K.; Tanaka, T.; Häbel, U.

    2017-01-01

    We demonstrate the first crosstalk-aware traffic engineering as a use case in a multicore fibre transport network. With the help of a software-defined network controller, modulation format and channel route are adaptively changed using programmable devices with XT monitors.......We demonstrate the first crosstalk-aware traffic engineering as a use case in a multicore fibre transport network. With the help of a software-defined network controller, modulation format and channel route are adaptively changed using programmable devices with XT monitors....

  14. Challenges to Participation in the Sharing Economy: The Case of Local Online Peer-to-Peer Exchange in a Single Parents’ Network

    Directory of Open Access Journals (Sweden)

    Airi Lampinen

    2015-05-01

    Full Text Available This paper depicts an initiative to deploy an online peer-to-peer exchange system for a community network of single parents – a group of people in need of goods, services, and social support in their local neighborhoods. We apply participant observation and semi-structured interviews to uncover key issues that can hinder the emergence of sharing practices in local community networks of this type. Our study illustrates how pressures related to single parenthood can impede opportunities to engage in peer-to-peer exchange, even when community members view the social and material benefits of participation as desirable and necessary. This complicates the prevalent narrative that local peer-to-peer exchange systems are an accessible and convenient alternative to traditional markets. Moreover, we discuss our collaboration with the community as well as the developers of the sharing platform, highlighting the challenges of user-centered design in the sharing economy.

  15. The influence of single neuron dynamics and network topology on time delay-induced multiple synchronous behaviors in inhibitory coupled network

    International Nuclear Information System (INIS)

    Zhao, Zhiguo; Gu, Huaguang

    2015-01-01

    Highlights: • Time delay-induced multiple synchronous behaviors was simulated in neuronal networks. • Multiple behaviors appear at time delays shorter than a bursting period of neurons. • The more spikes per burst of bursting, the more synchronous regions of time delay. • From regular to random via small-world networks, synchronous degree becomes weak. • An interpretation of the multiple behaviors and the influence of network are provided. - Abstract: Time delay induced-multiple synchronous behaviors are simulated in neuronal network composed of many inhibitory neurons and appear at different time delays shorter than a period of endogenous bursting of individual neurons. It is different from previous investigations wherein only one of multiple synchronous behaviors appears at time delay shorter than a period of endogenous firing and others appear at time delay longer than the period duration. The bursting patterns of the synchronous behaviors are identified based on the dynamics of an individual neuron stimulated by a signal similar to the inhibitory coupling current, which is applied at the decaying branch of a spike and suitable phase within the quiescent state of the endogenous bursting. If a burst of endogenous bursting contains more spikes, the synchronous behaviors appear at more regions of time delay. As the coupling strength increases, the multiple synchronous behaviors appear in a sequence because the different threshold of coupling current or strength is needed to achieve synchronous behaviors. From regular, to small-world, and to random networks, synchronous degree of the multiple synchronous behaviors becomes weak, and synchronous bursting patterns with lower spikes per burst disappear, which is properly interpreted by the difference of coupling current between neurons induced by different degree and the high threshold of coupling current to achieve synchronization for the absent synchronous bursting patterns. The results of the influence of

  16. Demonstration of Single-Mode Multicore Fiber Transport Network with Crosstalk-Aware In-Service Optical Path Control

    DEFF Research Database (Denmark)

    Tanaka, Takafumi; Pulverer, Klaus; Häbel, Ulrich

    2017-01-01

    transport network testbed and demonstrate an XT-aware traffic engineering scenario. With the help of a software-defined network (SDN) controller, the modulation format and optical path route are adaptively changed based on the monitored XT values by using programmable devices such as a real-time transponder...

  17. A mixed-methods approach for analysing social support and social anchorage of single mothers’ personal networks

    NARCIS (Netherlands)

    Lumino, Rosaria; Ragozini, Giancarlo; van Duijn, Marijtje; Vitale, Maria Prosperina

    2017-01-01

    The present paper analyses the relationship among social support and personal networks by focusing on social anchorage, which is a specific dimension of social support conveying to what extent people feel integrated into their personal networks. Specifying when, why, and how personal relationships

  18. First demonstration of single-mode MCF transport network with crosstalk-aware in-service optical channel control

    DEFF Research Database (Denmark)

    Pulverer, K.; Tanaka, T.; Häbel, U.

    2017-01-01

    We demonstrate the first crosstalk-aware traffic engineering as a use case in a multicore fibre transport network. With the help of a software-defined network controller, modulation format and channel route are adaptively changed using programmable devices with XT monitors....

  19. Self-Assembly of Single-Layer CoAl-Layered Double Hydroxide Nanosheets on 3D Graphene Network Used as Highly Efficient Electrocatalyst for Oxygen Evolution Reaction.

    Science.gov (United States)

    Ping, Jianfeng; Wang, Yixian; Lu, Qipeng; Chen, Bo; Chen, Junze; Huang, Ying; Ma, Qinglang; Tan, Chaoliang; Yang, Jian; Cao, Xiehong; Wang, Zhijuan; Wu, Jian; Ying, Yibin; Zhang, Hua

    2016-09-01

    A non-noble metal based 3D porous electrocatalyst is prepared by self-assembly of the liquid-exfoliated single-layer CoAl-layered double hydroxide nanosheets (CoAl-NSs) onto 3D graphene network, which exhibits higher catalytic activity and better stability for electrochemical oxygen evolution reaction compared to the commercial IrO2 nanoparticle-based 3D porous electrocatalyst. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. [Effects of blokade of the dopaminergic D1/D2 receptors on the single and network neuronal activity in the frontal and visual cortices and behavior of cats].

    Science.gov (United States)

    Kuleshova, E P; Zaleshin, A V; Sidorina, V V; Merzhanova, G Kh

    2010-01-01

    The results obtained at the levels of single and network neuronal activity in the frontal and visual cortices of cats with different types of behavior revealed features of activity of these structures in normal conditions and after local introductions of antagonists of DI/D2 receptors (SCH23390 and raclopride) into the n. accumbens and frontal cortex. Under the influence of the antagonists, long-latency reactions were characterized by a significant increase in the average frequency of neuronal activity in the frontal cortex, whereas in the visual cortex the average frequency decreased as compared to norm. At the same time, the network activity of the same neurons in the frontal cortex did not change but weakened in the visual cortex, which was expressed in a reduction of the number of neuronal interactions within the visual cortex and between the neurons of the frontal and visual cortices. Normally, during the long-latency conditioned reactions, the average frequency of single neuronal activity and the rate of neuronal interactions in the structures under study were significantly higher as compared to the loss of conditioned reactions. Administration of the dopamine antagonists did not change these features. The results suggest different dopamine modulations of the network activity of the cortical zones under study during the conditioned performance, which is expressed in responsiveness of the cortical projection of a trigger signal (the visual cortex) and visual-frontal networks generated in the course of training.

  1. Functional characterization of FLT3 receptor signaling deregulation in acute myeloid leukemia by single cell network profiling (SCNP.

    Directory of Open Access Journals (Sweden)

    David B Rosen

    Full Text Available BACKGROUND: Molecular characterization of the FMS-like tyrosine kinase 3 receptor (FLT3 in cytogenetically normal acute myeloid leukemia (AML has recently been incorporated into clinical guidelines based on correlations between FLT3 internal tandem duplications (FLT3-ITD and decreased disease-free and overall survival. These mutations result in constitutive activation of FLT3, and FLT3 inhibitors are currently undergoing trials in AML patients selected on FLT3 molecular status. However, the transient and partial responses observed suggest that FLT3 mutational status alone does not provide complete information on FLT3 biological activity at the individual patient level. Examination of variation in cellular responsiveness to signaling modulation may be more informative. METHODOLOGY/PRINCIPAL FINDINGS: Using single cell network profiling (SCNP, cells were treated with extracellular modulators and their functional responses were quantified by multiparametric flow cytometry. Intracellular signaling responses were compared between healthy bone marrow myeloblasts (BMMb and AML leukemic blasts characterized as FLT3 wild type (FLT3-WT or FLT3-ITD. Compared to healthy BMMb, FLT3-WT leukemic blasts demonstrated a wide range of signaling responses to FLT3 ligand (FLT3L, including elevated and sustained PI3K and Ras/Raf/Erk signaling. Distinct signaling and apoptosis profiles were observed in FLT3-WT and FLT3-ITD AML samples, with more uniform signaling observed in FLT3-ITD AML samples. Specifically, increased basal p-Stat5 levels, decreased FLT3L induced activation of the PI3K and Ras/Raf/Erk pathways, decreased IL-27 induced activation of the Jak/Stat pathway, and heightened apoptotic responses to agents inducing DNA damage were observed in FLT3-ITD AML samples. Preliminary analysis correlating these findings with clinical outcomes suggests that classification of patient samples based on signaling profiles may more accurately reflect FLT3 signaling

  2. Single- and two-phase flow simulation based on equivalent pore network extracted from micro-CT images of sandstone core.

    Science.gov (United States)

    Song, Rui; Liu, Jianjun; Cui, Mengmeng

    2016-01-01

    Due to the intricate structure of porous rocks, relationships between porosity or saturation and petrophysical transport properties classically used for reservoir evaluation and recovery strategies are either very complex or nonexistent. Thus, the pore network model extracted from the natural porous media is emphasized as a breakthrough to predict the fluid transport properties in the complex micro pore structure. This paper presents a modified method of extracting the equivalent pore network model from the three-dimensional micro computed tomography images based on the maximum ball algorithm. The partition of pore and throat are improved to avoid tremendous memory usage when extracting the equivalent pore network model. The porosity calculated by the extracted pore network model agrees well with the original sandstone sample. Instead of the Poiseuille's law used in the original work, the Lattice-Boltzmann method is employed to simulate the single- and two- phase flow in the extracted pore network. Good agreements are acquired on relative permeability saturation curves of the simulation against the experiment results.

  3. Carbonyl Functionalized Single-Walled Carbon Nanotube-Hb Crosslinked Network: A Novel Platform for Studying Bio-Electrochemistry and Electrocatalysis of Hemoglobin.

    Science.gov (United States)

    Kafi, A K M; Yam, C C L; Azmi, N S; Yusoff, Mashitah M

    2018-04-01

    In this work, the direct electrochemistry of hemoglobin (Hb), which was immobilized on carbonyl functionalized single walled carbon nanotube (SWCNT) and deposited onto a gold (Au) electrode has been described. The synthesis of the network of crosslinked SWCNT/Hb was done with the help of crosslinking agent EDC (1-ethyl-3-(3-dimethylaminopropyl) carbodiimide). The UV-Vis and FTIR spectroscopy of SWCNT/Hb networks showed that Hb maintained its natural structure and kept good stability. In addition with this, scanning electron microscopy (SEM) illustrated that SWCNT/Hb networks had a featured layered structure and Hb being strongly liked with SWCNT surface. Cyclic voltammetry (CV) was used to study and to optimize the performance of the resulting modified electrode. The cyclic voltammetric (CV) responses of SWCNT/Hb networks in pH 7.0 exhibit prominent redox couple for the FeIII/II redox process with a midpoint potential of -0.46 V and -0.34, cathodic and anodic respectively. Furthermore, SWCNT/Hb networks are utilized for the detection of hydrogen peroxide (H2O2). Electrochemical measurements reveal that the resulting SWCNT/Hb electrodes display high electrocatalytic activity to H2O2 with high sensitivity, wide linear range, and low detection limit. Overall, the electrochemical results are due to excellent biocompatibility and excellent electron transport efficiency of CNT as well as high Hb loading and synergistic catalytic effect of the modified electrode toward H2O2.

  4. Network-Behavior Dynamics in Bullying and Defending : A Multilevel Network Analysis of Single-Grade versus Multi-Grade Classes

    NARCIS (Netherlands)

    Rambaran, Johannes; McFarland, Daniel; Veenstra, David

    2017-01-01

    The social networks in which children participate in are strongly associated with their involvement in bullying and defending (Juvonen & Graham, 2014; Salmivalli, 2010). It is likely that peer effects – referring to selection and influence processes – explain this association. Children seek out

  5. Single-Molecule Fluorescence Microscopy Reveals Local Diffusion Coefficients in the Pore Network of an Individual Catalyst Particle

    NARCIS (Netherlands)

    Hendriks, Frank|info:eu-repo/dai/nl/412642697; Meirer, Florian; Kubarev, Alexey V.; Ristanovic, Zoran|info:eu-repo/dai/nl/328233005; Roeffaers, Maarten B J; Vogt, Eelco T. C.|info:eu-repo/dai/nl/073717398; Bruijnincx, Pieter C. A.|info:eu-repo/dai/nl/33799529X; Weckhuysen, Bert M.|info:eu-repo/dai/nl/285484397

    2017-01-01

    We used single-molecule fluorescence microscopy to study self-diffusion of a feedstock-like probe molecule with nanometer accuracy in the macropores of a micrometer-sized, real-life fluid catalytic cracking (FCC) particle. Movies of single fluorescent molecules allowed their movement through the

  6. EU COMPETITION LAW AND THE TELECOMS SINGLE MARKET: NETWORK NEUTRALITY IN THE AFTERMATH OF THE TSM REGULATION

    Directory of Open Access Journals (Sweden)

    Noemí ANGULO GARZARO

    2016-05-01

    Full Text Available Since the early 1990s, a sharp increase in the Internet traffic has been experienced. Technology, once again, has proven to be able to develop faster than regulation. In this endlessly evolving scenario, operators in the technology markets, as well as end-users, often find themselves under-protected. Therefore, it comes as a major concern the need to regulate those technological markets and, more specifically, the use –or abuse– of Internet. All Internet traffic should be treated equally and that is, precisely, what network neutrality aims at. Consequently, network operators may not take advantage of their position in the market to affect competition in related markets. All in all, network neutrality is crucial to achieve the highest degree of competition. In the absence of network neutrality, the Internet would find itself unable to qualify as a market merely driven by innovation, and it would unfailingly turn into one ruled by deal making. Competition law claims that the higher the neutrality is – i.e., the more equal the treatment is, the better it is for the consumer. If network operating companies create an exploitative business model, they might be able to block competitors’ websites and services; in other words, it may facilitate adoption of anticompetitive practices – namely, the abuse of their dominant position. Transcending all the arguments raised against network neutrality –such as the prevention of an overuse of bandwidth–, we will demonstrate that it must be deemed essential from a Competition law perspective. In addition, we will argue, the imperative necessity of leaving the market under the tough scrutiny of competition authorities, which are best placed to assess the anticompetitive character of the practices brought about by market operators.

  7. Study on desirable ionospheric corrections accuracy for network-RTK positioning and its impact on time-to-fix and probability of successful single-epoch ambiguity resolution

    Science.gov (United States)

    Paziewski, Jacek

    2016-02-01

    The mitigation of ionospheric delay is still of crucial interest in GNSS positioning, especially in precise solutions such as instantaneous RTK positioning. Thus, several effective algorithms and functional models were developed, and also numerous investigations of ionospheric correction properties in RTK positioning have been performed so far. One of the most highly effective approaches in precise relative positioning is the application of the ionosphere-weighted model with network-derived corrections. This contribution investigates the impact of the accuracy of the network ionospheric corrections on time-to-fix in RTK-OTF positioning. Also, an attempt has been made to estimate the desirable accuracy of the network ionospheric corrections, allowing for reliable instantaneous ambiguity resolution. The experiment is based on a multi-baseline GPS RTK positioning supported with network-derived ionospheric corrections for medium length baselines. The results show that in such scenario, the double-differenced ionospheric correction residuals should not exceed ∼1/3 of the L1 wavelength for successful single-epoch ambiguity resolution.

  8. Mesh-shape-and-size controlled rapid-melting growth for the formation of single-crystalline (100), (110), and (111) Ge networks on insulators

    International Nuclear Information System (INIS)

    Mizushima, Ichiro; Toko, Kaoru; Ohta, Yasuharu; Sakane, Takashi; Sadoh, Taizoh; Miyao, Masanobu

    2011-01-01

    Single-crystalline-Ge (c-Ge) networks with various crystal orientations on insulators formed on Si substrates are essential for integrating high-speed and multifunctional devices onto the Si platform. c-Ge networks are realized by rapid-melting growth of mesh-patterned amorphous-Ge over large areas (500x250 μm 2 ) on (110) and (111) as well as (100) Si substrates by optimizing the shape and the size of the mesh. It is revealed that latent-heat generated at the growth front can be controlled by selecting mesh-shape-and-size, which suppresses the spontaneous nucleation. In addition, essential role of the growth-direction on preventing the rotational growth is clarified.

  9. Single Layer Recurrent Neural Network for detection of swarm-like earthquakes in W-Bohemia/Vogtland - the method

    Czech Academy of Sciences Publication Activity Database

    Doubravová, Jana; Wiszniowski, J.; Horálek, Josef

    2016-01-01

    Roč. 93, August (2016), s. 138-149 ISSN 0098-3004 R&D Projects: GA ČR GAP210/12/2336; GA MŠk LM2010008 Institutional support: RVO:67985530 Keywords : event detection * artificial neural network * West Bohemia/Vogtland Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 2.533, year: 2016

  10. Monitoring Risk Behaviors by Managing Social Support in the Network of a Forensic Psychiatric Patient : A Single-Case Analysis

    NARCIS (Netherlands)

    ter Haar-Pomp, Lydia; de Beer, Carlijn; van der Lem, Rosalind; Spreen, Marinus; Bogaerts, Stefan

    2015-01-01

    This prospective case study examines changes over time in the social support network of a forensic psychiatric patient diagnosed with attention deficit hyperactivity disorder (ADHD). The focus is on the functional and dysfunctional influences of the patient's social support dynamics on his risk

  11. A 250-Mbit/s ring local computer network using 1.3-microns single-mode optical fibers

    Science.gov (United States)

    Eng, S. T.; Tell, R.; Andersson, T.; Eng, B.

    1985-01-01

    A 250-Mbit/s three-station fiber-optic ring local computer network was built and successfully demonstrated. A conventional token protocol was employed for bus arbitration to maximize the bus efficiency under high loading conditions, and a non-return-to-zero (NRS) data encoding format was selected for simplicity and maximum utilization of the ECL-circuit bandwidth.

  12. Synthesis and Characterization of Network Single Ion Conductors(NSIC) Based On Comb-Branched Polyepoxide Ethers and LithiumBis(allylmalonato)borate

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Xiao-Guang; Kerr, John B.

    2004-07-11

    Network single ion conductors (NSICs) based on comb-branch polyepoxide ethers and lithium bis(allylmalonato) borate have been synthesized and thoroughly characterized by means of ionic conductivity measurements, electrochemical impedance and by dynamic mechanical analysis (DMA). The materials have been tested as battery electrolytes by cycling in symmetrical Li/Li half cells and in Li/V{sub 6}O{sub 13} full cells in which the NSIC was used as both binder and electrolyte in the cathode electrode and as the electrolyte separator membrane,. The substitution of the trimethylene oxide (TMO) unit into the side chains in place of ethylene oxide (EO) units increased the polymerion mobility (lower glass transition temperature). However, the ionic conductivity was nearly one and half orders of magnitude lower than the corresponding pure EO based single ion conductor at the same salt concentration. This effect may be ascribed to the lower dielectric constant of the TMO side chains that result in a lower concentration of free conducting lithium cations. For a highly cross-linked system (EO/Li=20), only 47 wt% plasticizing solvent (ethylene carbonate (EC)/ethyl methyl carbonate (EMC), 1/1 by wt) could be taken up and the ionic conductivity was only increased by one order of magnitude over the dry polyelectrolyte while for a less densely crosslinked system (EO/Li=80), up to 75 wt% plasticizer could be taken up and the ionic conductivity was increased by nearly two orders of magnitude. A Li/Li symmetric cell that was cycled at 85 C at a current density of 25{micro}Acm{sup -2} showed no concentration polarization or diffusional relaxation, consistent with a lithium ion transference number of one. However, both the bulk and interfacial impedances increased after 20 cycles, apparently due to continued cross-linking reactions within the membrane and on the surface of the lithium electrodes. A Li/V{sub 6}O{sub 13} full cell constructed using a single ion conductor gel (propylene

  13. A network of networks.

    Science.gov (United States)

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

    2017-04-10

    from network members than participation in a single network, as it involves health service professionals and consumers in a multi-network dynamic. This dynamic requires deliberations and collaborations to be flexible, and it increasingly positions members as "strategic hybrids" - people who have moved on from singular taken-as-given stances and identities, towards hybrid positionings and flexible perspectives. Originality/value This paper is novel in that it identifies a critical feature of health service reform and large system transformation: network governance is empowered through the dynamic co-location of and collaboration among healthcare networks, particularly when complemented with "enabler" teams of people specialising in programme implementation and evaluation.

  14. A 3 W High-Voltage Single-Chip Green Light-Emitting Diode with Multiple-Cells Network

    Directory of Open Access Journals (Sweden)

    W. Wang

    2015-01-01

    Full Text Available A parallel and series network structure was introduced into the design of the high-voltage single-chip (HV-SC light-emitting diode to inhibit the effect of current crowding and to improve the yield. Using such a design, a 6.6×5 mm2 large area LED chip of 24 parallel stages was demonstrated with 3 W light output power (LOP at the current of 500 mA. The forward voltage was measured to be 83 V with the same current injection, corresponding to 3.5 V for a single stage. The LED chip’s average thermal resistance was identified to be 0.28 K/W by using infrared thermography analysis.

  15. Neural-network-based prediction techniques for single station modeling and regional mapping of the foF2 and M(3000F2 ionospheric characteristics

    Directory of Open Access Journals (Sweden)

    T. D. Xenos

    2002-01-01

    Full Text Available In this work, Neural-Network-based single-station hourly daily foF2 and M(3000F2 modelling of 15 European ionospheric stations is investigated. The data used are neural networks and hourly daily values from the period 1964- 1988 for training the neural networks and from the period 1989-1994 for checking the prediction accuracy. Two types of models are presented for the F2-layer critical frequency prediction and two for the propagation factor M(3000F2. The first foF2 model employs the E-layer local noon calculated daily critical frequency (foE12 and the local noon F2- layer critical frequency of the previous day. The second foF2 model, which introduces a new regional mapping technique, employs the Juliusruh neural network model and uses the E-layer local noon calculated daily critical frequency (foE12, and the previous day F2-layer critical frequency measured at Juliusruh at noon. The first M(3000F2 model employs the E-layer local noon calculated daily critical frequency (foE12, its ± 3 h deviations and the local noon cosine of the solar zenith angle (cos c12. The second model, which introduces a new M(3000F2 mapping technique, employs Juliusruh neural network model and uses the E-layer local noon calculated daily critical frequency (foE12, and the previous day F2-layer critical frequency measured at Juliusruh at noon.

  16. Detecting the single line to ground short circuit fault in the submarine’s power system using the artificial neural network

    Directory of Open Access Journals (Sweden)

    Behniafar Ali

    2013-01-01

    Full Text Available The electric marine instruments are newly inserted in the trade and industry, for which the existence of an equipped and reliable power system is necessitated. One of the features of such a power system is that it cannot have an earth system causing the protection relays not to be able to detect the single line to ground short circuit fault. While on the other hand, the occurrence of another similar fault at the same time can lead to the double line fault and thereby the tripping of relays and shortening of vital loads. This in turn endangers the personals' security and causes the loss of military plans. From the above considerations, it is inferred that detecting the single line to ground fault in the marine instruments is of a special importance. In this way, this paper intends to detect the single line to ground fault in the power systems of the marine instruments using the wavelet transform and Multi-Layer Perceptron (MLP neural network. In the numerical analysis, several different types of short circuit faults are simulated on several marine power systems and the proposed approach is applied to detect the single line to ground fault. The results are of a high quality and preciseness and perfectly demonstrate the effectiveness of the proposed approach.

  17. PERFORMANCE ANALYSIS OF ARQ AND HYBRID ARQ OVER SINGLE-HOP, DUAL-HOP, AND MULTIBRANCH DUAL-HOP NETWORKS

    KAUST Repository

    Hadjtaieb, Amir

    2014-05-01

    During the last decade, relay networks have attracted a lot of interest due to their numerous benefits. The relaying technique allows extending the coverage zone of wireless networks and offers a higher reliability for communication systems. The performance of relay networks can be improved further by the use of automatic repeat request (ARQ) and hybrid automatic repeat request (HARQ) techniques. ARQ and HARQ are retransmission mechanisms that ensure a good quality of service even in absence of channel state information at the transmitter. We, firstly, study the spectral and energy efficiency of ARQ in Nakagami-m block-fading channels. We maximize both spectral efficiency and energy efficiency with respect to the transmitted power. We derive exact expressions as well as compact and tight approximation for the solutions of these problems. Our analysis shows that the two problems of maximizing spectral efficiency and energy efficiency with respect to the transmitted power are completely different and give different solutions. Additionally, operating with a power that maximizes energy efficiency can lead to a significant drop in the spectral efficiency, and vice versa. Next, we consider a three node relay network comprising a source, a relay, and a destination. The source transmits the message to the destination using HARQ with incremental redundancy (IR). The relay overhears the transmitted message, amplifies it using a variable gain amplifier, and then forwards the message to the destination. This latter combines both the source and the relay message and tries to decode the information. In case of decoding failure, the destination sends a negative acknowledgement. A new replica of the message containing new parity bits is then transmitted in the subsequent HARQ round. This process continues until successful decoding occurs at the destination or a maximum number M of rounds is reached. We study the performance of HARQ-IR over the considered relay channel from an

  18. Informatics in radiology: integration of the medical imaging resource center into a teaching hospital network to allow single sign-on access.

    Science.gov (United States)

    Prevedello, Luciano M; Andriole, Katherine P; Khorasani, Ryan Roobian Ramin

    2009-01-01

    The RSNA Medical Imaging Resource Center (MIRC) software is an open-source program that allows users to identify, index, and retrieve images, teaching files, and other radiologic data that share a common underlying structure. The software is being continually improved as new challenges and different needs become apparent. Although version T30 is easily installed on a stand-alone computer, its implementation at healthcare enterprises with complex network architecture may be challenging with respect to security because users cannot log on by using a standard enterprise-wide authentication protocol. Instead, authentication takes place through the local MIRC database, creating security concerns and potential organizational problems. In this setting, the Lightweight Directory Access Protocol (LDAP) can be used to provide a single sign-on environment and increase authentication security. A commercial directory service using LDAP has been successfully integrated with MIRC in a large multifacility enterprise to provide single sign-on capability compatible with the institutional networking policies for password security. Copyright RSNA, 2009

  19. Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network

    Directory of Open Access Journals (Sweden)

    Faa-Jeng Lin

    2014-01-01

    Full Text Available This study presents a new active and reactive power control scheme for a single-stage three-phase grid-connected photovoltaic (PV system during grid faults. The presented PV system utilizes a single-stage three-phase current-controlled voltage-source inverter to achieve the maximum power point tracking (MPPT control of the PV panel with the function of low voltage ride through (LVRT. Moreover, a formula based on positive sequence voltage for evaluating the percentage of voltage sag is derived to determine the ratio of the injected reactive current to satisfy the LVRT regulations. To reduce the risk of overcurrent during LVRT operation, a current limit is predefined for the injection of reactive current. Furthermore, the control of active and reactive power is designed using a two-dimensional recurrent fuzzy cerebellar model articulation neural network (2D-RFCMANN. In addition, the online learning laws of 2D-RFCMANN are derived according to gradient descent method with varied learning-rate coefficients for network parameters to assure the convergence of the tracking error. Finally, some experimental tests are realized to validate the effectiveness of the proposed control scheme.

  20. Long-term stability of superhydrophilic oxygen plasma-modified single-walled carbon nanotube network surfaces and the influence on ammonia gas detection

    Energy Technology Data Exchange (ETDEWEB)

    Min, Sungjoon [Department of Biomicrosystem Technology, Korea University, Seoul 136-713 (Korea, Republic of); Kim, Joonhyub [Department of Control and Instrumentation Engineering, Korea University, 2511 Sejong-ro, Sejong City 339-770 (Korea, Republic of); Park, Chanwon [Department of Electrical and Electronic Engineering, Kangwon National University, Chuncheon 200-701 (Korea, Republic of); Jin, Joon-Hyung, E-mail: jj1023@chol.com [Department of Chemical Engineering, Kyonggi University, 154-42 Gwanggyosan-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do 16227 (Korea, Republic of); Min, Nam Ki, E-mail: nkmin@korea.ac.kr [Department of Biomicrosystem Technology, Korea University, Seoul 136-713 (Korea, Republic of)

    2017-07-15

    Graphical abstract: Superhydrophilic single-walled carbon nanotube obtained by O{sub 2} plasma treatment voluntarily and non-reversibly reverts to a metastable state. This aerobic aging is an essential process to develop a stable carbon nanotube-based sensor. - Highlights: • Superhydrophilic single-walled carbon nanotube network can be obtained by O{sub 2} plasma-based surface modification. • The modified carbon nanotube surface invariably reverts to a metastable state in a non-reversible manner. • Aerobic aging is essential to stabilize the modified carbon nanotube and the carbon nanotube-based sensing device due to minimized sensor-to-sensor variation. - Abstract: Single-walled carbon nanotube (SWCNT) networks are subjected to a low-powered oxygen plasma for the surface modification. Changes in the surface chemical composition and the stability of the plasma-treated SWCNT (p-SWCNT) with aging in air for up to five weeks are studied using X-ray photoelectron spectroscopy (XPS) and contact angle analysis. The contact angle decreases from 120° of the untreated hydrophobic SWCNT to 0° for the superhydrophilic p-SWCNT. Similarly, the ratio of oxygen to carbon (O:C) based on the XPS spectra increases from 0.25 to 1.19, indicating an increase in surface energy of the p-SWCNT. The enhanced surface energy is gradually dissipated and the p-SWCNT network loses the superhydrophilic surface property. However, it never revert to the original hydrophobic surface state but to a metastable hydrophilic state. The aging effect on sensitivity of the p-SWCNT network-based ammonia sensor is investigated to show the importance of the aging process for the stabilization of the p-SWCNT. The best sensitivity for monitoring NH{sub 3} gas is observed with the as-prepared p-SWCNT, and the sensitivity decreases as similar as the p-SWCNT loses its hydrophilicity with time goes by. After a large performance degradation during the aging time for about two weeks, the response

  1. An overview of the British Columbia Glomerulonephritis network and registry: integrating knowledge generation and translation within a single framework.

    Science.gov (United States)

    Barbour, Sean; Beaulieu, Monica; Gill, Jagbir; Djurdjev, Ognjenka; Reich, Heather; Levin, Adeera

    2013-10-29

    Glomerulonephritis (GN) is a group of rare kidney diseases with a substantial health burden and high risk of progression to end-stage renal disease. Research in GN has been limited by poor availability of large comprehensive registries. Substantial variations in access to and administration of treatment and outcomes in GN have been described. Leveraging provincial resources and existing infrastructure, the British Columbia (BC) GN Network is an initiative which serves to combine research and clinical care objectives. The goal of the BC GN Network is to coordinate and improve health care, including robust data capture, on all patients with GN in BC, a Canadian province of over 4.6 million people. This provincial initiative will serve as a model for Canadian or other national and international endeavours. The BC Provincial Renal Agency (BCPRA) is the provincial governmental agency responsible for health delivery for all kidney patients in BC. The BC GN Network has been created by the BCPRA to ensure high quality and equitable access to care for all patients with GN and is a platform for evidence based clinical care programs and associated health policy. All patients with biopsy-proven GN are registered at the time of kidney biopsy into the BCPRA provincial database of kidney disease patients, forming the BC GN Registry. Thereafter, all laboratory results and renal related outcomes are captured automatically. Histology data and core clinical variables are entered into the database. Additional linkages between the GN Registry and administrative databases ensure robust capture of medications, hospital admissions, health care utilization, comorbidities, cancer and cardiac outcomes, and vital statistics. The BC GN Network and Registry is a unique model in that it combines robust data capture, data linkages, and health care delivery and evaluation into one integrated system. This model utilizes existing health infrastructure to prospectively capture population level data

  2. Development of the self-learning machine for creating models of microprocessor of single-phase earth fault protection devices in networks with isolated neutral voltage above 1000 V

    Science.gov (United States)

    Utegulov, B. B.; Utegulov, A. B.; Meiramova, S.

    2018-02-01

    The paper proposes the development of a self-learning machine for creating models of microprocessor-based single-phase ground fault protection devices in networks with an isolated neutral voltage higher than 1000 V. Development of a self-learning machine for creating models of microprocessor-based single-phase earth fault protection devices in networks with an isolated neutral voltage higher than 1000 V. allows to effectively implement mathematical models of automatic change of protection settings. Single-phase earth fault protection devices.

  3. A 2D Coordination Network That Detects Nitro Explosives in Water, Catalyzes Baylis-Hillman Reactions, and Undergoes Unusual 2D→3D Single-Crystal to Single-Crystal Transformation.

    Science.gov (United States)

    Sharma, Vivekanand; De, Dinesh; Pal, Sanchari; Saha, Prithwidip; Bharadwaj, Parimal K

    2017-08-07

    The solvothermal reaction of Zn(NO 3 ) 2 ·6H 2 O and a linear dicarboxylate ligand H 2 L, in the presence of urotropine in N,N'-dimethylformamide (DMF), gives rise to a new porous two-dimensional (2D) coordination network, {[Zn 3 (L) 3 (urotropine) 2 ]·2DMF·3H 2 O} n (1), with hxl topology. Interestingly, framework 1 exhibits excellent emission properties owing to the presence of naphthalene moiety in the linker H 2 L, that can be efficiently suppressed by subtle quantity of nitro explosives in aqueous medium. Furthermore, presence of urotropine molecules bound to the metal centers, 1 is found to be an excellent heterogeneous catalyst meant for atom-economical C-C bond-forming Baylis-Hillman reactions. Additionally, crystals of 1 undergo complete transmetalation with Cu(II) to afford isostructural 1 Cu . Moreover, the 2D framework of 1 allows replacement of urotropine molecules by 4,4'-azopyridine (azp) linker resulting in a three-dimensional (3D) metal-organic framework, {[Zn(L)(azp)]·4DMF 2H 2 O} n (2). The 1→2 transformation takes place in single-crystal-to-single crystal manner supported by powder X-ray diffraction, atomic force microscopy, high-resolution transmission electron microscopy, and morphological studies. Remarkably, during this 2D→3D transformation, the original trinuclear [Zn 3 (COO) 6 ] secondary building unit changes to a mononuclear node, which is unprecedented.

  4. Two-Photon Functional Imaging of the Auditory Cortex in Behaving Mice: From Neural Networks to Single Spines

    Directory of Open Access Journals (Sweden)

    Ruijie Li

    2018-04-01

    Full Text Available In vivo two-photon Ca2+ imaging is a powerful tool for recording neuronal activities during perceptual tasks and has been increasingly applied to behaving animals for acute or chronic experiments. However, the auditory cortex is not easily accessible to imaging because of the abundant temporal muscles, arteries around the ears and their lateral locations. Here, we report a protocol for two-photon Ca2+ imaging in the auditory cortex of head-fixed behaving mice. By using a custom-made head fixation apparatus and a head-rotated fixation procedure, we achieved two-photon imaging and in combination with targeted cell-attached recordings of auditory cortical neurons in behaving mice. Using synthetic Ca2+ indicators, we recorded the Ca2+ transients at multiple scales, including neuronal populations, single neurons, dendrites and single spines, in auditory cortex during behavior. Furthermore, using genetically encoded Ca2+ indicators (GECIs, we monitored the neuronal dynamics over days throughout the process of associative learning. Therefore, we achieved two-photon functional imaging at multiple scales in auditory cortex of behaving mice, which extends the tool box for investigating the neural basis of audition-related behaviors.

  5. Insertion of a single-molecule magnet inside a ferromagnetic lattice based on a 3D bimetallic oxalate network: towards molecular analogues of permanent magnets.

    Science.gov (United States)

    Clemente-León, Miguel; Coronado, Eugenio; Gómez-García, Carlos J; López-Jordà, Maurici; Camón, Agustín; Repollés, Ana; Luis, Fernando

    2014-02-03

    The insertion of the single-molecule magnet (SMM) [Mn(III)(salen)(H2O)]2(2+) (salen(2-) = N,N'-ethylenebis-(salicylideneiminate)) into a ferromagnetic bimetallic oxalate network affords the hybrid compound [Mn(III)(salen)(H2O)]2[Mn(II)Cr(III)(ox)3]2⋅(CH3OH)⋅(CH3CN)2 (1). This cationic Mn2 cluster templates the growth of crystals formed by an unusual achiral 3D oxalate network. The magnetic properties of this hybrid magnet are compared with those of the analogous compounds [Mn(III)(salen)(H2O)]2[Zn(II)Cr(III)(ox)3]2⋅(CH3OH)⋅(CH3CN)2 (2) and [In(III)(sal2-trien)][Mn(II)Cr(III)(ox)3]⋅(H2O)0.25⋅(CH3OH)0.25⋅(CH3CN)0.25 (3), which are used as reference compounds. In 2 it has been shown that the magnetic isolation of the Mn2 clusters provided by their insertion into a paramagnetic oxalate network of Cr(III) affords a SMM behavior, albeit with blocking temperatures well below 500 mK even for frequencies as high as 160 kHz. In 3 the onset of ferromagnetism in the bimetallic Mn(II) Cr(III) network is observed at Tc = 5 K. Finally, in the hybrid compound 1 the interaction between the two magnetic networks leads to the antiparallel arrangement of their respective magnetizations, that is, to a ferrimagnetic phase. This coupling induces also important changes on the magnetic properties of 1 with respect to those of the reference compounds 2 and 3. In particular, compound 1 shows a large magnetization hysteresis below 1 K, which is in sharp contrast with the near-reversible magnetizations that the SMMs and the oxalate ferromagnetic lattice show under the same conditions. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Prenatal diagnosis and risk factors for preoperative death in neonates with single right ventricle and systemic outflow obstruction: screening data from the Pediatric Heart Network Single Ventricle Reconstruction Trial(∗).

    Science.gov (United States)

    Atz, Andrew M; Travison, Thomas G; Williams, Ismee A; Pearson, Gail D; Laussen, Peter C; Mahle, William T; Cook, Amanda L; Kirsh, Joel A; Sklansky, Mark; Khaikin, Svetlana; Goldberg, Caren; Frommelt, Michele; Krawczeski, Catherine; Puchalski, Michael D; Jacobs, Jeffrey P; Baffa, Jeanne M; Rychik, Jack; Ohye, Richard G

    2010-12-01

    The purpose of this analysis was to assess preoperative risk factors before the first-stage Norwood procedure in infants with hypoplastic left heart syndrome and related single-ventricle lesions and to evaluate practice patterns in prenatal diagnosis, as well as the role of prenatal diagnosis in outcome. Data from all live births with morphologic single right ventricle and systemic outflow obstruction screened for the Pediatric Heart Network's Single Ventricle Reconstruction Trial were used to investigate prenatal diagnosis and preoperative risk factors. Demographics, gestational age, prenatal diagnosis status, presence of major extracardiac congenital abnormalities, and preoperative mortality rates were recorded. Of 906 infants, 677 (75%) had prenatal diagnosis, 15% were preterm (<37 weeks' gestation), and 16% were low birth weight (<2500 g). Rates of prenatal diagnosis varied by study site (59% to 85%, P < .0001). Major extracardiac congenital abnormalities were less prevalent in those born after prenatal diagnosis (6% vs 10%, P = .03). There were 26 (3%) deaths before Norwood palliation; preoperative mortality did not differ by prenatal diagnosis status (P = .49). In multiple logistic regression models, preterm birth (P = .02), major extracardiac congenital abnormalities (P < .0001), and obstructed pulmonary venous return (P = .02) were independently associated with preoperative mortality. Prenatal diagnosis occurred in 75%. Preoperative death was independently associated with preterm birth, obstructed pulmonary venous return, and major extracardiac congenital abnormalities. Adjusted for gestational age and the presence of obstructed pulmonary venous return, the estimated odds of preoperative mortality were 10 times greater for subjects with a major extracardiac congenital abnormality. Copyright © 2010 The American Association for Thoracic Surgery. All rights reserved.

  7. Metabolic network analysis and experimental study of lipid production in Rhodosporidium toruloides grown on single and mixed substrates.

    Science.gov (United States)

    Bommareddy, Rajesh Reddy; Sabra, Wael; Maheshwari, Garima; Zeng, An-Ping

    2015-03-18

    Microbial lipids (triacylglycerols, TAG) have received large attention for a sustainable production of oleochemicals and biofuels. Rhodosporidium toruloides can accumulate lipids up to 70% of its cell mass under certain conditions. However, our understanding of lipid production in this yeast is still much limited, especially for growth with mixed substrates at the level of metabolic network. In this work, the potentials of several important carbon sources for TAG production in R.toruloides are first comparatively studied in silico by means of elementary mode analysis followed by experimental validation. A simplified metabolic network of R.toruloides was reconstructed based on a combination of genome and proteome annotations. Optimal metabolic space was studied using elementary mode analysis for growth on glycerol, glucose, xylose and arabinose or in mixtures. The in silico model predictions of growth and lipid production are in agreement with experimental results. Both the in silico and experimental studies revealed that glycerol is an attractive substrate for lipid synthesis in R. toruloides either alone or in blend with sugars. A lipid yield as high as 0.53 (C-mol TAG/C-mol) has been experimentally obtained for growth on glycerol, compared to a theoretical maximum of 0.63 (C-mol TAG/C-mol). The lipid yield on glucose is much lower (0.29 (experimental) vs. 0.58 (predicted) C-mol TAG/C-mol). The blend of glucose with glycerol decreased the lipid yield on substrate but can significantly increase the overall volumetric productivity. Experimental studies revealed catabolite repression of glycerol by the presence of glucose for the first time. Significant influence of oxygen concentration on the yield and composition of lipids were observed which have not been quantitatively studied before. This study provides for the first time a simplified metabolic model of R.toruloides and its detailed in silico analysis for growth on different carbon sources for their potential of

  8. An eHealth Intervention to Promote Physical Activity and Social Network of Single, Chronically Impaired Older Adults: Adaptation of an Existing Intervention Using Intervention Mapping.

    Science.gov (United States)

    Boekhout, Janet M; Peels, Denise A; Berendsen, Brenda Aj; Bolman, Catherine Aw; Lechner, Lilian

    2017-11-23

    Especially for single older adults with chronic diseases, physical inactivity and a poor social network are regarded as serious threats to their health and independence. The Active Plus intervention is an automated computer-tailored eHealth intervention that has been proven effective to promote physical activity (PA) in the general population of adults older than 50 years. The aim of this study was to report on the methods and results of the systematic adaptation of Active Plus to the wishes and needs of the subgroup of single people older than 65 years who have one or more chronic diseases, as this specific target population may encounter specific challenges regarding PA and social network. The Intervention Mapping (IM) protocol was used to systematically adapt the existing intervention to optimally suit this specific target population. A literature study was performed, and quantitative as well as qualitative data were derived from health care professionals (by questionnaires, n=10) and the target population (by focus group interviews, n=14), which were then systematically integrated into the adapted intervention. As the health problems and the targeted behavior are largely the same in the original and adapted intervention, the outcome of the needs assessment was that the performance objectives remained the same. As found in the literature study and in data derived from health professionals and focus groups, the relative importance and operationalization of the relevant psychosocial determinants related to these objectives are different from the original intervention, resulting in a refinement of the change objectives to optimally fit the specific target population. This refinement also resulted in changes in the practical applications, program components, intervention materials, and the evaluation and implementation strategy for the subgroup of single, chronically impaired older adults. This study demonstrates that the adaptation of an existing intervention is an

  9. Simultaneous Generations of Independent Millimeter Wave and 10 Gbit/s Wired Signal by Single Electrode Modulator in TDM-PON Network

    Science.gov (United States)

    Niazi, Shahab Ahmad; Zhang, Xiaoguang; Xi, Lixia; Idress, Muhammad

    2013-03-01

    We propose and present a cost effective and simple technique of simultaneous generation and propagation of millimeter wave with recently standardized 10 giga bit passive optical network (GPON) by mixing of 2.5 Gbit/s, 30 GHz radio wave with 10 Gbit/s based band signal and then modulated by single Mach Zehnder modulator (MZM). In this scheme, we have applied 1490 nm for downstream, 1310 nm for upstream transmission and ON OFF keying (OOK) modulation format to make it fully align with existing standards and infrastructure. Simulation results show error free transmission performance with negligible power penalty over 25 km bidirectional fiber. We also highlight the principles and discuss the main technical challenges for commercial realization of 60 GHz spectrum.

  10. Principle and Design of a Single-phase Inverter-Based Grounding System for Neutral-to-ground Voltage Compensation in Distribution Networks

    DEFF Research Database (Denmark)

    Wang, Wen; Yan, Lingjie; Zeng, Xiangjun

    2017-01-01

    Neutral-to-ground overvoltage may occur in non-effectively grounded power systems because of the distributed parameters asymmetry and resonance between Petersen coil and distributed capacitances. Thus, the constraint of neutral-to-ground voltage is critical for the safety of distribution networks....... In this paper, an active grounding system based on single-phase inverter and its control parameter design method is proposed to achieve this objective. Relationship between its output current and neutral-to-ground voltage is derived to explain the principle of neutral-to-ground voltage compensation. Then...... margin subjecting to large range of load change. The PI method is taken as the comparative method and the performances of both control methods are presented in detail. Experimental results prove the effectiveness and novelty of the proposed grounding system and control method....

  11. Synchronization, non-linear dynamics and low-frequency fluctuations: Analogy between spontaneous brain activity and networked single-transistor chaotic oscillators

    Science.gov (United States)

    Minati, Ludovico; Chiesa, Pietro; Tabarelli, Davide; D'Incerti, Ludovico; Jovicich, Jorge

    2015-03-01

    In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D2), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes.

  12. Synchronization, non-linear dynamics and low-frequency fluctuations: Analogy between spontaneous brain activity and networked single-transistor chaotic oscillators

    International Nuclear Information System (INIS)

    Minati, Ludovico; Chiesa, Pietro; Tabarelli, Davide; Jovicich, Jorge; D'Incerti, Ludovico

    2015-01-01

    In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functional MRI acquisitions of spontaneous activity during wakeful idleness, node degree maps are determined by thresholding the temporal correlation coefficient among all voxel pairs. In addition, for individual voxel time-series, the relative amplitude of low-frequency fluctuations and the correlation dimension (D 2 ), determined with respect to Fourier amplitude and value distribution matched surrogate data, are measured. Across cortical areas, high node degree is associated with a shift towards lower frequency activity and, compared to surrogate data, clearer saturation to a lower correlation dimension, suggesting presence of non-linear structure. An attempt to recapitulate this relationship in a network of single-transistor oscillators is made, based on a diffusive ring (n = 90) with added long-distance links defining four extended hub regions. Similarly to the brain data, it is found that oscillators in the hub regions generate signals with larger low-frequency cycle amplitude fluctuations and clearer saturation to a lower correlation dimension compared to surrogates. The effect emerges more markedly close to criticality. The homology observed between the two systems despite profound differences in scale, coupling mechanism and dynamics appears noteworthy. These experimental results motivate further investigation into the heterogeneity of cortical non-linear dynamics in relation to connectivity and underline the ability for small networks of single-transistor oscillators to recreate collective phenomena arising in much more complex biological systems, potentially representing a future platform for modelling disease-related changes

  13. High-sensitivity pH sensor using separative extended-gate field-effect transistors with single-walled carbon-nanotube networks

    Science.gov (United States)

    Pyo, Ju-Young; Cho, Won-Ju

    2018-04-01

    We fabricate high-sensitivity pH sensors using single-walled carbon-nanotube (SWCNT) network thin-film transistors (TFTs). The sensing and transducer parts of the pH sensor are composed of separative extended-sensing gates (ESGs) with SnO2 ion-sensitive membranes and double-gate structure TFTs with thin SWCNT network channels of ∼1 nm and AlO x top-gate insulators formed by the solution-deposition method. To prevent thermal process-induced damages on the SWCNT channel layer due to the post-deposition annealing process and improve the electrical characteristics of the SWCNT-TFTs, microwave irradiation is applied at low temperatures. As a result, a pH sensitivity of 7.6 V/pH, far beyond the Nernst limit, is obtained owing to the capacitive coupling effect between the top- and bottom-gate insulators of the SWCNT-TFTs. Therefore, double-gate structure SWCNT-TFTs with separated ESGs are expected to be highly beneficial for high-sensitivity disposable biosensor applications.

  14. An improved fault detection classification and location scheme based on wavelet transform and artificial neural network for six phase transmission line using single end data only.

    Science.gov (United States)

    Koley, Ebha; Verma, Khushaboo; Ghosh, Subhojit

    2015-01-01

    Restrictions on right of way and increasing power demand has boosted development of six phase transmission. It offers a viable alternative for transmitting more power, without major modification in existing structure of three phase double circuit transmission system. Inspite of the advantages, low acceptance of six phase system is attributed to the unavailability of a proper protection scheme. The complexity arising from large number of possible faults in six phase lines makes the protection quite challenging. The proposed work presents a hybrid wavelet transform and modular artificial neural network based fault detector, classifier and locator for six phase lines using single end data only. The standard deviation of the approximate coefficients of voltage and current signals obtained using discrete wavelet transform are applied as input to the modular artificial neural network for fault classification and location. The proposed scheme has been tested for all 120 types of shunt faults with variation in location, fault resistance, fault inception angles. The variation in power system parameters viz. short circuit capacity of the source and its X/R ratio, voltage, frequency and CT saturation has also been investigated. The result confirms the effectiveness and reliability of the proposed protection scheme which makes it ideal for real time implementation.

  15. Evolutionary rate heterogeneity between multi- and single-interface hubs across human housekeeping and tissue-specific protein interaction network: Insights from proteins' and its partners' properties.

    Science.gov (United States)

    Biswas, Kakali; Acharya, Debarun; Podder, Soumita; Ghosh, Tapash Chandra

    2017-12-02

    Integrating gene expression into protein-protein interaction network (PPIN) leads to the construction of tissue-specific (TS) and housekeeping (HK) sub-networks, with distinctive TS- and HK-hubs. All such hub proteins are divided into multi-interface (MI) hubs and single-interface (SI) hubs, where MI hubs evolve slower than SI hubs. Here we explored the evolutionary rate difference between MI and SI proteins within TS- and HK-PPIN and observed that this difference is present only in TS, but not in HK-class. Next, we explored whether proteins' own properties or its partners' properties are more influential in such evolutionary discrepancy. Statistical analyses revealed that this evolutionary rate correlates negatively with protein's own properties like expression level, miRNA count, conformational diversity and functional properties and with its partners' properties like protein disorder and tissue expression similarity. Moreover, partial correlation and regression analysis revealed that both proteins' and its partners' properties have independent effects on protein evolutionary rate. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. The influence of the residency application process on the online social networking behavior of medical students: a single institutional study.

    Science.gov (United States)

    Strausburg, Matthew B; Djuricich, Alexander M; Carlos, W Graham; Bosslet, Gabriel T

    2013-11-01

    To evaluate medical students' behavior regarding online social networks (OSNs) in preparation for the residency matching process. The specific aims were to quantify the use of OSNs by students to determine whether and how these students were changing OSN profiles in preparation for the residency application process, and to determine attitudes toward residency directors using OSNs as a screening method to evaluate potential candidates. An e-mail survey was sent to 618 third- and fourth-year medical students at Indiana University School of Medicine over a three-week period in 2012. Statistical analysis was completed using nonparametric statistical tests. Of the 30.1% (183/608) who responded to the survey, 98.9% (181/183) of students reported using OSNs. More than half, or 60.1% (110/183), reported that they would (or did) alter their OSN profile before residency matching. Respondents' opinions regarding the appropriateness of OSN screening by residency directors were mixed; however, most respondents did not feel that their online OSN profiles should be used in the residency application process. The majority of respondents planned to (or did) alter their OSN profile in preparation for the residency match process. The majority believed that residency directors are screening OSN profiles during the matching process, although most did not believe their OSN profiles should be used in the residency application process. This study implies that the more medical students perceive that residency directors use social media in application screening processes, the more they will alter their online profiles to adapt to protect their professional persona.

  17. Colleagues as Change Agents: How Department Networks and Opinion Leaders Influence Teaching at a Single Research University.

    Science.gov (United States)

    Andrews, T C; Conaway, E P; Zhao, J; Dolan, E L

    2016-01-01

    Relationships with colleagues have the potential to be a source of support for faculty to make meaningful change in how they teach, but the impact of these relationships is poorly understood. We used a mixed-methods approach to investigate the characteristics of faculty who provide colleagues with teaching resources and facilitate change in teaching, how faculty influence one another. Our exploratory investigation was informed by social network theory and research on the impact of opinion leaders within organizations. We used surveys and interviews to examine collegial interactions about undergraduate teaching in life sciences departments at one research university. Each department included discipline-based education researchers (DBERs). Quantitative and qualitative analyses indicate that DBERs promote changes in teaching to a greater degree than other departmental colleagues. The influence of DBERs derives, at least partly, from a perception that they have unique professional expertise in education. DBERs facilitated change through coteaching, offering ready and approachable access to education research, and providing teaching training and mentoring. Faculty who had participated in a team based-teaching professional development program were also credited with providing more support for teaching than nonparticipants. Further research will be necessary to determine whether these results generalize beyond the studied institution. © 2016 T. C. Andrews et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  18. Formation of multiple networks

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2013-01-01

    networks. Our model, motivated by an empirical analysis of real multi-layered network data, is a conservative extension of single-network models and emphasizes the additional level of complexity that we experience when we move from a single- to a more complete and realistic multi-network context.......While most research in Social Network Analysis has focused on single networks, the availability of complex on-line data about individuals and their mutual heterogenous connections has recently determined a renewed interest in multi-layer network analysis. To the best of our knowledge, in this paper...

  19. Vulnerability of network of networks

    Science.gov (United States)

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

    2014-10-01

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

  20. Single-cell network profiling of peripheral blood mononuclear cells from healthy donors reveals age- and race-associated differences in immune signaling pathway activation.

    Science.gov (United States)

    Longo, Diane M; Louie, Brent; Putta, Santosh; Evensen, Erik; Ptacek, Jason; Cordeiro, James; Wang, Ena; Pos, Zoltan; Hawtin, Rachael E; Marincola, Francesco M; Cesano, Alessandra

    2012-02-15

    A greater understanding of the function of the human immune system at the single-cell level in healthy individuals is critical for discerning aberrant cellular behavior that occurs in settings such as autoimmunity, immunosenescence, and cancer. To achieve this goal, a systems-level approach capable of capturing the response of the interdependent immune cell types to external stimuli is required. In this study, an extensive characterization of signaling responses in multiple immune cell subpopulations within PBMCs from a cohort of 60 healthy donors was performed using single-cell network profiling (SCNP). SCNP is a multiparametric flow cytometry-based approach that enables the simultaneous measurement of basal and evoked signaling in multiple cell subsets within heterogeneous populations. In addition to establishing the interindividual degree of variation within a broad panel of immune signaling responses, the possible association of any observed variation with demographic variables including age and race was investigated. Using half of the donors as a training set, multiple age- and race-associated variations in signaling responses in discrete cell subsets were identified, and several were subsequently confirmed in the remaining samples (test set). Such associations may provide insight into age-related immune alterations associated with high infection rates and diminished protection following vaccination and into the basis for ethnic differences in autoimmune disease incidence and treatment response. SCNP allowed for the generation of a functional map of healthy immune cell signaling responses that can provide clinically relevant information regarding both the mechanisms underlying immune pathological conditions and the selection and effect of therapeutics.

  1. A simplified fracture network model for studying the efficiency of a single well semi open loop heat exchanger in fractured crystalline rock

    Science.gov (United States)

    de La Bernardie, Jérôme; de Dreuzy, Jean-Raynald; Bour, Olivier; Thierion, Charlotte; Ausseur, Jean-Yves; Lesuer, Hervé; Le Borgne, Tanguy

    2016-04-01

    Geothermal energy is a renewable energy source particularly attractive due to associated low greenhouse gas emission rates. Crystalline rocks are in general considered of poor interest for geothermal applications at shallow depths (energy storage at these shallow depths is still remaining very challenging because of the complexity of fractured media. The purpose of this study is to test the possibility of efficient thermal energy storage in shallow fractured rocks with a single well semi open loop heat exchanger (standing column well). For doing so, a simplified numerical model of fractured media is considered with few fractures. Here we present the different steps for building the model and for achieving the sensitivity analysis. First, an analytical and dimensional study on the equations has been achieved to highlight the main parameters that control the optimization of the system. In a second step, multiphysics software COMSOL was used to achieve numerical simulations in a very simplified model of fractured media. The objective was to test the efficiency of such a system to store and recover thermal energy depending on i) the few parameters controlling fracture network geometry (size and number of fractures) and ii) the frequency of cycles used to store and recover thermal energy. The results have then been compared to reference shallow geothermal systems already set up for porous media. Through this study, relationships between structure, heat exchanges and storage may be highlighted.

  2. Single and combinatorial chromatin coupling events underlies the function of transcript factor krüppel-like factor 11 in the regulation of gene networks

    Science.gov (United States)

    2014-01-01

    Background Krüppel-like factors (KLFs) are a group of master regulators of gene expression conserved from flies to human. However, scant information is available on either the mechanisms or functional impact of the coupling of KLF proteins to chromatin remodeling machines, a deterministic step in transcriptional regulation. Results and discussion In the current study, we use genome-wide analyses of chromatin immunoprecipitation (ChIP-on-Chip) and Affymetrix-based expression profiling to gain insight into how KLF11, a human transcription factor involved in tumor suppression and metabolic diseases, works by coupling to three co-factor groups: the Sin3-histone deacetylase system, WD40-domain containing proteins, and the HP1-histone methyltransferase system. Our results reveal that KLF11 regulates distinct gene networks involved in metabolism and growth by using single or combinatorial coupling events. Conclusion This study, the first of its type for any KLF protein, reveals that interactions with multiple chromatin systems are required for the full gene regulatory function of these proteins. PMID:24885560

  3. Neurovascular Network Explorer 1.0: a database of 2-photon single-vessel diameter measurements with MATLAB® graphical user interface

    Directory of Open Access Journals (Sweden)

    Vishnu B Sridhar

    2014-05-01

    Full Text Available We present a database client software – Neurovascular Network Explorer 1.0 (NNE 1.0 – that uses MATLAB® based Graphical User Interface (GUI for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication [1]. These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization, and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches.

  4. Propensity approach to nonequilibrium thermodynamics of a chemical reaction network: controlling single E-coli β-galactosidase enzyme catalysis through the elementary reaction steps.

    Science.gov (United States)

    Das, Biswajit; Banerjee, Kinshuk; Gangopadhyay, Gautam

    2013-12-28

    In this work, we develop an approach to nonequilibrium thermodynamics of an open chemical reaction network in terms of the elementary reaction propensities. The method is akin to the microscopic formulation of the dissipation function in terms of the Kullback-Leibler distance of phase space trajectories in Hamiltonian system. The formalism is applied to a single oligomeric enzyme kinetics at chemiostatic condition that leads the reaction system to a nonequilibrium steady state, characterized by a positive total entropy production rate. Analytical expressions are derived, relating the individual reaction contributions towards the total entropy production rate with experimentally measurable reaction velocity. Taking a real case of Escherichia coli β-galactosidase enzyme obeying Michaelis-Menten kinetics, we thoroughly analyze the temporal as well as the steady state behavior of various thermodynamic quantities for each elementary reaction. This gives a useful insight in the relative magnitudes of various energy terms and the dissipated heat to sustain a steady state of the reaction system operating far-from-equilibrium. It is also observed that, the reaction is entropy-driven at low substrate concentration and becomes energy-driven as the substrate concentration rises.

  5. Neurovascular Network Explorer 1.0: a database of 2-photon single-vessel diameter measurements with MATLAB(®) graphical user interface.

    Science.gov (United States)

    Sridhar, Vishnu B; Tian, Peifang; Dale, Anders M; Devor, Anna; Saisan, Payam A

    2014-01-01

    We present a database client software-Neurovascular Network Explorer 1.0 (NNE 1.0)-that uses MATLAB(®) based Graphical User Interface (GUI) for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication (Tian et al., 2010). These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization), and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches.

  6. Neurovascular Network Explorer 1.0: a database of 2-photon single-vessel diameter measurements with MATLAB® graphical user interface

    Science.gov (United States)

    Sridhar, Vishnu B.; Tian, Peifang; Dale, Anders M.; Devor, Anna; Saisan, Payam A.

    2014-01-01

    We present a database client software—Neurovascular Network Explorer 1.0 (NNE 1.0)—that uses MATLAB® based Graphical User Interface (GUI) for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication (Tian et al., 2010). These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization), and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches. PMID:24904401

  7. Synchronization of networks

    Indian Academy of Sciences (India)

    We study the synchronization of coupled dynamical systems on networks. The dynamics is governed by a local nonlinear oscillator for each node of the network and interactions connecting different nodes via the links of the network. We consider existence and stability conditions for both single- and multi-cluster ...

  8. A mathematical model for optimum single-commodity distribution in the network of chain stores: a case study of food industry

    Directory of Open Access Journals (Sweden)

    Mohsen Cheshmberah

    2011-10-01

    Full Text Available Distribution refers to the steps taken to move and store a product from the suppliers to a customers in the supply chain and is a key driver of the overall profitability of a firm and overall supply chain. In this paper, a problem regarding managing of the move and store of goods are articulated and a mathematical model is presented to solve the model. The objective function is the total costs of distribution network, including transportation, storage rental, general warehousing, goods damages due to the transportation and storage, procurement, packing, and finally loading and unloading costs. The cost components described are defined based on the assumptions for a real distribution network of a chain stores firm. The aim of developing such a model is to find the optimum pattern to move and store goods based on the minimum cost of the distribution network.

  9. Self-consistent modeling of entangled network strands and linear dangling structures in a single-strand mean-field slip-link model

    DEFF Research Database (Denmark)

    Jensen, Mette Krog; Khaliullin, Renat; Schieber, Jay D.

    2012-01-01

    knowledge about the effect of dangling ends and soluble structures. To interpret our recent experimental results, we exploit a molecular model that can predict LVE data and non-linear stress–strain data. The slip-link model has proven to be a robust tool for both LVE and non-linear stress–strain predictions...... strands in the ensemble are attached to the network in both ends. Next we add dangling strands to the network representing the stoichiometric imbalance, or imperfections during curing. By considering monodisperse network strands without dangling ends, we find that the relative low-frequency plateau, G0/GN......0G0G0N, decreases linearly with the average number of entanglements. The decrease from GN0G0N to G 0 is a result of monomer fluctuations between entanglements, which is similar to “longitudinal modes” in tube theory. It is found that the slope of G′ is dependent on the fraction of network strands...

  10. Application of an entropy-based Bayesian optimization technique to the redesign of an existing monitoring network for single air pollutants.

    Science.gov (United States)

    Ainslie, B; Reuten, C; Steyn, D G; Le, Nhu D; Zidek, James V

    2009-06-01

    We apply the entropy-based Bayesian optimizing approach of Le and Zidek to the spatial redesign of the extensive air pollution monitoring network operated by Metro Vancouver, in the Lower Fraser Valley, British Columbia. This method is chosen because of its statistical sophistication, relative to other possible approaches, and because of the very rich, two-decade long data record available from this network. The redesign analysis is applied to ozone, carbon monoxide and PM(2.5) pollutants. The analysis provides guidance with regard to stations monitoring the three pollutants. For both ozone and PM(2.5), the analysis indicates a need for more stations in the eastern part of the monitoring domain. A parallel analysis indicates that stations may be removed from the more central parts of the domain. An analysis of the carbon monoxide network produces results that are not nearly as clearly defined as those for the other two pollutants, presumably because carbon monoxide is a primary pollutant with many locally important sources. The work demonstrates the great utility of the analysis technique, and also provides statistically defensible guidance on the spatial redesign of this important monitoring network.

  11. B-jet and c-jet identification with Neural Networks as well as combination of multivariate analyses for the search for of multivariate analyses for the search for single top-quark production

    Energy Technology Data Exchange (ETDEWEB)

    Renz, Manuel; /Karlsruhe U., EKP

    2008-06-01

    In the first part of this diploma thesis, the current version of the KIT Flavor Separator, a neural network which is able to distinguish between tagged b-quark jets and tagged c/light-quark jets, is presented. In comparison with previous versions four new input variables are utilized and new Monte Carlo samples with a larger number of simulated events are used for the training of the neural network. It is illustrated that the output of the neural network is continuously distributed between 1 and -1, whereas b-quark jets accumulate at 1, however, c-quark jets and light-quark jets have outputs next to -1. To ensure that the network output describes observed events correctly, the shapes of all input variables are compared in simulation and data. Thus the mismodelling of any input variable is excluded. Moreover, the b jet and light jet output distributions are compared with the output of samples of observed events, which are enhanced in the particular flavor. In contrast to previous versions, no b-jet output correction function has to be calculated, because the agreement between simulation and collision data is excellent for b-quark jets. For the light-jet output, correction functions are developed. Different applications of the KIT Flavor Separator are mentioned. For example it provides a precious input to all three CDF single top quark analyses. Furthermore, it is shown that the KIT Flavor Separator is a universal tool, which can be used in every high-p{sub T} analysis that requires the identification of b-quark jets with high efficiency. As it is pointed out, a further application is the estimation of the flavor composition of a given sample of observed events. In addition a neural network, which is able to separate c-quark jets from light-quark jets, is trained. It is shown, that all three flavors can be separated in the c-net-Flavor Separator plane. As a result, the uncertainties on the estimation of the flavor composition in events with one tagged jet are cut

  12. B-jet and c-jet identification with Neural Networks as well as combination of multivariate analyses for the search for of multivariate analyses for the search for single top-quark production

    International Nuclear Information System (INIS)

    Renz, Manuel

    2008-01-01

    In the first part of this diploma thesis, the current version of the KIT Flavor Separator, a neural network which is able to distinguish between tagged b-quark jets and tagged c/light-quark jets, is presented. In comparison with previous versions four new input variables are utilized and new Monte Carlo samples with a larger number of simulated events are used for the training of the neural network. It is illustrated that the output of the neural network is continuously distributed between 1 and -1, whereas b-quark jets accumulate at 1, however, c-quark jets and light-quark jets have outputs next to -1. To ensure that the network output describes observed events correctly, the shapes of all input variables are compared in simulation and data. Thus the mismodelling of any input variable is excluded. Moreover, the b jet and light jet output distributions are compared with the output of samples of observed events, which are enhanced in the particular flavor. In contrast to previous versions, no b-jet output correction function has to be calculated, because the agreement between simulation and collision data is excellent for b-quark jets. For the light-jet output, correction functions are developed. Different applications of the KIT Flavor Separator are mentioned. For example it provides a precious input to all three CDF single top quark analyses. Furthermore, it is shown that the KIT Flavor Separator is a universal tool, which can be used in every high-p T analysis that requires the identification of b-quark jets with high efficiency. As it is pointed out, a further application is the estimation of the flavor composition of a given sample of observed events. In addition a neural network, which is able to separate c-quark jets from light-quark jets, is trained. It is shown, that all three flavors can be separated in the c-net-Flavor Separator plane. As a result, the uncertainties on the estimation of the flavor composition in events with one tagged jet are cut into

  13. A new strategy for weak events in sparse networks: the first-motion polarity solutions constrained by single-station waveform inversion

    Czech Academy of Sciences Publication Activity Database

    Fojtíková, Lucia; Zahradník, J.

    2014-01-01

    Roč. 85, č. 6 (2014), s. 1265-1274 ISSN 0895-0695 R&D Projects: GA ČR GAP210/12/2336 Institutional support: RVO:67985891 Keywords : weak events * sparse networks * focal mechanism * waveform inversion Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 2.156, year: 2014 http://srl.geoscienceworld.org/content/85/6/1265.full

  14. Supramolecular self-assembly on the B-Si(111)-(√3x√3) R30° surface: From single molecules to multicomponent networks

    Science.gov (United States)

    Makoudi, Younes; Jeannoutot, Judicaël; Palmino, Frank; Chérioux, Frédéric; Copie, Guillaume; Krzeminski, Christophe; Cleri, Fabrizio; Grandidier, Bruno

    2017-09-01

    Understanding the physical and chemical processes in which local interactions lead to ordered structures is of particular relevance to the realization of supramolecular architectures on surfaces. While spectacular patterns have been demonstrated on metal surfaces, there have been fewer studies of the spontaneous organization of supramolecular networks on semiconductor surfaces, where the formation of covalent bonds between organics and adatoms usually hamper the diffusion of molecules and their subsequent interactions with each other. However, the saturation of the dangling bonds at a semiconductor surface is known to make them inert and offers a unique way for the engineering of molecular patterns on these surfaces. This review describes the physicochemical properties of the passivated B-Si(111)-(√3x√3) R30° surface, that enable the self-assembly of molecules into a rich variety of extended and regular structures on silicon. Particular attention is given to computational methods based on multi-scale simulations that allow to rationalize the relative contribution of the dispersion forces involved in the self-assembled networks observed with scanning tunneling microscopy. A summary of state of the art studies, where a fine tuning of the molecular network topology has been achieved, sheds light on new frontiers for exploiting the construction of supramolecular structures on semiconductor surfaces.

  15. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  16. NETWORK CODING BY BEAM FORMING

    DEFF Research Database (Denmark)

    2013-01-01

    Network coding by beam forming in networks, for example, in single frequency networks, can provide aid in increasing spectral efficiency. When network coding by beam forming and user cooperation are combined, spectral efficiency gains may be achieved. According to certain embodiments, a method...

  17. Integrated 10 Gb/s multilevel multiband passive optical network and 500 Mb/s indoor visible light communication system based on Nyquist single carrier frequency domain equalization modulation.

    Science.gov (United States)

    Wang, Yuanquan; Shi, Jianyang; Yang, Chao; Wang, Yiguang; Chi, Nan

    2014-05-01

    We propose and experimentally demonstrate a novel integrated passive optical network (PON) and indoor visible light communication (VLC) system based on Nyquist single carrier frequency domain equalization (N-SC-FDE) modulation with direct detection. In this system, a directly modulated laser and a commercially available red light emitting diode are served as the transmitters of the PON and VLC, respectively. To enable high spectral efficiency, high-speed transmission, and flexible multiple access with simplified optical network unit-side digital signal processing, multilevel, multiband quadrature amplitude modulations 128/64/16 are implemented here. VLC N-SC-FDE signals are successfully delivered a further 30 cm indoor distance after transmitting over a span of 40 km single mode fiber (SMF) together with 3 sub-band PON signals. As a proof of concept, a 10 Gb/s PON and 500 Mb/s VLC integrated system for three wired users and one wireless user is successfully achieved, which shows the promising potential and feasibility of this proposal to extend multiple services from metropolitan to suburban areas.

  18. Implementation of a kinematic fit of single top-quark production in association with a W boson and its application in a neural-network-based analysis in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Loddenkoetter, Thomas

    2012-08-15

    In order to provide discrimination between the Wt-channel signal and its backgrounds for analyses that try to measure single top-quark production in the Wt-channel, a kinematic fit to the lepton+jets decay mode of the Wt-channel has been implemented using the KLFitter package. The fit has been validated by studying its performance in terms of the efficiency of the fit to correctly assign the final-state quarks of the fit model to the measured jets as a function of various parameters, as well as the improvement of the energy resolutions of the fitted particles due to the fit. By combining the output variables of the kinematic fitter using neural networks, it has been shown that the fit results are suitable to identify the decay mode of the top quark in Wt events and to identify whether the kinematic fit succeeded in correctly assigning the final-state quarks to the measured jets. In order to demonstrate the value of the kinematic fit for analysis, another neural network - again using strictly results of the kinematic fit as input - has been trained to separate to the Wt-channel signal from its backgrounds. A separation power comparable to a conventional neural-network-based Wt-channel analysis has been achieved.

  19. Implementation of a kinematic fit of single top-quark production in association with a W boson and its application in a neural-network-based analysis in ATLAS

    International Nuclear Information System (INIS)

    Loddenkoetter, Thomas

    2012-08-01

    In order to provide discrimination between the Wt-channel signal and its backgrounds for analyses that try to measure single top-quark production in the Wt-channel, a kinematic fit to the lepton+jets decay mode of the Wt-channel has been implemented using the KLFitter package. The fit has been validated by studying its performance in terms of the efficiency of the fit to correctly assign the final-state quarks of the fit model to the measured jets as a function of various parameters, as well as the improvement of the energy resolutions of the fitted particles due to the fit. By combining the output variables of the kinematic fitter using neural networks, it has been shown that the fit results are suitable to identify the decay mode of the top quark in Wt events and to identify whether the kinematic fit succeeded in correctly assigning the final-state quarks to the measured jets. In order to demonstrate the value of the kinematic fit for analysis, another neural network - again using strictly results of the kinematic fit as input - has been trained to separate to the Wt-channel signal from its backgrounds. A separation power comparable to a conventional neural-network-based Wt-channel analysis has been achieved.

  20. Electrical Design and Evaluation of Asynchronous Serial Bus Communication Network of 48 Sensor Platform LSIs with Single-Ended I/O for Integrated MEMS-LSI Sensors

    Science.gov (United States)

    Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki

    2018-01-01

    For installing many sensors in a limited space with a limited computing resource, the digitization of the sensor output at the site of sensation has advantages such as a small amount of wiring, low signal interference and high scalability. For this purpose, we have developed a dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) (referred to as “sensor platform LSI”) for bus-networked Micro-Electro-Mechanical-Systems (MEMS)-LSI integrated sensors. In this LSI, collision avoidance, adaptation and event-driven functions are simply implemented to relieve data collision and congestion in asynchronous serial bus communication. In this study, we developed a network system with 48 sensor platform LSIs based on Printed Circuit Board (PCB) in a backbone bus topology with the bus length being 2.4 m. We evaluated the serial communication performance when 48 LSIs operated simultaneously with the adaptation function. The number of data packets received from each LSI was almost identical, and the average sampling frequency of 384 capacitance channels (eight for each LSI) was 73.66 Hz. PMID:29342923

  1. Stabilization of a Network of the FitzHugh–Nagumo Oscillators by Means of a Single Capacitor Based RC Filter Feedback Technique

    Directory of Open Access Journals (Sweden)

    Elena Adomaitienė

    2017-01-01

    Full Text Available We suggest employing the first-order stable RC filters, based on a single capacitor, for control of unstable fixed points in an array of oscillators. A single capacitor is sufficient to stabilize an entire array, if the oscillators are coupled strongly enough. An array, composed of 24 to 30 mean-field coupled FitzHugh–Nagumo (FHN type asymmetric oscillators, is considered as a case study. The investigation has been performed using analytical, numerical, and experimental methods. The analytical study is based on the mean-field approach, characteristic equation for finding the eigenvalue spectrum, and the Routh–Hurwitz stability criteria using low-rank Hurwitz matrix to calculate the threshold value of the coupling coefficient. Experiments have been performed with a hardware electronic analog, imitating dynamical behavior of an array of the FHN oscillators.

  2. Distributed Processing Using Single-chip Microcomputers

    National Research Council Canada - National Science Library

    Pritchett, William

    1996-01-01

    This project investigates the use of single-chip microprocessors as nodes in a token ring control network and explores the implementation of a protocol to manage communication across such a network...

  3. Biochemical characterization of the bi-lobe reveals a continuous structural network linking the bi-lobe to other single-copied organelles in Trypanosoma brucei.

    Science.gov (United States)

    Gheiratmand, Ladan; Brasseur, Anais; Zhou, Qing; He, Cynthia Y

    2013-02-01

    Trypanosoma brucei, a unicellular parasite, contains several single-copied organelles that duplicate and segregate in a highly coordinated fashion during the cell cycle. In the procyclic stage, a bi-lobed structure is found adjacent to the single ER exit site and Golgi apparatus, forming both stable and dynamic association with other cytoskeletal components including the basal bodies that seed the flagellum and the flagellar pocket collar that is critical for flagellar pocket biogenesis. To further understand the bi-lobe and its association with adjacent organelles, we performed proteomic analyses on the immunoisolated bi-lobe complex. Candidate proteins were localized to the flagellar pocket, the basal bodies, a tripartite attachment complex linking the basal bodies to the kinetoplast, and a segment of microtubule quartet linking the flagellar pocket collar and bi-lobe to the basal bodies. These results supported an extensive connection among the single-copied organelles in T. brucei, a strategy employed by the parasite for orderly organelle assembly and inheritance during the cell cycle.

  4. Multilayer Social Networks

    DEFF Research Database (Denmark)

    Dickison, Mark; Magnani, Matteo; Rossi, Luca

    Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate...... research communities, leading to the development of several independent models and methods to deal with the same set of problems. This book unifies and consolidates existing practical and theoretical knowledge on multilayer networks including data collection and analysis, modeling, and mining of multilayer...... social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various...

  5. Class network routing

    Science.gov (United States)

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

    2009-09-08

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

  6. Single neuron computation

    CERN Document Server

    McKenna, Thomas M; Zornetzer, Steven F

    1992-01-01

    This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real n

  7. A single-component multidrug transporter of the major facilitator superfamily is part of a network that protects Escherichia coli from bile salt stress.

    Science.gov (United States)

    Paul, Stephanie; Alegre, Kamela O; Holdsworth, Scarlett R; Rice, Matthew; Brown, James A; McVeigh, Paul; Kelly, Sharon M; Law, Christopher J

    2014-05-01

    Resistance to high concentrations of bile salts in the human intestinal tract is vital for the survival of enteric bacteria such as Escherichia coli. Although the tripartite AcrAB-TolC efflux system plays a significant role in this resistance, it is purported that other efflux pumps must also be involved. We provide evidence from a comprehensive suite of experiments performed at two different pH values (7.2 and 6.0) that reflect pH conditions that E. coli may encounter in human gut that MdtM, a single-component multidrug resistance transporter of the major facilitator superfamily, functions in bile salt resistance in E. coli by catalysing secondary active transport of bile salts out of the cell cytoplasm. Furthermore, assays performed on a chromosomal ΔacrB mutant transformed with multicopy plasmid encoding MdtM suggested a functional synergism between the single-component MdtM transporter and the tripartite AcrAB-TolC system that results in a multiplicative effect on resistance. Substrate binding experiments performed on purified MdtM demonstrated that the transporter binds to cholate and deoxycholate with micromolar affinity, and transport assays performed on inverted vesicles confirmed the capacity of MdtM to catalyse electrogenic bile salt/H(+) antiport. © 2014 The Authors. Molecular Microbiology published by John Wiley & Sons Ltd.

  8. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  9. Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing

    Directory of Open Access Journals (Sweden)

    M. Joseph Hughes

    2014-05-01

    Full Text Available The use of Landsat data to answer ecological questions is greatly increased by the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow. The method uses a neural network approach to determine cloud, cloud shadow, water, snow/ice and clear sky classification memberships of each pixel in a Landsat scene. It then applies a series of spatial procedures to resolve pixels with ambiguous membership by using information, such as the membership values of neighboring pixels and an estimate of cloud shadow locations from cloud and solar geometry. In a comparison with FMask, a high-quality cloud and cloud shadow classification algorithm currently available, SPARCS performs favorably, with substantially lower omission errors for cloud shadow (8.0% and 3.2%, only slightly higher omission errors for clouds (0.9% and 1.3%, respectively and fewer errors of commission (2.6% and 0.3%. Additionally, SPARCS provides a measure of uncertainty in its classification that can be exploited by other algorithms that require clear sky pixels. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of a method for vegetation change detection.

  10. Classroom Computer Network.

    Science.gov (United States)

    Lent, John

    1984-01-01

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

  11. Implementation of a kinematic fit of single top-quark production in association with a W boson and its implementation in a neural-network-based analysis in ATLAS

    CERN Document Server

    Loddenkötter, Thomas

    In order to provide discrimination between the $Wt$ channel signal and its backgrounds for analyses that try to measure single top-quark production in the $Wt$ channel, a kinematic fit to the lepton+jets decay mode of the $Wt$ channel has been implemented using the KLFitter package. The fit has been validated by studying its performance in terms of the efficiency of the fit to correctly assign the final-state quarks of the fit model to the measured jets as a function of various parameters, as well as the improvement of the energy resolutions of the fitted particles due to the fit. By combining the output variables of the kinematic fitter using neural networks, it has been shown that the fit results are suitable to identify the decay mode of the top quark in $Wt$ events and to identify whether the kinematic fit succeeded in correctly assigning the final-state quarks to the measured jets. In order to demonstrate the value of the kinematic fit for analysis, another neural network - again using strictly result...

  12. Ultrathin single-crystalline TiO2 nanosheets anchored on graphene to be hybrid network for high-rate and long cycle-life sodium battery electrode application

    Science.gov (United States)

    Shoaib, Anwer; Huang, Yongxin; Liu, Jia; Liu, Jiajia; Xu, Meng; Wang, Ziheng; Chen, Renjie; Zhang, Jiatao; Wu, Feng

    2017-02-01

    In view of the growing concern about energy management issues, sodium ion batteries (SIBs) as cheap and environmentally friendly devices have increasingly received wide research attentions. The high current rate and long cycle-life of SIBs are considered as two key parameters determining its potential for practical applications. In this work, the rigid single-crystalline anatase TiO2 nanosheets (NSs) with a thickness of ∼4 nm has been firstly prepared, based on which a stable nanostructured network consisting of ultrathin anatase TiO2 NSs homogeneously anchored on graphene through chemical bonding (TiO2 NSs-G) has fabricated by hydrothermal process and subsequent calcination treatment. The morphology, crystallization, chemical compositions and the intimate maximum contact between TiO2 NSs and graphene are confirmed by TEM, SEM, XRD, XPS and Raman characterizations. The results of electrochemical performance tests indicated that the TiO2 NSs-G hybrid network could be consider as a promising anode material for SIBs, in assessment of its remarkably high current rate and long cycle-life aside from the improved specific capacity, rate capability and cycle stability.

  13. The dynamics of networked power in a concentrated business network

    OpenAIRE

    Olsen, Per Ingvar; Prenkert, Frans; Hoholm, Thomas; Harrison, Debbie

    2014-01-01

    This is the authors' accepted and refereed manuscript to the article The purpose of this paper is to investigate the dynamics of networked power in a concentrated business network. Power is a long standing theme in inter-organisational research, yet there is a paucity of studies about how power emerges and is constructed over time at the network level. The paper adopts process, systems and network theory to interpret a rich single case study from the food industry. Three power mechanism...

  14. Biocatalytic Single Enzyme Nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Grate, Jay W.; Kim, Jungbae

    2004-03-31

    As an innovative way of enzyme stabilization, we recently developed a new enzyme composite of nano-meter scale that we call "single-enzyme nanoparticles (SENs)" (9). Each enzyme molecule is surrounded with a porous composite organic/inorganic network of less than a few nanometers think. This approach represents a new type of enzyme-containing nanostructure. In experiments with perotease (chymotrypsin, CT), the activity of single enzyme nanoparticle form of the enzyme was greatly stabilized compared to the free form, without imposing a serious mass transfer limitation of substrates. In this chapter we will describe the synthesis, characterization and catalytic activity of the new SENs.

  15. Measurement of the top quark mass in topologies enhanced with single top-quarks produced in the $t$-channel using flavour-tagging and a neural network with ATLAS data at $\\sqrt{s} = 8\\,\\mathrm{TeV}$

    CERN Document Server

    Esch, Hendrik

    In this thesis a measurement of the top quark mass in topologies that have been enhanced with single-top quark decays in the $t$-channel produced via weak interactions is presented. The dataset consists of proton-proton collisions at a centre-of-mass energy of $\\sqrt{s}=8\\,\\mathrm{TeV}$ collected with the ATLAS detector at the LHC with a total integrated luminosity of $\\mathcal{L}_{\\mathrm{int}} =20.3\\,\\mathrm{fb^{-1}}$. Selected events contain exactly one charged lepton - which can be either an electron or a muon -, missing transverse energy and two jets with exactly one of the two being $b$-tagged. The techniques of $b$-tagging used to identify jets induced by heavy quarks is explained further. In addition, the signal is enhanced using a neural network based discriminant that combines the ability to discriminate between signal and background of several correlated variables. To determine the mass of the top quark a template method is used in combination with the mass sensitive variable, $m(\\ell b)$, which i...

  16. A network security monitor

    Energy Technology Data Exchange (ETDEWEB)

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

    1989-11-01

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

  17. On Heterogeneous Covert Networks

    Science.gov (United States)

    Lindelauf, Roy; Borm, Peter; Hamers, Herbert

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

  18. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  19. Celestial data routing network

    Science.gov (United States)

    Bordetsky, Alex

    2000-11-01

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

  20. Heterogeneous broadband network

    Science.gov (United States)

    Dittmann, Lars

    1995-11-01

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

  1. BES Science Network Requirements

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-02-01

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

  2. BES Science Network Requirements

    International Nuclear Information System (INIS)

    Dart, Eli; Tierney, Brian; Biocca, A.; Carlson, R.; Chen, J.; Cotter, S.; Dattoria, V.; Davenport, J.; Gaenko, A.; Kent, P.; Lamm, M.; Miller, S.; Mundy, C.; Ndousse, T.; Pederson, M.; Perazzo, A.; Popescu, R.; Rouson, D.; Sekine, Y.; Sumpter, B.; Wang, C.-Z.; Whitelam, S.; Zurawski, J.

    2011-01-01

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

  3. Optical storage networking

    Science.gov (United States)

    Mohr, Ulrich

    2001-11-01

    For efficient business continuance and backup of mission- critical data an inter-site storage network is required. Where traditional telecommunications costs are prohibitive for all but the largest organizations, there is an opportunity for regional carries to deliver an innovative storage service. This session reveals how a combination of optical networking and protocol-aware SAN gateways can provide an extended storage networking platform with the lowest cost of ownership and the highest possible degree of reliability, security and availability. Companies of every size, with mainframe and open-systems environments, can afford to use this integrated service. Three mayor applications are explained; channel extension, Network Attached Storage (NAS), Storage Area Networks (SAN) and how optical networks address the specific requirements. One advantage of DWDM is the ability for protocols such as ESCON, Fibre Channel, ATM and Gigabit Ethernet, to be transported natively and simultaneously across a single fiber pair, and the ability to multiplex many individual fiber pairs over a single pair, thereby reducing fiber cost and recovering fiber pairs already in use. An optical storage network enables a new class of service providers, Storage Service Providers (SSP) aiming to deliver value to the enterprise by managing storage, backup, replication and restoration as an outsourced service.

  4. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago Vanderlei; Giannitsarou, Chrysi; Johnson, CR

    2017-01-01

    We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and define a network aggregator that preserves network cohesion.

  5. Network cosmology.

    Science.gov (United States)

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

    2012-01-01

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

  6. The network researchers' network

    DEFF Research Database (Denmark)

    Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter

    2009-01-01

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi...

  7. Herding Complex Networks

    KAUST Repository

    Ruf, Sebastian F.

    2018-04-12

    The problem of controlling complex networks is of interest to disciplines ranging from biology to swarm robotics. However, controllability can be too strict a condition, failing to capture a range of desirable behaviors. Herdability, which describes the ability to drive a system to a specific set in the state space, was recently introduced as an alternative network control notion. This paper considers the application of herdability to the study of complex networks. The herdability of a class of networked systems is investigated and two problems related to ensuring system herdability are explored. The first is the input addition problem, which investigates which nodes in a network should receive inputs to ensure that the system is herdable. The second is a related problem of selecting the best single node from which to herd the network, in the case that a single node is guaranteed to make the system is herdable. In order to select the best herding node, a novel control energy based herdability centrality measure is introduced.

  8. 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

  9. Thermoelectric properties of semiconductor nanowire networks

    Science.gov (United States)

    Roslyak, Oleksiy; Piryatinski, Andrei

    2016-03-01

    To examine the thermoelectric (TE) properties of a semiconductor nanowire (NW) network, we propose a theoretical approach mapping the TE network on a two-port network. In contrast to a conventional single-port (i.e., resistor) network model, our model allows for large scale calculations showing convergence of TE figure of merit, ZT, with an increasing number of junctions. Using this model, numerical simulations are performed for the Bi2Te3 branched nanowire (BNW) and Cayley tree NW (CTNW) network. We find that the phonon scattering at the network junctions plays a dominant role in enhancing the network ZT. Specifically, disordered BNW and CTNW demonstrate an order of magnitude higher ZT enhancement compared to their ordered counterparts. Formation of preferential TE pathways in CTNW makes the network effectively behave as its BNW counterpart. We provide formalism for simulating large scale nanowire networks hinged upon experimentally measurable TE parameters of a single T-junction.

  10. WE-AB-204-06: Pseudo-CT Generation Using Undersampled, Single-Acquisition UTE-MDixon and Direct-Mapping Artificial Neural Networks for MR-Based Attenuation Correction and Radiation Therapy Planning

    Energy Technology Data Exchange (ETDEWEB)

    Su, K; Kuo, J [Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio (United States); Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Hu, L; Traughber, M [Philips Healthcare, Cleveland, Ohio (United States); Pereira, G; Traughber, B [Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, Ohio (United States); Herrmann, K [Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio (United States); Muzic, R [Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio (United States); Department of Radiology, University Hospitals Case Medical Center, Case Western Reserve University, Cleveland, Ohio (United States); Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH (United States)

    2015-06-15

    Purpose: Emerging technologies such as dedicated PET/MRI and MR-therapy systems require robust and clinically practical methods for determining photon attenuation. Herein, we propose using novel MR acquisition methods and processing for the generation of pseudo-CTs. Methods: A single acquisition, 190-second UTE-mDixon sequence with 25% (angular) sampling density and 3D radial readout was performed on nine volunteers. Three water-filled tubes were placed in the FOV for trajectory-delay correction. The MR data were reconstructed to generate three primitive images acquired at TEs of 0.1, 1.5 and 2.8 ms. In addition, three derived MR images were generated, i.e. two-point Dixon water/fat separation and R2* (1/T2*) map. Furthermore, two spatial features, i.e. local binary pattern (S-1) and relative spatial coordinates (S-2), were incorporated. A direct-mapping operator was generated using Artificial Neural Networks (ANNs) for transforming the MR features to a pseudo-CT. CT images served as the training data and, using a leave-one-out method, for performance evaluation using mean prediction deviation (MPD), mean absolute prediction deviation (MAPD), and correlation coefficient (R). Results: The errors between measured CT and pseudo-CT declined dramatically when the spatial features, i.e. S-1 and S-2, were included. The MPD, MAPD, and R were, respectively, 5±57 HU, 141±41 HU, and 0.815±0.066 for results generated by the ANN trained without the spatial features and were 32±26 HU, 115±18 HU, and 0.869±0.035 with the spatial features. The estimation errors of the pseudo-CT were smaller when both the S-1 and S-2 were used together than when either the S-1 or the S-2 was used. Pseudo-CT generation (256×256×256 voxels) by ANN took < 0.5 s using a computer having an Intel i7 3.4GHz CPU and 16 GB RAM. Conclusion: The proposed direct-mapping ANN approach is a technically accurate, clinically practical method for pseudo-CT generation and can potentially help improve the

  11. Multi-agent model predictive control for transportation networks : Serial versus parallel schemes

    NARCIS (Netherlands)

    Negenborn, R.R.; De Schutter, B.; Hellendoorn, J.

    2006-01-01

    We consider the control of large-scale transportation networks, like road traffic networks, power distribution networks, water distribution networks, etc. Control of these networks is often not possible from a single point by a single intelligent control agent; instead control has to be performed

  12. Networks in the news media

    DEFF Research Database (Denmark)

    Bro, Peter

    When news reporters connect people in a single news story or in a series of coherent news stories they essentially construct networks in the news media. Networks through which social actors are aligned symbolically in written, visible or audible form. These socio-symbolic networks not only copy...... more formal types of social networks, but also complement or even substitute social networking elsewhere, and as such this particular type of social network offers people both inside and outside the news room new potentials - and problems. This article describe the basic vision of networks in the news...... media and discuss the importance of this analytical framework when it comes to understanding prevailing forms and norms in contemporary journalism....

  13. NP Science Network Requirements

    Energy Technology Data Exchange (ETDEWEB)

    Dart, Eli [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Rotman, Lauren [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Tierney, Brian [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

    2011-08-26

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

  14. Recurrent Spatial Transformer Networks

    DEFF Research Database (Denmark)

    Sønderby, Søren Kaae; Sønderby, Casper Kaae; Maaløe, Lars

    2015-01-01

    We integrate the recently proposed spatial transformer network (SPN) [Jaderberg et. al 2015] into a recurrent neural network (RNN) to form an RNN-SPN model. We use the RNN-SPN to classify digits in cluttered MNIST sequences. The proposed model achieves a single digit error of 1.5% compared to 2.......9% for a convolutional networks and 2.0% for convolutional networks with SPN layers. The SPN outputs a zoomed, rotated and skewed version of the input image. We investigate different down-sampling factors (ratio of pixel in input and output) for the SPN and show that the RNN-SPN model is able to down-sample the input...

  15. 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.

  16. Network class superposition analyses.

    Directory of Open Access Journals (Sweden)

    Carl A B Pearson

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

  17. Network maintenance

    CERN Multimedia

    GS Department

    2009-01-01

    A site-wide network maintenance operation has been scheduled for Saturday 28 February. Most of the network devices of the general purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites throughout the day. This upgrade will not affect the Computer Centre itself, Building 613, the Technical Network and the LHC experiments, dedicated networks at the pits. For further details of this intervention, please contact Netops by phone 74927 or e-mail mailto:Netops@cern.ch. IT/CS Group

  18. Network maintenance

    CERN Multimedia

    IT Department

    2009-01-01

    A site wide network maintenance has been scheduled for Saturday 28 February. Most of the network devices of the General Purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites along this day. This upgrade will not affect: the Computer centre itself, building 613, the Technical Network and the LHC experiments dedicated networks at the pits. Should you need more details on this intervention, please contact Netops by phone 74927 or email mailto:Netops@cern.ch. IT/CS Group

  19. Network Ambivalence

    Directory of Open Access Journals (Sweden)

    Patrick Jagoda

    2015-08-01

    Full Text Available The language of networks now describes everything from the Internet to the economy to terrorist organizations. In distinction to a common view of networks as a universal, originary, or necessary form that promises to explain everything from neural structures to online traffic, this essay emphasizes the contingency of the network imaginary. Network form, in its role as our current cultural dominant, makes scarcely imaginable the possibility of an alternative or an outside uninflected by networks. If so many things and relationships are figured as networks, however, then what is not a network? If a network points towards particular logics and qualities of relation in our historical present, what others might we envision in the future? In  many ways, these questions are unanswerable from within the contemporary moment. Instead of seeking an avant-garde approach (to move beyond networks or opting out of networks (in some cases, to recover elements of pre-networked existence, this essay proposes a third orientation: one of ambivalence that operates as a mode of extreme presence. I propose the concept of "network aesthetics," which can be tracked across artistic media and cultural forms, as a model, style, and pedagogy for approaching interconnection in the twenty-first century. The following essay is excerpted from Network Ambivalence (Forthcoming from University of Chicago Press. 

  20. Deploying temporary networks for upscaling of sparse network stations

    Science.gov (United States)

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

    2016-10-01

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

  1. Network neuroscience.

    Science.gov (United States)

    Bassett, Danielle S; Sporns, Olaf

    2017-02-23

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

  2. Network Science

    National Research Council Canada - National Science Library

    Leland, Will

    2006-01-01

    OVERVIEW: (1) A committee of technical experts, military officers and R&D managers was assembled by the National Research Council to reach consensus on the nature of networks and network research. (2...

  3. Modeling of wavelength multiplexing networks for storage area networking

    Science.gov (United States)

    Carranza, Aparicio; DeCusatis, Casimer M.

    2004-09-01

    Recently, there has been increased interest in the use of optical networks for disaster recovery of large computer systems by extending storage area networks (SANs) over hundreds of kilometers or more. These optical datacom networks, which incorporate wavelength division multiplexing (WDM), have several unique requirements. The purpose of this work has been to develop computer simulation tools for optical datacom networks. The models are capable of automatically designing a WDM network configuration based on minimal input; validating the design against any protocol-specific requirements; suggesting alternative configurations; and optimizing the design based on metrics including performance of the network (efficient use of bandwidth to support the attached computing devices), reliability (searching the proposed topology for single points of failure), scalability (based on user input of potential future upgrade paths), and cost of the associated networking equipment. The model incorporates typical computer performance data, which allows the prediction of system performance before the network is implemented. We present simulation results for a variety of MAN topologies, using currently available WDM networking equipment. These results have been validated by comparison with an enterprise optical networking testbed constructed for storage area networks.

  4. Alliance networks

    OpenAIRE

    Sroka, Władzimierz

    2015-01-01

    The article deals with the problems of cooperation in network organizations. The structure of the text is divided into a couple of parts. Firstly, the increasing importance of alliance networks is described. Secondly, the concept of alliance networks as well as the essence of multinational corporations are presented. Beside theoretical deliberations, two practical cases are presented in the text too. First case relates to the Toyota keiretsu and the second one describes the network organizati...

  5. Network Simulation

    CERN Document Server

    Fujimoto, Richard

    2006-01-01

    "Network Simulation" presents a detailed introduction to the design, implementation, and use of network simulation tools. Discussion topics include the requirements and issues faced for simulator design and use in wired networks, wireless networks, distributed simulation environments, and fluid model abstractions. Several existing simulations are given as examples, with details regarding design decisions and why those decisions were made. Issues regarding performance and scalability are discussed in detail, describing how one can utilize distributed simulation methods to increase the

  6. Network Coding

    Indian Academy of Sciences (India)

    message symbols downstream, network coding achieves vast performance gains by permitting intermediate nodes to carry out algebraic oper- ations on the incoming data. In this article we present a tutorial introduction to network coding as well as an application to the e±cient operation of distributed data-storage networks.

  7. Network Coding

    Indian Academy of Sciences (India)

    Network coding is a technique to increase the amount of information °ow in a network by mak- ing the key observation that information °ow is fundamentally different from commodity °ow. Whereas, under traditional methods of opera- tion of data networks, intermediate nodes are restricted to simply forwarding their incoming.

  8. Mathematical Formulation of Multilayer Networks

    Science.gov (United States)

    De Domenico, Manlio; Solé-Ribalta, Albert; Cozzo, Emanuele; Kivelä, Mikko; Moreno, Yamir; Porter, Mason A.; Gómez, Sergio; Arenas, Alex

    2013-10-01

    A network representation is useful for describing the structure of a large variety of complex systems. However, most real and engineered systems have multiple subsystems and layers of connectivity, and the data produced by such systems are very rich. Achieving a deep understanding of such systems necessitates generalizing “traditional” network theory, and the newfound deluge of data now makes it possible to test increasingly general frameworks for the study of networks. In particular, although adjacency matrices are useful to describe traditional single-layer networks, such a representation is insufficient for the analysis and description of multiplex and time-dependent networks. One must therefore develop a more general mathematical framework to cope with the challenges posed by multilayer complex systems. In this paper, we introduce a tensorial framework to study multilayer networks, and we discuss the generalization of several important network descriptors and dynamical processes—including degree centrality, clustering coefficients, eigenvector centrality, modularity, von Neumann entropy, and diffusion—for this framework. We examine the impact of different choices in constructing these generalizations, and we illustrate how to obtain known results for the special cases of single-layer and multiplex networks. Our tensorial approach will be helpful for tackling pressing problems in multilayer complex systems, such as inferring who is influencing whom (and by which media) in multichannel social networks and developing routing techniques for multimodal transportation systems.

  9. 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

  10. Network workshop

    DEFF Research Database (Denmark)

    Bruun, Jesper; Evans, Robert Harry

    2014-01-01

    This paper describes the background for, realisation of and author reflections on a network workshop held at ESERA2013. As a new research area in science education, networks offer a unique opportunity to visualise and find patterns and relationships in complicated social or academic network data...... research community. With this workshop, participants were offered a way into network science based on authentic educational research data. The workshop was constructed as an inquiry lesson with emphasis on user autonomy. Learning activities had participants choose to work with one of two cases of networks...

  11. Network science

    CERN Document Server

    Barabasi, Albert-Laszlo

    2016-01-01

    Networks are everywhere, from the Internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate and graduate level material. The mathematical formulas and derivations are included within Advanced Topics sections, enabling use at a range of levels. Extensive online resources, including films and software for network analysis, make this a multifaceted companion for anyone with an interest in network sci...

  12. Brand Marketing Model on Social Networks

    Directory of Open Access Journals (Sweden)

    Jolita Jezukevičiūtė

    2014-04-01

    Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

  13. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  14. MIMO Communication for Cellular Networks

    CERN Document Server

    Huang, Howard; Venkatesan, Sivarama

    2012-01-01

    As the theoretical foundations of multiple-antenna techniques evolve and as these multiple-input multiple-output (MIMO) techniques become essential for providing high data rates in wireless systems, there is a growing need to understand the performance limits of MIMO in practical networks. To address this need, MIMO Communication for Cellular Networks presents a systematic description of MIMO technology classes and a framework for MIMO system design that takes into account the essential physical-layer features of practical cellular networks. In contrast to works that focus on the theoretical performance of abstract MIMO channels, MIMO Communication for Cellular Networks emphasizes the practical performance of realistic MIMO systems. A unified set of system simulation results highlights relative performance gains of different MIMO techniques and provides insights into how best to use multiple antennas in cellular networks under various conditions. MIMO Communication for Cellular Networks describes single-user,...

  15. Shape-Shifting Droplet Networks.

    Science.gov (United States)

    Zhang, T; Wan, Duanduan; Schwarz, J M; Bowick, M J

    2016-03-11

    We consider a three-dimensional network of aqueous droplets joined by single lipid bilayers to form a cohesive, tissuelike material. The droplets in these networks can be programed to have distinct osmolarities so that osmotic gradients generate internal stresses via local fluid flows to cause the network to change shape. We discover, using molecular dynamics simulations, a reversible folding-unfolding process by adding an osmotic interaction with the surrounding environment which necessarily evolves dynamically as the shape of the network changes. This discovery is the next important step towards osmotic robotics in this system. We also explore analytically and numerically how the networks become faceted via buckling and how quasi-one-dimensional networks become three dimensional.

  16. A-Source Impedance Network

    DEFF Research Database (Denmark)

    Siwakoti, Yam Prasad; Blaabjerg, Frede; Galigekere, Veda Prakash

    2016-01-01

    A novel A-source impedance network is proposed in this letter. The A-source impedance network uses an autotransformer for realizing converters for any application that demand a very high dc voltage gain. The network utilizes a minimal turns ratio compared to other Magnetically Coupled Impedance S...... with an example single-switch 400 W dc-dc converter. For the closed-loop control design and stability assessment, a small signal model and its analysis of the proposed network are also presented in brief....... Source (MCIS) networks to attain a high voltage gain. In addition, the proposed converter draws a continuous current from the source, and hence it is suitable for many types of renewable energy sources. The derived network expressions and theoretical analysis are finally validated experimentally...

  17. Neural networks and statistical learning

    CERN Document Server

    Du, Ke-Lin

    2014-01-01

    Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...

  18. Single liner shipping service design

    DEFF Research Database (Denmark)

    Plum, Christian Edinger Munk; Pisinger, David; Salazar-González, Juan-José

    2014-01-01

    The design of container shipping networks is an important logistics problem, involving assets and operational costs measured in billions of dollars. To guide the optimal deployment of the ships, a single vessel round trip is considered by minimizing operational costs and flowing the best paying...... demand under commercially driven constraints. This paper introduces the Single Liner Shipping Service Design Problem. Arc-flow and path-flow models are presented using state-of-the-art elements from the wide literature on pickup and delivery problems. A Branch-and-Cut-and-Price algorithm is proposed...

  19. Tinnitus: Network pathophysiology-network pharmacology

    Directory of Open Access Journals (Sweden)

    Ana Belen eElgoyhen

    2012-01-01

    Full Text Available Tinnitus, the phantom perception of sound, is a prevalent disorder. One in 10 adults has clinically significant subjective tinnitus, and for 1 in 100, tinnitus severely affects their quality of life. Despite the significant unmet clinical need for a safe and effective drug targeting tinnitus relief, there is currently not a single FDA-approved drug on the market. The search for drugs that target tinnitus is hampered by the lack of a deep knowledge of the underlying neural substrates of this pathology. Recent studies are increasingly demonstrating that, as described for other central nervous system disorders, tinnitus is a pathology of brain networks. The application of graph theoretical analysis to brain networks has recently provided new information concerning their topology, their robustness and their vulnerability to attacks. Moreover, the philosophy behind drug design and pharmacotherapy in central nervous system pathologies is changing from that of magic bullets that target individual chemoreceptors or disease-causing genes into that of magic shotguns, promiscuous or dirty drugs that target disease-causing networks, also known as network pharmacology. In the present work we provide some insight into how this knowledge could be applied to tinnitus pathophysiology and pharmacotherapy.

  20. Tinnitus: network pathophysiology-network pharmacology.

    Science.gov (United States)

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

    2012-01-01

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

  1. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Krigslund, Jeppe; Hansen, Jonas; Roetter, Daniel Enrique Lucani

    2015-01-01

    incorporate content caching and storage, all of which are key challenges of the future Internet and the upcoming 5G networks. This paper proposes some of the keys behind this intersection and supports it with use cases as well as a an implementation that integrated the Kodo library (NC) into OpenFlow (SDN......Software Defined Networking (SDN) and Network Coding (NC) are two key concepts in networking that have garnered a large attention in recent years. On the one hand, SDN's potential to virtualize services in the Internet allows a large flexibility not only for routing data, but also to manage...... buffering, scheduling, and processing over the network. On the other hand, NC has shown great potential for increasing robustness and performance when deployed on intermediate nodes in the network. This new paradigm changes the dynamics of network protocols, requiring new designs that exploit its potential...

  2. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Hansen, Jonas; Roetter, Daniel Enrique Lucani; Krigslund, Jeppe

    2015-01-01

    Software defined networking has garnered large attention due to its potential to virtualize services in the Internet, introducing flexibility in the buffering, scheduling, processing, and routing of data in network routers. SDN breaks the deadlock that has kept Internet network protocols stagnant...... for decades, while applications and physical links have evolved. This article advocates for the use of SDN to bring about 5G network services by incorporating network coding (NC) functionalities. The latter constitutes a major leap forward compared to the state-of-the- art store and forward Internet paradigm....... The inherent flexibility of both SDN and NC provides fertile ground to envision more efficient, robust, and secure networking designs, which may also incorporate content caching and storage, all of which are key challenges of the upcoming 5G networks. This article not only proposes the fundamentals...

  3. Stages of neuronal network formation

    Science.gov (United States)

    Woiterski, Lydia; Claudepierre, Thomas; Luxenhofer, Robert; Jordan, Rainer; Käs, Josef A.

    2013-02-01

    Graph theoretical approaches have become a powerful tool for investigating the architecture and dynamics of complex networks. The topology of network graphs revealed small-world properties for very different real systems among these neuronal networks. In this study, we observed the early development of mouse retinal ganglion cell (RGC) networks in vitro using time-lapse video microscopy. By means of a time-resolved graph theoretical analysis of the connectivity, shortest path length and the edge length, we were able to discover the different stages during the network formation. Starting from single cells, at the first stage neurons connected to each other ending up in a network with maximum complexity. In the further course, we observed a simplification of the network which manifested in a change of relevant network parameters such as the minimization of the path length. Moreover, we found that RGC networks self-organized as small-world networks at both stages; however, the optimization occurred only in the second stage.

  4. Innovation networks

    OpenAIRE

    Ahrweiler, Petra; Keane, Mark T.

    2013-01-01

    This paper advances a framework for modeling the component interactions between cognitive and social aspects of scientific creativity and technological innovation. Specifically, it aims to characterize Innovation Networks; those networks that involve the interplay of people, ideas and organizations to create new, technologically feasible, commercially-realizable products, processes and organizational structures. The tri-partite framework captures networks of ideas (Concept Level), people (Ind...

  5. Overlay Network

    OpenAIRE

    Kronstrand, Alexander; Holmqvist, Andreas

    2015-01-01

    Nowadays, optical fiber is widely used in several areas, especially in communication networking. The main reason is that optical fiber has low attenuation and high bandwidth. However, the switching functionality is performed in the electrical domain (inside the router), thus we have transmission delays in the network lanes. In this study we explore the possibility of developing a hardware “plug-in” that can be connected in parallel with routers of the network enabling the router with “plug-in...

  6. 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

  7. Network security

    CERN Document Server

    Perez, André

    2014-01-01

    This book introduces the security mechanisms deployed in Ethernet, Wireless-Fidelity (Wi-Fi), Internet Protocol (IP) and MultiProtocol Label Switching (MPLS) networks. These mechanisms are grouped throughout the book according to the following four functions: data protection, access control, network isolation, and data monitoring. Data protection is supplied by data confidentiality and integrity control services. Access control is provided by a third-party authentication service. Network isolation is supplied by the Virtual Private Network (VPN) service. Data monitoring consists of applying

  8. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago V. V.; Giannitsarou, Chryssi; Johnson, Charles R.

    2016-01-01

    This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00199-016-0992-1 We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and d...

  9. LINCS: Livermore's network architecture

    International Nuclear Information System (INIS)

    Fletcher, J.G.

    1982-01-01

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

  10. Statistical Mechanics of Temporal and Interacting Networks

    Science.gov (United States)

    Zhao, Kun

    In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide

  11. Community Detection for Multiplex Social Networks Based on Relational Bayesian Networks

    DEFF Research Database (Denmark)

    Jiang, Jiuchuan; Jaeger, Manfred

    2014-01-01

    Many techniques have been proposed for community detection in social networks. Most of these techniques are only designed for networks defined by a single relation. However, many real networks are multiplex networks that contain multiple types of relations and different attributes on the nodes...... to express different models capturing different aspects of community detection in multiplex networks in a coherent manner, and to use a single inference mechanism for all models........ In this paper we propose to use relational Bayesian networks for the specification of probabilistic network models, and develop inference techniques that solve the community detection problem based on these models. The use of relational Bayesian networks as a flexible high-level modeling framework enables us...

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

    Science.gov (United States)

    Chopra, Shauhrat S; Khanna, Vikas

    2014-08-01

    Industrial symbiotic networks are based on the principles of ecological systems where waste equals food, to develop synergistic networks. For example, industrial symbiosis (IS) at Kalundborg, Denmark, creates an exchange network of waste, water, and energy among companies based on contractual dependency. Since most of the industrial symbiotic networks are based on ad-hoc opportunities rather than strategic planning, gaining insight into disruptive scenarios is pivotal for understanding the balance of resilience and sustainability and developing heuristics for designing resilient IS networks. The present work focuses on understanding resilience as an emergent property of an IS network via a network-based approach with application to the Kalundborg Industrial Symbiosis (KIS). Results from network metrics and simulated disruptive scenarios reveal Asnaes power plant as the most critical node in the system. We also observe a decrease in the vulnerability of nodes and reduction in single points of failure in the system, suggesting an increase in the overall resilience of the KIS system from 1960 to 2010. Based on our findings, we recommend design strategies, such as increasing diversity, redundancy, and multi-functionality to ensure flexibility and plasticity, to develop resilient and sustainable industrial symbiotic networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Overlay networks toward information networking

    CERN Document Server

    Tarkoma, Sasu

    2010-01-01

    With their ability to solve problems in massive information distribution and processing, while keeping scaling costs low, overlay systems represent a rapidly growing area of R&D with important implications for the evolution of Internet architecture. Inspired by the author's articles on content based routing, Overlay Networks: Toward Information Networking provides a complete introduction to overlay networks. Examining what they are and what kind of structures they require, the text covers the key structures, protocols, and algorithms used in overlay networks. It reviews the current state of th

  14. Network Protocols

    NARCIS (Netherlands)

    Tanenbaum, A.S.

    1981-01-01

    Dunng the last ten years, many computer networks have been designed, implemented, and put into service in the United States, Canada, Europe, Japan, and elsewhere. From the experience obtamed with these networks, certain key design principles have begun to emerge, principles that can be used to

  15. Organizational Networks

    DEFF Research Database (Denmark)

    Sørensen, Ole Henning; Grande, Bård

    1996-01-01

    The paper focuses on the concept of organizational networks. Four different uses of the concept are identified and critically discussed.......The paper focuses on the concept of organizational networks. Four different uses of the concept are identified and critically discussed....

  16. Bipartite Networks

    NARCIS (Netherlands)

    Agneessens, F.; Moser, C.; Barnett, G.A.

    2011-01-01

    Bipartite networks refer to a specific kind of network in which the nodes (or actors) can be partitioned into two subsets based on the fact that no links exist between actors within each subset, but only between the two subsets. Due to the partition of actors in two sets and the absence of relations

  17. Probabilistic Networks

    DEFF Research Database (Denmark)

    Jensen, Finn Verner; Lauritzen, Steffen Lilholt

    2001-01-01

    This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs.......This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs....

  18. Networked Identities

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Larsen, Malene Charlotte

    2008-01-01

    In this article we take up a critique of the concept of Communities of Practice (CoP) voiced by several authors, who suggest that networks may provide a better metaphor to understand social forms of organisation and learning. Through a discussion of the notion of networked learning and the critique...

  19. Network Affordances

    DEFF Research Database (Denmark)

    Samson, Audrey; Soon, Winnie

    2015-01-01

    This paper examines the notion of network affordance within the context of network art. Building on Gibson's theory (Gibson, 1979) we understand affordance as the perceived and actual parameters of a thing. We expand on Gaver's affordance of predictability (Gaver, 1996) to include ecological...... and computational parameters of unpredictability. We illustrate the notion of unpredictability by considering four specific works that were included in a network art exhibiton, SPEED SHOW [2.0] Hong Kong. The paper discusses how the artworks are contingent upon the parameteric relations (Parisi, 2013......), of the network. We introduce network affordance as a dynamic framework that could articulate the experienced tension arising from the (visible) symbolic representation of computational processes and its hidden occurrences. We base our proposal on the experience of both organising the SPEED SHOW and participating...

  20. 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...... of organisationalbehaviour developed by Miles and Snow (1978), this paper argues that thepatterns of network behaviour practiced by firms greatly depend on the businesstypology of the company. That is, a company's business typology will to a certaindegree dictate the network identity of the company. In this paper evidence...... elementsdistinguishing the types of network behaviour in relation to the business typology.The paper thus strives to argue how different business typologies develop anetwork identity on the basis of their network behaviour. Due to the correlationbetween a company's strategy, structure and processes and its pattern...

  1. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  2. Asynchronous control for networked systems

    CERN Document Server

    Rubio, Francisco; Bencomo, Sebastián

    2015-01-01

    This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

  3. Technological Networks

    Science.gov (United States)

    Mitra, Bivas

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

  4. 3D network single-phase Ni0.9Zn0.1O as anode materials for lithium-ion batteries

    DEFF Research Database (Denmark)

    Huang, Guoyong; Guo, Xueyi; Cao, Xiao

    2016-01-01

    two-step Li-ion storage mechanism in the 3D network single−phase Ni0.9Zn0.1O has been discovered and verified to be: a reversible conversion reaction between Ni0.9Zn0.1O and Ni-Zn alloy (Ni0.9Zn0.1), and a reversible Li-alloying reaction between Ni-Zn alloy and Ni0.9Zn0.1Li. More remarkably, due...

  5. Dynamic and interacting complex networks

    Science.gov (United States)

    Dickison, Mark E.

    individuals protect themselves by disconnecting their links to infected neighbors with probability w and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold wc separating a phase (w wc) where the disease does not spread out. We find that in our model the topology of the network strongly affects the size of the propagation and that wc increases with the mean degree and heterogeneity of the network. We also find that wc is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes. In the fourth chapter, we study epidemic processes on interconnected network systems, and find two distinct regimes. In strongly-coupled network systems, epidemics occur simultaneously across the entire system at a critical value betac. In contrast, in weakly-coupled network systems, a mixed phase exists below betac where an epidemic occurs in one network but does not spread to the coupled network. We derive an expression for the network and disease parameters that allow this mixed phase and verify it numerically. Public health implications of communities comprising these two classes of network systems are also mentioned.

  6. Fluctuations in percolation of sparse complex networks

    Science.gov (United States)

    Bianconi, Ginestra

    2017-07-01

    We study the role of fluctuations in percolation of sparse complex networks. To this end we consider two random correlated realizations of the initial damage of the nodes and we evaluate the fraction of nodes that are expected to remain in the giant component of the network in both cases or just in one case. Our framework includes a message-passing algorithm able to predict the fluctuations in a single network, and an analytic prediction of the expected fluctuations in ensembles of sparse networks. This approach is applied to real ecological and infrastructure networks and it is shown to characterize the expected fluctuations in their response to external damage.

  7. Distributed medium access control in wireless networks

    CERN Document Server

    Wang, Ping

    2013-01-01

    This brief investigates distributed medium access control (MAC) with QoS provisioning for both single- and multi-hop wireless networks including wireless local area networks (WLANs), wireless ad hoc networks, and wireless mesh networks. For WLANs, an efficient MAC scheme and a call admission control algorithm are presented to provide guaranteed QoS for voice traffic and, at the same time, increase the voice capacity significantly compared with the current WLAN standard. In addition, a novel token-based scheduling scheme is proposed to provide great flexibility and facility to the network servi

  8. Accelerating networks

    International Nuclear Information System (INIS)

    Smith, David M D; Onnela, Jukka-Pekka; Johnson, Neil F

    2007-01-01

    Evolving out-of-equilibrium networks have been under intense scrutiny recently. In many real-world settings the number of links added per new node is not constant but depends on the time at which the node is introduced in the system. This simple idea gives rise to the concept of accelerating networks, for which we review an existing definition and-after finding it somewhat constrictive-offer a new definition. The new definition provided here views network acceleration as a time dependent property of a given system as opposed to being a property of the specific algorithm applied to grow the network. The definition also covers both unweighted and weighted networks. As time-stamped network data becomes increasingly available, the proposed measures may be easily applied to such empirical datasets. As a simple case study we apply the concepts to study the evolution of three different instances of Wikipedia, namely, those in English, German, and Japanese, and find that the networks undergo different acceleration regimes in their evolution

  9. 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

  10. 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

  11. Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

    Directory of Open Access Journals (Sweden)

    Xi Jin

    2015-01-01

    Full Text Available The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the method A-MM is tighter than or equal to that computed by the method N-MM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the large-scale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.

  12. computer networks

    Directory of Open Access Journals (Sweden)

    N. U. Ahmed

    2002-01-01

    Full Text Available In this paper, we construct a new dynamic model for the Token Bucket (TB algorithm used in computer networks and use systems approach for its analysis. This model is then augmented by adding a dynamic model for a multiplexor at an access node where the TB exercises a policing function. In the model, traffic policing, multiplexing and network utilization are formally defined. Based on the model, we study such issues as (quality of service QoS, traffic sizing and network dimensioning. Also we propose an algorithm using feedback control to improve QoS and network utilization. Applying MPEG video traces as the input traffic to the model, we verify the usefulness and effectiveness of our model.

  13. Heterodox networks

    DEFF Research Database (Denmark)

    Lala, Purnima; Kumar, Ambuj

    2016-01-01

    -Configurable Intelligent Distributed Antenna System (SCIDAS)’ that overlays intelligence over the conventional DAS architecture and latter is in the form of a swarm of intelligent hovering base stations working in a team to cooperatively resolve the PTC congestion at the Area of Event (AoE). A suitable network......It is imperative for the service providers to bring innovation in the network design to meet the exponential growth of mobile subscribers for multi-technology future wireless networks. As a matter of research, studies on providing services to moving subscriber groups aka ‘Place Time Capacity (PTC...... architecture of ‘Hovering Ad-hoc Network (HANET)’ for the latter will be deployed to assist and manage the overloaded primary base stations enhancing the on-demand coverage and capacity of the entire system. Proposed modes can either operate independently or as a cascaded architecture to form a Heterodox...

  14. Organizational Networks

    DEFF Research Database (Denmark)

    Grande, Bård; Sørensen, Ole Henning

    1998-01-01

    The paper focuses on the concept of organizational networks. Four different uses of the concept of organizational network are identified and critically discussed. Special focus is placed on how information and communication technologies as communication mediators and cognitive pictures influence...... the organizational forms discussed in the paper. It is asserted that the underlying organizational phenomena are not changing but that the manifestations and representations are shifting due to technological developments....

  15. Pintadas network

    OpenAIRE

    Cruz, Maria do Carmo Meirelles T.

    2006-01-01

    The Pintadas Network has been organized in Pintadas, a small municipality (11.254 inhabitants) in Bahia, located in the semi-arid region. It has been composed by civil society organizacions (social, productive, cultural and religious organizations and a credit cooperative), with support from the local town hall and from national and international institutions. The Network is a space for articulation, which intends to formulate, execute, follow-up, inspect and evaluate the municipal public pol...

  16. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  17. Network Flows

    Science.gov (United States)

    1988-12-01

    n Vlog n ), which is a linear time algorithm for all but the sparsest classes of shortest path problems. 3.4. Label Correcting Algorithms Label...11962] (Programming , Games and Transportation Networks), Iri (1969] (Network Flows, Transportation and Scheduling), Hu [1969] (Integer Programming and...though the improvements are not as dramatic as they have been for E>inic’s and the FIFO preflow push algorithms. For example, the 0(nm + n^ Vlog U

  18. Sentient networks

    Energy Technology Data Exchange (ETDEWEB)

    Chapline, G.

    1998-03-01

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

  19. 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...

  20. Deep residual networks of residual networks for image super-resolution

    Science.gov (United States)

    Wei, Xueqi; Yang, Fumeng; Wu, Congzhong

    2017-11-01

    Single image super-resolution (SISR), which aims at obtaining a high-resolution image from a single low-resolution image, is a classical problem in computer vision. In this paper, we address this problem based on a deep learning method with residual learning in an end-to-end manner. We propose a novel residual-network architecture, Residual networks of Residual networks (RoR), to promote the learning capability of residual networks for SISR. In residual network, the signal can be directly propagated from one unit to any other units in both forward and backward passes when using identity mapping as the skip connections. Based on it, we add level-wise connections upon original residual networks, to dig the optimization ability of residual networks. Our experiments demonstrate the effectiveness and versatility of RoR, it can get a faster convergence speed and gain higher resolution accuracy from considerably increased depth.

  1. Single Top-Quark Production at CDF

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    The main challenge of the single top-quark search at the Tevatron is the huge background from W+jets events and QCD events, which makes the use of advanced multivariate techniques essential. The recent single top analyses using either the matrix element method, neural networks, likelihood discriminants or boosted decision trees as well as the combination of the former three analyses will be presented...

  2. Fiber Optic Tactical Local Network (FOTLAN)

    Science.gov (United States)

    Bergman, L. A.; Hartmayer, R.; Wu, W. H.; Cassell, P.; Edgar, G.; Lambert, J.; Mancini, R.; Jeng, J.; Pardo, C.

    1991-01-01

    A 100 Mbit/s FDDI (fiber distributed data interface) network interface unit is described that supports real-time data, voice and video. Its high-speed interrupt-driven hardware architecture efficiently manages stream and packet data transfer to the FDDI network. Other enhancements include modular single-mode laser-diode fiber optic links to maximize node spacing, optic bypass switches for increased fault tolerance, and a hardware performance monitor to gather real-time network diagnostics.

  3. Message transfer in a communication network

    Indian Academy of Sciences (India)

    Examples of transport processes on networks include the traffic of informa- tion packets [1–4], transport processes on biological networks [5,6], and road traffic. ... for this system. In the case of single message transfer, we study the dependence of average travel times on the hub density, and find that travel times fall off as a.

  4. Learning drifting concepts with neural networks

    NARCIS (Netherlands)

    Biehl, Michael; Schwarze, Holm

    1993-01-01

    The learning of time-dependent concepts with a neural network is studied analytically and numerically. The linearly separable target rule is represented by an N-vector, whose time dependence is modelled by a random or deterministic drift process. A single-layer network is trained online using

  5. Extreme Networks' 10-Gigabit Ethernet enables

    CERN Multimedia

    2002-01-01

    " Extreme Networks, Inc.'s 10-Gigabit switching platform enabled researchers to transfer one Terabyte of information from Vancouver to Geneva across a single network hop, the world's first large-scale, end-to-end transfer of its kind" (1/2 page).

  6. BER Science Network Requirements

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-11-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years. In April 2010 ESnet and the Office of Biological and Environmental Research, of the DOE Office of Science, organized a workshop to characterize the networking requirements of the science programs funded by BER. The requirements identified at the workshop are summarized and described in more detail in the case studies and the Findings section. A number of common themes emerged from the case studies and workshop discussions. One is that BER science, like many other disciplines, is becoming more and more distributed and collaborative in nature. Another common theme is that data set sizes are exploding. Climate Science in particular is on the verge of needing to manage exabytes of data, and Genomics is on the verge of a huge paradigm shift in the number of sites with sequencers and the amount of sequencer data being generated.

  7. Community detection using preference networks

    Science.gov (United States)

    Tasgin, Mursel; Bingol, Haluk O.

    2018-04-01

    Community detection is the task of identifying clusters or groups of nodes in a network where nodes within the same group are more connected with each other than with nodes in different groups. It has practical uses in identifying similar functions or roles of nodes in many biological, social and computer networks. With the availability of very large networks in recent years, performance and scalability of community detection algorithms become crucial, i.e. if time complexity of an algorithm is high, it cannot run on large networks. In this paper, we propose a new community detection algorithm, which has a local approach and is able to run on large networks. It has a simple and effective method; given a network, algorithm constructs a preference network of nodes where each node has a single outgoing edge showing its preferred node to be in the same community with. In such a preference network, each connected component is a community. Selection of the preferred node is performed using similarity based metrics of nodes. We use two alternatives for this purpose which can be calculated in 1-neighborhood of nodes, i.e. number of common neighbors of selector node and its neighbors and, the spread capability of neighbors around the selector node which is calculated by the gossip algorithm of Lind et.al. Our algorithm is tested on both computer generated LFR networks and real-life networks with ground-truth community structure. It can identify communities accurately in a fast way. It is local, scalable and suitable for distributed execution on large networks.

  8. Basketball teams as strategic networks.

    Directory of Open Access Journals (Sweden)

    Jennifer H Fewell

    Full Text Available We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1 whether teams consistently moved the ball towards their shooting specialists, measured as "uphill/downhill" flux, and (2 whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players and network entropy (unpredictability of ball movement had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.

  9. High voltage power network construction

    CERN Document Server

    Harker, Keith

    2018-01-01

    This book examines the key requirements, considerations, complexities and constraints relevant to the task of high voltage power network construction, from design, finance, contracts and project management to installation and commissioning, with the aim of providing an overview of the holistic end to end construction task in a single volume.

  10. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

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

  11. Plant single-cell and single-cell-type metabolomics.

    Science.gov (United States)

    Misra, Biswapriya B; Assmann, Sarah M; Chen, Sixue

    2014-10-01

    In conjunction with genomics, transcriptomics, and proteomics, plant metabolomics is providing large data sets that are paving the way towards a comprehensive and holistic understanding of plant growth, development, defense, and productivity. However, dilution effects from organ- and tissue-based sampling of metabolomes have limited our understanding of the intricate regulation of metabolic pathways and networks at the cellular level. Recent advances in metabolomics methodologies, along with the post-genomic expansion of bioinformatics knowledge and functional genomics tools, have allowed the gathering of enriched information on individual cells and single cell types. Here we review progress, current status, opportunities, and challenges presented by single cell-based metabolomics research in plants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Research on Network Scanning Strategy Based on Information Granularity

    Science.gov (United States)

    Qin, Futong; Shi, Pengfei; Du, Jing; Cheng, Ruosi; Zhou, Yunyan

    2017-10-01

    As the basic mean to obtain the information of the targets network, network scanning is often used to discover the security risks and vulnerabilities existing on the network. However, with the development of network technology, the scale of network is more and more large, and the network scanning efficiency put forward higher requirements. In this paper, the concept of network scanning information granularity is proposed, and the design method of network scanning strategy based on information granularity is proposed. Based on single information granularity and hybrid information granularity, four network scanning strategies were designed and verified experimentally. Experiments show that the network scanning strategies based on hybrid information granularity can improve the efficiency of network scanning.

  13. NETWORK SECURITY ATTACKS. ARP POISONING CASE STUDY

    Directory of Open Access Journals (Sweden)

    Luminiţa DEFTA

    2010-12-01

    Full Text Available Arp poisoning is one of the most common attacks in a switched network. A switch is a network device that limits the ability of attackers that use a packet sniffer to gain access to information from internal network traffic. However, using ARP poisoning the traffic between two computers can be intercepted even in a network that uses switches. This method is known as man in the middle attack. With this type of attack the affected stations from a network will have invalid entries in the ARP table. Thus, it will contain only the correspondence between the IP addresses of the stations from the same network and a single MAC address (the station that initiated the attack. In this paper we present step by step the initiation of such an attack in a network with three computers. We will intercept the traffic between two stations using the third one (the attacker.

  14. Self-organized critical neural networks

    International Nuclear Information System (INIS)

    Bornholdt, Stefan; Roehl, Torsten

    2003-01-01

    A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

  15. Nuclear networking.

    Science.gov (United States)

    Xie, Wei; Burke, Brian

    2017-07-04

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

  16. Fusion Energy Sciences Network Requirements

    Energy Technology Data Exchange (ETDEWEB)

    Dart, Eli [ESNet, Berkeley, CA (United States); Tierney, Brian [ESNet, Berkeley, CA (United States)

    2012-09-26

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy Office of Science, the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In December 2011, ESnet and the Office of Fusion Energy Sciences (FES), of the DOE Office of Science (SC), organized a workshop to characterize the networking requirements of the programs funded by FES. The requirements identified at the workshop are summarized in the Findings section, and are described in more detail in the body of the report.

  17. Dynamic Protection of Optical Networks

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée

    2008-01-01

    This thesis deals with making optical networks resilient to failures. The recovery performance of path, segment and span restoration is evaluated in a network with limited wavelength conversion capability using both standard and enhanced wavelength assignment schemes. The enhanced wavelength...... stubs at the failure adjacent nodes. Both modifcations have a positive influence on the recovery percentage. The recovery enhancements are applicable in both single and multi-domain network environments. Stub release, where the still working parts of a failure affected connection are released prior...... of the modularity of capacity units is investigated for resilient network design. Different span upgrading strategies and algorithms for finding restoration paths are evaluated. Furthermore, the capacity effciency of constraining restoration requests for the same destination node to the same restoration path...

  18. Industrial Networks

    DEFF Research Database (Denmark)

    Karlsson, Christer

    2015-01-01

    network” should not be seen as an organizational form but as a perspective that can be used to enrich one's understanding of organizations. The industrial network perspective has three basic building blocks: actors, resources, and activities. The three building blocks and their relations constitute...... the focus of operations management from managing the own organization to continuously developing and managing a network of external and internal resources forming a production system. This perspective may be called managing an “extraprise” rather than an “enterprise.” It should be noted that “an industrial...

  19. Industrial Networks

    DEFF Research Database (Denmark)

    Karlsson, Christer

    2015-01-01

    the focus of operations management from managing the own organization to continuously developing and managing a network of external and internal resources forming a production system. This perspective may be called managing an “extraprise” rather than an “enterprise.” It should be noted that “an industrial...... network” should not be seen as an organizational form but as a perspective that can be used to enrich one's understanding of organizations. The industrial network perspective has three basic building blocks: actors, resources, and activities. The three building blocks and their relations constitute...

  20. Multiple Social Networks, Data Models and Measures for

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

  1. Models of network access using feedback fluid queues

    NARCIS (Netherlands)

    Mandjes, M.R.H.; Mitra, D.; Scheinhardt, Willem R.W.

    2001-01-01

    At the access to networks, in contrast to the core, distances and feedback delays, as well as link capacities are small, which has network engineering implications that are investigated in this paper. We consider a single point in the access network which multiplexes several bursty users. The users

  2. Models of network access using feedback fluid queues

    NARCIS (Netherlands)

    Mandjes, M.R.H.; Mitra, Debasis; Scheinhardt, Willem R.W.

    At the access to networks, in contrast to the core, distances and feedback delays, as well as link capacities are small, which has network engineering implications that are investigated in this paper. We consider a single point in the access network which multiplexes several bursty users. The users

  3. Models of network access using feedback fluid queues

    NARCIS (Netherlands)

    M.R.H. Mandjes (Michel); D. Mitra; W.R.W. Scheinhardt (Werner)

    2002-01-01

    htmlabstractAt the access to networks, in contrast to the core, distances and feedback delay s, as well as link capacities are small, which has network engineering implications that are investigated in this paper. We consider a single point in the access network which multiplexes several bursty

  4. Message transfer in a communication network

    Indian Academy of Sciences (India)

    2015-11-27

    Nov 27, 2015 ... We study message transfer in a 2-d communication network of regular nodes and randomly distributed hubs. We study both single message transfer and multiple message transfer on the lattice. The average travel time for single messages travelling between source and target pairs of fixed separations ...

  5. Network Coding

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 15; Issue 7. Network Coding. K V Rashmi Nihar B Shah P Vijay Kumar. General Article Volume 15 Issue 7 July 2010 pp 604-621. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/015/07/0604-0621 ...

  6. 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...

  7. 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...

  8. Community Structure in Online Collegiate Social Networks

    Science.gov (United States)

    Traud, Amanda; Kelsic, Eric; Mucha, Peter; Porter, Mason

    2009-03-01

    Online social networking sites have become increasingly popular with college students. The networks we studied are defined through ``friendships'' indicated by Facebook users from UNC, Oklahoma, Caltech, Georgetown, and Princeton. We apply the tools of network science to study the Facebook networks from these five different universities at a single point in time. We investigate each single-institution network's community structure, which we obtain through partitioning the graph using an eigenvector method. We use both graphical and quantitative tools, including pair-counting methods, which we interpret through statistical analysis and permutation tests to measure the correlations between the network communities and a set of characteristics given by each user (residence, class year, major, and high school). We also analyze the single gender subsets of these networks, and the impact of missing demographical data. Our study allows us to compare the online social networks for the five schools as well as infer differences in offline social interactions. At the schools studied, we were able to define which characteristics of the Facebook users correlate best with friendships.

  9. Cooperative networking in a heterogeneous wireless medium

    CERN Document Server

    Ismail, Muhammad

    2013-01-01

    This brief focuses on radio resource allocation in a heterogeneous wireless medium. It presents radio resource allocation algorithms with decentralized implementation, which support both single-network and multi-homing services. The brief provides a set of cooperative networking algorithms, which rely on the concepts of short-term call traffic load prediction, network cooperation, convex optimization, and decomposition theory. In the proposed solutions, mobile terminals play an active role in the resource allocation operation, instead of their traditional role as passive service recipients in the networking environment.

  10. ASCR Science Network Requirements

    Energy Technology Data Exchange (ETDEWEB)

    Dart, Eli; Tierney, Brian

    2009-08-24

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

  11. Seamless Data Services for Real Time Communication in a Heterogeneous Networks using Network Tracking and Management

    OpenAIRE

    T, Adiline Macriga.; Kumar, Dr. P. Anandha

    2010-01-01

    Heterogeneous Networks is the integration of all existing networks under a single environment with an understanding between the functional operations and also includes the ability to make use of multiple broadband transport technologies and to support generalized mobility. It is a challenging feature for Heterogeneous networks to integrate several IP-based access technologies in a seamless way. The focus of this paper is on the requirements of a mobility management scheme for multimedia real-...

  12. Physical-layer Network Coding in Two-Way Heterogeneous Cellular Networks with Power Imbalance

    OpenAIRE

    Thampi, Ajay; Liew, Soung Chang; Armour, Simon; Fan, Zhong; You, Lizhao; Kaleshi, Dritan

    2014-01-01

    The growing demand for high-speed data, quality of service (QoS) assurance and energy efficiency has triggered the evolution of 4G LTE-A networks to 5G and beyond. Interference is still a major performance bottleneck. This paper studies the application of physical-layer network coding (PNC), a technique that exploits interference, in heterogeneous cellular networks. In particular, we propose a rate-maximising relay selection algorithm for a single cell with multiple relays assuming the decode...

  13. Fin-and-tube condenser performance evaluation using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Ling-Xiao [Institute of Refrigeration and Cryogenics, Shanghai Jiaotong University, Shanghai 200240 (China); Zhang, Chun-Lu [China R and D Center, Carrier Corporation, No. 3239 Shen Jiang Road, Shanghai 201206 (China)

    2010-05-15

    The paper presents neural network approach to performance evaluation of the fin-and-tube air-cooled condensers which are widely used in air-conditioning and refrigeration systems. Inputs of the neural network include refrigerant and air-flow rates, refrigerant inlet temperature and saturated temperature, and entering air dry-bulb temperature. Outputs of the neural network consist of the heating capacity and the pressure drops on both refrigerant and air sides. The multi-input multi-output (MIMO) neural network is separated into multi-input single-output (MISO) neural networks for training. Afterwards, the trained MISO neural networks are combined into a MIMO neural network, which indicates that the number of training data sets is determined by the biggest MISO neural network not the whole MIMO network. Compared with a validated first-principle model, the standard deviations of neural network models are less than 1.9%, and all errors fall into {+-}5%. (author)

  14. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  15. Single Event Kinetic Modelling without Explicit Generation of Large Networks: Application to Hydrocracking of Long Paraffins Modélisation cinétique par événements constitutifs sans génération explicite de grands réseaux : application à l’hydrocraquage des paraffines longues

    Directory of Open Access Journals (Sweden)

    Guillaume D.

    2011-08-01

    Full Text Available The single event modelling concept allows developing kinetic models for the simulation of refinery processes. For reaction networks with several hundreds of thousands of species, as is the case for catalytic reforming, rigorous relumping by carbon atom number and branching degree were efficiently employed by assuming chemical equilibrium in each lump. This relumping technique yields a compact lumped model without any loss of information, but requires the full detail of an explicitly generated reaction network. Classic network generation techniques become impractical when the hydrocarbon species contain more than approximately 20 carbon atoms, because of the extremely rapid growth of reaction network. Hence, implicit relumping techniques were developed in order to compute lumping coefficients without generating the detailed reaction network. Two alternative and equivalent approaches are presented, based either on structural classes or on lateral chain decomposition. These two methods are discussed and the lateral chain decomposition method is applied to the kinetic modelling of long chain paraffin hydroisomerization and hydrocracking. The lateral chain decomposition technique is exactly equivalent to the original calculation method based on the explicitly generated detailed reaction network, as long as Benson’s group contribution method is used to calculate the necessary thermodynamic data in both approaches. Le concept de modélisation par événements constitutifs permet de développer des modèles cinétiques pour la simulation des procédés de raffinage. Pour des réseaux réactionnels de centaines de milliers d'espèces, comme cela est le cas pour le reformage catalytique, le regroupement rigoureux par nombre d'atomes de carbone et degré de ramification a été utilisé efficacement en faisant l'hypothèse de l'équilibre chimique dans chaque groupe. Cette technique de regroupement conduit à un modèle regroupé compact sans perte d

  16. Association of rs1801157 single nucleotide polymorphism of CXCL12 gene in breast cancer in Pakistan and in-silico expression analysis of CXCL12–CXCR4 associated biological regulatory network

    Directory of Open Access Journals (Sweden)

    Samra Khalid

    2017-09-01

    Full Text Available Background C-X-C chemokine ligand 12 (CXCL12 has important implications in breast cancer (BC pathogenesis. It is selectively expressed on B and T lymphocytes and is involved in hematopoiesis, thymocyte trafficking, stem cell motility, neovascularization, and tumorigenesis. The single nucleotide polymorphism (SNP rs1801157 of CXCL12 gene has been found to be associated with higher risk of BC. Methods Our study focuses on the genotypic and allelic distribution of SNP (rs1801157; G/A in Pakistani population as well as its association with the clinico-pathological features. The association between rs1801157 genotypes (G/A and BC risks was assessed by a multivariate logistic regression (MLR analysis. Genotyping was performed in both healthy individuals and patients of BC using PCR-restriction fragment length polymorphism (PCR-RFLP method. Furthermore, in-silico approaches were adapted to investigate the association of CXCL12 and its receptor CXCR4 with genes/proteins involved in BC signalling. Results Significant differences in allelic and genotypic distribution between BC patients and healthy individuals of genotype (G/G and (A/G (p  0.05 was assessed. In a MLR analysis, a number of variables including age, weight of an individual, affected lymph nodes, hormonal status (estrogen and progesterone receptor, alcohol consumption and family history associated with the GG genotype (GG:AA, odds ratio (OR = 1.30, 95% CI [1.06–1.60] were found to be independent risk factors for BC. Our in-vitro results suggest that genotype GG is possibly increasing the risk of BC in Pakistani cohorts. in-silico analysis finds that CXCL12–CXCR4 is associated with an increased expression of PDZK1, PI3k and Akt which lead the breast tumor towards metastasis. Conclusion Multiple targets such as CXCL12, CXCR4, PDZK1, PI3k and Akt can be inhibited in combined strategies to treat BC metastasis.

  17. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

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

  18. Networking Japan

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    and activities in Japan. One concrete example was the earthquake relief Japan received from alumni in 2011. The exchanges have also already inspired an explicit focus on private sector and middle income countries in the Japanese Development Cooperation Charter announced in February 2015.......Human Resource Development was the first and remains an important pillar in Japanese foreign aid. I will argue that Japan has access to a global network of alumni who will co-define Japanese foreign aid in the future, because Japan has encouraged alumni societies and networking since 1965. A total...... of more than a million people in more than 100 countries have attended courses in Japan funded fully or partly by Japanese ODA since the inception of the technical assistance programs in 1954 through the Colombo Plan and since 1959 through the Association of Overseas Technical Scholarships (AOTS from 2009...

  19. Equivalence of Conventional and Modified Network of Generalized Neural Elements

    Directory of Open Access Journals (Sweden)

    E. V. Konovalov

    2016-01-01

    Full Text Available The article is devoted to the analysis of neural networks consisting of generalized neural elements. The first part of the article proposes a new neural network model — a modified network of generalized neural elements (MGNE-network. This network developes the model of generalized neural element, whose formal description contains some flaws. In the model of the MGNE-network these drawbacks are overcome. A neural network is introduced all at once, without preliminary description of the model of a single neural element and method of such elements interaction. The description of neural network mathematical model is simplified and makes it relatively easy to construct on its basis a simulation model to conduct numerical experiments. The model of the MGNE-network is universal, uniting properties of networks consisting of neurons-oscillators and neurons-detectors. In the second part of the article we prove the equivalence of the dynamics of the two considered neural networks: the network, consisting of classical generalized neural elements, and MGNE-network. We introduce the definition of equivalence in the functioning of the generalized neural element and the MGNE-network consisting of a single element. Then we introduce the definition of the equivalence of the dynamics of the two neural networks in general. It is determined the correlation of different parameters of the two considered neural network models. We discuss the issue of matching the initial conditions of the two considered neural network models. We prove the theorem about the equivalence of the dynamics of the two considered neural networks. This theorem allows us to apply all previously obtained results for the networks, consisting of classical generalized neural elements, to the MGNE-network.

  20. Loss Networks

    OpenAIRE

    Kelly, F. P.

    1991-01-01

    This paper describes work on the stochastic modelling of loss networks. Such systems have long been of interest to telephone engineers and are becoming increasingly important as models of computer and information systems. Throughout the century problems from this field have provided an impetus to the development of probability theory, pure and applied. This paper provides an introduction to the area and a review of recent work.

  1. Non-Linear Systems Identification Using Neural Networks

    OpenAIRE

    Chen, S.; Billings, S.A.; Grant, P.M.

    1989-01-01

    Multi-layered neural networks offer an exciting alternative for modelling complex non-linear systems. This paper investigates the identification of discrete-time non-linear systems using neural networks with a single hidden layer. New parameter estimation algorithms are derived for the neural network model based on a prediction error formulation and the application to both simulated and real data is included to demonstrate the effectiveness of the neural network approach.

  2. A New Artificial Network Approach for Membrane Filtration Simulation

    OpenAIRE

    Vivier, J.; Mehablia, A.

    2012-01-01

    To improve traditional neural networks, the present research used the wavelet network, a special feedforward neural network with a single hidden layer supported by the wavelet theory. Prediction performance and efficiency of the proposed network were examined with a published experimental dataset of cross-flow membrane filtration. The dataset was divided into two parts: 70 samples for training data and 330 samples for testing data. Various combinations of transmembrane pressure, filtration...

  3. Linear network theory

    CERN Document Server

    Sander, K F

    1964-01-01

    Linear Network Theory covers the significant algebraic aspect of network theory, with minimal reference to practical circuits. The book begins the presentation of network analysis with the exposition of networks containing resistances only, and follows it up with a discussion of networks involving inductance and capacity by way of the differential equations. Classification and description of certain networks, equivalent networks, filter circuits, and network functions are also covered. Electrical engineers, technicians, electronics engineers, electricians, and students learning the intricacies

  4. Modeling the citation network by network cosmology.

    Science.gov (United States)

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

    2015-01-01

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

  5. Fiber-Optic Terahertz Data-Communication Networks

    Science.gov (United States)

    Chua, Peter L.; Lambert, James L.; Morookian, John M.; Bergman, Larry A.

    1994-01-01

    Network protocols implemented in optical domain. Fiber-optic data-communication networks utilize fully available bandwidth of single-mode optical fibers. Two key features of method: use of subpicosecond laser pulses as carrier signals and spectral phase modulation of pulses for optical implementation of code-division multiple access as multiplexing network protocol. Local-area network designed according to concept offers full crossbar functionality, security of data in transit through network, and capacity about 100 times that of typical fiber-optic local-area network in current use.

  6. Optical networking standards a comprehensive guide for professionals

    CERN Document Server

    2006-01-01

    Optical Networking Standards: A Comprehensive Guide for Professionals provides a single source reference of over a hundred standards and industry technical specifications for optical networks at all levels: from components to networking systems through global networks, as well as coverage of networks management and services. This book focuses on the recently approved, adopted and implemented standards that have fueled the development of versatile switches, routers and multi-service provisioning platforms. These networking elements have enabled the service-providers world-wide to offer flexible yet customized bundled-services based on IP, MPLS and Carrier-Grade Ethernet.

  7. Networks of networks – An introduction

    International Nuclear Information System (INIS)

    Kenett, Dror Y.; Perc, Matjaž; Boccaletti, Stefano

    2015-01-01

    Graphical abstract: Interdependent network reciprocity. Only those blue cooperative domains that are initially present on both networks survive. Abstract: This is an introduction to the special issue titled “Networks of networks” that is in the making at Chaos, Solitons & Fractals. Recent research and reviews attest to the fact that networks of networks are the next frontier in network science [1–7]. Not only are interactions limited and thus inadequately described by well-mixed models, it is also a fact that the networks that should be an integral part of such models are often interconnected, thus making the processes that are unfolding on them interdependent. From the World economy and transportation systems to social media, it is clear that processes taking place in one network might significantly affect what is happening in many other networks. Within an interdependent system, each type of interaction has a certain relevance and meaning, so that treating all the links identically inevitably leads to information loss. Networks of networks, interdependent networks, or multilayer networks are therefore a much better and realistic description of such systems, and this Special Issue is devoted to their structure, dynamics and evolution, as well as to the study of emergent properties in multi-layered systems in general. Topics of interest include but are not limited to the spread of epidemics and information, percolation, diffusion, synchronization, collective behavior, and evolutionary games on networks of networks. Interdisciplinary work on all aspects of networks of networks, regardless of background and motivation, is very welcome.

  8. Pinning Synchronization of Switched Complex Dynamical Networks

    Directory of Open Access Journals (Sweden)

    Liming Du

    2015-01-01

    Full Text Available Network topology and node dynamics play a key role in forming synchronization of complex networks. Unfortunately there is no effective synchronization criterion for pinning synchronization of complex dynamical networks with switching topology. In this paper, pinning synchronization of complex dynamical networks with switching topology is studied. Two basic problems are considered: one is pinning synchronization of switched complex networks under arbitrary switching; the other is pinning synchronization of switched complex networks by design of switching when synchronization cannot achieved by using any individual connection topology alone. For the two problems, common Lyapunov function method and single Lyapunov function method are used respectively, some global synchronization criteria are proposed and the designed switching law is given. Finally, simulation results verify the validity of the results.

  9. Grip on complexity in chemical reaction networks.

    Science.gov (United States)

    Wong, Albert S Y; Huck, Wilhelm T S

    2017-01-01

    A new discipline of "systems chemistry" is emerging, which aims to capture the complexity observed in natural systems within a synthetic chemical framework. Living systems rely on complex networks of chemical reactions to control the concentration of molecules in space and time. Despite the enormous complexity in biological networks, it is possible to identify network motifs that lead to functional outputs such as bistability or oscillations. To truly understand how living systems function, we need a complete understanding of how chemical reaction networks (CRNs) create function. We propose the development of a bottom-up approach to design and construct CRNs where we can follow the influence of single chemical entities on the properties of the network as a whole. Ultimately, this approach should allow us to not only understand such complex networks but also to guide and control their behavior.

  10. Social networks and environmental outcomes.

    Science.gov (United States)

    Barnes, Michele L; Lynham, John; Kalberg, Kolter; Leung, PingSun

    2016-06-07

    Social networks can profoundly affect human behavior, which is the primary force driving environmental change. However, empirical evidence linking microlevel social interactions to large-scale environmental outcomes has remained scarce. Here, we leverage comprehensive data on information-sharing networks among large-scale commercial tuna fishers to examine how social networks relate to shark bycatch, a global environmental issue. We demonstrate that the tendency for fishers to primarily share information within their ethnic group creates segregated networks that are strongly correlated with shark bycatch. However, some fishers share information across ethnic lines, and examinations of their bycatch rates show that network contacts are more strongly related to fishing behaviors than ethnicity. Our findings indicate that social networks are tied to actions that can directly impact marine ecosystems, and that biases toward within-group ties may impede the diffusion of sustainable behaviors. Importantly, our analysis suggests that enhanced communication channels across segregated fisher groups could have prevented the incidental catch of over 46,000 sharks between 2008 and 2012 in a single commercial fishery.

  11. Understanding control of network spreading from network controllability

    Science.gov (United States)

    Sun, Peng Gang; Ma, Xiaoke

    2017-09-01

    How to control the spread of an epidemic or information is a great challenge for us. A dynamic network-based system’s structural controllability provides a new way to control spreading with the minimum input of external signals, and the dynamic system is controllable if the signals can drive it from any initial state to any desired final state in finite time. Therefore, we are motivated to develop a new framework by introducing spreading networks (SNs) to describe the spreading pathways from a global view, and we try to understand the control of the spreading by the structural controllability of the SNs. The SNs are transformed from original networks, in which each node is considered as a single spreading origin. The weights of directed links pointing at its direct contacts in the SNs denote the spreading abilities, which can be determined by a new probability function. Furthermore, we also investigate the impact of the dynamics of network structures on the framework. The results show that sparse homogeneous networks with a higher transmission probability tend to trigger a larger scale of diffusion, which is easier to control. We can also see that an epidemic or information is inclined to diffuse easily on the networks with strong community strengths and heterogeneous community sizes. From the structural controllability of the SNs, we observe that driver nodes for the control of the spread tend not to be the nodes located within the core of original networks or those with high-degree. In addition, the scale of diffusion, the number of driver nodes and positions of nodes are highly associated with the degree distribution of the original networks.

  12. Exploitation mathématique de données sédimentologiques pour reconstitutions architecturales Mathematical Processing of Sedimentological Data for Archtectural Reconstruction

    Directory of Open Access Journals (Sweden)

    Dagens Y.

    2006-11-01

    Full Text Available Le géologue pétrolier est couramment confronté avec le problème de la reconstitution d'un volume sédimentaire. Une méthode de traitement automatique a été mise au point pour reconstituer l'architecture de dépôts; elle permet le stockage du modèle obtenu dans un fichier et sa transmission sous une forme codifiée pour un traitement automatique ultérieur. L'objectif est d'obtenir une description aussi fidèle que possible de la série sédimentaire étudiée. Le travail est effectué par étapes, avec contrôle en continu par le géologue responsable de l'étude, ce contrôle est rendu facile par la représentation graphique automatique des résultats. Après développement des principes de la méthode et étude des différentes étapes du traitement, il est présenté un cas réel correspondant à la série sédimentaire d'un gisement pétrolier. La méthode a été mise au point pour la description des séries sédimentaires mais son domaine d'utilisation doit pouvoir être généralisé à tout type de données de sondages ou de coupes de terrain dont on veut caractériser graphiquement la répartition spatiale. Petroleum geologists are commonly confronted with the problem of reconstructing a sedimentary volume. A method of automatic processing has been developed for reconstructing the architecture of deposits. It enables the model obtained to be stored in a file and subsequently to be transmitted in a codified form for automatic processing. The aim is to obtain as exact a description as possible of the sedimentary series under study. The work is done in stages, with continuous control by a geologist. This control is facilitated by the automatic graphic plotting of results. After a description of the principles behind the method and a study of the different stages in processing the data, the method is illustrated by an actual case corresponding to the sedimentary series of an ail pool. The method was initially developed to describe sedimentary series, although it should be possible to extend its application to all types of data obtained from wells or profiles to determine their distribution in space.

  13. Generalized instantly decodable network coding for relay-assisted networks

    KAUST Repository

    Elmahdy, Adel M.

    2013-09-01

    In this paper, we investigate the problem of minimizing the frame completion delay for Instantly Decodable Network Coding (IDNC) in relay-assisted wireless multicast networks. We first propose a packet recovery algorithm in the single relay topology which employs generalized IDNC instead of strict IDNC previously proposed in the literature for the same relay-assisted topology. This use of generalized IDNC is supported by showing that it is a super-set of the strict IDNC scheme, and thus can generate coding combinations that are at least as efficient as strict IDNC in reducing the average completion delay. We then extend our study to the multiple relay topology and propose a joint generalized IDNC and relay selection algorithm. This proposed algorithm benefits from the reception diversity of the multiple relays to further reduce the average completion delay in the network. Simulation results show that our proposed solutions achieve much better performance compared to previous solutions in the literature. © 2013 IEEE.

  14. Parallel computing and networking; Heiretsu keisanki to network

    Energy Technology Data Exchange (ETDEWEB)

    Asakawa, E.; Tsuru, T. [Japan National Oil Corp., Tokyo (Japan); Matsuoka, T. [Japan Petroleum Exploration Co. Ltd., Tokyo (Japan)

    1996-05-01

    This paper describes the trend of parallel computers used in geophysical exploration. Around 1993 was the early days when the parallel computers began to be used for geophysical exploration. Classification of these computers those days was mainly MIMD (multiple instruction stream, multiple data stream), SIMD (single instruction stream, multiple data stream) and the like. Parallel computers were publicized in the 1994 meeting of the Geophysical Exploration Society as a `high precision imaging technology`. Concerning the library of parallel computers, there was a shift to PVM (parallel virtual machine) in 1993 and to MPI (message passing interface) in 1995. In addition, the compiler of FORTRAN90 was released with support implemented for data parallel and vector computers. In 1993, networks used were Ethernet, FDDI, CDDI and HIPPI. In 1995, the OC-3 products under ATM began to propagate. However, ATM remains to be an interoffice high speed network because the ATM service has not spread yet for the public network. 1 ref.

  15. Cognitive Networks

    Science.gov (United States)

    2007-06-15

    as the spread of fads, failures in electrical grids, and epidemics . In this manner, this model has already demonstrated some practical use. Simple...in Matlab , and consisted of nodes placed with a uniform random distribution in a square 2-D map with density 0.1 nodes/unit2. There is a single source

  16. Single Audit: Single Audit Act Effectiveness Issues

    National Research Council Canada - National Science Library

    Thompson, Sally

    2002-01-01

    As discussed in the report we are releasing today, our work to review agency actions to ensure that recipients take timely and appropriate corrective actions to fix audit findings contained in single...

  17. Single photon from a single trapped atom

    International Nuclear Information System (INIS)

    Dingjan, J.; Jones, M.P.A.; Beugnon, J.; Darquiee, B.; Bergamini, S.; Browaeys, A.; Messin, G.; Grangier, P.

    2005-01-01

    Full text: A quantum treatment of the interaction between atoms and light usually begins with the simplest model system: a two-level atom interacting with a monochromatic light wave. Here we demonstrate an elegant experimental realization of this system using an optically trapped single rubidium atom illuminated by resonant light pulses. We observe Rabi oscillations, and show that this system can be used as a highly efficient triggered source of single photons with a well-defined polarisation. In contrast to other sources based on neutral atoms and trapped ions, no optical cavity is required. We achieved a flux of single photons of about 10 4 s -1 at the detector, and observe complete antibunching. This source has potential applications for distributed atom-atom entanglement using single photons. (author)

  18. Green mobile networks a networking perspective

    CERN Document Server

    Ansari, Nirwan

    2016-01-01

    Combines the hot topics of energy efficiency and next generation mobile networking, examining techniques and solutions. Green communications is a very hot topic. Ever increasing mobile network bandwidth rates significantly impacts on operating costs due to aggregate network energy consumption. As such, design on 4G networks and beyond has increasingly started to focus on 'energy efficiency' or so-called 'green' networks. Many techniques and solutions have been proposed to enhance the energy efficiency of mobile networks, yet no book has provided an in-depth analysis of the energy consumption issues in mobile networks nor offers detailed theories, tools and solutions for solving the energy efficiency problems.

  19. Numerical simulation for gas-liquid two-phase flow in pipe networks

    International Nuclear Information System (INIS)

    Li Xiaoyan; Kuang Bo; Zhou Guoliang; Xu Jijun

    1998-01-01

    The complex pipe network characters can not directly presented in single phase flow, gas-liquid two phase flow pressure drop and void rate change model. Apply fluid network theory and computer numerical simulation technology to phase flow pipe networks carried out simulate and compute. Simulate result shows that flow resistance distribution is non-linear in two phase pipe network

  20. Open innovation in networks

    DEFF Research Database (Denmark)

    Hu, Yimei

    Open innovation in networks has been a popular topic for long, this paper rethinks the concepts of innovation network and network organization, and clarifies the differences between them based on the network perspective. Network perspective means that: network is the context of firms; market...... and hierarchy can be analyzed from a network approach. Within a network perspective, there are different levels of network, and a firm may not always has the power to “manage” innovation networks due to different levels of power. Based on the strength of a firm’s power, its role may varies from manager...

  1. Resilience of LTE networks against smart jamming attacks

    KAUST Repository

    Aziz, Farhan M.

    2014-12-08

    Commercial LTE networks are being studied for mission-critical applications, such as public safety and smart grid communications. In this paper, LTE networks are shown vulnerable to Denial-of-Service (DOS) and loss of service attacks from smart jammers, who may employ simple narrowband jamming techniques to attack without any need to hack the network or its users. We modeled the utilities of jamming and anti-jamming actions played by the jammer and the network under the framework of single-shot and repeated Bayesian games. In a single-shot game formulation the only Nash Equilibria (NE) are pure strategy equilibria at which network utility is severely compromised. We propose a repeated-game learning and strategy algorithm for the network that outperforms single-shot games by a significant margin. Furthermore, all of our proposed actions and algorithms can be implemented with current technology.

  2. Design principles in biological networks

    Science.gov (United States)

    Goyal, Sidhartha

    Much of biology emerges from networks of interactions. Even in a single bacterium such as Escherichia coli, there are hundreds of coexisting gene and protein networks. Although biological networks are the outcome of evolution, various physical and biological constraints limit their functional capacity. The focus of this thesis is to understand how functional constraints such as optimal growth in mircoorganisms and information flow in signaling pathways shape the metabolic network of bacterium E. coli and the quorum sensing network of marine bacterium Vibrio harveyi, respectively. Metabolic networks convert basic elemental sources into complex building-blocks eventually leading to cell's growth. Therefore, typically, metabolic pathways are often coupled both by the use of a common substrate and by stoichiometric utilization of their products for cell growth. We showed that such a coupled network with product-feedback inhibition may exhibit limit-cycle oscillations which arise via a Hopf bifurcation. Furthermore, we analyzed several representative metabolic modules and find that, in all cases, simple product-feedback inhibition allows nearly optimal growth, in agreement with the predicted growth-rate by the flux-balance analysis (FBA). Bacteria have fascinating and diverse social lives. They display coordinated group behaviors regulated by quorum sensing (QS) systems. The QS circuit of V. harveyi integrates and funnels different ecological information through a common phosphorelay cascade to a set of small regulatory RNAs (sRNAs) that enables collective behavior. We analyzed the signaling properties and information flow in the QS circuit, which provides a model for information flow in signaling networks more generally. A comparative study of post-transcriptional and conventional transcriptional regulation suggest a niche for sRNAs in allowing cells to transition quickly yet reliably between distinct states. Furthermore, we develop a new framework for analyzing signal

  3. Clusters in nonsmooth oscillator networks

    Science.gov (United States)

    Nicks, Rachel; Chambon, Lucie; Coombes, Stephen

    2018-03-01

    For coupled oscillator networks with Laplacian coupling, the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory, this approach has recently been extended to treat more general cluster states. However, the MSF and its generalizations require the determination of a set of Floquet multipliers from variational equations obtained by linearization around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by, the framework is often explored using numerical techniques. Here, we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of saltation matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration, we analyze an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris-Lecar neuron model. We use these examples to emphasize that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly, the procedure that we present here, for understanding cluster synchronization in networks, is valid for a wide variety of systems in

  4. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2017-01-01

    the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century.......Strategic communication needs a thorough understanding of the social forms of interaction, organization and social structure, it works within and through. Success is a scarce resource, and organizations compete to fulfill their mission and advance toward specific goals. In this chapter, we present...

  5. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2017-01-01

    Strategic communication needs a thorough understanding of the social forms of interaction, organization and social structure, it works within and through. Success is a scarce resource, and organizations compete to fulfill their mission and advance toward specific goals. In this chapter, we present...... the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century....

  6. ENLIGHT Network

    CERN Multimedia

    Ballantine, A; Dixon-Altaber, H; Dosanjh, M; Kuchina, L

    2011-01-01

    State-of-the-art techniques borrowed from particle accelerators and detectors are a key element in hadrontherapy and several European projects are actively fostering the collaboration amongst the various disciplines and countries. ENLIGHT was established in 2002 to coordinate these European efforts in hadron therapy. The ENLIGHT network is formed by the European hadrontherapy Community, with more than 300 participants from twenty European countries. A major achievement of ENLIGHT has been the blending of traditionally separate communities so that clinicians, physicists, biologists and engineers with experience and interest in particle therapy are working together.

  7. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2018-01-01

    Strategic communication needs a thorough understanding of the social forms of interaction, organization and social structure, it works within and through. Success is a scarce resource, and organizations compete to fulfill their mission and advance toward specific goals. In this chapter, we present...... the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century....

  8. Evolutionary games on multilayer networks: a colloquium

    Science.gov (United States)

    Wang, Zhen; Wang, Lin; Szolnoki, Attila; Perc, Matjaž

    2015-05-01

    Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

  9. Neural Circuitry Based on Single Electron Transistors and Single Electron Memories

    Directory of Open Access Journals (Sweden)

    Aïmen BOUBAKER

    2014-05-01

    Full Text Available In this paper, we propose and explain a neural circuitry based on single electron transistors ‘SET’ which can be used in classification and recognition. We implement, after that, a Winner-Take-All ‘WTA’ neural network with lateral inhibition architecture. The original idea of this work is reflected, first, in the proposed new single electron memory ‘SEM’ design by hybridising two promising Single Electron Memory ‘SEM’ and the MTJ/Ring memory and second, in modeling and simulation results of neural memory based on SET. We prove the charge storage in quantum dot in two types of memories.

  10. Feedforward Approximations to Dynamic Recurrent Network Architectures.

    Science.gov (United States)

    Muir, Dylan R

    2018-02-01

    Recurrent neural network architectures can have useful computational properties, with complex temporal dynamics and input-sensitive attractor states. However, evaluation of recurrent dynamic architectures requires solving systems of differential equations, and the number of evaluations required to determine their response to a given input can vary with the input or can be indeterminate altogether in the case of oscillations or instability. In feedforward networks, by contrast, only a single pass through the network is needed to determine the response to a given input. Modern machine learning systems are designed to operate efficiently on feedforward architectures. We hypothesized that two-layer feedforward architectures with simple, deterministic dynamics could approximate the responses of single-layer recurrent network architectures. By identifying the fixed-point responses of a given recurrent network, we trained two-layer networks to directly approximate the fixed-point response to a given input. These feedforward networks then embodied useful computations, including competitive interactions, information transformations, and noise rejection. Our approach was able to find useful approximations to recurrent networks, which can then be evaluated in linear and deterministic time complexity.

  11. Single frequency intracavity SRO

    DEFF Research Database (Denmark)

    Abitan, Haim; Buchhave, Preben

    2000-01-01

    Summary form only given. A single resonance optical parametric oscillator (SRO) is inserted intracavity to a CW high power, single frequency, and ring Nd:YVO4 laser. We obtain a stable single frequency CW SRO with output at 1.7-1.9 μm (idler) and a resonating signal at 2.3-2.6 μm. The behavior...

  12. Mesh network simulation

    OpenAIRE

    Pei, Ping; Petrenko, Y. N.

    2015-01-01

    A Mesh network simulation framework which provides a powerful and concise modeling chain for a network structure will be introduce in this report. Mesh networks has a special topologic structure. The paper investigates a message transfer in wireless mesh network simulation and how does it works in cellular network simulation. Finally the experimental result gave us the information that mesh networks have different principle in transmission way with cellular networks in transmission, and multi...

  13. Current redistribution in resistor networks: Fat-tail statistics in regular and small-world networks.

    Science.gov (United States)

    Lehmann, Jörg; Bernasconi, Jakob

    2017-03-01

    The redistribution of electrical currents in resistor networks after single-bond failures is analyzed in terms of current-redistribution factors that are shown to depend only on the topology of the network and on the values of the bond resistances. We investigate the properties of these current-redistribution factors for regular network topologies (e.g., d-dimensional hypercubic lattices) as well as for small-world networks. In particular, we find that the statistics of the current redistribution factors exhibits a fat-tail behavior, which reflects the long-range nature of the current redistribution as determined by Kirchhoff's circuit laws.

  14. Quantum networks based on cavity QED

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, Stephan; Bochmann, Joerg; Figueroa, Eden; Hahn, Carolin; Kalb, Norbert; Muecke, Martin; Neuzner, Andreas; Noelleke, Christian; Reiserer, Andreas; Uphoff, Manuel; Rempe, Gerhard [Max-Planck-Institut fuer Quantenoptik, Hans-Kopfermann-Strasse 1, 85748 Garching (Germany)

    2014-07-01

    Quantum repeaters require an efficient interface between stationary quantum memories and flying photons. Single atoms in optical cavities are ideally suited as universal quantum network nodes that are capable of sending, storing, retrieving, and even processing quantum information. We demonstrate this by presenting an elementary version of a quantum network based on two identical nodes in remote, independent laboratories. The reversible exchange of quantum information and the creation of remote entanglement are achieved by exchange of a single photon. Quantum teleportation is implemented using a time-resolved photonic Bell-state measurement. Quantum control over all degrees of freedom of the single atom also allows for the nondestructive detection of flying photons and the implementation of a quantum gate between the spin state of the atom and the polarization of a photon upon its reflection from the cavity. Our approach to quantum networking offers a clear perspective for scalability and provides the essential components for the realization of a quantum repeater.

  15. Auto-associative nanoelectronic neural network

    Energy Technology Data Exchange (ETDEWEB)

    Nogueira, C. P. S. M.; Guimarães, J. G. [Departamento de Engenharia Elétrica - Laboratório de Dispositivos e Circuito Integrado, Universidade de Brasília, CP 4386, CEP 70904-970 Brasília DF (Brazil)

    2014-05-15

    In this paper, an auto-associative neural network using single-electron tunneling (SET) devices is proposed and simulated at low temperature. The nanoelectronic auto-associative network is able to converge to a stable state, previously stored during training. The recognition of the pattern involves decreasing the energy of the input state until it achieves a point of local minimum energy, which corresponds to one of the stored patterns.

  16. Auto-associative nanoelectronic neural network

    International Nuclear Information System (INIS)

    Nogueira, C. P. S. M.; Guimarães, J. G.

    2014-01-01

    In this paper, an auto-associative neural network using single-electron tunneling (SET) devices is proposed and simulated at low temperature. The nanoelectronic auto-associative network is able to converge to a stable state, previously stored during training. The recognition of the pattern involves decreasing the energy of the input state until it achieves a point of local minimum energy, which corresponds to one of the stored patterns

  17. Communication network exchange

    International Nuclear Information System (INIS)

    Woo, Seung Sul

    1988-05-01

    This book has two parts. The first parts is comprised of five chapters, which deals with communication network constitution with design of network and types, telephone network about outline and management of network, telephone network · data network · private network, international data telephone network about service and international data network and technical standards of quality of service, communication and data. The second parts handles exchange, which is about institution of switching, a manual exchange and step-by step exchange, a crossbar exchange, electronic exchange, international switching system, design of equipment of test and measurement.

  18. Network Visualization Project (NVP)

    Science.gov (United States)

    2016-07-01

    Visualization Project (NVP) by Terry Wen American Society of Engineering Education, Washington, DC Lisa M Marvel Computational and Information Sciences...front-end presentation and construction of the application itself. 15. SUBJECT TERMS computer network traffic, computer network security, computer ...network visualization, network traffic analysis, network forensics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF

  19. Operating a heterogeneous telescope network

    Science.gov (United States)

    Allan, Alasdair; Bischoff, Karsten; Burgdorf, Martin; Cavanagh, Brad; Christian, Damien; Clay, Neil; Dickens, Rob; Economou, Frossie; Fadavi, Mehri; Frazer, Stephen; Granzer, Thomas; Grosvenor, Sandy; Hessman, Frederic V.; Jenness, Tim; Koratkar, Anuradha; Lehner, Matthew; Mottram, Chris; Naylor, Tim; Saunders, Eric S.; Solomos, Nikolaos; Steele, Iain A.; Tuparev, Georg; Vestrand, W. Thomas; White, Robert R.; Yost, Sarah

    2006-06-01

    In the last few years the ubiquitous availability of high bandwidth networks has changed the way both robotic and non-robotic telescopes operate, with single isolated telescopes being integrated into expanding "smart" telescope networks that can span continents and respond to transient events in seconds. The Heterogeneous Telescope Networks (HTN)* Consortium represents a number of major research groups in the field of robotic telescopes, and together we are proposing a standards based approach to providing interoperability between the existing proprietary telescope networks. We further propose standards for interoperability, and integration with, the emerging Virtual Observatory. We present the results of the first interoperability meeting held last year and discuss the protocol and transport standards agreed at the meeting, which deals with the complex issue of how to optimally schedule observations on geographically distributed resources. We discuss a free market approach to this scheduling problem, which must initially be based on ad-hoc agreements between the participants in the network, but which may eventually expand into a electronic market for the exchange of telescope time.

  20. Building a mentoring network.

    Science.gov (United States)

    McBride, Angela Barron; Campbell, Jacquelyn; Woods, Nancy Fugate; Manson, Spero M

    Mentoring has long been regarded as one of the key components of research training and faculty development. The Robert Wood Johnson Foundation Nurse Faculty Scholars program purposely facilitated scholars' development of a mentoring network by providing each individual with three mentors: a school-of-nursing mentor (primary), a university-based non-nurse research mentor (research), and a nationally-recognized nurse leader at another university (national). The Mentorship Effectiveness Scale was used to assess the effectiveness of each type of mentor in the first five completed cohorts. The ratings of mentorship effectiveness for all three kinds of mentors were generally high. Scholars valued most their mentors' support and advocacy; the biggest weakness in dealing with all mentors was accessibility. Even when one mentor proved a poor match, another mentor turned out to be an advocate and helpful, thus reaffirming the benefits of a mentoring network as opposed to only a single mentoring relationship. One lesson learned is the importance of preparing mentors for their role via written materials, in-person or phone orientations, and discussions at the annual meeting. Copyright © 2016. Published by Elsevier Inc.

  1. QUANTUM NETWORKS WITH SINGLE ATOMS, PHOTONS AND PHONONS

    Science.gov (United States)

    2016-10-04

    recovers the well-known form of a Beer - Lambert law , reading T (∆A)/T0(∆A) = exp [ −N ln ∆ 2 A + (Γ′ + Γ1D)2/4 ∆2A + Γ′2/4 ] ’ exp [ − OD1 + (2∆A/Γ′)2...Lett 111(26):260401. 46. Gong ZX, Foss-Feig M, Michalakis S , Gorshkov AV (2014) Persistence of locality in systems with power- law interactions. Phys...0704-0188).   Respondents should be aware that notwithstanding any other provision of law , no person shall be subject to any penalty for failing to

  2. Rigidity loss in disordered network materials

    Science.gov (United States)

    Ellenbroek, Wouter G.; Hagh, Varda F.; Kumar, Avishek; Thorpe, M. F.; van Hecke, Martin

    Weakly jammed sphere packings show a very peculiar elasticity, with a ratio of compression modulus to shear modulus that diverges as the number of contacts approaches the minimum required for rigidity. Creating artificial isotropic network materials with this property is a challenge: so far, the least elaborate way to generate them is to actually simulate weakly compressed repulsive spheres. The next steps in designing such networks hinge upon a solid understanding of what properties of the sphere-packing derived network are essential for its elasticity. We elucidate the topological aspects of this question by comparing the rigidity transition in these networks to that in other random spring network models, including the common bond-diluted triangular net and a self-stress-free variant of that. We use the pebble game algorithm for identifying rigid clusters in mechanical networks to demonstrate that the marginally rigid state in sphere packings is perfectly isostatic everywhere, and the addition or removal of a single bond creates a globally stressed or globally floppy network, respectively. By contrast, the other classes of random network random networks show a more localized response to addition and removal of bonds, and, correspondingly, a more gradual rigidity transition.

  3. Shaping Neuronal Network Activity by Presynaptic Mechanisms.

    Directory of Open Access Journals (Sweden)

    Ayal Lavi

    2015-09-01

    Full Text Available Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

  4. Reconstruction of periodic signals using neural networks

    Directory of Open Access Journals (Sweden)

    José Danilo Rairán Antolines

    2014-01-01

    Full Text Available In this paper, we reconstruct a periodic signal by using two neural networks. The first network is trained to approximate the period of a signal, and the second network estimates the corresponding coefficients of the signal's Fourier expansion. The reconstruction strategy consists in minimizing the mean-square error via backpro-pagation algorithms over a single neuron with a sine transfer function. Additionally, this paper presents mathematical proof about the quality of the approximation as well as a first modification of the algorithm, which requires less data to reach the same estimation; thus making the algorithm suitable for real-time implementations.

  5. Astroglial gap junctions shape neuronal network activity.

    Science.gov (United States)

    Pannasch, Ulrike; Derangeon, Mickael; Chever, Oana; Rouach, Nathalie

    2012-05-01

    Astrocytes, the third element of the tripartite synapse, are active players in neurotransmission. Up to now, their involvement in neuronal functions has primarily been investigated at the single cell level. However, a key property of astrocytes is that they communicate via extensive networks formed by gap junction channels. Recently, we have shown that this networking modulates the moment to moment basal synaptic transmission and plasticity via the regulation of extracellular potassium and glutamate levels. Here we show that astroglial gap junctional communication also regulates neuronal network activity. We discuss these findings and their implications for brain information processing.

  6. Transition Towards An Integrated Network Organisation

    DEFF Research Database (Denmark)

    Mykhaylenko, Alona; Wæhrens, Brian Vejrum

    2016-01-01

    Management of internationally dispersed and networked operations has been in the focus of research attention. However, the existing studies underestimate the incrementality of changes shaping such organisations. This work investigates how organisations evolve into network structures......, with particular attention to the role played by the home base (HB) organisation in this evolution. The research is focused on the intra-organisational global network and uses a longitudinal single-case study. Findings depict the transition as being enabled by the interaction between HB knowledge about...

  7. Replicability and generalizability of PTSD networks

    DEFF Research Database (Denmark)

    Eiko I., Fried; Eidhof, Marloes B.; Palic, Sabina

    2018-01-01

    The growing literature conceptualizing mental disorders like Posttraumatic Stress Disorder (PTSD) as networks of interacting symptoms faces three key challenges. Prior studies predominantly used (a) small samples with low power for precise estimation, (b) non-clinical samples, and (c) single...... samples. This renders network structures in clinical data, and the extent to which networks replicate across datasets, unknown. To overcome these limitations, the present cross-cultural multisite study estimated regularized partial correlation networks of 16 PTSD symptoms across four datasets...... of traumatized patients receiving treatment for PTSD (total N=2,782). Despite differences in culture, trauma-type and severity of the samples, considerable similarities emerged, with moderate to high correlations between symptom profiles (0.43-0.82), network structures (0.62-0.74), and centrality estimates (0...

  8. Innovation in Downstream Fashion Retail Networks

    DEFF Research Database (Denmark)

    Tambo, Torben

    2012-01-01

    While product marketers and brand owners struggle to make new products, manufacturing processes and inbound logistics, innovation taking place in retail networks is often overlooked. Networks in retailing are comprised by varieties of single- and multi-brand stores, chains and departments stores......, technology and service providers, ownership structures and local level supply chain facilities. This paper analyses theoretical and empirical views of innovation in international retail networks using the fashion industry as a case because this industry better than other industries maintain branded stores......-depth studies of the biggest Danish fashion brand owners and their respective retail networks. The study shows how brand owners can emphasise change by shifting from a passive and narrow observation of its downstream retail network to an active and broad observation, or at least develop a conscious approach...

  9. Learning Bayesian networks for discrete data

    KAUST Repository

    Liang, Faming

    2009-02-01

    Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.

  10. Visualization of Social Networks

    NARCIS (Netherlands)

    Boertjes, E.M.; Kotterink, B.; Jager, E.J.

    2011-01-01

    Current visualizations of social networks are mostly some form of node-link diagram. Depending on the type of social network, this can be some treevisualization with a strict hierarchical structure or a more generic network visualization.

  11. Animal transportation networks

    Science.gov (United States)

    Perna, Andrea; Latty, Tanya

    2014-01-01

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

  12. Applied Learning Networks (ALN)

    National Research Council Canada - National Science Library

    Bannister, Joseph; Shen, Wei-Min; Touch, Joseph; Hou, Feili; Pingali, Venkata

    2007-01-01

    Applied Learning Networks (ALN) demonstrates that a network protocol can learn to improve its performance over time, showing how to incorporate learning methods into a general class of network protocols...

  13. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

  14. Introduction to computer networking

    CERN Document Server

    Robertazzi, Thomas G

    2017-01-01

    This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional. • Features a concise, accessible treatment of computer networking, focusing on new technological topics; • Provides non-mathematical introduction to networks in their most common forms today;< • Includes new developments in switching, optical networks, WiFi, Bluetooth, LTE, 5G, and quantum cryptography.

  15. Tunable Sparse Network Coding for Multicast Networks

    DEFF Research Database (Denmark)

    Feizi, Soheil; Roetter, Daniel Enrique Lucani; Sørensen, Chres Wiant

    2014-01-01

    This paper shows the potential and key enabling mechanisms for tunable sparse network coding, a scheme in which the density of network coded packets varies during a transmission session. At the beginning of a transmission session, sparsely coded packets are transmitted, which benefits decoding...... complexity. At the end of a transmission, when receivers have accumulated degrees of freedom, coding density is increased. We propose a family of tunable sparse network codes (TSNCs) for multicast erasure networks with a controllable trade-off between completion time performance to decoding complexity....... Coding density tuning can be performed by designing time-dependent coding matrices. In multicast networks, this tuning can be performed within the network by designing time-dependent pre- coding and network coding matrices with mild conditions on the network structure for specific densities. We present...

  16. Reconfigurable Network of Networks for Multiscale Computing

    National Research Council Canada - National Science Library

    Sutton, Jeff

    2001-01-01

    The Network of Networks (NoN) model, which is a neurobiologically motivated smart algorithm co-developed by the PI, is being applied for rapid and accurate image processing of forward and side scan sonar images in turbid environments...

  17. Conception of Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Slavko Šarić

    2004-11-01

    Full Text Available This article presents a review of the existing networks andthe NGN concept. By analysing the condition of the existingtelecommunication networks and services it is obvious that theyare different single-se1vice networks that cannot meet the requirementsof the users for various se1vices. The increased demandsof the users for telecommunication se1vices have inducedthe introduction of liberalization in the telecommunicationmarket. That opened the door for competition and greatinvestments in the development of telecommunication networks.The existing telecommunication networks orientated to thetransmission of voice and the existing data network could notbe adapted to new requirements without difficulties. That is thereason why the search for a solution for convergence and unionof a great number of different single-service networks started.The basic requirement was reduced in the end to the conceptionof the universal wideband data network that can meet all thedemands of the users by dividing the resources. As a collSequenceof that it was necessmy to find the solution for the transmissionof voice by a data network. The solution was seen in theerection of softswitch architecture for VoiP. Thus, the voicewould be transmitted by packets as one of the components indata transmission. It was necessary to define protocols for enablingthe operation in the NGN conception, as well as to thoroughlyobserve the problems of the JP telephony operation in regardto the real-time voice component. Apart from these tasks itwas necessmy to see how to adapt the existing networks into theNGN conception and to provide interaction between differentnetworks and different layers of networks by applying certainstandards and protocols. The awareness of the necessity ofgradual introduction and realization of NGN conception hasbecome obvious, always in the relation to the existing conditionof PSTN and the users' demands. Special attention should begiven to the introduction of IN as a

  18. Basics of Computer Networking

    CERN Document Server

    Robertazzi, Thomas

    2012-01-01

    Springer Brief Basics of Computer Networking provides a non-mathematical introduction to the world of networks. This book covers both technology for wired and wireless networks. Coverage includes transmission media, local area networks, wide area networks, and network security. Written in a very accessible style for the interested layman by the author of a widely used textbook with many years of experience explaining concepts to the beginner.

  19. Packet Tracer network simulator

    CERN Document Server

    Jesin, A

    2014-01-01

    A practical, fast-paced guide that gives you all the information you need to successfully create networks and simulate them using Packet Tracer.Packet Tracer Network Simulator is aimed at students, instructors, and network administrators who wish to use this simulator to learn how to perform networking instead of investing in expensive, specialized hardware. This book assumes that you have a good amount of Cisco networking knowledge, and it will focus more on Packet Tracer rather than networking.

  20. The Economics of Networking

    DEFF Research Database (Denmark)

    Sørensen, Olav Jull

    The literature on business networks is often oversocialized. The economic side of business is implicitly assumed. This paper analyses the economics of network behavior by loking at each of the key concepts in the Network Theory.......The literature on business networks is often oversocialized. The economic side of business is implicitly assumed. This paper analyses the economics of network behavior by loking at each of the key concepts in the Network Theory....

  1. Advanced fault diagnosis methods in molecular networks.

    Science.gov (United States)

    Habibi, Iman; Emamian, Effat S; Abdi, Ali

    2014-01-01

    Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally.

  2. Single ventricle cardiac defect

    International Nuclear Information System (INIS)

    Eren, B.; Turkmen, N.; Fedakar, R.; Cetin, V.

    2010-01-01

    Single ventricle heart is defined as a rare cardiac abnormality with a single ventricle chamber involving diverse functional and physiological defects. Our case is of a ten month-old baby boy who died shortly after admission to the hospital due to vomiting and diarrhoea. Autopsy findings revealed cyanosis of finger nails and ears. Internal examination revealed; large heart, weighing 60 grams, single ventricle, without a septum and upper membranous part. Single ventricle is a rare pathology, hence, this paper aims to discuss this case from a medico-legal point of view. (author)

  3. Proximity effect and branching conditions in superconducting networks

    International Nuclear Information System (INIS)

    Riess, J.

    1983-01-01

    The onset of superconductivity on proximity networks made of very thin wires of different materials is investigated by adapting de Gennes' one-frequency approximation for dirty superconductors to networks. Branching conditions for the order parameter in the presence of a magnetic field H are derived and an equation for the global critical temperature T/sub c/(H) of arbitrary networks is obtained that generalizes Alexander's equation for networks made of a single material. Numerical applications to simple proximity networks are given showing phase boundaries T/sub x/(H) and the order parameter on adjacent branches as a function of geometry and mean free path

  4. AN AUTOMATED NETWORK SECURITYCHECKING AND ALERT SYSTEM: A NEW FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Vivek Kumar Yadav

    2013-09-01

    Full Text Available Network security checking is a vital process to assess and to identify weaknesses in network for management of security. Insecure entry points of a network provide attackers an easy target to access and compromise. Open ports of network components such as firewalls, gateways and end systems are analogues to open gates of a building through which any one can get into. Network scanning is performed to identify insecure entry points in the network components. To find out vulnerabilities on these points vulnerability assessment is performed. So security checking consists of both activities- network scanning as well as vulnerability assessment. A single tool used for the security checking may not give reliable results. This paper presents a framework for assessing the security of a network using multiple Network Scanning and Vulnerability Assessment tools. The proposed framework is an extension of the framework given by Jun Yoon and Wontae Sim [1] which performs vulnerability scanning only. The framework presented here adds network scanning, alerting and reporting system to their framework. Network scanning and vulnerability tools together complement each other and make it amenable for centralized control and management. The reporting system of framework sends an email to the network administrator which contains detailed report (as attachment of security checking process. Alerting system sends a SMS message as an alert to the network administrator in case of severe threats found in the network. Initial results of the framework are encouraging and further work is in progress.

  5. Coded Network Function Virtualization

    DEFF Research Database (Denmark)

    Al-Shuwaili, A.; Simone, O.; Kliewer, J.

    2016-01-01

    Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off-the-shelf ha......Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off...

  6. Local Social Networks

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Sørensen, Lene Tolstrup

    2011-01-01

    Online social networks have become essential for many users in their daily communication. Through a combination of the online social networks with opportunistic networks, a new concept arises: Local Social Networks. The target of local social networks is to promote social networking benefits...... in physical environment in order to leverage personal affinities in the users' surroundings. The purpose of this paper is to present and discuss the concept of local social networks as a new social communication system. Particularly, the preliminary architecture and the prototype of local social networks...

  7. Metannogen: annotation of biological reaction networks.

    Science.gov (United States)

    Gille, Christoph; Hübner, Katrin; Hoppe, Andreas; Holzhütter, Hermann-Georg

    2011-10-01

    Semantic annotations of the biochemical entities constituting a biological reaction network are indispensable to create biologically meaningful networks. They further heighten efficient exchange, reuse and merging of existing models which concern present-day systems biology research more often. Two types of tools for the reconstruction of biological networks currently exist: (i) several sophisticated programs support graphical network editing and visualization. (ii) Data management systems permit reconstruction and curation of huge networks in a team of scientists including data integration, annotation and cross-referencing. We seeked ways to combine the advantages of both approaches. Metannogen, which was previously developed for network reconstruction, has been considerably improved. From now on, Metannogen provides sbml import and annotation of networks created elsewhere. This permits users of other network reconstruction platforms or modeling software to annotate their networks using Metannogen's advanced information management. We implemented word-autocompletion, multipattern highlighting, spell check, brace-expansion and publication management, and improved annotation, cross-referencing and team work requirements. Unspecific enzymes and transporters acting on a spectrum of different substrates are efficiently handled. The network can be exported in sbml format where the annotations are embedded in line with the miriam standard. For more comfort, Metannogen may be tightly coupled with the network editor such that Metannogen becomes an additional view for the focused reaction in the network editor. Finally, Metannogen provides local single user, shared password protected multiuser or public access to the annotation data. Metannogen is available free of charge at: http://www.bioinformatics.org/strap/metannogen/ or http://3d-alignment.eu/metannogen/. christoph.gille@charite.de Supplementary data are available at Bioinformatics online.

  8. Challenges in Second-Generation Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Pescapé Antonio

    2008-01-01

    Full Text Available Wireless mesh networks have the potential to provide ubiquitous high-speed Internet access at low costs. The good news is that initial deployments of WiFi meshes show the feasibility of providing ubiquitous Internet connectivity. However, their performance is far below the necessary and achievable limit. Moreover, users' subscription in the existing meshes is dismal even though the technical challenges to get connectivity are low. This paper provides an overview of the current status of mesh networks' deployment, and highlights the technical, economical, and social challenges that need to be addressed in the next years. As a proof-of-principle study, we discuss the above-mentioned challenges with reference to three real networks: (i MagNets, an operator-driven planned two-tier mesh network; (ii Berlin Freifunk network as a pure community-driven single-tier network; (iii Weimar Freifunk network, also a community-driven but two-tier network.

  9. Challenges in Second-Generation Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Thomas Huehn

    2008-10-01

    Full Text Available Wireless mesh networks have the potential to provide ubiquitous high-speed Internet access at low costs. The good news is that initial deployments of WiFi meshes show the feasibility of providing ubiquitous Internet connectivity. However, their performance is far below the necessary and achievable limit. Moreover, users' subscription in the existing meshes is dismal even though the technical challenges to get connectivity are low. This paper provides an overview of the current status of mesh networks' deployment, and highlights the technical, economical, and social challenges that need to be addressed in the next years. As a proof-of-principle study, we discuss the above-mentioned challenges with reference to three real networks: (i MagNets, an operator-driven planned two-tier mesh network; (ii Berlin Freifunk network as a pure community-driven single-tier network; (iii Weimar Freifunk network, also a community-driven but two-tier network.

  10. Picture this: Managed change and resistance in business network settings

    DEFF Research Database (Denmark)

    Kragh, Hanne; Andersen, Poul Houman

    2009-01-01

    This paper discusses change management in networks. The literature on business networks tends to downplay the role of managerial initiative in network change. The change management literature addresses such initiative, but with its single-firm perspective it overlooks the interdependence of network...... actors. In exploring the void between these two streams of literature, we deploy the concept of network pictures to discuss managed change in network settings. We analyze a change project from the furniture industry and address the consequences of attempting to manage change activities in a network...... context characterized by limited managerial authority over these activities. Our analysis suggests that change efforts unfold as a negotiated process during which the change project is re-negotiated to fit the multiple actor constituencies. The degree of overlap in the co-existing network pictures...

  11. Composition and structure of a large online social network in The Netherlands.

    Science.gov (United States)

    Corten, Rense

    2012-01-01

    Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in The Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for The Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities.

  12. The architectural design of networks of protein domain architectures.

    Science.gov (United States)

    Hsu, Chia-Hsin; Chen, Chien-Kuo; Hwang, Ming-Jing

    2013-08-23

    Protein domain architectures (PDAs), in which single domains are linked to form multiple-domain proteins, are a major molecular form used by evolution for the diversification of protein functions. However, the design principles of PDAs remain largely uninvestigated. In this study, we constructed networks to connect domain architectures that had grown out from the same single domain for every single domain in the Pfam-A database and found that there are three main distinctive types of these networks, which suggests that evolution can exploit PDAs in three different ways. Further analysis showed that these three different types of PDA networks are each adopted by different types of protein domains, although many networks exhibit the characteristics of more than one of the three types. Our results shed light on nature's blueprint for protein architecture and provide a framework for understanding architectural design from a network perspective.

  13. A Distributed Password Scheme for Network Operating Systems

    National Research Council Canada - National Science Library

    Roth, Christopher

    2002-01-01

    Password-based user identification and authentication in a network-based operating system generally relies upon a single file that contains user information and the encoded or hashed representations...

  14. Multilevel temporal Bayesian networks can model longitudinal change in multimorbidity

    NARCIS (Netherlands)

    Lappenschaar, M.; Hommersom, A.; Lucas, P.J.; Lagro, J.; Visscher, S.; Korevaar, J.C.; Schellevis, F.G.

    2013-01-01

    Objectives Although the course of single diseases can be studied using traditional epidemiologic techniques, these methods cannot capture the complex joint evolutionary course of multiple disorders. In this study, multilevel temporal Bayesian networks were adopted to study the course of

  15. Identity and Professional Networking.

    Science.gov (United States)

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

    2017-06-01

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

  16. Microplastic relaxations of single and polycrystalline molybdenum

    Energy Technology Data Exchange (ETDEWEB)

    Pichl, W.; Weiss, B. [Wien Univ. (Austria). Inst. fuer Materialphysik; Chen, D.L.

    1998-05-01

    The microplasticity of high-purity molybdenum single crystals and of Mo polycrystals of technical purity has been investigated by relaxation step tests in uniaxial compression. A new model for the evaluation of relaxation tests in the microplastic range of b.c.c metals is presented which takes into account the decrease of the mobile dislocation density due to exhaustion of non-screw dislocations. The model allows an independent determination of the activation volume and of the microstructure parameters controlling dislocation exhaustion. The results indicate that in the high-purity single crystals the deformation rate is controlled by interactions of non-screw dislocations with the grown-in network. In the polycrystals additional interactions with impurity atoms seem to occur. In the single crystals the activity and subsequent exhaustion of two different glide systems was observed, followed by a gradual onset of screw dislocation motion. (orig.) 26 refs.

  17. Single-Molecule Spectroscopy

    Indian Academy of Sciences (India)

    IAS Admin

    GENERAL ARTICLE. Single-Molecule Spectroscopy. Every Molecule is Different! Kankan Bhattacharyya. Keywords. Single-molecule spectroscopy. (SMS), confocal microscopy,. FCS, sm-FRET, FLIM. 1 High-resolution spectrum re- fers to a spectrum consisting of very sharp lines. The sharp lines clearly display transitions to ...

  18. Single-Molecule Spectroscopy

    Indian Academy of Sciences (India)

    IAS Admin

    RESONANCE. February 2015. GENERAL ARTICLE. Single-Molecule Spectroscopy. Every Molecule is Different! Kankan Bhattacharyya. Keywords. Single-molecule ..... Resonance Energy. Transfer (FRET) is an elegant technique to measure the distance between a donor and an acceptor molecule. FRET refers to the.

  19. Single photon and nonlocality

    Indian Academy of Sciences (India)

    critical analysis of the concept of hidden variable used by the authors of [1] shows that the reasoning is not correct. Keywords. Nonlocality; single particle; hidden variables. PACS Nos 03.67.Ba; 03.65.Ta; 32.80.Lg; 07.79.Fc. 1. Introduction. Quantum nonlocality [2] for single particle is a subject of debate since the origin.

  20. Single gaze gestures

    DEFF Research Database (Denmark)

    Møllenbach, Emilie; Lilholm, Martin; Gail, Alastair

    2010-01-01

    This paper examines gaze gestures and their applicability as a generic selection method for gaze-only controlled interfaces. The method explored here is the Single Gaze Gesture (SGG), i.e. gestures consisting of a single point-to-point eye movement. Horizontal and vertical, long and short SGGs were...

  1. Understanding Single Adulthood.

    Science.gov (United States)

    Stein, Peter J.

    The life styles and life chances of the unmarried include elements of choices. Singles may be grouped and characterized according to whether their status may be considered stable or temporary. A life cycle, or continuum model of singlehood is reviewed, including its different factors, or phases. A new model for singles is proposed--a life spiral…

  2. Single-sided NMR

    CERN Document Server

    Casanova, Federico; Blümich, Bernhard

    2011-01-01

    Single-Sided NMR describes the design of the first functioning single-sided tomograph, the related measurement methods, and a number of applications. One of the key advantages to this method is the speed at which the images are obtained.

  3. Stability of a giant connected component in a complex network

    Science.gov (United States)

    Kitsak, Maksim; Ganin, Alexander A.; Eisenberg, Daniel A.; Krapivsky, Pavel L.; Krioukov, Dmitri; Alderson, David L.; Linkov, Igor

    2018-01-01

    We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

  4. Single molecules and nanotechnology

    CERN Document Server

    Vogel, Horst

    2007-01-01

    This book focuses on recent advances in the rapidly evolving field of single molecule research. These advances are of importance for the investigation of biopolymers and cellular biochemical reactions, and are essential to the development of quantitative biology. Written by leading experts in the field, the articles cover a broad range of topics, including: quantum photonics of organic dyes and inorganic nanoparticles their use in detecting properties of single molecules the monitoring of single molecule (enzymatic) reactions single protein (un)folding in nanometer-sized confined volumes the dynamics of molecular interactions in biological cells The book is written for advanced students and scientists who wish to survey the concepts, techniques and results of single molecule research and assess them for their own scientific activities.

  5. Single Nanoparticle Plasmonic Sensors

    Directory of Open Access Journals (Sweden)

    Manish Sriram

    2015-10-01

    Full Text Available The adoption of plasmonic nanomaterials in optical sensors, coupled with the advances in detection techniques, has opened the way for biosensing with single plasmonic particles. Single nanoparticle sensors offer the potential to analyse biochemical interactions at a single-molecule level, thereby allowing us to capture even more information than ensemble measurements. We introduce the concepts behind single nanoparticle sensing and how the localised surface plasmon resonances of these nanoparticles are dependent upon their materials, shape and size. Then we outline the different synthetic approaches, like citrate reduction, seed-mediated and seedless growth, that enable the synthesis of gold and silver nanospheres, nanorods, nanostars, nanoprisms and other nanostructures with tunable sizes. Further, we go into the aspects related to purification and functionalisation of nanoparticles, prior to the fabrication of sensing surfaces. Finally, the recent developments in single nanoparticle detection, spectroscopy and sensing applications are discussed.

  6. Single-photon imaging

    CERN Document Server

    Seitz, Peter

    2011-01-01

    The acquisition and interpretation of images is a central capability in almost all scientific and technological domains. In particular, the acquisition of electromagnetic radiation, in the form of visible light, UV, infrared, X-ray, etc. is of enormous practical importance. The ultimate sensitivity in electronic imaging is the detection of individual photons. With this book, the first comprehensive review of all aspects of single-photon electronic imaging has been created. Topics include theoretical basics, semiconductor fabrication, single-photon detection principles, imager design and applications of different spectral domains. Today, the solid-state fabrication capabilities for several types of image sensors has advanced to a point, where uncoooled single-photon electronic imaging will soon become a consumer product. This book is giving a specialist´s view from different domains to the forthcoming “single-photon imaging” revolution. The various aspects of single-photon imaging are treated by internati...

  7. Single-Phase PLLs

    DEFF Research Database (Denmark)

    Golestan, Saeed; Guerrero, Josep M.; Quintero, Juan Carlos Vasquez

    2017-01-01

    Single-phase phase-locked loops (PLLs) are popular for the synchronization and control of single-phase gridconnected converters. They are also widely used for monitoring and diagnostic purposes in the power and energy areas. In recent years, a large number of single-phase PLLs with different...... structures and properties have been proposed in the literature. The main aim of this paper is to provide a review of these PLLs. To this end, the single-phase PLLs are first classified into two major categories: 1) power-based PLLs (pPLLs), and 2) quadrature signal generation-based PLLs (QSG......-PLLs). The members of each category are then described and their pros and cons are discussed. This work provides a deep insight into characteristics of different single-phase PLLs and, therefore, can be considered as a reference for researchers and engineers....

  8. Neural dynamics in superconducting networks

    Science.gov (United States)

    Segall, Kenneth; Schult, Dan; Crotty, Patrick; Miller, Max

    2012-02-01

    We discuss the use of Josephson junction networks as analog models for simulating neuron behaviors. A single unit called a ``Josephson Junction neuron'' composed of two Josephson junctions [1] displays behavior that shows characteristics of single neurons such as action potentials, thresholds and refractory periods. Synapses can be modeled as passive filters and can be used to connect neurons together. The sign of the bias current to the Josephson neuron can be used to determine if the neuron is excitatory or inhibitory. Due to the intrinsic speed of Josephson junctions and their scaling properties as analog models, a large network of Josephson neurons measured over typical lab times contains dynamics which would essentially be impossible to calculate on a computer We discuss the operating principle of the Josephson neuron, coupling Josephson neurons together to make large networks, and the Kuramoto-like synchronization of a system of disordered junctions.[4pt] [1] ``Josephson junction simulation of neurons,'' P. Crotty, D. Schult and K. Segall, Physical Review E 82, 011914 (2010).

  9. Network epidemiology and plant trade networks.

    Science.gov (United States)

    Pautasso, Marco; Jeger, Mike J

    2014-01-01

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

  10. Cognitive radio networks efficient resource allocation in cooperative sensing, cellular communications, high-speed vehicles, and smart grid

    CERN Document Server

    Jiang, Tao; Cao, Yang

    2015-01-01

    PrefaceAcknowledgmentsAbout the AuthorsIntroductionCognitive Radio-Based NetworksOpportunistic Spectrum Access NetworksCognitive Radio Networks with Cooperative SensingCognitive Radio Networks for Cellular CommunicationsCognitive Radio Networks for High-Speed VehiclesCognitive Radio Networks for a Smart GridContent and OrganizationTransmission Slot Allocation in an Opportunistic Spectrum Access NetworkSingle-User Single-Channel System ModelProbabilistic Slot Allocation SchemeOptimal Probabilistic Slot AllocationBaseline PerformanceExponential DistributionHyper-Erlang DistributionPerformance An

  11. An algorithm for link restoration in wavwlength translating networks

    DEFF Research Database (Denmark)

    Limal, Emmanuel; Gliese, Ulrik Bo

    1999-01-01

    We propose the BONRA, a new and innovative algorithm for dynamic allocation of working and spare channel capacity for single link restoration in wavelength translating optical networks. The BONRA has very low calculation complexity yet gives high capacity utilisation.......We propose the BONRA, a new and innovative algorithm for dynamic allocation of working and spare channel capacity for single link restoration in wavelength translating optical networks. The BONRA has very low calculation complexity yet gives high capacity utilisation....

  12. Information transfer in community structured multiplex networks

    Directory of Open Access Journals (Sweden)

    Albert eSolé Ribalta

    2015-08-01

    Full Text Available The study of complex networks that account for different types of interactions has become a subject of interest in the last few years, specially because its representational power in the description of users interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.. The mathematical description of these interacting networks has been coined under the name of multilayer networks, where each layer accounts for a type of interaction. It has been shown that diffusive processes on top of these networks present a phenomenology that cannot be explained by the naive superposition of single layer diffusive phenomena but require the whole structure of interconnected layers. Nevertheless, the description of diffusive phenomena on multilayer networks has obviated the fact that social networks have strong mesoscopic structure represented by different communities of individuals driven by common interests, or any other social aspect. In this work, we study the transfer of information in multilayer networks with community structure. The final goal is to understand and quantify, if the existence of well-defined community structure at the level of individual layers, together with the multilayer structure of the whole network, enhances or deteriorates the diffusion of packets of information.

  13. Information transfer in community structured multiplex networks

    Science.gov (United States)

    Solé Ribalta, Albert; Granell, Clara; Gómez, Sergio; Arenas, Alex

    2015-08-01

    The study of complex networks that account for different types of interactions has become a subject of interest in the last few years, specially because its representational power in the description of users interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.). The mathematical description of these interacting networks has been coined under the name of multilayer networks, where each layer accounts for a type of interaction. It has been shown that diffusive processes on top of these networks present a phenomenology that cannot be explained by the naive superposition of single layer diffusive phenomena but require the whole structure of interconnected layers. Nevertheless, the description of diffusive phenomena on multilayer networks has obviated the fact that social networks have strong mesoscopic structure represented by different communities of individuals driven by common interests, or any other social aspect. In this work, we study the transfer of information in multilayer networks with community structure. The final goal is to understand and quantify, if the existence of well-defined community structure at the level of individual layers, together with the multilayer structure of the whole network, enhances or deteriorates the diffusion of packets of information.

  14. Analysis of complex networks using aggressive abstraction.

    Energy Technology Data Exchange (ETDEWEB)

    Colbaugh, Richard; Glass, Kristin.; Willard, Gerald

    2008-10-01

    This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.

  15. Biological and Environmental Research Network Requirements

    Energy Technology Data Exchange (ETDEWEB)

    Balaji, V. [Princeton Univ., NJ (United States). Earth Science Grid Federation (ESGF); Boden, Tom [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cowley, Dave [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Dart, Eli [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Dattoria, Vince [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Desai, Narayan [Argonne National Lab. (ANL), Argonne, IL (United States); Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Foster, Ian [Argonne National Lab. (ANL), Argonne, IL (United States); Goldstone, Robin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gregurick, Susan [U.S. Dept. of Energy, Washington, DC (United States). Biological Systems Science Division; Houghton, John [U.S. Dept. of Energy, Washington, DC (United States). Biological and Environmental Research (BER) Program; Izaurralde, Cesar [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Johnston, Bill [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Joseph, Renu [U.S. Dept. of Energy, Washington, DC (United States). Climate and Environmental Sciences Division; Kleese-van Dam, Kerstin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lipton, Mary [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Monga, Inder [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Pritchard, Matt [British Atmospheric Data Centre (BADC), Oxon (United Kingdom); Rotman, Lauren [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Strand, Gary [National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Stuart, Cory [Argonne National Lab. (ANL), Argonne, IL (United States); Tatusova, Tatiana [National Inst. of Health (NIH), Bethesda, MD (United States); Tierney, Brian [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Thomas, Brian [Univ. of California, Berkeley, CA (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Zurawski, Jason [Internet2, Washington, DC (United States)

    2013-09-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet be a highly successful enabler of scientific discovery for over 25 years. In November 2012, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the BER program office. Several key findings resulted from the review. Among them: 1) The scale of data sets available to science collaborations continues to increase exponentially. This has broad impact, both on the network and on the computational and storage systems connected to the network. 2) Many science collaborations require assistance to cope with the systems and network engineering challenges inherent in managing the rapid growth in data scale. 3) Several science domains operate distributed facilities that rely on high-performance networking for success. Key examples illustrated in this report include the Earth System Grid Federation (ESGF) and the Systems Biology Knowledgebase (KBase). This report expands on these points, and addresses others as well. The report contains a findings section as well as the text of the case studies discussed at the review.

  16. Network Medicine: A Network-based Approach to Human Disease

    Science.gov (United States)

    Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph

    2011-01-01

    Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525

  17. Wireless Local Area Network Performance Inside Aircraft Passenger Cabins

    Science.gov (United States)

    Whetten, Frank L.; Soroker, Andrew; Whetten, Dennis A.; Whetten, Frank L.; Beggs, John H.

    2005-01-01

    An examination of IEEE 802.11 wireless network performance within an aircraft fuselage is performed. This examination measured the propagated RF power along the length of the fuselage, and the associated network performance: the link speed, total throughput, and packet losses and errors. A total of four airplanes: one single-aisle and three twin-aisle airplanes were tested with 802.11a, 802.11b, and 802.11g networks.

  18. Neural network model to control an experimental chaotic pendulum

    NARCIS (Netherlands)

    Bakker, R; Schouten, JC; Takens, F; vandenBleek, CM

    1996-01-01

    A feedforward neural network was trained to predict the motion of an experimental, driven, and damped pendulum operating in a chaotic regime. The network learned the behavior of the pendulum from a time series of the pendulum's angle, the single measured variable. The validity of the neural

  19. Recent Developments in VSD Imaging of Small Neuronal Networks

    Science.gov (United States)

    Hill, Evan S.; Bruno, Angela M.; Frost, William N.

    2014-01-01

    Voltage-sensitive dye (VSD) imaging is a powerful technique that can provide, in single experiments, a large-scale view of network activity unobtainable with traditional sharp electrode recording methods. Here we review recent work using VSDs to study small networks and highlight several results from this approach. Topics covered include circuit…

  20. Long term behavior of dynamic equilibria in fluid queuing networks

    NARCIS (Netherlands)

    R. Cominetti (Roberto); J. Correa (José); N.K. Olver (Neil)

    2017-01-01

    textabstractA fluid queuing network constitutes one of the simplest models in which to study flow dynamics over a network. In this model we have a single source-sink pair and each link has a per-time-unit capacity and a transit time. A dynamic equilibrium (or equilibrium flow over time) is a flow

  1. Large scale road network generalization for vario-scale map

    NARCIS (Netherlands)

    Suba, R.; Meijers, B.M.; Van Oosterom, P.J.M.

    2015-01-01

    The classical approach for road network generalization consists of producing multiple maps, for a different scale or purpose, from a single detailed data source and quite often roads are represented by line objects. Our target is the generalization of a road network for the whole scale range from

  2. Convex Congestion Network Problems

    NARCIS (Netherlands)

    Quant, M.; Reijnierse, J.H.

    2004-01-01

    This paper analyzes convex congestion network problems.It is shown that for network problems with convex congestion costs, an algorithm based on a shortest path algorithm, can be used to find an optimal network for any coalition. Furthermore an easy way of determining if a given network is optimal

  3. Synchronization of networks

    Indian Academy of Sciences (India)

    For networks with time-varying topology we compare the synchronization properties of these networks with the corresponding time-average network. We find that if the different coupling matrices corresponding to the time-varying networks commute with each other then the stability of the synchronized state for both the ...

  4. 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...

  5. Hardening Software Defined Networks

    Science.gov (United States)

    2014-07-01

    the layers to act upon each other in very distinct ways. Examining the literature, we selected bipartite and tripartite network models are those...identify characteristics of multilayered networks . Bipartite and tripartite models are potentially most promising (and somewhat underutilized) in the... tripartite models are particularly well-suited to a confluence of traditional networks and software defined networks where SDN components are

  6. Single Policy Study

    DEFF Research Database (Denmark)

    Kronsell, Annica; Manners, Ian James

    2015-01-01

    Single policy studies are the most common form of European Union (EU) research. Single policy studies are widely used to understand the role of the EU in a wide variety of sectors, together with their development over time, and often offer public policy prescriptions. This chapter discusses the r...... Policy (CSDP). The examples are illustrative of how single policy studies can be designed to use different approaches in the analysis: multiple streams approach to policy-making; a comparative hypothesis testing; and feminist institutional theory.......Single policy studies are the most common form of European Union (EU) research. Single policy studies are widely used to understand the role of the EU in a wide variety of sectors, together with their development over time, and often offer public policy prescriptions. This chapter discusses...... the relevance of single policy studies in EU research and give examples of how such research can be designed and carried out. The chapter reviews three examples of single policy studies using different methods based on EU environmental policy, the EU biofuels directive, and the EU Common Security and Defence...

  7. Mapping change in large networks.

    Directory of Open Access Journals (Sweden)

    Martin Rosvall

    2010-01-01

    Full Text Available Change is a fundamental ingredient of interaction patterns in biology, technology, the economy, and science itself: Interactions within and between organisms change; transportation patterns by air, land, and sea all change; the global financial flow changes; and the frontiers of scientific research change. Networks and clustering methods have become important tools to comprehend instances of these large-scale structures, but without methods to distinguish between real trends and noisy data, these approaches are not useful for studying how networks change. Only if we can assign significance to the partitioning of single networks can we distinguish meaningful structural changes from random fluctuations. Here we show that bootstrap resampling accompanied by significance clustering provides a solution to this problem. To connect changing structures with the changing function of networks, we highlight and summarize the significant structural changes with alluvial diagrams and realize de Solla Price's vision of mapping change in science: studying the citation pattern between about 7000 scientific journals over the past decade, we find that neuroscience has transformed from an interdisciplinary specialty to a mature and stand-alone discipline.

  8. Organization of growing random networks

    Energy Technology Data Exchange (ETDEWEB)

    Krapivsky, P. L.; Redner, S.

    2001-06-01

    The organizational development of growing random networks is investigated. These growing networks are built by adding nodes successively, and linking each to an earlier node of degree k with an attachment probability A{sub k}. When A{sub k} grows more slowly than linearly with k, the number of nodes with k links, N{sub k}(t), decays faster than a power law in k, while for A{sub k} growing faster than linearly in k, a single node emerges which connects to nearly all other nodes. When A{sub k} is asymptotically linear, N{sub k}(t){similar_to}tk{sup {minus}{nu}}, with {nu} dependent on details of the attachment probability, but in the range 2{lt}{nu}{lt}{infinity}. The combined age and degree distribution of nodes shows that old nodes typically have a large degree. There is also a significant correlation in the degrees of neighboring nodes, so that nodes of similar degree are more likely to be connected. The size distributions of the in and out components of the network with respect to a given node{emdash}namely, its {open_quotes}descendants{close_quotes} and {open_quotes}ancestors{close_quotes}{emdash}are also determined. The in component exhibits a robust s{sup {minus}2} power-law tail, where s is the component size. The out component has a typical size of order lnt, and it provides basic insights into the genealogy of the network.

  9. Cooperation, clustering, and assortative mixing in dynamic networks.

    Science.gov (United States)

    Melamed, David; Harrell, Ashley; Simpson, Brent

    2018-01-30

    Humans' propensity to cooperate is driven by our embeddedness in social networks. A key mechanism through which networks promote cooperation is clustering. Within clusters, conditional cooperators are insulated from exploitation by noncooperators, allowing them to reap the benefits of cooperation. Dynamic networks, where ties can be shed and new ties formed, allow for the endogenous emergence of clusters of cooperators. Although past work suggests that either reputation processes or network dynamics can increase clustering and cooperation, existing work on network dynamics conflates reputations and dynamics. Here we report results from a large-scale experiment (total n = 2,675) that embedded participants in clustered or random networks that were static or dynamic, with varying levels of reputational information. Results show that initial network clustering predicts cooperation in static networks, but not in dynamic ones. Further, our experiment shows that while reputations are important for partner choice, cooperation levels are driven purely by dynamics. Supplemental conditions confirmed this lack of a reputation effect. Importantly, we find that when participants make individual choices to cooperate or defect with each partner, as opposed to a single decision that applies to all partners (as is standard in the literature on cooperation in networks), cooperation rates in static networks are as high as cooperation rates in dynamic networks. This finding highlights the importance of structured relations for sustained cooperation, and shows how giving experimental participants more realistic choices has important consequences for whether dynamic networks promote higher levels of cooperation than static networks.

  10. Energy Efficient Digital Networks

    Energy Technology Data Exchange (ETDEWEB)

    Lanzisera, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brown, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-01

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

  11. Networking for big data

    CERN Document Server

    Yu, Shui; Misic, Jelena; Shen, Xuemin (Sherman)

    2015-01-01

    Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It exa

  12. How to Analyze Company Using Social Network?

    Science.gov (United States)

    Palus, Sebastian; Bródka, Piotr; Kazienko, Przemysław

    Every single company or institution wants to utilize its resources in the most efficient way. In order to do so they have to be have good structure. The new way to analyze company structure by utilizing existing within company natural social network and example of its usage on Enron company are presented in this paper.

  13. Towards Dependable Network-on-Chip Architectures

    NARCIS (Netherlands)

    Chen, C.

    2015-01-01

    The aggressive semiconductor technology scaling provides the means for doubling the amount of transistors on a single chip each and every 18 months. To efficiently utilize these vast chip resources, Multi-Processor Systems on Chip (MPSoCs) integrated with a Network-on-Chip (NoC) communication

  14. Scalable infrastructure for distributed sensor networks

    National Research Council Canada - National Science Library

    Chakrabarty, Krishnendu; Iyengar, S. S

    2005-01-01

    ... network application is inventory tracking in factory warehouses. A single sensor node can be attached to each item in the warehouse. These sensor nodes can then be used for tracking the location of the items as they are moved within the warehouse. They can also provide information on the location of nearby items as well as the history of movement...

  15. Network effects in railways

    DEFF Research Database (Denmark)

    Landex, Alex

    2012-01-01

    . Therefore, sections 3 and 4 describe the network effects for passengers and how they can be measured using passenger delay models. Before the concluding remarks in section 6, section 5 discusses how the operation can be improved by examining network effects in the planning process. © 2012 WIT Press....... each other everywhere in the network. First this paper describes network effects in general (section 1). In section 2 the network effects for trains and how they can be measured by scheduled waiting time is described. When the trains are affected by network effects the passengers are also affected......Railway operation is often affected by network effects as a change in one part of the network can influence other parts of the network. Network effects occur because the train runs may be quite long and since the railway system has a high degree of interdependencies as trains cannot cross/overtake...

  16. Networks in Cell Biology

    Science.gov (United States)

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

    2010-05-01

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

  17. Single photon ECT

    International Nuclear Information System (INIS)

    Maeda, Toshio; Matsuda, Hiroshi; Tada, Akira; Bunko, Hisashi; Koizumi, Kiyoshi

    1982-01-01

    The detectability of lesions located deep in a body or overlapped with a physiologically increased activity improve with the help of single photon ECT. In some cases, the ECT is superior to the conventional gamma camera images and X-ray CT scans in the evaluation of the location and size of lesion. The single photon ECT of the brain compares favorably with the contrast enhansed X-ray CT scans. The most important adaptation of the single photon ECT are the detection of recurrent brain tumors after craniotomy and the evaluation of ischemic heart diseases. (author)

  18. Single Electron Tunneling

    International Nuclear Information System (INIS)

    Ruggiero, Steven T.

    2005-01-01

    Financial support for this project has led to advances in the science of single-electron phenomena. Our group reported the first observation of the so-called ''Coulomb Staircase'', which was produced by tunneling into ultra-small metal particles. This work showed well-defined tunneling voltage steps of width e/C and height e/RC, demonstrating tunneling quantized on the single-electron level. This work was published in a now well-cited Physical Review Letter. Single-electron physics is now a major sub-field of condensed-matter physics, and fundamental work in the area continues to be conducted by tunneling in ultra-small metal particles. In addition, there are now single-electron transistors that add a controlling gate to modulate the charge on ultra-small photolithographically defined capacitive elements. Single-electron transistors are now at the heart of at least one experimental quantum-computer element, and single-electron transistor pumps may soon be used to define fundamental quantities such as the farad (capacitance) and the ampere (current). Novel computer technology based on single-electron quantum dots is also being developed. In related work, our group played the leading role in the explanation of experimental results observed during the initial phases of tunneling experiments with the high-temperature superconductors. When so-called ''multiple-gap'' tunneling was reported, the phenomenon was correctly identified by our group as single-electron tunneling in small grains in the material. The main focus throughout this project has been to explore single electron phenomena both in traditional tunneling formats of the type metal/insulator/particles/insulator/metal and using scanning tunneling microscopy to probe few-particle systems. This has been done under varying conditions of temperature, applied magnetic field, and with different materials systems. These have included metals, semi-metals, and superconductors. Amongst a number of results, we have

  19. Network Coding Taxonomy

    OpenAIRE

    Adamson , Brian; Adjih , Cédric; Bilbao , Josu; Firoiu , Victor; Fitzek , Frank; Samah , Ghanem ,; Lochin , Emmanuel; Masucci , Antonia; Montpetit , Marie-Jose; Pedersen , Morten V.; Peralta , Goiuri; Roca , Vincent; Paresh , Saxena; Sivakumar , Senthil

    2017-01-01

    Internet Research Task Force - Working document of the Network Coding Research Group (NWCRG), draft-irtf-nwcrg-network-coding-taxonomy-05 (work in progress), https://datatracker.ietf.org/doc/draft-irtf-nwcrg-network-coding-taxonomy/; This document summarizes a recommended terminology for Network Coding concepts and constructs. It provides a comprehensive set of terms with unique names in order to avoid ambiguities in future Network Coding IRTF and IETF documents. This document is intended to ...

  20. Sequential Construction of Costly Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gutfraind, Alexander [Los Alamos National Laboratory

    2011-01-01

    Natural disasters or attacks often disrupt infrastructure networks requiring a costly recovery. This motivates an optimization problem where the objecitve is to construct the nodes of a graph G(V;E), and the cost of each node is dependent on the number of its neighbors previously constructed, or more generally, any properties of the previously-completed subgraph. In this optimization problem the objective is to find a permutation of the nodes which results in the least construction cost. We prove that in the case where the cost of nodes is a convex function in the number of neighbors, the optimal construction sequence is to start at a single node and move outwards. We also introduce algorithms and heuristics for solving various instances of the problem. Those methods can be applied to help reduce the cost of recovering from disasters as well as to plan the deployment of new network infrastructure.